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30 June 2023, Volume 42 Issue 3 Previous Issue   

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Digital Transformation of Oil and Gas Exploration and Development; Unstoppable Artificial Intelligence Application Liu He 2023, 42(3): 1-9.  DOI: 10.3969/j.issn.1002-302x.2023.03.001 Abstract ( )   PDF (2319KB) ( )   Artificial intelligence (AI) technology has been under explosion in recent years, becoming an important engine for digital economic development. Application of AI technology has become a key step for oil and gas digital transformation and played an important role in improvement of oil and gas exploration and development efficiency, reduction of business and production costs, assurance of work safety and reduction of environmental risks. This article elaborates the current conditions about R&D and application of AI technology in the areas of reservoir evaluation, logging, geophysical exploration, drilling and completion, oil reservoir engineering, and oil and gas field engineering. The Chinese and foreign oil companies actively study the cooperative AI R&D model, accelerated distribution of AI application in the unconventional oil and gas area, and achieved the preliminary results in those areas. Currently, AI application of oil and gas exploration and development faced a number of challenges, such as high cost for data acquisition, obvious problems of data quality, complicated business situations, unlikeliness for pure dependence on data drive, immaturity of the R&D environment, inapparent short-term results, inadequate understanding, and delay in the relative mechanisms. Focusing on actual AI application, the article proposes to establish the configuration of data quality management, bring about continual automatic inspection for a higher data quality, integrate industrial mechanism model with AI technology to foster cross-disciplinary talents, co-construct the environment for intelligent energy collaboration in encouragement of intelligent energy ecological development, and clarify the fact that digital transformation and intelligent development are the systematic and sustainable projects.

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Digital and Intelligent Development Trend of Oil and Gas Industry Li Jianfeng 2023, 42(3): 10-21.  DOI: 10.3969/j.issn.1002-302x.2023.03.002 Abstract ( )   PDF (3496KB) ( )   There is an unprecedented development opportunity for use of digitalization and intelligence in the oil and gas industry. This paper makes a comprehensive analysis of policy guidance, technological development, business demand and industrial prospect and puts forward the eight main trends for oil and gas industrial digitalized and intelligent development in the future. Based on the application extents, those industrial development trends can be listed in the following order: Digital transformation of the oil and gas industry enters the “deepwater area”. The industrial Internet platform serves as the company’s general platform. Data drive becomes the new orientation for business modernization. The oil and gas industry is fully improved for its independent research and development of the core industrial software. The oil and gas industry is turned to digital industry from traditional one. Industrial AI application triggers large-scale model. Technological innovation enters into the fifth model -- AI model. The oil and gas industry metaverse is poised for application. The main trends for digitalization and intelligence will have effects on enterprises and exert a far-reaching influence on the complex oil and gas industrial transition.

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Research and Practice of CNOOC AI Application Xie Xiaohui, An Peng 2023, 42(3): 22-29.  DOI: 10.3969/j.issn.1002-302x.2023.03.003 Abstract ( )   PDF (2261KB) ( )   Digital transformation is becoming an important driving force for modernization and high-quality development of oil and gas enterprises. The application scenarios for integration of artificial intelligence with oil and gas business is increasingly expanded with the application value gradually highlighted. AI application is currently tried by major oil and gas enterprises all over the world. The development trend has three characteristics – data drive, cross-disciplinary cooperation and gradual maturity. The AI construction of CNOOC has experienced two stages of application research and unified acceleration. The application research stage started from 2019 with AI application research focusing on maintenance of prediction, optimization of process, safety and early warning and awareness analysis. The technological application prospect and value were shown in a number of scenarios. However, some problems were also found in this area, such as a high threshold for development, low development efficiency, waste of calculation resources, and difficult model management. The unified acceleration stage entered into 2020. CNOOC identified the development scenarios, formulated the AI construction plan and steadily made acceleration in stages, achieving a series of results for infrastructure construction and pilot construction of AI application. Construction of the petroleum industrial AI application should be based fully on the oil business demands and continual accumulations of resources, technology and talents, while highlighting five areas of value guidance, data security, higher efficiency of platform, deregulation and cooperation, and security of talents.

