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
A medium-temperature waste-heat recovery system based on the organic Rankine cycle (ORC) is designed to recover the exhaust energy from a heavy-duty diesel engine. Analysis of the 1st law of thermodynamics for an ORC ...A medium-temperature waste-heat recovery system based on the organic Rankine cycle (ORC) is designed to recover the exhaust energy from a heavy-duty diesel engine. Analysis of the 1st law of thermodynamics for an ORC system is performed. This analysis contains two parts. The first part is an analysis with undefined heat exchangers to gain an understanding of the ORC and find out suitable organic fluid parameters for a better ORC efficiency. The second part of the analysis uses combined engine test results and two designs of heat exchangers. By comparing the two designs, an improved system of heat exchangers is described. This analysis also quantifies the effect of engine parameters on ORC system. The study concludes that the supercritical Rankine cycle is a better approach towards waste heat recovery. The ORC system is found to perform better under part-load conditions if the medium-high power condition rather than rated working point of the engine is used as the design parameter. The ORC system achieves the highest waste-heat recovery efficiency of up to 10-15% for the optimised heat ex-changer design.展开更多
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.
基金supported by the National Natural Science Foundation of China (Grant No. 51076013)the Specialized Research Fund for the Doc-toral Program of Higher Education of China (Grant No. 20101101110008)
文摘A medium-temperature waste-heat recovery system based on the organic Rankine cycle (ORC) is designed to recover the exhaust energy from a heavy-duty diesel engine. Analysis of the 1st law of thermodynamics for an ORC system is performed. This analysis contains two parts. The first part is an analysis with undefined heat exchangers to gain an understanding of the ORC and find out suitable organic fluid parameters for a better ORC efficiency. The second part of the analysis uses combined engine test results and two designs of heat exchangers. By comparing the two designs, an improved system of heat exchangers is described. This analysis also quantifies the effect of engine parameters on ORC system. The study concludes that the supercritical Rankine cycle is a better approach towards waste heat recovery. The ORC system is found to perform better under part-load conditions if the medium-high power condition rather than rated working point of the engine is used as the design parameter. The ORC system achieves the highest waste-heat recovery efficiency of up to 10-15% for the optimised heat ex-changer design.
