The oil refining and petrochemical industry in China has made great achievements after decades of development, and its capacity has already ranked second in the world. However, the refining industry is suffering some ...The oil refining and petrochemical industry in China has made great achievements after decades of development, and its capacity has already ranked second in the world. However, the refining industry is suffering some challenges, such as severe overcapacity at present, and has entered a new economic normal, in which the technological progress develops rapidly, the demand for green and low-carbon development is stricter, the market competition is increasingly fiercer and the profit margins are gradually narrowing. In such a situation, informatization and its new technologies are driving the significant reforming of manufacturing patterns, marketing patterns, management and decision-making patterns. Intelligent development is the inevitable choice for the transformation and upgrading of oil refining and petrochemical industry. It is suggested that the intelligent evaluating model and method should be adopted to enterprise’s intelligentializing transformation and upgrading by laying a solid foundation of digital refinery and implemenation of digital upgrading.展开更多
Triboelectric nanogenerators(TENGs)have potential to achieve energy harvesting and condition monitoring of oils,the“lifeblood”of industry.However,oil absorption on the solid surfaces is a great challenge for oil-sol...Triboelectric nanogenerators(TENGs)have potential to achieve energy harvesting and condition monitoring of oils,the“lifeblood”of industry.However,oil absorption on the solid surfaces is a great challenge for oil-solid TENG(O-TENG).Here,oleophobic/superamphiphobic O-TENGs are achieved via engineering of solid surface wetting properties.The designed O-TENG can generate an excellent electricity(with a charge density of 9.1μC m^(−2) and a power density of 1.23 mW m^(−2)),which is an order of magnitude higher than other O-TENGs made from polytetrafluoroethylene and polyimide.It also has a significant durability(30,000 cycles)and can power a digital thermometer for self-powered sensor applications.Further,a superhigh-sensitivity O-TENG monitoring system is successfully developed for real-time detecting particle/water contaminants in oils.The O-TENG can detect particle contaminants at least down to 0.01 wt%and water contaminants down to 100 ppm,which are much better than previous online monitoring methods(particle>0.1 wt%;water>1000 ppm).More interesting,the developed O-TENG can also distinguish water from other contaminants,which means the developed O-TENG has a highly water-selective performance.This work provides an ideal strategy for enhancing the output and durability of TENGs for oil-solid contact and opens new intelligent pathways for oil-solid energy harvesting and oil condition monitoring.展开更多
Intelligent well system is the well that has a set of equipment fixed in the down hole including sensing devices, data transmission system and operating devices for information acquiring, data gathering and decision a...Intelligent well system is the well that has a set of equipment fixed in the down hole including sensing devices, data transmission system and operating devices for information acquiring, data gathering and decision analysis. By this remote control process, the smart well system can ultimately optimize well deliverability; it is used more and more often in oil fields with its stability and control technique. At present, the main intelligent well systems in the worm include SCRAMS, Direct Hydraulic, Digital Hydraulic that belongs to WellDynamics Company, InForce and InCharge that belongs to Baker Oil Tools Company, RMC that belongs to Schlumberger Company. This paper compares different types of systems and their characteristics, recommending the InCharge system as the intelligent well system for East China Sea Oil Field according to its geological and reservoir conditions.展开更多
The real-time prediction of bearing wear for roller cone bits using the Intelligent Drilling Advisory system （IDAs） may result in better performance in oil and gas drilling operations and reduce total drilling cost....The real-time prediction of bearing wear for roller cone bits using the Intelligent Drilling Advisory system （IDAs） may result in better performance in oil and gas drilling operations and reduce total drilling cost. IDAs is a real time engineering software and being developed for the oil and gas industry to enhance the performance of complex drilling processes providing meaningful analysis of drilling operational data. The prediction of bearing wear for roller cone bits is one of the most important engineering modules included into IDAs to analyze the drilling data in real time environment. The Bearing Wear Prediction module in IDAs uses a newly developed wear model considering drilling parameters such as weight on bit （WOB）, revolution per minute （RPM）, diameter of bit and hours drilled as a function of International Association of Drilling Contractors （IADC） bit bearing wear. The drilling engineers can evaluate bearing wear status including cumulative wear of roller cone bit in real time while drilling, using this intelligent system and make a decision on when to pull out the bit in time to avoid bearing failure. The wear prediction module as well as the intelligent system has been successfully tested and verified with field data from different wells drilled in Western Canada. The estimated cumulative wears from the analysis match close with the corresponding field values.展开更多
为了辨识油气智慧管道系统中存在的信息安全风险,通过基于系统论事故分析模型(systems-theoretic accident modeling and process,STAMP)的方法,对油气智慧管道系统的信息物理安全进行全面评估与分析。首先,系统综合分析了油气智慧管道...为了辨识油气智慧管道系统中存在的信息安全风险,通过基于系统论事故分析模型(systems-theoretic accident modeling and process,STAMP)的方法,对油气智慧管道系统的信息物理安全进行全面评估与分析。首先,系统综合分析了油气智慧管道涉及的设备、设施、工艺、元件,评估其安全性。其次,通过建立STAMP模型,深入分析了各层级、元件之间的反馈信息与控制动作,形成了明确的控制反馈回路,突显了元件之间的关联与控制关系。在此基础上,系统辨识出了潜在的信息风险因素,推导并构建了可能发生的系统失效场景。以天然气输气首站油气智慧管道系统为例,研究验证了基于STAMP模型的可行性和有效性。结果显示,该方法不仅直观地描述了元件之间的关联与控制关系,而且从物理层功能安全的角度全面考虑了信息风险,特别凸显了过程控制系统(process control systems,PCS)及易受攻击的操作员站。与传统方法相比,本研究所提出的方法将信息物理安全风险因素的识别率提升至80%以上,提高了40%以上,有助于避免不必要的安全措施冗余设计,提高了安全风险管控的准确性。展开更多
文摘The oil refining and petrochemical industry in China has made great achievements after decades of development, and its capacity has already ranked second in the world. However, the refining industry is suffering some challenges, such as severe overcapacity at present, and has entered a new economic normal, in which the technological progress develops rapidly, the demand for green and low-carbon development is stricter, the market competition is increasingly fiercer and the profit margins are gradually narrowing. In such a situation, informatization and its new technologies are driving the significant reforming of manufacturing patterns, marketing patterns, management and decision-making patterns. Intelligent development is the inevitable choice for the transformation and upgrading of oil refining and petrochemical industry. It is suggested that the intelligent evaluating model and method should be adopted to enterprise’s intelligentializing transformation and upgrading by laying a solid foundation of digital refinery and implemenation of digital upgrading.
