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Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network

This paper proposes a new workflow for reservoir properties prediction including water saturation, volume of shale/net to gross and porosity based on new attrinbutes as input for the Probalistic Neural Netrwotk (PNN) method. The data set used in this study is acquered from east Malaysia offshore...

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Main Author: Maman Hermana, DP Ghosh, CW Sum, AMA Salim, .
Format: Article
Published: 2016
Subjects:
T Technology (General)
Online Access:https://www.onepetro.org/conference-paper/IPTC-18698-MS
http://eprints.utp.edu.my/12199/
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spelling my.utp.eprints.121992017-06-01T02:20:20Z Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network Maman Hermana, DP Ghosh, CW Sum, AMA Salim, . T Technology (General) This paper proposes a new workflow for reservoir properties prediction including water saturation, volume of shale/net to gross and porosity based on new attrinbutes as input for the Probalistic Neural Netrwotk (PNN) method. The data set used in this study is acquered from east Malaysia offshore consisting 3 wells data and 2D seismic parsial stack; near, mid and far stack data. 2016-11 Article PeerReviewed https://www.onepetro.org/conference-paper/IPTC-18698-MS Maman Hermana, DP Ghosh, CW Sum, AMA Salim, . (2016) Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network. Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network . http://eprints.utp.edu.my/12199/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic T Technology (General)
spellingShingle T Technology (General)
Maman Hermana, DP Ghosh, CW Sum, AMA Salim, .
Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network
description This paper proposes a new workflow for reservoir properties prediction including water saturation, volume of shale/net to gross and porosity based on new attrinbutes as input for the Probalistic Neural Netrwotk (PNN) method. The data set used in this study is acquered from east Malaysia offshore consisting 3 wells data and 2D seismic parsial stack; near, mid and far stack data.
format Article
author Maman Hermana, DP Ghosh, CW Sum, AMA Salim, .
author_facet Maman Hermana, DP Ghosh, CW Sum, AMA Salim, .
author_sort Maman Hermana, DP Ghosh, CW Sum, AMA Salim, .
title Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network
title_short Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network
title_full Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network
title_fullStr Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network
title_full_unstemmed Implementation of New Seismic Attributes to Improve Reservoir Properties Prediction Using Probability Neural Network
title_sort implementation of new seismic attributes to improve reservoir properties prediction using probability neural network
publishDate 2016
url https://www.onepetro.org/conference-paper/IPTC-18698-MS
http://eprints.utp.edu.my/12199/
_version_ 1738656021482569728
score 13.211869

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