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1468191

2024-2032 年按類型、功能、應用和地區分類的石油和天然氣市場人工智慧報告

AI in Oil and Gas Market Report by Type, Function, Application, and Region 2024-2032
出版日期: | 出版商: IMARC | 英文 137 Pages | 商品交期: 2-3個工作天內

價格

IMARC Group年，全球人工智慧在石油和天然氣領域的市場規模達到27億美元。 。石油和天然氣行業的資料爆炸式成長、對營運效率的要求不斷提高、對安全的日益重視、嚴格的環境法規的實施以及人工智慧（AI）演算法的最新技術進步是推動市場的一些主要因素。

石油和天然氣領域的人工智慧是指人工智慧（AI）技術在石油和天然氣產業最佳化流程、增強安全性和改善決策的應用。它包括神經網路、電腦視覺、機器學習 (ML)、機器人技術和自然語言處理 (NLP)。石油和天然氣領域的人工智慧廣泛應用於油藏模擬、自動化鑽井、預測性維護、地質測繪、安全監控、流程自動化和資產管理等領域。它有助於決策、降低成本、提高安全性、提高可靠性、增強可擴展性和促進永續性。

人工智慧的廣泛採用提供了具有成本效益的解決方案，可以最佳化資源並簡化整個石油和天然氣行業的營運，正在推動市場成長。此外，實施嚴格的環境法規迫使企業使用人工智慧來更好地合規並最大限度地減少石油和天然氣開採過程中的碳足跡，這對市場成長產生了積極影響。此外，人工智慧演算法的最新技術進步，加上運算能力的增強，使得實施基於人工智慧的解決方案更加實用和高效，正在支援市場成長。除此之外，執行複雜任務的熟練人員日益短缺，促進了對人工智慧的需求，以實現各種石油和天然氣鑽探作業的自動化能力。其他因素，包括對永續性的日益重視、對營運透明度的需求不斷增加以及石油和天然氣探勘的增加，預計將推動市場成長。

石油和天然氣市場趨勢/促進因素中的人工智慧：

石油和天然氣產業日益成長的資料爆炸

石油和天然氣產業正在透過感測器、鑽井設備和各種其他營運技術產生前所未有的資料量。與傳統的資料分析工具相比，人工智慧被廣泛用於即時有效地管理和解釋這些資料，這是了不起的。此外，它還提供高級分析功能，可以瀏覽大量資料集以檢查模式、趨勢和異常。除此之外，人工智慧還提供了將原始資料轉化為有用見解的工具，可用於監控鑽井作業和最佳化供應鏈流程。此外，公司擴大投資於人工智慧解決方案，以理解他們的資料並將其轉變為戰略資產，以做出更明智的決策。

對營運效率的需求不斷成長

石油和天然氣行業涉及複雜且往往危險的作業，需要精心規劃和執行。此外，人為錯誤、設備故障或操作任何部分的低效率都可能導致重大的財務損失或安全風險。與此一致的是，人工智慧技術，特別是機器學習 (ML) 和預測分析，提供了顯著最佳化這些操作的能力。此外，他們還可以在設備故障發生之前進行預測，自動執行重複任務，並提高鑽井和開採過程的精確度。此外，人工智慧不僅可以降低成本，還可以最大限度地降低與人為錯誤和系統故障相關的風險。因此，營運效率是人工智慧融入油氣產業的主要促進因素。

對安全的日益重視

由於石油和天然氣行業作業的危險性（例如深海鑽探或使用高度易燃材料），人們越來越重視石油和天然氣行業的安全，這正在推動市場成長。此外，傳統的安全措施往往無法完全消除事故和故障。據此，人工智慧透過即時監控、預測分析和自動化控制系統提供了先進的安全協定層。它可以分析來自多個感測器的資料，以檢測可能預示潛在事故的異常情況，從而能夠在事故發生之前採取預防措施。此外，人工智慧可以自動執行某些高風險任務，減少潛在危險場景中人工干預的需要。因此，採用人工智慧技術來增強安全措施是推動市場成長的重要因素。

