Wavelet Approaches to Seismic Data Analysis

dc.contributor.advisorKouri, Donald J.
dc.contributor.committeeMemberBodmann, Bernhard G.
dc.contributor.committeeMemberPapadakis, Emanuel I.
dc.contributor.committeeMemberGao, Fuchun
dc.creatorLiao, Qingqing
dc.date.accessioned2014-12-09T13:33:30Z
dc.date.available2014-12-09T13:33:30Z
dc.date.createdDecember 2012
dc.date.issued2012-12
dc.date.updated2014-12-09T13:33:30Z
dc.description.abstractThere have been extensive applications of wavelets to petroleum seismic data. In this dissertation, we focus on developing and testing new wavelets approaches to seismic data compression, microseismic first arrival picking, seismic event picking, and seismic reflectivity inversion. First, we developed new methodologies for seismic data compression based on wavelets. We started with applying matching pursuit to obtain a sparse representation of seismic signals on a dictionary, so we only need to store and transmit the sparse representation. The dictionaries tested initially are Symlets. To improve the performance of compression further, we proposed the new idea of using subspace matching pursuit to obtain perfect reconstruction for a phase-rotated signal. We obtained better fidelity than matching pursuit, but the convergence is slowed down due to the incompleteness of the dictionary. Finally we proposed using matching pursuit with a combination of Symlets dictionary and subspace dictionary, thereby obtaining the best quality with the same compression ratio. Second, we report a new method of automatic first break detection of P-waves and S-waves. Our method is based on a time-frequency analysis of the seismic trace using minimum uncertainty wavelets, in particular in the minimum-phase form. We have tested our method on both lab data with various signal-to-noise ratio (S/N or SNR) and on field data. Third, we explored methods of automatic seismic event picking. It is known that no single automatic seismic event indicator works for all data; therefore, we explored two indicators based on the minimum uncertainty wavelets and on an energy ratio. Thresholding was applied to pick seismic events. We have tested the methods with both synthetic data and offshore field data. Finally, we proposed new seismic sparse inversion methods based on complex basis pursuit (CBP) and a modified complex basis pursuit (MCBP). In practice, constant phase wavelets are used for seismic inversion algorithms, for example, the basis pursuit (BP). If the phase of the estimated wavelet is wrong, this will surely cause an error in reflectivity. We can obtain more accurate reflectivity even though the estimated wavelet has biased phase by using CBP and MCBP rather than BP.
dc.description.departmentMathematics, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/800
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.subjectWavelets
dc.subjectSeismic
dc.subjectData compression
dc.subjectMatching pursuit
dc.subjectSubspace matching pursuit
dc.subjectSymlets
dc.subjectMinimum uncertainty wavelets
dc.subjectFirst arrival
dc.subjectSeismic event picking
dc.subjectSeismic reflectivity inversion
dc.subjectBasis pursuit
dc.subjectComplex basis pursuit
dc.subjectModified complex basis purs
dc.subject.lcshMathematics
dc.titleWavelet Approaches to Seismic Data Analysis
dc.type.dcmiText
dc.type.genreThesis
thesis.degree.collegeCollege of Natural Sciences and Mathematics
thesis.degree.departmentMathematics, Department of
thesis.degree.disciplineMathematics
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
QingqingLiao_Final.pdf
Size:
27.16 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.11 KB
Format:
Plain Text
Description: