AI in Oil and Gas Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)

January 2021 •
162 pages •
Report ID: 6020214 •
Format: PDF

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The AI in Oil and Gas market was valued at USD 2040.89 million in 2019 and expected to register a CAGR of 10.14% over the forecast period 2021 - 2026. As the cost of IoT sensors declines, more major oil and gas organizations are bound to start integrating these sensors into their upstream, midstream, and downstream operations along with AI-enabled predictive analytics.

- Oil and gas remains as one of the most highly valued commodities in the energy sector. In recent years, there has been an increased focus on improving efficiency, and reducing downtime has been a priority for the oil and gas companies as their profits slashed since 2014, due to fluctuating oil prices. However, as concerns over the environmental impact of energy production and consumption persist, oil and gas companies are actively seeking innovative approaches to achieve their business goals, while reducing environmental impact.
- Additionally, according to the International Energy Agency (IEA), in the OECD countries, the oil price reduced by 40.6% from March to April 2020, nurturing concerns for oil and gas firms. Hence, companies in the oil and gas sector experiment with contemporary technologies to increase their efficiency and revenue. By leveraging artificial intelligence in oil and gas operations, corporations can design algorithms to guide drills on land mass and ocean floor.
- In addition, the Oil and Gas Authority (OGA) is making use of AI in parallel ways, owing to the United Kingdom’s first oil and gas National Data Repository (NDR), launched in March 2019, using AI to interpret data, which, according to the OGA anticipations, is likely to assist to discover new oil and gas forecast and permit more production from existing infrastructures.
- The offshore oil and gas business use AI in data science to make the complex data used for oil and gas exploration and production more reachable, which lets companies to discover new exploration prospects or make more use out of existing infrastructures. For instance, in January 2019, BP invested in Houston-based technology start-up, Belmont Technology, to bolster the company’s AI capabilities, developing a cloud-based geoscience platform nicknamed “Sandy.”
- With the help of the facilitation of the real-time study of multiple data, the solution can provide a digital map of the particular ESPoperations, while effectively creating smart operations. By deploying such advanced technology, AI-based systems will help spot the anomalies and abnormalities by sending important signals to the operators.
- In February 2020, Apergy Corporation launched XSPOC 3.0, the newly developed production optimization software. This development provides a significant number of updates to the XSPOC platform, enabling set point optimization of rod lift wells and AI-driven classifications for ESP wells
- However, high capital investments for the integration of AI technologies, along with the lack of skilled AI professionals, could hinder the growth of the market. A recent poll validated that 56% of senior AI professionals considered that a lack of additional and qualified AI workers was the only biggest hurdle to be overcome, in terms of obtaining the necessary level of AI implementation across business operations.

Key Market Trends
Upstream Operations to Witness a Significant Growth

- Organizations across the world are trying to make the exploration and the production processes more efficient and optimized. The operations in this field are the major factors that are driving the usage of AI in oil and gas companies. The AI tools can help oil and gas companies in digitizing records and can automate the analysis of the gathered geological data and charts, which can lead to potential identification of issues, such as pipeline corrosion or increased equipment usage.
- Oil and gas companies can potentially gain crucial insights to improve their business outcomes in their upstream processes with the integration of AI software. This process would involve the feeding of curated data records and information from data sources to the software that could include structured documents, PDFs, handwritten notes, audio, or video files.
- The market is witnessing many investments by big players in the technology. For instance, in Jan 2019, BP invested in a technology start-up: Belmont Technology to strengthen the company’s AI capabilities by developing a cloud-based geoscience platform. The investment will be used to support BP’s ongoing work in exploring the application of cognitive computing and machine learning in its global oil and gas business.
- AI has multiple applications in the oil and gas industry, such as production optimization with computer vision to analyze seismic and subsurface data faster, downtime minimizing for predictive maintenance for oil and gas equipment, reservoir understanding, and modeling for predicting of oil corrosion risks to reduce maintenance costs. Moreover, the market studied has been witnessing many investments by big players in the technology.
- In Sep 2020, scientists and experts at the Wadia Institute of Himalayan Geology (WIHG) have come up with a new artificial intelligence (AI) based technique to analyse data from seismic waves (natural or induced by explosive material) to ascertain the type of rock formation and geological features beneath the surface, which could help in exploring hydrocarbons, like oil and natural gas, in less time with high efficiency.

North America is Expected to Hold a Significant Market Share

- Owing to the increasing adoption of AI technologies across the oilfield operators and service providers and the robust presence of prominent AI software and system suppliers, especially in the United States and Canada, the North American segment is anticipated to account for the largest share of the AI in the oil and gas market, over the forecast period.
- Factors, such as the strong economy, the high adoption rate of AI technologies across the oilfield operators and service providers, robust presence of prominent AI software and system suppliers, and combined investment by government and private organizations for the development and growth of R&D activities are poised to drive the demand for AI in oil and gas sector, in the region.
- ExxonMobil, one of the leading oil producers in the country, announced its plans to increase the production activity in the Permian Basin of West Texas, by producing more than 1 million barrels per day (BPD) of oil-equivalent by as early as 2024. This is equivalent to an increase of nearly 80 percent compared to the present production capacity.
- In addition, owners and operators in the United States recognize how IT-based automation can productively address the unique challenges of the upstream oil and gas sector. For instance, Baker Hughes uses InForce surface control system which combines the hydraulic power to activate downhole tools and the control logic to govern an intelligent well system. PLC controls system functions for more complex completion configurations. It is primarily used where remote operations must be done through existing SCADA.
- Among all the enabling technologies, Artificial Intelligence is poised to play a significant role for oil and gas industry in the region. AI is also been used to increase the safety of gas stations for preventive maintenance. But there have been growing incidences of fires at the gas stations in North America.

Competitive Landscape
The AI in the oil and gas market is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. The companies are continuously capitalizing on acquisitions, in order to broaden, complement, and enhance its product and service offerings, to add new customers and certified personnel, and to help expand sales channels.

- September 2020 - Intel and Oracle deployed the next generation of cloud-based, high-performance computing (HPC) instances within Oracle Cloud Infrastructure, leveraging the computing performance of 10nm Intel Xeon Scalable processors. Leveraging 3rd Gen Intel Xeon Scalable processors and other improvements in Oracle’s new X9 Generation instance, performance gains may be up to 30% higher on certain workloads compared to older versions. Oracle’s X9 Generation cloud instance is targeted at computationally intensive workloads, such as crash simulations, seismic analysis for oil and gas exploration, and electronic design automation.
- February 2020 - Royal Dutch Shell PLC has been expanding an online program that teaches its employees artificial intelligence skills, part of an effort to cut costs, improve business processes, and generate revenue. Artificial intelligence enables the company to process the vast quantity of data across the businesses to generate new insights, which can keep the ahead of the competition.
- January 2020 - Gazprom and ICS Holding set up a joint venture to develop digital products for the oil and gas industry and roll them out in the Russian and global markets. The development strategy for the new joint venture is aimed at addressing the challenges of digitally transformation in the oil and gas sector through the application of Industry 4.0 technologies.

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