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作 者:赵汩凡[1] 李婧[1] 光新军[1] 马广军[1] ZHAO Gufan;LI Jing;GUANG Xinjun;MA Guangjun(SINOPEC Petroleum Engineering Technology Research Institute Co.,Ltd.,Beijing 102206,China)
机构地区:[1]中国石化石油工程技术研究院有限公司,北京102206
出 处:《石油化工应用》2024年第12期1-7,共7页Petrochemical Industry Application
基 金:国家知识产权局专利专项研究项目“智慧油气藏数字孪生技术专利分析研究”(FX202304)。
摘 要:专利因具有及时性、完备性、公开性等特点,在技术挖掘和创新等领域的重要性不断提升。钻井参数优化技术是实现高效率、高质量、低成本钻井的关键,受到国内外各研发机构和公司的高度重视,2011年后专利申请量逐步增加,目前仍处于快速发展阶段。国内外各大石油公司、油田技术服务公司申请了很多钻井参数优化技术专利,其中申请量主要集中在美国。钻井参数优化技术专利主要涉及利用机器学习、深度学习方法进行实时数据的综合获取、优化或预测等方面。建议国内相关企业应开发适合不同区域特点的系列钻井参数优化技术,同时加大专利申请量,采用跟踪学习、周边布局的方式,及早在潜在市场进行布局。同时强化与科研院校或大数据公司研发团队多方位、多层次的合作,推进钻井参数优化技术创新。Due to the characteristics of timeliness,completeness and openness,the importance of patents in the fields of technology mining and innovation has been increasing.Drilling parameter optimization technology is the key to realize high-efficiency,high-quality and low-cost drilling,and has been highly valued by domestic and foreign research and development institutions and companies,and the number of patent applications has been gradually increasing after 2011,and is still in the stage of rapid development.Domestic and foreign major oil companies and oilfield technology service companies have applied for many patents on drilling parameter optimization technology,of which the application volume is mainly concentrated in the United States.The drilling parameter optimization patent technology mainly involves the use of machine learning and deep learning methods for comprehensive acquisition,optimization or prediction of real-time data.It is suggested that relevant domestic enterprises should develop a series of drilling parameter optimization technologies suitable for the characteristics of different regions,and at the same time,increase the number of patent applications,and adopt the methods of tracking and learning and peripheral layout,so as to make an early layout in the potential market.At the same time,strengthen multi-faceted and multi-level cooperation with scientific research institution or big data companies,and promote technological innovation of drilling parameter optimization.
分 类 号:TE242[石油与天然气工程—油气井工程]
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