Port Said University Faculty of Engineering Natural Gas Engineering Program
A study on:Belayim Marine Field ( Zone II)
Submitted to:Natural Gas Engineering Program
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ACKNOWLEDGMENT
ACKNOWLEDGMENT Thanks and indebtedness is directed first and always to Allah for all his graces, without the power he gave to us , the accomplishment of this work would have been certainly impossible. We would like to extend our deep gratitude and appreciation to our family; for their love, help, understanding and continuous encouragement. We would like to express our deep gratitude, appreciation and sincerest thanks to our professor for his supervision, advices, constructive discussion and great help during the work Professor Doctor Attia M. Attia, our thesis supervisor. Finally, we would like to express our gratitude to our project assistant Eng. Ahmed Rayan who helped us technically and mentally throughout our work period.
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Contents
Contents CHAPTER 1 ...................................................................................................................... 1 1.1 Introduction .......................................................................................................................................... 1 Belayim Marine Field (ZoneII) ........................................................................................................ 1 1.2 Objectives ................................................................................................................................................ 4
CHAPTER 2 ...................................................................................................................... 5 2 Literature Review................................................................................................................................... 5 2.1 Reserves Definition .................................................................................................................... 5 2.1.1 SEC Definitions ............................................................................................................... 6 2.1.2 SPE Definitio n s ......................................................................................................... 9 2 . 2 R e s e r v e E s t i m a t i o n M e t h o d s .................................................................................... 12 2.2.1 Analogy:- ...................................................................................................................... 13 2.2.2 Volumetric Method ....................................................................................................... 15 2.2.2.1 Volumetric Uncertainty ....................................................................................... 17 2.2.3 Decline Curve Analysis (DCA): ............................................................................... 18 2.2.4 Material Balance Equation (MBE): .............................................................................. 24 2.2.4.1 MBE Assumptions:............................................................................................. 27 2.2.4.2 Primary Recovery Mechanism ............................................................................. 29 2.2.4.2 .1Rock And Liquid Expansion Drive: ....................................................... 30 2.2.4.2 .2 Depletion Drive: ......................................................................................... 31 2.2.4.2 .3 Gas-Cap Drive: .......................................................................................... 33 2.2.4.2.4 .Water Drive: ............................................................................................. 35 2.2.4.2.5 Gravity Drainage Drive : ............................................................................. 37 2.2.4.2.6 Combination: ............................................................................................. 39 2.2.4.3 Driving Indexes MBE: ........................................................................................ 40 2.2.4.3.1 Depletion Drive Index(Oil Zone Oil Expansion ),(DDI) ...................... 41 2.2.4.3.2Segregation Drive Index (Gas Zone Gas Expansion),(SDI) .................... 41 2.2.4.3.3Water Drive Index (W DI) .......................................................................... 41 2.2.4.3.4Expansion Drive Index (Rock And Liquid), (EDI) .............................. 41 2.2.4.4 MBE In Linear Form: .......................................................................................... 42 2.2.4.4.1 Volumetric Under saturated Reservoir ........................................................ 45 2.2.4.4 .2Volumetric Saturated Reservoirs ........................................................... 47 2.2.4.4 .3 Gas Cap Drive Reservoirs ...................................................................... 48 2.2.4.4 .4 Water Drive Reservoirs ............................................................................ 50 2.2.4.4 .5 Combination Drive Reservoir ............................................................... 57 2.2.4.5 Water Influx[5] .................................................................................................... 59 2.2.4.5 .1 Steady-state method .................................................................................... 59 2.2.4.5.2 VEH unsteady-state method ........................................................................ 61 2.2.4.5.3 Fetkovich Pseudo steady-state method ...................................................... 63 2.3 Enhanced Oil Recovery (EOR) [16,17] ................................................................................... 65 2.3 .1 Miscible EOR ................................................................................................................ 65 iv
Contents
2.3 .2 Chemical EOR ............................................................................................................. 66 2.3.3 Other EOR Processes ................................................................................................... 66 2.3 .2.1 Polymer Flooding ................................................................................................ 69 2.3.2.2 Surfactant Flooding ............................................................................................. 74 2.3 .2.3 Alkaline Flooding ............................................................................................... 75 2.4 Reservoir Simulation ......................................................................................................... 80 2.4.1 MBAL [22] .................................................................................................................... 81 2.4.2 Monte Carlo Simulation .............................................................................................. 83 2.4.3 ECLIPSE Simulation[21] .............................................................................................. 84 2.5 Comparison Between Reserve Estimation Methods[23] .......................................................... 87
CHAPTER 3 .................................................................................................................... 89 3 Methodology..............................................................................................................................................89 3.1 Available Data .......................................................................................................................... 89 3.2 Methodology............................................................................................................................. 92 3.2.1.1 The Material Balance Equation ............................................................................ 93 3.2.1.2 Water Influx ....................................................................................................... 101 3.2.1.2 .1Steady state Water Influx (SS) ................................................................... 101 3.2.1.2 .2 Semi-Steady State For Water Influx (SSS) ............................................... 105 3.2.1.2 .3 Unsteady state (USS) ................................................................................ 110 3.2.1.3 Prediction ........................................................................................................... 116 3.2.2 Reservoir Management Spread sheet ........................................................................... 125 3.2.3MBAL [24] ................................................................................................................... 129 3.2.3.1 Montecarlo Simulation Tool [24] : .................................................................... 129 3.2.3.2 MBE Tool [24] : ................................................................................................ 133 3.2.4 ECLIPSE [21] .............................................................................................................. 149
CHAPTER4 ................................................................................................................... 160 4
Result ..................................................................................................................................................160 4.1PVT Correlations [5] ............................................................................................................... 160 4.2 History Matching .................................................................................................................... 167 4.3 Prediction................................................................................................................................ 172 4.4EOR ......................................................................................................................................... 175 4.5 MBAL .................................................................................................................................... 178 4.6 ECLIPSE Results .................................................................................................................... 179 Conclusion .................................................................................................................................... 189 REFERENCES ............................................................................................................................. 191
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List of Figures
List of Figures Figure 1 Belayim Marine Oil Location Map . ........................................................................................................... 2 Figure 2 SEC Classification Of Oil And Gas Resources .[2] .................................................................................... 6 Figure 3 SPE Resource Classification System[1] ...................................................................................................... 9 Figure 4 Probabilistic Definition Of Reserves. ........................................................................................................ 10 Figure 5 Classification of production decline curves .[4] ........................................................................................ 19 Figure 6 Exponential, Hyperbolic And Harmonic Approaches . ............................................................................. 22 Figure 7 Decline Curve of an Oil well . [6] ............................................................................................................. 23 Figure 8 (Material Balance Tank Model) ................................................................................................................ 24 Figure 9 Solution Gas Drive Reservoir.[8] .............................................................................................................. 31 Figure 10 Production Data Of Depletion Drive Reservoir. [8] ............................................................................... 32 Figure 11 Gas-cap drive reservoir.[8] ..................................................................................................................... 33 Figure 12 Production Data For A Gas-Cap Drive Reservoir.[8] ............................................................................ 34 Figure 13 Reservoir With Water Drive .[8] ............................................................................................................. 35 Figure 14 Aquifer Geometries . [8].......................................................................................................................... 36 Figure 15 Production Data For A Water Drive Reservoir. [8] ............................................................................... 36 Figure 16 Initial Fluid Distribution In An Oil Reservoir . [8] ................................................................................. 37 Figure 17 Combination Drive Mechanism . [8] ....................................................................................................... 39 Figure 18 Classification Of The Reservoir. [5] ....................................................................................................... 46 Figure 19 Determining N For Saturated Reservoirs . [5] ........................................................................................ 47 Figure 20 F versus Eo + m Eg . [5] ........................................................................................................................ 49 Figure 21(F/Eo) versus (Eg/Eo)............................................................................................................................... 49 Figure 22 (F/Eo) As A Function Of (∆P/Eo) .[5] ..................................................................................................... 52 Figure 23 Steady State Model Applied To MBE.[5] ................................................................................................. 53 Figure 24 Havlena And Odeh Straight Line Plot . [10.11] ....................................................................................... 56 Figure 25 VEH Cylindrical In Shape Reservoir....................................................................................................... 61 Figure 26 Dimensionless Time And Fluid Influx Chart.[5] ..................................................................................... 62 Figure 27 Pressure Steps Used To Approximate The Pressure-Time Curve . [5] .................................................... 63 Figure 28 EOR Injection Method.[17] ..................................................................................................................... 67 Figure 29 Chemical EOR Target In Selected Countries.[17] .................................................................................. 68 Figure 30 Chemical Floods History. [17]................................................................................................................ 68 Figure 31 Current Status World Wide Production World Wide.[17] ....................................................................... 68 Figure 32 Polymer Flood Field Performance .[17] ................................................................................................. 73 Figure 33 Surfactant Flood [17] .............................................................................................................................. 74 Figure 34 pH Values Of Alkaline Solutions .[16] .................................................................................................... 76 Figure 35 Alkaline Flood Field Performance. [17] ................................................................................................. 78 Figure 36 Isopach Contour Map For Net Pay Zone OF Marine Zone 2 . ............................................................... 89 Figure 37 Reservoir MBE . ...................................................................................................................................... 94 Figure 38 Chart Calculate N. ................................................................................................................................ 100 Figure 39 Plot Of Pressure And Pressure Drop Versus Time. [15] ....................................................................... 101 Figure 40 Semi Steady State Behavior . ................................................................................................................ 105 Figure 41 Un Steady State Behavior ..................................................................................................................... 110 Figure 42 Plotting ∑Qt.∆P/Eo Vs (F-Wi*Βw)/EO At Re/Rw =2. .......................................................................... 113 Figure 43 Plotting ∑Qt.∆P/Eo vs (F-Wi*βw)/EO at re/rw =4............................................................................... 113 Figure 44 Plotting ∑Qt.∆P/Eo vs (F-Wi*βw)/EO at re/rw =8............................................................................... 114 Figure 45 Plotting ∑Qt.∆P/Eo vs (F-Wi*βw)/EO at re/rw =6............................................................................... 114 Figure 46 ∑Qt.∆P/Eo At Re/Rw = Infinity............................................................................................................. 115 Figure 47 Chart between P with ( wepe& we uss)) ................................................................................................ 123 Figure 48 Chart Between P With ( Wepe& We Uss)By Using Mew Wi. ................................................................ 124 Figure 49 Predicted p . .......................................................................................................................................... 124 Figure 50 Reservoir Management Spread Sheet Wells Input. ................................................................................ 125
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List of Figures
Figure 51Reservoir Management Spread Sheet Pressure Input. ........................................................................... 126 Figure 52 Pressure Matching ................................................................................................................................ 126 Figure 53 Reservoir Management Spread Sheet PVT Input . ................................................................................ 126 Figure 54 Reservoir management spread sheet PVT Matching . ......................................................................... 127 Figure 55 Reservoir Management Spread Sheet Well Locations. .......................................................................... 127 Figure 56 Reservoir Management Spread Sheet Prediction .................................................................................. 128 Figure 57 Reservoir Management Spread Sheet Prediction by chemical effect ..................................................... 128 Figure 58 Choosing Monte Carlo Tool. ................................................................................................................. 129 Figure 59 System Option Window.......................................................................................................................... 130 Figure 60 PVT Menu ............................................................................................................................................. 130 Figure 61 Data Input ............................................................................................................................................. 130 Figure 62 Match PVT data .................................................................................................................................... 131 Figure 63 Selecting Distributions. ......................................................................................................................... 131 Figure 64 Distributions.......................................................................................................................................... 132 Figure 65 General Option Widow. ........................................................................................................................ 134 Figure 66 PVT list ................................................................................................................................................ 135 Figure 67 Black Oil ( Data Input). ......................................................................................................................... 135 Figure 68 PVT Matching. ...................................................................................................................................... 136 Figure 69 Matching. .............................................................................................................................................. 136 Figure 70 Oil FVF Curve...................................................................................................................................... 137 Figure 71 Oil Viscosity Curve............................................................................................................................... 137 Figure 72 GOR Curve. .......................................................................................................................................... 138 Figure 73 Input List. ............................................................................................................................................. 138 Figure 74 Tank Parameters. .................................................................................................................................. 139 Figure 75 Water Influx.......................................................................................................................................... 139 Figure 76 Rock Compressibility............................................................................................................................. 140 Figure 77 Rock Compaction. ................................................................................................................................. 140 Figure 78 Relative Permeability. ........................................................................................................................... 141 Figure 79 Relative Permeability Curves. ............................................................................................................... 141 Figure 80 History Matching Table......................................................................................................................... 142 Figure 81 Import Window. .................................................................................................................................... 142 Figure 82 Import Setup. ........................................................................................................................................ 143 Figure 83 Import file. ............................................................................................................................................. 143 Figure 84 History Matching List........................................................................................................................... 144 Figure 85 Run History Matching. .......................................................................................................................... 144 Figure 86 Analytical Method. ............................................................................................................................... 145 Figure 87 Graphical method.................................................................................................................................. 145 Figure 88 Energy Plot........................................................................................................................................... 146 Figure 89 WD Function Plot.................................................................................................................................. 146 Figure 90 Production Prediction List. ................................................................................................................... 147 Figure 91 Prediction Calculation Setup. ............................................................................................................... 147 Figure 92 Tank Prediction Data. ........................................................................................................................... 148 Figure 93 Run Simulation Window. ....................................................................................................................... 148 Figure 94 Data File Section. .................................................................................................................................. 149 Figure 95 Simulator Preface.................................................................................................................................. 153 Figure 96 Run The Simulator................................................................................................................................. 153 Figure 97 Running The Simulator. ........................................................................................................................ 153 Figure 98 Print File Location. ............................................................................................................................... 154 Figure 99 Original Oil In Place (OOIP)................................................................................................................ 154 Figure 100 Start FLOVIZ ...................................................................................................................................... 154 Figure 101 Run The Model 1 . .............................................................................................................................. 155 Figure 102 Run The Model 3 . .............................................................................................................................. 155 Figure 103 Run The Model 2. ................................................................................................................................ 155 Figure 104 (FLOVIZ Parameters). ........................................................................................................................ 156 Figure 105 Reservoir Model . ............................................................................................................................... 156 Figure 106 RUN OFFICE...................................................................................................................................... 157
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List of Figures
