Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/29149
Title: Integrated Geophysical Analysis for reservoir characterization of Lumshiwal, Hangu and Lockhart Formations in Manzalai Area, Upper Indus Basin, Pakistan
Authors: Farman Ullah
Keywords: Earth Sciences
Issue Date: 2023
Publisher: Quaid I Azam University Islamabad
Abstract: Hydrocarbons play a crucial role in contemporary industrialized societies due to their capacity to supply energy. In order to accurately delineate and characterize a hydrocarbon reservoir, it is important to acquire more comprehensive subsurface data. The task at hand necessitates the examination and evaluation of geological formations pertaining to petroleum reservoirs and other geological features. The Upper Indus Basin exhibits proven potential for hydrocarbon reservoirs in the Paleocene and Cretaceous periods. Extensive investigation is necessary for the Manzalai Gas Field, which contains structural traps that hold hydrocarbon reserves. In order to evaluate the potential for hydrocarbon deposits and determine the structural favorability of the area, an analysis of seismic data was conducted. This analysis resulted in the mapping of five horizons, namely Lockhart, Hangu, Kawagarh, Lumshiwal, and Chichali and their time contour maps are generated which shows that horizons are dipping from North-West to South-East. The petrophysical investigation reveals the existence of a gas-bearing zone in the Hangu and Lumshiwal formations in wells Mnazalai-01, Manzalai-05, and Manzalai-06. However, the Lockhart formation only exhibits a possible gas-bearing zone in well Manzalai-05. The hydrocarbon-bearing zones demonstrate a high degree of hydrocarbon saturation; yet, the effective porosity is significantly low, resulting in a reservoir characterized as tight. The procedure of facies classification reveals the presence of five unique facies, which are gas sands, shale, shaly sand, limestone-wackstone, and limestone-packstone. The utilization of Rock physics modelling enhances the accuracy of logs by mitigating the adverse effects of undesirable logging phenomena, hence leading to improved outcomes in petrophysical analysis. The inversion analysis has been performed which gives the spatial distribution of low impedance zones characterized by the hydrocarbon bearing zones.
URI: http://hdl.handle.net/123456789/29149
Appears in Collections:M.Phil

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