%0 Journal Article
%T 人工智能识别技术在物探作业涉爆安全质量管理中的应用<br>Application of Artificial Intelligence Recognition Technology in Safety and Quality Management of Explosion Related Geophysical Operations
%A 孙伟鹏
%A 胡善政
%A 黄腾
%A 敬龙江
%A 李彦彰
%A 罗辑
%J Artificial Intelligence and Robotics Research
%P 459-466
%@ 2326-3423
%D 2024
%I Hans Publishing
%R 10.12677/AIRR.2024.132047
%X 随着人工智能技术发展的越发成熟，其实用性在各行业中得到充分发挥及应用，在石油勘探领域，人工智能识别技术的应用越来越广泛，也急需通过人工智能识别技术来解决制约生产和安全管理中的各种瓶颈问题。东方物探公司西南物探分公司将人工智能识别技术应用于四川盆地山地地震勘探项目的涉爆影像自证工序中，协助公司在施工作业安全无事故的大前提下，实现工序安全违章检测“提质、降本、增效”的目标。下面将从人工智能识别技术在山地地震勘探涉爆影像自证工序中的应用背景、现状、在该作业工序安全管理中的应用方案以及人工智能识别技术在该领域中的应用效果几个方面进行阐述。<br />
With the increasingly mature development of artificial intelligence technology, its practicality has been fully utilized and applied in various industries. In the field of oil exploration, the application of artificial intelligence recognition technology is becoming more and more widespread, and there is an urgent need to solve various bottleneck problems in production and safety management through artificial intelligence recognition technology. The Southwest Geophysical Branch of BGP has applied artificial intelligence recognition technology to the self verification process of explosion related images in the Sichuan Basin mountainous seismic exploration project, assisting the company in achieving the goal of “improving quality, reducing costs, and increasing efficiency” in process safety violation detection under the premise of safe construction operations without accidents. The following will elaborate on the application background and current situation of artificial intelligence recognition technology in the self certification process of explosive images in mountain seismic exploration, the application plan in the safety management of this operation process, and the application effect of artificial intelligence recognition technology in this field.
%K 山地地震勘探，人工智能识别，涉爆作业，安全检测，目标检测技术<br>Mountain Seismic Exploration
%K Artificial Intelligence Recognition
%K Explosive Operations
%K Safety Detection
%K Target Detection Technology
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=88748