Harilal, _ (Oil and Natural Gas Corporation Limited) | Rao, C.G. (Oil and Natural Gas Corporation Limited) | Saxena, R.C.P. (Oil and Natural Gas Corporation Limited) | Nangi, J.L. (Oil and Natural Gas Corporation Limited) | Sood, A. (Oil and Natural Gas Corporation Limited) | Gupta, S.K. (Oil and Natural Gas Corporation Limited)
The 3-D data of C-37 and adjoining prospects of Tapti-Daman sub-basin of Mumbai offshore Basin, India, have been evaluated for delineation and mapping of Mahuva pay sands. The pays were found over an anticlinal nosal feature in Upper Mahuva Unit of Lower Oligocene Mahuva Formation by one exploratory well in 1994. Conventional interpretation of 3-D data and subsequent drilling of wells towards up dip and down dip both could not map the areal extent of the pays. 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, high degree of vertical and lateral variability in net sand thickness, 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 iso-frequency slices mapped areal extent and temporal thickness of pay zone. Voxel based 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. The inferences are validated by drilled wells.