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| dc.contributor.author | Rabia Khalid, 01-262232-021 | |
| dc.date.accessioned | 2025-11-07T04:14:31Z | |
| dc.date.available | 2025-11-07T04:14:31Z | |
| dc.date.issued | 2025 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/20039 | |
| dc.description | Supervised by Dr. Urooj Shakir | en_US |
| dc.description.abstract | This research focuses on the reservoir characterization and pore pressure prediction of the Indus Offshore Basin, Pakistan. It employs an integrated workflow combining well log data, seismic interpretation, inversion techniques, and pore pressure training through Probabilistic Neural Network (PNN). Using petrophysical data, wells correlation developed based on Gamma Ray (GR) log data analysis, potential zones identified in Miocene Intervals of four wells (Indus Marine-1A, Indus Marine- 1B, Karachi South-1A, and Pakcan-01). These correlations enabled the recognition of key stratigraphic intervals and lithological variations, particularly within the Miocene formations. Petrophysical analysis determined essential reservoir parameters i.e. shale volume, porosity and fluid saturation, revealing heterogeneous reservoir characteristics. Karachi South-1A has more potential among other wells. Pore pressure calculated using Eaton’s method, which helped delineate normal pressure zones and overpressure zones. These variations are primarily due to rapid sedimentation and under compaction process within the Miocene intervals. Seismic interpretation and structural mapping provided a detailed understanding of subsurface geometry. Post-stack model-based inversion enhanced lithological and fluid discrimination. This was followed by neural network analysis to determine spatial and vertical pressure variations within the reservoir zones. A Probabilistic Neural Network (PNN) was applied to integrate seismic attributes with well data, generating 2D pore pressure sections with high accuracy (correlation coefficient R = 0.967, average error = 11.15%). The study results offers a practical guidance for safer drilling and better prospect targeting by using exploration enhanced and streamlined workflow. Moreover legacy wells and seismic data can be utilized in more critical way and generate pressure maps and pin pointing the Miocene zones with high reservoir quality and over pressure. These results will offer practical guidance for safer drilling and better prospect can be target in the Pakistan’s offshore Indus Basin. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Earth and Environmental Sciences, Bahria University Engineering School Islamabad | en_US |
| dc.relation.ispartofseries | MS Geophysics;T-3097 | |
| dc.subject | Geophysics | en_US |
| dc.subject | Volume of clean | en_US |
| dc.subject | Interpreted curves | en_US |
| dc.title | Reservoir Characterization and Pore Pressure Prediction of Offshore Indus Basin | en_US |
| dc.type | Thesis | en_US |