期刊文献+

2020国外石油物探技术进展与趋势 被引量:1

Development and trend of foreign petroleum geophysical exploration technologies in 2020
下载PDF
导出
摘要 为了解2020年国外石油物探业务和技术的主要进展及发展趋势,对EAGE(欧洲地质学家与工程师学会)和SEG(国际勘探地球物理学家学会)年会与展会情况,及国外主要石油物探技术服务公司的业务发展与技术研发动态进行跟踪。2020年新冠肺炎疫情叠加低油价冲击,对石油物探技术服务需求和地震作业活动产生重大负面影响,尚未完全复苏的石油物探行业再次面临巨大挑战和压力。石油物探业务发展更加依赖轻资产业务,石油物探技术更加依赖低成本、高效、环保型技术。基于人工智能的地震数据处理解释技术快速发展,软件产品不断完善,基于云的石油物探综合数据管理方案是行业发展热点。 In order to grasp the main progresses and development trends of foreign petroleum geophysical exploration business and technologies in 2020,the European Association of Geoscientists&Engineers and Society of Exploration Geophysicists annual meetings and exhibitions,and the business development and technology research and development trends of major foreign geophysical exploration technology service companies were tracked.The COVID-19 epidemic and low oil price have a significant negative impact on the geophysical exploration service demand and seismic operation activities in 2020.The petroleum geophysical industry,which has not yet fully recovered,is facing enormous challenges and pressures again.The development of geophysical exploration business relies more on asset light business,and geophysical technology relies more on low-cost,efficient and environmental protection technology.With the rapid development of seismic data processing and interpretation technology based on artificial intelligence,the software products are constantly improved.And the integrated geophysical data management scheme based on big data cloud computing is the hot spot of petroleum geophysical exploration development.
作者 李晓光 吴潇 LI Xiaoguang;WU Xiao(CNPC Economics and Technology Research Institute,Beijing,100724,China)
出处 《世界石油工业》 2020年第6期40-48,共9页 World Petroleum Industry
基金 中国石油集团经济技术研究院课题“2019-2020年石油科技信息研究”(编号:2019Z16)。
关键词 石油物探 海底节点 地震数据处理 可控震源 最小二乘偏移 全波形反演 机器学习 人工智能 geophysical exploration ocean bottom node(OBN) seismic data pricessing controlled source least square migration(LSM) full waveform inversion(FWI) machine learning(ML) artificial intelligence(AI)
  • 相关文献

参考文献6

二级参考文献48

共引文献134

同被引文献2

引证文献1

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部