Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural Network
Due to the lack of drilling data and poor quality of seismic data in deep-water offshore areas, conventional methods cannot effectively predict the total organic carbon (TOC) content. In this paper, the BP neural network method is used to predict the TOC of the strata overlying the target layer, whi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Geofluids |
| Online Access: | http://dx.doi.org/10.1155/2023/4803616 |
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| _version_ | 1849413349338513408 |
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| author | Jizhong Wu Ying Shi Qianqian Yang Yanan Wang |
| author_facet | Jizhong Wu Ying Shi Qianqian Yang Yanan Wang |
| author_sort | Jizhong Wu |
| collection | DOAJ |
| description | Due to the lack of drilling data and poor quality of seismic data in deep-water offshore areas, conventional methods cannot effectively predict the total organic carbon (TOC) content. In this paper, the BP neural network method is used to predict the TOC of the strata overlying the target layer, which adds to the TOC information in the study area. Then, the highest TOC value of the strata overlying the target layer is used to select the most sensitive seismic attributes. Finally, the sensitive seismic attributes are used to evaluate the source rocks with no or few wells. A set of TOC prediction technology flows is established for TOC combined with seismic attributes under the condition of no wells and few wells in deep-water areas. The application example shows the reliability of TOC prediction by this technical process, and the study has a certain reference significance for the evaluation of hydrocarbon source rocks in offshore deep water. |
| format | Article |
| id | doaj-art-678ca5fc07f142f08f3775f9ed2b9822 |
| institution | Kabale University |
| issn | 1468-8123 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geofluids |
| spelling | doaj-art-678ca5fc07f142f08f3775f9ed2b98222025-08-20T03:34:09ZengWileyGeofluids1468-81232023-01-01202310.1155/2023/4803616Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural NetworkJizhong Wu0Ying Shi1Qianqian Yang2Yanan Wang3School of Bohai Rim EnergySchool of Earth SciencesSchool of Bohai Rim EnergySchool of EnergyDue to the lack of drilling data and poor quality of seismic data in deep-water offshore areas, conventional methods cannot effectively predict the total organic carbon (TOC) content. In this paper, the BP neural network method is used to predict the TOC of the strata overlying the target layer, which adds to the TOC information in the study area. Then, the highest TOC value of the strata overlying the target layer is used to select the most sensitive seismic attributes. Finally, the sensitive seismic attributes are used to evaluate the source rocks with no or few wells. A set of TOC prediction technology flows is established for TOC combined with seismic attributes under the condition of no wells and few wells in deep-water areas. The application example shows the reliability of TOC prediction by this technical process, and the study has a certain reference significance for the evaluation of hydrocarbon source rocks in offshore deep water.http://dx.doi.org/10.1155/2023/4803616 |
| spellingShingle | Jizhong Wu Ying Shi Qianqian Yang Yanan Wang Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural Network Geofluids |
| title | Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural Network |
| title_full | Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural Network |
| title_fullStr | Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural Network |
| title_full_unstemmed | Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural Network |
| title_short | Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural Network |
| title_sort | source rock evaluation of hydrocarbons in deep water offshore areas based on a bp neural network |
| url | http://dx.doi.org/10.1155/2023/4803616 |
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