AI Meets Automation: Redefining the Future of Spatial Insights in Upstream

Abstract This paper explores a transformative approach to upstream spatial data management through the integration of artificial intelligence (AI), automation, and web-based geospatial systems. The objective is to accelerate decision-making, enhance data integrity, and reduce project timelines by automating seabed survey workflows using the IOGP Seabed Survey Data Model (SSDM), applying Generative AI for extracting insights from unstructured, multilingual documents, and consolidating surface and subsurface spatial data into a unified web platform. AI-assisted SSDM workflows achieved over 60% reduction in processing time, improving well planning efficiency and minimizing human error. Generative AI successfully converted legacy documents into actionable geospatial intelligence, unlocking previously inaccessible insights. The centralized web map fostered real-time collaboration across disciplines, eliminating data silos and enabling faster decision cycles. This work introduces novel applications of AI and automation in upstream operations, including operationalized SSDM workflows, LLM-driven spatial data extraction, and integrated visualization of surface and subsurface datasets. The results demonstrate tangible benefits—time savings, improved reliability, and enhanced team alignment—providing a scalable model for digital spatial transformation in the energy sector.