AI in Oil and Gas Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028
Description
AI in Oil and Gas Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028
The global AI in oil and gas market size reached US$ 2.4 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 4.5 Billion by 2028, exhibiting a growth rate (CAGR) of 9.76% during 2023-2028.
Artificial Intelligence (AI) refers to an advanced technology that assists in optimizing midstream, upstream, and downstream operations and productivity in the oil and gas industry. It is commonly used for analyzing exploration and reservoir data, enhancing back-office and invoicing and billing processes, maximizing labor productivity, improving reliability, automating financial controls, and managing and optimizing supply chains. Apart from this, AI in oil and gas assists in detecting problems earlier and faster, thus reducing costs, enhancing operational efficiency, scheduling maintenance, pre-planning safety measures, assuring quality, reducing downtime and increasing production. Consequently, it is also used for enhancing quality control, material movement, production planning and machinery inspection applications.
AI in Oil and Gas Market Trends:
The significant growth in the oil and gas industry across the globe is creating a positive outlook for the market. The AI tools aid in automating the analysis of gathered geological data, digitizing records and identifying issues, such as increased equipment usage and pipeline corrosion. In line with this, the widespread product adoption to monitor toxicity levels and leaks and automatically adjust cooling and heating systems is favoring the market growth. Apart from this, various advancements, such as the integration of machine learning (ML) with AI in the oil and gas industry to solve complex problems efficiently and quickly, are providing a considerable boost to the market growth. Additionally, the increasing demand for advanced solutions in drilling, boiler diagnostics, quality control, planning and predictive maintenance in various operations is positively impacting the market growth. Other factors, including the increasing product demand among oilfield operators, the implementation of various government initiatives to reduce the environmental impact of energy production, and extensive research and development (R&D) activities, are anticipated to drive the market further.
Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each sub-segment of the global AI in oil and gas market report, along with forecasts at the global, regional and country level from 2023-2028. Our report has categorized the market based on type, function and application.
Breakup by Type:
Hardware
Software
Services
Breakup by Function:
Predictive Maintenance and Machinery Inspection
Material Movement
Production Planning
Field Services
Quality Control
Reclamation
Breakup by Application:
Upstream
Downstream
Midstream
Breakup by Region:
North America
United States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa
Competitive Landscape:
The competitive landscape of the industry has also been examined along with the profiles of the key players being Accenture plc, C3.AI Inc., Cisco Systems Inc., Cloudera Inc., Fugenx Technologies, Huawei Technologies Co. Ltd, Infosys Limited, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, Neudax, Nvidia Corporation, Oracle Corporation and Shell plc.
Key Questions Answered in This Report:
How has the global AI in oil and gas market performed so far and how will it perform in the coming years?
What has been the impact of COVID-19 on the global AI in oil and gas market?
What are the key regional markets?
What is the breakup of the market based on the type?
What is the breakup of the market based on the function?
What is the breakup of the market based on the application?
What are the various stages in the value chain of the industry?
What are the key driving factors and challenges in the industry?
What is the structure of the global AI in oil and gas market and who are the key players?
What is the degree of competition in the industry?
The global AI in oil and gas market size reached US$ 2.4 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 4.5 Billion by 2028, exhibiting a growth rate (CAGR) of 9.76% during 2023-2028.
Artificial Intelligence (AI) refers to an advanced technology that assists in optimizing midstream, upstream, and downstream operations and productivity in the oil and gas industry. It is commonly used for analyzing exploration and reservoir data, enhancing back-office and invoicing and billing processes, maximizing labor productivity, improving reliability, automating financial controls, and managing and optimizing supply chains. Apart from this, AI in oil and gas assists in detecting problems earlier and faster, thus reducing costs, enhancing operational efficiency, scheduling maintenance, pre-planning safety measures, assuring quality, reducing downtime and increasing production. Consequently, it is also used for enhancing quality control, material movement, production planning and machinery inspection applications.
AI in Oil and Gas Market Trends:
The significant growth in the oil and gas industry across the globe is creating a positive outlook for the market. The AI tools aid in automating the analysis of gathered geological data, digitizing records and identifying issues, such as increased equipment usage and pipeline corrosion. In line with this, the widespread product adoption to monitor toxicity levels and leaks and automatically adjust cooling and heating systems is favoring the market growth. Apart from this, various advancements, such as the integration of machine learning (ML) with AI in the oil and gas industry to solve complex problems efficiently and quickly, are providing a considerable boost to the market growth. Additionally, the increasing demand for advanced solutions in drilling, boiler diagnostics, quality control, planning and predictive maintenance in various operations is positively impacting the market growth. Other factors, including the increasing product demand among oilfield operators, the implementation of various government initiatives to reduce the environmental impact of energy production, and extensive research and development (R&D) activities, are anticipated to drive the market further.
Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each sub-segment of the global AI in oil and gas market report, along with forecasts at the global, regional and country level from 2023-2028. Our report has categorized the market based on type, function and application.
Breakup by Type:
Hardware
Software
Services
Breakup by Function:
Predictive Maintenance and Machinery Inspection
Material Movement
Production Planning
Field Services
Quality Control
Reclamation
Breakup by Application:
Upstream
Downstream
Midstream
Breakup by Region:
North America
United States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa
Competitive Landscape:
The competitive landscape of the industry has also been examined along with the profiles of the key players being Accenture plc, C3.AI Inc., Cisco Systems Inc., Cloudera Inc., Fugenx Technologies, Huawei Technologies Co. Ltd, Infosys Limited, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, Neudax, Nvidia Corporation, Oracle Corporation and Shell plc.
Key Questions Answered in This Report:
How has the global AI in oil and gas market performed so far and how will it perform in the coming years?
What has been the impact of COVID-19 on the global AI in oil and gas market?
What are the key regional markets?
What is the breakup of the market based on the type?
What is the breakup of the market based on the function?
What is the breakup of the market based on the application?
What are the various stages in the value chain of the industry?
What are the key driving factors and challenges in the industry?
What is the structure of the global AI in oil and gas market and who are the key players?
What is the degree of competition in the industry?
Table of Contents
143 Pages
- 1 Preface
- 2 Scope and Methodology
- 2.1 Objectives of the Study
- 2.2 Stakeholders
- 2.3 Data Sources
- 2.3.1 Primary Sources
- 2.3.2 Secondary Sources
- 2.4 Market Estimation
- 2.4.1 Bottom-Up Approach
- 2.4.2 Top-Down Approach
- 2.5 Forecasting Methodology
- 3 Executive Summary
- 4 Introduction
- 4.1 Overview
- 4.2 Key Industry Trends
- 5 Global AI in Oil and Gas Market
- 5.1 Market Overview
- 5.2 Market Performance
- 5.3 Impact of COVID-19
- 5.4 Market Forecast
- 6 Market Breakup by Type
- 6.1 Hardware
- 6.1.1 Market Trends
- 6.1.2 Market Forecast
- 6.2 Software
- 6.2.1 Market Trends
- 6.2.2 Market Forecast
- 6.3 Services
- 6.3.1 Market Trends
- 6.3.2 Market Forecast
- 7 Market Breakup by Function
- 7.1 Predictive Maintenance and Machinery Inspection
- 7.1.1 Market Trends
- 7.1.2 Market Forecast
- 7.2 Material Movement
- 7.2.1 Market Trends
- 7.2.2 Market Forecast
- 7.3 Production Planning
- 7.3.1 Market Trends
- 7.3.2 Market Forecast
- 7.4 Field Services
- 7.4.1 Market Trends
- 7.4.2 Market Forecast
- 7.5 Quality Control
- 7.5.1 Market Trends
- 7.5.2 Market Forecast
- 7.6 Reclamation
- 7.6.1 Market Trends
- 7.6.2 Market Forecast
- 8 Market Breakup by Application
- 8.1 Upstream
- 8.1.1 Market Trends
- 8.1.2 Market Forecast
- 8.2 Downstream
- 8.2.1 Market Trends
- 8.2.2 Market Forecast
- 8.3 Midstream
- 8.3.1 Market Trends
- 8.3.2 Market Forecast
- 9 Market Breakup by Region
- 9.1 North America
- 9.1.1 United States
- 9.1.1.1 Market Trends
- 9.1.1.2 Market Forecast
- 9.1.2 Canada
- 9.1.2.1 Market Trends
- 9.1.2.2 Market Forecast
- 9.2 Asia-Pacific
- 9.2.1 China
- 9.2.1.1 Market Trends
