It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations...It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations. First, we use the plane-wave superposition model containing two plane waves with different velocities and able to change the values of phase velocity and group velocity. The numerical results show that whether phase velocity is higher or lower than group velocity, using the slowness-time coherence （STC） method we can only get phase velocities. Second, according to the results of the dispersion analysis and branch-cut integration, in a rigid boundary borehole model the results of dispersion curves and the waveforms of the first-order mode show that the velocities obtained by the STC method are phase velocities while group velocities obtained by arrival time picking. Finally, dipole logging in a slow formation model is investigated using dispersion analysis and real-axis integration. The results of dispersion curves and full wave trains show similar conclusions as the borehole model with rigid boundary conditions.展开更多
In order to solve the difficulty of detailed recognition of subdivisions of structural coal types,a differentiation model that combines BP neural network with an ultrasonic reflection method is proposed.Structural coa...In order to solve the difficulty of detailed recognition of subdivisions of structural coal types,a differentiation model that combines BP neural network with an ultrasonic reflection method is proposed.Structural coal types are recognized based on a suitable consideration of ultrasonic speed,an ultrasonic attenuation coefficient,characteristics of ultrasonic transmission and other parameters relating to structural coal types.We have focused on a computational model of ultrasonic speed,attenuation coefficient in coal and differentiation algorithm of structural coal types based on a BP neural network.Experiments demonstrate that the model can distinguish structural coal types effectively.It is important for the improved ultrasonic differentiation model to predict coal and gas outbursts.展开更多
基金supported by the National Natural Science Foundation of China (Grant No. 40774099, 10874202 and 11134011)National 863 Program of China (Grant No. 2008AA06Z205)
文摘It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations. First, we use the plane-wave superposition model containing two plane waves with different velocities and able to change the values of phase velocity and group velocity. The numerical results show that whether phase velocity is higher or lower than group velocity, using the slowness-time coherence （STC） method we can only get phase velocities. Second, according to the results of the dispersion analysis and branch-cut integration, in a rigid boundary borehole model the results of dispersion curves and the waveforms of the first-order mode show that the velocities obtained by the STC method are phase velocities while group velocities obtained by arrival time picking. Finally, dipole logging in a slow formation model is investigated using dispersion analysis and real-axis integration. The results of dispersion curves and full wave trains show similar conclusions as the borehole model with rigid boundary conditions.
基金Projects 50674093 supported by the National Natural Science Foundation of China20050290010 by the Doctoral Foundation of the Chinese Education Ministry
文摘In order to solve the difficulty of detailed recognition of subdivisions of structural coal types,a differentiation model that combines BP neural network with an ultrasonic reflection method is proposed.Structural coal types are recognized based on a suitable consideration of ultrasonic speed,an ultrasonic attenuation coefficient,characteristics of ultrasonic transmission and other parameters relating to structural coal types.We have focused on a computational model of ultrasonic speed,attenuation coefficient in coal and differentiation algorithm of structural coal types based on a BP neural network.Experiments demonstrate that the model can distinguish structural coal types effectively.It is important for the improved ultrasonic differentiation model to predict coal and gas outbursts.
