From Data to Impact: Lessons Learned in Leveraging Digitalization and Machine Learning to Boost Operational Efficiency and ESG Performance in Drilling Rigs
Authors: Poludasu S. , Hidad S. , Groh A. , Godumagadda A. , van Wissenkerke M. Snijder , Harrist J. 
Published: February 2025

While there is significant enthusiasm for leveraging data to drive optimization, discussions rarely focus on the challenges associated with the real-time deployment of data-driven workflows. This paper addresses these challenges, highlighting the crucial need for synergy between data, engineering expertise, technology, and organizational commitment to convert data-driven insights into tangible efficiency gains and reduced emissions. It details lessons learned from a drilling contractor's perspective in developing and implementing a data-driven performance evaluation system for a fleet of over a hundred onshore rigs.

This paper highlights the significance of robust data architecture, which is crucial for improving the system's reliability in developing representative models and metrics for the rig performance evaluation system. These metrics cover multiple dimensions of rig performance, including Health, Safety, and Environmental (HSE) standards, drilling performance, resource management, and financial metrics. The selection of these metrics and their targets was informed by data trends and stakeholder expectations, with a strong emphasis on prioritizing safety, ensuring that all targets adhered to strict safe operating standards. Initially introduced in 2019, the performance evaluation system underwent a significant update in early 2022 to better reflect the benefits of advancements in automation, technology, and training available to rig crews. An ESG metric was added to the evaluation system to support the organization's commitment to sustainability. This ESG metric employs ensemble machine learning and on-rig edge devices to assess CO2 emissions against modeled targets. The automated system detailed in this paper produces standardized scores based on these metrics, enabling the monthly assessment of individual rig performance, and ensuring continuous improvement aligned with environmental and efficiency goals.

Since updating the evaluation system in early 2022, standardized scores have increased by an average of 20% across the fleet. The addition of the ESG metric has led to a 4% reduction in CO2 emissions across the fleet over the past year. The automated performance evaluation system has promoted positive competition among rig crews, motivating them to enhance efficiency and performance. Accurate and representative metrics have been essential for establishing these achievable targets. Additionally, the standardized scores also help technical support staff identify challenges faced by rig crews and determine the necessary training for effectively utilizing drilling automation and optimization technologies available on the rigs.

This paper offers valuable insights into the practical challenges and successes associated with the application of digitalization and machine learning in the drilling industry. The focus on reducing emissions and improving fleet-wide performance highlights how drilling contractors can make incremental gains through data-driven insights and a focus on human factors.