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Ahead of Print Abstract
DOI:10.1306/04292523089
Fracture characterization from core and image log integration at Tengiz and Korolev fields, Kazakhstan
Ted Playton1 , Evan Earnest2 , Fermín Fernández-Ibáñez3 , Assem Bibolova4 , Dana Tolessin4 , Ilyas Tussupbayev4 , and Bagdat Toleubay4
1 Chevron Americas Exploration (formerly Tengizchevroil), 1500 Louisiana Street, Houston, Texas
2 Chevron Technology Center, 1500 Louisiana Street, Houston, Texas
3 Subsurface Alliance LLC, 23919 Enchanted Crossing, Katy, Texas, (formerly ExxonMobil Upstream Research Company)
4 Tengizchevroil, 3 Satpayev Street, Atyrau, Kazakhstan
Ahead of Print Abstract
The Tengiz and Korolev fields are carbonate reservoirs in western Kazakhstan with substantial oil production in part fed from naturally formed non-matrix networks (here defined as fractures, karst caverns, and smaller karst features). Borehole Image (BHI) logs are the primary tool for identifying and documenting fractures and karst caverns at wells due to their substantial reservoir coverage; however, core datasets, although much more spatially limited, provide critical ground truth for fracture presence and other characteristics. Utilizing established approaches, rigorous calibration of BHI-based fracture picks with core reveals that a considerable percentage of BHI picks did not represent natural fractures (false picks), and furthermore, some obvious natural fractures observed in core were not clearly detectable in BHI logs (missed fractures). Mining our calibration data, we found relationships with BHI pick attributes (e.g., sinusoid continuity) and geologic setting (e.g., environment of deposition; EoD) that allowed development of corrective measures to account for false picks and missed fractures away from core control, as well as guidelines to predict fracture openness and genetic fracture type. Corrected BHI fracture picks, when integrated with dynamic data, karst caverns interpreted from logs, and fracture openness relationships from core, allow for multiple fracture-karst density realizations at wells to capture a range of reservoir scenarios for static modeling. This study highlights the value of core in addressing the limitations and improving the accuracy of log-based fracture characterization and can be applied to other fields and reservoir settings.
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