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市場調查報告書
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1702401

全球石油和天然氣市場的數位孿生—2025-2032

Global Digital Twins in the Oil and Gas Market - 2025-2032
出版日期: | 出版商: DataM Intelligence | 英文 180 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

2024 年全球石油和天然氣市場的數位孿生規模達到 12 億美元，預計到 2032 年將達到 28.1 億美元，在 2025-2032 年預測期內的複合年成長率為 11.20%。

受物聯網、人工智慧和巨量資料分析在預測性維護和營運效率方面的日益普及的推動，石油和天然氣行業的全球數位孿生市場正在經歷快速成長。數位孿生技術可以實現資產的即時監控、類比和最佳化，減少停機時間和營運風險。由於數位轉型投資不斷增加，尤其是上游和中游業務的投資，市場正在擴大。

全球石油和天然氣市場的數位孿生趨勢

石油和天然氣市場數位孿生技術的主要趨勢包括生產最佳化、預測性維護、營運安全、即時資料整合、遠端操作和虛擬測試、永續性以及國家石油公司和國際石油公司的日益普及。例如，2024年8月，巴西石油公司成功測試了由巴西公司ESSS開發的數位孿生原型。該技術旨在透過提高監控和模擬能力，將海上產量提高約 1%。

動力學

對營運效率和降低成本的需求不斷增加

對營運效率和降低成本的不斷成長的需求是石油和天然氣行業採用數位孿生的主要驅動力。數位孿生可以實現即時監控、預測性維護和資產最佳化，減少非計劃性停機時間並延長設備使用壽命。透過模擬不同的營運場景，公司可以最大限度地降低風險，最佳化資源配置，提高整體生產力。

該公司正在推進數位孿生技術，以提高生產效率、減少停機時間並降低營運成本。例如，2023 年 6 月，霍尼韋爾推出了 Digital Prime，這是一款基於雲端的數位孿生解決方案，旨在追蹤、管理和測試流程控制變更和系統修改。 Digital Prime 提供了一個經濟高效的平台，用於頻繁測試，以減少被動維護並改善專案執行，而不會中斷生產系統。

實施成本高

高昂的實施成本是石油和天然氣產業採用數位孿生技術的重要限制因素。建立數位孿生系統的初始投資涉及昂貴的硬體，例如感測器、物聯網設備和人工智慧驅動的平台。此外，將數位孿生與現有的遺留系統結合需要技術資源和財務投資。先進模擬工具的軟體和授權費用進一步增加了成本，而需要熟練的勞動力來操作和維護這些系統又增加了財務負擔。

包括即時資料處理和雲端運算在內的基礎設施成本也會增加整體費用。公司在確定明確的投資報酬率 (ROI) 時經常面臨挑戰，因為收益需要時間才能實現，因此很難證明前期成本的合理性。預算限制，尤其是小公司的預算限制，進一步限制了他們投資數位孿生技術的能力。

目錄

第1章：方法論和範圍

第 2 章：定義與概述

第3章：執行摘要

第4章：動態

  • 影響因素
    • 驅動程式
      • 對營運效率和降低成本的需求不斷增加
    • 限制
      • 實施成本高
    • 機會
    • 影響分析

第5章：產業分析

  • 波特五力分析
  • 供應鏈分析
  • 定價分析
  • 監理與合規分析
  • 永續性分析
  • 技術進步分析
  • DMI 意見

第6章：奉獻

  • 產品數位孿生
  • 流程數位孿生
  • 系統數位孿生

第7章：依類型

  • 描述性雙胞胎
  • 資訊雙胞胎
  • 預測雙胞胎
  • 綜合雙床房
  • 自主雙胞胎

第 8 章：按部署模式

  • 雲
  • 本地

第9章：按操作

  • 上游
  • 中游
  • 下游

第 10 章：按應用

  • 探勘與生產
  • 鑽井作業
  • 水庫管理
  • 管道管理
  • 煉油業務
  • 資產績效管理
  • 其他

第 11 章：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 義大利
    • 西班牙
    • 歐洲其他地區
  • 南美洲
    • 巴西
    • 阿根廷
    • 南美洲其他地區
  • 亞太
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 亞太其他地區
  • 中東和非洲

第12章：公司簡介

  • AVEVA Group Limited
    • 公司概況
    • 產品組合和描述
    • 財務概覽
    • 關鍵進展
  • Emerson Electric Co
  • Halliburton
  • Honeywell International Inc.
  • IBM
  • SLB
  • Microsoft Corporation
  • General Electric
  • Schneider Electric
  • Siemens Energy

第 13 章：附錄

簡介目錄
Product Code: PAC2305

Global digital twins in the oil and gas market reached US$ 1.2 billion in 2024 and are expected to reach US$ 2.81 billion by 2032, growing with a CAGR of 11.20% during the forecast period 2025-2032.

