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PSCarbonate Reservoir Modeling Using Multiple-Point Statistics (MPS) / Previous HitFaciesNext Hit Distribution Modeling (FDM)*

By

Marjorie Levy1, Paul M. (Mitch) Harris1, and Sebastien Strebelle1

 

Search and Discovery Article #40293 (2008)

Posted August 1, 2008

 

*Adapted from poster presentation at AAPG Annual Convention, Houston Texas, April 9-12, 2006.

Click to view list of articles adapted from presentations by P.M. (Mitch) Harris or by his co-workers and him at AAPG meetings from 2000 to 2008.

 

1 Chevron Energy Technology Company, San Ramon, California, USA ([email protected]; [email protected]; [email protected])

 

Abstract

We have explored the use of MPS/FDM modeling in a carbonate reservoir. We have modeled the platform top of an isolated platform example and tested various scenarios for the distribution of grainstone Previous HitfaciesNext Hit.

The training image is a 3D conceptual model of the reservoir, containing information about Previous HitfaciesNext Hit dimensions and relationships among Previous HitfaciesNext Hit. Five Previous HitfaciesNext Hit were considered: Bar crest = best reservoir quality due to sorting in “highest energy” setting; Bar flank = good reservoir quality between bar crests, includes flanks of bars and intervening tidal channels; Island = localized areas where permeability is enhanced by dissolution during meteoric diagenesis; Deeper platform = poorer reservoir quality in platform areas away from bars and channels; and Background = “tight” intervals due to muddier Previous HitfaciesNext Hit or to porosity-plugging cementation.

The Previous HitfaciesNext Hit probability cube allows controlling the spatial distribution of the Previous HitfaciesNext Hit in the MPS model. First, Previous HitfaciesNext Hit depocenter maps were generated for deeper platform, bar flank, bar crest and island. Then, the stratigraphy of the reservoir was modeled by digitizing a vertical proportion curve reflecting the variations of Previous HitfaciesNext Hit proportions with depth. Three alternative vertical proportion curves were created, representing respectively a gradual trend, cyclicity at the scale of composite sequences, and high cyclicity at the scale of individual sequences. Corresponding alternative Previous HitfaciesNext Hit probability cubes were generated for these three cases.

Several scenarios were run: the gradual, cyclic and highly cyclic cases; both narrow and wide bar crests and bar flanks; and with constant and variable azimuth. The wide bar crest/bar flank and very cyclic simulation produce results that qualitatively appear most reasonable in both cross section and Previous HitmapNext Hit views.

 

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MPS (Multiple-Point Statistics)

MPS is an innovative depositional Previous HitfaciesNext Hit modeling technique, developed by Chevron in collaboration with Stanford University, that uses 3D conceptual geological models as training images to integrate geological information into reservoir models. Replacing the traditional variogram with a training image allows MPS to capture complex spatial relationships between multiple Previous HitfaciesNext Hit, and to model non-linear shapes such as sinuous channels that conventional variogram-based modeling techniques typically fail to reproduce. In addition, because MPS is not an object-based, but still a pixel-based algorithm, MPS models can be constrained by very large numbers of wells and 3D Previous HitfaciesNext Hit probability cubes derived from seismic data or from reservoir Previous HitfaciesNext Hit deposition interpretation (using FDM).

For the last three years, the MPS/FDM workflow has been preferred to variogram-based and object-based techniques to model important Chevron assets both shallow-water clastic reservoirs (Indonesia and Angola), and deepwater reservoirs (Gulf of Mexico, North Sea, Angola, and Nigeria). In those projects, the MPS/FDM workflow enabled the generation of geologically realistic Previous HitfaciesNext Hit models, which significantly improved reservoir OOIP and oil recovery uncertainty assessment.

 

Carbonate Reservoir Modeling Example Using MPS/FDM

1. Workflow.

2. Study rationale.

3. Model region and layering.

4. Build training images.

5. Generate Previous HitfaciesNext Hit probability cube.

6. Add well data conditioning and other modeling constraints.

7. Run MPS simulation.

8. Model summary.

Matches Previous HitfaciesNext Hit regions of platform top which were defined during reservoir characterization; Matches stratigraphic variation defined during sequence stratigraphy studies with Previous HitfaciesNext Hit proportion curves; Matches conceptual models for Previous HitfaciesNext Hit types from modern analogs with training images; Generally matches Previous HitfaciesNext Hit identified in cored wells.

 

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