AI in Oil & Gas market is projected to grow at a CAGR of 12.66% from 2017 to 2022

LONDON, Dec. 19, 2017 /PRNewswire/ -- Download the full report: https://www.reportbuyer.com/product/5248739

AI in Oil & Gas market is projected to reach USD 2.85 billion by 2022, growing at a CAGR of 12.66%, from 2017 to 2022. The growth of AI in Oil & Gas market can be attributed to the big data technology in the Oil & Gas industry to augment E&P capabilities, a significant increase in venture capital investments, growing need for automation in the Oil & Gas industry, and tremendous pressure to reduce production costs. Concerns regarding data security and cybersecurity are the major challenges faced by the players in this market.

The midstream segment is expected to grow at the highest CAGR from 2017 to 2022.
The midstream segment is expected to grow at the highest CAGR in the global AI in Oil & 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 provide the same to the human-machine interface in order to control the process. In the Oil & 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.

North America: The largest market for artificial intelligence in oil & gas and Middle East & Africa growing at the highest rate
North America is currently the largest market for AI in Oil & Gas, followed by the markets in Europe and Asia Pacific. Rising investments in the Oil & Gas infrastructure and increased focus toward automation and digitalization are expected to drive AI in the Oil & Gas market during the forecast period.

The Middle East and Africa is the fastest market for AI in Oil & Gas due to the recent discovery of offshore reserves in the Red Sea region. The increase in E&P activities is likely to boost the demand for AI solutions during the forecast period. The increasing investments in start-ups for AI implementation would further raise the demand for AI in the Oil & Gas market in the near future.

Breakdown of Primaries:
In-depth interviews have been conducted with various key industry participants, subject-matter experts, C-level executives of key market players, and industry consultants, among other experts, to obtain and verify critical qualitative and quantitative information, as well as assess future market prospects. The distribution of primary interviews is as follows: By Company Type: Tier 1- 55%, Tier 2- 25%, Tier 3- 20% By Designation: C-Level- 35%, Manager Level- 30%, Others- 35% By Region: Europe- 20%, North America- 15%, Asia Pacific- 25%, South America- 10%, and Middle East & Africa- 25% Note: The tier of the companies has been defined on the basis of their total revenue; as of 2016: Tier 1 = >USD 1 billion, Tier 2 = From USD 100 million to USD 500 million, and Tier 3 = The key players in AI in Oil & Gas market include IBM (US), Google (US), Microsoft (US), and Intel (US).

Research Coverage:
The report provides a picture of AI in Oil & Gas market and its segments across industries and regions. It aims at estimating the market size and future market growth potential across different segments, by type, function, application, and region. Furthermore, the report includes an in-depth competitive analysis of the key players in the market along with their company profiles, recent developments, and key market strategies.

Why buy this report?

1. The report identifies and addresses the key markets for AI in Oil & Gas, which would help OEMs review the growth in demand for the product.
2. The report helps solution providers understand the pulse of the market and provides insight into drivers, restraints, and challenges.
3. The report will help key players understand the strategies of their competitors better and will help in making strategic decisions.

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