Well logging technology in coalbed methane （CBM） exploration may develop in two directions： one is the novel well logging methods; the other is the new interpretation methods for the conventional logging data, on w...Well logging technology in coalbed methane （CBM） exploration may develop in two directions： one is the novel well logging methods; the other is the new interpretation methods for the conventional logging data, on which the authors of this paper concentrated mainly. The paper introduced several methods in calculating with well logs such important parameters as porosity, permeability and gas content of CBM reservoir and evaluated their effectiveness. A new method of well logging data interpretation was put forward for coalbed recognition, i.e., the combination of the principal component analysis and the wavelet transform. The authors find that the second principal component （PCA2） contains much more information of coalbed in the coal-bearing series and the reconstruction signal from the detailed wavelet coefficients at level 4 （PCA24） and 5 （PCA25） highlights the signature ofcoalbeds. In terms of the characteristics of CBM reservoir in China, the authors summarized the key points in the application of well logging technique to CBM exploration, and gave a guideline for further related research work.展开更多
Discriminating internal layers by radio echo sounding is important in analyzing the thickness and ice deposits in the Antarctic ice sheet.The signal processing method of synthesis aperture radar(SAR)has been widely us...Discriminating internal layers by radio echo sounding is important in analyzing the thickness and ice deposits in the Antarctic ice sheet.The signal processing method of synthesis aperture radar(SAR)has been widely used for improving the signal to noise ratio(SNR)and discriminating internal layers by radio echo sounding data of ice sheets.This method is not efficient when we use edge detection operators to obtain accurate information of the layers,especially the ice-bed interface.This paper presents a new image processing method via a combined robust principal component analysis-total variation(RPCA-TV)approach for discriminating internal layers of ice sheets by radio echo sounding data.The RPCA-based method is adopted to project the high-dimensional observations to low-dimensional subspace structure to accelerate the operation of the TV-based method,which is used to discriminate the internal layers.The efficiency of the presented method has been tested on simulation data and the dataset of the Institute of Electronics,Chinese Academy of Sciences,collected during CHINARE 28.The results show that the new method is more efficient than the previous method in discriminating internal layers of ice sheets by radio echo sounding data.展开更多
基金This work was supported by Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry （2006331）, China Postdoctoral Science Foundation （20070411106） and Open Fund of Key Laboratory of Depositional Mineralization ＆ Sedimentary Mineral, Shandong Province （DMSM200802）.
文摘Well logging technology in coalbed methane （CBM） exploration may develop in two directions： one is the novel well logging methods; the other is the new interpretation methods for the conventional logging data, on which the authors of this paper concentrated mainly. The paper introduced several methods in calculating with well logs such important parameters as porosity, permeability and gas content of CBM reservoir and evaluated their effectiveness. A new method of well logging data interpretation was put forward for coalbed recognition, i.e., the combination of the principal component analysis and the wavelet transform. The authors find that the second principal component （PCA2） contains much more information of coalbed in the coal-bearing series and the reconstruction signal from the detailed wavelet coefficients at level 4 （PCA24） and 5 （PCA25） highlights the signature ofcoalbeds. In terms of the characteristics of CBM reservoir in China, the authors summarized the key points in the application of well logging technique to CBM exploration, and gave a guideline for further related research work.
基金supported by the National Hi-Tech Research and Development Program of China("863"Project)(Grant No.2011AA040202)the National Natural Science Foundation of China(Grant No.40976114)
文摘Discriminating internal layers by radio echo sounding is important in analyzing the thickness and ice deposits in the Antarctic ice sheet.The signal processing method of synthesis aperture radar(SAR)has been widely used for improving the signal to noise ratio(SNR)and discriminating internal layers by radio echo sounding data of ice sheets.This method is not efficient when we use edge detection operators to obtain accurate information of the layers,especially the ice-bed interface.This paper presents a new image processing method via a combined robust principal component analysis-total variation(RPCA-TV)approach for discriminating internal layers of ice sheets by radio echo sounding data.The RPCA-based method is adopted to project the high-dimensional observations to low-dimensional subspace structure to accelerate the operation of the TV-based method,which is used to discriminate the internal layers.The efficiency of the presented method has been tested on simulation data and the dataset of the Institute of Electronics,Chinese Academy of Sciences,collected during CHINARE 28.The results show that the new method is more efficient than the previous method in discriminating internal layers of ice sheets by radio echo sounding data.
