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石油和天然氣領域的人工智慧- 市場佔有率分析、行業趨勢和統計、成長預測（2024-2029）

AI In Oil And Gas - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 130 Pages | 商品交期: 2-3個工作天內

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簡介目錄

石油和天然氣領域的人工智慧市場規模預計到2024年為31.4億美元，預計到2029年將達到57億美元，在預測期內（2024-2029年）複合年成長率為12.61%。

石油和天然氣市場中的人工智慧

人工智慧在石油和天然氣行業的儲存分析、鑽井最佳化、管道異常檢測、安全監測、排放、探勘和生產革命、環境永續性等方面的廣泛應用預計將推動市場成長。

主要亮點

  • 石油和天然氣市場中人工智慧驅動的預測性維護的興起正在改變公司管理該行業資產的方式。這確保了可靠性的提高和營運風險的降低，預計將推動未來市場的成長。
  • 例如，2023年10月，企業人工智慧應用軟體公司C3 AI宣布，其C3 AI可靠性應用將包含殼牌開發的預測維護軟體。這將增強C3AI人工智慧生態系統的使用，並使石油公司能夠維護關鍵設備。這顯示人工智慧平台在石油和天然氣領域的採用越來越多，支持了市場的成長。
  • 人工智慧技術在石油和天然氣營運中顯示出提高效率的潛力，包括發現模式、簡化工作流程、自動化決策以及探索來自感測器、機器和工業流程的大量資料。由人工智慧 (AI) 支援的預測性維護解決方案可以提前預測設備故障，使石油和天然氣營運商能夠主動規劃維護操作，節省停機時間，並最大限度地減少資產使用。
  • 全球石油和天然氣市場的人工智慧趨勢很大程度上是由生產成本下降的趨勢所推動的。面對波動的油價和不斷變化的市場動態，石油和天然氣營運商擴大尋求人工智慧（AI）技術來最佳化業務、簡化流程並降低成本。
  • 人工智慧正在加速其在包括石油和天然氣行業在內的各行業的採用，因為它可以處理整個價值鏈中的大量資料集。人工智慧可以透過機器學習從資料中提取更多價值，揭示隱藏的見解。透過最佳化複雜的營運，石油和燃氣公司可以降低成本並提高生產力。
  • 國際能源總署（IEA）報告稱，俄羅斯入侵烏克蘭後，俄羅斯削減了對歐洲的管道天然氣供應800億立方公尺（BCM），導致該地區出現能源危機。這影響了石油和天然氣行業中下游公司的營運，限制了市場的成長。
  • 歐盟（EU）的目標是透過基於可再生能源的能源舉措的出現來實現能源生產自給自足，但這可能會阻礙歐洲地區石油和天然氣產業的成長。這透過限制人工智慧解決方案和服務在石油和天然氣行業的實施範圍來間接影響市場成長。
  • COVID-19 大流行導致全球停工和經濟活動減少，限制了工業活動、旅行和其他用途的石油需求。在 COVID-19 大流行期間，國際原油價格也下跌，減少了世界各地石油和天然氣行業的生產探勘活動，影響了所研究市場中人工智慧技術的採用。

