油气勘探智能化方法落地应用的几个关键问题与思考  

Key Problems and Thoughts Related to Application of Intelligent Methods for Oil and Gas Exploration

作　　者：杨午阳[1] 杨谟玮 Yang Wuyang;Yang Mowei(PetroChina Research Institute of Petroleum Exploration and Development-Northwest,Lanzhou 730020,China;Institute of Materials Science and Engineering,Beijing University of Technology,Beijing 100022,China)

机构地区：[1]中国石油勘探开发研究院西北分院 [2]北京工业大学材料与制造学部材料科学与工程系

出　　处：《石油科技论坛》2024年第6期21-27,55,共8页PETROLEUM SCIENCE AND TECHNOLOGY FORUM

基　　金：中国石油天然气集团有限公司关键核心技术项目“碳酸盐岩储层裂缝识别与表征关键技术研究”(编号:2024ZG21);中国石油天然气股份有限公司科技项目“油气勘探开发人工智能关键技术研究”(编号:2023DJ84)。

摘　　要：人工智能技术在油气领域的应用迎来前所未有的发展机遇,其技术应用还需要经历一段时间的探索、磨合和积累。分析油气勘探领域智能化应用落地面临的几个关键问题,即应用场景、标签数据集构建、网络可解释性、专家领域知识嵌入和物理机制约束、智能化框架与平台等。结合当前技术发展现状,提出人工智能落地应用的相关建议和解决方案。理解和解决这些关键问题,有助于挖掘数据价值,优化企业科研布局,明确攻关目标,构建研发生态,助力人工智能技术切实落地应用。There is an unprecedented development opportunity for application of artificial intelligence technology in the oil and gas sector.However,application of this technology still calls for a period of time for study,coordination and accumulation.This article analyzes some key problems facing application of AI technology in the oil and gas exploration sector,such as application scenarios,construction of label data sets,network interpretability,the embedded knowledge of experts and physical mechanism constraints,and intelligent framework and platform.Based on the present conditions of technological development,the article also comes up with the suggestions and solutions related to AI application.Understanding and settlement of those key problems are helpful to mining the data values,optimize the R&D plans of an enterprise,identify the research targets,construct the R&D environment,and facilitate actual application of AI technology.

关 键 词：智能化 场景 标签 可解释性 专家领域知识嵌入 物理机制约束 智能化框架 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] P631[自动化与计算机技术—控制科学与工程]