(Source:Shanghai Securities News·China Securities Network2025-09-09）

On September 8, the National Development and Reform Commission and the National Energy Administration issued the "Implementation Opinions on Promoting the High-Quality Development of "Artificial Intelligence +" Energy" (hereinafter referred to as the "Implementation Opinions"). The "Implementation Opinions" propose that it is necessary to promote the in-depth application of more than five professional large-scale models in power grid, power generation, coal, oil and gas and other industries.Dong Xiucheng, Executive Dean of the China International Carbon Neutral Economic Research Institute at the w88 casino, Deputy Supervisor of the China Petroleum Distribution Association and Dean of the Carbon Neutral Research InstituteIn an interview with a reporter from Shanghai Securities News, he said that large oil and gas companies should work closely with artificial intelligence companies to break through key core technologies, independently develop algorithms suitable for the characteristics of the oil and gas industry, and customize and optimize industry-specific scenarios.

atDong XiuchengIt seems that the application potential of artificial intelligence technology in the oil and gas industry is mainly concentrated in three core areas, and is expected to bring revolutionary changes to the development of the industry:

First, improve the accuracy of oil and gas exploration and development. Artificial intelligence can integrate and analyze massive geological and other data for seismic data processing, well logging interpretation and oil and gas layer identification, improve the accuracy of reservoir identification and optimize development plans; it can also realize intelligent drilling parameter control and risk prediction based on geological and well site data.

Second, promote the efficiency of oil and gas production operations. Artificial intelligence can process and analyze Internet of Things data in real time, identify working conditions, predict production capacity and regulate solutions; combined with computer vision and other technologies, it can allow robots and drones to perform tasks in dangerous environments; based on cloud computing power, it can realize the automation of production operations and promote unmanned equipment and facilities.

Third, realize intelligent upgrade of management decision-making. Applying artificial intelligence technology to major decision-making scenarios such as oil and gas exploration and deployment, production command, etc. can quickly and accurately provide decision-making basis.

Although artificial intelligence brings broad prospects for the development of the oil and gas industry,Dong Xiuchengalso said that the current application of technology in the oil and gas industry still faces multiple potential obstacles and urgent breakthroughs are needed. For example, in terms of oil and gas data, the acquisition cost of oil and gas data is high, there are few big data with label meaning, and the data standards are not uniform, the samples are missing, and the quality is difficult to guarantee, which affects the model training effect; the risk of data security and leakage is high, and oil and gas data involves core strategic information, and there are security risks such as data leakage and forgery; in terms of computing resources, large-scale pre-training models and deep learning models have high computing power requirements, and the existing computing infrastructure in the oil and gas industry is difficult to meet, which limits the application of artificial intelligence technology.

In terms of subject integration, there is a serious shortage of compound talents. Artificial intelligence experts lack professional knowledge in the oil and gas field, and technical experts in the oil and gas field are not familiar with artificial intelligence technology. As a result, "customized" research on artificial intelligence technology in the oil and gas field faces challenges.

In addition, the problem of industry adaptability cannot be ignored. The business scenarios of the oil and gas industry are complex, and deepwater exploration and unconventional oil and gas development still face technical bottlenecks. Data silos and heterogeneous data integration problems restrict the comprehensive application of artificial intelligence, and general-purpose algorithms are difficult to directly apply.

In response to the above challenges,Dong Xiuchengbelieves that the key work of large oil and gas companies (such as Three Barrel Oil) is to strengthen data standardization and governance, establish unified data standards and specifications, and build a secure data sharing mechanism. At the same time, we will increase investment in computing infrastructure and rationally allocate and dynamically schedule computing resources. In addition, the integration of artificial intelligence and oil and gas industry-related technologies, such as digital twins and the Internet of Things, needs to be strengthened.

Finally, oil and gas companies should break through the traditional employment mechanism, build a youth-led innovation ecosystem, and establish compound talent positions related to youth oil and gas-artificial intelligence integration; establish talent incentive mechanisms and performance appraisal standards oriented by actual contributions, and cultivate compound talents who understand both oil and gas expertise and are proficient in artificial intelligence algorithms.

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