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Achievements and Practice in Construction of Digital Intelligent in Changqing Oil and Gas Field Hu Jianguo, Ma Jianjun, Li Qiushi 2023, 42(3): 30-40.  DOI: 10.3969/j.issn.1002-302x.2023.03.004 Abstract ( )   PDF (3068KB) ( )   Changqing Oilfield faces a number of contradictions, such as the increasingly rising contradiction between keeping the production stable and controlling investment of manpower is on the rise, the intensifying contradiction of between the decreasing grade of oil and gas resources and cost-effective development, and the contradiction between work safety and more and a more complex production environment. In response to the management difficulties in the working areas, such as long lines, a large amount of points, and a wide range of area, Changqing Oilfield continued its efforts for the new digital and intelligent revolutionary methods, the new technologies and the new mechanisms in the following seven areas – digitalized infrastructure, integration of data-based management, synergy between exploration and development, intelligent on-the-site service, integrated management and regulation of production, scientific decision-making management, and demonstration of digital and intelligent construction. Those efforts effectively helped the oil and gas field with rapid construction of productivity and high-efficiency development, leading to the revolutions in the operational method for production, business management model, and organizational structure of labor. In addition, the efforts continually promoted in-depth integration of digital and intelligent business with oilfield business, fully created the pilot brand of “Changqing Digit and Intelligence”, and provided a powerful support for transformation of “the oil company” organizational and operational model and high-quality development of the oilfield enterprise. Changqing Oilfield demonstrated a path of innovative transition for in-depth integration between industrialization and informatization for a large-scale energy enterprise.

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Research and Practice of Jianghan Oilfield Digital Transformation Gan Zhenwei, Lu Zhiyong, Li Sihai, Chang Guodong, Wang Cong 2023, 42(3): 41-47.  DOI: 10.3969/j.issn.1002-302x.2023.03.005 Abstract ( )   PDF (2103KB) ( )   Facing the current conditions of corporate digitalization and the challenges in this area, Jianghan Oilfield was committed to digital transformation, which was focused on data governance, platform construction, component-based development, and data mining. The oilfield established the data resources center that covered all the business areas and satisfied all the scenario applications. It also established the control center for management of the abnormal conditions, the industrial Internet software R&D base, and the oil and gas production command center that could effectively operated the stations and crews directly affiliated to the oil production plant. Meanwhile, the company developed 3D visualized oil and gas reservoir management platform for synergy between geological and engineering studies and deployed the 24-hour supervising and intelligent control platform that covered all the business processes of drilling, logging, well log, cementing and testing services. Based on digital transformation, Jianghan Oilfield effectively eliminated isolation of data and apparently improved its abilities for production operation, treatment of the abnormal conditions, and risks control, promoting reform of the corporate management model. As a result, the annual per-capita oil and gas equivalent was raised more than 50 percent, providing an example for the oil and gas production enterprise to accelerate their digital transformation.

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Practice and Achievements from Digital Transformation in Shengli Oilfield Duan Hongjie, Ma Chengjie, Dong Yan, Jing Ruilin, Liu Guangyou, Li Shouqin, Zhao Feng 2023, 42(3): 48-55.  DOI: 10.3969/j.issn.1002-302x.2023.03.006 Abstract ( )   PDF (2243KB) ( )   It is now an all-new historical stage marked by digital productivity. Against the new background of the accelerated energy revolution and energy transition, domestic and foreign oil and gas enterprises have effectively used digital and intelligent technology to accelerate industrial transformation and modernization as well as value growth. Guided by the Sinopec digital transformation technology system, Shengli Oilfield formulated the corporate digital transformation configuration plan that focused on “consolidating three foundations, building one platform and creating five application clouds”, as so-called “the three-one-five plan”. The internal dynamic power centered on business drive, technological drive, data drive and value drive to create the intelligently-applied production worksite, the uniformly-controlled business platform, the extensively-shared research environment, and the integrated service data center. As a result, the information coverage rate was 100 percent for the production worksites while the efficiency for research business of exploration and development and business operation was increased by two to three times. Those efforts have fully accelerated optimization and reconstruction of full elements, full procedures and full chain for production business operation of the oilfield, thus helping Shengli Oilfield bring about high-efficiency exploration and development, revolution of production business methods and green development with safety and environmental protection.

