Advances in Simulation of Stratigraphic-Structural Evolution of Basin Fill: A Retrospective to Guide Future Progress
The oil and gas industry relies heavily on inverse geostatistical modeling to predict static reservoir properties that influence hydrocarbon accumulation and flow. However, these methods face significant challenges due to sparse sampling and the inability to capture reservoir variability beyond bore...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | International Journal of Geophysics |
| Online Access: | http://dx.doi.org/10.1155/ijge/2790962 |
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| Summary: | The oil and gas industry relies heavily on inverse geostatistical modeling to predict static reservoir properties that influence hydrocarbon accumulation and flow. However, these methods face significant challenges due to sparse sampling and the inability to capture reservoir variability beyond boreholes. Geostatistical techniques typically depend on borehole data, which represent only a small fraction of the total reservoir volume. The large distances between boreholes further hinder the ability to achieve reliable and accurate predictions. An innovative approach in numerical forward modeling, the stratigraphic-structural forward modeling (SSFM) technique, offers an alternative or complementary workflow for modeling facies and property distribution in static reservoir models. The SSFM quantitatively integrates sedimentation and deformation processes in basins, grounded in the physics of basin formation, infill, and sedimentary architecture. By translating conceptual geological models into cellular geological volumes, SSFM requires minimal borehole and seismic data for validation. This review traces the historical evolution of various numerical techniques, with particular emphasis on the advancements and limitations of SSFM. However, these limitations present opportunities for guiding future research, fostering development in the field, and extending the application of SSFM techniques beyond hydrocarbon exploration. Understanding and addressing SSFM’s limitations is essential to optimizing and enhancing its effectiveness within the industry. |
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| ISSN: | 1687-8868 |