AI in Oil and Gas Market Size to Reach USD 18.94 Billion by 2032

The artificial intelligence (AI) in oil and gas market size was valued at USD 5.13 billion in 2022 and it is estimated to reach USD 18.94 billion by 2032, growing at a CAGR of 13.96% between 2023 and 2032.


Ottawa, Sept. 14, 2023 (GLOBE NEWSWIRE) -- According to Precedence Research, the global AI in oil and gas market size will rise at USD 14.59 billion in 2030. Artificial Intelligence (AI) in the oil and gas market refers to the application of advanced computer algorithms to optimize various aspects of the oil and gas industry. AI technologies are employed to analyze and interpret the vast amount of data generated during exploration, drilling, production, distribution, and management of oil and natural gas resources. The primary objective of AI in this sector is to improve operational efficiency, reduce costs, enhance safety, and mitigate environmental risks.

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Regional Insights

North America is expected to hold the largest market share over the forecast period. The growth in the region is attributed to the growing oil & gas production. For instance, according to the US Energy Information Administration (EIA), in 2022, the US produced over 28.5 trillion cubic feet (Tcf) of dry natural gas from shale deposits. North American oil and gas companies use AI to analyze seismic data, well data, and geological information to optimize exploration and reservoir management. Advanced AI algorithms help in predicting hydrocarbon reserves more accurately. Moreover, AI is employed to optimize production processes in North American oilfields. Real-time monitoring and predictive analytics are used to maximize production efficiency while minimizing operational costs.

Asia Pacific is expected to grow at the highest CAGR during the forecast period. Drilling, production, and exploration activities are being transformed due in large part to AI. These activities occur in remote areas where it is necessary to track and optimize a variety of assets. With the help of the Internet of Things, field workers may use tools for proactive maintenance, real-time data analytics, environmental monitoring, health and safety, asset management, and better working conditions.

According to estimates, Asia consumes the resource at a rate of 47%, followed by the rest of the globe (24%). They are one of the key markets for IoT and AI adoption in the upcoming years due to their expanding production and consumption. IBEF identifies the oil and gas industry as one of India's eight essential sectors as it has significant impact on how the other important economic parts make decisions. India's economic growth is strongly depends on its energy needs, more oil and gas are expected to be needed in the future, which makes the nation ideal for investment. Thus, this is expected to propel the market growth in the region.

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Scope of this report

Report CoverageDetails
Market Size in 2030USD 14.59 Billion in 2030
North America Revenue Share39% in 2022
Predictive Maintenance Segment Share31% in 2022
Upstream Application Segment Share52.3% in 2022
Key PlayersMicrosoft Corporation, IBM Corporation, C3.AI, Google LLC, NVIDIA Corp., Royal Dutch Shell PLC, FuGenX Technologies Pvt. Ltd, PJSC Gazprom Neft, Huawei Technologies Co. Ltd, Intel Corporation, Neudax, Infosys Limited, and Others

Report Highlights

  • By component, the hardware segment is expected to hold the largest market share over the forecast period. Artificial Intelligence (AI) in the oil and gas market relies not only on software and algorithms but also on specialized hardware solutions designed to support the unique computational demands of AI applications in the industry. These hardware components are essential for processing and analysing vast amounts of data and running complex machine learning and deep learning models efficiently. Some of the key hardware used in AI applications in the oil & gas industry are GPUs, CPUs, FPGAs, ASICs and Others.

For instance, GPUs are widely used for accelerating AI workloads, including deep learning. They excel at parallel processing and are crucial for training complex neural networks used in predictive modeling, image analysis, and natural language processing. Whereas, CPUs play a significant role in AI applications for data preprocessing, handling certain AI workloads, and managing overall system tasks. Modern CPUs with multiple cores and high clock speeds are essential for AI computations. Thus, these applications are expected to drive the segment growth over the forecast period.