目錄

第1章：前言

第 2 章：範圍與方法

  • 研究目的
  • 利害關係人
  • 資料來源
    • 主要資源
    • 二手資料
  • 市場預測
    • 自下而上的方法
    • 自上而下的方法
  • 預測方法

第 3 章：執行摘要

第 4 章：簡介

  • 概述
  • 主要行業趨勢

第 5 章：全球人工智慧在石油和天然氣市場的應用

  • 市場概況
  • 市場業績
  • COVID-19 的影響
  • 市場預測

第 6 章：市場區隔：按類型

  • 硬體
    • 市場走向
    • 市場預測
  • 軟體
    • 市場走向
    • 市場預測
  • 服務
    • 市場走向
    • 市場預測

第 7 章：市場區隔：按功能

  • 預測性維護和機械檢查
    • 市場走向
    • 市場預測
  • 物質運動
    • 市場走向
    • 市場預測
  • 計劃生產
    • 市場走向
    • 市場預測
  • 現場服務
    • 市場走向
    • 市場預測
  • 品質管制
    • 市場走向
    • 市場預測
  • 開墾
    • 市場走向
    • 市場預測

第 8 章：市場區隔：按應用

  • 上游
    • 市場走向
    • 市場預測
  • 下游
    • 市場走向
    • 市場預測
  • 中游
    • 市場走向
    • 市場預測

第 9 章：市場區隔：按地區

  • 北美洲
    • 美國
    • 加拿大
  • 亞太
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 其他
  • 歐洲
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 其他
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他
  • 中東和非洲
    • 市場走向
    • 市場細分：按國家/地區
    • 市場預測

第 10 章：SWOT 分析

  • 概述
  • 優勢
  • 弱點
  • 機會
  • 威脅

第 11 章：價值鏈分析

第 12 章：波特五力分析

  • 概述
  • 買家的議價能力
  • 供應商的議價能力
  • 競爭程度
  • 新進入者的威脅
  • 替代品的威脅

第 13 章：價格分析

第14章：競爭格局

  • 市場結構
  • 關鍵參與者
  • 關鍵參與者簡介
    • 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
    • Shell plc
Product Code: SR112024A6014

The global AI in oil and gas market size reached US$ 2.7 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 5.7 Billion by 2032, exhibiting a growth rate (CAGR) of 8.61% during 2024-2032. The increasing data explosion in the oil and gas industry, rising demand for operational efficiency, growing emphasis on safety, imposition of strict environmental regulations, and the recent technological advancements in artificial intelligence (AI) algorithms are some of the major factors propelling the market.

AI in oil and gas refers to the application of artificial intelligence (AI) technologies in optimizing processes, enhancing safety, and improving decision-making in the oil and gas industry. It includes neural networks, computer visions, machine learning (ML), robotics, and natural language processing (NLP). AI in oil and gas is widely used in reservoir simulation, automated drilling, predictive maintenance, geological mapping, safety monitoring, process automation, and asset management. It aids in decision-making, reducing costs, increasing safety, improving reliability, enhancing scalability, and promoting sustainability.

The widespread adoption of AI to provide cost-effective solutions that can optimize resources and streamline operations across the oil and gas industry is propelling the market growth. Furthermore, the imposition of strict environmental regulations that are compelling firms to use AI for better compliance and to minimize their carbon footprint during oil and gas extraction is positively influencing the market growth. Additionally, the recent technological advancements in AI algorithms, coupled with increased computational power, which makes it more practical and efficient to implement AI-based solutions, are supporting the market growth. Besides this, the rising shortage of skilled personnel for complex tasks is facilitating the demand for AI to enable automation capabilities across various oil and gas drilling operations. Other factors, including the growing emphasis on sustainability, increasing demand for operational transparency, and rising oil and gas exploration, are anticipated to drive the market growth.

