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The oil and gas industry has relied on traditional computers to tackle their mathematical challenges for decades 

Despite the significant improvements in the speed and precision of classical supercomputers, they can sometimes fall short when calculations involve multiple variables. This limitation could be overcome with quantum computers, which, in theory, can perform some of the most complex computations, says GlobalData, a data and analytics company.

The companys thematic report, Quantum Computing in Oil and Gas, provides an overview of the quantum computing technology and its potential implications in oil and gas operations. It also highlights the role of major oil and gas companies, such as BP, ExxonMobil, Equinor, Shell and TotalEnergies in the development of quantum computing to address complex business problems.

Ravindra Puranik, oil and gas analyst at GlobalData, comments, “Although the technology is still in the research and development stage, its potential use cases in the oil and gas industry are numerous and are likely to expand. Several promising areas of application have been identified, and companies are collaborating with technology players to advance their research. Oil majors, such as BP and ExxonMobil have joined IBM’s Q Network to develop quantum computers that will increase the understanding of subsurface geology.”

Quantum computers use the properties of quantum physics to store data and perform computations. There are many technologies with the potential to build their foundational quantum bits (qubits). However, it may be over a decade before quantum computing enters the commercial mainstream.

Puranik continues, “Nevertheless, companies are looking at these computers to study aspects, such as molecular modeling and emission mitigation. Besides, the longstanding problems of matching demand with production and optimising supply chains could be solved using quantum computing. As the technology is still at an early stage, companies have refrained from making any major acquisitions. However, venture financing deals have shown promise, with the total deals value staying above US$150mn after reaching a peak in Q3 2021. In January, French firm Pasqal raised around US$108mn in Series B funding from multiple investors, including Saudi Aramco.”

Quantum computing has the potential to solve complex mathematical problems faster and more accurately than traditional computers. Such information could assist companies in faster decision-making to minimise risks and optimise operational costs.

Puranik concludes, “Oil and gas industry leaders are experimenting with the quantum computing devices that are available today. This would help them build an understanding of this technology. It would also give them a first mover advantage when such computers actually become available.

“Upstream use cases continue to be the focus area of most companies. In this regard, Baker Hughes has filed several patents on the application of quantum computing in the drilling of oil wells. Besides, companies such as TotalEnergies, ExxonMobil, and Shell are leveraging quantum simulations to identify suitable materials for carbon capture technologies, which are key to the energy sector to achieve carbon neutrality and mitigate climate change.”

Yokogawa Electric Corporation has announced the launch of a reinforcement learning service for edge controllers 

This autonomous control service for OpreX Realtime OS-based Machine Controllers (e-RT3 Plus) utilises the Factorial Kernel Dynamic Policy Programming (FKDPP) reinforcement learning AI algorithm, and consists of packaged software and an optional consulting service and/or a training programme, depending on end user requirements. This software is being released globally, while consulting and the training programme will be provided first in Japan, then in other markets.

Development background

Given the complexity of the physical, chemical, and other processes at actual plants, there are still many areas that require the intervention of veteran operators, and controlling these areas is often difficult and has a direct impact on product quality and profitability. Conventional control technologies include PID control*1 and advanced process control (APC)*2. Achieving complex control using PID control or APC may sometimes require adjustments, which can take a considerable amount of time and effort. Also, some areas of plant operations are not suitable for PID control or APC and must be controlled manually, requiring operators to exercise judgement when entering control inputs. The autonomous control AI is a new technology for such situations that achieves complex control and eliminates the need to rely on manual operations. 

Product and service features

FKDPP is a new control technology that is different from PID control and APC. In March 2022, it was announced that Yokogawa and JSR Corporation’s elastomer business unit (now owned by ENEOS Materials) had successfully concluded a 35 day field test in which AI was used to autonomously control a facility in a chemical plant that could not be controlled using existing control methods and had necessitated the manual operation of control valves based on the judgements of plant personnel.

To use this system, edge controllers (sold separately), access to the autonomous AI learning service, a software package for the implementation of AI control models on edge controllers, and a license to run AI control models are required. Depending on the application, training programme related consulting services, engineering services, and more are available to help users get started.

Kenji Hasegawa, a Yokogawa vice-resident and head of the Yokogawa products headquarters, added, “Control is an important part of product quality and customer revenue, but the know-how of veteran operators has been essential. We believe the autonomous control AI (FKDPP) is a disruptive innovation that will address the concerns of customers who have issues with conventional control technologies, and this will do so in a number of new ways. In the future, we will also open up a new field that will involve the achievement of flexible control based on management strategy. By providing value to our customers, we will contribute to the sustainable development of industry, while minimisng the impact on the environment, and lead IA2IA – the transition from industrial automation to industrial autonomy."

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