基金want to thank Swedish Kempe Scholarship Project(No.JCK-1903.1)the Swedish Research Council for Environment,Agricultural Sciences and Spatial Planning(Formas,No.2019-00904)+1 种基金the Swedish Research Council(No.2019-04941)and the National Natural Science Foundation of China(Grant No.51905027).
文摘Triboelectric nanogenerators(TENGs)have potential to achieve energy harvesting and condition monitoring of oils,the“lifeblood”of industry.However,oil absorption on the solid surfaces is a great challenge for oil-solid TENG(O-TENG).Here,oleophobic/superamphiphobic O-TENGs are achieved via engineering of solid surface wetting properties.The designed O-TENG can generate an excellent electricity(with a charge density of 9.1μC m^(−2) and a power density of 1.23 mW m^(−2)),which is an order of magnitude higher than other O-TENGs made from polytetrafluoroethylene and polyimide.It also has a significant durability(30,000 cycles)and can power a digital thermometer for self-powered sensor applications.Further,a superhigh-sensitivity O-TENG monitoring system is successfully developed for real-time detecting particle/water contaminants in oils.The O-TENG can detect particle contaminants at least down to 0.01 wt%and water contaminants down to 100 ppm,which are much better than previous online monitoring methods(particle>0.1 wt%;water>1000 ppm).More interesting,the developed O-TENG can also distinguish water from other contaminants,which means the developed O-TENG has a highly water-selective performance.This work provides an ideal strategy for enhancing the output and durability of TENGs for oil-solid contact and opens new intelligent pathways for oil-solid energy harvesting and oil condition monitoring.
文摘Intelligent well system is the well that has a set of equipment fixed in the down hole including sensing devices, data transmission system and operating devices for information acquiring, data gathering and decision analysis. By this remote control process, the smart well system can ultimately optimize well deliverability; it is used more and more often in oil fields with its stability and control technique. At present, the main intelligent well systems in the worm include SCRAMS, Direct Hydraulic, Digital Hydraulic that belongs to WellDynamics Company, InForce and InCharge that belongs to Baker Oil Tools Company, RMC that belongs to Schlumberger Company. This paper compares different types of systems and their characteristics, recommending the InCharge system as the intelligent well system for East China Sea Oil Field according to its geological and reservoir conditions.
文摘The real-time prediction of bearing wear for roller cone bits using the Intelligent Drilling Advisory system （IDAs） may result in better performance in oil and gas drilling operations and reduce total drilling cost. IDAs is a real time engineering software and being developed for the oil and gas industry to enhance the performance of complex drilling processes providing meaningful analysis of drilling operational data. The prediction of bearing wear for roller cone bits is one of the most important engineering modules included into IDAs to analyze the drilling data in real time environment. The Bearing Wear Prediction module in IDAs uses a newly developed wear model considering drilling parameters such as weight on bit （WOB）, revolution per minute （RPM）, diameter of bit and hours drilled as a function of International Association of Drilling Contractors （IADC） bit bearing wear. The drilling engineers can evaluate bearing wear status including cumulative wear of roller cone bit in real time while drilling, using this intelligent system and make a decision on when to pull out the bit in time to avoid bearing failure. The wear prediction module as well as the intelligent system has been successfully tested and verified with field data from different wells drilled in Western Canada. The estimated cumulative wears from the analysis match close with the corresponding field values.
文摘为了辨识油气智慧管道系统中存在的信息安全风险,通过基于系统论事故分析模型(systems-theoretic accident modeling and process,STAMP)的方法,对油气智慧管道系统的信息物理安全进行全面评估与分析。首先,系统综合分析了油气智慧管道涉及的设备、设施、工艺、元件,评估其安全性。其次,通过建立STAMP模型,深入分析了各层级、元件之间的反馈信息与控制动作,形成了明确的控制反馈回路,突显了元件之间的关联与控制关系。在此基础上,系统辨识出了潜在的信息风险因素,推导并构建了可能发生的系统失效场景。以天然气输气首站油气智慧管道系统为例,研究验证了基于STAMP模型的可行性和有效性。结果显示,该方法不仅直观地描述了元件之间的关联与控制关系,而且从物理层功能安全的角度全面考虑了信息风险,特别凸显了过程控制系统(process control systems,PCS)及易受攻击的操作员站。与传统方法相比,本研究所提出的方法将信息物理安全风险因素的识别率提升至80%以上,提高了40%以上,有助于避免不必要的安全措施冗余设计,提高了安全风险管控的准确性。
