| Autor: |
Peter E. K. Deveugle, Martyn D. Clough, James K. Miller, Matthew D. Jackson, Thaddeus Ehighebolo, Gary J. Hampson, Michael E. Farrell, Craig S. Calvert, Jonathan Stewart |
| Rok vydání: |
2014 |
| Předmět: |
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| Zdroj: |
AAPG Bulletin. 98:729-763 |
| ISSN: |
0149-1423 |
| DOI: |
10.1306/08281313035 |
| Popis: |
Multiple techniques are available to construct three-dimensional reservoir models. This study uses comparative analysis to test the impact of applying four commonly used stochastic modeling techniques to capture geologic heterogeneity and fluid-flow behavior in fluvial-dominated deltaic reservoirs of complex facies architecture: (1) sequential indicator simulation; (2) object-based modeling; (3) multiple-point statistics (MPS); and (4) spectral component geologic modeling. A reference for comparison is provided by a high-resolution model of an outcrop analog that captures facies architecture at the scale of parasequences, delta lobes, and facies-association belts. A sparse, pseudosubsurface data set extracted from the reference model is used to condition models constructed using each stochastic reservoir modeling technique. Models constructed using all four algorithms fail to match the facies-association proportions of the reference model because they are conditioned to well data that sample a small, unrepresentative volume of the reservoir. Simulated sweep efficiency is determined by the degree to which the modeling algorithms reproduce two aspects of facies architecture that control sand-body connectivity: (1) the abundance, continuity, and orientation of channelized fluvial sand bodies; and (2) the lateral continuity of barriers to vertical flow associated with flooding surfaces. The MPS algorithm performs best in this regard. However, the static and dynamic performance of the models (as measured against facies-association proportions, facies architecture, and recovery factor of the reference model) is more dependent on the quality and quantity of conditioning data and on the interpreted geologic scenario(s) implicit in the models than on the choice of modeling technique. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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