MarketsandMarkets projects that the AI in the oil and gas market was worth $1.42 billion in 2016 and is expected to grow at a CAGR of 12.66 percent from 2017 to 2022 to reach a market size of $2.85 billion by 2022.
Improving operational efficiency in the oil and gas industry and predictive maintenance to avoid costly downtime will drive the artificial intelligence in oil and gas in the coming future.
The growth of the artificial intelligence in the oil and gas market can be attributed to the increasing big data technology in the oil and gas industry to augment E&P capabilities, significant increases in venture capital investments, the growing need for automation driving the oil and gas industry, and tremendous pressure to reduce production costs.
In the coming years, the market is expected to witness the highest growth rate in the North American region. This growth is due to increasing adoption of AI technologies by oilfield operators and service providers and the strong presence of prominent AI software and system suppliers, especially in the US and Canada. The Middle East and Africa are the fastest growing markets due to increasing investments in start-ups for AI implementation, which would further raise the demand for AI in the near future.
The research study of AI in oil and gas, further segmented into Type, Function and Application Type is classified into hardware, software, and services. The software segment led AI in the oil and gas market in 2016. Software in AI in the oil and gas market are applicable in upstream oil and gas exploration and production activities. The hardware segment in AI in the oil and gas market is expected to grow swiftly during the forecasted period (2017 to 2022), mainly due to the increasing requirement for sophisticated hardware system configurations and components capable of handling massive data, including, but not limited to Tensor Processor Unit (TPU), Graphic Processing Unit (GPU), Resistive Processing Unit (RPU), Field Programmable Gate Array (FPGA), and Visual Processing Unit (VPU) to install software-based AI capabilities.
Function is classified into predictive maintenance and machinery inspection, material movement, production planning, field services, quality control, and reclamation. Preventive maintenance is the largest and one of the fastest growing segment in AI in the oil and gas market. Predictive maintenance aids in addressing costly downturn by predicting maintenance schedules for equipment to prevent the possibility of equipment failures and, thus, save millions of dollars.
Application is classified into upstream, midstream, and downstream. The midstream segment is expected to grow at the highest CAGR in the global AI in oil and gas market during the forecast period. The growth in the shale oil and gas production in the US is creating the need for an expanded midstream network of pipelines, rail, tankers, and terminals. AI is widely used in the midstream sector to gather data during the transportation process through pipelines and provides the same to the human-machine interface to control the process. In the oil and gas industry these tools have been used to solve problems such as pressure transient analysis, well log interpretation, reservoir characterization, and well selection for stimulation, among others.
IBM (US), Accenture (Republic of Ireland), Google (US), Microsoft Corporation (US), and Oracle (US).
Oil and gas companies are regularly faced with many industry-specific issues to overcome. Such issues, including exploration and drilling, are often complex and intricate processes with many unique challenges to overcome. Data analytics can play a massive part in streamlining some of the most fundamental operations that are involved in the oil and gas industry.