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Date of Award
Campus Access Master's Thesis
Master of Science in Geophysics (MS)
Administrative Home Department
Department of Geological and Mining Engineering and Sciences
Wayne D. Pennington
Committee Member 1
Roger M. Turpening
Committee Member 2
Fractures play an important role in unconventional oil exploration at the present time. This study focuses on seismic attribute analysis and acoustic impedance inversion along with petrophysical data to delineate structures relating to the fractures and identify potential hydrocarbon targets in the Taranaki Basin, New Zealand. Some seismic attributes, such as volumetric curvature and similarity allow us to see certain structures, such as folds and faults; these are the main features where fractures and petroleum traps occur. I use Maari-3D post-stack seismic data to create volumetric curvature and coherence for fault and fold analysis, and model-based inversions for acoustic impedance volume. The analysis is supported by well log data interpretation, primarily density, sonic (both compressional and shear), resistivity, gamma ray, photoelectric and image logs. While the major challenge presented in this data set is the effect of a gas chimney producing noise on seismic data throughout the survey, the results from a combined analysis of seismic and acoustic impedance volumes with well logs appear to determine the locations of fractures and potential reservoirs. First, both coherence and curvature are used to examine the relationship between these two attributes. Second, total organic content and Young’s modulus are calculated from well logs. Then, I perform deterministic and stochastic acoustic impedance inversions of the vi seismic data. Lastly, the combination of the results of each of these methods are used to identify locations where production from shaly reservoirs would be most likely, assuming that the maximum potential lies where fractures intersect zones of high total organic content in brittle rock.
Karakus, Ender, "FRACTURE AND PETROPHYSICAL ANALYSIS FROM SEISMIC DATA IN MAARI FIELD, NEW ZEALAND", Campus Access Master's Thesis, Michigan Technological University, 2016.