● Wang Hao, Jiang Shan, Shi Dapeng, Luozuo County
At present, the era of deep embedding of artificial intelligence (AI) in various industries is coming. Driven by the "three horses" of computing power, algorithms, and big data, artificial intelligence is developing rapidly and setting off a wave of innovation in various industries, giving birth to unprecedented new products, new models, and new formats. The integration of machine learning and neural networks in the global oil and gas industry has a long history. After the introduction of cloud computing, artificial intelligence technology has shown a wide range of application scenarios in various links such as exploration, mining, transportation, and refining. The deep integration of artificial intelligence technology and the oil and gas industry and the continuous expansion and improvement of application scenarios will drive the oil and gas industry to develop in a more efficient, safer and more environmentally friendly direction, and then lead a more profound industrial transformation.
Current status of artificial intelligence applications in the oil and gas industry
In the field of oil and gas exploration and development, artificial intelligence technology has been applied to a certain extent in seismic exploration and seismic data interpretation and processing, well logging interpretation, oil and gas layer identification, drilling and completion, reservoir dynamic analysis and simulation, oil and gas field surface engineering and other businesses. For example, Schlumberger's wellbore data comprehensive interpretation technology is based on advanced rock physics, covering 32 analytical technologies in 8 professional fields such as drilling, logging, geology, production, reservoirs, geophysics, unconventional and rock mechanics. Its use runs through the entire life cycle of oil fields from exploration, development to production, and can provide a series of high-quality geological and engineering parameters for reservoir evaluation, reservoir description and engineering operations. It has completed more than 10,000 well operations. Domestic oil and gas companies rely on artificial intelligence to accelerate the construction of smart oil fields. Sinopec Northwest Oilfield has basically achieved on-site visualization, production automation, reservoir digitization, management informationization, and intelligent decision-making based on the Sinopec Zhiyun platform, with remarkable construction results. PetroChina has built application platforms such as the Dream Cloud Collaborative Platform, integrated logging processing and interpretation software, and a new generation of multi-well evaluation software. Intelligent applications in reservoir description and simulation, logging multi-well interpretation, etc. have begun to show results. CNOOC has used cloud computing, big data, artificial intelligence and other information technologies to build the first domestic offshore smart oilfield construction project in Bohai Bay.
The application of artificial intelligence in storage and transportation is mainly to improve the level of safe storage and transportation of oil and gas through computer recognition, data analysis and prediction, make good seasonal demand forecasts for users, and then support scheduling decisions. The first is to provide safety protection. At present, oil and gas stations and pipelines are mainly guaranteed by installing a large number of cameras and manual detection. However, when encountering large-scale projects and thousands of camera images, the effect of manual recognition and monitoring is often not good, and artificial intelligence technology is needed. The second is to support business decisions through predictive analysis. Using AI technology to comprehensively process parameters such as temperature, pressure, flow, and equipment status during transportation and storage, abnormal load changes can be found and then the rules can be summarized to give optimized decision-making plans. Taking the construction of natural gas storage as an example, the industry has been working towards intelligent gas storage. The application fields of technological innovation cover underground gas storage, liquefied natural gas (LNG) receiving stations and other types. The application of intelligent gas storage technology is concentrated in intelligent monitoring systems, automatic control, etc., with the aim of improving the safety and operation efficiency of gas storage. After matching perfect rules and regulations and operating procedures, the safe and stable operation level of gas storage will be improved.
In the refining industry, the application of artificial intelligence is mainly focused on improving production efficiency, optimizing production processes, predicting equipment failures, controlling product quality, environmental management and energy conservation. Saudi Basic Industries Corporation cooperates with Siemens and other companies to build a fully automatic digital refining product production line based on cutting-edge technologies such as AI, big data, and sensors, effectively reducing production costs and product cycles. BASF also cooperates with IBM to obtain and analyze data information generated during the production process to optimize process flow and reduce production costs. Since the 13th Five-Year Plan, under the national intelligent manufacturing strategic deployment, domestic refining companies have built a number of intelligent refining companies based on the three-layer model of business decision-making, manufacturing execution, and process control by applying technologies such as big data, cloud manufacturing, and industrial Internet. These companies have formed practical experience in planning and scheduling coordination, intelligent production, intelligent warehousing, robot inspection, intelligent logistics, intelligent laboratories, and digital delivery, and promoted the innovation and development of corporate management models. As early as 2012, Sinopec took the lead in proposing the concept of petrochemical smart factory in China. According to the "six unifications" principle of information construction, it promoted the construction of smart factories and related supporting information projects, and a number of national smart manufacturing benchmark enterprises such as Jiujiang Petrochemical emerged.
