|
시장보고서
상품코드
1812186
석유 및 가스 데이터 수익화 시장 : 세계 산업 규모, 점유율, 동향, 기회, 예측 - 방법별, 전개 방식별, 용도별, 지역별, 경쟁별(2020-2030년)Oil And Gas Data Monetization Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Method, By Deployment Mode, By Application, By Region & Competition, 2020-2030F |
||||||
세계의 석유 및 가스 데이터 수익화 시장 규모는 2024년에 346억 1,000만 달러로 평가되었으며, 예측 기간 동안 CAGR 12.18%로 2030년까지 696억 달러에 달할 것으로 예측됩니다.
| 시장 개요 | |
|---|---|
| 예측 기간 | 2026-2030년 |
| 시장 규모 : 2024년 | 346억 1,000만 달러 |
| 시장 규모 : 2030년 | 696억 달러 |
| CAGR : 2025-2030년 | 12.18% |
| 급성장 부문 | 간접적 데이터 수익화 |
| 최대 시장 | 북미 |
세계 석유 및 가스 데이터 수익화 시장은 에너지 산업의 광범위한 디지털 전환에서 매우 중요한 분야로 부상하고 있습니다. 석유 및 가스 부문은 탐사, 시추, 생산, 정제, 유통 업무를 통해 대량의 정형 및 비정형 데이터를 생성하고 있습니다. 그동안 이러한 데이터는 충분히 활용되지 못하고 업무 보고용으로만 사용되어 왔습니다. 그러나 고급 분석, 인공지능(AI), 빅데이터 플랫폼, 클라우드 컴퓨팅의 급속한 보급과 함께 업계는 현재 데이터 수익화로 전환하고 있습니다. 즉, 제3자 판매 및 라이선싱을 통해 직접적으로 정보를 활용하거나, 업무 최적화, 의사결정 강화, 다운타임 감소, 새로운 수익원 창출에 활용함으로써 간접적으로 정보를 활용합니다. 이 두 가지 접근 방식은 특히 기업들이 가격 변동, 환경적 압력, 효율성의 필요성과 같은 과제에 대응하기 위해 노력하는 가운데 시장의 큰 성장을 촉진하고 있습니다.
센서, 디지털 인프라, 실시간 데이터 수집의 대중화
고급 분석, AI, 디지털 트윈, 예측 기능, 예측 기능
데이터 보안과 사이버 보안 리스크
인공지능과 머신러닝 도입 확대
The Global Oil And Gas Data Monetization Market was valued at USD 34.61 Billion in 2024 and is expected to reach USD 69.60 Billion by 2030 with a CAGR of 12.18% during the forecast period.
| Market Overview | |
|---|---|
| Forecast Period | 2026-2030 |
| Market Size 2024 | USD 34.61 Billion |
| Market Size 2030 | USD 69.60 Billion |
| CAGR 2025-2030 | 12.18% |
| Fastest Growing Segment | Indirect Data Monetization |
| Largest Market | North America |
The global Oil and Gas Data Monetization Market is emerging as a pivotal segment within the broader digital transformation of the energy industry, as companies increasingly recognize the untapped potential of data as a strategic asset. The oil and gas sector generates massive volumes of structured and unstructured data through exploration, drilling, production, refining, and distribution operations. Historically, much of this data remained underutilized, serving only operational reporting purposes. However, with the rapid adoption of advanced analytics, artificial intelligence (AI), big data platforms, and cloud computing, the industry is now shifting toward data monetization-leveraging information either directly by selling or licensing it to third parties, or indirectly by utilizing it to optimize operations, enhance decision-making, reduce downtime, and create new revenue streams. This dual approach is fueling significant growth in the market, especially as organizations seek to counter challenges of price volatility, environmental pressures, and the need for efficiency gains.
