‌Intrduction to Reservoir Facies Modeling

Introduction to Reservoir Facies Modeling Slide 1

Key Points: This is a porosity modeling exercise using a purely statistical approach.

Additional Additional Notes: Notes: Using audience interaction, provide a porosity modeling exercise using a purely statistical approach; a conventional geostatistical approach and a geological interpretation-based approach (reservoir facies modeling). Point out that this approach approach helps you interpret the data collect collected ed from from the field to be able to make reliable predictions. If we think about geostatistics, we really have to go back to the origins of geostatistics. It's about making estimates within space. It's about having data available to us within some area of interest and looking at that data and asking the question, "Given that data, what could be going on at that location right there?" If I was to ask you the question, what is the value of the porosity units of porosity at that location, that unknown location, what would you say? You could average the numbers and come up with 15%. Other possible answers might include taking the value of the nearest neighbor or averaging the values. You could do a distance weighted average. Easy to do and commonly commonly employed. But is this the best solution? ES - Reservoir Facies Modeling in Petrel: Petrel: The MPS/FDM Workflow

Slide # 1


Key Points: This is a porosity modeling exercise using a conventional geostatistical approach.

The conventional geostatistical approach that accounts for distance to data and for trends is Kriging. Kriging was developed in the 1940s for gold mining and adopted in the petroleum industry in the 80s. Additional Additional Notes: Notes: There is another way to do this, using a conventional geostatistical approach. Another option is to account for a whole model of spatial continuity. Kriging would be a method to do that. If we account for the distance to the data and for the trends and for spatial continuity, we're effectively doing kriging. Kriging developed in the 1940s, gold mining adopted in the petroleum industry in the 1980s and was developed by Danny Krige.

Using this approach, we come up with 18%.

ES - Reservoir Facies Modeling in Petrel: Petrel: The MPS/FDM Workflow

Slide # 2


Key Points: This is a porosity modeling exercise using a geological interpretation approach.

Field data are typically: 

Either sparse (wells), thus need interpolation and/or extrapolation

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Ambiguous (seismic), thus need calibration

Geological interpretation consists in developing a story to interpolate, extrapolate and calibrate these sparse and ambiguous data.

Additional Notes: You could also use geological interpretation. What if you had a geologic interpretation that blue meant a channel, red meant overbank? What would you do now? What would you do if the channel went like this? Now our answer is 22% Field data are typically either sparse and need interpolation and/or extrapolation or ambiguous (seismic). ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow

Slide # 3


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Geologic and interpretation consist of developing a story to interpolate, extrapolate. You calibrate this sparse and ambiguous data into one consistent framework. l

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Additional Notes: Geologic interpretation consist of developing a story to interpolate, extrapolate. You calibrate this sparse and ambiguous data into one consistent framework. If we look at what we actually do within reservoir modeling, we have our data sets available to us. There's a lot of good data available to us. We have seismic data that gives us the framework, gives us structure and correlation styles. There's a lot of sequence stratigraphy we can do with it. Core data, which provides us really good exhaustive data, sample directly from the reservoir. r i t y /

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We get to actually see the reservoir, but sampled at what level of coverage? What fraction of the reservoir do you think we actually extract with cores? A trillionth of the reservoir, a billionth of the reservoir. In most scientific areas, people won't even consider making too much inference with that level of information, but we have to. That's inherent to our problem. t i

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Slide # 4


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The geological interpretation (the “story”) plays a critical role to ensure that the reservoir models do not violate any fundamental geological knowledge, which would make resulting flow performance forecasting unreliable. l

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The importance of the conceptual geological model depends on the amount of data available: f

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In green fields, with only a few wells, the conceptual geological model plays a central role; l i l

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In mature fields with dense well data or good quality high resolution seismic, purely statistical approaches can be applied. h

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The geological interpretation is most often uncertain. In most projects, alternative conceptual geological models need to be considered as part of a probabilistic modeling approach. i c l

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Slide # 5


Key Points: 

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Reservoir Connectivity: Consider how are low and/or high poro/perm values connected (barriers and flow paths).

Reservoir Heterogeneity or Spatial Distribution: Consider where are the low and/or high poro/perm values located.

In most reservoirs, porosity, permeability, connectivity, and spatial distributions are very complicated and extremely difficult to describe or model directly. Additional Notes: Questions to answer from Data Analysis or Geological Interpretation when building reservoir models. What are we concerned about?

In most reservoirs, porosity, permeability, connectivity, and spatial distributions are very complicated and extremely difficult to describe or model directly.

ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow

Slide # 6


Key Points: 



In most reservoirs, poro/perm connectivity and spatial distribution are very complex and extremely difficult to describe and model directly It is typically impossible for geologists to provide a conceptual model of poro/perm, i.e. to articulate a story using the poro/perm language Instead, geologists can interpret the reservoir as a combination of multiple poro/perm populations (or facies) defined by specific value ranges and/or continuity patterns

Additional Notes: “Mean” would not be a good statistics to use. Nor is “mode” a g ood statistic for this situation. You have to actually split this up spatially. When you do that, what you hope to see is you'll actually divide the statistics, the histogram in a way that it will be rational. That's the balancing act with the whole idea of breaking things up in facies. If you want to break it up, so that you separate the statistics, so that you can make sense of those, that you separate highs and lows or what, and you want to also separate it, so that it's mappable. The geologist can interpret reservoir as a combination of multiple porosity permeability populations or facies, defined by a specific value ranges and or continuity patterns. Value ranges continuity patterns. Those are very important concepts. If your facies are doing a wonderful job of separating the values, if there are distinct distributions, but provides you no information about how to map them, that's not useful either. Because at the end of the day, we need to map things. If your facies provide good spatial separation, but the distributions are ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow

Slide # 7

Introduction to Reservoir Facies Modeling

still the same, that's not useful either, because it's not actually pulling apart high and low porosity values. It's not providing information. If you have facies where all the porosity, permeability’s are the same, it's not going to have any impact anyway.

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ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow y

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Slide # 7


Key Points: Facies Definition: “A body of rock characterized by a particular combination of lithology, physical and/or biological structures that bestow an aspect (“facies”) different from the bodies of rock above, below and laterally adjacent” (from Walker and James, 1992). There are many different types of facies. Facies Association Definition: “Groups of facies genetically related to one another with a progressive succession and which have some environmental significance” (modified from Collinson, 1969) Grouping rocks into facies and facies successions greatly assists with the interpretation of geological environments.

Additional Notes: Facies, a value of rock characterized by a particular combination of lithology, physical, and biological structures that bestow an aspect different from the bodies above, below, and laterally adjacent. Some characteristic of the rock that's different than the rock near it. A way to separate and distinct rock from each other.

There are many different types of facies, which we'll describe the next few slides. We'll tell you, we have some favorites. In general, we have facies, and then we have facies associations. Facies associations tend to be ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow

Slide # 8

Introduction to Reservoir Facies Modeling

groups of genetically related facies with progressive succession which have some environmental significance. It means that they can be grouped together. They have progressive successions, so they have similarity to each other, and they have environmental significance which usually means they're mappable. There's a reason that they're mappable. There's a good process understanding. Grouping rock into facies or facies successions greatly assist in interpretation of geologic environments.

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Slide # 8


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“Facies” needs an adjective to indicate what type of facies is being described otherwise it’s too general. i c t

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In this section, we’ll focus more on the first two types of facies: Lithofacies and depositional facies.


Slide # 9


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Lithofacies are “ a defined a body of sedimentary strata which distinguished and delimited on the basis of lithic, physical characteristics and stratigraphic position.” Lithofacies are internally lithologically homogeneous. l i t h l

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Examples of lithofacies are clastics and carbonates.

