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AI in Oil and Gas Market, Share & Trends Analysis by Application (Quality Control, Production Planning, Predictive Maintenance, Thermal Detection, Others), by Operation (Upstream, Midstream, Downstream), by Region, Competitive Strategies and Segment Forecasts, 2016-2026

  • ID: 5351560
  • Report
  • August 2019
  • Region: Global
  • 246 pages
  • Reports and Data
Increasing adoption rate of advanced and new technologies, high investments in AI implementation and presence of a large number of AI software and system suppliers, especially in developed regions are key factors driving market revenue growth.

Market Size - USD 2.28 Billion in 2020, Market Growth - CAGR of 12.4%, Market Trends - Rising demand for oil and gas from various sectors across the globe.

The global AI in oil and gas market size is expected to reach USD 5.74 Billion in 2028, and register a CAGR of 12.4% during the forecast period. Increasing investments for launching start-ups for implementation of AI (Artificial Intelligence), and increasing demand for oil and gas, coupled with need for AI for smooth functioning of the processes in the industry are major factors expected to drive growth of the global AI in oil and gas market.

However, demand for oil and gas has been decreasing since the pandemic due to standstill in the industrial sector. This is a major factor that could hamper growth of the global AI in oil and gas market. For instance, according to IEA (International Energy Agency), demand and adoption of oil has decreased by around 29 Million barrels a day in April 2020, and further decreased by nearly 23.1 Million barrels a day in second Quarter 2020.

Some Key Findings From the Report:
  • Among the application segments, the predictive maintenance segment accounted for the largest revenue share of 37.1% in 2020
  • The Asia Pacific market valued at USD 637.1 Million in 2020, and is expected to register a robust revenue growth rate during the forecast period.
  • North America market accounted for the largest revenue share in the global AI in oil and gas market in 2020, and is expected to continue with its dominance over the forecast period.
  • The Middle East and Africa market accounted for moderately high revenue share in 2020.
  • Key players profiled in the report include Google LLC, IBM Corp., FuGenX Technologies Pvt. Ltd., Hortonworks Inc., Microsoft Corp., Exxon Mobil, Numenta Inc., and Cisco Systems Inc. The market players have adopted various strategies including mergers, acquisitions, partnerships, and new product developments, among other strategies, to stay ahead of the competition and expand market footprint.
For the purpose of this report, the global AI in oil and gas market is segmented on the basis of operation, application, and region:

Operation Outlook
  • Upstream
  • Midstream
  • Downstream
Application Outlook
  • Quality Control
  • Production Planning
  • Predictive Maintenance
  • Thermal Detection
  • Others
Region Outlook
  • North America
  • US
  • Canada
  • Mexico
  • Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Benelux
  • Rest of Europe
  • Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • Rest of Asia Pacific
  • Latin America
  • Brazil
  • Rest of Latin America
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • South Africa
  • Rest of Middle East & Africa
Reasons to Buy the Report
  • A robust analysis and estimation of the AI in Oil and Gas Market with four levels of quality check - in-house database, expert interviews, governmental regulation, and a forecast specifically done through time series analysis
  • A holistic competitive landscape of the all the major players in the AI in Oil and Gas Market. The report covers their market shares, strategic initiatives, new product launches, R&D expenditure, M&As, Joint ventures, expansionary plans, product wise metric space analysis and key developments
  • Go-to-market strategies specifically formulated in line with location analysis which takes into the factors such as government regulations, supplier mapping, supply chain obstacles, and feedback from local vendors
  • Most deep dive segmental bifurcation available currently in the market. Our stellar methodology helps us understand the overall gamut of the supply chain and will help you explain the current market dynamics
  • Special focus given on vendor landscape, supplier portfolio, customer mapping, production capacity, and yearly capacity utilization
Note: Product cover images may vary from those shown
1 Industry Overview of AI in Oil and Gas
1.1AI in Oil and Gas Market Overview
1.1.1 AI in Oil and Gas Product Scope
1.1.2 Market Status and Outlook
1.2 Global AI in Oil and Gas Market Size and Analysis by Regions
1.2.1 United States
1.2.2 EU
1.2.3 Japan
1.2.4 China
1.2.5 India
1.2.6 Southeast Asia
1.3 AI in Oil and Gas Market by Type
1.3.1 Hardware
1.3.2 Software
1.3.3 Hybrid
1.4 AI in Oil and Gas Market by End Users/Application
1.4.1 Upstream
1.4.2 Downstream
1.4.3 Midstream

2 Global AI in Oil and Gas Competition Analysis by Players
2.1 AI in Oil and Gas Market Size (Value) by Players (2016 and 2017)
2.2 Competitive Status and Trend
2.2.1 Market Concentration Rate
2.2.2 Product/Service Differences
2.2.3 New Entrants
2.2.4 The Technology Trends in Future