石油和天然氣領域的人工智慧市場趨勢

上游業務部門可望大幅成長

  • 上游業務是指石油和天然氣行業的探勘活動，包括進行地質調查、獲取土地權以及透過陸上和海上鑽探進行生產。在上游作業中，地質學家和探勘團隊在尋找新的石油蘊藏量和泉水地層時面臨挑戰。
  • 資料集在探勘等石油和天然氣作業中儲存人工智慧將變得更加容易。
  • 例如，石油天然氣公司埃克森美孚在石油探勘中使用人工智慧。透過人工智慧模型分析即時地震資料、歷史鑽井資料等諸多因素，精確探測海洋中的天然石油礦藏。
  • 世界各地的石油和燃氣公司都在尋求提高石油探勘的有效性和效率。人工智慧正在支援企業的營運活動。透過使用各種人工智慧工具對記錄進行數位化並自動分析地質資料和圖表，石油和燃氣公司可以識別潛在的問題，例如管道腐蝕或設備使用增加。
  • 華為建構了油氣探勘專用雲，利用人工智慧和巨量資料能力，重新分析了客戶過去10PB的探勘資料，從中挖掘出新的價值，支持開採決策。這為油田付加了巨大的價值，並改變了地震資料收集的操作模式。
  • 基於雲端基礎的資料分析的最新進展以及石油和天然氣營運中數位孿生的出現正在突破預測性維護技術的界限，使其成為監控資產完整性的寶貴工具。石油和天然氣行業的公司（包括 BP、埃克森美孚和殼牌）使用預測性維護來評估其操作設備的運作狀況並預測維護需求。
  • 根據歐佩克2024年4月公佈的資料，原油需求正在增加並呈現成長趨勢，顯示石油和天然氣產業的生產需求增加，這似乎將支撐預測期內的市場成長。
  • 石油和天然氣產業對環保生產過程的日益重視，透過航空攝影、衛星影像和遙感探測資料的分析，可以及早發現潛在的環境危害，以防止海上石油洩漏和管道損壞 增加人工智慧技術的應用來識別洩漏。這使得公司能夠減少對環境的影響並防止污染物的擴散。所有上述因素預計將推動所研究市場的成長。

北美佔最大市場佔有率

  • 北美是一個先進且高度發展的人工智慧市場。該地區經濟強勁、油田營運商和服務供應商廣泛採用人工智慧技術、頂級人工智慧軟體和系統供應商的強大影響力，以及政府和私人實體支援研發活動和共同投資的努力。人工智慧需求的因素。擴大石油和天然氣產能以及增加對該行業的投資預計將進一步增加市場機會。
  • 由於石油和天然氣行業範圍更廣以及人工智慧在該行業的應用日益廣泛，預計該地區的佔有率將由美國主導。根據美國能源資訊署的數據，過去六年來，美國的原油產量一直高於其他國家。 2023年，包括冷凝油的原油每日平均產量達到1,290萬桶，超過了2019年創下的美國和世界紀錄1,230萬桶。該國豐富的石油和天然氣供應降低了能源成本，支持私人投資，並有助於美國經濟的進一步成長。
  • 人工智慧考慮到不斷變化的能源生產格局，並在整個價值鏈中提供顯著的效益。我們協助石油和天然氣公司評估儲存價值，根據地質條件調整鑽井和完井策略，並評估與每口井相關的風險。由於其完善的基礎設施能夠為石油和天然氣行業提供尖端的解決方案，該地區預計將在一段時間內引領全球市場。新興企業人工智慧實施投資的增加預計將推動未來幾年的市場成長。
  • 人工智慧與石油和天然氣探勘的融合徹底改變了公司發現和開採碳氫化合物資源的方法，開創了一個高效和精確的新時代。因此，石油探勘活動的投資預計將增加，人工智慧在該行業的應用將加速。
  • 值得注意的是，埃克森美孚和西方石油等美國著名石油公司已投入數十億美元用於各種石油探勘活動，同時也透過大規模併購擴大石化燃料業務。
  • 2024 年 3 月，尖端人工智慧 (AI) 程式控制了納伯斯工業公司的遠端鑽機。 Corva LLC 開發的該程序利用衛星通訊完美地執行了鑽入岩層的瞬間決策。在此過程中，人工智慧程式預計將減少人類操作員發出的命令數量約 5,000 條，同時將鑽井速度提高至少 30%。這項創新技術背後的主要目標是降低成本並最大限度地從地表開採石油。美國公司在石油探勘活動中如此大量採用人工智慧技術預計將對市場成長產生積極影響。

人工智慧在石油和天然氣行業的概述

石油和天然氣的人工智慧市場高度分散，既有全球參與者，也有中小型公司。該市場的主要企業包括 IBM 公司、Fugenx Technologies、C3.AI Inc.、微軟公司和英特爾公司。市場上的主要企業正在採取聯盟和收購等策略來增強其產品供應並獲得永續的競爭優勢。

