--> Modeling Low Net to Gross Complex Fluvial Reservoir- A Case Study From Aishwariya Field, Barmer Basin, NW India

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Modeling Low Net to Gross Complex Fluvial Reservoir- A Case Study From Aishwariya Field, Barmer Basin, NW India

Abstract

Aishwariya field is one of the major oil fields in Barmer basin, NW India. Fatehgarh formation is primary producing formation deposited in continental fluvial environment in a Paleocene failed rift. The formation is further subdivided unto five subunits. Younger units (FA1 -2) are deposited in low energy fluvial environment; older units (FA3-5) are dominated by multistory braided channel facies associations. The field is in oil production since 2013, currently producing with edge water drive mechanism. Reservoirs deposited in fluvial environment commonly contains significant heterogeneity in facies association; ranging from channel sands, point bar deposits, flood plain mud and crevasse splay deposits etc. The Aishwariya field has relatively low NTG (~20%) with individual channel average width ranges 20-100 m; reservoir modeling in such a low net fluvial reservoir has always been a challenge especially in simulation scale grids. Existing dynamic models struggled to replicate field performance without multiple local modifiers; hence model has limited predictive capabilities. This paper describes how thin channels were integrated into modeling workflow by adopting both top-down and bottom-up approaches. Which is integration of conceptual understanding, regional data, analogues and careful sub-zonation of exiting units based on inter-well connectivity understanding; And, integrating field surveillance and production data into concepts. As modeling workflow- to capture reservoir facies heterogeneity, two facies were classified. The facies classes were grouped on porosity-permeability information by zone and cross-checked against core interpreted depo-facies. The facies were modeled using conventional sequential indicator simulation. Thin sand-bodies and channels were incorporated into model as deterministic objects. The updated static model honors regional depositional trends and reasonably captures local fluvial bodies. The static model is now able to explain the reservoir connectivity issue, especially in low energy fluvial reservoir units (FA1-2). Updated dynamic reservoir model is able to closely replicate water flood performance and have shown a significant improvement in matching high water cut wells without local modifiers as compared to previous model. This indicates that the modeled depositional heterogeneity reflects field geological complexity and provides a better basis for estimating ultimate recovery and production forecast.