399 / 2024-03-29 18:25:26
Estimating coal measures associated geothermal resources using Monte Carlo simulation in the Pingdingshan Coalfield, China
geothermal resources; coal measures associated geothermal; Monte Carlo simulation; the volumetric method; evaluation of thermal storage resources
Draft Accepted
Yanhe Li / China University of Mining and Technology, School of Mines;Pingdingshan Tianan Coal. Mining Co.,Ltd
Zhijun Wan / China University of Mining and Technology, School of Mines;Key Laboratory of Deep Coal Resource Mining (CUMT), Ministry of Education
Peng Shi / China University of Mining and Technology, School of Mines
Yuan Zhang / China University of Mining and Technology, School of Mines
Zheng Zhen / China University of Mining and Technology, School of Mines
 As a renewable clean energy associated with coal measures, mine geothermal is being widely developed. Accurate evaluation of coal measures associated geothermal resources can help us realize the effective development and utilization of deep minerals and geothermal energy. The most widely used evaluation method in geothermal resources is the static volume method. However, this approach only assigns specific values to the parameters and ignores the dynamics of the input parameters. Therefore, this paper takes the Cambrian limestone heat storage in the eastern mining area of Pingdingshan Coalfield as a case study. Based on the volume method, the Monte Carlo method is adopted to reduce the uncertainty of input parameters, to more accurately estimate the geothermal resources associated with coal measures in the eastern mining area of Pingdingshan coalfield. When the Monte Carlo method is applied to the evaluation of heat storage resources, triangle, and uniform distribution models are used as input parameters, and the number of simulation iterations is 10000. The results show that the heat contained in geothermal resources is (5.037 ~ 15.82) × 1014 J (most likely 9.538 × 1014 J, the probability is greater than 7.8%), in which the heat contained in geothermal water is (0.8806 ~ 6.531) × 1014 J (most likely 3.196 × 1014 J, probability greater than 7.1%), and the heat contained in the rock matrix of Cambrian limestone is (3.287 ~ 10.36) × 1014 J (most likely 6.341 × 1014 J, probability greater than 7.3%). On this basis, the theoretical and technical framework of coal thermal co-mining is proposed to realize the collaborative mining of coal measures associated geothermal resources.

 
Important Date
  • Conference Date

    May 29

    2024

    to

    Jun 01

    2024

  • May 08 2024

    Draft paper submission deadline

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China University of Mining and Technology