  • 2023年1月，人工智慧應用軟體公司C3 AI宣布推出C3 Generative AI產品套件，並發表了首款產品C3 Generative AI for Enterprise Search。 C3 AI 的預先建置人工智慧應用程式包含在 C3 生成式人工智慧產品套件中，其中包括先進的變壓器模型，客戶可以在整個價值鏈中輕鬆使用。 C3 Generative AI 將加速跨業務職能和產業（包括石油和天然氣產業）的轉型工作。
  • 2023 年 8 月，歐洲著名的獨立天然氣和石油公司 Wintershall Deer 宣布與 IBM Consulting 合作建立 AI 卓越中心，該公司正在轉型成為天然氣和碳管理領域的主要企業。此次合作旨在推動各種人工智慧使用案例，以提高能源生產。兩家公司都與微軟作為技術盟友有著密切的聯繫。

其他好處

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章簡介

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場洞察

  • 市場概況
  • 產業吸引力－波特五力分析
    • 新進入者的威脅
    • 買家/消費者的議價能力
    • 供應商的議價能力
    • 替代品的威脅
    • 競爭公司之間敵對關係的強度
  • 影響市場的宏觀經濟因素評估
  • 技術簡介 - 按下應用
    • 品管
    • 生產計畫
    • 預測性維護
    • 其他應用

第5章市場動態

  • 市場促進因素
    • 越來越重視輕鬆處理巨量資料
    • 降低生產成本的趨勢日益明顯
  • 市場限制因素
    • 初始實施成本高
    • 石油和天然氣行業缺乏熟練的專業人員
  • 主要使用案例

第6章 市場細分

  • 按操作
    • 上游
    • 中產階級
    • 下游
  • 按類型
    • 平台
    • 按服務
  • 按地區
    • 北美洲
    • 歐洲
    • 亞洲
    • 澳洲/紐西蘭
    • 拉丁美洲
    • 中東/非洲

第7章 競爭格局

  • 公司簡介
    • IBM Corporation
    • FuGenX Technologies
    • C3.AI Inc.
    • Microsoft Corporation
    • Intel Corporation
    • ABB Ltd
    • Honeywell International Inc.
    • Huawei Technologies Co. Ltd
    • NVIDIA Corporation
    • Infosys Limited
    • oPRO.ai Inc.

第8章投資分析

第9章 市場的未來

簡介目錄
Product Code: 64253

The AI In Oil And Gas Market size is estimated at USD 3.14 billion in 2024, and is expected to reach USD 5.70 billion by 2029, growing at a CAGR of 12.61% during the forecast period (2024-2029).

AI In Oil And Gas - Market

The increasing application of AI in reservoir analysis, drilling optimization, anomaly detection in pipelines, safety monitoring, emissions reduction, revolutionizing exploration, production, and environmental sustainability in the oil and gas industries is expected to fuel the growth of the market.

Key Highlights

  • The emergence of predictive maintenance powered by artificial intelligence in the oil and gas market is transforming companies in the sector's asset management. This ensures better reliability and reduces operational risks, which is expected to drive the growth of the market in the future.
  • For instance, in October 2023, C3 AI, the Enterprise AI application software company, announced that the C3 AI reliability application would include predictive maintenance software developed by Shell. This would strengthen the use of C3AI's AI ecosystem to maintain the oil company's critical equipment. This shows the increasing adoption of AI platforms in the oil and gas sector, supporting market growth.
  • AI technologies present the potential for increased efficiency in oil and gas operations to find patterns, streamline workflows, automate decision-making, and examine enormous amounts of data from sensors, machinery, and industrial processes. Predictive maintenance solutions, equipped with artificial intelligence (AI), can forecast equipment breakdowns beforehand, allowing oil & gas businesses to plan maintenance tasks in advance, save downtime, and maximize asset usage.
  • The global AI in the oil and gas market is driven largely by the growing trend of lower production costs. In the face of fluctuating oil prices and shifting market dynamics, oil and gas businesses increasingly seek artificial intelligence (AI) technologies to optimize operations, streamline procedures, and alleviate costs.
  • AI adoption is accelerating across industries, including the oil & gas sector, as it processes massive datasets across the value chain. AI can extract more value from data through machine learning that uncovers hidden insights. Optimizing complex operations enables oil & gas companies to reduce costs and enhance productivity.
  • The International Energy Agency (IEA) reported that after Russia invaded Ukraine, Russia cut 80 billion cubic meters (BCM) of pipeline gas supplies to Europe, which caused an energy crisis in the region. This impacted the operations of midstream and downstream companies in the oil and gas industry, restricting market growth.
  • The European Union's objective to become self-sufficient in energy production with the emergence of renewable source-based energy initiatives can potentially hinder the growth of the oil and gas industry in the European region. This indirectly impacts market growth by limiting the implementation scope of AI solutions and services in the oil and gas industry.
  • The COVID-19 pandemic led to a global shutdown and decreased economic activity worldwide, restricting the demand for oil used for industrial activity, travel, and other applications. The international crude oil price also fell during the COVID-19 pandemic, reducing production exploration activities in the oil and gas industries worldwide and impacting AI technology adoption in the market studied.

