Simulative Density Inversion Method for Qualitative and Quantitative Forecasting of Coal Bed Methane

To achieve a reasonable assessment on coal bed methane in SH work area, we further analyze the logging and drilling data and seismic data. Combining with the measured data of coal bed methane content of coal sample, we conduct mathematical statistics regression analysis and BP neural network analysis, and make scientific transformation of logging curves to achieve the transformation of air containing discrete points to a continuous line distribution, and get the intuitive continuous gas content data. Combined with improved and more flexible pseudo-acoustic impedance pre-stack and post-stack inversion method to obtain the corresponding analog-acoustic impedance body and simulative density body and realize the distribution of gas content from line to body, and to do a regional assessment of gas content more macroscopically and fine interpretation of qualitative and quantitative to improve the accuracy of gas reservoir description.