3 Company (Top Players) Profiles
3.1 IBM (US)
3.1.1 Company Profile
3.1.2 Main Business/Business Overview
3.1.3 Products, Services and Solutions
3.1.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.1.5 Recent Developments
3.2 Intel (US)
3.2.1 Company Profile
3.2.2 Main Business/Business Overview
3.2.3 Products, Services and Solutions
3.2.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.2.5 Recent Developments
3.3 Accenture (Republic of Ireland)
3.3.1 Company Profile
3.3.2 Main Business/Business Overview
3.3.3 Products, Services and Solutions
3.3.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.3.5 Recent Developments
3.4 Google (US)
3.4.1 Company Profile
3.4.2 Main Business/Business Overview
3.4.3 Products, Services and Solutions
3.4.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.4.5 Recent Developments
3.5 Microsoft (US)
3.5.1 Company Profile
3.5.2 Main Business/Business Overview
3.5.3 Products, Services and Solutions
3.5.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.5.5 Recent Developments
3.6 Oracle (US)
3.6.1 Company Profile
3.6.2 Main Business/Business Overview
3.6.3 Products, Services and Solutions
3.6.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.6.5 Recent Developments
3.7 Numenta (US)
3.7.1 Company Profile
3.7.2 Main Business/Business Overview
3.7.3 Products, Services and Solutions
3.7.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.7.5 Recent Developments
3.8 Sentient technologies (US)
3.8.1 Company Profile
3.8.2 Main Business/Business Overview
3.8.3 Products, Services and Solutions
3.8.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.8.5 Recent Developments
3.9 Inbenta (US)
3.9.1 Company Profile
3.9.2 Main Business/Business Overview
3.9.3 Products, Services and Solutions
3.9.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.9.5 Recent Developments
3.10 General Vision (US)
3.10.1 Company Profile
3.10.2 Main Business/Business Overview
3.10.3 Products, Services and Solutions
3.10.4 AI in Oil and Gas Revenue (Value) (2012-2017)
3.10.5 Recent Developments
3.11 Cisco (US)
3.12 FuGenX Technologies (US)
3.13 Infosys (India)
3.14 Hortonworks (US)
3.15 Royal Dutch Shell (Netherlands)

4 Global AI in Oil and Gas Market Size by Type and Application (2012-2017)
4.1 Global AI in Oil and Gas Market Size by Type (2012-2017)
4.2 Global AI in Oil and Gas Market Size by Application (2012-2017)
4.3 Potential Application of AI in Oil and Gas in Future
4.4 Top Consumer/End Users of AI in Oil and Gas

5 United States AI in Oil and Gas Development Status and Outlook
5.1 United States AI in Oil and Gas Market Size (2012-2017)
5.2 United States AI in Oil and Gas Market Size and Market Share by Players (2016 and 2017)

6 EU AI in Oil and Gas Development Status and Outlook
6.1 EU AI in Oil and Gas Market Size (2012-2017)
6.2 EU AI in Oil and Gas Market Size and Market Share by Players (2016 and 2017)

7 Japan AI in Oil and Gas Development Status and Outlook
7.1 Japan AI in Oil and Gas Market Size (2012-2017)
7.2 Japan AI in Oil and Gas Market Size and Market Share by Players (2016 and 2017)

8 China AI in Oil and Gas Development Status and Outlook
8.1 China AI in Oil and Gas Market Size (2012-2017)
8.2 China AI in Oil and Gas Market Size and Market Share by Players (2016 and 2017)

9 India AI in Oil and Gas Development Status and Outlook
9.1 India AI in Oil and Gas Market Size (2012-2017)
9.2 India AI in Oil and Gas Market Size and Market Share by Players (2016 and 2017)

10 Southeast Asia AI in Oil and Gas Development Status and Outlook
10.1 Southeast Asia AI in Oil and Gas Market Size (2012-2017)
10.2 Southeast Asia AI in Oil and Gas Market Size and Market Share by Players (2016 and 2017)

11 Market Forecast by Regions, Type and Application (2017-2022)
11.1 Global AI in Oil and Gas Market Size (Value) by Regions (2017-2022)
11.1.1 United States AI in Oil and Gas Revenue and Growth Rate (2017-2022)
11.1.2 EU AI in Oil and Gas Revenue and Growth Rate (2017-2022)
11.1.3 Japan AI in Oil and Gas Revenue and Growth Rate (2017-2022)
11.1.4 China AI in Oil and Gas Revenue and Growth Rate (2017-2022)
11.1.5 India AI in Oil and Gas Revenue and Growth Rate (2017-2022)
11.1.6 Southeast Asia AI in Oil and Gas Revenue and Growth Rate (2017-2022)
11.2 Global AI in Oil and Gas Market Size (Value) by Type (2017-2022)
11.3 Global AI in Oil and Gas Market Size by Application (2017-2022)

12 AI in Oil and Gas Market Dynamics
12.1 AI in Oil and Gas Market Opportunities
12.2 AI in Oil and Gas Challenge and Risk
12.2.1 Competition from Opponents
12.2.2 Downside Risks of Economy
12.3 AI in Oil and Gas Market Constraints and Threat
12.3.1 Threat from Substitute
12.3.2 Government Policy
12.3.3 Technology Risks
12.4 AI in Oil and Gas Market Driving Force
12.4.1 Growing Demand from Emerging Markets
12.4.2 Potential Application

13 Market Effect Factors Analysis
13.1 Technology Progress/Risk
13.1.1 Substitutes
13.1.2 Technology Progress in Related Industry
13.2 Consumer Needs Trend/Customer Preference
13.3 External Environmental Change
13.3.1 Economic Fluctuations
13.3.2 Other Risk Factors

14 Research Finding/Conclusion

15 Appendix
  • Methodology
  • Analyst Introduction
  • Data Source
Note: Product cover images may vary from those shown
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