How is the robotics revolution going to be delivered for the oil and gas industry?

What does an automated and robotised industry look like? 

How will AI and robotics help to re-shape the future?

Champions: Ashok Belani, Susan Nash, Attilio Pisoni, & Joerg Schubert


The advent of robots in industrial automation in the 1960’s was primarily motivated by operational safety. Early on, the feasibility of automation for repetitious tasks was recognized. In the past two decades, mechanization and systems automation has progressed further and is replacing labour in domains hitherto thought to be exclusive to humans (e.g., inventory management and warehouse delivery, infantry, medical diagnosis, surgery etc.) With the decline in price of automation, rapid transformation in a multitude of industries is inevitable and may be hindered only by social constructs.

Robotics are playing an increasingly important role in the oil and gas industry, including upstream, midstream, and downstream.  Innovation in robotics has focused on increasing efficiencies and assuring a safe and fully functional operational environment.

In the oil and gas industry, price decline has imposed an unprecedented drive to reduce E&P costs while improving quality and safety. Automation and customized robots may be the only avenue for this industry to retain its historical profitability.  However, there are pitfalls in the early adoption in robotics since many times, a solution that has been implemented becomes the “legacy” solution and very difficult to modify or expand. Further, as opposed to warehouse operations or factories, the operational environment of data acquisition for upstream (geophysics, etc.), imaging (geological), sampling (geological), drilling, completing, processing, and transportation are highly variable, and often quite remote. Thus, it is not as easy to implement robotics solutions, and they must be able to withstand harsh conditions (arctic, subsea, etc.) and long periods without maintenance.

Nonetheless, the adoption of robotics in oil & gas well-construction has been challenged by process and domain uncertainty, environmental conditions, diverse supply chain and equipment complexity. This is not to belittle advances in dynamic station-keeping to position floating rigs, rotary steerable tools to control drilling trajectory etc. Most modern drilling rigs incorporate mechanized equipment manipulation such as automated pipe-handling that have reduced operating manpower, while increasing efficiency and process consistency. 

The expensive land and off-shore infrastructure that supports the production and transportation of hydrocarbons is inspected by human operators for preventive maintenance, fault diagnosis and regulatory compliance.  Here, repetitive tasks are amenable to robotics with improved efficiency of Inspection, Maintenance and Repair (IMR).  On land, the advent of drones has enabled new and safe approaches for inspection in hazardous locations.  Off-shore, remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) have extended the operator’s ability for subsea infrastructure IMR.  Whether on land or off-shore, regardless of the unstructured environment, oil and gas robotic systems need to be robust and reliable, with sophisticated operational flexibility to complete the desired tasks.
Industrial innovation over the next decade is likely to be led by emerging intelligent systems that rely on sophisticated inferences for performing complex tasks through robotic intermediaries.

The early industrial successes of AI depend on data sourced from diverse sensors, and interconnected distributed computing. Could emerging intelligent systems and availability of prolific data-processing lead to disruptive changes in the domain-knowledge dependent E & P industry where performance reliability despite uncertainty is paramount? If so, are these disruptions going to be timely?

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