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Some example of clastic lithofacies are sand, silt, shale and conglomerate. These are based on the type/size of grains that comprise the rock. :

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Some carbonate lithofacies include grainstone, packstone, wackestone and mudstone. These are primarily based on the amount of grainstone vs mud in the rock, with grainstones have the greatest amount of grains and mudstone the least. i l t

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Lithofacies focuses also on separating by lithologic physical properties, so it tends to do a very good job of separating porosity, permeability distributions, the statistics, but they don't tend to be quite as mappable as depofacies. r i n t

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Slide # 10


Key Points: “An association of facies deposited within a geographic environment that can be defined by a given depositional process, geometry, lithology, and/or biota.” Depositional facies tend to be synchronous (deposited during a given time interval), and therefore, predictive of adjacent and superposed facies. Additional Notes: Key point of the definition is that they are synchronous – i.e., deposited during the same time interval, therefore, they are predictive unlike lithofacies. They are predictive in both a lateral and vertical sense because they fit nicely into a conceptual depositional system model and you know what facies associations to expect when you see a given depositional facies. Being predictive is key to building a useful reservoir model. Some example of clastic depositional facies are…….., these are components of different larger -scale depositional systems. Each depositional system contains several different depositional facies, organized in a predictable fashion. Ex: mouth bars are at the end of fluvial channels, splays are on the sides of channels, upper shoreface is landward of lower shoreface, etc. Some carbonate depositional facies include……, car bonate depositional facies are not quite as clear cut as clastic depositional facies. They are commonly termed environments of deposition (EODs) and tend to occur in belts. Ex: a ramp setting contains a linear belt of carbonate EODs, whereas a carbonate platform EOD may contain circular belts. ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow

Slide # 11


Key Points: Lithofacies: 

easy to define; e.g. using poro/perm cut-offs

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but difficult to describe connectivity and spatial distribution

Depositional facies: 

combinations of lithofacies; requires well log interpretation and core data calibration

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conceptual models of depositional facies well established (language of geologists!)

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Model depositional facies if primary control on poro/perm distribution.

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If post-depositional phenomena occur and have a major impact on poro/perm (e.g. diagenesis, fractures), consider other types of facies.

Additional Notes: These are not extreme hard boundaries. It's not a binary system. It's not one or the other. You can make a choice to merge the concepts from both. That's definitely part of what we're doing. It's part of the balancing act. ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow

Slide # 12


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These are examples of depositional conceptual models. All of these are different types of information that could be mined from this type of conceptual model. They provide these concepts that we can then use within our models. Additional Notes: These are examples of depositional conceptual models. All of these are different types of information that could be mined from this type of conceptual model. They provide these concepts that we can then use within our models.


Slide # 13


Key Points: Classifications for different depositional systems have been developed over the last several years at Chevron: 

Deepwater Classification System

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Wave-Dominated Shorelines Reservoir Architecture Classification

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Fluvial Res

Classification systems were built from: 

Modern analogs

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Outcrop studies

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High-resolution seismic data

Additional Notes: Classifications of different depositional systems have been developed over last several years. Deep water classification system is probably the most mature of all of them. They've been doing it longer. Classification systems were built from modern analogs. This is a picture taken by Sebastien Strebelle while flying. He took this picture a course of a barrier bar or a barrier island while flying across the shore. The next one is what you can see in the outcrop study – perhaps the ross formation. The third is high-resolution seismic data. ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow

Slide # 14


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Key Points: Use all available data to identify the right depositional setting. There's a lot we can do to identify which one of these we should be in. If in doubt, we can choose more than one and put it through our management plan. Additional Notes: Great scheme here where they separate the different types of depositional settings based on fundamental concepts, and they relate those concepts to gradient of the system and to the slope profile. Different types of architectural building blocks, different stacking patterns, different types of geometries, These basic building blocks are going to be those depositional facies.

Ask How do we identify the right depositional setting if we're the reservoir modeler and we have the scheme? Answer: Using all available data. There's a lot we can do to identify which one of these we should be in. If in doubt, we can choose more than one and put it through our management plan.


Slide # 15


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Sequence stratigraphy is really about linking large scale architecture and geometry stratal patterns from the conceptual models down to the fine scale rock types of facies depositional environments, petrophysical properties that we observe within our cores and our logs in which we need to use for the purpose of reservoir modeling. f c i ,

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Sequence stratigraphy is really about linking large scale architecture and geometry stratal patterns from the conceptual models down to the fine scale rock types of facies depositional environments, petrophysical properties that we observe within our cores and our logs in which we need to use for the purpose of reservoir modeling. f r

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Explains very simply why we want to use sequence stratigraphy, ie, the links it provides. Gives you the correct large-scale architecture, etc, but also ties into what you say in your MPS lecture about the geobodies being the containers that hold the petrophysical properties.

