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dc.date.accessioned2020-05-08T11:45:16Z
dc.date.available2020-05-08T11:45:16Z
dc.date.issued2020
dc.identifier.urihttp://hdl.handle.net/10852/75245
dc.description.abstractThe interpretation of seismic data is an integrated process that requires geophysical knowledge and an intuitive geological understanding. While seismic interpretation is essential in order to accumulate knowledge and build an understanding of the subsurface, some elements of the interpretation workflow can be tedious, subjective and in some cases even trivial. In this thesis, we present data-driven methods that seek to integrate data science and geoscience in order to address different aspects of automated seismic interpretation. The data-driven methods that we present are based on digital tools from image processing, signal processing and machine learning. With these methods, we aim to (1) identify and individualize faults and unconformities, (2) correlate and track non-coherent seismic horizons, (3) identify stratigraphic units and (4) improve seismic image quality.en_US
dc.language.isoenen_US
dc.relation.haspartPaper 1: Aina J. Bugge, Stuart R. Clark, Jan E. Lie, and Jan I. Faleide, (2018), "A case study on semiautomatic seismic interpretation of unconformities and faults in the southwestern Barents Sea," Interpretation 6: SD29-SD40. DOI: 10.1190/INT-2017-0152.1. The article is included in the thesis. Also available at: https://doi.org/10.1190/INT-2017-0152.1
dc.relation.haspartPaper 2: Automatic extraction of dislocated horizons from 3D seismic data using nonlocal trace matching. Aina Juell Bugge, Jan Erik Lie, Andreas Kjelsrud Evensen, Jan Inge Faleide, and Stuart Clark. Geophysics, 84(6), 2019; p. IM77–IM86. DOI: 10.1190/GEO2019-0029.1. The article is included in the thesis. Also available at: https://doi.org/10.1190/GEO2019-0029.1
dc.relation.haspartPaper 3: Data-driven identification of stratigraphic units in 3D seismic data using unsupervised machine learning (HDBSCAN) (In review) To be published. The paper is not available in DUO awaiting publishing.
dc.relation.haspartPaper 4: Addressing key aspects of automated seismic interpretation (manuscript prepared for submission). To be published. The paper is not available in DUO awaiting publishing.
dc.relation.urihttps://doi.org/10.1190/INT-2017-0152.1
dc.relation.urihttps://doi.org/10.1190/GEO2019-0029.1
dc.titleAspects of automated seismic interpretationen_US
dc.typeDoctoral thesisen_US
dc.creator.authorBugge, Aina Juell
dc.identifier.urnURN:NBN:no-78349
dc.type.documentDoktoravhandlingen_US
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/75245/1/PhD-AJ-Bugge-2020.pdf


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