石油、天然氣的AI市場規模 - 成長,趨勢,及預測(2019年 - 2024年)

AI in Oil & Gas Market Size - Growth, Trends, and Forecast (2020 - 2025)

出版商 Mordor Intelligence LLP 商品編碼 871447
出版日期 內容資訊 英文 120 Pages
商品交期: 2-3個工作天內
石油、天然氣的AI市場規模 - 成長,趨勢,及預測(2019年 - 2024年) AI in Oil & Gas Market Size - Growth, Trends, and Forecast (2020 - 2025)
出版日期: 2020年01月01日內容資訊: 英文 120 Pages




第1章 簡介

  • 研究成果
  • 調查的前提條件
  • 調查範圍

第2章 調查方法

第3章 摘要整理

第4章 市場動態

  • 市場概況
  • 市場成長及阻礙因素的簡介
  • 市場成長要素
    • 能源及電力部門整體巨量資料的投資擴大
    • 處理由IoT生成的大量資料的必要性增加化
    • 為了削減製造成本合理化廢棄物的自動化的趨勢
  • 市場阻礙因素
    • AI引進的高初期投資成本
    • 跨石油、天然氣產業整體的熟練專家不足
  • 產業的魅力 - 波特的五力分析
    • 新加入廠商的威脅
    • 買主/消費者談判力
    • 供應商談判力
    • 替代產品的威脅
    • 產業內的競爭

第5章 市場區隔

  • 各用途
    • 品管
    • 生產計劃
    • 預測維修
    • 熱探測(無人機分析)
    • 其他的用途
  • 各營運
    • 上游
    • 中游
    • 下游
  • 各服務形式
    • 專業
    • 管理
  • 各地區
    • 北美
    • 歐洲
    • 亞太地區
    • 南美
    • 中東及非洲

第6章 競爭情形

  • 企業簡介
    • Google LLC
    • IBM Corporation
    • FuGenX Technologies Pvt. Ltd.
    • Hortonworks Inc.
    • Microsoft Corporation
    • Intel Corporation
    • Royal Dutch Shell PLC
    • PJSC Gazprom Neft
    • Huawei Technologies Co., Ltd.
    • NVIDIA Corp.
    • Infosys Ltd.

第7章 投資分析

第8章 市場機會及今後趨勢


Product Code: 64253

Market Overview

The AI in Oil and Gas market was valued at USD 2 billion in 2019 and is expected to reach USD 3.98 million by 2025, at a CAGR of 12.14% over the forecast period 2020 - 2025. As the cost of IoT sensors declines, more major oil & gas organizations are bound to start integrating these sensors into their upstream, midstream, and downstream operations along with AI enabled predictive analytics.

  • The increasing demand for big data technology in the oil & gas industry to augment E&P capabilities with the growing need for automation in the oil & gas industry is thereby increasing the investments through joint venture capitals. Since artificial intelligence systems can optimize and automate data rich processes, they help in minimizing or eliminating duplication of efforts and further in mitigating business risk. This enhances productivity and minimizes the overall operational cost.
  • The increasing demand for big data technology in the oil & gas industry to augment E&P capabilities with the growing need for automation in the oil & gas industry is thereby increasing the investments through joint venture capitals.
  • However, high capital investments for the integration of AI technologies along with the lack of skilled AI professionals could hinder the growth of the market.

Scope of the Report

The upstream sector of Oil and Gas industry includes searching for potential underground or underwater crude oil and natural gas fields, drilling exploratory wells, and subsequently drilling and operating the wells that recover and bring the crude oil or raw natural gas to the surface. The midstream sector involves transportation (by pipeline, rail, barge, oil tanker or truck), storage, and wholesale marketing of crude or refined petroleum products. Pipelines and other transport systems can be used to move crude oil from production sites to refineries and deliver the various refined products to downstream distributors. The downstream sector is the refining of petroleum crude oil and the processing and purifying of raw natural gas as well as the marketing and distribution of products derived from crude oil and natural gas.

Key Market Trends

Predictive Maintenance is Expected to Hold a Major Market Share in the Forecast Period

  • With the increasing demands for oil and gas, the manufacturers have started focussing on the discovery of the new oil wells. The predictive maintenance helps the manufacturer to save the money as the input cost which is majorly dominated by the maintenance costs are reduced due to the continuous monitoring being held.
  • Oil and gas companies store crude and refined oils in large tanks and transport it through pipelines. As crude oil from oil fields usually varies in its chemical compositions, the corrosiveness of the crude also depends on the environment it is stored in. Corrosion caused by crude oils is one of the prevalent risks for equipment failures in the oil and gas industries.
  • Corrosion engineers are employed for this purpose in order to keep the machinery corrosion free. AI has come into the picture recently with its software-driven solutions. For instance, Maana, Palo Alto California-based company, offers software called Computational Knowledge Graph, which it claims can help oil and gas companies reduce unplanned maintenance from oil corrosion using predictive analytics.
  • The data collected over several years can be used to improve the efficiency of their predictive maintenance techniques. With AI getting implemented at a broader level in the oil and gas industry, the manufacturers can now take advantage of it to improvise on their maintenance techniques to reduce machine failures. For instance, Alejandro Betancourt, the lead of the analytics team at Columbian oil and gas company Ecopetrol, seemed to suggest that the oil and gas industry has collected data over the years that might have been curated and analyzed by human experts, making it ripe for feeding into AI systems. A large part of this data includes exploration, production and reservoir data logs. This helps in analyzing the failure patterns of the machinery this powering the predictive maintenance techniques positively.
  • With global emission policies tightening up, the limelight of the industry has shifted to the predictive maintenance of the machinery. With proper maintenance strategies, a company can control the carbon emissions thus reducing the threat of government penalties.

