A new method for the estimation of lost gas during the measurement of the gas content of coal

In this text, the authors present a study on estimating the lost gas during the retrieval process of coal sample within wellbores. A new method is proposed because the traditional ones often give inaccurate predictions. To this end, the major sources of errors with those routine methods are first discussed briefly, and modifications are made accordingly in the present method to improve the accuracy of prediction. This new method takes into account these aspects: (1) Both the advection and diffusion effects are included in the proposed flow equation; (2) the present model uses the actual shape of the core sample (say, a cylinder) rather than a simplified 1D spherical object; and (3) a fully numerical scheme is developed in which the actual retrieval history is used to specify the boundary conditions of the core sample. When the relevant sorption isothermal curve for the coal is known, the proposed model contains three parameters to be determined, which refer to the effective permeability, the effective diffusion coefficient, and the initial gas content or the initial gas pressure. The three parameters are determined through best matching the experimental data with the aid of an artificial-neural-network (ANN) technique. Two application examples are presented in this study. One is with a benchmark laboratory test, and the other is with a standard field case studied by means of an established method. It is shown with the two examples that the present method can give accurate predictions for the lost gas volume concerned, and offers some important advantages that the traditional ones do not have.