Keywords
RMS amplitude
Seismic attribute
Facies architecture
Carbonate reservoirs
Petrophysical properties
How to Cite
Abstract
Carbonate reservoirs present significant challenges in characterizing and extracting hydrocarbons due to their low permeability, matrix heterogeneities, fractures, and dissolution patterns. Accurately predicting the facies architecture and reservoir properties in such complex formations has been a persistent challenge for geoscientists.
This paper proposes an integrated approach that combines geo-body extraction and geostatistical modeling to accurately predict the facies architecture and reservoir properties in carbonate reservoirs. The methodology begins by generating 3D seismic root mean square amplitude (RMS) attributes, which are then used to extract geo-bodies along the pay sequences. The extracted geo-bodies are then subjected to geostatistical modeling to analyze reservoir properties to facilitate the optimization of drilling and production strategies.
To validate the effectiveness of the proposed approach, a small field in the Mumbai offshore basin is chosen as a case study. This field is located on the Mumbai High-Deep Continental Shelf and exhibits westerly dipping structures. Structural mapping confirms the presence of an antiformal structure, with one particular well (D-8) at the crest showing the absence of hydrocarbons.
The proposed approach mapped two seismic reflectors within the reservoir zones and generated window-based 3D seismic RMS attributes to extract three geo-bodies within the reservoir. Facies and property modeling revealed the presence of distinct non-reservoir facies with poor reservoir properties near dry wells (D-8, D-4, and D-7), which is in line with the production performance observed in the drilled wells.
The proposed integrated approach of geo-body extraction and geostatistical modeling is effective in delineating the facies architecture and reservoir heterogeneity of carbonate reservoirs. It enables the identification of favorable reservoir facies and facilitates a comprehensive assessment of the remaining potential.
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