Seismic Resolution And Reservoir Characterization of Thin Sands by Applying, Spectral Broadening, Non-conventional Attributes, and Multiattribute Analysis, in the Daqing Field, China.

dc.contributor.advisorCastagna, John P.
dc.contributor.committeeMemberMeza, Ramses
dc.contributor.committeeMemberColli, Lorenzo
dc.contributor.committeeMemberChesnokov, Evgeni M.
dc.creatorMora Calderon, David Alexander
dc.creator.orcid0000-0002-5858-8332
dc.date.accessioned2021-08-06T19:31:49Z
dc.date.createdDecember 2020
dc.date.issued2020-12
dc.date.submittedDecember 2020
dc.date.updated2021-08-06T19:31:51Z
dc.description.abstractThe Daqing field, in the Songliao Basin in northeastern China, is the largest oil field in the country. Most of the production in this field comes from seismically thin sand bodies with thicknesses between 1 and 15 meters. It is thus not usually possible to resolve Daqing reservoirs using only conventional seismic data. I evaluate the effectiveness of seismic multi-attribute analysis of bandwidth extended data in resolving and making inferences about these thin layers. The multi-attribute analysis finds relationships between well data and seismic attributes to predict layer properties. Initially, I applied such analysis separately to conventional seismic data and data that was spectrally broadened using sparse-layer inversion, as this inversion method usually increases the vertical resolution of the seismic. The resulting resolution, statistical significance, and accuracy in the determination of layer properties were higher for the predictions made using spectrally-broadened volume. In thin reservoirs, tuning can obscure relationships between seismic amplitude and rock properties. In such cases, the seismic phase varies with layer impedance and may thus aid in characterization. I show seismically determined relative geologic age to be a useful attribute in rock properties prediction as it helps define the stratigraphic position of a given layer. When utilized in the multi-attribute analysis, spectral decomposition amplitude and phase are preferentially selected by stepwise regression for prediction of well log effective porosity from seismic data.
dc.description.departmentEarth and Atmospheric Sciences, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.citationPortions of this document appear in: Calderon, David Mora, and John Castagna. "Seismic resolution and reservoir characterization of thin sands using multi-attribute analysis and spectrally-broadened data in the Daqing Field, China." In 2018 SEG International Exposition and Annual Meeting. OnePetro, 2018.
dc.identifier.urihttps://hdl.handle.net/10657/8027
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. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectseismic, thin beds
dc.titleSeismic Resolution And Reservoir Characterization of Thin Sands by Applying, Spectral Broadening, Non-conventional Attributes, and Multiattribute Analysis, in the Daqing Field, China.
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2022-12-01
local.embargo.terms2022-12-01
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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