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
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.