Uncertainty in estimation of coalbed methane resources by geological modelling

Abstract

This paper presents an uncertainty analysis of coalbed methane resources estimation for a coal seam gas field containing multiple coal seams. Firstly, logs from nine wells and laboratory data from nine coal seams were used to predict the coal thickness, ash content and gas content at nine boreholes. Secondly, the structural models were determined using the well correlation, structural contour and coal seam thicknesses maps from coal mine data by the convergent gridder and sequential Gaussian simulation methods. Then, distributions of coal density and ash content were generated in 3D by using sequential Gaussian simulation based on the well log interpretations. Then, the distributions of gas content for each cell were built by two methods; one is multivariable regression analysis in 3D and the other is sequential Gaussian simulation based on the log interpreted gas content. Finally, coalbed methane resources were estimated based on the cell volume, coal density, net to gross ratio and gas content. In coalbed methane resources estimation, four different density cutoffs were used to define the net to gross ratio of coal in 3D. Results show that the gas contents decreases with increase in depth though with increases of vitrinite reflectance ratio, fixed carbon content and pressure. Calculated gas content from linear multivariate regression by using parameters of ash content, volatile matter content and fixed carbon content and sample's burial depth matches well with laboratory measured values. The total coalbed methane resources estimated are similar by the two geological modelling processes, the multivariable regression analysis in 3D and the sequential Gaussian simulation. It has been found that the effects of coal density cutoffs on coalbed methane resources for different coal seams are different.