3D SEISMIC DISCONTINUITY ATTRIBUTES FOR RESERVOIR FRACTURES CHARACTERISATION OF “KIN” FIELD, NIGER DELTA

Abstract

Over the last decade, there has been increased success at placing wells within productive zones (sweet spots) of fractured reservoirs. Fractures are major pathways for fluid flow in the reservoir and their exact positions must be identified and accurately mapped for optimal well placement. On the standard seismic display, fractures often occurs below the seismic resolution and are thus difficult to detect but recent advancement in seismic attributes like similarity and curvature attributes are helping geophysicists to identify and characterize them. This study is aimed at identifying and evaluating fractured hydrocarbon reservoirs within ‘KIN’ Field by using the seismic discontinuity attributes and conventional well logs. The workflow involved; wells correlation, petrophysical analysis, fault / horizon mapping and fracture density prediction. Prior to the prediction and mapping of fractures, optimal data conditioning was carried out using the Dip steering algorithm on OpendTectTM to remove the seismic noises and improve the image quality of fractures. Time-slices were extracted within the horizons of interest for seismic attribute analysis involving two discontinuity attributes. Rose diagrams were plotted to reveal the predominant and orientation of the mapped fractures. Conventional logs such as Resistivity, Sonic, Calliper and Density Logs were used to validate the seismic mapped fractures within the borehole environment. Four sand units (Sand 1, 2, 3 and 4) were picked and evaluated. Fractures influence on the petrophysical properties of each reservoir (Sand 1, 2, 3 and 4) were also evaluated. A total of nineteen faults (F1-F19) were picked on the seismic data. The attribute analysis results at time-slices 2024msec, 2100msec and 2197msec show subtle features (fractures) with SE – NW and SW - NE predominant. Finally, possible new hydrocarbon prospect areas were located SW of the field base on high amplitude from the Energy attribute and high fracture density from the multi-attribute maps.