In this research, multiple scales of intrusive sand bodies in the Lower Palaeocene Panoche Giant Injection Complex (PGIC) were investigated in order to better understand their distribution from source beds, geometry, network, role in the upward migration of fluids, and significance as reservoirs in petroleum systems. Their geometrical properties were documented and integrated into a 3-D reservoir model. In addition, the links between sandstone intrusions in outcrops and in seismic was examined, with the aim of providing more insights into intrusive sand bodies that are undetected when using subsurface data. The significance of sandstone intrusions are commonly overlooked, underestimated, or neglected. Even though these geological features have been long recognised, their potentials as hydrocarbon reservoirs have only recently become evident (Hurst, et al., 2005). Apart from their potential as hydrocarbon reservoirs, they also have significant control on distribution and recovery of reserves (Hurst & Cartwright, 2007). Subseismic-scale intrusive sand bodies, which are extensions of deeper depositional sand units that cut across low permeable beds, promote migration and discharge of reservoir fluids. Various studies have shown the importance of sandstone intrusions in oil and gas exploration and production, however many challenges associated with the presence of these intrusive bodies still persist. Some present problems include; underestimating the widespread distribution of sandstone intrusions in regions where they occur due to the two dimensional visualization of geological bodies (Hurst & Cartwright, 2007); predicting the number and volume of small scale and steeply dipping intrusions of more than 45 degrees which are not visible on seismic; and, constructing a more comprehensive model of reservoirs that have sandstone intrusions within them. This research work, thus, aims to address some of these issues, and provide solutions that aid characterization and prediction of sand intrusive body networks, in terms of their distribution, geometry, network, and other geostatistical properties.
Date of Award | 31 Dec 2023 |
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Original language | English |
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Awarding Institution | - The University of Manchester
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Supervisor | David Hodgetts (Supervisor) & Mads Huuse (Supervisor) |
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MULTISCALE IMAGING OF OUTCROP DATA FOR PETROLEUM RESERVOIR CHARACTERIZATION
Ojero, J. (Author). 31 Dec 2023
Student thesis: Phd