Machine learning prediction of fracture length in tight reservoirs by integrating geostress characteristics

LU XUEJIAO; LI HONGCHANG; LI YUZHENG; WANG SIYI; WANG JING; YANG HUANYING; PING YI

doi:10.13809/j.cnki.cn32-1825/te.2025253

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Machine learning prediction of fracture length in tight reservoirs by integrating geostress characteristics

更新时间：2025-12-29

- Machine learning prediction of fracture length in tight reservoirs by integrating geostress characteristics
- “In the field of tight oil reservoir development in Huaqing Oilfield, Ordos Basin, experts have constructed a multivariate coupling model and developed a fracturing fracture length prediction system, providing theoretical methods and technical paradigms for efficient development.”
- Petroleum Reservoir Evaluation and Development Pages: 1-9(2025)
- 作者机构：
  
  1.中国石油长庆油田分公司勘探开发研究院，陕西西安 710018
  2.低渗透油气田勘探开发国家工程实验室，陕西西安 710018
- 作者简介：
- 基金信息：
- DOI：10.13809/j.cnki.cn32-1825/te.2025253
  CLC： TE348
- Received：28 May 2025，
  
  Published Online：29 December 2025，
- 稿件说明：
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陆雪皎,李洪畅,李宇征等.融合地应力特征的致密储层压裂缝长机器学习预测[J].油气藏评价与开发,

LU Xuejiao,LI Hongchang,LI Yuzheng,et al.Machine learning prediction of fracture length in tight reservoirs by integrating geostress characteristics[J].Petroleum Reservoir Evaluation and Development,
陆雪皎,李洪畅,李宇征等.融合地应力特征的致密储层压裂缝长机器学习预测[J].油气藏评价与开发, DOI：10.13809/j.cnki.cn32-1825/te.2025253.XXXX, XX(XX): 1-9.

LU Xuejiao,LI Hongchang,LI Yuzheng,et al.Machine learning prediction of fracture length in tight reservoirs by integrating geostress characteristics[J].Petroleum Reservoir Evaluation and Development, DOI：10.13809/j.cnki.cn32-1825/te.2025253.XXXX, XX(XX): 1-9.

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Machine learning prediction of fracture length in tight reservoirs by integrating geostress characteristics

DOI：10.13809/j.cnki.cn32-1825/te.2025253