AUTHOR=Guo Jianhong , Zhang Zhansong , Xiao Hang , Zhang Chaomo , Zhu Linqi , Wang Can TITLE=Quantitative interpretation of coal industrial components using a gray system and geophysical logging data: A case study from the Qinshui Basin, China JOURNAL=Frontiers in Earth Science VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2022.1031218 DOI=10.3389/feart.2022.1031218 ISSN=2296-6463 ABSTRACT=

The content of industrial components of coalbeds, one of the main parameters of coalbed methane (CBM) reservoirs, is crucial in the entire coal mine resource exploration and exploitation process. Currently, using geophysical logging data to determine the content of industrial components is the most widely implemented method. In this study, the PZ block in the Qinshui Basin was employed as a target block to evaluate ash (Aad), fixed carbon (FCad), volatile matter (Vdaf), and moisture (Mad) under the air-dry (AD) base condition based on the autocorrelation between the geophysical logging curves and industrial component contents combined with the OBGM (1, N) model. The results indicate that 1) the geophysical logging curves combined with the OBGM (1, N) model can accurately predict the Aad and FCad contents and an increase in geophysical logging curve types can effectively improve the model performance, compared to using a single geophysical logging curve for prediction. 2) When predicting the Vdaf content, using the geophysical logging curves combined with Aad and FCad contents had the highest prediction accuracy. Further, prediction bias does not exist, compared to using only the geophysical logging curve or the autocorrelation between the industrial component contents. The entire evaluation process begins with an assessment of the Aad and FCad contents. Then, the Vdaf content was assessed using the content of these two industrial components combined with geophysical logging data. Finally, the Mad content was calculated using the volumetric model. Accurate application results were obtained for the verification of new wells, demonstrating the efficacy of the method and procedure described in this study. 3) The OBGM (1, N) model has the highest prediction accuracy compared with the multiple regression and GM (0, N) models, which have the same computational cost. The geophysical logging interpretation model of the proposed coalbed industrial component contents is simple to calculate and suitable for small samples, providing a new method for the evaluation process of industrial component contents.