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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Online Access: | https://doi.org/10.1515/pomr-2017-0058 |
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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 |
work_keys_str_mv |
AT yangwei geophysicalpredictiontechnologybasedonorganiccarboncontentinsourcerocksofthehuizhousagthesouthchinasea AT gongxiaoxing geophysicalpredictiontechnologybasedonorganiccarboncontentinsourcerocksofthehuizhousagthesouthchinasea AT pengfeifei geophysicalpredictiontechnologybasedonorganiccarboncontentinsourcerocksofthehuizhousagthesouthchinasea |
_version_ |
1717812975664889856 |