Artificial
Intelligence is an advanced technology which supports to achieving improved
production and business efficiencies in the oil and gas industry. The inclusion
of artificial intelligence technology provides new ways and approaches in
exploration, development, refining, production, sales and transformation
systems. Oil and gas companies are highly investing in AI technology services
and solutions to minimize human errors in the process and to prevent critical
business process challenges with the support of advanced technology in
automation. The major driving factors causing an increase in the demand for
artificial intelligence in the oil and gas industry has been the worldwide decrease
in oil prices. This has in turn tightened margins and pushed the oil and gas
operators to change their emphasis away from raising their overall production
to effectively optimizing it. Prevention of expensive risk of drilling,
leveraging big data to enhance operational performance and transformation of conventional
production system into new predictive technologies are the factors propelling
the growth of artificial intelligence in oil and gas market. Furthermore, the substantial
increase in health and safety concerns of the personnel on production sites is
also boosting the growth of the global artificial intelligence market in oil
and gas. Artificial intelligence can avoid the health and safety issues by supporting
the operators to regulate critical tasks through automated systems without the requirement
for human presence. Hence, the artificial intelligence systems can automate and
optimize data rich processes, they help in reducing or avoiding duplication of
efforts and further in reducing business risk. This improves the productivity
and reduces the overall operational cost. Across the world, the oil and gas companies
have reengineered their production strategies and operational models to involve
artificial intelligence as a prominent element in business transformation. Thus,
the artificial intelligence market in oil and gas has an enormous scope for
rapid growth. However, the heavy coat of installation is likely to limit the
market growth.
With the advancement
in computer hardware and software in the past few years, and rise in the number
of providers providing data-driven solutions, the artificial intelligence-enabled
technology has relatively succeeded in domains such as healthcare, finance and
manufacturing, and has also grasped the attention of the oil and gas industry.
The
global Artificial Intelligence (AI) in Oil & Gas Market is segregated on
the basis of Type as Hardware, Software and Hybrid. Based on Function the
global Artificial Intelligence (AI) in Oil & Gas Market is segmented in Predictive
maintenance and machinery inspection, Material movement, Production planning,
Field services, Quality control and Reclamation. Based on Application the
global Artificial Intelligence (AI) in Oil & Gas Market is segmented in Upstream,
Downstream and Midstream.
The
global Artificial Intelligence (AI) in Oil & Gas Market report provides
geographic analysis covering regions, such as Europe, North America, Asia
Pacific, and Rest of The World. The Artificial Intelligence (AI) in Oil &
Gas Market for each region is further segmented for major countries including
the U.S., Canada, Germany, the U.K., France, Italy, China, India, Japan,
Brazil, South Africa, and others.
Competitive Analysis
IBM, ExxonMobil,
Royal Dutch Shell, China Petroleum and Chemical Corp, Total S.A., Gazprom and
others are among the major players in the global Artificial Intelligence (AI)
in Oil & Gas Market. The companies studied in terms of product strategy and
various n several growth and expansion strategies to gain a competitive edge in
the market. The major players not only follow value chain integration with
business operations in multiple stages of the value chain.
- In
October 2019, Microsoft declared the collaboration with Baker Hughes an energy
industry tech company and AI developer C3.ai to bring enterprise AI technology
to the energy industry through its Azure cloud computing platform. It would enable
customers to streamline the adoption of AI designed to address problems such as
energy management, inventory, predictive maintenance and equipment reliability.
- In
September 2020, Intel and Oracle adopted the next generation of cloud-based,
high-performance computing (HPC) instances within Oracle Cloud Infrastructure, influencing
the computing performance of 10nm Intel Xeon Scalable processors. Leveraging
3rd Gen Intel Xeon Scalable processors and other enhancements in Oracle’s new
X9 Generation instance, performance gains may be up to 30% higher on few
workloads over older versions. Oracle’s X9 Generation cloud instance is
targeted at computationally intensive workloads, including crash simulations,
seismic analysis for oil and gas exploration and electronic design automation.
The global Artificial Intelligence (AI) in Oil
& Gas Market has been segmented as below:
Artificial
Intelligence (AI) in Oil & Gas Market, By Type
Artificial
Intelligence (AI) in Oil & Gas Market, By Function
- Predictive maintenance and
machinery inspection
- Material movement
- Production planning
- Field services
- Quality control
- Reclamation
Artificial
Intelligence (AI) in Oil & Gas Market, By Application
- Upstream
- Downstream
- Midstream
Artificial
Intelligence (AI) in Oil & Gas Market, By Region
- Europe
- North America
- Asia Pacific
- Rest of The World
Artificial
Intelligence (AI) in Oil & Gas Market, By Company
- IBM
- ExxonMobil
- Royal Dutch Shell
- China Petroleum and Chemical Corp
- Total S.A.
- Gazprom
- Accenture
- Google
- Microsoft
- Oracle
- Intel
- Numenta
- Sentient Technologies
- Inbenta
- General Vision
- Cisco
- Fugenx Technologies
- Infosys
The
report covers the below scope:
- Global Artificial Intelligence (AI)
in Oil & Gas Market sizes from 2020 to 2026, along with CAGR for 2020-2026
- Market size comparison for 2019 vs
2026, with actual data for 2019, estimates for 2019 and forecast from 2020 to
2026
- Global Artificial Intelligence (AI)
in Oil & Gas Market trends, covering comprehensive range of consumer trends
& manufacturer trends
- Value chain analysis covering
participants from raw material suppliers to the downstream buyer in the global Artificial
Intelligence (AI) in Oil & Gas Market
- Major market opportunities and
challenges in forecast timeframe to be focused
- Competitive landscape with analysis
on competition pattern, portfolio comparisons, development trends and strategic
management
- Comprehensive company profiles of
the key industry players
The
years considered for the study are as follows:
- Base year - 2019
- Estimated year - 2019
- Projected year - 2020
- Forecast period - 2021 to 2026
Report
Scope:
The global Artificial Intelligence (AI) in Oil
& Gas Market report scope includes detailed study covering underlying
factors influencing the industry trends. The report covers analysis on regional
and country level market dynamics. The scope also covers competitive overview
providing company market shares along with company profiles for major revenue
contributing companies. The report scope includes detailed competitive outlook
covering market shares and profiles key participants in the global Artificial
Intelligence (AI) in Oil & Gas Market share. Major industry players with
significant revenue share include IBM, ExxonMobil, Royal
Dutch Shell, China Petroleum and Chemical Corp, Total S.A., Gazprom and others.
Why to
Buy this Report:
- Gain detailed insights on the Artificial Intelligence (AI) in Oil & Gas industry trends
- Find complete analysis on the
market status
- Identify the Artificial
Intelligence (AI) in Oil & Gas Market opportunities and growth segments
- Analyse competitive dynamics by
evaluating business segments & product portfolios
- Facilitate strategy planning and
industry dynamics to enhance decision making
Target
Audience:
- The report targeted towards the existing players in
the industry is as follows:
- Market Manufacturers/Service
Providers
- Market Wholesale/Traders
- Investment and Financial Institutions
Free
and Paid Customization based on the requirement