Transforming Drilling Operations with Intelligent Reporting: Leveraging AI to Cut Downtime, Drive Efficiency, and Maximize Well Performance

Abstract In the rapidly evolving landscape of petroleum exploration and production, efficient data management and analysis are critical for maximizing operational efficiency and profitability. Recognizing this, we have developed a unique automated data analytical portal designed to streamline data gathering, analysis, and decision-making processes for oil and gas operators. This platform allows for the effortless aggregation and analysis of data from single wells, multiple wells across various petroleum disciplines, or entire project datasets. The primary objective of our portal is to reduce downtime, enhance operational planning, decision-making capabilities, and ultimately increase profitability for operators. In today's high-stakes drilling landscape—where cost control, operational precision, and performance optimization are paramount—the ability to transform raw operational data into actionable insights offers a vital competitive edge. This paper introduces an AI-enabled intelligent reporting framework that empowers drilling teams to make real-time, data-driven decisions, thereby minimizing nonproductive time (NPT), reducing invisible lost time (ILT), and improving overall well economics. The objective is to establish a unified, intelligent drilling ecosystem that integrates real-time data capture, automated KPI tracking, and advanced analytics into a centralized reporting platform. The system leverages live data from both surface and downhole sensors to compute and visualize key performance indicators (KPIs) such as connection time, reaming duration, rate of penetration (ROP), and torque and drag—enabling proactive operational control and continuous performance enhancement. Key capabilities include: Pattern-based benchmarking of connection times to identify and eliminate inefficiencies Real-time optimization of reaming practices through historical trend analysis Automated torque and drag analysis to improve hole cleaning and reduce mechanical risks Role-based, real-time reporting tailored to crew members, engineers, and managers for faster and more informed decision-making This approach demonstrates how AI-driven reporting can drive measurable improvements in both operational and financial KPIs. By seamlessly integrating real-time data, adaptive analytics, and automated decision support, the platform fosters a proactive drilling culture that continuously learns, reduces manual interventions, and delivers consistent, high-value outcomes across diverse drilling campaigns.