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dc.date.accessioned2013-11-21T11:04:47Z
dc.date.available2013-11-21T11:04:47Z
dc.date.issued2013en_US
dc.date.submitted2013-04-25en_US
dc.identifier.citationRebekka, Mørken. Computation of curvature in seismic data. Masteroppgave, University of Oslo, 2013en_US
dc.identifier.urihttp://hdl.handle.net/10852/37734
dc.description.abstractDigital analysis of seismic images is a key component in the automation of seismic data interpretation. Other authors have explored using curvature as an attribute in this kind of analysis, but only on data which has been manually interpreted. In this project the subject is the use of curvature as a feature for automatic highlighting of saltdomes in seismic images. Saltdomes are of particular interest in seismic exploration, as they are often linked to hydrocarbon finds. By using the so-called dip to extract discrete curve segments representing the seismic horizons in the image, the local curvature may be estimated. This in turn requires approxi- mation of first and second order derivatives. Derivative approximation is done by locally fitting a parabola to each data point, and approximating the derivatives in that point by the derivatives of the parabola. The presented method is applied to a set of inline seismic saltdome images. The results show the saltdomes clearly highlighted from their surroundings, with distinct areas of positive and negative curvature values.eng
dc.language.isoengen_US
dc.titleComputation of curvature in seismic dataen_US
dc.typeMaster thesisen_US
dc.date.updated2013-11-15en_US
dc.creator.authorRebekka, Mørkenen_US
dc.subject.nsiVDP::413en_US
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft.au=Rebekka, Mørken&rft.title=Computation of curvature in seismic data&rft.inst=University of Oslo&rft.date=2013&rft.degree=Masteroppgaveen_US
dc.identifier.urnURN:NBN:no-39762
dc.type.documentMasteroppgaveen_US
dc.identifier.duo179081en_US
dc.contributor.supervisorAnne H. S. Solbergen_US
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/37734/1/RebekkaMorkenValdmanis_thesis.pdf


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