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Robotics Adoption in Oil and Gas Resources Industry

May 2, 2019

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Our Take on Scaling Robotics Adoption in Oil and Gas Resources Industry

By Vasuki Upadhya, CTO and Digital Lead for Energy and Natural Resources, Wipro Limited.


In recent years the adoption of intelligent robots in the oil and gas industry has accelerated. The industry has used technology like unmanned robots such as Remote Operated Vehicles (ROVs) for subsea pipeline inspection and Unmanned Aerial Vehicles (UAVs) for flare inspection for quite some time.

As technology evolves the robots are becoming increasingly intelligent having the awareness of the context, location and situation. Multiple technologies are converging to make intelligent robots, which not only enables their ability to move around and perform data collection, but also allows the interpretation and analysis of the data to be done by human experts.

Apart from the technology evolution, the reason for increased adoption of robots has been the economic feasibility. Almost every major player in oil and gas has made inroads into building and deploying intelligent robots in operations, especially those which require performing high risk tasks. The move is aligning well with the industry vision of shifting to unmanned platforms or autonomous operations and in the process it improves operational efficiency and benefits health, safety and environment issues. For example, Equinor deployed Eelume robot underwater subsea installations to perform tasks like turning on or off valves and filming pipelines to check for faults; Total deployed a pilot robots in Total’s gas plant on Shetland to perform visual inspection and detect the gas leakages; BP deployed robots and drones in Cherry Point refinery in Washington State to inspect vessels to spot the microscopic cracks in vessel walls of hydrocarbon crackers; Shell deployed self-docking and recharging explosion proof “Sensabots” in manufacturing plants to perform mobile inspections in the area of extreme temperatures and high level of H2S.


The common characteristics across all the above examples are

·         Home grown solution with partner ecosystem by each of these Enterprises

·         The use cases of deploying it in hostile and hazardous environment.

·         The successful deployment in a few areas implies the limited scale and high TCO.

·         Signifies the evolution of robotics technology from data capture to performing tasks in intrinsically safe environment or in the                    subsea operations.

·         There are lot more opportunities to extend the usage of Robotics to solve complex tasks in the field by leveraging the high                        bandwidth connectivity, artificial intelligence, low cost sensors, edge analytics.


It is now time for businesses to scale up robotics adoption by introducing new capabilities with significant reduction in total cost of ownership. This is well corroborated with the data from The Global Robotics Market, which forecasts the expected market growth at a rate of CAGR of 24.52% over the forecast period of 2018-2023. Large oil and gas mining enterprises have already embedded these initiatives such as unmanned operations, autonomous operations, Field of the Future or Mine of the Future.


Foundation blocks for the larger scale adoption of robotics, we see the following aspects.

a.    New Models of delivery of robotics to reduce TCO.

b.    Continuous innovation to embed new capabilities into robots.

c.     Robust Quality assurance or certification process Reliability and Durability Robots

d.    Continuous engagement with stakeholders and user communities to adopt to Cultural change. 


New Delivery Models to reduce the total cost of ownership of robots.

Setting up the robotics innovation centre and labs in low cost countries in a new commercial model like “Lab as a service”, “Lighthouse centre”. Of course these centres have to be located in the place where the best talent available at low cost.     

Innovation around leveraging low cost sensors, new age connectivity solutions like 5G, new age secured IOT data, analytics platforms and remote device management can greatly disrupt the operations technology environment allowing it to be more cost effective, secured, connected and collaborative.

When robots are deployed on the field, the robots have to be managed like similarly to the way the field staff are managed, especially to track and trace, health monitoring, task and task management for example. The remote mobile solution or hologram technology can help simulate the real condition in a virtual control centre. This essentially reduces the turnaround time to fix issues, reduces the cost and improve the safety.


Continuous innovation to embed new capabilities into robots.

The level of intelligence in robotics is increasing exponentially with the advancements in sensor technologies, connectivity, real time decision making at the chip level and at the edge and the power of connecting back to cloud for continuous learnability from the patterns seen on the wider dataset in the cloud. All of which keeps the robot’s software up to date on a continuous basis.

Establish the digital lighthouse and digital pods to perform research-based studies, ideate, envision, prioritise, plan and deliver quick prototypes. This will be a collaborative exercise between business operations team, experience designers, solution designers. The design led ideation with the stakeholders’ provider’s quick iteration churns and demonstrable fit for purpose use cases.

When the idea is moving from concept stage to implementation stage, there is a need for High performance engineering centres that will house multi discipline specialists working as a virtual team. Typically it would be composed of 6-8 member scrum teams delivering features in agile delivery model, let us say every 2 weeks. This team will have automated process software development through DevOps Model. The scrum team of robotics development may house specialist skills like robotics engineers, User experience designers, electrical engineers, Mechanical engineers, data scientists, scrum master & there can be many such teams can work in parallel to deliver their scope.


Robust Quality assurance or certification process:

Reliability and Durability Robots Robotics being another machine on the field, the generic concern around robotics is around reliability, durability and maintenance. That is essentially the number of failures of robotics as a machine, the frequency of failures and the kind of maintenance required. In any case the risk of the current operating environment can be compromised and hence it should be convincing for the operation team see that on the ground. The pilot deployment done so far have proven it to a large extent. However there are still lot more opportunity to mature it to the next level, as in automated health monitoring & notification, failure prediction and self-healing. Additive manufacturing (3D printing) can be explored for cost effective, high durable, just in time component delivery. The intrinsic safe robots are the common ask in the industry and that needs robust quality assurance and certification process. The long-life battery technologies, self-powered cum self-charging capabilities are crucial to minimise the human intervention to make the robots self-sufficient.

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With the evolution of technology, the robotics have to offer new levels capabilities to the oil and gas resources industry. The industry has already gone through the hardships making robots real, but with a limited scale. Given the industry focus of transformation with visions such as unmanned platforms and autonomous operations the time is right to jump start the adoption of robotics in wider scale, thereby the economics of scale would prove to make the case for wider adoption.

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