Gas-solid two-phase flow theory was used to predict dust distribution and movement at the working face of a mine.The software package FLUENT was used to numerically simulate dust motion and the results were compared t...Gas-solid two-phase flow theory was used to predict dust distribution and movement at the working face of a mine.The software package FLUENT was used to numerically simulate dust motion and the results were compared to observed data.The simulation agrees with the data taken from an actual working face,which confirms the choice of mathematical model and numerical simulation method. Using the model we predict a set of conditions optimum for reducing dust concentrations at the mine working face.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
基金supported by the Special Foundation for Doctor Degree of the Ministry of Education(No.2006008001)the Construction Project of Beijing Municipal Education Committee (No.XK100080432)the Joint Development Project of Beijing.
文摘Gas-solid two-phase flow theory was used to predict dust distribution and movement at the working face of a mine.The software package FLUENT was used to numerically simulate dust motion and the results were compared to observed data.The simulation agrees with the data taken from an actual working face,which confirms the choice of mathematical model and numerical simulation method. Using the model we predict a set of conditions optimum for reducing dust concentrations at the mine working face.
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.
