ehsan golmohamadi

One of the significant challenges in studying the oil and gas fields is assessing the fractured reservoirs. The existence of such fractures plays a crucial role in productivity and the amount of final offtake from hydrocarbon reservoirs, specifically, in carbonate formation. Hence, presenting a practical method in the identification and determination of fractures intensity is necessary. Image log tools are the first informative references in studying the fractured reservoir by which geologists can identify the details of layers, faults, fractures, and lithological status. FMI (Fullbore formation microimager) image logs are powerful tools in identifying fractures in wellbore surroundings. FMI image logs are indirect images with high resolution from wellbores. This study aims to employ the FMI image logs and optimal seismic attributes in assessing the fracture distribution in the field that we are about to study. To reach the target, 3D post-stack seismic data and FMI image log data of three wells (A, B, and C) that existed in the field are deployed. Two out of three wells (A and B) are utilized for determination and identification, and the third well (C) is utilized for validation which such identifications are carried out by “Geolog” software. As a result, fractures were identified in well A with a total of 152 open and closed fractures with a general trend of northeast-southwest, in well B with a total of 235 open and closed fractures with a general trend of north-south, and zones with high fracture density were determined. Therefore, with the usage of optimal seismic attributes in the “Hampson Russell”, the fracture density in the whole field was determined. Moreover, by using the distribution of fracture density, the field faults were determined. The results show that using the integration of FMI Image logs and seismic attributes is a practical method in studying and assessing the fracture distribution in fractured reservoirs.