Figure 107 Load All Vectors . ................................................................................................................................ 157 Figure 108 Input Variables . .................................................................................................................................. 158 Figure 109 Output OFFICE. ................................................................................................................................. 158 Figure 110 OFFICE Output table.......................................................................................................................... 159 Figure 111 OFFICE Output Charts . .................................................................................................................... 159 Figure 112 Gas Solubility ...................................................................................................................................... 160 Figure 113 Correction..................................................................................................................................... 161 Figure 114 FVF ..................................................................................................................................................... 162 Figure 115 Oil Compressibility ............................................................................................................................. 163 Figure 116 Oil Viscosity ........................................................................................................................................ 164 Figure 117 Crude Oil Denisty................................................................................................................................ 165 Figure 118 Bw ....................................................................................................................................................... 165 Figure 119 Water Compressibility ......................................................................................................................... 166 Figure 121 Gp Vs Years ......................................................................................................................................... 168 Figure 120 Wp,Wi,Np (bbl) Vs Years ..................................................................................................................... 168 Figure 122 Cw,Co,Rs ............................................................................................................................................. 170 Figure 123 Bo, Mo ................................................................................................................................................. 170 Figure 124 re/rw=infinty ....................................................................................................................................... 171 Figure 125 Past& Future....................................................................................................................................... 174 Figure 126Purely Viscous...................................................................................................................................... 175 Figure 127 Visco Elastic ........................................................................................................................................ 176 Figure 128 prediction by chemical effect ............................................................................................................... 177 Figure 129 Montecarlo Results 2 ........................................................................................................................... 178 Figure 130 Montecarlo Results 1 ........................................................................................................................... 178 Figure 131 Drive mechanism ................................................................................................................................. 179 Figure 132 Bottom drive aquifer............................................................................................................................ 179 Figure 133 graphical method................................................................................................................................. 180 Figure 134 Analytical method ................................................................................................................................ 180 Figure 135 Gas and oil rate ................................................................................................................................... 181 Figure 136 Average water injected with cumulative oil produced ......................................................................... 181 Figure 137 cumulative gas and oil produced ......................................................................................................... 182 Figure 138 Cumulative oil produced with water injected ...................................................................................... 182 Figure 139 water injection And cumulative oil production with time .................................................................... 183 Figure 140 oil saturation with time........................................................................................................................ 183 Figure 141 recovery factor .................................................................................................................................... 184 Figure 142 Reservoir Model .................................................................................................................................. 185 Figure 143 Side view ............................................................................................................................................. 185 Figure 144 FOPT,FGPT, FWPT, FWIT Vs Date ................................................................................................... 186 Figure 145FGPR, FOPR, FWPR, FWIR Vs Date .................................................................................................. 186 Figure 146 In place calculation ............................................................................................................................. 187 Figure 147 New Well ............................................................................................................................................. 188 Figure 148 Comparison no. of wells ...................................................................................................................... 188 Figure 149 Comparison Inj. Wells ......................................................................................................................... 189
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LIST OF TABLES
List Of Tables Table 1 Classification Of Proved Reserves.[2] .......................................................................................................... 8 Table 2 Historical Development Of Reserves Definitions And Classifications. ........................................................ 11 Table 3 Recovery Factors For Oil And Gas Reservoirs .[2] .................................................................................... 16 Table 4 Decline Curve Equations'. ......................................................................................................................... 21 Table 5 Dimensionless Time And Fluid Influx Table .[5] ........................................................................................ 62 Table 6 Polymer Structures And Their Characteristics.[16] ................................................................................... 70 Table 7 Properties Of Several Common Alkalis .[16].............................................................................................. 77 Table 8 Reserve Estimation Methods Comparison .[23] ......................................................................................... 87 Table 9 Summary Of Reserve Estimation Methods.[23] .......................................................................................... 88 Table 10 Belayim Marine Field (Zone 2) Data........................................................................................................ 90 Table 11 Belayim Marine Field (Zone 2) Pvt Data . ............................................................................................... 91 Table 12 Calculate Oil Compressibility. .................................................................................................................. 96 Table 13 Calculate Water Compressibility . ............................................................................................................ 97 Table 14 Calculate Effective Compressibility. ........................................................................................................ 98 Table 15 Calculate Wi ,Wp,βw . ............................................................................................................................... 98 Table 16 Calculate (Eo)&(F-Wi βw). ...................................................................................................................... 99 Table 17 Marine zone II Data ................................................................................................................................ 103 Table 18 Calculated k' values ................................................................................................................................ 104 Table 19 Determining Semi Steady State Equations’ Parameters ......................................................................... 108 Table 20 Comparing Values Of (Δwe SSS)/ΔT And (Δwe MBE)/ΔT. .................................................................. 109 Table 21 Td vs pressure and Ce. ............................................................................................................................ 112 Table 22 Calculation of ∑Qt.∆P/Eo at re/rw = 2 and 4. ....................................................................................... 113 Table 23 Calculation Of ∑Qt.∆P/Eo At Re/Rw = 6 And 8. .................................................................................... 114 Table 24 Calculating ∑Qt.∆P/Eo At Re/Rw = Infinity. .......................................................................................... 115 Table 25 Prediction Table ..................................................................................................................................... 116 Table 26 3 Pressures Assumption .......................................................................................................................... 116 Table 27 Cw,Co,Ce, βo, βw for P.=1400 ............................................................................................................... 116 Table 28 Cw,Co,Ce, βo, βw for P.=1410 ............................................................................................................... 117 Table 29 Cw,Co,Ce, βo, βw for P.=1420 ............................................................................................................... 117 Table 30 Input Cw,Co,Ce, βo, βw for the 3 P. ....................................................................................................... 117 Table 31Calculate Delta P..................................................................................................................................... 118 Table 32 Calculate TD ........................................................................................................................................... 118 Table 33 Calculate TD at re/rw >10 [5]................................................................................................................ 119 Table 34 Calculate (QT) ........................................................................................................................................ 119 Table 35 Calculate ∑Qt.∆P ................................................................................................................................... 120 Table 36 Input QT ,∑Qt.∆P. .................................................................................................................................. 120 Table 37 Calculate We uss ..................................................................................................................................... 121 Table 38 Input Wp ,NP........................................................................................................................................... 121 Table 39 Calculate Wi ........................................................................................................................................... 122 Table 40 Calculate NP*βo ,WP*βw, WI*βw ,∆P ................................................................................................... 122 Table 41 Calculate N*βoi*Ce*∆P ......................................................................................................................... 122 Table 42 Calculate We MBE .................................................................................................................................. 123 Table 43 crude oil denisty used correletion. .......................................................................................................... 164 Table 44 Oil Denisty suitable Correlation ............................................................................................................. 164 Table 45 PVT Conculosion .................................................................................................................................... 166 Table 46 History Matching. ................................................................................................................................... 167 Table 47 PVT Matching. ........................................................................................................................................ 169 Table 48 Wi/Np & dWi/Np ..................................................................................................................................... 172 Table 49 Prediction Calculation ............................................................................................................................ 173 Table 50 Conclusion .............................................................................................................................................. 190
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LIST OF TABLES
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CHAPTER 1
CHAPTER 1 1.1 Introduction Belayim Marine Field (ZoneII) Zone II is one of the oil reservoirs composing Belayim Marine field; from the stratigraphic point of view, it belongs to the upper portion of Belayim formation. Zone II was discovered by 113M-1 in 1962 and production started in 1963 through wells 113M-1 & BM2, by Dec. 1996, Zone II had produced a cum. of 6.75*106 STD m3 of oil and the production rate was 526 STD m3/d. The geological structure of Zone II that was reconstructed based composed of sand bodies mainly deposited in the west-southwest flank of an anticline with a north-west southeast trend. The sand thickness reduces along the crest of the structure and is interrupted by a fault along the west flank. Two aquifers have been identified based on the different original OWC depths. The OWC of the main aquifer is identified based on the log analysis of well 113M-25, the secondary aquifer is present only in an isolated area and well 113M-31 identified it. The oil characteristics were determined based on the analysis of the surface sample collected at well 113M-26; it points out a mediumhigh density oil of 20.7 API.
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CHAPTER 1
Balayim Marine Oil Field – Location map
CHAPTER 1
Figure 1 Belayim Marine Oil Location Map .
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CHAPTER 1
This book starts with showing the project objectives to be a good reservoir engineer and whats the purpose of reservoir engineering and what is reservoir engineer concerns. Then talking about literature review about reservoir engineering which used to build knowledge about types of reservoirs, driving mechanisms and different types of reserve calculation. Then starts to show the available data that will be used in calculations and starts it in methodology that shows the procedures followed in calculation to get final results Finally the book shows the final results and conclusion of different calculations type and compare between results to get the best one and build recommendations to increasing the recovery factor and productivity
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CHAPTER 1
1.2 Objectives From Reservoir Engineering Concepts Starting The Main Project Objectives:1- Selecting the most suitable correlations to calculate fluid properties of (Belayim Marine Field (ZoneII)) with lowest
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average absolute error(AAE) to helping and decrease money paid in core analysis and PVT Lab. Knowing the reservoir type and its driving mechanism. Calculating the original oil in place (OOIP) by using different methods e.g.(MBE, Montecarlo , Decline curve, MBAL ,Eclipse) , compare between those methods and choose the most accurate result. Predicting of the reservoir life and production rate with highest recovery factor. Enhancing oil recovery method to increase oil production and decrease water cut percentage.
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CHAPTER 2 2 Literature Review 2.1 Reserves Definition Unfortunately, there are some disagreements in the world related to reserve definition. While some countries base their reserves on maximum recoverable, others rely on minimum recoverable. Many countries tend to maximize their reserves for political and economic reasons and keep their reserves confidential. So it is very difficult to estimate the world reserves, not only for the disagreements in definitions but also for the lack of data and incorrect aggregation. The problem of definitions is being solved over the years by applying standard definitions. The most common definitions used globally are those set by SPE and The US Securities and Exchange Commission (SEC).
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2.1.1 SEC Definitions According to the US Securities and Exchange Commission (SEC), Oil and Gas resources are classified according to the flow chart shown in Figure
Figure 2 SEC Classification Of Oil And Gas Resources .[2]
The total oil and gas resources are the total quantities expected to be present underground, this can be divided into discovered resources and undiscovered resources. Undiscovered resources are those quantities not yet discovered. Discovered resources are those resources already discovered using existing technology. They can be classified into recoverable and unrecoverable resources. Unrecoverable resources are those quantities that cannot be recovered due to lack of technology or economic reasons. Recoverable resources are those quantities that can be recovered using existing technology and current economic conditions. They can be further classified into reserves and cumulative production.
Cumulative production is the quantities already produced from known accumulation s using the existing technology and under current economic conditions. 6
Reserves are estimated volumes of crude oil, condensate, natural gas, natural gas liquids, and associated substances anticipated to be commercially recoverable from known accumulations from a given date forward, under existing economic conditions, by established operating practices, and under current government regulations. Reserve estimates are based on geologic and/or engineering data available at the time of estimate. The relative degree of an estimated uncertainty is reflected by the categorization of reserves as either "proved" or "unproved" Proved Reserves can be estimated with reasonable certainty to be recoverable under current economic conditions. Current economic conditions include prices and costs prevailing at the time of the estimate. Reserves are considered proved if the commercial productivity of the reservoir is supported by actual engineering tests. By using probabilistic approach, if the probability that the real production will have a chance of 90% to exceed or be equal to the calculated value, we consider the estimated value as proved reserves. Proved reserves can be further classified as shown in Figure 2. Unproved Reserves are based on geological and/or engineering data similar to those used in the estimates of proved reserves, but when technical, contractual, economic or regulatory uncertainties preclude such reserves being classified as proved. They may be estimated assuming future economic conditions different from those prevailing at the time of the estimate.. Unproved reserves may further be classified as probable and possible.
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Probable Reserves (P50) are less certain than proved reserves and can be estimated with a degree of certainty sufficient to indicate they are more likely to be recovered than not. By using probabilistic approach, the chance of the real production figure to be equal to or exceed the calculated value is 50%, we usually refer to it as proved plus probable reserves and are given by (P50). Possible Reserves are less certain than proved reserves and can be estimated with a low degree of certainty, insufficient to indicate whether they are more likely to be recovered than not Table 1 Classification Of Proved Reserves.[2]
PDP are those quantities expected to be recovered from locations where a proper field development plan was introduced, wells were drilled, and production is on-going. PDNP are those quantities expected to be recovere3d from locations where a proper field development plan was introduced, wells were drilled, but production has not yet started. PUD are those quantities that in order to be recovered, the accumulation sin which they exist need a proper development plan to take place in order to decide the number of wells needed And other requirement for these quantities to be produced and the field to be productive.
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2.1.2 SPE Definitions Figure 4 presents the petroleum resource classification according to Society of Petroleum Engineers (SPE) and its similarity to the SEC resource classification
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Figure 3 SPE Resource Classification System[1]
Discovered Petroleum-initially-in-place is that quantity of petroleum which is estimated, on a given date, to be contained in known accumulations, plus those quantities already produced therefrom. This may be may be subdivided into Commercial and Sub-commercial categories, with the estimated potentially recoverable portion being classified as Reserves and Contingent Resources respectively. Reserves are defined as those quantities of petroleum which are anticipated to be commercially recovered from known accumulations from a given date forward. The uncertainty in reserve estimation can be reflected in proved. Probable, and possible reserves. Proved, probable and possible reserves have the same definitions of the SEC classification. The probabilistic approach is best explained in figure 4. 9
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Figure 4 Probabilistic Definition Of Reserves.
Contingent Resources are those quantities of petroleum which are estimated, on a given date, to be potentially recoverable from known accumulations, but which are not currently considered to be commercially recoverable. Undiscovered Petroleum-initially-in-place is that quantity of petroleum which is estimated, on a given date, to be contained in accumulations yet to be discovered. Prospective Resources are those quantities of petroleum which are estimated, on a given date, to be potentially recoverable from undiscovered accumulations Many governments, organisations and companies have made their own reserves definitions and classifications. The complete historical development of reserves definitions and classifications is shown in table 2.
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Table 2 Historical Development Of Reserves Definitions And Classifications. Society of Petroleum Engineers (SPE) Date 1964
Other Organizations
Definition SPE Reserves Definitions [20]
Organization Name
Date
American Petroleum
1936
Institute Reserves Definition (API) [27] 1981
SPE, WPC, AAPG [21]
ARPS Reserve
1962
Classification [28] October, 1988
SPE Reserves Definitions [22]
McKelvey Resource
1972
Classification System [29] March, 1997
SPE/ WPC [23]
SEC Reserve
1975
Classification [30] February,
SPE/WPC/AAPG [24]
Norwegian Petroleum Directorate (NPD) [31]
2000 2001
Guidelines for the Evaluation
The UNFC
of Petroleum Reserves and
Classification System
Resources, 2001 2005
[25]
2001
November 2003
[32]
Glossary of Terms Used in Petroleum Reserves/Resources Definitions [26]
Chinese Classification System [33]
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2005
2 . 2 Reserve Estimation Methods Reserves can be calculated using the following techniques[2] :Analogy Volumetric Decline curve analysis Material Balance Reservoir simulation Two calculation approaches can be applied. These are deterministic and probabilistic approaches. The deterministic approach involves using a single value from each input parameter of the equation used in the estimation process. This generates a single value for the IOIP. This approach is used when uncertainty is low or when the degree of confidence in the data available is very high. The probabilistic approach involves making a probability distribution function for each input parameter using the range of uncertainty in each parameter (minimum, maximum, average). This distribution function allows the calculation of all the possible outcomes of the IOIP value and covers all the ranges of uncertainty. This approach I used when the uncertainty is very high and can be also used as a risk analysis method.
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2.2.1 Analogy:Reserves are estimated by analogy to reservoir in the same geographic area or field with similar properties. The SEC institute that only offset wells in the same field can be used to estimate proved reserves by analogy. Nevertheless, analogy is most used to determine probable and possible reserves in the same geographic area. The similarities between the target reservoir and the analogy model should include :• Lithology and depositional environment of the reservoir rock • Petrophysical parameters of the rock and fluid saturations • Initial bottom hole pressure (BHP) and temperature (BHT) • BHP at the start-up of a project • Reservoir fluid properties (PVT) • Structural configuration • Reservoir heterogeneity and continuity • Recovery mechanism, natural or induced • Well spacing and spacing pattern
Reservoir maturity and the stage of development of both the analogy and the target reservoir should be taken into account. When the proper analogy has been established, it can be used to estimate[2]: • Ultimate recovery per well • Drainage area and appropriate well spacing • Initial reservoir parameters • Initial productivity per well • Typical decline type and decline characteristics • Expected abandonment pressure • Expected drive mechanism 13
• Enhanced recovery factor for pressure maintenance • Recovery for a given drive mechanism: − Per well − Per acre-foot (RF) The analogy method is applied by comparing the following factors for the analogous and current fields or wells: 1. Recovery Factor (RF), 2. Barrels per Acre-Foot (BAF). 3. Estimated Ultimate Recovery (EUR). The RF of a close-to-abandonment analogous field is taken as an approximate value for another field. Similarly, the BAF is assumed to be the same for the analogous and current field or well, which is calculated by the following equation
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2.2.2 Volumetric Method The volumetric technique is the most widely used approach to estimate reserves during the exploration stage of a field. Often used as first step, it is compared with other techniques as more data become available and the uncertainty decrease. The estimate ultimate recovery (EUR) for an oil reservoir is given by:
Where:N = oil in place (STB) RF = Recovery factor Vb = Bulk reservoir volume (acre ft) Ø = Average reservoir porosity Sw = Average reservoir water saturation Bo = Oil formation volume factor (RB/STB)
From a contour map:
where Vb = contour interval Ao = area of the contour Using reservoir drainage area and thickness:-
Where: A = reservoir area (acres) h = thickness (ft)
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Table 3 (gives the typical primary recovery factors for oil and gas reservoirs by drive mechanism. The primary oil driving mechanisms will be discussed in the Material balance equation section .
Table 3 Recovery Factors For Oil And Gas Reservoirs .[2]
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2.2.2.1 Volumetric Uncertainty A volumetric estimate provides a static measure of oil or gas in place. The accuracy of the estimate depends on the amount of data available, which is very limited in the early stages of exploration and increases as wells are drilled and the pool is developed. Monte Carlo simulation provides a methodology to quantify the uncertainty in the volumetric estimate based on assessing the uncertainty in input parameters such as: • Gross rock volume, reservoir geometry and trapping • Pore volume and permeability distribution • Fluid contacts
The accuracy of the reserve or resource estimates also increases once production data is obtained and performance type methods such as material balance and decline analysis can be utilized. Finally, integrating all the techniques provides more reliable answers than relying solely on any one method
17
2.2.3 Decline Curve Analysis (DCA): Production decline analysis is a basic tool for forecasting production from a well or a group of wells once there is sufficient production to establish a decline trend as a function of time or cumulative production. The technique is more accurate than volumetric methods when sufficient data is available to establish a reliable trend and is applicable to both oil and gas wells. It is most often used to estimate remaining recoverable reserves, but it is also useful for water flood and enhanced oil recovery (EOR) performance assessments and in identifying production issues/mechanical problems. Production decline analysis of an analogous producing pool provides a basis for forecasting production and ultimate recovery from an exploration prospect or stepout drilling location. A well‘s production capability declines as production proceeds. This happens mainly due to combination of pressure depletion, displacement of another fluid (gas and/or water) and changes in relative fluid permeability. Plots of production rate versus production history (time or cumulative production) illustrate declining production rates as cumulative production increases. In theory, production decline analysis is only applicable to individual wells but in practice extrapolations of group production trends often provide acceptable approximations for group performance. The estimated ultimate recovery (EUR) for a producing unit is obtained by extrapolating the trend to an economic production limit. The extrapolation is valid provided that [3]: • Past trends were developed with the well producing at capacity. • Volumetric expansion was the primary drive mechanism. The technique is not valid when there is significant pressure support from an underlying aquifer. • The drive mechanism and operating practices continue into the future.