International energy companies are deeply engaged in AI technology research and development and application
According to research and analysis by market analysis agency Mordor Intelligence, the global oil and gas industry artificial intelligence market size is expected to be US$3.14 billion in 2024 and will reach US$5.7 billion by 2029, with a compound growth rate of 12.61% from 2024 to 2029. Among them, IBM, C3.AI, Microsoft, Intel, etc., as major technology service providers, have carried out extensive cooperation with major global oil and gas companies. For example, C3.AI has launched the C3 Generative AI Product Suite, and the pre-built AI advanced converter model will accelerate the transformation of the oil and gas business; Wintershall announced last year that it would cooperate with IBM to establish an AI capability center focusing on natural gas and carbon management; Schlumberger cooperated with GeminusAI at the beginning of this year to combine physical methods with process data to quickly and cheaply create highly accurate AI models; Abu Dhabi National Oil Company cooperated with AIQ in March this year to use AI tools to analyze reservoir data to improve efficiency and safety while reducing emissions and costs.
A recent survey by consulting firm EY shows that 92% of oil and gas companies around the world will integrate artificial intelligence with the oil and gas industry as a key investment area in the next two years. This is mainly due to the widespread application and remarkable results of artificial intelligence technologies such as machine learning, predictive analysis and automatic control systems in the oil and gas industry in recent years. The integration of artificial intelligence in business scenarios such as reservoir simulation, automatic drilling, predictive maintenance, geological mapping, safety monitoring, process automation and asset management has improved the operational efficiency of enterprises, reduced safety risks and optimized decision-making processes. In the application of artificial intelligence technology in the oil and gas industry to serve different business scenarios, the world's major oil and gas companies play the role of leaders. For example, Shell applies AI technology to material research and development and precision drilling, BP uses AI technology for site selection and predictive maintenance, Total develops conversational AI products, Chevron has achieved remarkable results in AI reservoir image processing, ExxonMobil applies AI technology to drilling data collection and ship tracking, and Petronas and Saudi Aramco have made innovative breakthroughs in predicting equipment failures, reservoir modeling and leak detection.
Exploring new application scenarios of AI technology in the oil and gas industry
At present, the application of artificial intelligence technology in the oil and gas industry is gradually deepening, from exploration and development to storage and transportation, and then to the transformation of the refining industry, all of which reflect the huge potential of AI technology.
As oil and gas exploration and development expand to deepwater, deep layers and unconventional fields, the difficulty of exploration and development is increasing. The application of AI technology in the exploration field will mainly focus on the following aspects: First, improve the accuracy of geological exploration and reservoir management. Artificial intelligence can process huge amounts of geological, seismic and logging data, providing more accurate and comprehensive data support for the identification and evaluation of oil and gas reservoirs. It is necessary to further identify the patterns and laws hidden behind the data through technologies such as deep learning. The success rate of oil and gas resource discovery can be improved and exploration risks can be reduced through more accurate analysis of the geological structure of the oil field. In terms of reservoir management, artificial intelligence can be used to strengthen the real-time monitoring of formation changes and injection and production data, and timely analyze and reflect the dynamic changes of the reservoir. Second, improve the level of production data analysis and optimization. Artificial intelligence can not only provide operational suggestions in the production process to optimize oil field production decisions, but also be able to carry out production planning, formulate the best production plan based on historical data and real-time information, and make the entire production process more coordinated and consistent. Third, strengthen equipment health monitoring and maintenance. Timely and accurate identification of patterns and anomalies in equipment data, predict the future health status of equipment, and formulate the best equipment maintenance strategy. Fourth, enhance risk prediction and safety management capabilities. The real-time monitoring function of artificial intelligence can provide strong support for accident prevention. By monitoring the real-time data of the production environment, it helps oilfield companies quickly discover abnormal situations and take countermeasures to improve the level of safety management.
Intelligent storage and transportation technology has been widely used worldwide, but it still faces some challenges, such as breakthroughs in key technologies, improvements in safety and efficiency, etc. International oil and gas demand will remain strong for a long time, and the scale of development of the oil and gas storage and transportation industry will continue to maintain necessary growth. In the process of growth, some new scenarios will emerge in the scale of oil and gas storage and transportation, such as the gradual expansion of the scale of long-distance hydrogen transmission of natural gas pipelines. The emergence of new storage and transportation scenarios requires AI technology to play a further role in safe operation and maintenance, data analysis and decision-making. In the long run, combined with the urgent requirements of digital transformation and safe production in the oil and gas industry, promoting the integrated application of industrial Internet technologies such as big data, artificial intelligence, and cloud computing in the intelligent operation and maintenance of oil and gas storage and transportation equipment, and establishing a digital, networked, and intelligent oil and gas storage and transportation system are of great significance to ensuring the safety, reliability and long-term operation of the oil and gas lifeline.
