OFM 2005.1 Forecast Analysis Fundamentals

OilField Manager Forecast Analysis Fundamentals Training and Exercise Guide Version 2005.1

Schlumberger Information Solutions May 16, 2005

Copyright Notice © 2005 Schlumberger. All rights reserved. No part of this manual may be reproduced, stored in a retrieval system, or translated in any form or by any means, electronic or mechanical, including photocopying and recording, without the prior written permission of Schlumberger Information Solutions, 5599 San Felipe, Suite 1700, Houston, TX 77056-2722.

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Creating a Forecast Analysis

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Table of Contents Chapter 1

Creating Forecast Analysis ............................................................ 2

Learning Objectives ............................................................................................................ 2 Setting Up a Forecast Scenario ......................................................................................... 3 Editing the Graph ................................................................................................................ 7 Working with Different Forecasting Features................................................................... 14 Hyperbolic Fit Type ................................................................................................... 17 Exponential Fit Type.................................................................................................. 23 Add Schedule ............................................................................................................ 25 Exponential Fit Type.................................................................................................. 27 Manual Match for Empirical Solutions.............................................................................. 41

Chapter 2

Forecast.......................................................................................... 44

Using the Output Features ............................................................................................... 44 Working with Cases .......................................................................................................... 47 Auto Decline...................................................................................................................... 49

Chapter 3

Additional Forecasts ..................................................................... 51

Water Cut versus Cum.Oil Analysis ................................................................................. 51 P/Z vs. Cum.Gas Analysis................................................................................................ 55

Chapter 4

Fetkovich Type Curve Analysis ................................................... 64

Using Fetkovich Type Curve Analysis (Late-Time) ......................................................... 65

Chapter 5

Analytical Transient Solutions..................................................... 75

Using Analytical Transient Solutions................................................................................ 75

Chapter 6

Retrieving Forecast Results......................................................... 85

Calculated Variables ......................................................................................................... 85

OFM Forecast Analysis Fundamentals May 16, 2005

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Chapter 1

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Creating Forecast Analysis

Welcome to Introduction to Forecast Analysis in OilField Manager (OFM)! In this course you will learn how to use empirical and analytical techniques to forecast production and retrieve forecast information for further studies. Formerly known as Decline Curve Analysis (DCA), the Forecast module in OFM has been enhanced to facilitate more sophisticated analyses. In OFM 2005, the Forecast module consists of four major categories (techniques); Empirical, Fetkovich, Locke & Sawyer, and Analytical Transient solutions. Forecasts can be done on single well (completion) level, category level, or on a group of wells. If you choose to perform the forecast on a group of wells, the forecast result will be slightly different than that of grouped individual well forecasts (i.e. summing the individual forecasts). This is the issue of “forecast of a group” vs. “group of the forecasts”.

Interactive manual match techniques for empirical solutions are introduced in this version of OFM. OFM will initially plot control points based on historical or digitized data regression. Once a control point is moved, manual match method is automatically activated and the user will have total control of how the match should be performed. The Well Deliverability Analysis enables you to analyze data from FlowAfter-Flow tests (Back Pressure Analyses), Isochronal Tests, and Modified Isochronal Tests using the following empirical equation, q=C(Pws^2 - Pwf ^2) ^n. The online Help file has been updated for the Forecast module. All the terms used in this module have been documented to give users more comprehensive information.

Learning Objectives In this section, you will be introduced to the fundamentals of creating forecast analysis. You will successfully learn how to perform the following procedures within this workflow: •

Set up a forecast scenario

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Use different forecast features


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In addition to basic forecasts like rate vs. time, rate vs. cum, OFM allows you to perform more advanced techniques such as ratios and cuts vs. cum. Fetkovich, Locke & Sawyer and Analytical Transient Solution techniques are type-curve analyses, which require better understanding of the reservoir model as well as the parameters controlling the well/entity behavior. In this lesson, you will focus on using the Empirical method of forecasting. There is a session covering the basics of Fetkovich and Analytical Transient methods. More in-depth coverage of the type curve-based methods will be addressed in more advanced OFM training courses.


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Setting Up a Forecast Scenario In the Demo2005 database, about half of the wells are not productive and approximately 80% of the other half has already stopped producing. We are going to use the active producer after 1998. 1. From the Filter pane, select the Well List node, right-click and select Open. The Well List dialog displays.

2. Select Prod_Wells98.txt and click Open. Note: If you do not have the well list or the query file, please take some time to set up the query to do it. The definition of the query is (Monthlyprod.Oil > 50) & (Date >= 19980101), the criteria is met 3 times, and the Consecutively box checked. It should resemble the image below.

3. Click OK to save the query. 4. From the Filter pane, select the newly created filter to apply the conditions to the basemap.


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5. Click

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to Group all the wells.

6. Select Analysis>Forecast. The forecast tabbed page is displayed in the OFM main window.


7. Select Edit>Scenario Manager. The Scenario Manager dialog displays. 8. Highlight the DefaultScenario from the Scenarios list and click Edit. The Edit Scenario dialog displays. 9. Select Oil from the Phase/Analysis list field. OFM Forecast Analysis Fundamentals May 16, 2005

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10. For this phase (Oil), the Time (Date) variable should be Date. 11. The Cum.Oil variable should be Oil.Cum (a monthly frequency variable); the Oil Rate variable is Oil.CalDay.

12. Go through all other phases (Gas and Water) and Ratios (GOR, WOR, Water Cut, and Oil Cut) and set them up accordingly. Reselect the Oil phase. 13. Select the Historical Regression tab. We will work on the Oil phase and use the Empirical method. 14. Select Best Method from the Method section of the dialog.


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15. Select the Forecast tab. 16. You are defaulted to Schedule 1. In that schedule, specify the following: Start Time – Months from End, starting at 0 (zero) month

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Start Rate – Last Historical Rate

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Reserve Type – Proven-Developed

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End Time – Months from Start, set for 60 months (5 years)

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End Rate. Enter 1 as the end limit.

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Decline Type – Historical Regression



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Note: The Forecast tab has lots of options. Please read the online help to understand the usage of those available options (for example, when to use Last Historical Rate, and when to use From Historical). 17. Click OK.

Editing the Graph 1. Now that the forecast scenario is set, it is time to work on the appearance of the graph. Select Edit>Graph or right-click on the graph and select the Graph option from the menu. The Edit Plot dialog in Forecast module is similar to the Edit Plot dialog in Plot module.


