Reducing Non-Productive Time (NPT) in Oil Well Drilling: A Comprehensive Approach using Learning Management Systems

Document Type : Original Article

Authors

1 Kuwait Oil Company (KOC), Kuwait

2 Petroleum Engineering Department, Faculty of Petroleum and Mining engineering, Suez University, Egypt. Department of petroleum Engineering, Faculty of Engineering and Technology, Future University in Egypt, Cairo

3 Petroleum Engineering Department, Faculty of Mining and Petroleum engineering, Al-Azhar University, Egypt Department of petroleum Engineering, Faculty of Engineering and Technology, Future University in Egypt, Cairo

Abstract

Nonproductive Time (NPT) in the drilling operations is a longstanding inefficiency in the oil and gas industry, leading to well delivery delays, production losses, and reduced profitability. To address these challenges, a new methodology integrates advanced software with a specialized Learning Management System (LMS) designed to minimize NPT while driving continuous improvement in drilling operations. This system enables an automated monitoring and mapping of NPT events, allowing rapid identification of operational issues and their root causes with effective learning. By systematically addressing these issues, it significantly reduces NPT and enhances daily operational efficiency.
The LMS plays a vital role by capturing and sharing learning and root causes from NPT incidents, fostering a culture of learning that prevents repeated errors. This paper introduces a proactive approach to NPT reduction, with a user-friendly interface, the automated investigation system helps to standardizes NPT definitions and centralizes knowledge, reducing the effect of staff turnovers lack of experience.
In initial trials, this methodology has reduced NPT from 24.9% to 17.7%, saving over 450 operational days annually across 26 rigs, equivalent to drilling an additional 14 wells per year. This improvement translates to over $40 million in savings per rig set yearly. Additionally, rig contractor-related NPT dropped from 11.2% to 5.4%, with significant gains in productivity and operational efficiency

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