地层孔隙压力预测的机器学习算法研究进展

IF 1.4 4区工程技术 Q4 ENERGY & FUELS

Petroleum Science and Technology Pub Date : 2024-01-03 DOI:10.1080/10916466.2023.2299711

Haoyu Pan, Song Deng, Chaowei Li, Yanshuai Sun, Yanhong Zhao, Lin Shi, Chao Hu

引用次数: 0

摘要

地层孔隙压力是石油勘探和开发中最重要的基础数据之一。传统的地层孔隙压力预测模型依赖于人工经验...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Research progress of machine-learning algorithm for formation pore pressure prediction

Formation pore pressure is one of the most important basic data in petroleum exploration and development. The traditional prediction model of formation pore pressure relies on artificial experience...

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Petroleum Science and Technology 工程技术-工程：化工

CiteScore

2.90

自引率

13.30%

发文量

277

审稿时长

2.7 months

期刊介绍： The international journal of Petroleum Science and Technology publishes original, high-quality peer-reviewed research and review articles that explore: -The fundamental science of fluid-fluid and rock-fluids interactions and multi-phase interfacial and transport phenomena through porous media related to advanced petroleum recovery processes, -The application of novel concepts and processes for enhancing recovery of subsurface energy resources in a carbon-sensitive manner, -Case studies of scaling up the laboratory research findings to field pilots and field-wide applications. -Other salient technological challenges facing the petroleum industry.