A neural network is applied to high-quality 3-D seismic data during micro-seismic facies analysis to perform the waveform analysis and training on single reflection events. Modeled seismic channels are established and...A neural network is applied to high-quality 3-D seismic data during micro-seismic facies analysis to perform the waveform analysis and training on single reflection events. Modeled seismic channels are established and the real seismic channels are classified. Thus, a distribution of micro-seismic facies having a high precision over a fiat surface was acquired. This method applied to existing geological data allows the distribution of areas rich in coal bed methane to be clearly defined. A distribution map of the micro-seismic facies in the research area is shown. The data accord well with measured methane con- tents, indicating that the analysis using micro-seismic facies is reliable and effective. This method could be applied to coal bed methane exploration and is of great importance to future exploration work and to an increase in the drilling success rate.展开更多
The control system determines the effectiveness of an underwater hydraulic shock shovel. This paper begins by analyzing the working principles of these shovels and explains the importance of their control systems. A n...The control system determines the effectiveness of an underwater hydraulic shock shovel. This paper begins by analyzing the working principles of these shovels and explains the importance of their control systems. A new type of control system’s mathematical model was built and analyzed according to those principles. Since the initial control system’s response time could not fulfill the design requirements, a PID controller was added to the control system. System response time was still slower than required, so a neural network was added to nonlinearly regulate the proportional element, integral element and derivative element coefficients of the PID controller. After these improvements to the control system, system parameters fulfilled the design requirements. The working performance of electrically-controlled parts such as the rapidly moving high speed switch valve is largely determined by the control system. Normal control methods generally can’t satisfy a shovel’s requirements, so advanced and normal control methods were combined to improve the control system, bringing good results.展开更多
Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was...Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was used synthetically. Artificial neural network was combined with genetic algorithm to found integrated AI method of genetic algorithm artificial neural network(GA ANN). Fault recognition and coal seam thickness forecast were carried to completion by case studies. And the research results are satisfactory.展开更多
Non-liner wave equation inversion,wavelet analysis and artificial neural networks were used to obtain stratum parameters and the distribution of thin coal seams.The lithology of the water-bearing/resisting layer in th...Non-liner wave equation inversion,wavelet analysis and artificial neural networks were used to obtain stratum parameters and the distribution of thin coal seams.The lithology of the water-bearing/resisting layer in the Quaternary system was also predicted.The implementation process included calculating the well log parameters,stratum contrasting the seismic data and the well logs,and extracting,studying and predicting seismic attributes.Seismic inversion parameters,including the layer velocity and wave impedance,were calculated and effectively used for prediction and analysis.Prior knowledge and seismic interpretation were used to remedy a dearth of seismic data during the inversion procedure.This enhanced the stability of the inversion method.Non-linear seismic inversion and artificial neural networks were used to interpret coal seismic lithology and to study the water-bearing/resisting layer in the Quaternary system.Interpretation of the 1～2 m thin coal seams,and also of the water-bearing/resisting layer in the Quaternary system,is provided.The upper mining limit can be lifted from 60 m to 45 m.The predictions show that this method can provide reliable data useful for thin coal seam exploitation and for lifting the upper mining limit,which is one of the principles of green mining.展开更多
A staggered-grid finite difference method is used to model seismic wave records in a coal bearing, porous medium. The variables analyzed include the order of the difference calculations, the use of a perfect match lay...A staggered-grid finite difference method is used to model seismic wave records in a coal bearing, porous medium. The variables analyzed include the order of the difference calculations, the use of a perfect match layer to provide absorbing boundary conditions, the source location, the stability conditions, and dispersion in the medium. The results show that the location of the first derivative of the dynamic variable with respect to space is coincident with the location of the first derivative of the kinematic varable with respect to time. Outgoing waves are effectively absorbed and reflection at the boundary is very weak when more than 20 perfect match layer cells are used. Blot theory considers the liquid phase to be homogeneous so the ratio of liquid to solid exposure of the seismic source depends upon the medium porosity. Numerical dispersion and generation of false frequencies is reduced by increasing the accuracy of the difference calculations and by reducing the grid size and time step. Temporal second order accuracy, a tenth order spatial accuracy, and a wavelength over more than ten grid points gave acceptable numerical results. Larger grid step sizes in the lateral direction and smaller grid sizes in the vertical direction allow control of dispersion when the medium is a low speed body. This provides a useful way to simulate seismic waves in a porous coal bearing medium.展开更多
基金supported financially by the National Key Project(No. 2008ZX05035-005-003)the National Basic Research Program of China (No. 2009CB219603)
文摘A neural network is applied to high-quality 3-D seismic data during micro-seismic facies analysis to perform the waveform analysis and training on single reflection events. Modeled seismic channels are established and the real seismic channels are classified. Thus, a distribution of micro-seismic facies having a high precision over a fiat surface was acquired. This method applied to existing geological data allows the distribution of areas rich in coal bed methane to be clearly defined. A distribution map of the micro-seismic facies in the research area is shown. The data accord well with measured methane con- tents, indicating that the analysis using micro-seismic facies is reliable and effective. This method could be applied to coal bed methane exploration and is of great importance to future exploration work and to an increase in the drilling success rate.
