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市场调查报告书

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1489182

全球石油和天然气人工智慧市场研究报告 - 2024 年至 2032 年行业分析、规模、份额、成长、趋势和预测

Global AI in Oil and Gas Market Research Report - Industry Analysis, Size, Share, Growth, Trends and Forecast 2024 to 2032

出版日期: 2024年05月01日 | 出版商:

Value Market Research | 英文 130 Pages | 商品交期: 最快1-2个工作天内

价格

简介目录图表

全球石油和天然气市场对人工智慧的需求预计将从 2023 年的 30.9 亿美元达到近 93.2 亿美元的市场规模，2024-2032 年研究期间复合年增长率为 13.05%。

油气人工智慧是指应用人工智慧（AI）技术来提高油气资源勘探、生产和分配的效率、安全性和生产力。人工智慧驱动的解决方案可实现预测性维护、油藏建模和即时资料分析，优化决策流程并降低营运成本。透过利用机器学习演算法和资料分析，人工智慧系统可以识别模式、检测异常并优化钻井和开采过程，从而提高石油和天然气行业的资源回收率和环境永续性。

市场动态

石油和天然气营运的复杂性和规模不断增加，加上降低成本、提高效率和降低风险的需求，促使采用人工智慧技术来优化流程和决策。人工智慧驱动的解决方案可实现预测性维护、油藏建模和即时资料分析，从而提高整个价值链的营运绩效和资产完整性。此外，人工智慧演算法、机器学习技术和巨量资料分析的进步从感测器、设备和生产设施产生的大量资料中释放出可操作的见解，推动人工智慧在石油和天然气市场的成长。

此外，对数位转型和工业 4.0 计画的日益关注加速了人工智慧在石油和天然气领域的采用，促进了该产业的创新和竞争力。此外，监管压力、环境问题以及石油和天然气市场波动中的人工智慧推动了对永续实践和减排策略的需求，进一步推动了对人工智慧驱动的能源效率和环境管理解决方案的需求。然而，网路安全威胁、资料隐私问题以及传统石油和天然气业务中采用人工智慧的潜在阻力可能会在未来几年对石油和天然气市场成长的人工智慧构成挑战。

研究报告涵盖波特五力模型、市场吸引力分析和价值链分析。这些工具有助于清晰地了解行业结构并评估全球范围内的竞争吸引力。此外，这些工具也对全球石油和天然气人工智慧市场的各个细分市场进行了包容性评估。石油和天然气行业人工智慧的成长和趋势为本研究提供了整体方法。

市场区隔

石油和天然气市场人工智慧报告的这一部分提供了国家和区域层面的细分资料，从而帮助战略家确定相应产品或服务的目标人口统计数据以及即将到来的机会。

按功能分类

开垦
物质运动
计划生产
品质管制
维护
其他的

按操作

上游
中游
下游

区域分析

本节涵盖区域展望，重点介绍北美、欧洲、亚太地区、拉丁美洲以及中东和非洲地区石油和天然气市场人工智慧当前和未来的需求。此外，该报告重点关注所有主要地区各个应用领域的需求、估计和预测。

该研究报告还涵盖了市场主要参与者的全面概况以及对全球竞争格局的深入了解。石油和天然气市场人工智慧的主要参与者包括埃森哲、Google、微软、甲骨文、IBM、英特尔、英伟达。本节包含竞争格局的整体视图，包括各种策略发展，例如关键併购、未来产能、合作伙伴关係、财务概况、合作、新产品开发、新产品发布和其他发展。

如果您有任何客製化要求，请写信给我们。我们的研究团队可以根据您的需求提供客製化报告。

区域展望
介绍
北美销售分析
- 概览、历史与预测资料销售分析
- 北美按细分市场销售分析
- 北美按国家销售分析
- 美国销售分析
- 加拿大销售分析
- 墨西哥销售分析
欧洲销售分析
- 概览、历史与预测资料销售分析
- 欧洲按细分市场销售分析
- 欧洲按国家销售分析
- 英国销售分析
- 法国销售分析
- 德国销售分析
- 义大利销售分析
- 俄罗斯销售分析
- 欧洲其他地区销售分析
亚太地区销售分析
- 概览、历史与预测资料销售分析
- 亚太地区按细分市场销售分析
- 亚太地区按国家销售分析
- 中国销售分析
- 印度销售分析
- 日本销售分析
- 韩国销售分析
- 澳洲销售分析
- 东南亚销售分析
- 亚太地区其他地区销售分析
拉丁美洲销售分析
- 概览、历史与预测资料销售分析
- 拉丁美洲按细分市场销售分析
- 拉丁美洲按国家销售分析
- 巴西销售分析
- 阿根廷销售分析
- 秘鲁销售分析
- 智利销售分析
- 拉丁美洲其他地区销售分析
中东和非洲销售分析
- 概览、历史与预测资料销售分析
- 中东和非洲按细分市场销售分析
- 中东和非洲按国家销售分析
- 沙乌地阿拉伯销售分析
- 阿联酋销售分析
- 以色列销售分析
- 南非销售分析
- 中东其他地区和非洲销售分析

第 8 章：石油和天然气公司中人工智慧的竞争格局

人工智慧在石油和天然气市场竞争中的应用
伙伴关係/协作/协议
併购
新产品发布
其他发展

第 9 章：公司简介

顶级公司市占率分析
市场集中度
Accenture

公司简介
公司收入
产品
最近的发展

Google LLC

公司简介
公司收入
产品
最近的发展

Microsoft Corporation

公司简介
公司收入
产品
最近的发展

Oracle

公司简介
公司收入
产品
最近的发展

公司简介
公司收入
产品
最近的发展

Intel Corporation

公司简介
公司收入
产品
最近的发展

Nvidia Corporation

公司简介
公司收入
产品
最近的发展

註 - 在公司概况中，财务详细资料和最新进展视情况而定，或对私人公司而言可能不包括在内

简介目录图表

Product Code: VMR112114577

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.

In case you have any custom requirements, do write to us. Our research team can offer a customized report as per your need.

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