Also stress the predictive nature of sequence stratigraphy, both depositional facies in both lateral and vertical sense, but also scale issue – it consists of a hierarchy that is predictable from small-scale to large-scale. ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow

Slide # 16


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Key Points: Sequence stratigraphy is all about that ability to map out and to have a consistent story over time of how the reservoir evolved. The data that goes into that type of model will of course be the data such as well logs that are available to us.

Additional Notes: If we will look at this block diagram right here, sequence stratigraphy would tell us important concepts that if we observe this up-dip, we should observe something different down-dip at the gradient changed. We should expect that the architecture will have certain features in stacking patterns and time correlatable bodies.


Slide # 17


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Deepwater channels and sheets are the primary deepwater reservoir facies; they have very different connectivity and spatial distribution n

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Well log signatures can be analyzed and interpreted l l l

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Using these concepts that we observed within outcrop and other types of data settings, we're able to work out from well logs what type of large scale sequence stratigraphics constraints we have on our reservoir model: whether it is sheets, channels, etc. l y

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It might seem odd that you can take a one dimensional well log and be able to actually figure out large scale sequence stratigraphic concepts, but in fact, we can do it.

Using these concepts that we observed within outcrop and other types of data settings, we're able to work out from well logs what type of large scale sequence stratigraphics type of constraints we have on our reservoir model: whether it is sheets, channels, etc.


Slide # 18


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There is a range of channel architecture and channel fills that provides a full range of internal poro/perm connectivity and spatial distribution: h

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Amalgamated channel fills Semi-amalgamated channel fills

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Internal depositional facies associations can also determine not just channels and sheets, but whether or not we have more axial type of a fill of a channel. i

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ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow t

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Slide # 19


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Key Points: Core data interpretation as well as OBMI, can help us get more info on texture, texture changes tell us about depositional processes, depositional processes tell us about geometries and the size of geobodies and so forth.


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Key Points: 

Petrophysical Rock Types (PRTs)are the category of rocks which: r i

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Exhibit distinct relationships relevant for flow characterization; u r v y ;

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Are identified by logging surveys; and r

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Are linked to geological attributes like primary texture or diagenetic modifications.” t

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In carbonate settings things are more complicated. You don't have the same level of constraint on geometries, and things can get more mixed up, so they tend to use petrophysical rock types. PRTs are characterized by specific ranges of petrophysical properties, permeability, porosity. You look at these trends. They break those up into petrophysical rock types. They exhibit distinct relationships relevant for full characterization identified from logging surveys or linked to geologic attributes like primary texture or diagenetic alterations modifications. r i

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Slide # 21


Key Points: Facies should be considered whenever populations with significantly different porosity permeability distributions can be identified, interpreted, characterized, separated, mapped, and it does a better job of getting porosity, permeability. When you find that facies does not help you build better porosity permeability models, that is when we don't use facies. Factors influencing the impact of facies modeling: 

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Project relative uncertainties; e.g., reservoir OOIP can be a uncertainty source much more important than reservoir internal architecture for green fields Reservoir with very high good-reservoir facies proportions (note that percolation theory does not apply to heterogeneous reservoirs)

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Type of fluid (gas vs. oil)

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Data availability (e.g., brown fields with 10,000 wells)

Additional Notes: Facies should be considered whenever populations with significantly different porosity permeability distributions can be identified, interpreted, characterized, separated, mapped, and it does a better job of getting porosity, permeability. When you find that facies does not help you build better porosity permeability models is when we don't use facies.


Slide # 22


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In reservoir modeling projects, there is typically a need to supplement sparse and ambiguous field data with an interpretation of the expected geological features: the conceptual geological model l

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Although porosity and permeability are the two properties that we ultimately want to model, they are extremely difficult to model directly. Facies modeling is most often a necessary intermediate step. r t h t

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Depositional facies are typically modeled in clastic reservoirs. In carbonates, modeling PRT’s is the current best practice t

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ES - Reservoir Facies Modeling in Petrel: The MPS/FDM Workflow r t y i c l l y m

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Slide # 23

‌Intrduction to Reservoir Facies Modeling

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