18
Curves that can be used for production forecasting include: 1. Production rate versus time. 2. Production rate versus cumulative production. 3. Water cut percentage versus cumulative production 4. Water level versus cumulative production 5. Cumulative gas versus cumulative oil 6. Pressure versus cumulative production.
Figure 5 shows the classification of production decline curves and how each of them can be applied by using exponential, hyperbolic and harmonic approaches.[4]
Figure 5 Classification of production decline curves .[4]
19
The first two types are the most common types of decline curves, because the trend for wells producing from conventional reservoirs under primary production will be ―exponential‖ ,which means that the data will present a straight line trend when production rate vs. time is plotted on a semi-logarithmic scale. The data will also present a straight line trend when production rate versus cumulative production is plotted on regular Cartesian coordinates. The well‘s ultimate production volume can be read directly from the plot by extrapolating the straight line trend to the production rate economic limit. Arps (1945, 1956) developed the initial series of decline curve equations to model well performance [3]. The equations were initially considered as empirical and were classified into (Exponential, Hyperbolic, Harmonic), based on the value of the exponent ―b‖ that characterizes the change in production decline rate with the rate of production. For exponential decline ‗b‘=0, for hyperbolic ‗b‘ is generally between 0 and 1. Harmonic decline is a special case of hyperbolic decline where ‗b‘=1. Table 4 summarizes ARPS‘ equation used in DCA.
20
Table 4 Decline Curve Equations'.
Figure 6 shows the difference between the exponential, hyperbolic, and harmonic approaches used in DCA (rate versus time). [5]
21
Figure 6 Exponential, Hyperbolic And Harmonic Approaches .
22
Chapter 2
Figure7 is an example of a typical oil well showing the difference between Exponential and Harmonic Extrapolations (rate versus cumulative production) and also shows the economic limit at which data are extrapolated. [6]
Figure 7 Decline Curve of an Oil well . [6]
In Figure 7, the Exponential extrapolation yields a straight line, while the Harmonic extrapolation yielded a concave upward shape (curve). This is due to the difference in the exponent ‗b‘ values for both methods. The economic limit line is the line showing the economic production limit at which the data are extrapolated in order to predict future production.
23
Chapter 2
2.2.4 Material Balance Equation (MBE): Material balance is the technique that uses the law of conservation of matter. The material balance method is a tank model equation. It is written from start of production to any time (t) as the expansion of oil in the oil zone plus the expansion of gas in the gas zone plus the expansion of connate water in the oil and gas zones plus the contraction of pore volume in the oil and gas zones plus the water influx plus the water injected plus the gas injected equal to the oil produced plus the gas produced plus the water produced.[5] Figure 8 shows the tank model on which MBE was built.
Figure 8 (Material Balance Tank Model)
A general material balance equation that can be applied to all reservoir types was first developed by Schilthuis in 1936 [7]. Although it is a tank model equation, it can provide great insight for the practicing reservoir Engineer.
24
Chapter 2
It is written from start of production to any time (t) as follows: Expansion of oil in the oil zone + Expansion of gas in the gas zone + Expansion of connate water in the oil and gas zones + Water influx + Water injected + Gas injected = Oil produced + Gas produced + Water produced The Generalized MBE can be written mathematically as:
Where: N = initial oil in place, STB Np = cumulative oil produced, STB G = initial gas in place, SCF Gi = cumulative gas injected into reservoir, SCF Gp = cumulative gas produced, SCF We = water influx into reservoir, bbl Wi = cumulative water injected into reservoir, STB Wp = cumulative water produced, STB Bti = initial two-phase formation volume factor, bbl/STB = Boi Boi = initial oil formation volume factor, bbl/STB 25
Chapter 2
Bgi = initial gas formation volume factor, bbl/SCF Bt = two-phase formation volume factor, bbl/STB = Bo + (Rsoi - Rso)Bg Bo = oil formation volume factor, bbl/STB Bg = gas formation volume factor, bbl/SCF Bw = water formation volume factor, bbl/STB Big = injected gas formation volume factor, bbl/SCF Biw = injected water formation volume factor, bbl/STB Rsoi = initial solution gas-oil ratio, SCF/STB Rso = solution gas-oil ratio, SCF/STB Rp = cumulative produced gas-oil ratio, SCF/STB Cf = formation compressibility, psia-1 Cw = water isothermal compressibility, psia-1, Swi = initial water saturation, Δpt = reservoir pressure drop, psia = pi - p(t) p(t) = current reservoir pressure, psia
26
Chapter 2
2.2.4.1 MBE Assumptions: The MBE keeps an inventory on all material entering, leaving, or accumulating within a region over discrete periods of time during the production history. The calculation is most vulnerable to many of its underlying assumptions early in the depletion sequence when fluid movements are limited and pressure changes are small. Uneven depletion and partial reservoir development compound the accuracy problem. The basic assumptions in the MBE are as follows [5]:Constant temperature: Pressure–volume changes in the reservoir are assumed to occur without any temperature changes. If any temperature changes occur, they are usually sufficiently small to be ignored without significant error. Reservoir characteristics: The reservoir has uniform porosity, permeability, and thickness characteristics. In addition, the shifting in the gas–oil contact or oil–water contact is uniform throughout the reservoir. Fluid recovery: The fluid recovery is considered independent of the rate, number of wells, or location of the wells. The time element is not explicitly expressed in the material balance when applied to predict future reservoir performance. Pressure equilibrium: A uniform pressure is assumed to apply across the pool. The model is considered as a tank with infinite permeability. Constant reservoir volume: Reservoir volume is assumed to be constant except for those conditions of rock and water expansion or water influx that are specifically considered in the equation. Reliable production data: There are essentially three types of production data that must be recorded in order to use the MBE in performing reliable reservoir calculations. These are: 1. Oil production data, even for properties not of interest, can usually be obtained from various sources and is usually fairly reliable. 2. Gas production data is becoming more available and reliable as the market value of this commodity increases; unfortunately, this data will often be more questionable where gas is flared.
27
Chapter 2
3. The water production term need represent only the net withdrawals of water; therefore, where subsurface disposal of produced brine is to the same source formation, most of the error due to poor data will be eliminated.
28
Chapter 2
2.2.4.2 Primary Recovery Mechanism The overall performance of oil reservoirs is greatly affected by the nature of energy (driving mechanism), responsible for moving the oil to the well bore. There are basically six driving mechanisms which are [5] :1. Rock and Liquid expansion drive. 2. Depletion drive. 3. Gas-cap drive. 4. Water drive. 5. Gravity drainage drive. 6. Combination drive.
29
Chapter 2
2.2.4.2 .1Rock And Liquid Expansion Drive: An under-saturated reservoir is a reservoir that initially exists at a pressure higher than its bubble point pressure. At pressures above the bubble point pressure, crude oil, connate water and rock are the only materials present. As the reservoir pressure declines (with production), the rock and fluids expand due to their compressibilities. This compressibility is due to the expansion of individual rock grains and formation compaction. As a result of this expansion, the pore volume will be reduced as a result of a decrease in fluid pressure. This reduction in pore volume will force the crude oil and water out of the pore volume to the wellbore which explains this driving mechanism. The reservoirs under this driving mechanism, usually has a constant gas oil ratio. This driving mechanism is considered the least efficient driving force and has the lowest oil recovery rates.
30
Chapter 2
2.2.4.2 .2 Depletion Drive: This mechanism is also referred to as: Solution gas drive Dissolved gas drive Internal gas drive In this type of reservoir, the major source of energy us a result of gas liberation from the crude oil and the subsequent expansion of the solution gas as the reservoir pressure is reduced. As pressure falls below bubble point pressure, gas bubbles are liberated; these bubbles expand and force the crude oil out of the pore space as shown in figure 9.
Figure 9 Solution Gas Drive Reservoir.[8]
Cole (1969), suggested that a depletion drive reservoir can be identified by the following characteristics:[9] 1)
Reservoir pressure declines rapidly and continuously
2)
Gas Oil ratio increases to maximum ad then declines
3)
Water production is absent or negligible
4)
Well behavior: requires pumping at early stage
5)
Oil recovery ranges from 8% to 25%
31
Chapter 2
The above characteristic trends occurring during the production life of depletion drive reservoirs is shown in figure 10.
Figure 10 Production Data Of Depletion Drive Reservoir. [8]
32
Chapter 2
2.2.4.2 .3 Gas-Cap Drive: Gas-cap drive reservoirs can be identified by the presence of a gas cap with little or no water drive as shown in figure 11.
Figure 11 Gas-cap drive reservoir.[8]
The natural energy available to produce the crude oil comes from: The expansion of the gas cap The expansion of solution gas as it is liberated
Cole and Clark (1969), suggested that gas-cap drive reservoirs have the following characteristics [9]: 1)
Reservoir pressure falls slowly and continuously
2)
Gas Oil ratio rises continuously
3)
Water production is absent or negligible
4)
Well behavior: gas-cap drive reservoirs tend to flow longer than depletion drive reservoirs
5)
Oil recovery ranges from 20% to 40%
33
Chapter 2
The above characteristic trends occurring during the production life of gascap drive reservoirs is shown in figure 12 .
Figure 12 Production Data For A Gas-Cap Drive Reservoir.[8]
34
Chapter 2
2.2.4.2.4 .Water Drive: any reservoirs are bounded on a portion or all of their edges by water bearing rocks called aquifers. The aquifers may be so large compared to the reservoir where they act infinitely. They may also range down to small (almost negligible), in their effects on the reservoir performance. The aquifer may be entirely bounded by impermeable rock so that the reservoir and aquifer together form a volumetric (closed unit). On the other hand, the reservoir may be outcropped at one or more places where it may be replenished by surface water as shown in figure 13.
Figure 13 Reservoir With Water Drive .[8]
When talking about water influx, it is common to speak about edge water and bottom water drive. Bottom water occurs directly beneath the oil and edge water occurs in the flanks at the edge of the oil as shown in figure 14 . Regardless of the source of water, the water drive mechanism is the result of water moving into the pore spaces originally occupied by oil, replacing the oil and displacing it to the producing wells.
35
Chapter 2
Figure 14 Aquifer Geometries . [8]
Cole (1969), suggested that water drive reservoirs have the following characteristics [11]: 1)
Reservoir pressure remains high
2)
Gas Oil ratio remains low
3)
Water production starts early and increase to appreciable amounts
4)
Well behavior: flow until water production gets excessive
5)
Oil recovery ranges from 20% to 55%
Figure 15 shows the production data for a water drive reservoir.
Figure 15 Production Data For A Water Drive Reservoir. [8]
36
Chapter 2
2.2.4.2.5 Gravity Drainage Drive : The mechanism of gravity drainage occurs in petroleum reservoirs as a result of differences in densities of the reservoir fluids. The effects of gravitational forces can be simply illustrated by placing a quantity of crude oil and a quantity of water in a jar and agitating the contents. After agitation, the jar is placed at rest, and the denser fluid (normally water) will settle to the bottom of the jar, while the less dense fluid (normally oil) will rest on top of the denser fluid. The fluids have separated as a result of the gravitational forces acting on them. The fluids in petroleum reservoirs have all been subjected to the forces of gravity, as evidenced by the relative positions of the fluids, i.e., gas on top, oil underlying the gas, and water underlying oil. The relative positions of the reservoir fluids are shown in Figure 16 .
Figure 16 Initial Fluid Distribution In An Oil Reservoir . [8]
Gravity segregation of fluids is probably present to some degree in all petroleum reservoirs, but it may contribute substantially to oil production in some reservoirs.
37
Chapter 2
Cole (1969), stated that reservoirs under gravity drainage drive have the following characteristics [9] :1)
Reservoir pressure has variable rates of pressure decline depending on the amount of gas. In most cases, there is a rapid pressure decline.
2)
Gas Oil ratio remains low.
3)
Water production starts is absent or negligible.
4)
Oil recovery ranges from 30% to 70%.
38
Chapter 2
2.2.4.2.6 Combination: In real cases, a reservoir usually includes at least two main drive mechanisms. For instance, in the case shown in the figure below, the management of the reservoir for different drive mechanisms can be diametrically opposed (e.g. low perforation for gas cap reservoirs compared with high perforation for water drive reservoirs). If both occur as in Figure, a compromise must be required, and this compromise must take into account the strength of each drive present, the size of the gas cap, and the size/permeability of the aquifer. It is the job of the reservoir manager to identify the strengths of the drives as early as possible in the life of the reservoir to optimize the reservoir performance.
Figure 17 Combination Drive Mechanism . [8]
39
Chapter 2
2.2.4.3 Driving Indexes MBE: As discussed earlier, oil can be primarily recovered by five driving mechanisms, to determine the relative magnitude of each of these driving mechanisms, the compressibility term in the general material balance equation is neglected and the equation is rearranged as follows:
Dividing by the right hand side of the equation gives:
The terms on the left hand side of equation above represent the depletion drive index (DDI), the segregation drive (gas cap drive) index (SDI), and the water drive index (WDI) respectively. The expansion drive index (EDI), has a minor effect on the oil recovery and can be neglected (not included in the equation). Prison‘s abbreviation can be used to give the following equation [7] : DDI + SDI+ WDI+ EDI + 1 Where EDI can be neglected as mentioned earlier.
The driving index for each mechanism can be calculated for a reservoir in order to calculate the efficiency of each driving mechanism.
40
Chapter 2
2.2.4.3.1
Depletion Drive Index(Oil Zone Oil Expansion ),(DDI)
Depletion drive is the oil recovery mechanism wherein the production of the oil from its reservoir rock is achieved by the expansion of the original oil volume with all its original dissolved gas.
2.2.4.3.2
Segregation Drive Index (Gas Zone Gas Expansion),(SDI)
Segregation drive (gas cap drive) is the mechanism wherein the displacement of oil from the formation is accomplished by the expansion of the original free gas cap.
2.2.4.3.3
Water Drive Index (W DI)
Water drive is the mechanism wherein the displacement of the oil is accomplished by the net encroachment of water into the oil zone.
2.2.4.3.4
Expansion Drive Index (Rock And Liquid), (EDI)
For under saturated oil reservoirs with no water influx, the principle source of energy is a result of the rock and fluid expansion. Where all the other three driving mechanisms are contributing to the production of oil and gas from the reservoir, the contribution of the rock and fluid expansion to the oil recovery is too small and essentially negligible and can be ignored.
41
Chapter 2
2.2.4.4 MBE In Linear Form: Normally, when using the material balance equation, each pressure and the corresponding production data is considered as being a separate point from other pressure values. From each separate point, a calculation is made and the results of these calculations are averaged. However, a method is required to make use of all data points with the requirement that these points must yield solutions to the material balance equation that behave linearly to obtain values of the independent variable. The straight- line method was developed by Havlena and Odeh (1963) by starting with[10,11] :
Defining the ratio of the initial gas cap volume to the initial oil volume as:
Putting m in the equation gives:
42
Chapter 2
Let:
Where: F = Underground withdrawal Eo = Oil and Dissolved gas expansion terms Eg = Gas cap expansion term Ef,w = rock and water compression/expansion terms So we obtain:
(E1)
The above equation was developed in order to determine the following three unknowns [10,11] 1. The Original Oil in Place N 2. The cumulative water influx We 3. The original gas cap size compared to the oil zone size m.
43
Chapter 2
The straight line relationship developed by Havlena and Odeh can be used in the following six applications:
Case 1: Determination of N in volumetric undersaturated reservoirs Case 2: Determination of N in volumetric saturated reservoirs Case 3: Determination of N and m in gas cap drive reservoirs Case 4: Determination of N and We‖ in water drive reservoirs Case 5: Determination of N, m, and We in combination drive reservoirs Case 6: Determination of average reservoir pressure, p
In this study, the main aim is to calculate the IOIP (N), and so the first five cases will be considered for calculating N only.
