Evaluation of Seismic Responses from Well-Associated Gas Producing Sands Using Integrated Approaches for Optimal Field Production in Zamzama Gas Field, Pakistan

The producing fields often observe early decline due to many misapprehended factors concerning structural interpretation, facies identification, and proper estimation of geological properties. The accuracy of the estimation of these characteristics is critical for enhanced recovery. An integrated approach based on well identified potential lithofacies distribution in relation to seismic trace responses and accurate fluid estimation is vital. In the present study, gas-bearing sands are appraised for their reservoir characteristics within a complex anticline structure. The faulted anticline's hanging wall provided suitable locations for optimum gas entrapment; however, its connection with the footwall through lateral ramps allows the aquifer's early encroachment into the reservoir. For enhanced recovery, the combination of well-derived petrophysical parameters with seismic extracted responses provided insight into the producing facies with quantitative fluids identification using fluid replacement modeling (FRM) and their amplitude variation with offset (AVO) responses. The reliable AVO responses of substituted fluids comprising 85% gas with 15% brine are observed for identified potential sands, classifying sands as class-II. Similarly, the intercept (A), gradient (B), and product (A*B) of angle dependent seismic traces were mapped within the Pab Formation and showed amplitude anomalies for porous channelized gas-bearing sands. Finally, crossplotting intercept-gradient volumes differentiated the gas-bearing sands and precisely demarcated the identified gas sands throughout the field, with confirmation at producing well locations. Hence, the integrated assessment of the outcomes resulting from structural interpretation, petrophysical evaluation, and seismic trace valuation can be readily employed for distinguishing the producing sand facies in complex structures and demarcating risk-efficient zones.