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Notes: Database Forecast - Once you like your forecast result, you can save it to the database. This database forecast result can be retrieved from other modules in this project.

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Working Forecast - Forecasting is an ongoing process. As long as you have not saved your forecast result yet, your forecast is still a “working forecast”. Working forecast results can only be seen in the Forecast module, not anywhere else in the project.

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Control Points - In this module, you can select to exclude data points (that you do not think are reliable), so they do not affect your result. Working points then have different attributes to distinguish with excluded points. Control Points are the end and middle points used for the manual match.

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Fitted Curve - Attributes of the fitted line.

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Historical - Attributes of the diagnostic variable data (historical data).

2. Locate the Legend section of the Properties pane. 3. Click in the field to the right of Result Items. This action enables a browse button.


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4. Click the button to display the Result Legend Items dialog and select the result items to display.

5. Clear the checkbox of the parameters you do not want to display and click OK. 6. Locate the Graph Settings section of the Properties pane. 7. Click in the field to the right of Setup. This action enables a browse button.


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8. Click this button to open the Headers dialog.


9. Click Add. 10. Click Assist and enter "Forecast: "+@name(). 11. Click OK. 12. Add another header that reports today’s date. The definition is @fmtdate( @today(), "mm/dd/yyyy"). Your Headers dialog should resemble the image pictured below.


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13. Click OK. The graph displays. Move and edit the Header/Label Fonts, resize the graph, move the legend to get an output similar to the one pictured below.

Notes: •

To move a header, use the left mouse button in a “drag and drop” operation.

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To edit the headers, select Edit>Graph>Headers.

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To move/resize graph, click the right mouse on the graph and select Graph Move/Size.

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To move Legend and/or Axis Label, use the left mouse button to “drag and drop”, or highlight the item to move then select Move from the right mouse click menu.

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The Legend/Axis Label Fonts can be edited from the right mouse click>Font menu. The Label can also be modified via from the right mouse click>Edit menu.

14. Select Edit>Limits>Lower.


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15. Click to draw the line under the last declining portion of the historical curve as shown.

16. When the action is complete, right-click and select Done from the shortcut menu. Schlumberger Private

Notes: •

When applying the Lower Limit line, any data points below and out of the line are excluded.

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When drawing the line, the right mouse click gives you the options to complete or undo (last or all) the operation.

17. Select File>Case (or click the Save button), to save to the current case, Case1.


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Note: (Optional) You can save to another case using Save to Different Case by select File>Save to Different Case.

You can edit the group name now for future use if you wish.

If you do not suppress warning messages, OFM will provide a message to remind you that you have to regroup before the saved forecasts can be viewed in other modules.


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Working with Different Forecasting Features 1. Locate the Step toolbar at the top of the OFM main window. 2. Click

Next. The BLUE_1:Ge_6 well displays.

3. Place a lower limit on the data as shown to exclude the first and the last two data points. Right-click and select Done when finished. Schlumberger Private

Our starting rate is set at Last Historical Rate, which may not be very good with insufficient historical data and with the last historical rate excluded. 4. Select Edit>Scenario, click the Forecast tab and select Last Fit Rate from the Start Rate list.


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5. Click OK. Save the forecast (from File>Save or using the Save button) and the graph displays.

6. Click Next. The forecast for BLUE_1:He_0 displays (based on the default case).

Note: that the best-fit case for historical regression is Exponential. However, excluding the first few data points that are not representative of the well’s decline behavior, the best fit should be hyperbolic. 7. Place the lower limit as shown. Right-click and select Done.


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Note: The start time is at the last date of the project. In this case, we may want to start forecasting from the last historical date of the well. 8. Select Edit>Scenario. 9. Select the Forecast tab, and select Last Historical Date from the Start Time list. 10. Click OK. Save the forecast. The graph displays. Schlumberger Private

11. Click Next. The working forecast for BLUE_5:Sc_0 displays.


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Even though it appears to be a good fit, and the forecast looks acceptable, there are things that we can do to obtain a better result. 12. Place a lower limit (and upper limit if needed) to rule out the anomalous data points (noise), for example at the beginning of the production history.

Hyperbolic Fit Type 1. Locate the Historical Match section of the Properties pane. 2. Set the Fit Type to Hyperbolic. 3. Set the b Value Method to User. 4. Set the User value to 0.6 (if you do not enter your own b-value, OFM will select the best b-value to use Hyperbolic regression).


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5. Select Edit>Scenario and click on the Forecast tab. 6. From the Start Rate list, select From Fit. Note: In the Decline Parameters Type list box, the Historical Regression option is selected. It means that the forecast will be the continuation of the historical hyperbolic regression. You can also select the Hyperbolic in the Decline Type list box, and then enter the value of 0.6 for the “b-value”. The result should be similar if you enter a value for decline rate that is close to the default (calculated) decline case.


7. Click OK.

8. Click Next. The forecast for GREEN_4:Ad_3BU displays.


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Note that the last historical rate is already below the economic limit. Thus there is no default forecast on this well. Still we can reasonably perform the forecast on this well. 9. Place a lower limit as shown in the image below.

10. Select Edit>Scenario. 11. Select the Forecast tab. 12. Select Last Historical Date for Start Time. 13. Select From Fit for Start Rate. 14. From the Decline Parameters Type list field select Exponential. 15. From the Decline Parameters Rate list field select User Defined and enter 0.01 for Decline Rate.


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16. Click OK.

17. Click Next. The forecast for GREEN_6:Li_1C displays.


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18. Place an upper limit as shown in the image below.

19. From the Properties pane, modify the following settings from the History Match section. 20. Set the Fit Type value to Hyperbolic. 21. Set the b Value Method to Range. 22. Set the Minimum and Maximum values to 0.3 and 0.6, respectively.


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23. Click Next. The forecast for ORANGE_18:De_3 displays.


24. Place a lower limit as shown in the image below.


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25. Place an upper limit as shown in the image below.

Exponential Fit Type 1. From the Properties pane change the Fit Type to Exponential. 2. Select Edit>Scenarios. 3. Select the Forecast tab. 4. Select Last Historical Date for Start Time. 5. Select Last Fit Rate for Start Rate. 6. Click OK.

