AVO ANALYSIS, RESERVOIR CHARACTERIZATION AND QUANTITATIVE INTERPRETATION OF ZAMZAMA BLOCK IN SOUTHERN INDUS BASIN, PAKISTAN

Abstract

The Zamzama Gas Field was discovered in 1998 on the Dadu concession, which lies 200 km north of Karachi, the capital of Sindh Province. Geologically, it lies in the Kirthar Foredeep of the Lower Indus Basin. The 3D depth migrated seismic data, having improved structural resolution in both hanging and footwalls compensated for the anisotropy issues, is utilized for interpretation purposes with seven wells. A well-to-seismic correlation is performed in all wells, and three horizons are interpreted on seismic data delineating an anticlinal structure along with thrust faults. A major thrust cut the anticlinal structure at its eastern limb and extended in the North-South direction throughout the field. The interpreted horizons included the shallower secondary reservoir of the Khadro Formation, the underneath primary reservoir of the Pab Formation having confirmable contact with the Khadro Formation, and the Fort Munro Limestone present at the base of the Pab Formation. The Pab Formation faces the challenge of early water influx in the producing wells as the major faults connect the hanging and footwall at the ramps, but still contains potential in the crestal areas where gas-water-contact (GWC) is present below the gas column. Seismic attributes delineate the channelized gas-bearing sands passing through all wells, but the advanced technique based on petro-elastic relationships is adopted to distinguish between wet and gas-bearing sand facies. To establish the petro-elastic relationship, a detailed assessment of well information is needed regarding the characterization of fluids and lithologies. The petrophysical analysis was carried out for both the Pab and Khadro Formations and estimated the saturations, porosities, volumetrics, and net-to-gross (N/G) thicknesses. The Pab contains good porous sands with gas-saturations up to 65%, while Khadro has thin (6 m) heterogeneous sands with only 6-7% of effective porosity. The Amplitude Variation with Offset (AVO) analysis is carried out for fluids and lithology identification within the Pab Formation. Various scenarios are generated through fluid replacement modeling and their synthetic responses are analyzed for in-situ fluids recognition along with the type of gas-bearing sands. After detailed formation evaluation through petrophysical and AVO analysis, rock physics modeling (RPM) based on petro-elastic models was accomplished for the Pab and Khadro Formations that distinguished the litho-facies more pronouncedly in the petro-elastic DRSML QAU xxiii domains. The resultant optimized elastic logs compensated for the poor bore conditions and provided the missing shear sonic logs of wells. The elastic responses are utilized in the inversion processes for enhanced litho-facies discrimination on the inverted elastic volumes. The prestack simultaneous seismic inversion is adopted for thick Pab Formation characterization that differentiates the gas-bearing sands on the specific values of elastic properties such as p-impedance, s-impedance, and Vp/Vs ratio. The inverted attributes are utilized in the Bayesian inference along with well-based lithologies to predict litho probability cubes, especially gas sands. The quality of sand is assessed through volumetric estimation of porosity and clay through Probabilistic Neural Networking (PNN) methodology. PNN has the capability to differentiate sand and shale probabilities through the non-linear algorithm. The outcomes, i.e., elastic properties, pay-probability, porosity, and clay volumetrics, confirmed the channelized sand bodies passing through all producing wells, delineating the play fairway. The Khadro sandstone is thin and below seismic resolution, confirmed by the wedge modeling. Therefore, the Bayesian stochastic inversion is employed for the illumination of thin gas-bearing sands. The Bayesian stochastic inversion has the advantage of incorporating the high frequencies of wells through variograms along with petro-elastic models (PEMs) optimized elastic responses that amalgamate the effects of pores, grains, fluids, pressure, temperature, and salinity to deal with the heterogeneities. The high-resolution elastic properties differentiate the gas sand facies and a reliable correlation is observed at well locations with petrophysical properties, i.e., saturations, porosities, and clay volumetrics. The posterior elastic properties are classified by the Bayesian algorithm along with the integration of wells and geological information for gas probability cubes. The gas-bearing sands are mapped at various levels, i.e., A, B, and C, which declared that Zamzama-06 and Zamzama 08 are insignificant for gas-bearing sands while Zamzama-04, Zamzama-02, and Zamzama 07 need perforations like Zamzama-03 and Zamzama-05 before drilling addition