Abstract

The Cambay Basin is 450-km-long north–south-trending graben with an average width of 50 km, having maximum depth of about 7 km. The origin of the Cambay and other Basins on the western margin of India are related to the break up of the Gondwana super-continent in the Late-Triassic to Early-Jurassic (215 ma). The structural disposition of the Pre-Cambrian basement—a complex of igneous and metamorphic rocks exposed in the vicinity of the Cambay Basin—controls its architecture. The principal lineaments in the Basin are aligned towards NE-SE, ENE-WSW and NNW-SSE, respectively. Rock physics templates (RPTs) are charts and graphs generated by using rock physics models, constrained by local geology, that serve as tools for lithology and fluid differentiation. RPT can act as a powerful tool in validating hydrocarbon anomalies in undrilled areas and assist in seismic interpretation and prospect evaluation. However, the success of RPT analysis depends on the availability of the local geological information and the use of the proper model. RPT analysis has been performed on well logs and seismic data of a particular study area in mid Cambay Basin. Rock physics diagnostic approach is adopted in the study area placed at mid Cambay Basin to estimate the volume in the reservoir sands from 6 wells (namely; A, B, C, D, E and F) where oil was already encountered in one well, D. In the study area, hydrocarbon prospective zone has been marked through compressional (P wave) and shear wave (S wave) impedance only. In the RPT analysis, we have plotted different kinds of graphical responses of Lame’s parameters, which are the function of P-wave velocity, S-wave velocity and density. The discrete thin sand reservoirs have been delineated through the RPT analysis. The reservoir pay sand thickness map of the study area has also been derived from RPT analysis and fluid characterization. Through this fluid characterization, oil-bearing thin sand layers have been found in well E including well D. The sand distribution results prove that this methodology has able to perform reservoir characterization and seismic data interpretation more quantitatively and efficiently.

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