Key Market Drivers
Proliferation of Sensors, Digital Infrastructure, and Real-Time Data Capture
The growing adoption of IoT sensors and real-time monitoring systems is a primary driver of oil and gas data monetization. Across the sector, more than 1.3 million sensors are currently deployed to track pressure, flow, and temperature in exploration and production assets. These sensors generate over 9.7 billion gigabytes of data annually, creating a vast pool of information that can be transformed into actionable insights and monetized services. Offshore rigs, numbering more than 14,000 globally, now transmit telemetry data via satellite or fiber to centralized data lakes, enabling continuous visibility into operations. Edge computing is also expanding, with more than 11,500 upstream sites processing data locally to reduce dependence on high-bandwidth transmission. Companies using real-time processing platforms report up to 37% improvements in operational efficiency, proving the tangible benefits of data-driven operations. This proliferation of digital infrastructure establishes the foundation for monetizing data by enhancing internal efficiency while simultaneously creating opportunities to commercialize operational insights and services to external stakeholders.
Advanced Analytics, AI, Digital Twins, and Predictive Capabilities
The rapid adoption of advanced analytics, AI, and machine learning is unlocking unprecedented opportunities for data monetization. In 2024 alone, more than 240 million labeled well-log and seismic datasets were used to train AI models that significantly improved drilling precision and reservoir understanding. Digital twin technology, now applied to over 37 major pipeline and refinery projects, integrates up to 150 million data points, helping operators cut inspection times by 29% and maintenance costs by 21%. Predictive maintenance powered by analytics has reduced unplanned downtime by 25% and trimmed overall maintenance expenditure by 15% for several operators. Real-time monitoring and forecasting models are achieving up to 93% accuracy in predicting pipeline flows and midstream logistics bottlenecks. Additionally, reservoir simulation platforms supported by AI have improved recovery rates by 5-7%, directly increasing the economic value of reserves. These advancements illustrate how analytics and AI convert massive raw data pools into monetizable insights, cost savings, and improved production outcomes.
Key Market Challenges
Data Security and Cybersecurity Risks
One of the most pressing challenges in the oil and gas data monetization market is data security. Oil and gas companies handle vast amounts of sensitive geological, production, and financial data, making them prime targets for cyberattacks. The increasing integration of IoT devices, cloud platforms, and cross-industry data exchanges exposes multiple vulnerabilities. In recent years, high-profile cyber incidents have highlighted the scale of risk, with ransomware attacks on pipeline networks and refineries disrupting operations for days. The growing adoption of real-time monitoring systems and digital twins adds more entry points for hackers, and a single breach can compromise millions of gigabytes of valuable exploration and production data. Moreover, compliance requirements around data privacy and security-such as GDPR and regional data sovereignty laws-place an additional burden on firms seeking to monetize their data. Companies must also deal with insider threats, as employees and contractors with access to critical data may misuse it. Ensuring robust encryption, secure APIs, and end-to-end monitoring requires significant investment, but many operators still lag in cybersecurity maturity. The financial and reputational risks of a data breach are enormous, as compromised data can lead to regulatory fines, contract cancellations, and loss of investor confidence. This security dilemma slows the pace of data monetization, as companies often hesitate to fully embrace external data sharing or licensing models out of fear that sensitive information could fall into the wrong hands. Thus, unless cybersecurity strategies evolve in parallel with monetization initiatives, the full potential of this market cannot be realized.
Key Market Trends
Growing Adoption of Artificial Intelligence and Machine Learning
Artificial intelligence and machine learning are reshaping data monetization strategies by enabling more accurate predictions, deeper insights, and automated decision-making. In drilling operations, AI models trained on millions of seismic and well-log datasets are achieving unprecedented accuracy in reservoir mapping and production forecasting. Machine learning is also driving predictive maintenance, helping operators anticipate equipment failures before they occur, thereby reducing downtime and maintenance costs. In the midstream sector, AI is optimizing pipeline monitoring and logistics, improving flow efficiency and preventing leaks. Downstream operators are using AI for refining optimization, pricing models, and demand forecasting, which enhance profitability. The monetization opportunity arises when companies not only use AI to improve their operations but also package AI-driven insights as commercial services for partners and third parties. Additionally, AI is being embedded into digital twin models, allowing companies to simulate and optimize operations in real time with data flowing from thousands of sensors. These capabilities reduce costs, improve safety, and enable companies to create new offerings such as predictive data services for external clients. The adoption of AI and machine learning is no longer experimental but central to monetization strategies, as companies increasingly recognize data as a strategic revenue-generating asset rather than a byproduct of operations.
In this report, the Global Oil And Gas Data Monetization Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Oil And Gas Data Monetization Market.
Global Oil And Gas Data Monetization Market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report: