Developing Human-Inspired Operational Intelligence for Drilling Interventions Using Generative AI

View at publisher
Authors: Neha Jamil, Mohammad Rasheed Khan, Syed Hassan Ali Shah
Cited by: 0

Abstract

Abstract In today’s complex drilling environment, quick access to operational knowledge is vital for effective decision making. This work introduces a system that combines real time intervention recording with generative artificial intelligence to close the gap between historical data and field requirements. All intervention details are captured automatically through a custom platform, creating a complete and traceable operational record that serves as the foundation for intelligent analysis. A generative artificial intelligence layer powered by the Gemma model provides direct access to this operational database. Instead of depending on static dashboards or manual reviews, the system interprets user queries, searches relevant data segments, and generates summaries or recommendations that reflect expert level reasoning. This interaction transforms drilling data into an intelligent decision support system that enhances both speed and clarity in operational responses.

Fields of Study & Subjects

Drilling and Well Engineering Artificial Intelligence Applications Oil and Gas Production Techniques

Publication details

Publication date
13 January 2026