- 9.2.1.2 Market Forecast
- 9.2.2 Japan
- 9.2.2.1 Market Trends
- 9.2.2.2 Market Forecast
- 9.2.3 India
- 9.2.3.1 Market Trends
- 9.2.3.2 Market Forecast
- 9.2.4 South Korea
- 9.2.4.1 Market Trends
- 9.2.4.2 Market Forecast
- 9.2.5 Australia
- 9.2.5.1 Market Trends
- 9.2.5.2 Market Forecast
- 9.2.6 Indonesia
- 9.2.6.1 Market Trends
- 9.2.6.2 Market Forecast
- 9.2.7 Others
- 9.2.7.1 Market Trends
- 9.2.7.2 Market Forecast
- 9.3 Europe
- 9.3.1 Germany
- 9.3.1.1 Market Trends
- 9.3.1.2 Market Forecast
- 9.3.2 France
- 9.3.2.1 Market Trends
- 9.3.2.2 Market Forecast
- 9.3.3 United Kingdom
- 9.3.3.1 Market Trends
- 9.3.3.2 Market Forecast
- 9.3.4 Italy
- 9.3.4.1 Market Trends
- 9.3.4.2 Market Forecast
- 9.3.5 Spain
- 9.3.5.1 Market Trends
- 9.3.5.2 Market Forecast
- 9.3.6 Russia
- 9.3.6.1 Market Trends
- 9.3.6.2 Market Forecast
- 9.3.7 Others
- 9.3.7.1 Market Trends
- 9.3.7.2 Market Forecast
- 9.4 Latin America
- 9.4.1 Brazil
- 9.4.1.1 Market Trends
- 9.4.1.2 Market Forecast
- 9.4.2 Mexico
- 9.4.2.1 Market Trends
- 9.4.2.2 Market Forecast
- 9.4.3 Others
- 9.4.3.1 Market Trends
- 9.4.3.2 Market Forecast
- 9.5 Middle East and Africa
- 9.5.1 Market Trends
- 9.5.2 Market Breakup by Country
- 9.5.3 Market Forecast
- 10 SWOT Analysis
- 10.1 Overview
- 10.2 Strengths
- 10.3 Weaknesses
- 10.4 Opportunities
- 10.5 Threats
- 11 Value Chain Analysis
- 12 Porters Five Forces Analysis
- 12.1 Overview
- 12.2 Bargaining Power of Buyers
- 12.3 Bargaining Power of Suppliers
- 12.4 Degree of Competition
- 12.5 Threat of New Entrants
- 12.6 Threat of Substitutes
- 13 Price Analysis
- 14 Competitive Landscape
- 14.1 Market Structure
- 14.2 Key Players
- 14.3 Profiles of Key Players
- 14.3.1 Accenture plc
- 14.3.1.1 Company Overview
- 14.3.1.2 Product Portfolio
- 14.3.1.3 Financials
- 14.3.1.4 SWOT Analysis
- 14.3.2 C3.AI Inc.
- 14.3.2.1 Company Overview
- 14.3.2.2 Product Portfolio
- 14.3.2.3 Financials
- 14.3.3 Cisco Systems Inc.
- 14.3.3.1 Company Overview
- 14.3.3.2 Product Portfolio
- 14.3.3.3 Financials
- 14.3.3.4 SWOT Analysis
- 14.3.4 Cloudera Inc.
- 14.3.4.1 Company Overview
- 14.3.4.2 Product Portfolio
- 14.3.5 Fugenx Technologies
- 14.3.5.1 Company Overview
- 14.3.5.2 Product Portfolio
- 14.3.6 Huawei Technologies Co. Ltd
- 14.3.6.1 Company Overview
- 14.3.6.2 Product Portfolio
- 14.3.6.3 SWOT Analysis
- 14.3.7 Infosys Limited
- 14.3.7.1 Company Overview
- 14.3.7.2 Product Portfolio
- 14.3.7.3 Financials
- 14.3.7.4 SWOT Analysis
- 14.3.8 Intel Corporation
- 14.3.8.1 Company Overview
- 14.3.8.2 Product Portfolio
- 14.3.8.3 Financials
- 14.3.8.4 SWOT Analysis
- 14.3.9 International Business Machines Corporation
- 14.3.9.1 Company Overview
- 14.3.9.2 Product Portfolio
- 14.3.9.3 Financials
- 14.3.10 Microsoft Corporation
- 14.3.10.1 Company Overview
- 14.3.10.2 Product Portfolio
- 14.3.10.3 Financials
- 14.3.10.4 SWOT Analysis
- 14.3.11 Neudax
- 14.3.11.1 Company Overview
- 14.3.11.2 Product Portfolio
- 14.3.12 Nvidia Corporation
- 14.3.12.1 Company Overview
- 14.3.12.2 Product Portfolio
- 14.3.12.3 Financials
- 14.3.12.4 SWOT Analysis
- 14.3.13 Oracle Corporation
- 14.3.13.1 Company Overview
- 14.3.13.2 Product Portfolio
- 14.3.13.3 Financials
- 14.3.13.4 SWOT Analysis
- 14.3.14 Shell plc
- 14.3.14.1 Company Overview
- 14.3.14.2 Product Portfolio
- 14.3.14.3 Financials
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