地震探鉱・連続モニタリングデータ処理・解析へのAI技術浸透とDX化

抄録

To achieve “carbon neutrality by 2050,” there are many issues related to the monitoring operation in carbon capture and storage/carbon capture utilization and storage（CCS/CCUS）and EGS projects. Mechanization and automation of various monitoring tasks are essential to promote efficiency and cost reduction in the processing and analysis of huge amounts of seismic data and continuous monitoring data. Recent AI technologies, such as deep learning techniques, have shown their ability to compensate for the shortcomings of existing methods and human tasks in CCS/ CCUS and EGS. They are considered helpful tools for DX̶still, the potential risks of applying them need to be taken care and proper actions will have to be given to arising problems. While AI technology is a promising tool for streamlining and reducing the cost of processing and analysis of seismic data and continuous monitoring data, the responsibility for any consequences of using it lies with people. Both developers and users must take responsibility for potential risks when using it. Rather than completely replacing people, AI technologies are expected to gradually penetrate the market, helping to mechanize and improve efficiency so that anyone can complete the necessary tasks.