Abstract

In this study, the geophysical strata rating (GSR) is calculated from petrophysical data using the equations developed for clastic rocks. The region being investigated is the South Pars gas field in the Persian Gulf Basin, where the Permian–Triassic Dalan and Kangan reservoirs host the largest accumulations of gas in the world. A 3D GSR model is estimated from 3D poststack seismic data by using a probabilistic neural network model. In this study, two methodologies are used to obtain GSR values at the different scales of wireline logs and 3D seismic data.Strong correlations between neural network predictions and actual GSR data at a blind well prove the validity of the intelligent model for estimating GSR. The GSR results are also in good agreement with porosity and elastic moduli of these carbonate rocks. Discrimination between the reservoir and non-reservoir shaly units can easily be obtained by comparing GSR and well logs. Very low GSR values with high gamma ray log responses indicate shaly intervals. These can cause washouts, casing collapse and other related drilling problems. Intervals with low GSR values and low gamma ray log responses indicate the presence of good reservoir units.

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