44
Chapter 2
2.2.4.4.1 Volumetric Under saturated Reservoir For a volumetric under-saturated reservoir, the conditions associated with a driving mechanism are [5]: • We = 0, since the reservoir is volumetric • m = 0, since the reservoir is undersaturated • Rs = Rsi = Rp, since all produced gas is dissolved in the oil Applying the above condition to Equation (E1) gives:
(E2)
Or
0
(E2)
To calculate N, a plot of (F/ Eo+ Ef ,w) versus cumulative production Np is 0 plotted. Figure shows an example of this plot. Dake (1994) suggest that this plot can take two shapes [12]. As shown in figure 9, Line A implies that the reservoir is a volumetric reservoir. This defines a purely depletion drive reservoir whose energy drives solely form the expansion of rock, connate water and oil. Lines B and C, implies the existence of a water drive in which the reservoir was energized by water influx, Line B represents a moderate aquifer whose degree of energizing decreases with time. While, Line c represents a strong aquifer who is acting infinitely. In all cases, IOIP (N) is the ordinate value of the plateau as shown in figure 18.
45
Chapter 2
Figure 18 Classification Of The Reservoir. [5]
46
Chapter 2
2.2.4.4 .2Volumetric Saturated Reservoirs A saturated oil reservoir is an oil reservoir that originally exists at its bubble point pressure (Pb). The main driving mechanism in saturated reservoirs results from the liberation and expansion of the solution gas as the pressure drops below bubble point pressure. Havlena and Odeh equation (Equation (E1)) can be written as [10, 11]:
(E3) Assuming that the water and rock expansion term Ef,w is negligible in comparison with the expansion of solution gas. This relationship can be used to determine N for saturated reservoirs by plotting F versus Eo. This should result in a straight line going through the origin with a slope of N as shown in figure 19.
Figure 19 Determining N For Saturated Reservoirs . [5]
47
Chapter 2
2.2.4.4 .3 Gas Cap Drive Reservoirs In gas cap reservoirs, the expansion of the gas-cap gas is the dominant driving mechanism and assuming that natural water influx is negligible (We=0), the Havlena and Odeh MBE (Equation (E1)) can be written as:
(E4) The way in which equation (E4) is applied depends on the number of unknowns in the equation, there are three possible unknowns in equation (E4). N is unknown, m is known. M is unknown, N is known. N and m are unknown. The first and last case will be considered, because in the second case, N is known ,and as mentioned earlier; only methods to determine N will be discussed.
Unknown N, Known m: Equation 3 indicates that when m is known, a plot of F versus (Eo + m Eg) on a Cartesian scale would produce a straight line through the origin with a slope of N as shown in figure 20.
48
Chapter 2
Figure 20 F versus Eo + m Eg . [5]
N and m are unknown: If both N and m are unknown, equation (E4) can be re-expressed as:
(E5) A plot of F/Eo versus Eg/Eo should be linear with intercept N and slope mN as shown in figure 21.
Figure 21(F/Eo) versus (Eg/Eo). 49
Chapter 2
2.2.4.4 .4 Water Drive Reservoirs Dake (1978) points out that the term Ef,w can be neglected in water drive reservoirs. And so equation (E1) can be written as [13]: (E6) If, the reservoir has no initial gas cap, equation (E6) can be re-written as: (E7) Dake (1978) points out that in attempting to use the above two equations to match the production and pressure history of a reservoir, the greatest uncertainty is always the determination of the water influx (We) [13]. In fact, in order to calculate the influx the engineer is confronted with what is inherently the greatest uncertainty in the whole subject of reservoir engineering. The reason is that the calculation of (We) requires a mathematical model which itself relies on the knowledge of aquifer properties. Three water influx models will be discussed. These models are: Pot aquifer model Schilthuis steady-state model. Van Everdingen- Hurst unsteady state model. The assumed reservoir for these models will be a water drive reservoir with no gas cap which is represented by the following equation: (E8)
50
Chapter 2
Pot-Aquifer model: The pot aquifer model is used to represent water influx and is summarised by the following equation (E8)
(E9) The aquifer properties cw, cf, h, ra, and θ are rarely available and they can be combined as one unknown (K) and so equation (E9) can be written as: (E10) Combining equations (E8) and (E10) gives:
(E11)
Equation (E11) implies that a plot of (F/Eo) as a function of (∆P/Eo) would yield a straight line with an intercept of N and slope of K as shown in figure 22. 51
Chapter 2
Figure 22 (F/Eo) As A Function Of (∆P/Eo) .[5]
Schilthuis steady-state model: The steady state aquifer model was proposed by Schilthuis (1936) is given by [11]:
(E12) 52
Chapter 2
Combining equation (E8) with equation (E12) gives:
(E13) Plotting F/Eo versus
results in a straight line with an intercept N and
a slope (C) that describes the water influx as shown in figure 23.
Figure 23 Steady State Model Applied To MBE.[5]
53
Chapter 2
Van Everdingen - Hurst unsteady state model: The Van Everdingen-Hurst unsteady state model is given by [14]:
(E14)
With:
Van Everdingen and Hurst presented the dimensionless water influx WeD as a function of the dimensionless time tD and dimensionless radius rD that are given by:
Combining equation (E8) with (E14) gives:
(E14) 54
Chapter 2
The proper methodology of solving the above linear relationship is summarized in the following steps. Step 1. From the field past production and pressure history, calculate the underground withdrawal F and oil expansion Eo. Step 2. Assume an aquifer configuration, i.e., linear or radial. Step 3. Assume the aquifer radius ra and calculate the dimensionless radius rD. Step 4. Plot (F/Eo) versus (Σ Δp WeD)/Eo on a Cartesian scale. If the assumed aquifer parameters are correct, the plot will be a straight line with N being the intercept and the water influx constant B being the slope. It should be noted that four other different plots might result. These are: • Complete random scatter of the individual points, which indicates that the calculation and/or the basic data are in error. • A systematically upward curved line, which suggests that the assumed aquifer radius (or dimensionless radius) is too small. • A systematically downward curved line, indicating that the selected aquifer radius (or dimensionless radius) is too large. • An s-shaped curve indicates that a better fit could be obtained if a linear water influx is assumed.
Figure 24 shows a schematic illustration of Havlena-Odeh (1963) methodology in determining the aquifer fitting parameters [10,11].
55
Chapter 2
Figure 24 Havlena And Odeh Straight Line Plot . [10.11]
56
Chapter 2
2.2.4.4 .5 Combination Drive Reservoir The general straight line MBE equation is illustrated in equation E1 and is given by:
(E1) Where:
Havlena and Odeh differentiated equation (E1) with respect to pressure and rearranged the equation to eliminate m to give [10, 11]:
(E15) Where:
57
Chapter 2
A plot of the left-hand side of equation (E15) versus the second term on the right for a selected aquifer model should, if the choice is correct, provide a straight line with unit slope whose intercept on the ordinate gives the initial oil in place, N. After determining N and We, equation (E1) can be used to solve directly for m.
The derivatives used in equation (E15) can be evaluated numerically by any finite difference technique including forward , backward and central techniques.
58
Chapter 2
2.2.4.5 Water Influx[5] Many reservoirs are bounded on a portion or all their perimeters by water bearing rocks – aquifers. As reservoir fluids are produced, a pressure differential develops between the surrounding aquifer and the reservoir. The aquifer reacts by encroaching across the original hydrocarbon-water contact. Aquifers retard pressure decline in reservoirs by providing a sourceof water influx We. We is a function of time (production). We is dependent on the size of aquifer and the pressure drop from the aquifer to the reservoir.
2.2.4.5 .1 Steady-state method Schilthuis Steady-state method is the simplest model for water influx. Water influx is proportional to the pressure drawdown (pi – p):
Integrating Eq gives Where: k′= water flux constant, bbl/day-psi P = pressure at the original oil-water contact pi= initial pressure at the external boundary of the aquifer.
Calculation of k′and Wefrom production data: In a reasonably long period, if the production rate and reservoir pressure remain substantially constant, there is:
59
Chapter 2
The equation can be rearranged to:
If the pressure stabilizes and the withdraw rates are not reasonably constant, water influx in the pressure stabilized period Δt can be calculated from the total productions of oil, gas and water within Δt:
Then k′can be found from the following equation:
For an under-saturated oil reservoir and at pressures higher than the bubble point pressure, Equation can be simplified to:
60
Chapter 2
2.2.4.5.2 VEH unsteady-state method Van Everdingen and Hurst solutions to the single-phase unsteady state flow equation are used to calculate water influx. The hydrocarbon reservoir is the inner boundary condition and is analogous to the well and the aquifer is the flow medium analogous to the reservoir. Properties of aquifer are assumed homogeneous and constant. Reservoir and aquifer are assumed cylindrical in shape.
Figure 25 VEH Cylindrical In Shape Reservoir.
Water flux is calculated by the following equations:
In Where WeD is given as a function of dimensionless time D t and dimensionless radius D r (see Tables 5and Figures 26):
The dimensionless time and dimensionless radius are defined as
61
Chapter 2
Figure 26 Dimensionless Time And Fluid Influx Chart.[5]
Table 5 Dimensionless Time And Fluid Influx Table .[5]
62
Chapter 2
Values for Δpj are determined from measure pressures. The pressure changes are calculated as follows to approximate the pressure-time curve:
Figure 27 Pressure Steps Used To Approximate The Pressure-Time Curve . [5]
2.2.4.5.3 Fetkovich Pseudo steady-state method The size of the aquifer is known-finite aquifer. Any water influx from the aquifer depletes the pressure accordingto the material balance equation. Steps of calculation of water influx by using Fetkovich Pseudo steady state method: 1. Calculate the initial encroachable water, Wei(in bbls), in the aquifer
63
Chapter 2
2. Calculate the productivity index, J, for flow from the aquifer to the reservoir a) For finite aquifer with no flow at the outer boundary:
b) For finite aquifer with constant pressure the outer boundary:
3. Calculate the average reservoir pressure during a time step:
4. Calculate the water influx during a time step
5. Calculate the total cumulative water influx at the current time
6. Calculate the average aquifer pressure at the end of the current timestamp
7. Repeat Steps 3 to 6 for next time step. 64
Chapter 2
2.3 Enhanced Oil Recovery (EOR) [16,17] The life of an oil well goes through three distinct phases where various techniques are employed to maintain crude oil production at maximum levels. The primary importance of these techniques is to force oil into the wellhead where it can be pumped to the surface. Techniques employed at the third phase, commonly known as Enhanced Oil Recovery (EOR), can substantially improve extraction efficiency. Laboratory development of these techniques involves setups that duplicate well and reservoir conditions. Core Flooding Pumps or Core Analysis Pumps, such as Teledyne Isco Syringe Pumps, are used in laboratory testing of these Enhanced Oil Recovery (EOR) techniques.
The Three Stages of Oil Field Development Primary Recovery : In Primary Recovery, oil is forced out by pressure generated from gas present in the oil. Secondary Recovery : In Secondary Recovery, the reservoir is subjected to water flooding or gas injection to maintain a pressure that continues to move oil to the surface. Tertiary Recovery : Tertiary Recovery, also known as Enhanced Oil Recovery (EOR), introduces fluids that reduce viscosity and improve flow. These fluids could consist of gases that are miscible with oil (typically carbon dioxide), steam, air or oxygen, polymer solutions, gels, surfactant-polymer formulations, alkalinesurfactant-polymer formulations, or microorganism formulations.
2.3 .1 Miscible EOR Commonly applied in West Texas, this method usually employs supercritical CO2 to displace oil from a depleted oil reservoir with suitable characteristics (typically containing ―light‖ oils). Through changes in pressure and temperature, carbon dioxide can form a gas, liquid, solid, or supercritical fluid. When at or above the critical point of pressure and temperature, supercritical CO2 can maintain the properties of a gas while having the density of a liquid. Injected miscible CO2 will mix thoroughly with the oil within the reservoir such that the interfacial tension between these two substances effectively disappears. CO2 can also improve oil recovery by dissolving in, swelling, and reducing the viscosity of oil.
65
Chapter 2
In deep, high-pressure reservoirs, compressed nitrogen has been used instead of CO2. Hydrocarbon gases have also been used for miscible oil displacement in some large reservoirs. CO2, nitrogen, hydrocarbon gases, and flue gases have also been injected to immiscibly displace oil. At one extreme of conditions, these displacements may simply amount to ―pressure maintenance‖ in the reservoir (a secondary recovery process). Depending on oil character, gas composition and pressure, and temperature, the displacements could have a range of efficiencies up to and approaching a miscible displacement. CO2 has also been injected in a ―huff ‗n puff‖ or cyclic injection mode, like cyclic steam injection.
2.3 .2 Chemical EOR Three chemical flooding processes include polymer flooding, surfactant-polymer flooding, and alkaline-surfactant-polymer (ASP) flooding. In the polymer flooding method, water-soluble polymers increase the viscosity of the injected water, leading to a more efficient displacement of moderately viscous oils. Addition of surfactant to the polymer formulation may, under very specific circumstances, reduce oil-water interfacial tension to almost zero—displacing trapped residual oil. Although no large-scale surfactant-polymer floods have been implemented, the process has considerable potential to recover oil. A variation of this process involves addition of alkaline to the surfactant-polymer formulation. For some oils, alkaline may convert some acids within the oil to surfactants that aid oil recovery. The alkaline may also play a beneficial role in reducing surfactant retention in the rock. For all chemical flooding processes, inclusion of a viscosifier (usually a water-soluble polymer) is required to provide an efficient sweep of the expensive chemicals through the reservoir. Gels are also often used to strategically plug fractures (or other extremely permeable channels) before injecting the relatively expensive chemical solutions, miscible gases, or steam.
2.3.3 Other EOR Processes Over the years, a number of other innovative EOR processes have been conceived, including injection of carbonated water, microorganisms, foams, alkaline (without surfactant), and other formulations. These methods have shown varying degrees of promise, but require additional development before such applications will become common. 66
Chapter 2
Figure 28 EOR Injection Method.[17]
In our case we will focus in chemical EOR Why we use chemical EOR? Conventional oil RF <33%, worldwide ―Unrecoverable‖ oil = 2x1012bbls Much of it is recoverable by chemical methods Chemical methods are attractive: Burgeoning energy demand and high oil prices, most likely for longterm Diminishing reserves Advancements in technologies Better understanding of failed projects
67
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Chemical Method: Chemical EOR target in selected countries
Figure 29 Chemical EOR Target In Selected Countries.[17]
Chemical floods history
Figure 30 Chemical Floods History. [17]
Current status world wide production world wide
Figure 31 Current Status World Wide Production World Wide.[17]
68
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Objectives of chemical flooding: 1) Increase the Capillary Number Nc to mobilize residual oil 2) Decrease the Mobility Ratio M for better sweep 3) Emulsification of oil to facilitate production
Chemical Flooding General Limitations 1) Cost of chemicals 2) Excessive chemical loss: adsorption, reactions with clay and brines, dilution 3) Gravity segregation 4) Lack of control in large well spacing 5) Geology is unforgiving! 6) Great variation in the process mechanism, both areal and crosssectional
2.3 .2.1 Polymer Flooding the mobility control requirement is closely related to the ratio of displacing fluid mobility to displaced fluid mobility .Because changing displaced oil mobility (relative permeability and/or viscosity)often is not feasible without the injection of heat, most often we inject chemicals to change displacing fluid mobility. Primarily, the injected chemicals are polymers whose obvious function is to increase the displacing polymer solution viscosity, although other mechanisms are involved. Type of polymers and polymer related systems The two main types of polymers are synthetic polymers such as hydrolyzed polyacrylamide (HPAM) and biopolymers such as xan than gum. Less commonly used are natural polymers and their derivatives, such as guar gum ,sodium carboxymethyl cellulose, and hydroxyl ethyl cellulose (HEC). Table6 summarizes the characteristics of different polymer structures.
69
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Table 6 Polymer Structures And Their Characteristics.[16]
properties: o o o o
No –O– in the backbone (carbon chain) for thermal stability Negative ionic hydrophilic group to reduce adsorption on rock surfaces Good viscosifying powder Nonionic hydrophilic group for chemical stability
Based on these criteria, HPAM is a good polymer.