7. Save the forecast. 8. Click Next. The forecast for ORANGE_19:Ad_1A displays.


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This well has a good history of production. As seen, the decline trend from 1984 to 1994 could be identified as the common trend of the well. Somewhere in 1996, a work over was successfully completed with significant increase in production afterwards. The decline trend after work over has been different from the common trend. Further studies of this completion indicate that the well would follow this current trend for a short period and then return to the historical best-fit trend. This will be a case to apply a multiple schedule forecast. 9. Set the lower limit as shown in the image below.


10. Set the upper limit to exclude the points that constitute the spike in late 1995, early 1996. 11. Select Edit>Scenario. 12. Select the Forecast tab. 13. Specify the following: •

Start Time - Months from End. Enter “0” in the adjoining field.

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Start Rate - Last Historical Rate.

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End Time - Months from Start. Enter “30” (months) in the adjoining field.

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End Rate - 1.

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Decline Parameter Type - Exponential.

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Rate - User Defined and 0.03 in the adjoining field.


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Add Schedule 1. Click Add to add Schedule #2. 2. Specify the following: •

Start Time - Months from End. Enter “0” in the adjoining field.

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Start Rate - Previous.

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End Time - Months from Start. Enter “30” in the adjoining field.

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End Rate - 1.

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Decline Type - Historical Regression.


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3. Click OK.

4. Click Next. The forecast for ORANGE_23:Li_1C displays.


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Exercise 1

Create a Forecast

Using what you have learned, do the forecast for this well. Save the forecast. The trend from mid-1994 to the last historical date could well determine the well’s behavior for forecasting.

Exponential Fit Type 1. Click Next. The graph for ORANGE_26:Cl_3 displays.

For this well, the last historical rate is below the economic limit. Therefore, no default forecast can be carried out. The production (decline) trend of this well is easily identified. However, the forecast will be stopped before the end of the forecast period due to the forecast rate reaching economic limit first. 2. Set the lower limit to exclude the first and the last production data points as desired. 3. From the Properties pane, set the Fit Type to Exponential. 4. Select Edit>Scenario. 5. Select the Forecast tab. 6. Select Last Fit Rate from the Start Rate list. 7. Click OK.


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8. (Optional) If you select Best Fit from the Method choices, OFM will use hyperbolic regression in this case. Still the forecast will stop before it reaches the time limit. Save the forecast.


9. Take a look at the legend. The Forecast Ended By field reads “Rate”. That means the specified End Rate is met before the forecast End Time.

10. Click Next. The forecast for ORANGE_31:De_1 displays.


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This well has produced consistently throughout its production history. Somewhere in the second half of 1997, the well experienced an increase in production, and the decline trend for this well should follow this trend instead of the overall trend that takes into account data points from previous production periods. 11. Set the lower limit as shown in the image below.

12. Select Edit>Scenario. 13. Select the Forecast tab and enter 150 (to verify the well reaches economic limit before the time limit) in the adjoining field of Ending Time>Months from Start. 14. Click OK.


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Save the forecast. Read the legend. The remaining reserve is about 31 Mbbl. The value of EUR is about 347 Mbbl. The Forecast Ended By field is Rate.

However, separate analyses suggest that the well has about 40 Mbbl in remaining reserve, or about 355 Mbbl in total reserve. We can schedule reserve (or specify total reserve) and ask OFM to adjust decline rate to reserve. 15. Select Edit>Scenario. Schlumberger Private

16. Select the Forecast tab. 17. In the Schedule Reserves field enter 40. 18. In the Decline Parameters Rate field select Calculate from Reserves and Schedule Time. 19. Click OK. The forecast displays.

20. Edit the Scenario again. Clear the Schedule Reserves list field. 21. In the Total Reserves field enter 355. 22. Click OK and do not forget to read the legend to verify the results. The graph displays. OFM Forecast Analysis Fundamentals May 16, 2005

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23. Save the forecast. 24. Click Next. The forecast for ORANGE_32:Li_1C displays.

Study the production history of this well. The behavior from mid-95 to mid-98, and the one from mid-99 on could well be the trend for our forecast. However, there is a period of anomaly (from mid-98 to mid-99) that needs to be reckoned for. 25. Set the lower limit to take into account the production period from mid-95 to mid-98.


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26. Select Edit>Scenario. 27. Select the Forecast tab. 28. From the Start Time list, select Date, and then enter 19980630 in the adjoining field. 29. Set the Start Rate list to From Fit. 30. Select Months from Start from the End Time list, and enter 84 (including 2 years from mid-98 to the last historical date). 31. Select Reserve Type of Possible. Schlumberger Private


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32. Click OK. You are returned to the Scenario Manager. 33. Click Close. The graph displays.

34. Save the forecast. 35. Click Next. The forecast for ORANGE_34:Ad_1A displays.


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ORANGE_34:Ad_1A has short historical production data. The limited data for this completion shows a sharp drop in production, which may indicate this is a troubled well. However, the last data point does not follow the generic trend, and it could be incorrect if we decide to use the overall best fit (dictated by the first five data points) or the partial fit through the last two data points. It has been suggested that this well may be put on production for a short period of time and be shut in to perform corrective measures and then put back on production following the partially fitted trend (Decline Rate of about 0.05 M.e.). All these operations/parameters can be reflected in your forecast estimation, using multiple-schedule forecast technique.

2. Select Edit>Scenario. 3. Select the Forecast tab. We can see that the well will have about four more months before reaching10 bbls/d, which is a fairly good shut-in rate. 4. From the End Time drop-down list, select Date and enter 20001031 in the adjoining field. The End Rate and Reserve Type are of insignificance in this example.


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1. From the Properties pane, set the Fit Type to Hyperbolic.


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5. Click Add. Schedule #2 displays. 6. From the End Time drop-down list, verify Months from Start is selected, and enter 6 (months) in the adjoining field. 7. In the Oil Advanced Settings group box, check the Days Off options and enter 31 (days) in the adjoining field.


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9. From the End Time list, verify Months from Start is selected and enter 50 (months) in the adjoining field. 10. Select Unproven for Reserve Type. In the End Rate field enter 1 (bbl/d) as the desired limit. 11. In the Decline Parameters section of the dialog, from the Type list field select Exponential. 12. In the Decline Parameters Rate field select User Defined and enter 0.05 (M.e.) in the adjoining field. 13. In Oil Advanced Settings, check Shut In Effect and enter 300 (%) in the adjoining field.


