Cretaceous Pab Reservoir Quantitative Interpretation And PNN Estimation Of Petrophysical Properties For Hydrocarbon Assessment Using Integrated Well And Seismic Data.

Abstract

Seismic reflection is an indirect geophysical tool for hydrocarbon exploration that is commonly employed. The main goal is to characterize physical reservoir parameters and evaluate hydrocarbon reservoirs. The use of seismic amplitude in conjunction with wireline logs aids in the estimation of these crucial reservoir parameters. The major goal of this research is to improve reservoir characteristics assessment in the sands of the Pab formation in the Zamzama Gas Field in Pakistan's Lower Indus Basin. Seismic interpretation, wireline log analysis, seismic inversion techniques and Probabilistic Neural Network ( PNN ) are used to achieve the goals. The database has a very significant role in the project. In our study area, the data is used to estimate the study purpose i.e. 3D seismic interpretation, petrophysics, inversion, and PNN etc. For detiled studies I used ten lines i-e five seismic inlines ( inline 450,460,470,480, and 470 ) and five seismic crossline ( crossline 1360,1370,1380,1390,1400 ) along with two well i-e Zamzama 03 and 05. Because the Zamzama gas field is located in the Lower Indus Basin, which has a compressional regime, the structure identified here is a thrusted anticline. Three horizons, Khadro , Pab, and Fort Munro are marked on a synthetic seismogram. Faults are being indicated along with the distortion or discontinuity with an eastward-facing N-S thrust fault. Our subsurface structures were also validated by time and depth contour maps. Petrophysical analysis of borehole log data is used to evaluate reservoir parameters. At Zamzama well 03 and 05 the Pab formation is classified as a reservoir that meets all of the requirements for a reservoir. According to petrophysical data, the Pab formation has a high effective porosity of 10-16 percent, a low volume of shale of 6-10 percent, and a hydrocarbon saturation of 70-87 percent. The reservoir lithology is proven using well Zamzamz 03 by facies analysis, which is the cross-plotting of different logs such as Neutron vs Sonic logs. These tests are carried out at the reservoir level, revealing that the reservoir's principal lithology is sand with thin shale sequences interbedded. The reservoir location is confirmed using seismic Model-based inversion (MBI). Pab sandstone has a low impedance value on the inverted seismic section, which could be a significant indicator of hydrocarbon content. Model-based inversion (MBI) are used to choose low impedance zones with a high correlation coefficient and low error. At the reservoir level, MBI has a correlation coefficient of (0.99) and an error of (0.045). Inversion algorithm strategies resolve the reservoir well, however, MBI outperforms them all in terms of maximum correlation and smallest error in the research region. And last we perform Probabilistic Neural Network ( PNN ) to predict seismic reservoir properties from well log data and seismic attributes by using Hampson Russell software .