70
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1) Hydrolyzed Polyacrylamide The most widely used polymer in EOR applications is HPAM (Manriqueet al.2007). For either a given polymer concentration or viscosity level, HPAM solutions have provided significantly greater oil recovery under Daqing conditions. The reason is that HPAM solutions exhibit significantly greater viscoelasticity than xanthan solutions (Wang et al., 2006a). Polyacrylamide adsorbs strongly on mineral surfaces. Thus, the polymer is partially hydrolyzed to reduce adsorption by reacting polyacrylamide with a base, such as sodium or potassium hydroxide or sodium carbonate. Hydrolysis converts some of the amide groups (CONH2) to carboxyl groups (COO−), as shown in the following structure:
2) Xanthan Gum Another widely used polymer, a biopolymer, is xanthan gum (corn sugar gum),or xanthan for short. The structure of a xanthan biopolymer is shown in the following figure. The polymer acts like a semirigid rod and is quite resistant to mechanical degradation. Average reported molecular weights of xanthan biopolymerused in EOR processes range from 1 million to 15 million. Xanthanbiopolymers are supplied as a dry powder or as a concentrated broth (Greenand Willhite, 1998). Generally, polyacrylamide copolymers are much more viscous than polysaccharide biopolymer at equivalent concentrations in freshwater, but these copolymers are much more sensitive to saline water than thebiopolymers. The viscosity of copolymers is lower than that of biopolymers in the saline water (10,000 ppm TDS). Some permanent shear loss of viscosity could occur for polyacrylamide, but not for polysaccharide at the wellbore .However, the residual permeability reduction factor of polysaccharide polymersis low (Luo et al., 2006). In EOR processes, HPAM is much more widelyused. Other potential EOR biopolymers are scleroglucan, simusan, AGBP, and so on (Luo et al., 2006).
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3) Salinity-Tolerant Polyacrylamide—KYPAM KYPAM is the commercial name of a new Chinese product; its meaning in English is salinity-tolerant polyacrylamide, and its English translation is combshapepolyacrylamide. There are several sample products of this type in the laboratory. RSP1 is used mainly in treating drilling fluids; RSP2 is used main lyin EOR; and RSP3 is used mainly in water shut-off or profile control. The commercial product RSP2, which is known as KYPAM in EOR, is produced by Beijing Hengju (Luo et al., 2002). This new copolymer incorporates a small fraction of functional monomers with acrylamide to form comb-like
copolymers. The structure of a functional monomer, aromatic hydrocarbon with ethylene(AHPE), is
and the structure of KYPAM is
4) Hydrophobically Associating Polymer The polymer is hydrophobically associating water soluble, meaning it contains one or more water-soluble monomers (acrylamides) and a small fraction (0.5to 4%) of water-insoluble (hydrophobic) monomers. A typical hydrophobically associating polymer (HAP) structure is
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5) 2-Acrylamide-2-Methyl Propane-Sulfonate Copolymer The structure of the AM and Na-AMPS copolymer is
AMPS, or 2-Acrylamide-2-Methyl Propane-Sulfonate, has water-soluble anionic sulfonate, shielding acrylamide, and unsaturated double bond. Sulfonate makes it have good ionic exchange capability, electric conductivity, andgood resistance to divalence and salinity in general. Acrylamide gives it good thermal stability and good resistance to hydrolysis, acid, and alkaline. Plus, the double bond leads to easy synthesis and polymerization. The rigid side chains, large chains, or chains of ring structure also give it good thermal stability. AMPS are combined with other monomers to produce copolymers that are used in many industries (Lu and Chen, 1996). In the oil industry, the main application is in drilling (Hou et al., 2003). And other types like: Movable Gels,pH-Sensitive Polymers ,Bright Water , Micro ball ,Inverse Polymer Emulsion and Preformed Particle Gel. Polymer flood field performance
Figure 32 Polymer Flood Field Performance .[17] 73
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2.3.2.2 Surfactant Flooding Types of Surfactants The term surfactant is a blend of surface acting agents. Surfactants are usually organic compounds that are amphiphilic, meaning they are composed of a hydrocarbon chain (hydrophobic group, the ―tail‖) and a polar hydrophilic group (the ―head‖). Therefore, they are soluble in both organic solvents and water. They adsorb on or concentrate at a surface or fluid/fluid interface to alterthe surface properties significantly; in particular, they reduce surface tensionor interfacial tension (IFT). Surfactants may be classified according to the ionic nature of the head group as anionic, cationic, nonionic, and zwitter ionic (Ottewill, 1984). Anionic surfactants are most widely used in chemical EOR processes because they exhibit relatively low adsorption on sandstone rocks whose surface charge is negative. Nonionic surfactants primarily serve as co-surfactants to improve system phase behavior. Although they are more tolerant of high salinity, their function to reduce IFT is not as good as anionic surfactants. Quite often, a mixture of anionic and nonionic is used to increase the tolerance to salinity. Cationic surfactants can strongly adsorb in sandstone rocks; therefore, they are generally not used in sandstone reservoirs, but they can be used in carbonate rocks to change wettability from oilwet to water-wet. Zwitterionic surfactants contain two active groups. The types of zwitterionic surfactants can be non ionic-anionic ,nonionic-cationic, or anioniccationic. Such surfactants are temperature-and salinity-tolerant, but they are expensive. A term amphoteric is also used elsewhere for such surfactants (Lake, 1989). Sometimes surfactants are grouped into low-molecular and high-molecular according to their weight. Within any class, there is a huge variety of possible surfactants. For more surfactants used in oil recovery, see Akstinat (1981). For more details on the effect of structure on surfactant properties, see Graciaa et al. (1982) and Barakatet al. (1983). Surfactant flood field performance
Figure 33 Surfactant Flood Field Performance .[17]
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2.3 .2.3 Alkaline Flooding The alkaline flooding method relies on a chemical reaction between chemicals such as sodium carbonate and sodium hydroxide (most common alkali agents)and organic acids (saponifiable components) in crude oil to produce in situ surfactants (soaps) that can lower interfacial tension. Another very important mechanism is emulsification. The addition of the alkali increases pH and lowers the surfactant adsorption so that very low surfactant concentrations can be used to reduce cost.
Comparison of alkalis used in alkaline flooding 1) General Comparison and pH Alkaline flooding is also called caustic flooding. Alkalis used for in situ formation of surfactants include sodium hydroxide, sodium carbonate, sodium orthosilicate, sodium tri-polyphosphate, sodium metaborate, ammonium hydroxide, and ammonium carbonate. In the past, the first two were used most often. However, owing to the emulsion and scaling problems observed in Chinese field applications, the tendency now is not to use sodium hydroxide. The dissociation of an alkali results in high pH. For example, NaOH dissociates to yield OH:-
Sodium carbonate dissociates as:
followed by the hydrolysis reaction:
The dissociation of sodium silicate is complex and cannot be described by a single reaction equation. The pH values of several commonly used alkaline agents are presented in Figure 10.1. Of course, the pH of the solutions varies with salt content. For instance, the pH of caustic solutions decreases from 13.2to 12.5 when the salinity increases from 0 to 1% NaCl. By comparison, the pH of sodium carbonate solutions is less dependent on salinity (Labrid, 1991). In terms of effectiveness to reduce interfacial tension (IFT), it has been observed that there is little difference among the commonly used alkalis (Campbell,1982; Burk, 1987).
75
Chapter 2
Figure 34 pH Values Of Alkaline Solutions .[16]
Figure 34 shows a comparison of some of the properties of several common alkalis. Potassium-based alkalis, the price of which is higher than sodium-based alkalis, are not included. They are considered when clay swelling and injectivity problems are expected. Some alkalis are further discussed and compared in the following sections.
2) Polyphosphate Chang (1976) showed that use of a polyphosphate, which is a buffer, improved recovery. Sodium tri-polyphosphate (STPP) was used in laboratory tests for Cretaceous Upper Edwards reservoir (Central Texas). STPP was proposed to minimize divalent precipitation, for wettability alteration and emulsification(Olsen et al., 1990). Generally, it is not used as a primary alkali to generate soap for purposes of IFT reduction. Instead, it is used together with other alkalis such as sodium carbonate when divalent could be a problem (Harry Chang , Chemor Tech International, Plano, Texas, personal communication on June 16,2009). 76
Chapter 2
Silicate versus Carbonate Campbell (1981) compared sodium or thosilicate and sodium hydroxide in recovering residual oil. The test results showed that the former was more effective than the latter under the conditions studied, both for continuous flood in gand 0.5 PV slug. The mechanisms through which sodium or thosilicate produced higher recovery than sodium hydroxide in those tests were not concluded. Reduction in interfacial tension is similar for both chemicals. Other factors must play a more important role .Radke and Somerton (1978) investigated the use of a sodium meta silicate(Na2SiO3) buffer in core floods. A meta silicate buffer at a pH of 11.2 showed break through at 2.5 PV injection, whereas sodium hydroxide of the same pH did not appear until a 12 PV injection (Mayer et al., 1983). This result means that sodium meta silicate reaction with rock is much weaker than sodium hydroxide. Chang and Wasan (1980) indicated that there were differences in coalescence behavior and emulsion stability that favor sodium or thosilicate over sodium hydroxide .Silicate precipitates, however, are generally hydrated, flocculent, and highly plugging even at low concentrations. Carbonate precipitates are relatively granularand less adhering on solid surfaces (Cheng, 1986). Thus, under equivalent experimental conditions of porosity and flow rate, sodium carbonate shows less degree of permeability damage in the presence of hard water . Table 7 Properties Of Several Common Alkalis .[16]
77
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Alkaline flood field performance
Figure 35 Alkaline Flood Field Performance. [17]
And other types of chemical methods like Surfactant-Polymer Flooding, AlkalinePolymer Flooding, Alkaline-Surfactant Flooding, and Alkaline-SurfactantPolymer Flooding.
How to plan a flood a) Choose a process likely to succeed in a candidate reservoir b) Determine the reasons for success or failure of past projects of the process c) Research to ―fill in the blanks‖ i. Determine process mechanisms ii. Derive necessary scaling criteria iii. Carry out lab studies d) Field based research e) Establish chemical supply f) Financial incentives essential
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Chapter 2
Process evaluation a) b) c) d) e) f) g)
Compare field results with lab (numerical) predictions Relative permeability changes? Oil bank formation? If so, what size? Mobility control? Fluid injectivity? Extent of areal and vertical sweep? Oil saturations from post-flood cores?
The case for chemical flooding a) Escalating energy demand, declining reserves b) Two trillion bbl oil remaining, mostly in depleted reservoirs or those nearing depletion c) Infill drilling often meets the well spacing required d) Fewer candidate reservoirs for CO2 and miscible e) Opportunities exist under current economic conditions f) Improved technical knowledge, better risk assessment and implementation techniques
Conclusions: a) Valuable insight has been gained through chemical floods in the past – failures as well as successes b) Chemical flooding processes must be re-evaluated under the current technical and economic conditions c) Chemical floods offer the only chance of commercial success in many depleted and water flooded reservoirs d) Chemical flooding is here to stay because it holds the key to maximizing the reserves in our known reservoirs
79
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2.4 Reservoir Simulation Reservoir simulation is the technique that applies mathematical modeling to the analysis of reservoir performance. It generally uses the finite difference method to solve the partial differential equations that govern the flow behavior of all fluid phases in the porous medium (reservoir). Generally the outputs from the simulator are the reserves estimate, the depletion, the production forecast, and the field development strategy that optimize the recovery factor. The reservoir simulation process encompasses five fundamentals phases: 1. Data collection 2. Model grid design 3. Sensitivity tests 4. History matching 5. Performance prediction
Reserves determination carries a lot of uncertainty even when calculated by the most skilled estimators and the most sophisticated means.
80
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2.4.1 MBAL [22] Efficient reservoir development requires a good understanding of reservoir and production systems. MBAL helps the engineer better define reservoir drive mechanisms and hydrocarbon volumes. This is a prerequisite for reliable simulation studies. MBAL is commonly used for modeling the dynamic reservoir effects prior to building a numerical simulator model. MBAL contains the classical reservoir engineering tool and has redefined the use of Material Balance in modern reservoir engineering. For existing reservoirs, MBAL provides extensive matching facilities. Realistic production profiles can be run for reservoirs with or without history matching. MBAL is an intuitive program with a logical structure that enables the reservoir engineer to develop reliable reservoir models quickly. Reservoir Engineering Tool Material
Balance Monte Carlo Simulator Decline Curve Analysis 1D model Multi-Layer Tight Gas Material Balance This incorporates the classical use of Material Balance calculations for history matching through graphical methods (like Havlena-Odeh, Campbell, Cole etc.). Detailed PVT models can be constructed (both black oil and compositional) for oils, gases and condensates. Furthermore, predictions can be made with or without well models and using relative permeabilities to predict the amount of associated phase productions. Multi
Tank Variable PVT with Depth Determine Components of Reservoir Energy Visualize the Parameters that Impact Performance
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Forecast Well and Reservoir Performance Forecast
Using Rate Schedule or Well and manifold pressure
schedule Set well and global constraints: At well and field level Determine when wells will water out Forecast pressure decline, producing GOR The long term effects of completion decisions on compression, gas/water injection, gas recycling PVT Black
oil Fully Compositional Compositional Tracking
82
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2.4.2 Monte Carlo Simulation The probabilistic method is less commonly used than the deterministic method because it is not accepted by many governments for reserves estimation. However, many companies use the probabilistic methods to evaluate potential reserves when the uncertainty is very high, especially in the early stage of field development and areas where new technology is applied. There are several different probabilistic methods used to estimate reserves such as the scenario approach, the decision tree, and the Monte Carlo method. Due to huge improvements in computer technology, the Monte Carlo method became easier to use with no expensive commercial software. Monte Carlo simulation, named for the famous gambling capital of Monaco [18] , is a very potent methodology. For the practitioner, simulation opens the door for solving difficult and complex but practical problems with great ease. Perhaps the most famous early use of Monte Carlo simulation was by the Nobel physicist Enrico Fermi (sometimes referred to as the father of the atomic bomb) in 1930, when he used a random method to calculate the properties of the newly discovered neutron. Monte Carlo methods were central to the simulations required for the Manhattan Project, where in the 1950s Monte Carlo simulation was used at Los Alamos for early work relating to the development of the hydrogen bomb, and became popularized in the fields of physics and operations research [19]. By the early 1970‘s petroleum engineers were beginning to use this technique to model reserve estimates[20]. The Monte Carlo method depends on making a probability distribution function for each input parameter, this PDF is used to get all the possible variations of this parameters. This leads to the calculation of multiple values for the IOIP along with their probability of occurrence. A plot between the IOIP and the frequency can then be used to determine the proved reserves (P90), proved plus probable reserves (P50) , and proved plus probable plus possible reserves (P10). This method is used when the data is very limited, when production and pressure history are not available and we cannot confirm the IOIP value. Also, this technique is used in risk analysis. This can be done by many computer software such as EXCEL and MBAL. 83
Chapter 2
2.4.3 ECLIPSE Simulation[21] ECLIPSE from the most advanced software in reservoir engineering, Its developed by many great companies in Petroleum Engineering e.g.(Schumberger) ECLIPSE software based on Governing Physic (Darcy‘s Law (without gravity term)& Mass Balance Equation) Darcy‘s Law (without gravity term)
q
k
P
Mass Balance Equation
The ECLIPSE simulator consists of two separate simulators: ECLIPSE 100 specializing in black oil modeling, and ECLIPSE 300 specializing in compositional modeling. ECLIPSE 100 (Black oil Simulation) With fully implicit, three-phase, 3D simulations, ECLIPSE Black oil reservoir simulation software models extensive well controls and supports efficient field operations planning, including water and miscible-solvent gas injection. The black oil model assumes that the reservoir fluids consist of three phases—oil, water, and gas, with gas dissolving in oil and oil vaporizing in gas.
84
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The Benefits of using Simulator:• Accurate determination of reserves. • Prediction of production performance. • Determination of number of wells needed. • Determination of the best well pattern. • Determination of the best perforation interval. • Determination of the best completion size. • Assessment of the early gas or water breakthrough and investigate how to minimize it. • Determination of the best injection rates and the best time for injection. • Confirm understanding of reservoir flow barriers to assess whether undrained regions exist. • Estimate the optimum time for a new phases.
Reservoir Simulation Basics • The reservoir is divided into a number of cells • Basic data is provided for each cell • Wells are positioned within the cells • The required well production rates are specified as a function of time • The equations are solved to give the pressure and saturations for each block as well as the production of each phase from each well
85
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Required data to enabling use Simulator – Reservoir structure
– Rock/fluid functions
Depth Faults – Gross thickness
PVT analysis
– Lithology
Rock compressibility
– NTG
Capillary pressure
– Porosity
Relative permeability
– Permeability
Special core analysis
– Pressure RFT and well test data
– Fluids contacts – Initial saturation
– Production data Well data
surveys,
completion
Historical production pressure data
86
and
Chapter 2
2.5 Comparison Between Reserve Estimation Methods[23] Table 8 shows when each method is best used Table 8 Reserve Estimation Methods Comparison .[23]
Method Volumetric
Best used when • you don‘t have production trends • you have a good estimate of recovery factor • a representative reservoir model exists
DCA and MBAL
• reliable production trends exist • history of reservoir pressure available • detailed reservoir model/data is not available • reliable production trends exist • you have an accurate reservoir model • you have complete & accurate reservoir properties
Simulation
• you have no other choice • geographic location, formation characteristics, etc. render analogy appropriate
Analogy
87
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Table 9 shows the data needed, the advantages, the disadvantages, and the results of using different estimation methods. Table 9 Summary Of Reserve Estimation Methods.[23]
88
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CHAPTER 3 3 Methodology 3.1 Available Data Isopach Contour Map for NetPay Zone
Figure 36 Isopach Contour Map For Net Pay Zone OF Marine Zone 2 .
