Abstract

Seismic lithofacies estimation is a critical element in understanding the stratigraphy and lithology of deep mixed sedimentary (e.g., clastic and carbonate) hydrocarbon reservoirs. In this study, an all-embracing multidisciplinary quantitative analysis on interpretation of reservoir lithofacies and petrophysical property (porosity) description is carried out through the integration of 3D Pre-Stack seismic reflection data and well information (logs). Elastic logs which honored the pore geometric distribution from the well observations using rock physics modeling (RPM) scheme have been used along with pre-conditioned seismic data to make the data more suitable for well to seismic calibration and inversion process. Pre-Stack simultaneous (AVA) inversion is performed to accurately estimate 3D elastic properties (p-impedance and Vp/Vs ratio) which are further used to generate multi-variate lithology probability volumes (e.g., limestones, sand, and shale) to enhance reservoir characterization and geologic model building for the reservoir's units delineation. The lithofacies prediction as well as body checking of the desired lithofacies based on Markov Chain Monte Carlo (MCMC) Bayesian framework is found to be consistent with well observations at the well location and the present geological continuity. Porosity estimation from the multi-attributes approach showed a reasonable match with wells data, and the high porosity clastic (sandstone) rocks are observed to be mostly located in the central and northern fault blocks of the studied field. The interpretation derived from Pre-Stack simultaneous inversion over the mixed sedimentary interval provided a good geological understanding of the target reservoirs in the DS field by generating high-quality geo-models of the desired facies and petrophysical property of the interest for managing the hydrocarbon field.

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