AI in Oil and Gas Market Trends

Upstream Operations Segment Expected to Witness Significant Growth

  • Upstream operations refer to the oil and gas industry's exploration activities, which include conducting geological surveys, obtaining land rights, and producing with onshore and offshore drilling. In upstream operations, businesses face challenges when geologists and exploration teams search for new oil reserves and seeps.
  • The adoption of AI in oil and gas operations, such as oil exploration, becomes easy as advanced AI algorithms can analyze larger datasets of seismic surveys, geological formations, historical well logs, and satellite imagery to pinpoint potential oil reservoirs on the land and ocean accurately.
  • For instance, the oil and gas company ExxonMobil is leveraging AI for oil exploration. It uses AI models to analyze real-time seismic data, historical drilling data, and many other factors to accurately detect natural oil seeps in the ocean.
  • Global oil and gas corporations are trying to enhance the effectiveness and efficiency of their oil exploration procedures. AI helps companies with their operations activity. Using different AI tools to digitize records and automate the analysis of geological data and charts, oil and gas companies can identify possible problems like corrosion in pipelines or increased equipment usage.
  • Huawei built a dedicated oil and gas exploration cloud and used AI and Big Data capabilities to re-analyze 10 PB of the customer's historical exploration data, mine new value from it, and support extraction decision-making. This brought substantial additional value to the oilfield and switched the seismic data collection operation modes.
  • Recent advancements in cloud-based data analytics and the advent of digital twins in oil and gas operations have been expanding the boundaries of predictive maintenance technologies, making them a valuable tool for monitoring asset integrity. Companies in the oil and gas industry, including BP, ExxonMobil, and Shell, have been using predictive maintenance to evaluate the condition of their operational equipment and predict maintenance requirements.
  • According to data published by OPEC in April 2024, the demand for crude oil has been increasing and following a growth trend, showing the increasing production demand in the oil and gas industries, which would support the market's growth during the forecast period.
  • The increasing priority on the environment-friendly production process in the oil and gas industry would increase the application of AI technology in the early detection of potential environmental hazards through analyzing aerial photos, satellite imagery, and remote sensing data to identify the oil spills in offshore locations and leakages in pipelines. This enables companies to mitigate the environmental impact and prevent the spread of pollutants. All the above-mentioned factors are expected to drive the growth of the market studied.

North America Holds Largest Market Share

  • North America stands as a leading and highly developed market for AI. The region's strong economy, widespread adoption of AI technologies among oilfield operators and service providers, the significant presence of top AI software and system suppliers, as well as the joint investments made by government and private entities to support research and development activities are all factors that will fuel the demand for AI in the oil and gas sector. The expanding oil and gas production capacities and rising investments in the industry are expected to further enhance market opportunities.
  • The region's share is expected to be dominated by the United States due to its extensive oil and gas sector and the increasing adoption of AI within the sector. As per the US EIA, the United States has consistently produced more crude oil than any other nation for the past six years. In 2023, the average daily crude oil production, including condensate, reached 12.9 million barrels, surpassing the previous United States and global record of 12.3 million barrels set in 2019. The country's abundant oil and gas supply has led to lower energy costs, supporting private-sector investments and contributing to further economic growth in the United States.
  • AI offers significant advantages throughout the entire value chain, considering the ever-changing energy production landscape. It assists oil and gas companies in evaluating the worth of reservoirs, tailoring drilling and completion strategies based on geological conditions, and evaluating risks associated with each well. This region is expected to lead the global market in the foreseeable future due to its well-established infrastructure, which can provide cutting-edge solutions to the oil and gas industry. The growing influx of investments in AI implementation for startups is expected to bolster market growth in the coming years.
  • The integration of AI into oil and gas exploration has brought about a fresh era of effectiveness and precision, revolutionizing the methods employed by companies to locate and uncover hydrocarbon resources. Consequently, the growing investments in oil exploration activities are anticipated to bolster the utilization of AI in this industry.
  • Notably, prominent US-based oil companies such as Exxon Mobil and Occidental Petroleum allocate billions of dollars for diverse oil exploration endeavors while directing substantial funds into their fossil fuel enterprises through significant mergers and acquisitions.
  • In March 2024, a cutting-edge Artificial Intelligence (AI) program assumed control of the remote Nabors Industries Ltd rig. Utilizing satellite communication, this program, developed by Corva LLC, flawlessly executed split-second decisions to drill through the rock formations. By doing so, it is estimated that the AI program will reduce the number of commands issued by the human operator by approximately 5,000 while also enhancing drilling speed by a minimum of 30%. The primary goal behind this innovative technology is to reduce expenses and maximize oil extraction from the earth's surface. Such significant adoption of AI technology in oil exploration activities by US companies is expected to positively influence market growth.

