1.5D Internal Multiple Prediction: an Application on Synthetic Data, Physical Modelling Data and Land Data Synthetics

atmire.migration.oldid3339
dc.contributor.advisorInnanen, Kris
dc.contributor.authorPan, Pan
dc.date.accessioned2015-06-29T15:24:58Z
dc.date.available2015-11-20T08:00:32Z
dc.date.issued2015-06-29
dc.date.submitted2015en
dc.description.abstractA 1.5D implementation of the inverse scattering series internal multiple prediction algorithm is investigated with the challenges of land seismic data application in mind. This method does not require any subsurface information and is suitable for situations where there is close interference between primaries and internal multiples; however, in land environments, issues of noise, coupling and statics have led to fewer reported successes. The methodology is also computationally costly, with the cost increasing dramatically as the implementation makes the transition from its 1D form to 1.5D, 2D and ultimately 3D. With these issues in mind, the algorithm is examined using a step-by-step approach: first, by carrying out synthetic examples; second, by testing physical modelling data; and finally, by operating on well log synthetics from land data. In the synthetic environment a study is undertaken to determine under what circumstances lower-dimension versions of the prediction algorithm can be applied to higher dimension problems to take advantage of the computational speed. The effects of various ϵ values are analyzed. A method to mitigate large-dip artifacts noticeable in unfiltered 1.5D internal multiple prediction is developed. Applicability of these ideas to real measurements taken in a physical modelling experiment, and using realistic synthetic data produced from real well logs is confirmed.en_US
dc.identifier.citationPan, P. (2015). 1.5D Internal Multiple Prediction: an Application on Synthetic Data, Physical Modelling Data and Land Data Synthetics (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/24619en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/24619
dc.identifier.urihttp://hdl.handle.net/11023/2323
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
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.
dc.subjectGeophysics
dc.subjectGeotechnology
dc.subject.classificationinternal multiple predictionen_US
dc.subject.classificationphysical modellingen_US
dc.subject.classificationinverse scattering seriesen_US
dc.subject.classificationProcessingen_US
dc.subject.classificationland applicationen_US
dc.title1.5D Internal Multiple Prediction: an Application on Synthetic Data, Physical Modelling Data and Land Data Synthetics
dc.typemaster thesis
thesis.degree.disciplineGeoscience
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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