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8. Add Schedule #3. From the Start Rate list, select Change By Percent and enter 300 (%) in the adjoining field.

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14. Click OK.

Exercise 2

Shut in activities Experiment other ways to simulate shut in activities in this well.


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15. Click Next. The forecast for ORANGE_34:Ad_3BU displays.

This well has a very short and erratic production history. Therefore, it is nearly impossible to determine a trend of any kind. A different approach must be used to estimate the forecast for this well. Studies show that this well has all the same parameters as a nearby well, which we know the trend. 16. Right-click on the graph and select Digitize Points (or select Edit>Digitize Points). Schlumberger Private

17. Click the points where you believe the best-fit line should be (For your reference, review the magenta points selected on the graph - you may want to zoom in from the View menu).

18. When finished, right-click and select Done. The best-fit line is redrawn. Reset the zoom on the graph if needed. The graph is redisplayed.


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19. Save the forecast. 20. Click Next. The forecast for ORANGE_34:Li_1C displays.

This looks like a very reasonable forecast. The well has excellent production trend but ask yourself why there are no production data after August 1999. You may want to rule out data points before the peak production (early time) to obtain a better fit. 21. Set a lower limit to rule out the first five data points. The best-fit line should then be hyperbolic.

22. Select Edit>Scenario. 23. Select the Forecast tab. 24. Select Last Historical Date from Start Time drop-down list and From Fit from Start Rate list. 25. Click OK.


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The next three wells, ORANGE_35:Ad_1A, ORANGE_35:Ad_3BU, and ORANGE_36:Li_1C all have very brief and erratic production history. Study those three wells and perform the forecasts for them. Do not forget to save your forecasts when done. 26. Select the last well from the filter list, RED_4:Cl_3 (you can do it from the drop-down well list).


This well has good history, and there might have been a work over near the end of 1986, which really revitalized its production. Thus the trend should be determined from that time on. 27. Set the lower limit and upper limit so the used points are as shown:


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28. Once you are satisfied with this forecast, save it.

Question

Now that we have done the forecasts on the selected wells, how do we view the forecast results?

Manual Match for Empirical Solutions OFM will initially plot control points based on historical or digitized data regression. Once a control point is moved, manual match method is automatically activated and the user will have total control of how the match should be performed. Users have the ability to interactively adjust the regression parameters by using the mouse to change the shape and position of the fit curves. The manual match mode remains active until the match method is changed to Auto in the Properties pane.

Note: There are constraints in the manual matching algorithm (i.e. constraints to the movement of the control points). For example, if the fit type is set to exponential you cannot move the control points to make a hyperbolic regression line. OFM Forecast performs historical regression automatically by default when using empirical solutions. 1. Select Blue_5:Sc_0 from the Step pane.


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2. To view Historical Regression results, click the Historical Regression tab located at the base of the Forecast window. On the Historical Regression results pane you can see that the best fit for the historical data is hyperbolic decline with an R-squared (R^2) value of 0.902190.

There are three data points (in blue color) on the historical fit curve. These points are Control Points, which control the shape and position of the fit curve during manual match process. The control points are initially calculated using the equation obtained from auto match. The number of control points are determined by the decline type (or the relationship between dependent and independent variables) and the number of to-be-determined parameters. In the example shown there are three control points, which are used to determine initial flow rate (qi), b value and initial decline rate (Di).


3. Select a control point and then drag it.


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Note: You can also move the fit curve selecting it and dragging it. If you want to move the curve do not position the mouse over the control point. This will only result in moving the control point. Note the match method property on the property pane is now set to Manual.

During manual match process the parameters (qi, b, and Di) are calculated instantaneously based on the control points, and their position to the X- and Yaxis as you dragging and moving them.


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Viewing the Forecast

Chapter 2

Forecast

Even though you can generate forecast from monthly, daily, or even sporadic data, the forecast (rate) results in OFM are stored in monthly frequency. By default, OFM activates four report tabs, Historical Regression Report, Forecast Report, Summary Report, and Database Forecast Report. You can close any of these tabs from the View menu as desired or by selecting the tabbed page and clicking the Close button.

Learning Objectives In this section, you will be introduced to viewing the forecast. You will successfully learn how to perform the following procedures within this workflow: •

Create and compare cases

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Use the auto decline feature

Using the Output Features Note: The next steps assume that you are on the last well, RED_4:Cl_3, and have saved its forecast results to the database.

1. Select the Historical Regression tab and the following displays.


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Viewing the Forecast and Output Window Features

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This tabbed page enables you to read the information about your (real) historical data and the fitted data, the fit equation, and its correlation coefficient. Note: To anchor the window, click the push-pin in the upper right corner. The vertical push-pin indicates that the auto-hide feature is turned off. Refer to the image below. 2. Drag the vertical scroll bar to view the portion of fitted rates.

Note: In this tab or in any other tabs of the Output Window, you can right click to access a text-editing menu to copy/paste, format the fonts, or save the information to a text file. 3. Select the Forecast tab.


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This tabbed page enables you to read the forecast (decline) equation, forecast rates and cumulatives/reserves. Scroll down to see the rest of the report. If you have multiple scheduled forecasts, each schedule has its own equation. 4. Select ORANGE_34:Ad_1A from the well name drop-down list, select the Forecast tab (in Output Window). The information pictured below displays.


5. Scroll down to see the rest of the report. 6. Select the Summary tab.


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7. This tabbed page contains a summary of your forecast, per schedule. Select RED_4:Cl_3 again from the well list (and reselect the Summary tab).

8. Select the Database Forecast tab. Remember that you may set up your forecast and keep working on it without saving the result. OFM keeps a copy of your working forecast, so you can compare and evaluate your case. Once a forecast is saved to your database, you will have two forecast results displayed in this Database Forecast tab; one is of the saved forecast, and the other one is of the work-in-progress forecast. 9. Right-click on the graph and select Limits>Reset. 10. Set a lower limit as shown.

This is our working forecast, which uses a hyperbolic regression instead of an exponential regression in case1. The working forecast results in higher forecast rates, especially towards the end of the forecast period. 11. Click on the Database Forecast tab in the Output Window (you may want to resize this window), scroll down and view the result. The results shown are of the saved forecast (case1). Note: Remember that the current forecast (working) is not saved yet; you cannot retrieve other information (i.e., equations, correlation coefficient, etc.).

