Computer modeling of terrigenous sedimentation as a new tool for prediction of hydrocarbon reservoir architecture
https://doi.org/10.7868/S2587739920020019
Abstract
The subject of the article is a new approach based on the integration of seismic facies analysis with modeling of sedimentation system – submarine fan, which is a potential lithological trap. The new approach allows introducing sedimentation systems modeling into the traditional process of seismic data interpretation. The approach was tested on data of the target interval in Cherkashin formation (West Siberia, Priobskoye-Salym region, Neocomian progradation complex). The presence of submarine fans selected as test-subjects for modeling is confirmed by lithofacial analysis, distribution of effective thicknesses over the area according to drilling results, seismic facies analysis. Two criteria were used to evaluate the simulation results: compare the shape of the model with the results of seismic facies analysis and comparison of the parameters describing the geological process and selected in the modeling process with modern data on turbidite systems. Modeling of submarine fan sedimentation was carried out in the Geological Process Modeling (GPM) module of the Petrel software (Schlumberger), Seismic Facies Analysis – in tratimagic software (Emerson). The approach can be recommended for studying of deep-water Achimov deposits; predicting the development of the distal parts of the submarine fan, not evident in the seismic data and predicting the internal architecture of the potential lithological traps.
About the Authors
T. V. Olneva
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
V. Yu. Ovechkina
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
E. A. Zhukovskaia
Gazpromneft NTC LLC
Russian Federation
Russian Federation
Saint-Petersburg
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Review
For citations:
Olneva T.V., Ovechkina V.Yu., Zhukovskaia E.A. Computer modeling of terrigenous sedimentation as a new tool for prediction of hydrocarbon reservoir architecture. PROneft. Professionally about Oil. 2020;(2):12-17. (In Russ.) https://doi.org/10.7868/S2587739920020019
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