AI in Oil and Gas Market Trends/Drivers:

The increasing data explosion in the oil and gas industry

The oil and gas sector is generating an unprecedented volume of data stemming from sensors, drilling equipment, and various other operational technologies. As compared to traditional data analytics tools, AI is widely used to effectively manage and interpret this data in real-time, which is something. Furthermore, it offers advanced analytics capabilities that can browse through vast data sets to examine patterns, trends, and anomalies. Apart from this, AI provides the tools to transform raw data into useful insights that can be utilized for monitoring drilling operations and optimizing the supply chain processes. Moreover, companies are increasingly investing in AI solutions to make sense of their data and turn it into a strategic asset for smarter decision-making.

The rising demand for operational efficiency

The oil and gas sector involves complex, often hazardous operations that require meticulous planning and execution. Furthermore, human error, equipment failure, or inefficiencies in any part of the operation can result in significant financial losses or safety risks. In line with this, AI technologies, particularly machine learning (ML) and predictive analytics provide the capability to significantly optimize these operations. In addition, they can forecast equipment failures before they occur, automate repetitive tasks, and improve the precision of drilling and extraction processes. Moreover, AI not only reduces costs but also minimizes the risks associated with manual errors and system failures. As a result, operational efficiency is a major driving factor for the integration of AI in the oil and gas industry.

The growing emphasis on safety

The growing emphasis on safety in the oil and gas industry due to the hazardous nature of its operations, such as deep-sea drilling or working with highly flammable materials, is propelling the market growth. Furthermore, traditional safety measures often fall short of completely eliminating accidents and failures. In line with this, AI offers an advanced layer of safety protocols through real-time monitoring, predictive analytics, and automated control systems. It can analyze data from multiple sensors to detect irregularities that could signify a potential accident, enabling preventive actions to be taken before an incident occurs. Moreover, AI can automate certain high-risk tasks, reducing the need for manual intervention in potentially dangerous scenarios. As a result, the adoption of AI technologies for enhancing safety measures is a significant factor fueling the market growth.

AI in Oil and Gas Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the global AI in oil and gas market report, along with forecasts at the global, regional and country levels from 2024-2032. Our report has categorized the market based on type, function and application.

Breakup by Type:

Hardware

Software

Services

Software dominate the market

The report has provided a detailed breakup and analysis of the market based on type. This includes hardware, software, and services. According to the report, software represented the largest segment.

Software is dominating the market as it offers excellent flexibility and scalability, which make it highly adaptable to diverse operational needs. Furthermore, it can be easily updated to include new algorithms or features, ensuring that the oil and gas operations remain at the forefront of technological advancements. In addition, software solutions are more cost-effective in the long term, as they eliminate the need for heavy machinery or additional hardware installations. Besides this, it can be seamlessly integrated into existing systems, allowing for the centralization of data and processes. This harmonization significantly improves data analytics, enabling more accurate and timely decision-making. Moreover, software can be deployed across multiple sites, providing a unified approach to operations management. Apart from this, it can be continuously refined to address specific issues and opportunities presented by the oil and gas sector.

Breakup by Function:

Predictive Maintenance and Machinery Inspection

Material Movement

Production Planning

Field Services

Quality Control

Reclamation

Predictive maintenance and machinery inspection hold the largest share in the market

A detailed breakup and analysis of the market based on the function has also been provided in the report. This includes predictive maintenance and machinery inspection, material movement, production planning, field services, quality control, and reclamation. According to the report, predictive maintenance and machinery inspection accounted for the largest market share.

Predictive maintenance and machinery inspection are dominating the market as they aid in reducing downtime by analyzing equipment data and predicting failures before they happen. Furthermore, they help in identifying wear and tear or other forms of degradation that, if not addressed, could lead to serious safety issues. By preemptively identifying potential problems, companies can replace or repair components as needed, thereby improving the overall safety of operations. Additionally, the advancement in sensor technology and the Internet of Things (IoT), which has made data collection more robust and accurate, making predictive maintenance and machinery inspection increasingly reliable and effective, is positively influencing the market growth. Moreover, predictive maintenance and machinery inspection offers a strong return on investment (ROI), as they reduce maintenance costs, increase operational efficiency, and enhance security protocols.