89
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Belayim Marine Field(Zone 2) Case Study Reservoir Data Table 10 Belayim Marine Field (Zone 2) Data.
Initial Reservoir Pressure (psi) Reservoir Temperature (oF) Water Salinity (PPM) API Saturation Pressure (psi) Porosity Permeability (md) rw (m) Connate water saturation Water viscosity (cp) Cf (psi-1) Initial Formation Volume Factor
3558 205 150000 21 1050 0.2 500 2460 0.3098 0.5 3.75*10-6 1.1563
Reservoir History
This reservoir belongs to Belayim Petroleum Company PETROPEL) in Belayim Field zone ΙΙ. The production started on October 1963 from zone II , In May 1973 all the wells were shut off and the reservoir has produced 4595000.00stb of oil. In Jan/1978 all the wells were put on stream The water injection was started at Jan/1985, then a program of water injection has started to compensate the sharp decrease in the reservoir pressure. In October 2007 the reservoir has produced 6.42E+07 stb of oil with Production rate =932.5 bbl/day
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Table 11 Belayim Marine Field (Zone 2) Pvt Data .
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3.2 Methodology
1
• Calculation MBE (Excel)
2
• Prediction (Excel)
3
• Montecarlo Simulation
4
• Reservoir Management Spread Sheet
5
• MBAL
6
• Eclipse
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3.2.1.1 The Material Balance Equation The material balance equation (MBE) has long been recognized as one of the basic tools of reservoir engineers for interpreting and predicting reservoir performance. The MBE, when properly applied, can be used to: 1- Estimate initial hydrocarbon volumes in place 2- Predict future reservoir performance 3- Predict ultimate hydrocarbon recovery under various types of primary driving mechanisms The equation is structured to simply keep inventory of all materials entering, leaving, and accumulating in the reservoir. In its simplest form, the equation can be written on volumetric basis as: Initial volume = volume remaining + volume removed Since oil, gas, and water are present in petroleum reservoirs, the material balance equation can be expressed for the total fluids or for any one of the fluids present. Before deriving the material balance, it is convenient to denote certain terms by symbols for brevity. The symbols used conform where possible to the standard nomenclature adopted by the Society of Petroleum Engineers.
Reservoir type:- This reservoir is oil reservoir According to production history There‘s no gas cap in the reservoir GP : produced during production from tubing Also that‘s small value
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The saturation of reservoir according to PVT data:From reservoir pressure records and PVT data Pb= 1050 Psi And the current reservoir pressure =1390 Psi This reservoir is under saturated reservoir
Type of under saturated reservoir From MBE The driving mechanism in this case depends on Cw: that‘s water compressibility from (correlation) CF: formation compressibility from (chart) Assume that this reservoir is without bottom water drive
Figure 37 Reservoir MBE .
94
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From 1, 2
95
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1-Co : That’s Oil Compressibility
Table 12 Calculate Oil Compressibility.
2-CF: Formation Compressibility From (Chart Between Porosity Vs Cf )[5] Cf=0.0000037
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3- Solubility Of Oil From (Data) So= 0.6962 Solubility of water from (Data) Sw=0.3038 4- Cw: That’s Water Compressibility From (Correlation) Table 13 Calculate Water Compressibility .
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5- Ce: Effective Compressibility Table 14 Calculate Effective Compressibility.
6- From History Data Get Table 15 Calculate Wi ,Wp,βw .
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7- Final Equation Will Be Applied.
Table 16 Calculate (Eo)&(F-Wi βw).
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10E6
N 40 35 30
F-wiBw
25 20
N
15 10 5 0 -5
0
0.01
0.02
0.03
Eo Figure 38 Chart Calculate N.
From this chart (N) is not constant So This reservoir is with bottom water drive
100
0.04
0.05
CHAPTER 3
3.2.1.2 Water Influx 3.2.1.2 .1Steady state Water Influx (SS) In this type of influx , the rate of water influx ,
is directly
proportional to , where the pressure (P) , is measured at the original oil-water contact . This type assumes that the pressure at the external boundary of the aquifer is maintained at the initial value (Pi) , and that flow to the reservoir is , by Darcy’s Law , proportional to the pressure differential , assuming the water viscosity ,average permeability ,and aquifer geometry remain constant.
Figure 39 Plot Of Pressure And Pressure Drop Versus Time. [15]
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Where o k’ is the water influx constant in barrels per day per pounds per square inch . o (Pi-P) is the boundary pressure drop in pounds per square inch.
From MBE Equation:
Since We cant be determined due to inability to calculate N , by differentiation previous equation with time:
If the reservoir is under steady state water influx condition , then k’ must be constant.
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How to Calculate k’? y using the Microsoft excel software , K can be easily determined by following the following steps : 1. A table is made with Date , Pressure , Δ P , Np , Wp , Wi , Δ NP , ΔWP , ΔWi , βo and βw values as shown in table:
Table 17 Marine zone II Data
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2. By substituting the equation’s parameters , k’ can be easily calculated as follow : Table 18 Calculated k' values
Since k‘ values aren‘t constant , then the reservoir isn‘t under steady state conditions and other states has to be tested.
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3.2.1.2 .2 Semi-Steady State For Water Influx (SSS) In the semi-steady state, ∆P remains constant but there's a change in the initial pressure (Pi) with time that depends on time interval.
Pi1 i
Pi2 i Pw1 www Pi3 3i
Pw2
Pw3
Figure 40 Semi Steady State Behavior .
re : increases with time
Characteristics : -has strong We (water Influx). -Has external boundary. -Initial Pressure declines with time. -(re) increases with time.
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For number of periods of time: Log(a) . ∑Ki + Log(ti) . ∑Ki = n.C
(1)
By Multiplying time (t) in each period of time: t . K.Log (a) + t . K.Log (t) = t.C
Total: Log(a) . ∑ti.Ki + Log(t) . ∑ti.Ki = C.∑ti (2)
Where: a : constant. C: a constant refers to the reservoir‘s characteristics. t : time in days. n : number of periods of time included in the calculations.
From equations (1) & (2) the values of " a & c "can be determined as Shown Below :-
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Using This Table we determine the parameters of the equations (1) and (2) using the Microsoft excel software :Table 19 Determining Semi Steady State Equations’ Parameters
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By using this Table : Table 20 Comparing Values Of (Δwe SSS)/ΔT And (Δwe MBE)/ΔT.
It is found that
Then this reservoir doesn‘t follow the semi steady state behavior.
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3.2.1.2 .3 Unsteady state (USS) Unsteady state models for both edge water and bottom water drives are presented. An edge water drive is defined as water influxing the reservoir from its flanks with negligible flow in the vertical direction . in contrast , a bottom water drive has significant vertical flow. The van Everdingen and Hurst Edge-Water Drive Model: Consider a circular reservoir of radius Rw , as shown , in a horizontal circular aquifer of radius Re which is uniform in thickness , permeability and porosity and in rock and water compressibilities. The radial diffusivity equation expresses the relation ship between pressure , radius and time for a radial system as shown in fig . where the driving potential of the system is the water expandibility and the rock compressibility. Re
Rw
Figure 41 Un Steady State Behavior
The diffusivity equation is applied to the aquifer where the inner boundary is defined as the interface between the reservoir and the aquifer With the interface as the inner boundary , it would be more useful to require he pressure at the inner boundary o remain constant and observe
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the flow rate as it crosses he boundary or as it enters the reservoir from the auifer. Mathmaically , this condistion is stated as P = constant = Pi – ΔP at R=Rw Where Rw is constant and is equal to the outer radius of the reservoir (the original oil-watter contact). The pressure P must be determined at this original oil-water conact . van Everdingen and Hurst solved the diffusivity equation for his condition , which is referred to as the constan terminal pressure case , and the following initial and outter boundary conditions: Initial condition: P= Pi for all values of R Outer boundary condition: For an infinite aquifer : P = Pi at R = For a finite aquifer:
= 0 at R =Re
At this point , the diffusivity equation is rewritten in terms of the following dimensionless parameters: Dimensionless Time : Dimensionless Radius : Dimensionless Pressure : With these dimensionless parameters , the diffusivity equation becomes:
Van Everdingen and Hurst converted their solutions to dimensionless cummulative water influx values and made he results available in a
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convenient form given in tables for various ratios of aquifer to reservoir size by he ration of their radii
.
The data are given in terms of dimensionless time tD , and dimensionless water influx Qt so that one set of values suffices for all aquifers whose behavior can be represented by the radial form of the diffusivity equation The water influx is then found by using this equation :
Where B‘ is the water influx constant in barrels per pounds per square inch. Each radii ratio is tested and plotted to determine the type of the aquifer as follows: Table 21 Td vs pressure and Ce.
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Table 22 Calculation of ∑Qt.∆P/Eo at re/rw = 2 and 4.
re/rw=4 Millions
7
6
7
6
5
5
4
4
3 re/rw=2 Linear (re/rw=2) 2
1
3
re/rw=4
2
Linear (re/rw=4)
1
0
0 0
-1
[F-(Wi*Bw)]/Eo
[F-(Wi*Bw)]/Eo
Millions
re/rw=2
50
100 Thousands
0
0.2
0.4 0.6 Millions
-1
∑Qt*∆P/Eo
∑Qt*∆P/Eo
Figure 42 Plotting ∑Qt.∆P/Eo Vs (FWi*Βw)/EO At Re/Rw =2.
Figure 43 Plotting ∑Qt.∆P/Eo vs (FWi*βw)/EO at re/rw =4.
113
CHAPTER 3
Table 23 Calculation Of ∑Qt.∆P/Eo At Re/Rw = 6 And 8.
Millions
(F-Wi*βw)/EOMillions
re/rw=6 500 450 400 350 300 250 200 150 100 50 0
500 450 400 350 300 250
re/rw=8
200 re/rw=6
150 100 50
0
0.5
1
0
∑Qt.∆P/EoMillions
0
Figure 45 Plotting ∑Qt.∆P/Eo vs (F-Wi*βw)/EO at re/rw =6.
0.5
1
1.5 2 Millions
Figure 44 Plotting ∑Qt.∆P/Eo vs (F-Wi*βw)/EO at re/rw =8. 114
CHAPTER 3
From the results , the reservoir is clearly not under finite outer boundary conditions so , infinite outer boundary calculations are applied as follows Table 24 Calculating ∑Qt.∆P/Eo At Re/Rw = Infinity.
The result shows that the outer boundary is infinite.
Millions
(F-Wi.Bw)/Eo
re/rw=infinty 300 250 200 150 re/rw=infinty
100
Linear (re/rw=infinty)
50 0 0
10
20
30
40 Millions
∑Qt.∆P/Eo
Figure 46 ∑Qt.∆P/Eo At Re/Rw = Infinity.
115
CHAPTER 3
3.2.1.3 Prediction 1) Assume 3 pressures : 1400 ,1410 , 1420 Table 25 Prediction Table
2) From Reservoir Management Spread sheet , Interpolating Cw, Co, Ce, Cf, βo, βw with actual data Table 26 3 Pressures Assumption
Table 27 Cw,Co,Ce, βo, βw for P.=1400
116
CHAPTER 3
Table 28 Cw,Co,Ce, βo, βw for P.=1410
Table 29 Cw,Co,Ce, βo, βw for P.=1420
3) Put the data in the prediction table :
where C = Cf + Cw Table 30 Input Cw,Co,Ce, βo, βw for the 3 P.
117
CHAPTER 3
4) Calculate ∆P : Table 31Calculate Delta P
5) Then Calculate Td : Table 32 Calculate TD
118
CHAPTER 3
6) Calculate (QT) From Unsteady State (re/rw >10) :By using
Interpolation: Table 33 Calculate TD at re/rw >10 [5]
Table 34 Calculate (QT)
7) Then Calculate ∑Qt.∆P :
119
CHAPTER 3
Table 35 Calculate ∑Qt.∆P
Then put the final result
Table 36 Input QT ,∑Qt.∆P.
120
CHAPTER 3
8) Calculate We uss
Table 37 Calculate We uss
9) Calculate NP :
Enter Wp Values : Table 38 Input Wp ,NP
10)
Calculate Wi :
―Assume this const. Until We USS curve intercepts with We MBE curve‖ ―
‖ 121
CHAPTER 3
First assume it = 1 Table 39 Calculate Wi
11) Calculate NP*βo ,WP*βw, WI*βw ,∆P( ) Table 40 Calculate NP*βo ,WP*βw, WI*βw ,∆P
12) Calculate : N*βoi*Ce*∆P Table 41 Calculate N*βoi*Ce*∆P
122
CHAPTER 3
13) Calculate We MBE :
Table 42 Calculate We MBE
14) Draw a Chart Between P with ( WE MBE& WE USS) :
Figure 47 Chart between P with ( wepe& we uss))
15) Change the value of the const. Until We uss intercepts with We mbe Const. Should be less than 2.5 At const. = 1.2992 the 2 curves are intercepted
123
Millions
CHAPTER 3 3.93 3.92 3.91 3.9 We uss
3.89
me
3.88 3.87 3.86 1395
1400
1405
1410 P
1415
1420
1425
Millions
Figure 48 Chart Between P With ( Wepe& We Uss)By Using Mew Wi. 3.93 3.92 3.91 3.9 uss 3.89
mbe
3.88 3.87 3.86 1395 1400 1405 1410 1415 1420 1425
Figure 49 Predicted p .
16) Get the P. at the intercept P. = 1416 17) Repeat these steps for every 2 years until : NP/Wi = 2.5 Then the prediction stops .
124
CHAPTER 3
3.2.2 Reservoir Management Spread sheet It‘s an Excel sheet depends on mathematical calculation by using Microsoft Macros to calculate reservoir engineering purpose. The benefits of using Reservoir Management Spread sheet
Interpolate the PVT data to match data with reservoir pressure. Draw Production History Matching Curve. Reservoir Production Prediction. Comparing the production will be with changing water viscosity by (Polymer Flooding).
The Required Data
Start of Production date . Initial pressure . Reservoir Area and hight. Number and names of wells , wells types (production or injection), wells location and initial flow rate per day PVT data from lab or by correlations at different pressures. Reservoir pressure for each well along production history. Injection water viscosity.
Steps:1- Insert wells information.
Insert initial pressure and starting of production date Insert well name, Type and initial flow rate in bbl/day
Figure 50 Reservoir Management Spread Sheet Wells Input.
125
CHAPTER 3 2-
Press (Pressure Matcher) to insert wells pressures along production history.
Figure 51Reservoir Management Spread Sheet Pressure Input.
3- Press (MATCH) to history matching the pressure with time.
Figure 52 Pressure Matching
4- From Fig.53 press (PVT LAB MATCHER) to insert pvt lab data and start to match the data with different reservoir pressure.
Figure 53 Reservoir Management Spread Sheet PVT Input .
126
CHAPTER 3
5- Press (GO TO LAB) to start matching the PVT data with wells pressure.
Figure 54 Reservoir management spread sheet PVT Matching .
6- From Fig. 55 press (PREDICTION) , Insert (Wells locations, Reservoir area, Height , Initial injection water viscosity and injection water with polymers viscosity) then press (Predict).
Figure 55 Reservoir Management Spread Sheet Well Locations.
127
CHAPTER 3
7- The following fig shows the prediction of the production of the reservoir.
Figure 56 Reservoir Management Spread Sheet Prediction
8- The following fig showing prediction of reservoir production behavior at initial injection water viscosity and changing in water viscosity.
Figure 57 Reservoir Management Spread Sheet Prediction by chemical effect
128
CHAPTER 3
3.2.3MBAL [24] 3.2.3.1 Montecarlo Simulation Tool [24] : The tool enable the user to perform statistical evaluation of reservoir .distribution can be assigned to variable like porosity or thickness of reservoir and the program will generate the range of probability associated with reserve range. Decline Curve Analysis : Production data can be fitted to Hyperbolic , exponential or Hermic decline . these is can be the extrapolation in future for generation forecasts. Software steps: 1-Choose Mote Carlo Tool From Tool Manu As Shown:
Figure 58 Choosing Monte Carlo Tool.
129
CHAPTER 3
2- Defining the general option :
Figure 59 System Option Window
3- enter the PVT fluid properties data form PVT menu :
Figure 60 PVT Menu
4- then enter the data required in the new window as shown :
Figure 61 Data Input 130
CHAPTER 3
5-Match PVT data :
Figure 62 Match PVT data
6- Then choose Distribution from Input menu:
Figure 63 Selecting Distributions.
