基于深度学习的地震队井深测量

Depth measurement of seismic teams based on deep learning

地石油与天然气是现代工业的“血液”,是国家生存和发展不可或缺的战略资源,对保障国家经济和社会发展以及国防安全有着不可估量的作用。因此石油与天然气的勘探就变得尤为重要。原因是地震勘探作业对于油气资源的寻找和分析起着至关重要的作用,然而作业人员常常会因为工作中的操作不规范,造成采集数据的偏差,影响勘探的判断和结果。除此以外,针对传统质证工作周期长、效率慢的问题,设计了一种智能质证方法。采用基于深度学习的目标检测方法,对地震队工人的作业过程视频进行识别,根据目标检测结果来对工人作业过程中的安全帽、灭火器等安全标志进行判断,并判断量井开始和结束,计算出工人的钻井和量井深度,智能判断作业过程是否合规。该智能质证方法不仅可以检测出作业人员是否有不规范操作,并及时培训学习,而且还可以通过计算机算力代替人力完成传统质证中周期长,效率慢的工作内容。从而保障了更高效的油气勘探任务。

Abs0tract:As the "blood" of modern industry,oil and natural gas are indispensable strategic resources for national survival and development,and play an immeasurable role in guaranteeing national economic and social development and national defense s ecurity.Therefore,oil and gas exploration has become particularly important.The reason is that seismic exploration plays a crucial role in the search and analysis of oil and gas resources.However,operators often have deviations in data acquisition due to non-stan dard operation in their work,which affects the judgment and results of exploration.In addition,aiming at the problem of long working cycle and slow efficiency of traditional cross-examination,an intelligent cross-examination method is designed.Target detection method based on depth of learning,the process of seismic crew workers video identification,according to the results of target detection for workers to work in the process of safety helmet,fire extinguishers and other safety sign to judge,and judge the amount well begin and end,calculate the amount of drilling and well depth of the workers,the intelligence to determine whether a process compliance.This intelligent quality assurance method can not only detect whether operators have irregular operations and Timely train and learn for operators,but also replace human labor with computer power to complete the long cycle and slow efficiency of intelligent quality assurance method.This ensures a more efficient oil and gas exploration mission.