IR 4.0 Technologies Enable Breakthroughs in Upstream Production Operations

Abstract

The fourth industrial revolution (IR 4.0) has brought about many exciting and game changing technological advancements in recent years that span across different industries. Our petroleum industry was no exception. In this paper, we will present realizations of IR 4.0's fruitful impact on multiple upstream production engineering and operation problems. The first IR 4.0 technology uses machine learning techniques to predict scale inhibition and design inhibition programs that arrest scale formation. Scale formation is a common oilfield problem that consumes a lot of expense from operators. The machine learning method has shown its ability to curtail such expenses and manage risks associated with scale formation. The second technology is modeling the reliability of downhole Inflow Control Valves (ICVs) and predicting their failure. The technology is based on advanced big data analytics and uses automated statistical techniques to achieve the method objectives. This technology provides production engineers with an analytical decision-making model to predict ICVs failures and suggest the optimum frequency for stroking or cycling of the downhole valves as a preventive maintenance practice. The third IR 4.0 technology is the automated well integrity risk ranking. This particular technology uses smart interfaces and advanced computation algorithms applied on big data to assign (or weigh) risks of a well in terms of well integrity. This intelligent integrity ranking or classification shifts focus to wells prone to integrity failures more than the healthy ones. In addition, the method helps optimize integrity surveillance resources and prevents the obvious setbacks from a well integrity issue. The paper will explain detailed methodologies of all three IR 4.0 technologies and outline expected results from field implementation of those technologies.