AI in Oil and Gas Industry Overview

The AI in oil and gas market is extremely fragmented due to the presence of both global players and small and medium-sized enterprises. Some of the major players in the market are IBM Corporation, Fugenx Technologies, C3.AI Inc., Microsoft Corporation, and Intel Corporation. Key players in the market are adopting strategies such as partnerships and acquisitions to enhance their product offerings and gain sustainable competitive advantage.

  • In January 2023, C3 AI, an AI application software company, launched the C3 Generative AI Product Suite, which was the release of its initial product, C3 Generative AI for Enterprise Search. C3 AI's pre-built AI applications in the C3 Generative AI Product Suite include advanced transformer models, making it easier for customers to use them throughout their value chains. Transformation efforts across business functions and industries, including the oil and gas sector, would be accelerated by C3 Generative AI.
  • In August 2023, Wintershall Dea, a prominent independent natural gas and oil company in Europe that is transitioning into a key player in gas and carbon management, announced its collaboration with IBM Consulting to form an AI Center of Competence (CoC). This partnership aims to advance various AI use cases that enhance energy production. Both companies have solid ties with Microsoft as a technology ally.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Threat of New Entrants
    • 4.2.2 Bargaining Power of Buyers/Consumers
    • 4.2.3 Bargaining Power of Suppliers
    • 4.2.4 Threat of Substitute Products
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Assessment of Macroeconomic Factors on the Market
  • 4.4 Technology Snapshot - By Application
    • 4.4.1 Quality Control
    • 4.4.2 Production Planning
    • 4.4.3 Predictive Maintenance
    • 4.4.4 Other Applications

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Increasing Focus to Easily Process Big Data
    • 5.1.2 Rising Trend to Reduce Production Cost
  • 5.2 Market Restraints
    • 5.2.1 Initial High Cost of Adoption
    • 5.2.2 Lack of Skilled Professionals in the Oil and Gas Industry
  • 5.3 Key Use Cases

6 MARKET SEGMENTATION

  • 6.1 By Operation
    • 6.1.1 Upstream
    • 6.1.2 Midstream
    • 6.1.3 Downstream
  • 6.2 By Type
    • 6.2.1 Platform
    • 6.2.2 Services
  • 6.3 By Geography***
    • 6.3.1 North America
    • 6.3.2 Europe
    • 6.3.3 Asia
    • 6.3.4 Australia and New Zealand
    • 6.3.5 Latin America
    • 6.3.6 Middle East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles*
    • 7.1.1 IBM Corporation
    • 7.1.2 FuGenX Technologies
    • 7.1.3 C3.AI Inc.
    • 7.1.4 Microsoft Corporation
    • 7.1.5 Intel Corporation
    • 7.1.6 ABB Ltd
    • 7.1.7 Honeywell International Inc.
    • 7.1.8 Huawei Technologies Co. Ltd
    • 7.1.9 NVIDIA Corporation
    • 7.1.10 Infosys Limited
    • 7.1.11 oPRO.ai Inc.

8 INVESTMENT ANALYSIS

9 FUTURE OF THE MARKET