The global artificial intelligence in oil and gas market size was valued at USD 2,257 million in 2022. It is estimated to reach an expected value of USD 5775 million by 2031, registering a CAGR of 11% during the forecast period (2022-2031). Artificial intelligence (AI) is a cost-effective investment in the oil and gas sector. From boiler diagnostics to real drilling, artificial intelligence is employed more frequently to enhance various industries' upstream, middle, and downstream processes. Additionally, the International Energy Agency (IEA) reports that from March to April 2020, the oil price decreased by 40.6% in OECD nations, raising worries for oil and gas companies. As a result, businesses in the oil and gas industry experiment with cutting-edge technologies to boost productivity and profits. Using artificial intelligence in oil and gas operations, businesses may create algorithms that direct drilling on the continents and ocean floors.
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Increasing Focus to Easily Process Big Data
The recent technological enhancements have resulted in the daily generation of massive datasets in the oil and gas exploration and production industries. It has been reported that managing these datasets is a significant concern among oil and gas companies. Moreover, it is anticipated that petroleum engineers and geoscientists spend over half of their time browsing and assembling data.
Unstructured data, such as weather reports, maintenance reports, and media reports, can be analyzed with natural language processing and facilitate business solutions for practical decisions. Emma and Ethan are AI assistants designed for customer support launched by a leading global energy company, Shell. According to Shell, these AI assistants can answer various technical queries related to the lubricant. Such instances reflect the growth of AI in the oil and gas sector because of the growth of Big Data.
Rising Trend to Reduce Production Cost
Oil and gas companies are spending on AI to assisting automate operations, anticipate equipment malfunctions, and boost fossil fuel production while reducing costs. For instance, Norwegian firm Aker BP deployed an AI program from Texas-based SparkCognition to trace data from sensors appended to a suitable pump at an unmanned oil platform and detect glitches so that the engineers can intervene and avert shutdowns.
Low oil and gas prices and production residues have driven companies to significantly cut operational production costs to maintain profit margins. According to a new study from Rystad Energy, the United Kingdom reduced the cost of its offshore oil and gas production. For example, between 2014 and 2018, the United Kingdom reduced operational production costs by a hefty 31%. This compares with Norway's cuts of 19% and 15% by the United States. In the UK's case, it was found that operational expenditure (OPEX) per barrel of oil equivalent (boe) fell from more than USD 30 per barrel in 2014 to just USD 16 per barrel in 2019. This almost halved attributable to two main factors. This was owing to the general increase in production due to the automation of the process across various companies. All such factors drive segment growth.
Dearth of Skilled Professionals across the Oil and Gas Industry
This lack of AI-skilled professionals has been hampering the adoption of AI in the oil and gas industry. Furthermore, the oil and gas industry comprises geoscientists, subsea engineers, drilling engineers/ drilling supervisors, subsurface and completions engineers, pipeline and piping engineers, and offshore maintenance technicians. These professionals lack an AI-related skillset.
Moreover, a professional needs to be able to monitor the efficiency of work on a rig and evaluate problems before they even affect the project. The lack of AI skillsets among the oil and gas professional and fewer AI professionals worldwide have been hampering the adoption of the market studied.
High Safety And Security Standards
AI enhances operations during the downstream, midstream, and upstream functions. AI in the oil & gas industry promotes high security and safety standards. Oil & gas are hazardous because of the fuels' flammability and the production of toxic fumes. Artificial Intelligence systems can monitor toxicity levels & leaks and send an alert to repair the flagged issues. Another safety hazard in the oil & gas industry is temperature change. AI can automatically adjust cooling and heating systems so that the product remains safe through the year's changing seasons. Artificial Intelligence will also help alert the maintenance crew when maintenance is needed on any machinery used to process & transport the crude oil.
The global artificial intelligence in oil and gas market is segmented by operation, service type, and region.
By operation, the global artificial intelligence in oil and gas market is segmented into upstream, midstream, and downstream. The downstream dominated the market and is estimated to register a CAGR of 11.1% during the forecast period. The downstream segment of the market studied primarily includes oil refineries, petrochemical plants, natural gas distribution companies, and petroleum product distributors. Gasoline, jet fuel, diesel, lubricants, fertilizers, polymers, natural gas, and propane are just a few of the many items produced by this industry. AI helps refiners in the downstream sector plan optimal blending, anticipate demand, estimate prices, and build relationships with customers. Oil and gas corporations have long employed technology to enhance petrochemicals and refining downstream activities. These businesses have created and implemented cutting-edge methods for controlling complex operations and deciphering data to enhance performance. Given the strategic effort by many firms to develop their downstream operations of the oil and gas value chain, specifically petrochemicals, it is anticipated that the continuous change to becoming digital will bring even greater opportunity.