North America is Expected to Hold a Major Market Share in the Forecast Period

Owing to the increasing adoption of AI technologies across the oilfield operators and service providers and the robust presence of prominent AI software and system suppliers, especially in the United States and Canada, the North American segment is anticipated to account for the largest share of the AI in the oil & gas market, over the forecast period.

Owing to the increasing inflow of investments in startups for AI implementation, which would further augment the demand for AI in the near future, the region is poised to be the fastest-growing segment. Some of the prominent players of the North American region are - Google LLC, IBM Corp., FuGenX Technologies Pvt. Ltd, Hortonworks Inc., Microsoft Corporation, and Intel Corp., among others.

The largest oil and gas companies in the USA are poised to impact the market positively as they embrace the latest technologies and innovations. They launched an American energy renaissance, leading to new natural gas finds and expansion of oil production from reserves that were once deemed unavailable.

'The Environmental Partnership', is an industry-led initiative created to help the largest oil and gas companies in the USA to work together and continuously negate adverse environmental impacts. It's a landmark collaboration that's initially focused on further reducing emissions from oil and gas production in the USA. This shows the shift towards growing environmental concerns. Artificial Intelligence can facilitate the control of carbon emissions by streamlining the predictive maintenance techniques.

Competitive Landscape

The AI in the Oil and Gas market is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. The companies are continuously capitalizing on acquisitions, in order to broaden, complement, and enhance its product and service offerings, to add new customers and certified personnel, and to help expand sales channels.

October 2018 - IBM recently acquired Red Hat to position itself as a cloud power. With the deal, IBM carves out a place for itself that's separate from the top cloud providers. Whereas Amazon, Microsoft, and Google are primarily public cloud and software providers, IBM specializes in hybrid cloud, offering a deep hardware and software stack stretching back through literally 60 years of enterprise legacy, and looking ahead to the containerized and AI-enabled future.

Reasons to Purchase this report:

  • The market estimate (ME) sheet in Excel format
  • Report customization as per the client's requirements
  • 3 months of analyst support

Table of Contents


  • 1.1 Study Deliverables
  • 1.2 Study Assumptions
  • 1.3 Scope of the Study




  • 4.1 Market Overview
  • 4.2 Introduction to Market Drivers and Restraints
  • 4.3 Market Drivers
    • 4.3.1 Growing Investment on Big Data across the Energy and Power Sector
    • 4.3.2 Increasing Need to Handle the Significant Volume of Data Generated from IoT
    • 4.3.3 Rising Trend of Automation to Reduce Production Cost and Streamline Wastage
  • 4.4 Market Restraints
    • 4.4.1 High Initial Investment Costs in AI Implementation
    • 4.4.2 Lack of Skilled Professional across the Oil and Gas Industry
  • 4.5 Industry Attractiveness - Porter's Five Force Analysis
    • 4.5.1 Threat of New Entrants
    • 4.5.2 Bargaining Power of Buyers/Consumers
    • 4.5.3 Bargaining Power of Suppliers
    • 4.5.4 Threat of Substitute Products
    • 4.5.5 Intensity of Competitive Rivalry


  • 5.1 By Application
    • 5.1.1 Quality Control
    • 5.1.2 Production Planning
    • 5.1.3 Predictive Maintenance
    • 5.1.4 Thermal Detection (Drone Analytics)
    • 5.1.5 Other Applications
  • 5.2 By Operation
    • 5.2.1 Upstream
    • 5.2.2 Midstream
    • 5.2.3 Downstream
  • 5.3 By Service Type
    • 5.3.1 Professional
    • 5.3.2 Managed
  • 5.4 Geography
    • 5.4.1 North America
    • 5.4.2 Europe
    • 5.4.3 Asia-Pacific
    • 5.4.4 Latin America
    • 5.4.5 Middle East & Africa


  • 6.1 Company Profiles
    • 6.1.1 Google LLC
    • 6.1.2 IBM Corporation
    • 6.1.3 FuGenX Technologies Pvt. Ltd.
    • 6.1.4 Hortonworks Inc.
    • 6.1.5 Microsoft Corporation
    • 6.1.6 Intel Corporation
    • 6.1.7 Royal Dutch Shell PLC
    • 6.1.8 PJSC Gazprom Neft
    • 6.1.9 Huawei Technologies Co., Ltd.
    • 6.1.10 NVIDIA Corp.
    • 6.1.11 Infosys Ltd.