基金the 863 Program Item of Hi-tech Research and Development Program of China Foundation under Grant No.2002AA602012-1Harbin Engineering University Foundation under Grant No. HEUFT05071the Research Fund for the Doctoral Program of Higher Education under Grant No.20070217016.
文摘The control system determines the effectiveness of an underwater hydraulic shock shovel. This paper begins by analyzing the working principles of these shovels and explains the importance of their control systems. A new type of control system’s mathematical model was built and analyzed according to those principles. Since the initial control system’s response time could not fulfill the design requirements, a PID controller was added to the control system. System response time was still slower than required, so a neural network was added to nonlinearly regulate the proportional element, integral element and derivative element coefficients of the PID controller. After these improvements to the control system, system parameters fulfilled the design requirements. The working performance of electrically-controlled parts such as the rapidly moving high speed switch valve is largely determined by the control system. Normal control methods generally can’t satisfy a shovel’s requirements, so advanced and normal control methods were combined to improve the control system, bringing good results.
基金National Natural Science Foundation of China(5 97740 0 5 )
文摘Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was used synthetically. Artificial neural network was combined with genetic algorithm to found integrated AI method of genetic algorithm artificial neural network(GA ANN). Fault recognition and coal seam thickness forecast were carried to completion by case studies. And the research results are satisfactory.
基金Projects 40574057 and 40874054 supported by the National Natural Science Foundation of ChinaProjects 2007CB209400 by the National Basic Research Program of ChinaFoundation of China University of Mining and Technology (OF4471)
文摘Non-liner wave equation inversion,wavelet analysis and artificial neural networks were used to obtain stratum parameters and the distribution of thin coal seams.The lithology of the water-bearing/resisting layer in the Quaternary system was also predicted.The implementation process included calculating the well log parameters,stratum contrasting the seismic data and the well logs,and extracting,studying and predicting seismic attributes.Seismic inversion parameters,including the layer velocity and wave impedance,were calculated and effectively used for prediction and analysis.Prior knowledge and seismic interpretation were used to remedy a dearth of seismic data during the inversion procedure.This enhanced the stability of the inversion method.Non-linear seismic inversion and artificial neural networks were used to interpret coal seismic lithology and to study the water-bearing/resisting layer in the Quaternary system.Interpretation of the 1～2 m thin coal seams,and also of the water-bearing/resisting layer in the Quaternary system,is provided.The upper mining limit can be lifted from 60 m to 45 m.The predictions show that this method can provide reliable data useful for thin coal seam exploitation and for lifting the upper mining limit,which is one of the principles of green mining.
基金supported by the National Basic Research Program of China (Nos.2009CB219603 and 2006CB202209)the National Natural Science Foundation of Special Equipment (No. 50727401)the National Science & Technology Pillar Program in the Eleventh Five-Year PlanPeriod (No. 2007BAK28B03)
文摘A staggered-grid finite difference method is used to model seismic wave records in a coal bearing, porous medium. The variables analyzed include the order of the difference calculations, the use of a perfect match layer to provide absorbing boundary conditions, the source location, the stability conditions, and dispersion in the medium. The results show that the location of the first derivative of the dynamic variable with respect to space is coincident with the location of the first derivative of the kinematic varable with respect to time. Outgoing waves are effectively absorbed and reflection at the boundary is very weak when more than 20 perfect match layer cells are used. Blot theory considers the liquid phase to be homogeneous so the ratio of liquid to solid exposure of the seismic source depends upon the medium porosity. Numerical dispersion and generation of false frequencies is reduced by increasing the accuracy of the difference calculations and by reducing the grid size and time step. Temporal second order accuracy, a tenth order spatial accuracy, and a wavelength over more than ten grid points gave acceptable numerical results. Larger grid step sizes in the lateral direction and smaller grid sizes in the vertical direction allow control of dispersion when the medium is a low speed body. This provides a useful way to simulate seismic waves in a porous coal bearing medium.
