Artificial General Intelligence (AGI) Applications and Prospect in Oil and Gas Reservoir Development
文献类型：期刊论文
| 作者 | Wang, Jiulong1,2; Luo, Xiaotian2,3; Zhang, Xuhui4 ; Du, Shuyi2,3
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| 刊名 | PROCESSES
 |
| 出版日期 | 2025-05-06 |
| 卷号 | 13期号:5页码:16 |
| 关键词 | large language models artificial intelligence oil and gas reservoir development |
| DOI | 10.3390/pr13051413 |
| 通讯作者 | Du, Shuyi(15702449699@163.com) |
| 英文摘要 | The cornerstone of the global economy, oil and gas reservoir development, faces numerous challenges such as resource depletion, operational inefficiencies, safety concerns, and environmental impacts. In recent years, the integration of artificial intelligence (AI), particularly artificial general intelligence (AGI), has gained significant attention for its potential to address these challenges. This review explores the current state of AGI applications in the oil and gas sector, focusing on key areas such as data analysis, optimized decision and knowledge management, etc. AGIs, leveraging vast datasets and advanced retrieval-augmented generation (RAG) capabilities, have demonstrated remarkable success in automating data-driven decision-making processes, enhancing predictive analytics, and optimizing operational workflows. In exploration, AGIs assist in interpreting seismic data and geophysical surveys, providing insights into subsurface reservoirs with higher accuracy. During production, AGIs enable real-time analysis of operational data, predicting equipment failures, optimizing drilling parameters, and increasing production efficiency. Despite the promising applications, several challenges remain, including data quality, model interpretability, and the need for high-performance computing resources. This paper also discusses the future prospects of AGI in oil and gas reservoir development, highlighting the potential for multi-modal AI systems, which combine textual, numerical, and visual data to further enhance decision-making processes. In conclusion, AGIs have the potential to revolutionize oil and gas reservoir development by driving automation, enhancing operational efficiency, and improving safety. However, overcoming existing technical and organizational challenges will be essential for realizing the full potential of AI in this sector. |
| 资助项目 | National Natural Science Foundation of China ; China Postdoctoral Science Foundation[2022M713204] ; [52274027] |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001495679400001 |
| 资助机构 | National Natural Science Foundation of China ; China Postdoctoral Science Foundation |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/101625]  |
| 专题 | 力学研究所_流固耦合系统力学重点实验室(2012-) |
| 通讯作者 | Du, Shuyi |
| 作者单位 | 1.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100083, Peoples R China 2.Natl Dev & Reform Commiss, Natl & Local Joint Engn Lab Big Data Anal & Comp T, Beijing 100083, Peoples R China 3.Univ Sci & Technol Beijing, Sch Civil & Resource Engn, Beijing 100083, Peoples R China 4.Inst Mech, Chinese Acad Sci, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Jiulong,Luo, Xiaotian,Zhang, Xuhui,et al. Artificial General Intelligence (AGI) Applications and Prospect in Oil and Gas Reservoir Development[J]. PROCESSES,2025,13(5):16. |
| APA | Wang, Jiulong,Luo, Xiaotian,Zhang, Xuhui,&Du, Shuyi.(2025).Artificial General Intelligence (AGI) Applications and Prospect in Oil and Gas Reservoir Development.PROCESSES,13(5),16. |
| MLA | Wang, Jiulong,et al."Artificial General Intelligence (AGI) Applications and Prospect in Oil and Gas Reservoir Development".PROCESSES 13.5(2025):16. |
入库方式： OAI收割
来源：力学研究所
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