Gas-bearing sands appraisal for Zamzama gas field in Pakistan through inverted elastic attributes assisted with PNN approximation of petrophysical properties.

The Pab Formation of Zamzama block, lying in the Lower Indus Basin of Pakistan, is a prominent gas-producing sand reservoir. The optimized production is limited because of water encroachment surrounding the gas-producing wells, thus it is required to distinguish the gas-sand facies from the remainder of the wet sands and shales for additional drilling zones. An approach is adopted based on the relation between petrophysical and elastic properties to characterize the prospect locations. Petro-elastic models (PEMs) for the identified facies were generated to distinguish lithologies in their elastic ranges. Several elastic properties, including p-impedance (11,600-12,100 m/s*g/cc), s-impedance (7,000-7,330 m/s*g/cc), and Vp/Vs ratio (1.57-1.62), were calculated from the simultaneous prestack seismic inversion (SPSI), allowing the identification of gas sands in the field. The inverted elastic attributes and well-based lithologies were incorporated into the Bayesian framework to evaluate the probability of gas sands. To determine the reservoir quality, bulk volumes of PHIE and clay were estimated using elastic volumes trained on well logs by employing Probabilistic neural networking (PNN), which effectively handles heterogeneity effects. The results showed that the channelized gas sands passing through the existing well locations exhibited reduced clay content and maximum effective porosities of 9%, confirming the reservoir's good quality. Such approaches can be widely implemented in producing fields to completely assess lithofacies and achieve maximum production with minimal risks. [ABSTRACT FROM AUTHOR]