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Abstract
Carbonate reservoirs are very prone to diagenetic modification of pre-existing fabrics. The process around the modification of pre-existing depositional fabrics is often interrelated with diagenetic phases that impact reservoir quality and distribution. Characterization and 3D modeling of these features have always been a challenge in the upstream industry. This paper outlines a novel workflow for characterizing and modeling the Integrated Diagenetic-Depositional Facies (IDDF) in carbonate reservoirs, from 1D IDDF classification and Neural Network (NN) estimation, to 2D IDDF trend and seismic-based probability region modeling, culminating with the 3D geo-cellular modeling processes. The workflow integrates several geoscience data sets including; linking of petrographic thin sections analyses with other scales of data from core descriptions, well-logs signatures, Routine Core Analyses (RCA), Production Logging Tool (PLT) inflow analyses, diagenetic proxies and depositional concepts. The IDDF workflow ties these features with 3D seismic attribute region extraction to benefit 3D geo-cellular property modeling. This workflow greatly improves reservoir quality prediction, 3D reservoir modeling and volume estimation.
Published Version
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