Breakup by Application:

Upstream

Downstream

Midstream

Upstream hold the largest share in the market

A detailed breakup and analysis of the market based on the application has also been provided in the report. This includes upstream, downstream, and midstream. According to the report, upstream accounted for the largest market share.

The upstream is dominating the market as it involves various complex and data-intensive tasks, such as drilling, exploration, and extraction of natural gas and crude oil. Furthermore, it requires extensive data analysis for geological interpretation and reservoir modeling to identify promising drilling locations. In addition, AI-based predictive analytics are widely used in upstream operations to forecast equipment failures, allowing for preemptive actions that can save both time and money. Besides this, AI-powered remote sensing technologies and robotics are widely utilized to perform critical tasks that are either hazardous for human workers or logistically challenging to manage, thereby enhancing safety and operational efficiency. Moreover, the widespread adoption of AI in the upstream sector due to the imposition of strict environmental regulations is favoring the market growth.

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

North America exhibits a clear dominance, accounting for the largest AI in oil and gas market share

The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America accounted for the largest market share.

North America has a well-developed infrastructure for both oil and gas extraction and AI technology, making it easier for companies to adopt and integrate AI solutions. Furthermore, the escalating level of investment in research and innovation by regional governments and private players to ensure continuous development and implementation of AI in the oil and gas sector is positively influencing the market growth. Besides this, companies in North America have a more mature understanding of the value of data analytics. This data-driven culture is conducive to the acceptance and optimization of AI capabilities across various sectors, including oil and gas. Moreover, the easy availability of a skilled workforce trained in data sciences and AI algorithms, which facilitates the implementation of advanced technologies, is contributing to the market growth.

Competitive Landscape:

Leading companies are leveraging machine learning (ML), predictive analytics, and natural language processing (NLP) to optimize every aspect of the oil and gas lifecycle, from exploration and drilling to production and distribution. Additionally, they are forging strategic partnerships with technology providers, academic institutions, and competitors to accelerate innovation and share knowledge. Furthermore, they are focusing on gaining customer insights to address specific problems and offer tailored solutions, which aids in building trust and improving overall customer satisfaction. Besides this, market leaders are investing in pilot programs to test the practical applications of AI technologies before full-scale implementation. Moreover, the escalating emphasis on sustainability and environmental responsibility has prompted companies to build AI solutions that meet the stringent regulatory requirements of various regions and countries.

The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

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

Shell plc.

Recent Developments:

In January 2023, C3.AI Inc. launched the C3 Generative AI product suite, which will accelerate transformation efforts across business and industries, including oil and gas.

In March 2020, Accenture plc and SAP launched an upstream oil and gas solution to streamline processes and costs. This innovative solution uses AI to assist clients in increasing their visibility into operations and cash flow.

In October 2022, Huawei Technologies Co. Ltd showcased its Integrated Oil and Gas Field Network Solution, which uses edge computing, AI, and hard pipe isolation to manage all operations and enhance security.

Key Questions Answered in This Report

  • 1. What was the size of the global AI in oil and gas market in 2023?
  • 2. What is the expected growth rate of the global AI in oil and gas market during 2024-2032?
  • 3. What are the key factors driving the global AI in oil and gas market?
  • 4. What has been the impact of COVID-19 on the global AI in oil and gas market?
  • 5. What is the breakup of the global AI in oil and gas market based on the type?
  • 6. What is the breakup of the global AI in oil and gas market based on the function?
  • 7. What is the breakup of the global AI in oil and gas market based on the application?
  • 8. What are the key regions in the global AI in oil and gas market?
  • 9. Who are the key players/companies in the global AI in oil and gas market?

