Seismic Characterization of Faults from 3-D Seismic Data: Fault Detection, and Characterization of the Bakken Formation

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dc.contributor.committeeMemberCastagna, John P.
dc.contributor.committeeMemberMurphy, Michael A.
dc.contributor.committeeMemberLi, Aibing
dc.contributor.committeeMemberNasser, Mosab
dc.creatorJahan, Ismot 1985-
dc.date.accessioned2018-03-13T12:43:08Z
dc.date.available2018-03-13T12:43:08Z
dc.date.createdDecember 2017
dc.date.issued2017-12
dc.date.submittedDecember 2017
dc.date.updated2018-03-13T12:43:08Z
dc.description.abstractThis dissertation focuses on automatic fault detection and generation of different fault attributes from a seismic discontinuity volume such as dip and strike, density, displacement, and rose diagrams to characterize faults from 3D seismic data in the Bakken Formation. I use principal component analysis (PCA) for automatic fault detection. The PCA fault attribute indicates significantly different, and geologically more plausible, 3D fault distributions than do conventional seismic attributes, such as curvature. The PCA fault attribute identifies different fault patterns in the Upper, Middle, and Lower Bakken members and the Three Forks Formation. Two distinct fault trends in approximately N40–50°E and N50–60°W directions are observed in the Bakken Formation. Fault cuts interpreted from missing well-log sections also correlate well with the PCA fault attribute. Seismically derived fault orientations correlate with borehole image logs in horizontal wells. Crossing conjugate faults observed on the fault-dip attribute are interpreted to result in widening of the faulted area and localized thinning of the rock sequence at the intersection of conjugate faults. This fault network potentially enhances permeability in the direction of fault strike. I demonstrate the potential for using the time-frequency continuous wavelet transform (TWCFT) for detecting small faults in the thin Bakken Formation. TWCFT, along with PCA, detected faults with different vertical displacements which are preferentially highlighted at different dominant frequencies. At the Bakken level, major faults are seen best at low frequencies, while antithetic faults around the master faults are seen best at high frequencies. I analyze rose diagrams from seismic to identify different patterns of preexisting faults in ~N45°E, ~N75°E, and ~N15°E orientations for normal and strike-slip faulting stress state. The rose diagram results correlate well with rose plot generated from image logs. Fault analysis of vertical sections illustrates fault connectivity from the Bakken to the adjacent formations. Finally, density-porosity predicted with multi-attribute analysis of seismic data is correlated to fault density.
dc.description.departmentEarth and Atmospheric Sciences, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/2935
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectSeismic faults
dc.subjectBakken Formation
dc.subjectSeismic attributes
dc.titleSeismic Characterization of Faults from 3-D Seismic Data: Fault Detection, and Characterization of the Bakken Formation
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2019-12-01
local.embargo.terms2019-12-01
thesis.degree.collegeCollege of Natural Sciences and Mathematics
thesis.degree.departmentEarth and Atmospheric Sciences, Department of
thesis.degree.disciplineGeophysics
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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