In acoustic logging-while-drilling （ALWD） finite difference in time domain （FDTD） simulations, large drill collar occupies, most of the fluid-filled borehole and divides the borehole fluid into two thin fluid colu...In acoustic logging-while-drilling （ALWD） finite difference in time domain （FDTD） simulations, large drill collar occupies, most of the fluid-filled borehole and divides the borehole fluid into two thin fluid columns （radius -27 mm）. Fine grids and large computational models are required to model the thin fluid region between the tool and the formation. As a result, small time step and more iterations are needed, which increases the cumulative numerical error. Furthermore, due to high impedance contrast between the drill collar and fluid in the borehole （the difference is 〉30 times）, the stability and efficiency of the perfectly matched layer （PML） scheme is critical to simulate complicated wave modes accurately. In this paper, we compared four different PML implementations in a staggered grid finite difference in time domain （FDTD） in the ALWD simulation, including field-splitting PML （SPML）, multiaxial PML（M- PML）, non-splitting PML （NPML）, and complex frequency-shifted PML （CFS-PML）. The comparison indicated that NPML and CFS-PML can absorb the guided wave reflection from the computational boundaries more efficiently than SPML and M-PML. For large simulation time, SPML, M-PML, and NPML are numerically unstable. However, the stability of M-PML can be improved further to some extent. Based on the analysis, we proposed that the CFS-PML method is used in FDTD to eliminate the numerical instability and to improve the efficiency of absorption in the PML layers for LWD modeling. The optimal values of CFS-PML parameters in the LWD simulation were investigated based on thousands of 3D simulations. For typical LWD cases, the best maximum value of the quadratic damping profile was obtained using one do. The optimal parameter space for the maximum value of the linear frequency-shifted factor （a0） and the scaling factor （β0） depended on the thickness of the PML layer. For typical formations, if the PML thickness is 10 grid points, the global error can be reduced to 〈1% using the optimal PML parameters, and the error will decrease as the PML thickness increases.展开更多
The existing methods for extracting the arrival time and amplitude of ultrasonic echo cannot eff ectively avoid the local interference of ultrasonic signals while drilling,which leads to poor accuracy of the echo arri...The existing methods for extracting the arrival time and amplitude of ultrasonic echo cannot eff ectively avoid the local interference of ultrasonic signals while drilling,which leads to poor accuracy of the echo arrival time and amplitude extracted by an ultrasonic imaging logging-while-drilling tool.In this study,a demodulation algorithm is used to preprocess the ultrasonic simulation signals while drilling,and we design a backpropagation neural network model to fit the relationship between the waveform data and time and amplitude.An ultrasonic imaging logging model is established,and the finite element simulation software is used for forward modeling.The response under diff erent measurement conditions is simulated by changing the model parameters,which are used as the input layer of the neural network model;The ultrasonic echo signal is considered as a low-frequency signal modulated by a high-frequency carrier signal,and a low-pass fi lter is designed to remove the high-frequency signal and obtain the low-frequency envelope signal.Then the amplitude of the envelope signal and its corresponding time are extracted as an output layer of the neural network model.By comparing the application eff ects of the various training methods,we fi nd that the conjugate gradient descent method is the most suitable method for solving the neural network model.The performance of the neural network model is tested using 11 groups of simulation test data,which verify the eff ectiveness of the model and lay the foundation for further practical application.展开更多
基金supported by NSFC(No.41174118)one of the major state S&T special projects(No.2008ZX05020-004)+1 种基金a Postdoctoral Fellowship of China(No.2013M530106)China Scholarship Council(No.2010644006)
文摘In acoustic logging-while-drilling （ALWD） finite difference in time domain （FDTD） simulations, large drill collar occupies, most of the fluid-filled borehole and divides the borehole fluid into two thin fluid columns （radius -27 mm）. Fine grids and large computational models are required to model the thin fluid region between the tool and the formation. As a result, small time step and more iterations are needed, which increases the cumulative numerical error. Furthermore, due to high impedance contrast between the drill collar and fluid in the borehole （the difference is 〉30 times）, the stability and efficiency of the perfectly matched layer （PML） scheme is critical to simulate complicated wave modes accurately. In this paper, we compared four different PML implementations in a staggered grid finite difference in time domain （FDTD） in the ALWD simulation, including field-splitting PML （SPML）, multiaxial PML（M- PML）, non-splitting PML （NPML）, and complex frequency-shifted PML （CFS-PML）. The comparison indicated that NPML and CFS-PML can absorb the guided wave reflection from the computational boundaries more efficiently than SPML and M-PML. For large simulation time, SPML, M-PML, and NPML are numerically unstable. However, the stability of M-PML can be improved further to some extent. Based on the analysis, we proposed that the CFS-PML method is used in FDTD to eliminate the numerical instability and to improve the efficiency of absorption in the PML layers for LWD modeling. The optimal values of CFS-PML parameters in the LWD simulation were investigated based on thousands of 3D simulations. For typical LWD cases, the best maximum value of the quadratic damping profile was obtained using one do. The optimal parameter space for the maximum value of the linear frequency-shifted factor （a0） and the scaling factor （β0） depended on the thickness of the PML layer. For typical formations, if the PML thickness is 10 grid points, the global error can be reduced to 〈1% using the optimal PML parameters, and the error will decrease as the PML thickness increases.
基金funded by the Sinopec Engineering Technology Research InstituteThe name of the project is the Research and Development of Drilling Wall Ultrasonic Imaging System(No.PE19011-1)。
文摘The existing methods for extracting the arrival time and amplitude of ultrasonic echo cannot eff ectively avoid the local interference of ultrasonic signals while drilling,which leads to poor accuracy of the echo arrival time and amplitude extracted by an ultrasonic imaging logging-while-drilling tool.In this study,a demodulation algorithm is used to preprocess the ultrasonic simulation signals while drilling,and we design a backpropagation neural network model to fit the relationship between the waveform data and time and amplitude.An ultrasonic imaging logging model is established,and the finite element simulation software is used for forward modeling.The response under diff erent measurement conditions is simulated by changing the model parameters,which are used as the input layer of the neural network model;The ultrasonic echo signal is considered as a low-frequency signal modulated by a high-frequency carrier signal,and a low-pass fi lter is designed to remove the high-frequency signal and obtain the low-frequency envelope signal.Then the amplitude of the envelope signal and its corresponding time are extracted as an output layer of the neural network model.By comparing the application eff ects of the various training methods,we fi nd that the conjugate gradient descent method is the most suitable method for solving the neural network model.The performance of the neural network model is tested using 11 groups of simulation test data,which verify the eff ectiveness of the model and lay the foundation for further practical application.