The global digital twins market in the oil and gas industry is experiencing rapid growth, driven by the increasing adoption of IoT, AI, and big data analytics for predictive maintenance and operational efficiency. Digital twin technology enables real-time monitoring, simulation, and optimization of assets, reducing downtime and operational risks. The market is expanding due to rising investments in digital transformation, particularly in upstream and midstream operations.

Global Digital Twins in the Oil and Gas Market Trend

The key trends in digital twin technology for the oil & gas market include production optimization, predictive maintenance, operational safety, real-time data integration, remote operations & virtual testing, sustainability, and increased adoption by NOCs & IOCs. For instance, in August 2024, Petrobras successfully tested a digital twin prototype developed by ESSS, a Brazilian company. This technology aims to enhance offshore production by approximately 1% through improved monitoring and simulation capabilities.

Dynamics

Increasing Demand for Operational Efficiency and Cost Reduction

The increasing demand for operational efficiency and cost reduction is a major driver of digital twin adoption in the oil and gas industry. Digital twins enable real-time monitoring, predictive maintenance, and asset optimization, reducing unplanned downtime and improving equipment lifespan. By simulating different operational scenarios, companies can minimize risks, optimize resource allocation, and enhance overall productivity.

Companies are advancing digital twin technologies to enhance production efficiency, reduce downtime, and lower operational costs. For instance, in June 2023, Honeywell launched Digital Prime, a cloud-based digital twin solution designed to track, manage, and test process control changes and system modifications. Digital Prime offers a cost-effective platform for frequent testing to reduce reactive maintenance and improve project execution without disrupting production systems.

High Implementation Costs

High implementation costs are a significant restraint for the adoption of digital twins in the oil and gas industry. The initial investment for setting up digital twin systems involves expensive hardware, such as sensors, IoT devices, and AI-driven platforms. Additionally, integrating digital twins with existing legacy systems requires technical resources and financial investment. The software and licensing fees for advanced simulation tools further add to the costs, while the need for a skilled workforce to operate and maintain these systems adds a financial burden.

Infrastructure costs, including real-time data processing and cloud computing, also contribute to the overall expenses. Companies often face challenges in determining a clear return on investment (ROI), with the benefits taking time to materialize, making it difficult to justify the upfront costs. Budget constraints, particularly among smaller firms, further limit their ability to invest in digital twin technology.

Segment Analysis

The global digital twins in the oil and gas market are segmented based on offering, type, deployment mode, operation, application and region.

Upstream Segment Dominates Digital Twin Market in Oil & Gas Due to Advanced Exploration, Drilling, and Production Optimization

In the global digital twins market for oil and gas, the upstream segment holds a significant share due to its reliance on advanced technologies for exploration, drilling, and production optimization. Digital twins enable real-time reservoir modeling, well performance analysis, and predictive maintenance, reducing operational risks and downtime.

In November 2024, Venture Builder VC launched the NOV Supernova Accelerator, a five-month program to drive digital transformation in upstream oil and gas. The program provides startups with direct access to NOV's R&D teams and business units, enabling them to test solutions and build long-term partnerships. This initiative fosters innovation and collaboration to address critical industry challenges.

Geographical Penetration

High Technology Adoption and Strong Presence of Key Industry Players in North America

North America holds a significant share in the global digital twins market for oil and gas due to its strong technological infrastructure and early adoption of digital innovations. The region is home to major oil and gas companies investing in AI, IoT, and cloud-based digital twin solutions to enhance operational efficiency. The presence of advanced shale gas exploration, deepwater drilling, and strict regulatory requirements further drive demand for predictive maintenance and asset optimization.

According to IEA, in 2023, the US directed approximately US$ 200 billion toward oil and gas investments, accounting for about 19% of the global total. This accelerates the adoption of digital twins by driving technological advancements and operational efficiencies. With increased capital, companies are leveraging digital twins to optimize exploration, drilling, and production processes, reducing downtime and improving asset performance.

Technological Advancement Analysis

Twin technology in the oil and gas market has advanced significantly, leveraging digital twins to enhance operational efficiency, predictive maintenance, and real-time monitoring. By integrating AI, IoT, and big data analytics, companies can simulate drilling conditions, optimize production, and reduce downtime. Digital twins improve asset management by enabling remote inspections and predictive failure analysis, minimizing risks and costs.

The adoption of cloud-based twin solutions facilitates seamless data exchange between offshore and onshore operations, improving decision-making. For instance, BP has been implementing its APEX digital twin system across global operations, including the North Sea and the Gulf of Mexico. This system enables engineers to simulate production systems, optimize operations, and predict future scenarios, leading to increased efficiency and output.

