Market Research Report
AI in Oil & Gas Market Size - Growth, Trends, and Forecast (2020 - 2025)
|Published by||Mordor Intelligence LLP||Product code||871447|
|Published||Content info||120 Pages
Delivery time: 2-3 business days
|AI in Oil & Gas Market Size - Growth, Trends, and Forecast (2020 - 2025)|
|Published: January 1, 2020||Content info: 120 Pages||
The AI in Oil and Gas market was valued at USD 2 billion in 2019 and is expected to reach USD 3.98 million by 2025, at a CAGR of 12.14% over the forecast period 2020 - 2025. As the cost of IoT sensors declines, more major oil & gas organizations are bound to start integrating these sensors into their upstream, midstream, and downstream operations along with AI enabled predictive analytics.
The upstream sector of Oil and Gas industry includes searching for potential underground or underwater crude oil and natural gas fields, drilling exploratory wells, and subsequently drilling and operating the wells that recover and bring the crude oil or raw natural gas to the surface. The midstream sector involves transportation (by pipeline, rail, barge, oil tanker or truck), storage, and wholesale marketing of crude or refined petroleum products. Pipelines and other transport systems can be used to move crude oil from production sites to refineries and deliver the various refined products to downstream distributors. The downstream sector is the refining of petroleum crude oil and the processing and purifying of raw natural gas as well as the marketing and distribution of products derived from crude oil and natural gas.
Predictive Maintenance is Expected to Hold a Major Market Share in the Forecast Period
North America is Expected to Hold a Major Market Share in the Forecast Period
Owing to the increasing adoption of AI technologies across the oilfield operators and service providers and the robust presence of prominent AI software and system suppliers, especially in the United States and Canada, the North American segment is anticipated to account for the largest share of the AI in the oil & gas market, over the forecast period.
Owing to the increasing inflow of investments in startups for AI implementation, which would further augment the demand for AI in the near future, the region is poised to be the fastest-growing segment. Some of the prominent players of the North American region are - Google LLC, IBM Corp., FuGenX Technologies Pvt. Ltd, Hortonworks Inc., Microsoft Corporation, and Intel Corp., among others.
The largest oil and gas companies in the USA are poised to impact the market positively as they embrace the latest technologies and innovations. They launched an American energy renaissance, leading to new natural gas finds and expansion of oil production from reserves that were once deemed unavailable.
'The Environmental Partnership', is an industry-led initiative created to help the largest oil and gas companies in the USA to work together and continuously negate adverse environmental impacts. It's a landmark collaboration that's initially focused on further reducing emissions from oil and gas production in the USA. This shows the shift towards growing environmental concerns. Artificial Intelligence can facilitate the control of carbon emissions by streamlining the predictive maintenance techniques.
The AI in the Oil and Gas market is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. The companies are continuously capitalizing on acquisitions, in order to broaden, complement, and enhance its product and service offerings, to add new customers and certified personnel, and to help expand sales channels.
October 2018 - IBM recently acquired Red Hat to position itself as a cloud power. With the deal, IBM carves out a place for itself that's separate from the top cloud providers. Whereas Amazon, Microsoft, and Google are primarily public cloud and software providers, IBM specializes in hybrid cloud, offering a deep hardware and software stack stretching back through literally 60 years of enterprise legacy, and looking ahead to the containerized and AI-enabled future.