Theoretical Development of a Digital-Twin Based Automation System for Oil Well Drilling Rigs

Abstract

Advancements in digital technology and digitalization of industrial process have opened new frontiers for the oil and gas industry. The amount of historical data generated from drilled wells over the past decades of operations is currently being digitized and processed to provide operators with the option to make more informed decisions based on previous experiences that current staff may not be aware of due to the constant loss of experience during industry downturns. The industry is combating this loss of experience through the innovative use of digitalization, integrated operations, and automation. Real time support centers operating under integrated operations business model are now utilizing digital twins (high fidelity models of the ongoing process being supported) to run forecasting simulations and compare results to digitalized historical data with the help of artificial intelligence and expert systems to aid with decision making and training junior staff. The existence of high-fidelity models, and digital twins is a solid foundation for automation. In this paper a review of the emergence of these technologies is used to identify where digital twins can be used as the foundation of automation solutions that would shift the focus of drilling crews from efficiency to operation and process safety.