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Study and Application of Collaborative Research Model for Exploration and Development of Southwest Oil and Gas Field Zhang Enli, Kang Qiang 2023, 42(3): 56-64.  DOI: 10.3969/j.issn.1002-302x.2023.03.007 Abstract ( )   PDF (4141KB) ( )   The mineral area of Southwest Oil and Gas Field is rich in oil and gas resources. With oil and gas exploration and development unfolded extensively, more and more oil and gas resources were found in the environment with the complicated surface like high mountains. The traditional conditions of exploration and development business were unable to satisfy the demand for high-intensity and in-depth cooperation. Based on the current business conditions bottlenecks of collaboration and technological research demand of Southwest Oil and Gas Field, this article clarifies that the new-type business model for exploration and development research collaboration should be focused on “improvement of quality and efficiency” and targeted at the physical oil and gas assets (gas reservoir-wellbore-surface) to establish the standardized research process, pursue the intelligent auxiliary research and support cross-disciplinary joint research. With the three-year efforts for technological research and application, the collaborative research platform for exploration and development was established on the basis of Dream Cloud and regional lakes. It provides the researchers with a set of the integrated collaborative and sharing research work environment, the integrated research model at the level of basins and the full business chain intelligent research process to help exploration and development research bring about effective sharing and coordination of oil and gas reservoir data, software and research achievements, fully support exploration and development business of oil and gas fields, and improve research work quality and efficiency. Currently, the achievements were made in application of the platform for evaluation of the zone and belt targets, thus promoting development of the business model of Southwest Oil and Gas Field and helping CNPC with digital transformation.

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Cost-effective Internet of Things Constructed and Applied by Jilin Oilfield Teng Qigang 2023, 42(3): 65-71.  DOI: 10.3969/j.issn.1002-302x.2023.03.008 Abstract ( )   PDF (2129KB) ( )   Based on independent research and development, independent design, independent construction, and independent operation and maintenance, Jilin Oilfield established the simple and applicable cost-effective Internet of things (IoT) with the experience that could be duplicated and extended. A series of featured products were innovated and developed, such as the pumping unit shutdown alarm, the oil well measurement and control instrument, and the well site electronic eye. They helped solve some actual production problems, such as the difficulties to find abnormal shutdown and abnormal well conditions as well as the difficult for well site inspection. Those products not only have a reliable performance but also one third of the cost as compared to the equipment of the same kind. Based on integrated application of a number of technologies, the labor strength of supervisors was lowered by more than 85 percent while the supervision efficiency was improved by five times. All the efforts aimed at optimize the IoT system configuration, bring about cloud deployment of servers, cut down the quantity of IoT parts on the well site, reduce the technological difficulty for front-end equipment, change the transmission method, simplify the system structure and ensure a high online rate. The oilfield also tapped big data of IoT and developed the series of technology for in-depth application of electrical parameters, thus making remarkable achievements in diagnosis of well conditions and energy saving. It established the unified cloud platform and brought the whole oilfield under one set of systems, namely one platform,to facilitate software deployment, upgrading and daily maintenance and complete a cost-effective construction, operation and maintenance model. The oilfield promoted transformation of the management process on the basis of digital mindset, adopted the closed-loop management over the whole life cycle of data application and established the new model for the oil production plants to bring oil and water wells under direct and concentrated management.

