GSA Connects 2022 meeting in Denver, Colorado

Paper No. 203-10
Presentation Time: 2:00 PM-6:00 PM

AN IMPROVED SEISMIC INTERPRETATION APPROACH FOR RESERVOIR MODELING, COMPARISON OF SEQUENTIAL GAUSSIAN SIMULATION PROPERTY MODELING WITH MODEL-BASED INVERSION FOR POROSITY COMPUTATION IN STRUCTURALLY COMPLEX FOLD BELT AREA OF SOUTHERN INDUS BASIN, PAKISTAN


KHAN, Muhammad Asif1, AMJAD, Raiees1, ALI, Aamir2, AHMED, Adeeb1, HAYAT, Tassawar3 and MUNIR, Nofal4, (1)Bahria University Islamabad, Islamabad, 44000, Pakistan, (2)Quaid-e-Azam University Islamabad, Islamabad, 44000, Pakistan, (3)Earth Sciences Division, Pakistan Museum of Natural History, Islamabad, Pakistan; Bahria University Islamabad, Islamabad, 44000, Pakistan, (4)LMK Resources Pakistan (Private) Limited, Jinnah Avenue, Islamabad, 44000 Pakistan, Islamabad, 44000, Pakistan

3D structural maps of Late Cretaceous Pab Sandstone at reservoir level in a gas producing field of Kirthar Fold Belt Southern Indus Basin, Pakistan were generated, and Ant-Tracking attribute for fault extraction was applied for improved structural understandings. Re-interpretation reveals large north-south thrusted anticline, pattern of north-south oblique ramp thrusts on the southeast flank, and combination of easterly vergent thrusts with counter back thrust creating a local pop-up structure in the area. 3D seismic interpretation and application of Ant-Tracking for fault extraction identifies discrete structural styles and reveals that all thrusting has occurred as a result of compression in the Plio-Pleistocene. Structural modeling leads to the generation of static model which serves as an input to populate petrophysical properties for generating reservoir model using sequential gaussian simulation algorithm. Intersection from model populates the porosity across the main fault and shows good reservoir porosity in south-western part, whereas in north-eastern part, reservoir porosities are poor at deeper levels. In order to validate porosity, Model based inversion which uses generalized linear inversion algorithm have been applied on the same data. Inversion analysis provides high correlation coefficient with an estimated error 0.15 illustrating the reliability of results. Direction of cross section from east to west represents acoustic impedances and high impedances are corresponds to low porosity sands. Inversion results have been used as a training data for porosity calculation. Regression analysis was performed on impedance results to get porosity distribution across the reservoir. Porosity estimated from inversion gives indication of porosity distribution over the high-resolution impedance derived seismic data. A strong correlation between porosity estimation from petrophysical modeling using sequential gaussian simulation and seismic inversion derived porosity values at reservoir scale makes porosity estimation a reliable and efficient reservoir characterization in the structurally complex areas.
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