Estimation of Reservoir Porosity Using Seismic Post-Stack Inversion in Lower Indus Basin, Pakistan

Seismic post-stack inversion is one of the best techniques for effective reservoir characterization. This study intends to articulate application Model-Based Inversion (MBI) and Probabilistic Neural Networks (PNN) identification properties i.e. porosity estimation. MBI technique applied observe low impedance zone at porous formation. PNN a geostatistical that transforms volume into volume. Inverted estimated spatial distribution in Lower Goru sand beyond well data control. The result inverted compared with well-computed porosity. ranges from 13-13.5% which shows correlation 99.63% computed Rehmat-02 well. observed high cube targeted horizon suggest it could be probable potential channel. Furthermore, results seismic analysis indicate very good agreement each other. Hence, can effectively estimate further prospective zones identification, volumetric estimation future exploration.