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Discuss Digitalized Model of Economic Evaluation for Oilfield Enterprises Guo Fujun 2023, 42(3): 72-78.  DOI: 10.3969/j.issn.1002-302x.2023.03.009 Abstract ( )   PDF (2113KB) ( )   The digitalized model of economic evaluation uses digital information technology like big data and cloud computing to construct the digitalized management system of “three-level operational system”. The model is established in the efforts to formulate the systematic process, create the integrated databank of economic evaluation, develop the software platform for oilfield economic evaluation and construct a number of digitalized modules for economic evaluation of reserves, evaluation of productivity construction and development plans, evaluation of single-well performance, evaluation of treatment results from ineffective wells, and evaluation of benefits from the treatment measures. The oilfield digitalized performance-managing model covers the whole life cycle of the oilfield, focusing on “management of the whole process, analysis of all elements and all-around evaluation”. Liaohe Oilfield uses the digitalized model to eliminate the hurdles among the cross-disciplinary data, increase and invigorate the economic reserve assets, optimize the productivity construction projects, and evaluate the feasibility of development plans. Good results have been achieved in evaluation of single-well performance and treatment of ineffective wells. The performance-based yield was boosted 5.2 percent as compared to the previous year, while the marginal benefit yield and ineffective yield declined 3.3 percent and 1.8 percent separately. The structure of performance-based yield was remarkable for optimization. In addition, the profit-making and performance-controlling abilities of the oilfield were effectively improved, thus fueling high-quality development of the oilfield.

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Understanding and Practice from Laboratory Digital Transformation at Oilfield Enterprises Wang Bin, Yang Jian, He Yiguo, Tan Jinfeng, Min Jian 2023, 42(3): 79-85.  DOI: 10.3969/j.issn.1002-302x.2023.03.010 Abstract ( )   PDF (2153KB) ( )   Laboratory is the support center for the oilfield enterprise to make decisions and directly involved in the whole process of oil and gas exploration and development. Thanks to rapid development of information technology, some problems cropped up in traditional operation of a laboratory, such as low work efficiency, inadequate development of data value, and difficult quality control. To raise the development and application level of experiment data, it is necessary to improve the abilities for business testing, scientific research, and decision-making management and coordination. Based on the requirements for CMA and CNAS quality certificates, the efforts are focused on management of laboratory personnel, equipment, materials and inspecting. Information technology like Internet of Things, mobile application and big data is used for reconstruction of the business process, data integration and data analysis. The digitalized management platform is established on the basis of laboratory data application while a complete set of new digital management models is put in place for optimization of business process, scientific arrangement of resources, reliable quality control, precise risks control, and high-efficiency application of data. The laboratory is in transition to “online process management” from “offline business management”. The operational efficiency of experiment inspection is improved by 30 percent, the workload of quality management personnel lowered by more than 70 percent, and the management cost saved by more than 20 percent, thus raising both quality and performance.

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Patent Analysis of AI-based Oil and Gas Pipeline Digital Twin Technology Wang Yuqin,Gao Bohao,Meng Fangfang 2023, 42(3): 86-92.  DOI: 10.3969/j.issn.1002-302x.2023.03.011 Abstract ( )   PDF (2387KB) ( )   The artificial intelligence (AI) and digital twin technology have found wide application in construction of oil and gas pipelines in recent years, fueling the transition from traditional oil and gas pipeline network to intelligent network. The applications for the patent of digital twin technology has been steadily on the rise since 2016. At present, 60.37 percent of the invention patents is under examination. As of August 31, 2022, there were 3045 applications for the patent of digital twin technology in China, making the nation a world leader in this area and followed by the United States, the World Intellectual Property Organization (WIPO) and Republic of Korea. Of all the main applicants in the world, Siemens ranked first for its 262 applications with obvious advantages. Four Chinese units are also in the leading position in this area. The patent analysis of the AI-based oil and gas pipeline digital twin technology indicates that the patents worldwide are mainly concentrated in China, WIPO, the United States and Republic of Korea. China University of Petroleum (East China), Landmark Graphics Corporation, PipeChina and GE are also on the forefront of the global applicants. The risks for patent exist mainly in the areas of space model, dynamic modeling, real-time modeling and movement model. The study indicates the application trend for patent, regional distribution of application, key patentees and technical barriers. Focusing on the oil and gas pipeline enterprises, it also comes up with the relative suggestions on enhancement of technological R&D and patent distribution, improvement of patent application quality and expansion of patent protective scope.