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=Volume 10 - 2022

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, as one of the important parameters of the coalbed methane (CBM) reservoirs, runs through the whole stage of coal mine resource exploration and exploitation and is also a significant parameter for assessing the CBM content. Using the geophysical logging data to predict the content of industrial components is the most widely used method at present. In this paper, the PZ block in the Qinshui Basin is used as the target block to evaluate the ash (Aad), fixed carbon (FCad), volatile matter (Vdaf), and moisture (Mad) in the air-dry (AD) base condition using the autocorrelation between the geophysical logging curves and the industrial component contents, combined with the OBGM (1, N) model. The results show that: (1) The geophysical logging curves combined with the OBGM (1, N) model can accurately predict the Aad and FCad contents, and the increase of geophysical logging curve types can effectively enhance the model performance compared with using a single geophysical logging curve for prediction; (2) When predicting the Vdaf content, the use of the geophysical logging curves combined with the Aad and FCad contents has the highest prediction accuracy and no bias in prediction compared with only using the geophysical logging curve or the autocorrelation between the contents of industrial component. The entire evaluation process begins with the assessment of the Aad content and FCad content. Next, the Vdaf content is assessed using the content of these two industrial components above combined with the geophysical logging data. Finally, the Mad content is calculated using the volumetric model, and accurate application results are obtained in the verification of new wells, demonstrating the efficacy of the method and procedure described in this paper. (3) The OBGM (1, N) model has the highest prediction accuracy compared with the multiple regression model and GM (0, N) model, which have the same computational cost. The geophysical logging interpretation model of industrial component contents of coalbeds proposed in this paper is simple in calculation and suitable for small samples, which provides a new idea for the evaluation process of industrial component contents.