Home Journals Articles Updates About
CN
image
收藏切换
Establishment of Total Organic Carbon Prediction Method for Shale Reservoirs Using Improved Adaboost-WOA-BP Model: A Case Study of X Area in Longmaxi Formation, Sichuan Basin
收藏切换
PDF
Zhen-ming CHEN, Rui-jie XIE*, Hong-chang PENG, Yao LI, Yong-qiang CAO
Science Technology and Engineering | 2025, 25(2) : 494 - 501
Less
收藏切换
Science Technology and Engineering | 2025, 25(2): 494-501
• Papers·Astronomy and Geosciences •
Establishment of Total Organic Carbon Prediction Method for Shale Reservoirs Using Improved Adaboost-WOA-BP Model: A Case Study of X Area in Longmaxi Formation, Sichuan Basin
Full
Zhen-ming CHEN, Rui-jie XIE*, Hong-chang PENG, Yao LI, Yong-qiang CAO
Affiliations
  • College of Geophysics and Petroleum Resources, Yangtze University, Wuhan 430100, China
Published: 2025-01-18 doi: 10.12404/j.issn.1671-1815.2402873
Outline
收藏切换

The total organic carbon content in shale reservoirs is a crucial parameter for assessing hydrocarbon generation potential and shale gas enrichment. Accurate prediction of TOC(total organic carbon) is essential for oil and gas exploration and development. Conventional linear regression methods are limited in their predictive accuracy due to the complex nonlinear relationships among regional and well logging data. To address this issue, a prediction model based on Adaboost-WOA-BP was proposed for predicting TOC content. This model integrates WOA(whale optimization algorithm) optimized Backpropagation neural networks as weak learners within the Adaboost framework to construct a strong learner. Use of optimal natural gamma, density, acoustic time difference, and other sensitive logging parameters associated with TOC content calculation as inputs for the prediction model. Compared to conventional linear regression, BP neural networks and WOA-BP neural networks, the Adaboost-WOA-BP model demonstrates higher predictive accuracy, achieving a 95% match between predicted and measured TOC values.

neural networks  /  TOC content prediction  /  whale optimization algorithm  /  ensemble algorithm
Zhen-ming CHEN, Rui-jie XIE, Hong-chang PENG, Yao LI, Yong-qiang CAO. Establishment of Total Organic Carbon Prediction Method for Shale Reservoirs Using Improved Adaboost-WOA-BP Model: A Case Study of X Area in Longmaxi Formation, Sichuan Basin[J]. Science Technology and Engineering, 2025 , 25 (2) : 494 -501 . DOI: 10.12404/j.issn.1671-1815.2402873
Appendix
Less
Year 2025 volume 25 Issue 2
PDF
235
86
Cite this Article
BibTeX
Article Info
doi: 10.12404/j.issn.1671-1815.2402873
  • Receive Date：2024-04-19
  • Online Date：2025-12-05
  • Published：2025-01-18
Article Data
Affiliations
History
  • Received：2024-04-19
  • Revised：2024-11-07
Funding
Affiliations
    College of Geophysics and Petroleum Resources, Yangtze University, Wuhan 430100, China
References
Share
https://castjournals.cast.org.cn/joweb/kxjsygc/EN/10.12404/j.issn.1671-1815.2402873
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House