Moving Toward Smart Monitoring and Predictive Maintenance of Downhole Tools Using the Industrial Internet of Things IIoT

Abstract

Abstract While all other industries are aligned with the digital evolution, oil and gas operations have also taken advantage of the importance of the digital transformation, especially in the actual context. Our industry is arguably in a new wave of the digital oilfield, with a growing consensus toward "smart" operations and "predictive" maintenance instead of the "reacting better" approach, which is not adequate in the new industry conditions and has been proven as an inefficient approach. Oil and gas operators and services companies have a major opportunity to increase efficiency and reduce operational costs through better asset tracking and predictive maintenance, combined with operations and technology expertise. This paper will focus on the maintenance management of downhole equipment, evolving in an unforgiving downhole environment, which in the case of equipment failure, can cause high financial losses. It will also present a use case and opportunities and challenges of smart monitoring and the predictive equipment maintenance approach, which is supported by newer technologies, such as the industrial internet of things (IIoT) and data analytics that use machine learning (ML) algorithms compared to the traditional, reactive approaches to equipment maintenance.