In the process of transformation of the oil refining industry, artificial intelligence technology is coupled with the management and control levels of enterprise business decision-making, manufacturing execution, process control, etc., to improve the intelligence level of refining and chemical enterprises, which will effectively help the high-quality development of the oil refining industry. At the production decision-making level, we must give full play to the learning ability of artificial intelligence, improve the intelligence level of crude oil market price forecasting, crude oil procurement optimization, crude oil value chain integration optimization, finished oil logistics optimization, supplier risk management based on knowledge graphs, and customer relationship management through big data analysis, efficiently explore the value of data assets, and build an intelligent decision support system. At the manufacturing execution level, artificial intelligence technology can be used to analyze the device operation data, dynamic equipment shaft system monitoring data, static equipment corrosion monitoring data, etc., deeply explore the laws existing in the data, establish a device operation expert knowledge base and equipment failure symptom library, realize expert guidance of the device production process, optimize production operations; realize predictive maintenance of equipment failures, eliminate safety risks and hidden dangers from the source, and improve the level of safety management. Use artificial intelligence technology to upgrade the energy management system and environmental monitoring system, improve the level of energy conservation and environmental protection, accept more renewable energy, and promote green production. Artificial intelligence technology is used to efficiently generate a three-dimensional dynamic model of the production process to provide support for troubleshooting, operation training, etc. At the process control level, artificial intelligence technology is coupled with advanced control, real-time optimization, intelligent equipment, and automated instruments. By improving data cleaning, soft measurement maintenance, advanced control model maintenance, control loop parameter self-tuning, and instrument fault intelligent diagnosis, the level of intelligent production control is finally improved, empowering on-site production.
(Author's unit: Sinopec Economic and Technological Research Institute)
Comment: Improve quality with "intelligence" and accelerate innovation in the energy industry
● Luozuo County
Since the beginning of this century, the renewable energy industry has flourished, and low-carbon economy and carbon neutrality have become hot topics of the times. Behind these trends, all rely on the continuous advancement of technology. The transformation of the economic model requires strong support, and technological progress is its core driving force. It is in this context that artificial intelligence (AI) technology came into being and rose rapidly.
AI is the key supporting technology for new quality productivity. "Artificial intelligence + hundreds of industries" is expected to lead a new round of industrial revolution and inject strong impetus into high-quality development. Under the current situation, the energy field is one of the most urgent and important areas for the application of AI technology. my country is vigorously promoting the energy revolution and is committed to optimizing various production factors. Whether it is efficient mining or clean utilization of coal, whether it is deep-layer deepwater oil and gas or unconventional oil and gas exploration and development, whether it is the production, storage, transportation and sales of oil products or chemical products, whether it is the application of smart grid or virtual power plant technology, there is a high demand for the processing, simulation and model prediction of massive data, and it is highly dependent on the application of AI technology. Vigorously promoting the application of AI technology in the field of energy production, supply, storage and sales is a major strategic choice to form and develop new quality productivity in the energy field and promote the energy revolution to go deeper and more practical.
As one of the main players in the energy revolution of the new era, energy companies should always bear in mind the important instruction that "energy rice bowl must be held in their own hands", actively participate in the wave of AI technology, and embrace the era of AI technology. Specifically, energy companies should organically combine the research and development and application of AI technology with the practice of energy consumption revolution, energy supply revolution, energy technology revolution, energy system revolution and international cooperation. As the main body of energy consumption, energy enterprises should widely promote and apply AI technology in energy conservation and consumption reduction, organically combine intelligent control systems with various energy consumption index adjustments and energy consumption, and be the pioneers and role models of energy efficiency improvement; as the main body of energy supply, they should combine green energy substitution and stable supply with the research and development and application of AI technology, and give full play to the potential of AI technology to improve quality and efficiency in smart grid dispatching, deepwater and deep-layer oil and gas exploration and development, etc.; as the main body of technological revolution, energy enterprises should, based on the development characteristics of their industry, increase research and development and technology demonstration efforts according to business development needs, and make good plans and designs to lead the development of industry enterprises with AI technology; as one of the main bodies of institutional revolution, they should create an enterprise management system and operation mechanism that matches the development of AI technology and create a combat-ready talent team; as the main body of international cooperation, energy enterprises should have an inclusive and hand-in-hand mind, look at the world, establish a broad strategic alliance with domestic and foreign enterprises, jointly promote the advancement of AI technology, and promote the improvement of global energy governance.
my country attaches great importance to the development of artificial intelligence, and has successively experienced the development stages of "Internet +", "Intelligence +", and "Artificial Intelligence +". The development of AI technology is both a change in science and technology and a requirement of the times. my country's energy companies are at this critical juncture and will certainly be able to seize the opportunities of the times and promote the high-quality development of the energy industry with the strong momentum of AI technology applications.
