Mapping Thin Sandstone Reservoirs - Application of 3D Visualization and Spectral Decomposition Techniques

Abstract

The 3-D data of C-37 of Tapti-Daman sub-basin of Mumbai offshore Basin, India, have been evaluated for delineation and mapping of Oligocene Mahuva pay sands. Post drill analysis of log and seismic data show that low impedance pay sands, embedded in high impedance shales, are separated in thin beds by limestone and/or shale streaks. Delineation of these sands by conventional interpretation methods is difficult because of thin and discontinuous occurrences, abundance of limestone streaks and limited bandwidth of seismic data. 3-D visualization of surfaces and volume attributes, neural network based seismic trace shape classification and spectral decomposition techniques have been applied with integration of well and log data. Amplitude attributes based on full bandwidth data were found more contaminated by thin limestone streaks. Spectral decomposition based iso-frequency sections and slices mapped areal extent and temporal thickness of pay zone. 3-D visualization of selected frequencies from instantaneous frequency volumes and seismic trace shape classification maps provided comparable image of the reservoir sands. Marine sands near shore-zone areas during continued sea level fall are envisaged depositional system for the pay sands. The sandstones are spread over 90 km2 area in isolated sand bodies.