SEISMIC ATTRIBUTES AIDED DETECTION OF NW-SE TRENDING FAULTS DEVELOPED ON AN ISOLATED CARBONATE PLATFORM IN THE NW SIRTE BASIN, NORTH CENTRAL LIBYA

Abstract

The lower and upper Paleocene reservoir formations, the primary producing formations in the northwest Sirte Basin, north-central Libya have complex structures which have an impact on the performance of the reservoirs. It is extremely crucial to understand the complex relationships between the fault networks and stratigraphy of the area for future field development. However, delineating faults particularly subtle faults is not an easy process due to the low signal-to-noise ratio in the post stack seismic data despite the effort and careful process of the pre-stack data. Seismic attributes are critical tools in detecting and enhancing major and minor fault interpretation beyond the seismic resolution of the conventional seismic dataset. This study utilizes variance, root mean square, and curvature attributes computed from the post-stack 3D seismic data acquired in the northwest Sirte Basin to detect major and minor faults along an isolated carbonate platform. A spectral whitening and median filter were applied to improve the quality of the data and remove random noise resulted from data acquisition and processing steps. Those methods were utilized to provide high-resolution seismic data and better show edges and structural features. Numerous faults have been detected in the study area. Most major faults in the lower and upper Paleocene reservoir formations are located along the margins of the isolated carbonate platform and have a NW-SE trend. Data conditioning and seismic attribute analyses applied on the 3-D seismic dataset effectively enhanced our understanding of the reservoir complexity and improve the detection of the major and minor faults and fracture zones in the study area.