Shear wave velocity prediction using seismic attributes and well log data

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 sa...

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Main Authors: Gholami, Raoof, Moradzadeh, A., Rasouli, Vamegh, Hanachi, J.
Format: Journal Article
Published: Polska Akademia Nauk * Instytut Geofizyki 2014
Online Access:http://hdl.handle.net/20.500.11937/12369
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author Gholami, Raoof
Moradzadeh, A.
Rasouli, Vamegh
Hanachi, J.
author_facet Gholami, Raoof
Moradzadeh, A.
Rasouli, Vamegh
Hanachi, J.
author_sort Gholami, Raoof
building Curtin Institutional Repository
collection Online Access
description 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.
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T06:58:59Z
publishDate 2014
publisher Polska Akademia Nauk * Instytut Geofizyki
recordtype eprints
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spelling curtin-20.500.11937-123692017-09-13T14:59:51Z Shear wave velocity prediction using seismic attributes and well log data Gholami, Raoof Moradzadeh, A. Rasouli, Vamegh Hanachi, J. 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. 2014 Journal Article http://hdl.handle.net/20.500.11937/12369 10.2478/s11600-013-0200-7 Polska Akademia Nauk * Instytut Geofizyki fulltext
spellingShingle Gholami, Raoof
Moradzadeh, A.
Rasouli, Vamegh
Hanachi, J.
Shear wave velocity prediction using seismic attributes and well log data
title Shear wave velocity prediction using seismic attributes and well log data
title_full Shear wave velocity prediction using seismic attributes and well log data
title_fullStr Shear wave velocity prediction using seismic attributes and well log data
title_full_unstemmed Shear wave velocity prediction using seismic attributes and well log data
title_short Shear wave velocity prediction using seismic attributes and well log data
title_sort shear wave velocity prediction using seismic attributes and well log data
url http://hdl.handle.net/20.500.11937/12369