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Quantifying fracture density within the Asmari reservoir: an integrated analysis of borehole images, cores, and mud loss data to assess fracture-induced effects on oil production in the Southwestern Iranian Region
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Quantifying fracture density within the Asmari reservoir: an integrated analysis of borehole images, cores, and mud loss data to assess fracture-induced effects on oil production in the Southwestern Iranian Region
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Quantifying fracture density within the Asmari reservoir: an integrated analysis of borehole images, cores, and mud loss data to assess fracture-induced effects on oil production in the Southwestern Iranian Region
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Journal Article
Quantifying fracture density within the Asmari reservoir: an integrated analysis of borehole images, cores, and mud loss data to assess fracture-induced effects on oil production in the Southwestern Iranian Region
2024
Overview
Oil and gas production from carbonate reservoirs heavily depends on the extent of fracture propagation in the producing formations. Detecting fractures in subsurface rock formations is challenging due to their potential impact on oil production, fluid movement, reservoir connectivity to wells, and hydrocarbon production methods. Therefore, detecting fractures and quantifying their characteristics in carbonate reservoirs is of utmost importance. Detecting fractures in subsurface rock formations is challenging due to their potential impact on oil production, fluid movement, reservoir connectivity to wells, and hydrocarbon production methods. This study identifies natural fractures in the Asmari reservoir (with Eligo-Miocene age and Cenozoic era) of an oil field in Southern Iran. The Asmari carbonate reservoir owes most of its hydrocarbon production to natural fractures. This study uses image logs, drilling cores, maximum flow rate, and mud loss data to analyze fractures in reservoirs due to their complexities and limitations, including high cost, non-directionality, and low recovery coefficient in fractured zones. Data from cores and full-bore Formation MicroImager (FMI) logs acquired from five wells drilled into this reservoir identify fractures and enhance our understanding of their effect on hydrocarbon production. In addition, by analyzing the image logs and creating rose diagrams of fractures, a better interpretation of the dip and direction of the fractures on the fault map is obtained. As a result, it was found that the density of the fractures and faults calculated from image logs corresponds closely with the bubble map of mud loss and maximum flow rate in the production sections of the reservoir. According to the extent of the Asmari reservoir anticline, in three sectors
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including northwest, southwest, and central areas, where the highest fracture density is detected, bubble maps of mud loss and flow rate index also show the highest values.
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