AI in the oil and gas industry increases profit while improving oil and gas output through predictive maintenance and machinery inspection, quality control, dwelling, exploration, tank and reservoir monitoring, and other methods. Machine learning, artificial neutral networks, fuzzy logic, and expert systems are a few examples of artificial intelligence techniques that help turn data into useful knowledge that can then be used at various stages of the exploration and production phases of the lifecycle.
Global Artificial Intelligence (AI) in Oil and Gas Market Driving Factors and Challenges
The primary factor driving greater demand for artificial intelligence in the oil and gas business has been the steep drop in global oil prices. Margin restrictions pushed oil and gas companies to shift their focus from increasing overall output to successfully optimizing it. Eliminating the costly risk of drilling, exploiting big data to improve operational efficiency, and changing the existing production system into new predictive technologies are the drivers driving the growth of the worldwide artificial intelligence market in the oil and gas industry.
One of the factors hindering the expansion of Artificial Intelligence (AI) in the Oil and Gas business is the unpredictability of raw material prices. The introduction of artificial intelligence (AI) into the oil and gas industry faces various challenges. To begin, the industry is dealing with massive amounts of data, and efficiently handling and evaluating this data remains a significant difficulty. It is critical for AI systems to ensure the precision, perfection, and dependability of data in order to provide reliable forecasts and choices.
Furthermore, AI algorithms necessitate a large amount of processing capability, and many oil and gas facilities, particularly those in distant offshore areas, may lack the necessary infrastructure to support advanced AI applications. Integrating AI into current systems can also be complicated and costly.
Impact of COVID-19 on Global Artificial Intelligence (AI) in Oil and Gas Market
Due to the COVID-19 pandemic, worldwide crude oil demand increased due to pent-up consumer demand. However, macroeconomic concerns such as rising global interest rates and geopolitical tensions, particularly the Ukraine crisis, put pressure on crude oil prices again.
Artificial Intelligence (AI) in Oil and Gas Market Key Players:
The market study provides market data by competitive landscape, revenue analysis, market segments and detailed analysis of key market players such as; C3 AI, IBM, Flowserve Corporation, Google LLC, Microsoft Corporation, Oracle, FuGenX Technologies Pvt Ltd Inc, Cloudera Inc, Cisco Systems Inc, NVIDIA Corporation, Intel Corporation.
Global Artificial Intelligence (AI) in Oil and Gas Market Segmentation:
By Component: Based on the Component, Global Artificial Intelligence (AI) in Oil and Gas Market is segmented as; Solution, Services.
By Operation: Based on the Operation, Global Artificial Intelligence (AI) in Oil and Gas Market is segmented as; Upstream, Midstream, Downstream.
By Region: This report also provides the data for key regional segments of North America, Asia-Pacific, Latin America, Middle East & Africa and Europe.
This study also encompasses various drivers and restraining factors of this market for the forecast period. Various growth opportunities are also discussed in the report.