Guest Editorial: Digitally Transforming Oil Fields With Connected, Intelligent Hardware

Abstract

In recent years, the oil and gas industry has placed significant emphasis on digital transformation. For most early adopters, this journey began with real-time monitoring and remote operation of equipment. This has been followed by the increasing application of modern data science techniques in order to extract actionable insight from the growing volumes of data. The emergence of highly scalable data storage and compute power has provided a step change in the ability to derive actionable insights from data and perform simulations at a scale previously inaccessible. What we derive from this combination allows us to deliver new levels of performance and efficiency. But, in addition to these now well recognized elements of the digital transformation, there is a need to evolve our industry hardware through the application of enhanced edge computing and the application of intelligence at the edge. There will, of course, continue to be engineering innovation in our hardware, resulting from creative new designs that result in new functional features, cost efficiency, enhanced reliability and greater operational performance. But there are now myriad opportunities to enhance hardware in ways that maximize the value of data capture. Thus, the emergence of connected, intelligent hardware is key to realizing the vision of the digitalized oil field. Connected, Intelligent Hardware Explained Much conventional hardware has little to no digital enablement or means of monitoring its own function or state. In a first step, it is largely trivial to make it connected to cloud-based data stores, thus enabling the use of modern data analysis techniques such as artificial intelligence (AI) and machine learning (ML). Each piece of hardware in this scenario will benefit from remote intelligence to enrich its capabilities. Intelligent hardware takes the “connected” concept in another direction and refers to equipment with embedded edge computing that can host models and algorithms, creating capabilities beyond remote intelligence. These machines can now take advantage of both edge and cloud digital capabilities to learn and gain intelligence, thus continuously improving operational performance and service delivery. By populating oil fields with connected and intelligent hardware, operators gain access to optimized, secure, and sustainable operations. Connected and intelligent hardware enables advanced planning, real-time performance optimization, and higher levels of automation and health management. It is a critical part of a broader architecture that is adapted to problems where latency, communications fallibility, and system reliability are important considerations that make a central command-and-control approach inappropriate.