131
CHAPTER 3
7- Entre the required data in the window where the bulk volume is calculated from reservoir geology information :
Figure 64 Distributions.
8- Then press ― Calc ― , to watch the results .
132
CHAPTER 3
3.2.3.2 MBE Tool [24] :
Data loading History matching Prediction Field development planning using MBE will be applied using MBAL software, the workflow can be divided into:
1. Data loading: This step is the initial step of the development process. In this stage, the available data of the reservoir is loaded into the software, and the general options of the model are determined. These data include: i. Fluid properties ii. PVT properties iii. Estimation of the IOIP from the results of Eclipse simulation results. iv. Production start date. v. Petro-physical data vi. Relative permeability data. vii. Historical data (production and pressure) After loading the data, matching process should be applied for the fluid properties and PVT data as discussed earlier in the volumetric method. The main output of this step is the relative permeability plot and the cumulative oil production and pressure plot.
133
CHAPTER 3
2. History matching: History matching process involves matching the historical data with the data predicted by the model. 3. Model validation: Before using the model for any future prediction, the model‘s ability to predict the past performance in agreement with the input data must be checked. In order to check the model, the model is run on prediction from the start till the end data of the input data. A plot of the cumulative production and historical pressure can be constructed to compare the input data with the prediction data, if the values match; then the model is ready for the prediction process. 4. Prediction: After making sure that the model is valid for prediction, we have to define the target and constraints for the prediction and then check the reservoir behavior under different scenarios.
Software step: 1. Data loading Defining model general options
Figure 65 General Option Widow.
134
CHAPTER 3
Fluid properties From PVT list , choosing fluid properties
Figure 66 PVT list .
Then data would be entered
Figure 67 Black Oil ( Data Input).
135
CHAPTER 3
Then match the data by using Match button and input the data in the table
Figure 68 PVT Matching.
Then click Match and choose data which will match on such as (Bubble point , Gas oil ratio , Oil FVF and Oil Viscosity ) as shown and press Calc button
Figure 69 Matching.
136
CHAPTER 3
Then click Plot button to plot the matched data graphs as shown in the figure :
1-Oil FVF
Figure 70 Oil FVF Curve.
2-oil viscosity
Figure 71 Oil Viscosity Curve.
137
CHAPTER 3
3- Gas Oil Ratio
Figure 72 GOR Curve.
Reservoir parameters The next step is to define the tank (reservoir parameters which include the estimation of the IOIP , average petro-physical data (porosity, water saturation), the relative permeability data, and production history. Figure 73 shows the determination of tank parameters From Input choose Tank Data
Figure 73 Input List.
138
CHAPTER 3
1-Input tank parameters as shown :
Figure 74 Tank Parameters.
2-the water influx of the aquifer was defined using Van EverdingenHurst model discussed earlier in the literature review section as shown:
Figure 75 Water Influx.
139
CHAPTER 3
3-Then enter the rock compressibility by correlation as shown
Figure 76 Rock Compressibility.
4-Enter the rock compaction reversible as shown :
Figure 77 Rock Compaction. 140
CHAPTER 3
5- Relative permeability from tables
Figure 78 Relative Permeability.
The plots of permeability
Figure 79 Relative Permeability Curves.
141
CHAPTER 3
6- production History
Figure 80 History Matching Table.
input the production history by using Import will appear
Figure 81 Import Window.
142
a new window
CHAPTER 3
Choose ―Browse‖ and identify the file location then choose " done " in the new window choose ― Tab Delimited ― then choose "done "
Figure 82 Import Setup.
choose data shown with given field names
Figure 83 Import file. 143
CHAPTER 3
2- History matching Click on the History Matching button then choose Run Simulation to run the simulation
Figure 84 History Matching List.
In the new window click Clac button
\
Figure 85 Run History Matching.
144
to start calculation
CHAPTER 3
Then choose : 1- Analytical method :
Figure 86 Analytical Method.
2-Graphical method :
Figure 87 Graphical method. 145
CHAPTER 3
3- energy plot :
Figure 88 Energy Plot.
4-WD function plot :
Figure 89 WD Function Plot.
146
CHAPTER 3
4-prediction : The main objective of this study is the identification and evaluation of the remaining potential in existing producing zones.
Prediction steps : 1-choose production prediction from prediction set up :
Figure 90 Production Prediction List.
2-entire the data required as shown
Figure 91 Prediction Calculation Setup. 147
CHAPTER 3
3- then choose prediction and constrains and enter the required data
Figure 92 Tank Prediction Data.
4-Then run the simulation and click Calc
Figure 93 Run Simulation Window. 148
CHAPTER 3
3.2.4 ECLIPSE [21] As shown in the literature review before the importance of using software or especially simulators, Here starts to know the steps of using the Reservoir Simulation (ECLIPSE).
ECLIPSE Data File Its consist of eight sections each section specialized in a specific data to input in it as shown:
Figure 94 Data File Section.
Start the Data Input Open New Text pad file and start input data sections
1- RUNSPEC The RUNSPEC section is the first section of an ECLIPSE data input file. It contains the run title, start date, units, various problem dimensions (numbers of blocks, wells, tables etc.), The RUNSPEC section must always be present. 149
CHAPTER 3
The used data code :( TITLE, START, DIMENS, OIL, GAS, WATER, DISGAS, FIELD,EQLDIMS ,TABDIMS, WELLDIMS, AQUDIMS) each of this data code require a specific data, ECLIPSE Manual must had used for helping what this codes needs.
2- GRID The GRID section determines the basic geometry of the simulation grid and various rock properties (porosity, absolute permeability, net-to-gross ratios) in each grid cell. From this information, the program calculates the grid block pore volumes, mid-point depths and inter-block transmissibilities. The actual keywords used depend upon the use of the radial or cartesian geometry options. The program accepts the radial form in a cartesian run and vice versa, but issues a warning.
The used data code :(TOPS,DX, DY, DZ, PERMX, PERMY, PERMZ, PORO, NTG, GRIDFILE, INIT, NOECHO, PINCH).
3- EDIT The EDIT section contains instructions for modifying the pore volumes, block center depths, transmissibilities, diffusivities, and nonneighbor connections (NNCs) computed by the program from the data entered in the GRID section. It is entirely optional.
150
CHAPTER 3
4- PROPS Tables of properties of reservoir rock and fluids as functions of fluid pressures, saturations and compositions (density, viscosity, relative permeability, capillary pressure, etc.). Contains the equation of state description in compositional runs.
The used data code :(SWFN, SGFN, SOF3, ROCK, DENISITY, PVDG, PVTO, PVTW, AQUATAB)
5- REGIONS ` Empty, because this section used for divide the reservoir in different regions and different properties.
6- SOLUTION The SOLUTION section contains sufficient data to define the initial state (pressure, saturations, compositions) of every grid block in the reservoir .
The used data code :(EQUIL, RSVD, RPTRST, RPTSOL)
7- SUMMARY Specification of data to be written to the Summary file after each time step. Necessary if certain types of graphical output (for example watercut as a function of time) are to be generated after the run has finished. If this section is omitted no Summary files are created.
151
CHAPTER 3
The used data code :(RPTONLY, DATE, EXCEL, SEPARATE, ELAPSED, FOIP, FOPR, FOPRH,FOPT,FOPTH,FLPR,FLPRH,FLPT,FLPTH,GOPR,GOPRH, GOPT,GOPTH,GWPR,GGPR,WOPR,WOPRH,WOPT,WOPTH, WWPR,WWPRH,WGPR,WGPRH,FWPR,FWPRH,FWCT,FWCTH, FWPT,FWPTH,GWPR,GWPRH,GWCT,GWCTH,GWPT,GWPTH, WWPRH,WWCTH,WWPT,WWPTH,FGIP,FGPR,FGPRH,FGOR, FGORH,FGPT,FGPTH,RGIP,GGPR,GGPRH,GGOR,GGORH,GGPT, GGPTH,WGPR,WGPRH,WGOR,HWGPT,WGPTH,FPR,RPR,WBHP, WBP5,WBP9,WBHPH,WPI,WPIH,FAQR,FOEW,ROEW,TCPU, WMCTL,WLPR,WLPRH,WPR,AAQR,FAQR,FAQT, AAQP,FOPV,FWPV, WLPT, WLPTH, WWIR,WWIT, FWIR, FWIT,WPI, WBP9)
8- SCHEDULE Specifies the operations to be simulated (production and injection controls and constraints) and the times at which output reports are required. Vertical flow performance curves and simulator tuning parameters may also be specified in the SCHEDULE section.
The used data code :(WELSPECS, COMPDAT, WCONPROD)
WCONHIST,
WCONINJE,
DATES,
After Input the reservoir Data in the Data File, Starting the next step that‘s running the simulation
152
CHAPTER 3
Running the Simulator:1- From the Program Launcher ballet press ECLIPSE
Figure 95 Simulator Preface.
2- Browsing computer drivers to select input data file and press RUN
Figure 96 Run The Simulator.
3- Running the Simulator till end and having confirmation that there is no warning massages or errors
Figure 97 Running The Simulator.
153
CHAPTER 3
4- After running to show the calculation of OOIP, open the file (.PRT) from input folder and search for OOIP
Figure 98 Print File Location.
Figure 99 Original Oil In Place (OOIP).
5- Showing the Model, From Program Launcher select (FLOVIZ)
Figure 100 Start FLOVIZ 154
CHAPTER 3
6- After pressing (RUN), FILEOPENECLIPS
Figure 101 Run The Model 1 .
Figure 103 Run The Model 2.
Figure 102 Run The Model 3 .
155
CHAPTER 3
Figure 105 Reservoir Model .
7- (GRID PROPERTEY ) Button enable to show the different properties required and response of model with TIME factor, that can be selected from (PLAY,PAUSE, …ETC. ) Buttons which at the top bar of the software.
Figure 104 (FLOVIZ Parameters).
156
CHAPTER 3
To get the last report and drawing the curves of different requirements from production rates (Gas, Oil & Water) along reservoir life from the beginning till the predicted depletion, Select from program Launcher (OFFICE).
Figure 106 RUN OFFICE.
8- Select REPORTFILEOPEN VECTORS.
SUMMERY
Figure 107 Load All Vectors .
157
LOAD
ALL
CHAPTER 3
9- At (INPUT), select the vectors required to plot or shown in the output file then press (GENERATE REPORT) .
Figure 108 Input Variables .
10- To see the report Press (OUTPUT) then select showing it as table or Plot as required.
Figure 109 Output OFFICE.
158
CHAPTER 3
Figure 110 OFFICE Output table.
Figure 111 OFFICE Output Charts .
11- Finally, may have more than one plot and different vectors as required.
159
CHAPTER 4
CHAPTER4 4 Result 4.1 PVT Correlations [5] Gas Solubility (Rs) The used correlations : Standing‘s Glaso‘s
Gas Solubility 200 180 160 140 120 Rs 100 80 60 40 20 0
Actual Modified Rs Glaso Standin 0
2000 4000 Pressure
6000
Figure 112 Gas Solubility
The Best and suitable correlation was (Standing correlation) with Average Absolute Error (AAE%) = 50.98 %
x= 0.0125 API - 0.00091(T - 460)
the modified correlation
160
CHAPTER 4
Gas Specific gravity From knowing the gas specific gravity in the separator enabling to calculate the gas specific gravity in different reservoir conditions by adding the factor Delta (∆) from the followed chart. 0.2 0.1 0 ∆ -0.1
0
100
200
300
400
500
600
700
800
-0.2 -0.3 ∆= -6E-15 Poly. (p,delta)
p,delta
P5
Figure 113
p + 1E-11 P4 - 9E-09P3 + 1E-06P2 + 0.001P - 0.255 R² = 1
Correction.
At known pressure -15
∆= (-6×10
5
-11
P )+(10
4
-9
3
-6
2
P )-(9×10 P )+(10 P )+(.001P)-.255
=
±(∆)
Formation Volume Factor (Bo) The used correlatins:Above Bubble Point Pressure (Calhoun's correlation) Calhoun's correlation
161
CHAPTER 4
Below Bubble Point Pressure Standing's correlation Glaso‘s Correlation The Vasquez-Beggs Correlation Standing's correlation
Glaso’s Correlation
The Vasquez-Beggs Correlation
The Suitable Correlation where
P
Pb was (Calhoun's correlation) with AAE%= 1.033 % Bo
1.2 1.18 1.16 1.14 1.12 Bo 1.1 1.08 1.06 1.04 1.02
Actual Standing Bo calhoun's correlation Modified Glaso’s Correlation 0
1000
2000 3000 Pressure
4000
Figure 114 FVF
162
5000
The Vasquez-Beggs Correlation
CHAPTER 4
Oil Compressibility (Co) The used correlations:
The Petrosky-Farshad Correlation (P>Pb)
The Vasquez-Beggs Correlation (P>Pb)
Best correlation was Petrosky-Farshad Correlation with AAE %= 19.11% 40
Co *10^-6 The Petrosky-Farshad Correlation Co real * 10^-6
35 30 25 20
Co *10^-6 The Vasquez-Beggs Correlation Modified PetroskyFarshed *10^6
15 10 5 0 0
1000
2000
3000
4000
5000
Figure 115 Oil Compressibility
Oil Viscosity The used correlation:
The Chew-Connally Correlation (P
163
Mob = (10)^a (Mod)^b a = Rs [2.2(10^-7) Rs - 7.4(10^-4)] b=(0.68/10^c)+(0.25/10^d)+(0.062/10^e) c = 8.62(10^-5)Rs d = 1.1(10^-3)Rs e = 3.74(10^-3)Rs
CHAPTER 4
The Best Correlation Chew-Connally Correlation with AAE%=2.972%
Mo
Oil viscosity 10 9 8 7 6 5 4 3 2 1 0
Mo Actual Mo chew Mo Beggs-Robinson Modified Chew
0
500
1000
1500
Pressure
Figure 116 Oil Viscosity
Crude Oil Density The used correlation:Table 43 crude oil denisty used correletion.
Below Bubble Point Pressure 1. Material Balance Equation 2. Standing
Above Bubble Point Pressure 1. Vasquez-Beggs 2. Petrosky-Farshad
The most suitable correlation:Table 44 Oil Denisty suitable Correlation
Below Bubble Point Pressure Standing
Above Bubble Point Pressure Vasquez-Beggs
AAE % = 8.28%
AAE %= 0.946866842
164
80
CHAPTER 4
75 70 Actual
65
MBE Standing
60
Vasques-Beggs 55
Petrosky-Farshad Modified
50 45 40 0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Figure 117 Crude Oil Denisty.
