세계의 석유 및 가스용 AI 시장 조사 보고서 : 산업 분석, 규모, 점유율, 성장, 동향, 예측(2024-2032년)

The global demand for AI in Oil and Gas Market is presumed to reach the market size of nearly USD 9.32 Billion by 2032 from USD 3.09 Billion in 2023 with a CAGR of 13.05% under the study period 2024-2032.

AI in oil and gas refers to applying artificial intelligence (AI) technologies to enhance efficiency, safety, and productivity in the exploration, production, and distribution of oil and gas resources. AI-powered solutions enable predictive maintenance, reservoir modeling, and real-time data analysis, optimizing decision-making processes and reducing operational costs. By leveraging machine learning algorithms & data analytics, AI systems can identify patterns, detect anomalies, and optimize drilling and extraction processes, leading to improved resource recovery and environmental sustainability in the oil & gas industry.

MARKET DYNAMICS

The increasing complexity and scale of oil and gas operations, coupled with the need for cost reduction, efficiency improvements, and risk mitigation, prompt the adoption of AI technologies to optimize processes and decision-making. AI-powered solutions enable predictive maintenance, reservoir modeling, and real-time data analysis, enhancing operational performance and asset integrity across the value chain. Moreover, advancements in AI algorithms, machine learning techniques, and big data analytics unlock actionable insights from vast amounts of data generated by sensors, equipment, and production facilities, driving AI in oil and gas market growth.

Additionally, the growing focus on digital transformation and Industry 4.0 initiatives accelerates AI adoption in oil and gas, fostering innovation and competitiveness in the sector. Furthermore, regulatory pressures, environmental concerns, and AI in oil and gas market volatility drive the need for sustainable practices and emissions reduction strategies, further fuelling demand for AI-driven solutions for energy efficiency and environmental stewardship. However, cybersecurity threats, data privacy concerns, and potential resistance to AI adoption within traditional oil and gas operations may challenge AI in oil and gas market growth in the coming years.

The research report covers Porter's Five Forces Model, Market Attractiveness Analysis, and Value Chain analysis. These tools help to get a clear picture of the industry's structure and evaluate the competition attractiveness at a global level. Additionally, these tools also give an inclusive assessment of each segment in the global market of AI in Oil and Gas. The growth and trends of AI in Oil and Gas industry provide a holistic approach to this study.

MARKET SEGMENTATION

This section of the AI in Oil and Gas market report provides detailed data on the segments at country and regional level, thereby assisting the strategist in identifying the target demographics for the respective product or services with the upcoming opportunities.

By Function

• Reclamation
• Material Movement
• Production Planning
• Quality Control
• Maintenance
• Others

By Operation

• Upstream
• Midstream
• Downstream

REGIONAL ANALYSIS

This section covers the regional outlook, which accentuates current and future demand for the AI in Oil and Gas market across North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa. Further, the report focuses on demand, estimation, and forecast for individual application segments across all the prominent regions.

The research report also covers the comprehensive profiles of the key players in the market and an in-depth view of the competitive landscape worldwide. The major players in the AI in Oil and Gas market include Accenture, Google LLC, Microsoft Corporation, Oracle, IBM, Intel Corporation, Nvidia Corporation. This section consists of a holistic view of the competitive landscape that includes various strategic developments such as key mergers & acquisitions, future capacities, partnerships, financial overviews, collaborations, new product developments, new product launches, and other developments.

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TABLE OF CONTENTS

1. PREFACE

• 1.1. Report Description
  • 1.1.1 Objective
  • 1.1.2 Target Audience
  • 1.1.3 Unique Selling Proposition (USP) & offerings
• 1.2. Research Scope
• 1.3. Research Methodology
  • 1.3.1 Market Research Process
  • 1.3.2 Market Research Methodology

2. EXECUTIVE SUMMARY

• 2.1. Highlights of Market
• 2.2. Global Market Snapshot

3. AI IN OIL AND GAS - INDUSTRY ANALYSIS

• 3.1. Introduction - Market Dynamics
• 3.2. Market Drivers
• 3.3. Market Restraints
• 3.4. Opportunities
• 3.5. Industry Trends
• 3.6. Porter's Five Force Analysis
• 3.7. Market Attractiveness Analysis
  • 3.7.1 Market Attractiveness Analysis By Function
  • 3.7.2 Market Attractiveness Analysis By Operation
  • 3.7.3 Market Attractiveness Analysis By Region

4. VALUE CHAIN ANALYSIS

• 4.1. Value Chain Analysis
• 4.2. Raw Material Analysis
  • 4.2.1 List of Raw Materials
  • 4.2.2 Raw Material Manufactures List
  • 4.2.3 Price Trend of Key Raw Materials
• 4.3. List of Potential Buyers
• 4.4. Marketing Channel
  • 4.4.1 Direct Marketing
  • 4.4.2 Indirect Marketing
  • 4.4.3 Marketing Channel Development Trend

5. GLOBAL AI IN OIL AND GAS MARKET ANALYSIS BY FUNCTION

• 5.1. Overview By Function
• 5.2. Historical and Forecast Data
• 5.3. Analysis By Function
• 5.4. Reclamation Historic and Forecast Sales By Regions
• 5.5. Material Movement Historic and Forecast Sales By Regions
• 5.6. Production Planning Historic and Forecast Sales By Regions
• 5.7. Quality Control Historic and Forecast Sales By Regions
• 5.8. Maintenance Historic and Forecast Sales By Regions
• 5.9. Others Historic and Forecast Sales By Regions