The midstream segment is the second largest. Improving transparency in the oil supply chain concerning product quality within a company's operations and between counterparties in the market studied is expected to create a significant opportunity for AI to impact the midstream sector. Additionally, the recent surge in basin price differentials has repositioned the midstream sector, where infrastructure planning capabilities have become critical to the market attractiveness and growth opportunities for upstream firms.
By service type, the global artificial intelligence in oil and gas market is segmented into professional and managed services. The managed segment dominated the market and is estimated to register a CAGR of 11.5% during the forecast period. Organizations need to consider vendors as their strategic partners in the rapidly growing technological world of anything-as-a-service. They need to onboard those with capabilities to deliver an end-to-end support system. Owing to the rapidly increasing number of cloud technologies that an enterprise has to work with, the relevance of managed services providers is at an all-time high. Whenever enterprises engage with large MSPs, offering a wide range of advanced technology and infrastructure services, they expect them to take complete responsibility for their operations optimizations. This is the reason that the vendors in the market are offering multiple services to the oil and gas players.
The professional segment is the second largest, primarily owing to the increased usage of digital applications by enterprises worldwide to address their growing issues and quickly create a competitive advantage.
By region, the global artificial intelligence in oil and gas market is bifurcated into North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa.
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North America dominated the market and is anticipated to register a CAGR of 10.7% during the forecast period. One of the biggest and most advanced marketplaces for AI is in North America. The region's strong economy, the high rate of adoption of AI technologies by oilfield operators and service providers, the significant presence of top AI software and system suppliers, and combined investments by government and private organizations for the growth and development of R&D activities are all expected to contribute to the region's demand for AI in the oil and gas sector. Due to its developed infrastructure, which can house cutting-edge technologies in the oil and gas sector, the area is predicted to dominate the global market throughout the projection period. The rising influx of investments will further aid the industry's future expansion into startups for the use of AI.
Asia-Pacific is the second largest region. It is estimated to reach a predicted value of USD 1650 million by 2031, registering a CAGR of 11.7%. Asia-Pacific is the fastest-growing market for digital technologies adoption globally. The Asia-Pacific region has a high demand from the downstream oil and gas sector. The International Energy Agency (IEA) anticipates that the demand for petrochemicals will continue to rise, particularly in Asia, during the next five years, further helping AI in the oil and gas market to grow. With substantial refineries tightly integrated with petrochemical production facilities, countries like China, India, Japan, and South Korea have some of the region's most active oil and downstream gas sectors, accounting for over 78% of the oil refining capacity in the region. Many companies are partnering with companies offering Ai solutions, such as Amazon, Microsoft, and others. For instance, in November 2021, Orica, a provider of commercial explosives and blasting systems for the oil and gas industry, partnered with Microsoft Azure to expand its digital capabilities by creating rich and AI-infused tools that enable step-change improvements in customers' productivity, safety, and sustainability. Furthermore, countries like Singapore are gaining over 10% refinery throughput in a year. This provides the scope for expansion in current refineries, and new possible projects are expected to drive the demand for AI deployment.
Europe is the third largest region. Europe is among the regions holding a significant global AI market share. The major driving factor in the region is the government's initiatives to boost the adoption of AI in the region. Considerable activity in the downstream oil and gas sector and high industrial activity in the region is one of the most prominent drivers for the AI market in the region. Also, as of November 2020, the region has 71 land oil rigs and 31 offshore oil rigs. Some of the critical oil-producing countries in the region include Russia and the United Kingdom. Amidst the growing need to cut operating costs, oil companies in the region seek help from AI to automate functions, predict equipment problems, and increase oil and gas output. For instance, in February 2021, Royal Dutch Shell (Shell) strategized to net zero emissions by 2050 by effectively and sustainably managing its existing business lines. This strategy includes collaborating with Microsoft to create a collaborative digital platform to track sustainability initiatives and gain insights into detailed business requirements.
|Market Size||USD in Billion By 2030|
|Forecast Units||Value (USD Million)|
|Report Coverage||Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends|
|Segments Covered||by Type (Hardware, Software), Function (Field Service, Material Movement), Application (Upstream)|
|Geographies Covered||North America, Europe, Asia-Pacific, LAME and Rest of the World|
|Key Companies Profiled/Vendors||IBM (U.S.), Intel Corporation (U.S.), Microsoft Corporation (U.S.), Accenture (Ireland), Google LLC (U.S.), Oracle (U.S.), Numenta (U.S.), Sentient Technologies (U.S.), Inbenta Technologies Inc(U.S.), General Vision (U.S.), Cisco (U.S.),|
|Key Market Opportunities||Rapid Growth In Technology Industry Enhances Artificial Intelligence In Oil And Gas Market|