Table of Contents

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

List of Figures

  • Figure 1: Global: AI in Oil and Gas Market: Major Drivers and Challenges
  • Figure 2: Global: AI in Oil and Gas Market: Sales Value (in Billion US$), 2018-2023
  • Figure 3: Global: AI in Oil and Gas Market Forecast: Sales Value (in Billion US$), 2024-2032
  • Figure 4: Global: AI in Oil and Gas Market: Breakup by Type (in %), 2023
  • Figure 5: Global: AI in Oil and Gas Market: Breakup by Function (in %), 2023
  • Figure 6: Global: AI in Oil and Gas Market: Breakup by Application (in %), 2023
  • Figure 7: Global: AI in Oil and Gas Market: Breakup by Region (in %), 2023
  • Figure 8: Global: AI in Oil and Gas (Hardware) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 9: Global: AI in Oil and Gas (Hardware) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 10: Global: AI in Oil and Gas (Software) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 11: Global: AI in Oil and Gas (Software) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 12: Global: AI in Oil and Gas (Services) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 13: Global: AI in Oil and Gas (Services) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 14: Global: AI in Oil and Gas (Predictive Maintenance and Machinery Inspection) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 15: Global: AI in Oil and Gas (Predictive Maintenance and Machinery Inspection) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 16: Global: AI in Oil and Gas (Material Movement) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 17: Global: AI in Oil and Gas (Material Movement) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 18: Global: AI in Oil and Gas (Production Planning) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 19: Global: AI in Oil and Gas (Production Planning) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 20: Global: AI in Oil and Gas (Field Services) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 21: Global: AI in Oil and Gas (Field Services) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 22: Global: AI in Oil and Gas (Quality Control) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 23: Global: AI in Oil and Gas (Quality Control) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 24: Global: AI in Oil and Gas (Reclamation) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 25: Global: AI in Oil and Gas (Reclamation) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 26: Global: AI in Oil and Gas (Upstream) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 27: Global: AI in Oil and Gas (Upstream) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 28: Global: AI in Oil and Gas (Downstream) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 29: Global: AI in Oil and Gas (Downstream) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 30: Global: AI in Oil and Gas (Midstream) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 31: Global: AI in Oil and Gas (Midstream) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 32: North America: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 33: North America: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 34: United States: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 35: United States: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 36: Canada: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 37: Canada: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 38: Asia-Pacific: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 39: Asia-Pacific: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 40: China: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 41: China: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 42: Japan: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 43: Japan: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 44: India: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 45: India: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 46: South Korea: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 47: South Korea: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 48: Australia: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 49: Australia: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 50: Indonesia: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 51: Indonesia: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 52: Others: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 53: Others: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 54: Europe: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 55: Europe: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 56: Germany: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 57: Germany: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 58: France: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 59: France: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 60: United Kingdom: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 61: United Kingdom: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 62: Italy: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 63: Italy: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 64: Spain: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 65: Spain: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 66: Russia: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 67: Russia: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 68: Others: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 69: Others: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 70: Latin America: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 71: Latin America: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 72: Brazil: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 73: Brazil: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 74: Mexico: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 75: Mexico: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 76: Others: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 77: Others: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 78: Middle East and Africa: AI in Oil and Gas Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 79: Middle East and Africa: AI in Oil and Gas Market: Breakup by Country (in %), 2023
  • Figure 80: Middle East and Africa: AI in Oil and Gas Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 81: Global: AI in Oil and Gas Industry: SWOT Analysis
  • Figure 82: Global: AI in Oil and Gas Industry: Value Chain Analysis
  • Figure 83: Global: AI in Oil and Gas Industry: Porter's Five Forces Analysis

List of Tables

  • Table 1: Global: AI in Oil and Gas Market: Key Industry Highlights, 2023 and 2032
  • Table 2: Global: AI in Oil and Gas Market Forecast: Breakup by Type (in Million US$), 2024-2032
  • Table 3: Global: AI in Oil and Gas Market Forecast: Breakup by Function (in Million US$), 2024-2032
  • Table 4: Global: AI in Oil and Gas Market Forecast: Breakup by Application (in Million US$), 2024-2032
  • Table 5: Global: AI in Oil and Gas Market Forecast: Breakup by Region (in Million US$), 2024-2032
  • Table 6: Global: AI in Oil and Gas Market: Competitive Structure
  • Table 7: Global: AI in Oil and Gas Market: Key Players