Geophysical Prediction Technology Based on Organic Carbon Content in Source Rocks of the Huizhou Sag, the South China Sea

Due to the high exploration cost, limited number of wells for source rocks drilling and scarce test samples for the Total Organic Carbon Content (TOC) in the Huizhou sag, the TOC prediction of source rocks in this area and the assessment of resource potentials of the basin are faced with great chall...

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Main Authors: Yang Wei, Gong Xiao-xing, Peng Fei-fei
Format: Article
Language:English
Published: Sciendo 2017-08-01
Series:Polish Maritime Research
Subjects:
toc
Online Access:https://doi.org/10.1515/pomr-2017-0058
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spelling doaj-d400807903fa4339a962b6fa862bc33d2021-09-05T13:59:50ZengSciendoPolish Maritime Research2083-74292017-08-0124s241310.1515/pomr-2017-0058pomr-2017-0058Geophysical Prediction Technology Based on Organic Carbon Content in Source Rocks of the Huizhou Sag, the South China SeaYang Wei0Gong Xiao-xing1Peng Fei-fei2School of Geoscience and technology, Southwest Petroleum University, Chengdu, ChinaCollege of energy resources ,Chengdu University of Technology ,Chengdu, ChinaExploration and development research institute of Dagang Oilfield, CNPC, Tianjin, ChinaDue to the high exploration cost, limited number of wells for source rocks drilling and scarce test samples for the Total Organic Carbon Content (TOC) in the Huizhou sag, the TOC prediction of source rocks in this area and the assessment of resource potentials of the basin are faced with great challenges. In the study of TOC prediction, predecessors usually adopted the logging assessment method, since the data is only confined to a “point” and the regional prediction of the source bed in the seismic profile largely depends on the recognition of seismic facies, making it difficult to quantify TOC. In this study, we combined source rock geological characteristics, logging and seismic response and built the mathematical relation between quasi TOC curve and seismic data based on the TOC logging date of a single well and its internal seismic attribute. The result suggested that it was not purely a linear relationship that was adhered to by predecessors, but was shown as a complicated non-linear relationship. Therefore, the neural network algorithm and SVMs were introduced to obtain the optimum relationship between the quasi TOC curve and the seismic attribute. Then the goal of TOC prediction can be realized with the method of seismic inversion.https://doi.org/10.1515/pomr-2017-0058huizhou sagsource rocktocseparate-frequency inversiongeophysical prediction
collection DOAJ
language English
format Article
sources DOAJ
author Yang Wei
Gong Xiao-xing
Peng Fei-fei
spellingShingle Yang Wei
Gong Xiao-xing
Peng Fei-fei
Geophysical Prediction Technology Based on Organic Carbon Content in Source Rocks of the Huizhou Sag, the South China Sea
Polish Maritime Research
huizhou sag
source rock
toc
separate-frequency inversion
geophysical prediction
author_facet Yang Wei
Gong Xiao-xing
Peng Fei-fei
author_sort Yang Wei
title Geophysical Prediction Technology Based on Organic Carbon Content in Source Rocks of the Huizhou Sag, the South China Sea
title_short Geophysical Prediction Technology Based on Organic Carbon Content in Source Rocks of the Huizhou Sag, the South China Sea
title_full Geophysical Prediction Technology Based on Organic Carbon Content in Source Rocks of the Huizhou Sag, the South China Sea
title_fullStr Geophysical Prediction Technology Based on Organic Carbon Content in Source Rocks of the Huizhou Sag, the South China Sea
title_full_unstemmed Geophysical Prediction Technology Based on Organic Carbon Content in Source Rocks of the Huizhou Sag, the South China Sea
title_sort geophysical prediction technology based on organic carbon content in source rocks of the huizhou sag, the south china sea
publisher Sciendo
series Polish Maritime Research
issn 2083-7429
publishDate 2017-08-01
description Due to the high exploration cost, limited number of wells for source rocks drilling and scarce test samples for the Total Organic Carbon Content (TOC) in the Huizhou sag, the TOC prediction of source rocks in this area and the assessment of resource potentials of the basin are faced with great challenges. In the study of TOC prediction, predecessors usually adopted the logging assessment method, since the data is only confined to a “point” and the regional prediction of the source bed in the seismic profile largely depends on the recognition of seismic facies, making it difficult to quantify TOC. In this study, we combined source rock geological characteristics, logging and seismic response and built the mathematical relation between quasi TOC curve and seismic data based on the TOC logging date of a single well and its internal seismic attribute. The result suggested that it was not purely a linear relationship that was adhered to by predecessors, but was shown as a complicated non-linear relationship. Therefore, the neural network algorithm and SVMs were introduced to obtain the optimum relationship between the quasi TOC curve and the seismic attribute. Then the goal of TOC prediction can be realized with the method of seismic inversion.
topic huizhou sag
source rock
toc
separate-frequency inversion
geophysical prediction
url https://doi.org/10.1515/pomr-2017-0058
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AT gongxiaoxing geophysicalpredictiontechnologybasedonorganiccarboncontentinsourcerocksofthehuizhousagthesouthchinasea
AT pengfeifei geophysicalpredictiontechnologybasedonorganiccarboncontentinsourcerocksofthehuizhousagthesouthchinasea
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