Revolutionizing Drilling Operations: Next-gen Llm-AI for Real-time Support in Well Construction Control Rooms

Abstract In the fast-paced and precision-driven environment of well construction operations, efficient decision-making is paramount. This paper introduces an advanced artificial intelligence (AI) model leveraging Large Language Models (LLM) to classify log records and complex WITSML data in real time. By integrating this AI model into drilling control rooms, decision-making efficiency has been enhanced by over 50 times, significantly reducing the time required for search and background analysis from hours to minutes. The implementation of LLMs such as GPT-3 and GPT-4 has revolutionized the process by enabling zero-shot inference, allowing for the accurate classification of complex texts without extensive labeled training datasets. This breakthrough has facilitated the rapid processing and analysis of structured and unstructured data, which is crucial for real-time response to critical events in drilling operations. A collaborative effort between drilling experts and digital developers resulted in a functional proof of concept within two weeks, expanding to a minimum viable product (MVP) in under 90 days. The AI model now categorizes technical texts into 42 distinct categories, surpassing initial goals and demonstrating substantial improvements in both accuracy and processing speed. This paper concludes by highlighting the significant operational efficiencies and data consistency achieved through the AI model. It also discusses potential future enhancements, including the integration of diversified data sources and the development of predictive and prescriptive models, positioning this AI-driven approach as a cornerstone for future advancements in well construction control rooms.