Theory-guided machine learning in geophysics

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dc.contributor.advisorTrad, Daniel Osvaldo
dc.contributor.authorNiu, Zhan
dc.contributor.committeememberlnnanen, Kristopher A.H.
dc.contributor.committeememberKarchewski, Brandon Anthony James
dc.contributor.committeememberZhao, Richard
dc.date2022-06
dc.date.accessioned2021-10-20T16:27:48Z
dc.date.available2021-10-20T16:27:48Z
dc.date.issued2021-10-18
dc.description.abstractMachine learning has become a popular topic in the past decade thanks to the booming in computer hardware and the tools invented. Many successful applications have been made in various subjects in geophysics, including salt body detection, facies recognition and inversion etc. However, the fact that most geophysical theory is well-established sometimes contradicts the black box theory in machine learning when combining methods in the two fields. This thesis will discuss several ways of incorporating well-established knowledge into machine learning by giving a few applications and experiments in geophysics. We will also discuss the limitations and challenges machine learning is facing.en_US
dc.identifier.citationNiu, Z. (2021). Theory-guided machine learning in geophysics (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/39354
dc.identifier.urihttp://hdl.handle.net/1880/114064
dc.language.isoengen_US
dc.publisher.facultyScienceen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectReverse time migrationen_US
dc.subjectMachine learningen_US
dc.subjectU-neten_US
dc.subjectRecurrent neural networken_US
dc.subject.classificationGeophysicsen_US
dc.titleTheory-guided machine learning in geophysicsen_US
dc.typemaster thesisen_US
thesis.degree.disciplineGeoscienceen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrueen_US
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