Water formation volume factor (Bw) The used correlation βw = βwp(1+A*y*10^-4) Where βwp = C1+C2*P+C3*P^2 A=5.1*10^-8*P+ (T-60)*(5.47*10^-6-1.95*10^-10*P) + (T-60) ^2 * (3.23*10^-8+8.5*10^-13*P) y= 150000 ppm C1=0.9911+6.35*10^-5*T+8.5*10^-7*T^2 T= 205 F C2=1.093*10^-6-3.497*10^-9*T+4.57*10^-12*T2 C1= 1.039839 C3=-5*10^-11+6.429*10^-13*T-1.43*10^-15*T^2 C2= 3.77E-07 C3=
Where βwp= water formation volume factor at (p=14.7, T), bbl/Stb T = Reservoir Temperature Bw (oF) Y =water salinity (PPM) 1.042 P =reservoir pressure (psia) 1.0415
2.17E-11
Bw 1.041 1.0405
Bw
1.04 0
1000
2000 3000 Pressure
Figure 118 Bw
165
4000
5000
CHAPTER 4
Water Compressibility (Cw) Cw =Cwp * (1+X*Y*10^-4) Where X =5.1*10^-8*P+(T-60)*(5.47*10^-6+1.95*10^-10*P)+(T-60)^2*(3.23*10^-8+8.5*10^-13*P) Cwp =(C1+C2*T+C3*T^2)*10^-6
Wc
Water Comprisibliity
0.0000033
C1=3.8546-0.000134*P
3.25E-06 0.0000032
C2=-0.01052+4.77*10^-7*P
3.15E-06
C3=3.9267*10^-5-(8.8*10^-10*P)
Water Comprisibliity
0.0000031 3.05E-06
Pressure
0.000003 0
Where Cwp =water compressibility at p=14.7,T,cp T = Reservoir Temperature (oF) Y =water salinity (PPM) P =reservoir pressure (Psi)
2000
4000
6000
Figure 119 Water Compressibility
Table 45 PVT Conculosion
Property Gas Solubility (Rs)
Suitable Correlation Standing correlation =
Gas Specific gravity
Formation Volume Factor(Bo)
Oil Compressibility (Co) Oil Viscosity
Crude Oil Density
AAE% ±(∆)
PPb Calhoun's correlation Petrosky-Farshad Correlation Chew-Connally PPb Vasquez-Beggs
166
50.98 ---1.282454 1.033 19.11 2.972 0.946866842 8.28
CHAPTER 4
4.2 History Matching Table 46 History Matching.
∆t days
Date
T press,psi year
t days
NP (bbl)
Oct-63
1963
3550
0
Dec-63
1963
3500
60.8
60.8
131161.4
36833.19739
69.18792
0
Dec-65
1965
3110
730
790.8
1594203
457607.4514
1012.66
0
Dec-67
1967
2860
730
1521
2258608
690542.993
1320.86
0
Dec-69
1969
2695
730
2251
2874789
906562.8094
1346.02
0
Dec-71
1971
2555
730
2981
3360180
1057850.842
3943.711
0
Dec-73
1973
2415
730
3711
4553037
1338178.666
6660.91
0
Dec-75
1975
2275
730
4441
4595367
1347607.682
6660.91
0
Dec-77
1977
2165
730
5171
4595367
1347607.682
6660.91
0
Dec-79
1979
2055
730
5901
5856330
1793137.517
9315.21
0
Dec-81
1981
1970
730
6631
7480535
2408742.788
97529.81
0
Dec-83
1983
1860
730
7361
11147941
3251562.624
124991.1
0
Dec-85
1985
1805
730
8091
17339241
4279254.74
593802.2
912552.4
Dec-87
1987
1695
730
8821
21990877
5659457.859
1791955
5727963
Dec-89
1989
1665
730
9551
27760281
7581882.371
3303377
9440997
Dec-91
1991
1600
730
10281 32935028
8540004.594
5576024
11020377
Dec-93
1993
1525
730
11011 37532647
9438303.772
7078767
18805440
Dec-95
1995
1470
730
11741 41055155
10393282.99
8506195
27964291
Dec-97
1997
1390
730
12471 43656149
10987734.77
9514156
33643078
Dec-99
1999
1335
730
13201 45965899
11659207.85
10828708
38510358
Dec-01
2001
1335
730
13931 51218395
12879859.3
12529240
47821449
Dec-03
2003
1350
730
14661 56173602
14039769.53
14640220
65198390
Dec-05
2005
1360
730
15391 60766000
15604244.58
17798347
78063401
Oct-07
2007
1390
669.2
16060 64211703
16789192.91
21056041
91329803
167
GP(MMSCF) WP(bbl) WI(bbl)
CHAPTER 4
Millions
NP
WP
WI
Pressure
100
4000 3500
80 3000
Wp,Wi,Np (bbl)
60
40
2000
Pressure
2500
1500 20 1000 0 1960
1965
1970
-20
1975
1980
1985
1990
1995
2000
2005
2010500 0
time (YEARS)
18
4000
16
3500
14
3000
Gp(MSCF)
12 2500 10 2000 8 1500 6 1000
4
500
2 0 1960
1970
1980 1990 Time(years)
Figure 121 Gp Vs Years
168
2000
0 2010
Pressure(PSIA)
Millions
Figure 120 Wp,Wi,Np (bbl) Vs Years
GP(MMSCF) press,psi
CHAPTER 4
PVT Matching
Table 47 PVT Matching.
169
CHAPTER 4
Cw, Co, Rs 200
0.000014
180
0.000012
160 0.00001
140 120
0.000008
100 0.000006
80 60
0.000004
40 0.000002
20 0 0
500
1000
1500
Pb
2000 Rs
2500 Co
3000
3500
0 4000
Cw
Figure 122 Cw,Co,Rs
1.18
5 4.9
1.175 4.8 1.17
4.7 4.6
1.165 4.5
Bo 1.16
4.4
Bo
4.3
Mo
1.155 4.2 1.15 0
500
1000
1500
Pb
2000 P
2500
Figure 123 Bo, Mo
170
3000
3500
4.1 4000
Undersaturated Oil Reservoir
Active Bottom water Drive
Aquifer State
Driving Mechanism
Reservoir Type
CHAPTER 4
Unsteady state with infinity Aquifer Boundary
Reservoir type: under saturated reservoir with active water drive Aquifer type: Unsteady state with infinite Aquifer boundary OOIP=205749458 STB
Millions
(F-Wi.Bw)/Eo
re/rw=infinty 300 250 200 150 re/rw=infint y
100 50 0 0
10
20
30
40 Millions
∑Qt.∆P/Eo
Figure 124 re/rw=infinty
171
Linear (re/rw=infin ty)
CHAPTER 4
4.3 Prediction The project gets the prediction from ends of available data times : 2009, 2011, 2013, 2015, 2017, 2019 get Wi/Np and then ΔWi/Np as shown :
Table 48 Wi/Np & dWi/Np
ΔWI/NP
Time
WI/NP
2009
1.2992
2011
1.326
0.0268
2013
1.3524
0.0264
2015
1.3775
0.0251
2017
1.4021
0.0246
2019
1.4265
0.0244
172
CHAPTER 4
Then get (avg: ΔWI/NP) which equals = 0.0253625
Table 49 Prediction Calculation T
NP
NP/N
WP
WI
WI/NP
WI/VP
2009
68000000
0.330497555
22157428
88345600
1.2992
0.223612
2011
72000000
0.349938587
24905428
95472000
1.326
0.241649
2013
76000000
0.36937962
27813428
102782400
1.3524
0.260153
2015
80000000
0.388820652
30881428
110200000
1.3775
0.278927
2017
84000000
0.408261685
34109428
117776400
1.4021
0.298104
2019
88000000
0.427702718
37497428
125532000
1.4265
0.317734
2021
92000000
0.44714375
41045428
133571350
1.451863
0.338082
2023
96000000
0.466584783
44753428
141813600
1.477225
0.358944
2025
100000000
0.486025816
48621428
150258750
1.502588
0.38032
2027
104000000
0.505466848
52649428
158906800
1.52795
0.402209
2029
108000000
0.524907881
56837428
167757750
1.553313
0.424612
2031
112000000
0.544348913
61185428
176811600
1.578675
0.447528
2033
116000000
0.563789946
65693428
186068350
1.604038
0.470958
2035
120000000
0.583230979
70361428
195528000
1.6294
0.494901
2037
124000000
0.602672011
75189428
205190550
1.654763
0.519358
2039
128000000
0.622113044
80177428
215056000
1.680125
0.544328
2041
132000000
0.641554076
85325428
225124350
1.705488
0.569812
2043
136000000
0.660995109
90633428
235395600
1.73085
0.59581
2045
140000000
0.680436142
96101428
245869750
1.756213
0.622321
2047
144000000
0.699877174
1.02E+08
256546800
1.781575
0.649346
2049
148000000
0.719318207
1.08E+08
267426750
1.806938
0.676884
2051
152000000
0.73875924
1.13E+08
278509600
1.8323
0.704936
2053
156000000
0.758200272
1.2E+08
289795350
1.857663
0.733501
2055
160000000
0.777641305
1.26E+08
301284000
1.883025
0.76258
2057
164000000
0.797082337
1.32E+08
312975550
1.908388
0.792172
2059
168000000
0.81652337
1.39E+08
324870000
1.93375
0.822278
2061
172000000
0.835964403
1.46E+08
336967350
1.959113
0.852898
2063
176000000
0.855405435
1.53E+08
349267600
1.984475
0.884031
2065
180000000
0.874846468
1.6E+08
361770750
2.009838
0.915678
2067
184000000
0.894287501
1.67E+08
374476800
2.0352
0.947838
2069
188000000
0.913728533
1.74E+08
387385750
2.060563
0.980512
173
CHAPTER 4
Then predict that : The reservoir Abundant time is 2069 as : NP/N =0.913728533 and WI/VP=0.980512 and this is the maximum acceptable values for each of them !!
Now draw a chart between :Time on (x-axis) and (P, Np, Wi, Wp) on (y-axis) :
140000000
1500 1480
120000000
1460 100000000 1440 Np, 80000000 Wp, Wi 60000000
1420 Pressure 1400
Np Wp Wi
1380 40000000 1360 20000000 0 1999
1340
2004
2009 Time
2014
Figure 125 Past& Future
174
1320 2019
P
CHAPTER 4
4.4EOR From last study in literature review about types of recovery the best one and most suitable one is the(Polymer Flooding) that will be environmentally and economically good for the reservoir. Using polymers to increase viscosity of water in small bores and making the displacement of oil by water with same rate to not to trap oil So must use special type of polymers: 1. Purely Viscous This type at small diameter Ɣ1 increase water has low viscosity (high speed) so in small pores oil will be trapped that‘s make this type not suitable for use. Ex: a) Poly Socharide (PS). b) Hydroxy Ethyle Celelouse (HEC)
Figure 126Purely Viscous
175
CHAPTER 4
2. Visco Elastic This type is suitable as in small diamter Ɣ1 has high water viscosity (low speed) and In large diamters Ɣ2 has low viscosity (high speed) . Ex: a) Poly Acylamide (PA) b) Poly Ethylene Oxyde (PEO) so by adding visco elastic polymer with optimum concentration make water in large and small diameter move at same velocity.
Figure 127 Visco Elastic
The Viscosity selection The selection of water viscosity that will flood its defends on the condition of the reservoir at moment of flooding and the target required By using (Reservoir management spread sheet) its able to show the behavior of reservoir with different water viscosity and comparing between them.
176
CHAPTER 4
As shown in the following chart Where Visc.1= 0.5 CP, Visc.2= 1 CP & Visc.3= 10 CP From this chart notice that the effect of changing viscosity on production where with increasing water viscosity the result is increasing in cumulative oil produced and retardant of water production
prediction by chemical effect 1.2E+11 1E+11 8E+10 6E+10 4E+10 2E+10 0 0
2E+09
4E+09 time (days) visc. 1
visc. 2
6E+09
visc. 3
Figure 128 prediction by chemical effect
177
8E+09
CHAPTER 4
4.5MBAL 1- Montecarlo Tool
Figure 130 Montecarlo Results 1
Figure 129 Montecarlo Results 2
178
CHAPTER 4
2-MBAL MBE
1- History Matching results : A-Drive mechanism is shown in the figure
Figure 131 Drive mechanism
The figure shows the drive mechanism of the reservoir where it start with fluid expansion with Fluid expansion Pore volume compressibility and water influx with the percentage shown in the figure was the dominated driving mechanism . and at 1985 the water injection was started . B-Bottom drive aquifer
179 Figure 132 Bottom drive aquifer
CHAPTER 4
C-Graphical method graph
Figure 133 graphical method
The Graphical method shows the relationship between (F/Et ) and (We/ Et ) where the intercept is the original oil in place (OOIP ) as shown in the figure = 205.79 MMSTB D-Analytical method graph :
Figure 134 Analytical method
180
CHAPTER 4
Prediction results: 1-average gas and oil rate with time
Figure 135 Gas and oil rate
2-Average water injected with cumulative oil produced
Figure 136 Average water injected with cumulative oil produced
181
CHAPTER 4
3-cumulative gas and oil produced with time
Figure 137 cumulative gas and oil produced
4 - Cumulative oil produced with water injected
Figure 138 Cumulative oil produced with water injected
182
CHAPTER 4
5-water injection And cumulative oil production with time
Figure 139 water injection And cumulative oil production with time
6-oil saturation with time
Figure 140 oil saturation with time
183
CHAPTER 4
7- Oil recovery factor
Figure 141 recovery factor
Recovery factor is 47 % at 1-1-2035
184
CHAPTER 4
4.6 ECLIPSE Results 1- Model Eclipse model the reservoir with its wells in present time and in future till reservoir depletion with different properties.
Figure 142 Reservoir Model
Side view of reservoir with different saturations.
Figure 143 Side view 185
CHAPTER 4
2- GRAPHES a. Total production (Oil, Gas & Water) , total water injection verses Years
Total oil production (FOPT) Total gas production (FGPT) Total water Production (FWPT) Total water injection (FWIT)
Figure 144 FOPT,FGPT, FWPT, FWIT Vs Date
b. Production and injection rates verses date Field Gas Production Rate (FGPR) Field Oil Production Rate (FOPR) Field Water Production Rate (FWPR) Field Water Injection Rate (FWIR)
Figure 145FGPR, FOPR, FWPR, FWIR Vs Date 186
CHAPTER 4
3- Originally In Place Calculations
Figure 146 In place calculation
Eclipse provide report for each year till depletion in the previous report show that:Original Oil In Place 204.653154 MMSTB Original Water In Place 215.737127 MMSTB Original Gas In Place 43664.797 MMSCF
Prediction
187
CHAPTER 4
Recommendation Final Recovery factor can be increase by increasing number of produced wells or increase the injection rate . New produced well in marine zone at cell (9,2) Result recovery factor = .68
Cell(9,2) New produced well
Figure 147 New Well
Increasing number of produced wells in highly oil saturation cells and thick formation will be economically and increasing the recovery factor and have the optimum production
.68 RF 0.63 Series2 Series1 4 no. of wells 3
0
1
2
3
4
Figure 148 Comparison no. of wells
188
5
CHAPTER 4
RF With and Without Injection The following chart shows the importsance of the water injection in the reservoir to increase the recovery factor. So By increasing the injection wells the production increase 70 60
RF %
50 40 Wiyhout inj. 30
With inj.
20 10 0 1
Figure 149 Comparison Inj. Wells
189
CHAPTER 4
Conclusion Based on the case study and the previous explanation, the following can be concluded: MBE by Excel calculations must be used to know the reservoir type and primary reserve estimate. Monte Carlo simulation (probabilistic approach) proved to be more successful in estimating IOIP as it gives all the possible values based on the data available (P10, P50, P90). MBAL Material Balance Tool can be used to confirm the IOIP from Monte Carlo and can also be used to determine the reservoir driving mechanism. ECLIPSE Simulation very useful for model the reservoir , shows the whole parameters of the reservoir with time changing , predict the reservoir behavior with changing conditions .
The summary of IOIP and RF results of the case study can be summarized as follows. Table 50 Conclusion
OOIP RF%
MBE Calculation 205.6 @ 2035 .69
Montecalo 209 Not applicaple
190
MBE MBAL 205.3 .47
ECLIPSE 204 .65
REFERENCES
REFERENCES 1- The Petroleum Society of CIM, Determination of Oil and Gas Reserves, Canada,1994. 2- Repsol YPF, Reserves Reporting System, Louisiana, 2005. 3- Arps,J.J, 1945, Analysis of Decline Curves, Trans. AIME 4- Arps,J.J, 1956, Estimation of primary oil reserves, Trans. AIME 5- Ahmed, Tarek. Reservoir Engineering Handbook. Amsterdam , Elsevier, GPP, 2006.Print. 6- Reservoir Issue 1, part of Reservoir Engineering for Geologists, Fekete, February 2008 7- Schilthius,R., Solution-Gas-Drive Reservoirs, Trans. AIME, 1936, Vol.118. 8- Clark, N., Elements of Petroleum Reservoirs. Dallas, TX:SPE, 1969. 9- Cole, F., Reservoir Engineering Manual, Houston, TX: Gulf Publishing Co., 1969. 10- Havlena, D., and Odeh, A. S., “The Material Balance as an Equation of a Straight. Line,” JPT, August 1963, 11- Havlena, D., and Odeh, A. S., “The Material Balance as an Equation of a Straight Line, Part II—Field Cases,” JPT, July 1963. 12-
Dake, L., The Practice of Reservoir Engineering, Amsterdam: Elsevier. 1994.
13- Dake, L. P., Fundamentals of Reservoir Engineering. Amsterdam: Elsevier. 1978. 14- Van Everdingen, A., and Hurst, W., “The Application of the Laplace Transformation to Flow Problems in Reservoirs,” Trans. AIME, 1949. 15- B.C.Craft, Applied Petroleum Reservoir Engineering,2nd edition ,1991. 16- James J. Sheng,Ph.D.,Modern Chemical Enhanced Oil Recovery Theory and Practices, Elsevier, GPP,2010, Print 17- Sara Thomas , Chemical EOR-The Past, Does It Have A Future , SPE Distinguished Lecturer Series ,2005. 18- George S. Monte Carlo: Concepts, Algorithms, and Applications. New York, Springer, 2008. Print 19- Metropolis, N. and Ulam, S., “The Monte Carlo Method” J. Amer. Stat. Assoc., 1949. 20- “Petroleum Reserves Definitions” published by SPE, 1964. 191
REFERENCES
21- Schlumberger ,Simulation Software Manuals , Eclipse , 2005. 22- Petroleum Expert, MBAL Explanation, www.petex.com/products/?ssi=4 23- Islam Amged Nassar , Reservoir Project , BUE, 2010 24- Petroleum Experts, Reservoir Analytical Simulation , MBAL, version 7 , 2003.
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