Overcoming Barriers to Adoption of Drilling Automation: Moving Towards Automated Well Manufacturing

Abstract

Abstract There has been a growing interest in automated drilling in the recent decade, motivated primarily by increased well construction efficiency, enhanced safety and well quality requirements. Many drilling tasks have been successfully automated and pilot technologies have been deployed, but broader adoption has remained slow. This can be attributed to some key factors. First, no two wells or rigs are the same. So the concept of “developing one algorithm applicable to all scenarios” is difficult except in the simplest of cases where only a limited set of tightly integrated sensors and actuators are involved. Secondly, full automation requires cohesive data and information integration between multiple stakeholders: the operator, the service provider, the drilling contractor and the equipment manufacturer. No efficient mathematical construct has been adopted for integrating data / information from these different stakeholders. Thirdly, any drilling automation task requires the full buy-in of the drilling crew, which is often difficult when these algorithms are presented as black-box solutions and it is unclear how to bring the rig to a safe condition when automation fails. A mathematical construct, and the methodology / architecture is presented that would enable one to combine information and data from multiple sources in a meaningful way and the rapid development of intuitive control algorithms that can be easily understood without advanced degrees or training is demonstrated. The algorithm development process is purposefully simplified, allowing for well engineers to easily develop their own control strategies while enabling rig- and site-specific customization. Additionally, the visual nature of the methodology enables easy monitoring by the rig crew for troubleshooting purposes. Automation scenarios are presented for tripping and Managed Pressure Drilling operations that demonstrate the ease of use. Multiple control strategies are developed for each task, and compared against criteria that include easy comprehension of the algorithm and optimality. This automation approach can help reduce some of the current barriers to broad scale adoption of automation.