The integration of AI in oil and gas ecosystem sector has reshaped all operations in the industry by creating ‘digital oilfields’ of the future. Investment expectations for AI in oil and gas ecosystem has been increasing from the past few years and it is expected to be twice by 2022. The AI in oil and gas industry will bring in radical changes in oilfield working force, machines, and the operating system. The oil industry must ensure that there is timely and adequate investment so as not to lead to a supply shortage in the future. To meet the demand for crude oil worldwide, the industry is required to invest $11 trillion in the coming 20 years. The rise of the machines, analytics, and the digital oilfield has created new processes for exploration and production. AI helps in automated decision-making and real time reactions to improve operational efficiencies and connect infrastructure platforms together. It makes the interaction between machines and humans better, which in turn, is changing the expectation for the industry.

AI in oil and gas ecosystem has made the decision-making process faster by detecting patterns that human eyes cannot see and thus, take advantage of the insights quicker. AI assistants in the oil industry are helping in providing customer support assistance, identifying key details, providing actionable summaries, and in removing the need for multitasking during important tasks. With help of an AI assistant, oil and gas companies can minimize or eliminate the duplication of efforts and reduce risks. AI assistants make decisions in real time and handle the growing complexity of engineering systems. According to our estimates, the AI in Oil and Gas Ecosystem is expected to witness growth at ~16.2% CAGR from 2019 to 2020.

Figure 1: Ecosystem Snapshot: AI in Oil and Gas Ecosystem

Today, companies are investing more in AI software and technology. Ambyint Infinity operates AWS Lamda and EMR to scale automatically and securely compute resources and for data storage. AWS prefers Ambyint’s software for real-time visualization, which it is offering to the oil and gas industry. Rosneft has already set drilling data monitoring stations with artificial intelligence elements at heavy drilling rigs. Shell is planning to implement Smart Fields to increase the total amount of oil recovered from a field by 10% and enhance the rate of production. The AI technology is allowing sensors with fiber optic cables to transmit digital information about temperature, pressure, and other field conditions to control centers where engineers constantly monitor production and make swift decisions on the best manner/process for extracting oil and gas. AI technologies are helping in activating underground valves electronically for better management of the oil flow. BP North America Petroleum, Inc. has installed sensors and fiber optic networks across its North Sea, Gulf of Mexico, and other assets to collect and interpret huge amounts of data. North America has 60% of oil below the earth’s surface due to natural seeps. Robots powered by AI will navigate these oceanic regions and detect oil seeps, and thereby contribute to protecting the ecosystem and serve as indicators for robust energy resources.

Figure 2: AI in Oil and Gas Ecosystem: Segmentation

Global AI in Oil and Gas Ecosystem

The AI in Oil and Gas Ecosystem size was valued at $413 Million in 2018. Energy projects in the Middle East and North Africa (MENA) region are expected to bring in about $1 trillion investments over the next five years. The GCC region is also looking to adopt new technologies in its petroleum industry to increase efficiency, reduce costs, and make processes more competent. Accenture and Microsoft are helping these regions in better decision-making. The Middle East is witnessing significant traction in the field of AI, and local entrepreneurs are working on developing region-specific AI tools for oil extraction. AI robots are helping in reducing the risk of exposure to dangerous working conditions for many employees. The U.S. has already experienced a decreasing trend of labor injuries or fatalities in the field in recent years. AI in oil and gas industry is an effort to improve employee working conditions and this is a smart investment for the oil and gas industry.

Figure 3 – AI in Oil and Gas Ecosystem Market Statistics Glimpse

There are many trends that are having an impact on the market forecast. These, when evaluated from a company’s perspective, can drive growth. Our numerous consulting projects have generated sizeable synergies across all regions and all sizes of companies.

The major players operating in the Global AI in Oil and Gas Ecosystem are as follows:

Company Ecosystem Positioning Total Revenue (US$) Industry Region Weatherford Solution and service US$5.7 Billion Oilfield services & equipment Global National Oilwell Varco Solution and service US$7.3 Billion Oilfield services & equipment Global Halliburton Solution and service ‎US$ 1.656 billion Oilfield services & equipment Global Kuwait Oil Company Solution and service US$10.9 Billion Oilfield services & equipment Global Sinopec Solution and service US$61.6 Billion Oilfield services & equipment Global

Very few markets have the interconnectivity with other markets like AI. Our Interconnectivity module focuses on the key nodes of heterogenous markets in detail. Hardware Solutions Reservoir, Optimization, Onshore, IoT, Software & Service Solutions, Drilling Optimization, Offshore, Robotics

Figure 4 – AI in Oil and Gas Ecosystem Major Interconnectivities

Glance on AI in Oil and Gas Ecosystem Trends:

Trends Process Application Solution Technology Impact Autonomous robots in the oil & gas industry are used for applications such as welding, drilling, pipeline inspection, etc. Autonomous robots help in performing difficult and dangerous tasks. Production Optimization RPA 050% AI helps enhance data management in the oil & gas industry, which in turn, helps in reducing the overall cost. Others ML 0.32% A lot of data gets generated in the oil & gas industry every day. Cloud computing has significant demand in the oil & gas industry, especially in Dubai. Others Cloud Computing 0.21% Trend 4 XX xx xx Trend 5 XX xx

Figure 5: AI in Oil and Gas Ecosystem Standard Research methodology