Generative AI Powered Virtual Data Rooms for Energy

Abstract

Abstract In the ever-evolving Oil & Gas (O&G) industry, National Oil Companies (NOCs) are central to the management and distribution of critical energy resources. A key aspect of their operations involves conducting bidding rounds to attract investments and forge partnerships for the exploration and development of oil and gas fields. Historically, this process required physical data rooms where interested parties could access confidential information related to the bids. However, with the rise of cloud technology, this practice has been transformed by the introduction of virtual data rooms (VDRs), which offer "a faster, more cost-effective, and efficient way to manage data and information during licensing and bidding rounds" (1). Generative AI, a subset of artificial intelligence, involves models that can generate new data based on patterns learned from existing data. This technology presents remarkable potential in various applications and could "transform the human-machine interaction in the oil and gas industry" (3). When applied to Virtual Data Rooms, Generative AI augments existing processes by extracting summaries from automated document analysis. Gen AI will enhance search and retrieval of data, compared to traditional keyword-based search. Generative AI search functionality significantly improves by understanding data context and intent, allowing for more accurate and relevant search results. Organizing and categorizing documents in a VDR can be a daunting task, particularly during large transactions where the volume of data is overwhelming. Generative AI assists by automatically categorizing and organizing documents based on their relevance.