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市场调查报告书
商品编码
1702401

全球石油和天然气市场的数位孪生—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个工作天内

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简介目录

2024 年全球石油和天然气市场的数位孪生规模达到 12 亿美元，预计到 2032 年将达到 28.1 亿美元，在 2025-2032 年预测期内的复合年增长率为 11.20%。

受物联网、人工智慧和巨量资料分析在预测性维护和营运效率方面的日益普及的推动，石油和天然气行业的全球数位孪生市场正在经历快速增长。数位孪生技术可以实现资产的即时监控、类比和最佳化，减少停机时间和营运风险。由于数位转型投资不断增加，尤其是上游和中游业务的投资，市场正在扩大。

全球石油和天然气市场的数位孪生趋势

石油和天然气市场数位孪生技术的主要趋势包括生产优化、预测性维护、营运安全、即时资料整合、远端操作和虚拟测试、永续性以及国家石油公司和国际石油公司的日益普及。例如，2024年8月，巴西石油公司成功测试了由巴西公司ESSS开发的数位孪生原型。该技术旨在透过提高监控和模拟能力，将海上产量提高约 1%。

动力学

对营运效率和降低成本的需求不断增加

对营运效率和降低成本的不断增长的需求是石油和天然气行业采用数位孪生的主要驱动力。数位孪生可以实现即时监控、预测性维护和资产优化，减少非计划性停机时间并延长设备使用寿命。透过模拟不同的营运场景，公司可以最大限度地降低风险，优化资源配置，提高整体生产力。

该公司正在推进数位孪生技术，以提高生产效率、减少停机时间并降低营运成本。例如，2023 年 6 月，霍尼韦尔推出了 Digital Prime，这是一款基于云端的数位孪生解决方案，旨在追踪、管理和测试流程控制变更和系统修改。 Digital Prime 提供了一个经济高效的平台，用于频繁测试，以减少被动维护并改善专案执行，而不会中断生产系统。

实施成本高

高昂的实施成本是石油和天然气产业采用数位孪生技术的重要限制因素。建立数位孪生系统的初始投资涉及昂贵的硬件，例如感测器、物联网设备和人工智慧驱动的平台。此外，将数位孪生与现有的遗留系统结合需要技术资源和财务投资。先进模拟工具的软体和授权费用进一步增加了成本，而需要熟练的劳动力来操作和维护这些系统又增加了财务负担。

包括即时资料处理和云端运算在内的基础设施成本也会增加整体费用。公司在确定明确的投资报酬率 (ROI) 时经常面临挑战，因为收益需要时间才能实现，因此很难证明前期成本的合理性。预算限制，尤其是小公司的预算限制，进一步限制了他们投资数位孪生技术的能力。

目录

第一章：方法论和范围

第 2 章：定义与概述

第三章：执行摘要

第四章：动态

  • 影响因素
    • 驱动程式
      • 对营运效率和降低成本的需求不断增加
    • 限制
      • 实施成本高
    • 机会
    • 影响分析

第五章：产业分析

  • 波特五力分析
  • 供应链分析
  • 定价分析
  • 监理与合规分析
  • 可持续性分析
  • 技术进步分析
  • DMI 意见

第六章：奉献

  • 产品数位孪生
  • 流程数位孪生
  • 系统数位孪生

第七章：依类型

  • 描述性双胞胎
  • 资讯双胞胎
  • 预测双胞胎
  • 综合双床房
  • 自主双胞胎

第 8 章：按部署模式

  • 云
  • 本地

第九章：按操作

  • 上游
  • 中游
  • 下游

第 10 章：按应用

  • 勘探与生产
  • 钻井作业
  • 水库管理
  • 管道管理
  • 炼油业务
  • 资产绩效管理
  • 其他的

第 11 章：按地区

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 义大利
    • 西班牙
    • 欧洲其他地区
  • 南美洲
    • 巴西
    • 阿根廷
    • 南美洲其他地区
  • 亚太
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 亚太其他地区
  • 中东和非洲

第十二章：公司简介

  • AVEVA Group Limited
    • 公司概况
    • 产品组合和描述
    • 财务概览
    • 关键进展
  • Emerson Electric Co
  • Halliburton
  • Honeywell International Inc.
  • IBM
  • SLB
  • Microsoft Corporation
  • General Electric
  • Schneider Electric
  • Siemens Energy

第 13 章：附录

简介目录
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.

Why Choose DataM?

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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