6. GLOBAL AI IN OIL AND GAS MARKET ANALYSIS BY OPERATION

• 6.1. Overview By Operation
• 6.2. Historical and Forecast Data
• 6.3. Analysis By Operation
• 6.4. Upstream Historic and Forecast Sales By Regions
• 6.5. Midstream Historic and Forecast Sales By Regions
• 6.6. Downstream Historic and Forecast Sales By Regions

7. GLOBAL AI IN OIL AND GAS MARKET ANALYSIS BY GEOGRAPHY

• 7.1. Regional Outlook
• 7.2. Introduction
• 7.3. North America Sales Analysis
  • 7.3.1 Overview, Historic and Forecast Data Sales Analysis
  • 7.3.2 North America By Segment Sales Analysis
  • 7.3.3 North America By Country Sales Analysis
  • 7.3.4 United States Sales Analysis
  • 7.3.5 Canada Sales Analysis
  • 7.3.6 Mexico Sales Analysis
• 7.4. Europe Sales Analysis
  • 7.4.1 Overview, Historic and Forecast Data Sales Analysis
  • 7.4.2 Europe By Segment Sales Analysis
  • 7.4.3 Europe By Country Sales Analysis
  • 7.4.4 United Kingdom Sales Analysis
  • 7.4.5 France Sales Analysis
  • 7.4.6 Germany Sales Analysis
  • 7.4.7 Italy Sales Analysis
  • 7.4.8 Russia Sales Analysis
  • 7.4.9 Rest Of Europe Sales Analysis
• 7.5. Asia Pacific Sales Analysis
  • 7.5.1 Overview, Historic and Forecast Data Sales Analysis
  • 7.5.2 Asia Pacific By Segment Sales Analysis
  • 7.5.3 Asia Pacific By Country Sales Analysis
  • 7.5.4 China Sales Analysis
  • 7.5.5 India Sales Analysis
  • 7.5.6 Japan Sales Analysis
  • 7.5.7 South Korea Sales Analysis
  • 7.5.8 Australia Sales Analysis
  • 7.5.9 South East Asia Sales Analysis
  • 7.5.10 Rest Of Asia Pacific Sales Analysis
• 7.6. Latin America Sales Analysis
  • 7.6.1 Overview, Historic and Forecast Data Sales Analysis
  • 7.6.2 Latin America By Segment Sales Analysis
  • 7.6.3 Latin America By Country Sales Analysis
  • 7.6.4 Brazil Sales Analysis
  • 7.6.5 Argentina Sales Analysis
  • 7.6.6 Peru Sales Analysis
  • 7.6.7 Chile Sales Analysis
  • 7.6.8 Rest of Latin America Sales Analysis
• 7.7. Middle East & Africa Sales Analysis
  • 7.7.1 Overview, Historic and Forecast Data Sales Analysis
  • 7.7.2 Middle East & Africa By Segment Sales Analysis
  • 7.7.3 Middle East & Africa By Country Sales Analysis
  • 7.7.4 Saudi Arabia Sales Analysis
  • 7.7.5 UAE Sales Analysis
  • 7.7.6 Israel Sales Analysis
  • 7.7.7 South Africa Sales Analysis
  • 7.7.8 Rest Of Middle East And Africa Sales Analysis

8. COMPETITIVE LANDSCAPE OF THE AI IN OIL AND GAS COMPANIES

• 8.1. AI in Oil and Gas Market Competition
• 8.2. Partnership/Collaboration/Agreement
• 8.3. Merger And Acquisitions
• 8.4. New Product Launch
• 8.5. Other Developments

9. COMPANY PROFILES OF AI IN OIL AND GAS INDUSTRY

• 9.1. Top Companies Market Share Analysis
• 9.2. Market Concentration Rate
• 9.3. Accenture
  • 9.3.1 Company Overview
  • 9.3.2 Company Revenue
  • 9.3.3 Products
  • 9.3.4 Recent Developments
• 9.4. Google LLC
  • 9.4.1 Company Overview
  • 9.4.2 Company Revenue
  • 9.4.3 Products
  • 9.4.4 Recent Developments
• 9.5. Microsoft Corporation
  • 9.5.1 Company Overview
  • 9.5.2 Company Revenue
  • 9.5.3 Products
  • 9.5.4 Recent Developments
• 9.6. Oracle
  • 9.6.1 Company Overview
  • 9.6.2 Company Revenue
  • 9.6.3 Products
  • 9.6.4 Recent Developments
• 9.7. IBM
  • 9.7.1 Company Overview
  • 9.7.2 Company Revenue
  • 9.7.3 Products
  • 9.7.4 Recent Developments
• 9.8. Intel Corporation
  • 9.8.1 Company Overview
  • 9.8.2 Company Revenue
  • 9.8.3 Products
  • 9.8.4 Recent Developments
• 9.9. Nvidia Corporation
  • 9.9.1 Company Overview
  • 9.9.2 Company Revenue
  • 9.9.3 Products
  • 9.9.4 Recent Developments

Note - In company profiling, financial details and recent developments are subject to availability or might not be covered in the case of private companies