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dc.contributor.authorGholami, Raoof
dc.contributor.authorMoradzadeh, A.
dc.contributor.authorRasouli, Vamegh
dc.contributor.authorHanachi, J.
dc.date.accessioned2017-01-30T11:30:23Z
dc.date.available2017-01-30T11:30:23Z
dc.date.created2015-03-02T00:00:56Z
dc.date.issued2014
dc.identifier.citationGholami, R. and Moradzadeh, A. and Rasouli, V. and Hanachi, J. 2014. Shear wave velocity prediction using seismic attributes and well log data. Acta Geophysica. 62: (4) : pp. 818-848.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/12369
dc.identifier.doi10.2478/s11600-013-0200-7
dc.description.abstract

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data isnot usually acquired during well logging, which is most likely for costsaving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this informationis inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis(ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented.

dc.publisherPolska Akademia Nauk * Instytut Geofizyki
dc.titleShear wave velocity prediction using seismic attributes and well log data
dc.typeJournal Article
dcterms.source.volume62
dcterms.source.startPage818
dcterms.source.endPage848
dcterms.source.issn1895-6572
dcterms.source.titleActa Geophysica
curtin.note

This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by-nc-nd/3.0/.Please refer to the licence to obtain terms for any further reuse or distribution of this work.

curtin.departmentDepartment of Petroleum Engineering
curtin.accessStatusOpen access


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