Competitive Landscape

The major global players in the market include AVEVA Group Limited, Emerson Electric Co, Halliburton, Honeywell International Inc., IBM, SLB, Microsoft Corporation, General Electric, Schneider Electric, Siemens Energy and others.

Key Developments

  • The upcoming Oil & Gas Digital Twin Conference and Exhibition is scheduled for May 14-15, 2025, in Houston, Texas. This event will explore the digital twin ecosystem and its role in achieving a net-zero future.
  • In July 2020, Doris Group, AVEVA, and Schneider Electric formed a Digital Twin Alliance to address complex digital transformation challenges in the upstream oil and gas sector. This collaboration focuses on integrating digital twin technologies to enhance asset performance and operational efficiency.

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Target Audience 2024

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Offering
  • 3.2. Snippet by Type
  • 3.3. Snippet by Deployment Mode
  • 3.4. Snippet by Operation
  • 3.5. Snippet by Application
  • 3.6. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Increasing Demand for Operational Efficiency and Cost Reduction
    • 4.1.2. Restraints
      • 4.1.2.1. High Implementation Costs
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory and Compliance Analysis
  • 5.5. Sustainability Analysis
  • 5.6. Technological Advancement Analysis
  • 5.7. DMI Opinion

6. By Offering

  • 6.1. Introduction
    • 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 6.1.2. Market Attractiveness Index, By Offering
  • 6.2. Product digital twin*
    • 6.2.1. Introduction
    • 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 6.3. Process digital twin
  • 6.4. System digital twin

7. By Type

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 7.1.2. Market Attractiveness Index, By Type
  • 7.2. Descriptive Twin*
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. Informative Twin
  • 7.4. Predictive Twin
  • 7.5. Comprehensive Twin
  • 7.6. Autonomous Twin

8. By Deployment Mode

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 8.1.2. Market Attractiveness Index, By Deployment Mode
  • 8.2. Cloud*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. On-premises

9. By Operation

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Operation
    • 9.1.2. Market Attractiveness Index, By Operation
  • 9.2. Upstream*
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Midstream
  • 9.4. Downstream

10. By Application

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 10.1.2. Market Attractiveness Index, By Application
  • 10.2. Exploration & Production*
    • 10.2.1. Introduction
    • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 10.3. Drilling Operations
  • 10.4. Reservoir Management
  • 10.5. Pipeline Management
  • 10.6. Refining Operations
  • 10.7. Asset Performance Management
  • 10.8. Others

11. By Region

  • 11.1. Introduction
    • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 11.1.2. Market Attractiveness Index, By Region
  • 11.2. North America
    • 11.2.1. Introduction
    • 11.2.2. Key Region-Specific Dynamics
    • 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Operation
    • 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.2.8.1. US
      • 11.2.8.2. Canada
      • 11.2.8.3. Mexico
  • 11.3. Europe
    • 11.3.1. Introduction
    • 11.3.2. Key Region-Specific Dynamics
    • 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Operation
    • 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.3.8.1. Germany
      • 11.3.8.2. UK
      • 11.3.8.3. France
      • 11.3.8.4. Italy
      • 11.3.8.5. Spain
      • 11.3.8.6. Rest of Europe
  • 11.4. South America
    • 11.4.1. Introduction
    • 11.4.2. Key Region-Specific Dynamics
    • 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Operation
    • 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.4.8.1. Brazil
      • 11.4.8.2. Argentina
      • 11.4.8.3. Rest of South America
  • 11.5. Asia-Pacific
    • 11.5.1. Introduction
    • 11.5.2. Key Region-Specific Dynamics
    • 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Operation
    • 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.5.8.1. China
      • 11.5.8.2. India
      • 11.5.8.3. Japan
      • 11.5.8.4. Australia
      • 11.5.8.5. Rest of Asia-Pacific
  • 11.6. Middle East and Africa
    • 11.6.1. Introduction
    • 11.6.2. Key Region-Specific Dynamics
    • 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
    • 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Operation
    • 11.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application

12. Company Profiles

  • 12.1. AVEVA Group Limited*
    • 12.1.1. Company Overview
    • 12.1.2. Product Portfolio and Description
    • 12.1.3. Financial Overview
    • 12.1.4. Key Developments
  • 12.2. Emerson Electric Co
  • 12.3. Halliburton
  • 12.4. Honeywell International Inc.
  • 12.5. IBM
  • 12.6. SLB
  • 12.7. Microsoft Corporation
  • 12.8. General Electric
  • 12.9. Schneider Electric
  • 12.10. Siemens Energy

LIST NOT EXHAUSTIVE

13. Appendix

  • 13.1. About Us and Services
  • 13.2. Contact Us