Seismic Stratigraphy, Geomorphology, and Lithology Prediction of Fluvial and Deepwater Systems, North Malay and Delaware Basins.

dc.contributor.advisorPranter, Matthew J.
dc.contributor.authorZhai, Rui
dc.contributor.committeeMemberBedle, Heather
dc.contributor.committeeMemberHu, Hao
dc.contributor.committeeMemberWu, Xingru
dc.date.accessioned2025-05-14T22:17:15Z
dc.date.embargoExpiration
dc.date.issued2025
dc.date.proquestAvailable01/01/2025
dc.date.updated2025-05-14T22:17:15Z
dc.description.abstractHigh-frequency seismic sequence stratigraphy and quantitative seismic interpretation are essential for characterizing subsurface reservoirs' architecture and heterogeneity. Although significant advances in the theoretical understanding and research methods of fluvial and deepwater turbidite reservoirs, the inherent complexity of depositional architecture and the variability of reservoir properties continue to pose significant challenges for accurate seismic interpretation. This study addresses these limitations by integrating seismic sequence stratigraphy, seismic geomorphology, seismic inversion, and limited well data, all guided by geological prior knowledge. The aim is to enhance seismic interpretation and lithological prediction in the North Malay and Delaware Basins. The investigation focuses on the falling-stage systems tract (FSST) developed in two contrasting depositional environments, coastal plain and deepwater. First, a high-frequency seismic sequence stratigraphic analysis of the Pleistocene strata in the Northern Malay Basin is conducted, with particular attention paid to the FSST interval. This analysis reveals the internal fill architecture of two distinct types of incised valleys associated with the FSST. Then, seismic geomorphological analysis, using coherence attributes and spectral decomposition, is employed to characterize various mud-filled abandoned channels in fluvial systems spanning multiple FSSTs within the Pliocene–Pleistocene strata. These mud plugs are shown to impact reservoir connectivity significantly. Lastly, in the Delaware Basin, the study applies machine learning techniques and integrated well-seismic Bayesian lithology inversion to predict lithology and assess heterogeneity in mixed siliciclastic–carbonate turbidite reservoirs within the FSST of the Bone Spring Formation. The insights gained from these multi-disciplinary approaches can be broadly applied to improve the quantitative seismic interpretation of analogous reservoir systems.
dc.identifier.isbn9798314811764
dc.identifier.urihttps://hdl.handle.net/11244/341370
dc.language.isoen
dc.publisherUniversity of Oklahoma – Graduate College
dc.subjectGeophysics
dc.subjectdeepwater turbidite system
dc.subjectfluvial system
dc.subjectquantitative seismic interpretation
dc.subjectseismic geomorphology
dc.subjectseismic sequence stratigraphy
dc.thesis.degreeD.Phil.
dc.titleSeismic Stratigraphy, Geomorphology, and Lithology Prediction of Fluvial and Deepwater Systems, North Malay and Delaware Basins.
ou.groupGeology and Geophysics: Earth & Energy

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