Working with Cases 1. Select File>Save to Different Case. The Case dialog displays. 2. Name the new case Case2. The rest of the fields are optional.


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3. Click OK. 4. Select the Database Forecast tab and scroll down. You can see that the Database Forecast Rate and Volume now reflects the information of Case2. Note: Once you add a new case to the database, your working forecast is defaulted to that new case (but not saved until you do so). 5. Select File>Cases. The Case window displays. You can see that Case2 is checked (denoting the active case).


6. Click OK to close the window. 7. Now that you have more than one case saved to the database, you can select to compare the results of those two cases and view the comparison in the Output Window. 8. Select Tools>Compare Cases. The Current Case, as mentioned earlier, is the active case - Case2. 9. Select Case1 from the Compare Case drop-down list.


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10. Click OK. 11. Select the Compare Cases pane (OFM automatically activates this pane when you set up Compare Cases). 12. Scroll down to see the rest of the comparison report. Note: To deactivate the Compare Cases pane, select Tools>Compare Cases and select None from the Compare list. Upon clicking the OK button, the Compare pane will disappear.

Auto Decline Another useful tool regarding basic forecasting is Auto Decline. If you have a filter list that contains many wells and would like to set up a baseline forecast case for all the wells in the list, you can do it via Auto Decline. This feature is designed to give users a baseline, and most of the time would not yield the best-forecast possible for every well. You are strongly advised to check and modify (if needed) every individual forecast afterwards. 13. Select Tools>Auto Decline. The Auto Decline window displays.

The following options are available from this dialog: •

Cases - Assigns the case name.

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Default Scenario - Restores the default values.

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Scenario - Sets up the scenario.


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Range - Specifies the data range.

OFM also provides the grouping option that pre-groups data before performing the forecast and facilitates output control options as saving/printing, etc. 14. Click OK.

Exercise 3

Auto Decline Feature Experiment with this Auto Decline feature.

Exercise 4

Perform Forecast Analysis Perform the forecast on gas phase for a well of your choice.



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Additional Forecasts

Chapter 3


In the previous session, we used Rate vs. Time decline model to forecast the rates and reserves. OFM also allows other common types of forecasting approaches using other variables such as Water Cut, Cumulative Production, and P/Z, etc.

Learning Objectives In this session you will spend some time with two other forecasting models, Water Cut vs. Cumulative Oil and P/Z vs. Cumulative Gas. You will successfully learn how to perform the following procedures within this workflow: •

Water cut versus Cum.Oil analysis

•

Use grid map tools

Water Cut versus Cum.Oil Analysis 1. Select ORANGE_32:Li_1C from the well list. 2. Select Edit>Scenario Manager. The Scenario Manager dialog displays. 3. Select the default scenario and click Edit. 4. From the Variable Association section of the dialog, select Water Cut for Phase/Analysis. Make sure you have Time set to Date, Oil.Cum for Cum.Oil, and Water.Cut for Water Cut.

5. Click OK. The Edit Scenario dialog closes and you are returned to the Scenario Manager. 6. Click Close.


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Notice that since we did not specify the Limiting Water Cut, OFM uses 95% water cut for the cut off point, while the starting water cut is already higher than 95%, resulting in no forecasting at all. Therefore, you will need to specify the limiting water cut. 7. Select Edit>Scenario Manager. The Scenario Manager dialog displays. 8. Select the Default Scenario and click Edit. The Edit Scenario dialog displays. 9. Select the Historical Regression and Forecast tab.

11. For End Water Cut, select the Value radio button and enter a value of 99 (%) in the adjoining field.


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10. In the Forecast section of the dialog, for Start Water Cut select the Last Historical radio button.


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12. Click OK. Then click Close. The graph displays.

Take a look at the Reserves and EUR. Since the starting water cut is already high, there is not much that we can do. OFM Forecast Analysis Fundamentals May 16, 2005

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13. Select Edit>Scenario. 14. Select the Forecast tab. For Starting Water Cut select Value and enter 98 (%) in the adjoining field.

15. Click OK then Close. The graph displays.


Notice that even with a little lower water cut, you can increase the reserves. If you lower the starting water cut even more, the reserves will be increased significantly. However, that is not a good approach in this case. 16. Set up a lower limit on this curve as shown.


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The graph refreshes.

17. Now that you know the value of EUR (~331 Mbbl), and Remaining Reserve (~14 Mbbl), you can get back to the Scenario and schedule your reserves correspondingly.

Exercise 5

Schedule Your Reserves Switch the phase back to Oil; schedule your reserves (Remain or

Total).

P/Z vs. Cum.Gas Analysis In most of OFM projects, pressure data is not adequately available. For each individual well, you may find a scattered set of pressure information, yet usually not enough to conduct an effective analysis. Fortunately, many wells OFM Forecast Analysis Fundamentals May 16, 2005

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may belong to the same entity (i.e. reservoir), and have comparable properties. With other parameters being similar (relatively), their pressure data could also be of the similar ranges. OFM provides this capability of plotting discrete individual pressure points versus grouped (combined) cumulative gas. As the name suggests, we need pressure and gas production data, as well as PVT information. In this lesson, we will create a P/Z vs. Cum.Gas forecast to determine gas recoverables. 1. Check the PVT information first. Select Database>PVT. The PVT Entity Name dialog displays.


2. You should have at least one PVT profile (named Default) in your PVT Entity Name list. Select one, and click Edit. The Edit PVT Information dialog displays. 3. Select the PVT Data tab.


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4. Click OK. 5. Close the PVT Entity Name window. 6. The next thing to do is to load some pressure data into this project. In this Demo2005 project, there is a field in Monthlyprod table named Pressure. That is the field we want to load pressure data into. We will interactively add in pressure data from the Data Editor. Note: You may want to use the Data Loader to load them in, yet you need to create the data file first. 7. From the Filter pane, click the by Completion dialog displays.

Filter by Completion icon. The Filter

8. Select GREEN_6:Li_1C, ORANGE_19:Ad_1A, and RED_4:Cl_3 from the list. Click OK. 9. Click Next button, well GREEN_6:Li_1C displays. 10. Select Database>Data. The Select OFM Table to Edit dialog displays. 11. Select the Monthlyprod table from the table list.


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12. Click OK. 13. In the Pressure column, enter the following: 2900 at 1/1/1981

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2700 at 2/1/1982

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2500 at 5/1/1983

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2300 at 1/1/1985

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2200 at 12/1/1985

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2000 at 7/1/1989

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1900 at 1/1/1992


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14. Click away from the last cell. 15. Click Next to move to ORANGE_19:Ad_1A and enter the following: •

3500 at 1/1/1973

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2800 at 8/1/1981

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2650 at 3/1/1982

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2400 at 11/1/1984

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2100 at 3/1/1987

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1850 at 11/1/1992

16. Click away from the last cell. 17. Click Next to move to RED_4:Cl_3 and enter the following: •

3000 at 4/1/1980


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•

2500 at 1/1/1983

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2000 at 3/1/1988

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1900 at 7/1/1990

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1800 at 11/1/1992

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1700 at 4/1/1994

18. Click away and then close the editing window. 19. Select Group Data then select Analysis>Forecast to open a forecast window (if you do not already have one opened). 20. Select Edit>Scenario Manager and click Edit. 21. Make the selections shown in the image below.

22. Click OK for the graph to be displayed. Take a look at the graph; you can see all individual well’s pressure points plotted together against the combined cumulative gas production. Since we did not specify the initial, current, and abandonment P/Z, OFM uses its default (calculated) values there.


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23. Select Edit > Scenario Manager. The Scenario Manager dialog displays. Click Edit. 24. Verify that the Phase/Analysis is set to PZ and select the Historical Regression Forecast tab. 25. Enter the following: •

4000 (psia) for Initial P/Z

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1800 (psia) for Start P/Z

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800 (psia) for End P/Z


26. Click OK. Observe the result from the Legend box.


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27. Select Edit > Scenario Manager. The Scenario Manager dialog displays. Click Edit. 28. Select the Historical Regression Forecast tab. Select From Fit for Current P/Z and unlock Initial P/Z (you will let OFM determine those values).


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29. Click OK.


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Exercise 6

Performing Gas Forecasting

Return to the Forecast Scenario, switch the phase to gas and perform gas forecasting using the reserves obtained in this lesson.

Question

Compare the result with previous result. What kind of conclusion can you make from this analysis? 30. Click Next to move to GREEN_6:Li_1C. The forecast graph displays.

Exercise 7

Performing Additional Analyses

Perform P/Z vs. Cum.Gas, then Gas Rate vs. Time analyses on the other two wells. Save the results.


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Fetkovich Type Curve Analysis

Chapter 4

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In the last chapter, you have used the empirical solution method to forecast production. That method is based on a set of decline equations (documented in the Online Help, under DCA equations), which also is fundamental for a more advanced technique, Fetkovich Type Curve. Fetkovich Type Curve Analysis uses a set of “type curves” representing the typical performance of ideal (conventional) finite radial (flow) reservoirs. Production data for the entity are plotted against time on a dimensionless loglog scale. The plotted (real) curve is then matched with one of the provided Fetkovich curve, and the real entity can be referenced to the ideal curve. The ideal Fetkovich log-log type curve analysis assumes that the well rates will decline after a period of pseudo-steady state, denoting by a rather flat (constant) rate when it is plotted against time on a log-log scale.

Technically, Fetkovich Type Curve Analysis (TCA) is designed for late-time history matching and should not be applied to early-time analysis. Users are required to “re-initialize” data (to the first point, or close, where the rates start declining).

Learning Objectives In this section, you will learn the basics of Fetkovich TCA functionalities in OFM2005. More advanced analytical skills regarding this method will be addressed in the higher levels of OFM training. You will successfully learn how to perform the following procedures within this workflow: •

Use Fetkovich TCA


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Perform Type Cure Match

Using Fetkovich Type Curve Analysis (Late-Time) 1. Clear any previously applied filter. 2. Expand the Well List node in the Filter pane and select Prod_Wells98.txt. 3. Select BLUE_5:Sc_0. 4. Open a Forecast window. 5. Add a new case named Case3 to the project, so you will not override the previous forecasts. 6. Select Edit>Scenario Manager and set this scenario as the default then click Edit. The Edit Scenario dialog displays. 7. Associate the following on the Flow Model tabbed page.

Notes: •

When you select Fetkovich Type Curve from the Solution list, the other parameters in Model Description section of the dialog are grayed out.


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The known set of reservoir parameters that Fetkovich TCA uses can be read from there. •

If you have dynamic (data loaded into a table, i.e. monthly) pressure data and want to use them, associate the variable at the Flowing Pressure list. Otherwise, you can enter (static) pressure values in the Pressure group box.

•

Once you select either Fetkovich Type Curve or Analytical Transient from the Solution drop-down list, the Historical Regression tab (in Empirical method) disappears and substituted by the Parameters tab.

8. Select the Parameters tab and accept the default parameters to start history matching.


9. Click OK. The graph displays. (You will have to add the header, resize the graph, legend to get the desired output)


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10. Reinitialize your data by right-clicking on the graph. A shortcut menu displays. Select Reinitialize.

11. Position your cursor at your desired data point and click to highlight the point. 12. Right-click and select Done from the shortcut menu. Note: OFM may display a dialog with a Reinitialize Data Tip as shown below. OFM Forecast Analysis Fundamentals May 16, 2005

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13. Click OK. Your data has been reinitialized.

Note: You can also adjust the data fitted curve (Dark Green) by positioning the cursor over that curve and when a hand appears, click the curve and drag it to your desired location then release the mouse. 15. Select Tools>Typecurve Match. OFM runs the matching algorithm and returns the following:


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14. Position your cursor over the real curve until the cursor changes to a fourheaded arrow, drag it and move it (remember the “initial” point of the decline period) closer to the displayed type curves.


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Note: You may get a failure message as the result of this operation. In this case, go back to the Scenario>Parameters tab and adjust the values of your matching parameters and re-run the Typecurve Match command. If you have any questions, please feel free to seek help from your instructor. 16. Select Edit>Scenario. 17. Click on the Parameters tab. Observe that after running the matching algorithm, OFM returns the calculated results for the b value and Permeability, Skin factor, Drainage area (if you are performing both earlyand late-time analysis). 18. Select the Flow Model tab and clear the Late-Time Only checkbox (just an exercise). 19. Close the dialog and rerun the matching algorithm. The program returns a set of parameters. 20. Clear b value and Permeability boxes, check Skin factor and enter 45 in the Estimates box, check Drainage Area and enter 300 in the Estimates box. 21. Click OK. 22. Select Tools>Typecurve Match. The new result returns:


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Question

Compare this with the previous result, what do you see? 23. Select Edit>Scenario. Schlumberger Private

24. Select the Parameters tab. Based on the returned skin factor, you would have a good idea of what the next estimate Skin factor should be. Remember that you can vary all four parameters in your matching criteria. 25. Check the Permeability box, and enter 30 (md). 26. Check the Skin factor box, and enter 60. 27. Check the Drainage area box, and enter 700 (acre). 28. Check the b value box, and enter 0.3. 29. Click OK. If required, re-initialize your data. 30. Select Tools>Typecurve Matching. The graph displays and the results reported in the Legend box are different.