  • By function, the production planning segment is expected to grow at the highest CAGR during the forecast period. Artificial Intelligence (AI) is playing a significant role in improving production planning in the oil and gas industry. Production planning involves optimizing the allocation of resources, scheduling operations, and managing production processes to ensure efficient and cost-effective hydrocarbon extraction and processing. AI technologies are used to enhance decision-making in this critical area.
  • AI-driven reservoir simulation tools create detailed models of subsurface reservoirs. These models consider geological data, well data, and historical production information. AI helps in optimizing reservoir development strategies and production planning. Moreover, AI models analyze historical production data and combine it with real-time information to predict future production rates accurately. This aids in resource planning and optimizing production schedules. Furthermore, AI systems continuously monitor well and facility performance data, adjusting operating parameters in real time to optimize production. This includes controlling artificial lift systems, adjusting valve settings, and managing flow rates for maximum efficiency. Therefore, driving the market growth over the forecast period.
  • By application, the downstream segment is expected to grow significantly during the forecast period. In the downstream sector of the oil and gas business, which includes refining, distribution, and marketing, artificial intelligence (AI) is rapidly gaining ground. AI is applied in the downstream industry to streamline operations, raise safety standards, reduce negative effects on the environment, and boost profitability. AI-powered systems optimize refinery processes, such as distillation, cracking, and blending, to improve yield, product quality, and energy efficiency. These systems help refineries operate more cost-effectively and produce higher-quality products.

Moreover, AI systems analyze energy consumption patterns within refineries and petrochemical plants, optimizing the use of energy-intensive equipment like pumps, compressors, and heat exchangers. This leads to energy cost savings and reduced environmental impact. Furthermore, AI is employed to monitor safety protocols and compliance with industry regulations. Real-time monitoring helps identify potential safety hazards and ensures that safety procedures are followed. Thus, this is expected to drive the segment growth.

Market Dynamics

Driver

Reduction in the oil prices

The most surprising factor boosting demand for artificial intelligence in the oil and gas business has been the steep drop in global oil prices. Due to margin restrictions, oil and gas producers were compelled to switch their focus from increasing total output to effectively optimizing it. Eliminating the expensive risk of drilling, using big data to enhance operational efficiency, and modernizing the conventional production system are some of the drivers boosting the growth of the worldwide artificial intelligence market in the oil and gas sector.

Restraint

Data quality and data privacy

Oil and gas operations generate vast amounts of data, but ensuring data quality, consistency, and availability can be difficult. Incomplete or inaccurate data can lead to unreliable AI predictions and decisions. In addition, the industry handles sensitive and confidential data, raising concerns about data privacy and security. Compliance with data protection regulations is essential but challenging.

Opportunity

Quality assurance        

In the oil and gas sector, artificial intelligence is excellent for quality control. The risk variables are significant and the sector is quite dynamic. Artificial intelligence-based solutions are built for countless applications. This improves the overall process quality from the beginning of exploration to the finish of processing and purifying crude oil and natural gas. This is achieved by promptly correcting any risks that are discovered early on, whether they are real or hypothetical. Thus, this is expected to offer a lucrative opportunity for the market growth.

Challenge

Environmental and safety enhancement        

AI can assist in monitoring and reducing emissions, managing environmental risks, and ensuring compliance with strict environmental regulations. This enables companies to operate more sustainably and avoid penalties. In addition, AI-powered surveillance and monitoring systems improve safety by detecting safety breaches, equipment malfunctions, and potential hazards in real time, reducing workplace accidents. Thus, this is expected to provide an attractive opportunity for the market growth.

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Recent Development

  • In August 2023, Wintershall Dea, one of Europe's top independent natural gas and oil producers that is currently transforming into a top gas and carbon management firm, is collaborating with IBM Consulting to establish an AI Center of Competence (CoC) and advance several AI use cases that add value and support effective energy production. Together, the two businesses sustain fruitful partnerships with Microsoft as a technology partner.
  • On the one hand, IBM Consulting and Microsoft continue to work together to provide data and AI projects based on Azure, while Wintershall Dea was already utilizing Azure as its data platform. To optimize processes and production throughout the organization and better capitalize on data, Wintershall Dea has started a comprehensive program for expanding AI.
  • In May 2023, ADNOC, the largest oil firm in the UAE, and UNIST, a national university of South Korea, established a strategic alliance to dominate the worldwide digital carbon-neutral market. By leveraging artificial intelligence, this cooperation aims to pioneer the creation of a decarbonization optimization system for massive petrochemical and oil refining operations.

Market Segmentation

By Component

  • Software
  • Hardware
  • Services

By Function

  • Predictive Maintenance
  • Machinery Inspection
  • Material Movement
  • Production Planning
  • Field Services
  • Quality Control
  • Reclamation

By Application

  • Upstream
  • Midstream
  • Downstream

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

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