Petroleum Science and Technology Forum ›› 2018, Vol. 37 ›› Issue (4): 32-40.DOI: 10.3969/j.issn.1002-302x.2018.04.006

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Application and Influence of Artificial Intelligence in Petroleum Engineering Area

Liu Wei1,Yan Na2   

  1. 1. CNPC Engineering Technology R&D Company Limited, Beijing 102200, China; 2. Sinopec Research Institute of Petroleum Engineering, Beijing 100101, China
  • Online:2018-09-26 Published:2018-09-26
  • Supported by:
     

人工智能在石油工程领域应用及影响

刘 伟1 闫 娜2   

  1. 1. 中国石油集团工程技术研究院有限公司;2. 中国石化石油工程技术研究院
  • 基金资助:
    中国石油天然气集团公司基础研究和战略储备技术基金课题“智能钻井控制关键模型与方法研究”(编号: 2017D5008-04)。

Abstract: Study and application of artificial intelligence (AI) in the petroleum engineering area has a history of decades with the application scope covering a variety of links from management to exploration and development. Investigation of SPE specialized databank indicates that the enthusiasm for AI research has remained high in the petroleum engineering area since 2000. The number of published research papers has grown dramatically since 2010. In the area of management, the AIbased intelligent work flow develops into the cross-disciplinary work platform in collaboration of multiple links. The AI-based specialized management tools replace some of the employees while the AI-based assets management tools provide predicative maintenance with higher efficiency and accuracy. Application of various AI analysis methods for seismic data analysis lays a solid foundation for more accurate drilling. AI application for drilling design and service promotes drilling automation with higher safety and efficiency. AI application for reservoir development maximizes the production in the full oilfield service life period. Based on analysis of the successful application cases from oil companies and oilfield service companies, this paper analyzes the potential AI influence on work efficiency, investment performance, company’s organizational structure and work flow and industrial competition trend in the petroleum engineering area. Focusing on the main barriers for largescale commercialized AI application, such as credibility and confidentiality of data, this paper comes up with a series of measures, including making plans for research and development of related technology and equipment at an early time, studying interpretability AI technology and promoting standardized management of industrial data.

 

摘要: 人工智能在石油工程领域的研究应用已有几十年历史,应用范围渗透到从管理到勘探开发施工现场的各 个环节。SPE 专业数据库调查显示,从2000 年开始,石油工程领域对AI 保持了较高的研究热情,2010 年之后公开发 表的研究文章数量大幅增长。在管理领域,基于AI 的智能工作流,形成了多学科、多环节协作的工作平台;基于AI 的专项管理工具已替代部分人类员工;基于AI 的资产管理工具提供了更高效准确的预测性维护。多种AI 分析方法在 地震资料分析中的应用,为更精确钻井提供了坚实基础;在钻井设计和施工中的应用,促进了钻井自动化和更安全、 更高效;在油藏开发中的应用,促进油田在整个生命周期的产出最大化。通过剖析油公司、油服公司的成功应用案例, 分析AI 对石油工程领域的工作效率、投资效益、公司组织结构及流程、行业竞争态势的潜在影响,并针对AI 大规模 商业化应用所面临的可信任程度、数据保密性等主要障碍,提出了及早谋划相关技术研发和储备、攻关可解释型人工 智能技术、推动行业数据标准化管理等应对措施。

关键词: 人工智能, 石油工程, 大数据, 自动化, 黑箱

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