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31. Edit the Scenario. Select the Parameters tab and examine the return values of the matching parameters.

Keep repeating the operation by supplying better estimates, running history match, until you get a good match. Do not forget, these parameters are really important. By changing the values of Wellbore Radius, Net Pay, and Porosity, OFM Forecast Analysis Fundamentals May 16, 2005

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the magnitude of your matching parameters is strongly affected. For example, you can run the matching algorithm with this set of parameters:


Note: Sometimes you will get a matching failure message. One of the reasons could be that it does not converge after a certain number of iterations. Click on the Matching Calculation Settings and this window appears:

Note: You can select to match on production rate, incremental production, or cumulative production. You can also specify the number of iterations and the tolerance.


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32. After running the matching algorithm, OFM returns the calculated match parameters (which normally will be different than the estimates you entered). Click on Update to use the Results as Estimates for the next run, or click on Revert the other way around. Remember, the settings on your Forecast tab are of your default setting (Current Scenario). 33. Select Tools>Forecast. OFM will run the forecast and display the forecast results. Note: Review the values of your reserves in this forecast. You may want to compare it with the forecasts of other methods.

Question

Examine the results. What conclusion can you make? 34. Select Edit>Scenario. 35. Check the Late-Time Only box, and all the pressure information is grayed out. 36. Click OK. 37. Move the real curve closer to the type curves, and then select Tools>Typecurve Match. The result displays:

Note the values in the Legend box. It looks like we’ve got better reserves.


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38. Select Edit>Scenario and select the Parameters tab. You can see in Late Time analysis, the only matching parameter used is the b value.

Note: After running Fetkovich Type Curve analysis (Late Time and all), your matching parameters can be used back in Empirical Solution method to get a better decline estimation.



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Analytical Transient Solutions

Chapter 5

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Fetkovich Type Curve method uses a particular set of reservoir parameters. The applicability of Fetkovich TCA is somewhat limited. OFM allows users to specify different types of reservoirs/formations, based on the phase and the technique that they select to pursue. The new solution (only available in OFM 2002 and later versions) is called Analytical Transient Solution, handling a variety of different parameter combinations. In other words, you can always claim that Fetkovich TCA is a special case of Analytical Transient Solution. The usage of Analytical Transient Solution is very similar to Fetkovich TCA, except that you have to describe your model. Therefore, the users are required to know more about their reservoirs/formations to effectively use this tool. Unwanted results could be the product of incorrectly specifying reservoir parameters and/or matching criteria.

Learning Objectives

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Set up basing forecast case

•

Combine all three solutions

Using Analytical Transient Solutions 1. Make sure that you have a forecast window opened. Select BLUE_5:Sc_0 from the well list. 2. From the Properties pane verify that you are on Oil phase. 3. Select Analytical Transient Solution from the Solution list.


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In this section, you will learn to set up a basic forecast case using Analytical Transient Analysis. (Advanced training on this topic is addressed in other OFM courses.) We will then pull everything that we have learned together to combine all three solutions to perform the forecast on a well that does not have good production data (or does not even have production data). You will successfully learn how to perform the following procedures within this workflow:


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4. Select the Parameters tab. To be consistent with what we did in the Fetkovich TCA lesson, enter the following values: •

Wellbore Radius - 0.2 (ft)

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Net Pay - 20 (ft)

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Porosity - 0.3 (fraction)


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5. Click OK. 6. If your curve has not been reinitialized (from the previous exercise), do it now. 7. Select Tools>Typecurve Match.

Exercise 8

Compare the Results

8. Select Edit>Scenario and select the Parameters tab. Take a look at the returned (matching) parameters:

9. Compare these values with ones obtained from previous Fetkovich TCA. With the formation parameters the same, model description the same, what would possibly be the contributing reason(s) for the differences (if any)? OFM Forecast Analysis Fundamentals May 16, 2005

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Compare this result with the one you obtained using Fetkovich TCA previously. What kind of conclusion can you make? (Pay attention to the model description.)


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10. Select the Flow Model tab. Describe the model as shown below.

Note: Depending on your associated choice in the Model Description, your next choice (in that description) and your match parameters list change. 12. Click OK to display the graph. Re-initialize your data. 13. Move the real curve closer to the type curves (and the fitted data curve) and select Tools>Typecurve Match.


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11. Select the Parameters tab. Specify a Skin Factor of 45 and a Fracture Conductivity of 500. Uncheck the other parameters.

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14. Examine the results on the graph and legend box. Notice that with your model description, you see more type curve parameters such as Cr, Skinf, etc. Examine the results from the Output Window and experiment with the match parameters by different combinations and estimate values.

Exercise 9

Perform an Analytical Transient Analysis

Pick a well of your choice and perform Analytical Transient Analysis on it. Save the result when you are satisfied with it. Note: Let your instructor know what you find in your experience. There will be a lot of interactive learning with this kind of analysis and environment. The next exercise demonstrates the capability of combining all three types of solutions you have learned to forecast oil production on a well that has a brief production history. 15. Select BLUE_1:Ge_6 from the well list. 16. The (Empirical) forecast may display. Notice that with only a few data points, a visual trend may be unreliable. Assume that we know the reservoir model and have formation parameters available; we could start the forecast from a different approach. 17. From the Properties pane select Empirical solution. 18. Change the Fit Type to Hyperbolic method. 19. Locate the b Value properties. Set the Method to User and enter User value of 0.6.


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Note: During this lesson, you will probably encounter quite a few “Type Curve match failure” messages. It is due to either incorrect parameter specifications or the algorithm not converging. Remember that you can specify your own Matching Settings. If needed, change the matching criteria (i.e. match on cumulative rate instead of production rate, increase number of iterations/tolerance). Always keep in mind that anything that you make may affect the validity of your results.


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20. Select Edit > Scenario. The Current Scenario dialog displays. 21. Select the Forecast tab and specify the following:


22. Click OK and the graph shows (you may have to set the limits). 23. Save the forecast.


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24. Select Edit>Scenario. 25. Select the Forecast tab and add Schedule #2. 26. For this schedule, use Analytical Transient Solution method and specify the following on the Forecast tab:



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27. Enter these values on the Parameters tab:

28. Click OK. 29. Select Tools>Typecurve Match.


30. Save the forecast. 31. Select the Forecast tab in the Output Window and find the section for Schedule #2. 32. Select Edit>Scenario. 33. Change Schedule #2 to Empirical. 34. Click OK. The graph displays (both working and saved forecasts). Note: Pay attention to the saved forecast (in Cyan), you can distinguish the two portions of the curve, with different hyperbolic b values.


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35. Select Edit>Scenario. 36. Add Schedule #3. 37. On this schedule, use Fetkovich Type Curve. 38. Specify the following on the Forecast tab:

Start Time – Months from End

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Start Rate – Previous

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End Time – Months from Start and in the adjoining field 36 months

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Decline Type – Exponential

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Decline Rate – User Defined and in the adjoining field 0.3


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39. Click OK. 40. Select Tools>Typecurve Match. 41. Save the forecast. 42. Click on the Forecast tab (Output Window) to check the result. 43. Switch back to Empirical to see the saved forecast.

Exercise 10 Pick a well that does not have good production history (or one that does not have production at all) and do the forecast.


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44. Close the forecast window. 45. Clear the filter and return to the Basemap.



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Retrieving Forecast Results

Chapter 6

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Forecast information (reserves, rates, etc.) can be retrieved via calculated variables and displayed/used in other modules such as report, plot. In this session, we will create variables to return rates on group and individual wells. We will then create variables to return remaining reserves and estimate ultimate recoverables. We will use the forecast results saved in Case1.

Prerequisites Knowledge of calculated variables, plotting, and reporting is a prerequisite in this lesson. If you have any problems, refer to the Online Help (or any training material that applies).

Learning Objectives In this section, you will successfully learn how to perform the following procedures within this workflow: •

Create variables to return remaining reserves

•

Estimate ultimate recoverables

•

Use forecast result

Calculated Variables 1. Create a calculated variable named FCST.OilonGroup to retrieve forecast oil rates on a group of wells. The definition of this variable is: FCST.OilonGroup = @Forecast( date, "oil", "Case1", "group" ) 2. Assign unit to the variable accordingly. 3. Create a calculated variable named FCST.GroupofOil. This variable adds individual forecasts (oil rates) together for a group of wells. The definition of this variable is: FCST.GroupofOil = @Forecast( date, “oil”, “Case1”, “sum” ) 4. Assign unit to the variable accordingly. 5. Create a calculated variable named FCST.RemRes. This variable retrieves (oil) Remaining Reserves for the selected entity (group/well) based on the specified case. The definition is: FCST.RemRes = @DcaResults( "oil RES", "Case1", 1 ) 6. Assign unit and multiplier to the variable.


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7. Create a calculated variable named FCST.EUR. This variable retrieves (oil) Ultimate Recoverables for the selected entity based on the specified case. The definition is: FCST.EUR = @DcaResults( "oil EUR", "Case1", 1) 8. Assign unit and multiplier to the variable. 9. We will use these variables on the report first. 10. From the Filter pane, expand the Well List node. Right-click, select Open and select the Prod_Wells98.txt file. 11. Group the data. 12. Select Analysis>Report to open a report window. 13. Select Edit>Report Parameters. In the Select section of the Edit Report dialog enter Date, Monthlyprod.Oil, FCST.OilonGroup.


14. Click OK. The report displays. 15. Select Edit>Report Parameters. Add FCST.GroupofOil to the report.


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16. Click OK. 17. Use the Next and Previous buttons to navigate through all the wells. As you can see, for individual well the group and the sum options are the same. Thus for individual well, you can even omit this last argument in the variable definition, i.e. @Forecast( Date, “Oil”, “Case1” ). 18. Add the other two variables (FCST.RemRes and FCST.EUR) to the report. 19. Group the data to regroup all the wells in the list. Constant values of Reserves and Recoverables are reported. These values are the results of your forecast on the group, not the sums of individual reserves and recoverables.

Exercise 11

Verify Report Results

Bring up a Forecast window and verify the results (by comparing the retrieved values on the report and the saved values on the forecast). 20. Create a variable named FCST.OilRate. The definition is: FCST.OilRate = @Forecast( Date, "Oil", "Case1" ) 21. Associate the unit properly to the above variable. 22. Add FCST.OilRate to the report as shown below.


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23. Click OK. 24. Scroll down to see the results.

25. Select Tools>Settings>Group. The Settings dialog displays. 26. Check the Sum individual well forecasts when grouping wells option.


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Notice that if you omit the last argument, the @Forecast() function takes the “group” option. (In other words, “group” is the default option). If the variable has been created this way (without the last argument) you still want to retrieve the summed values, you can specify an OFM option from the Tools>Settings menu.

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27. Click OK. Regroup the wells and the report displays. 28. Verify the result. Reverse the operation (by clearing that group option).

Exercise 12

Create Variable to Retrieve Data

Select a few wells and perform forecast on gas phase. Save them to another case. Create variables to retrieve forecast gas rates, reserves, and recoverables. 29. Select Analysis>Plot. The Edit Plot dialog displays. 30. Add the following variables - Plot Oil.CalDay, FCST.OilonGroup and FCST.GroupofOil versus Date. Your plot should look similar to the one pictured below.


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31. Navigate through all the wells in the list and see their plots. On individual well, the two forecast variables are the same. You should expect to see the forecast portion consistent (in trend) to the historical portion. Example:


Exercise 13

Create Bubble and Grid Maps

Create bubble map and grid map of oil RES and EUR. Notes: •

@Forecast() function can only retrieve rates

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@DcaResults() function retrieves constants (i.e., forecast parameters)

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If you perform forecast using ratios or cuts and would like to retrieve those variables, use the @DcaCalc() function

Congratulations! You have completed the OilField Manager – Forecast Analysis Fundamentals course.


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OFM 2005.1 Forecast Analysis Fundamentals

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