Classification of Coal Structure Combinations and Their Influence on Hydraulic Fracturing: A Case Study from the Qinshui Basin, China

Du Liu, Yanbin Wang, Xiaoming Ni, Chuanqi Tao, Jingjing Fan, Xiang Wu and Shihu Zhao
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Du Liu: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Yanbin Wang: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Xiaoming Ni: School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, China
Chuanqi Tao: School of Mining Engineering, Liaoning Shihua University, Fushun 113001, China
Jingjing Fan: Research Institute of Petroleum Exploration and Development, Beijing 100083, China
Xiang Wu: China United Coalbed Methane Co., Ltd., Beijing 100011, China
Shihu Zhao: College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China

Energies, 2020, vol. 13, issue 17, 1-24

Abstract: Coal structure directly correlates to permeability and hydraulic fracturing effects. Underground coal mining indicates that a single coal section generally contains multiple coal structures in superposition, making how to recognise the coal structure combination and predict its influence on coal permeability a challenging problem. Based on well-drilling sampled cores, the geological strength index (GSI), and well-logging data, the DEN, GR, CALX, and CALY were selected to establish a model to predict GSI by multiple regression to identify coal structure from 100 coalbed methane wells. Based on fitting GSI and corresponding permeability test values, injection fall-off (IFO) testing, and hydraulic fracturing results, permeability prediction models for pre- and post-fracturing behaviour were established, respectively. The fracturing effect was evaluated by the difference in permeability. The results show that a reservoir can be classified into one of nine types by different coal structure thickness proportion (and combinations thereof) and the fracturing curves can be classified into four categories (and eight sub-categories) by the pressure curve. Up-down type I and type II reservoirs (proportion of hard coal >60%) and intervening interval type I reservoir (proportion of hard coal >70%) are prone to form stable and descending fracturing curves and the fracturing effects are optimal. Intervening interval type II (hard coal:soft coal:hard coal or soft coal:hard coal:soft coal ≈1:1:1) and up-down type III (hard coal:soft coal =1:1) form descending type II, rising type I and fluctuating type I fracturing curves and fracturing effect ranks second; up-down type IV and V (proportion of hard coal <40%), interval type III (proportion of hard coal <30%), and multi-layer superposition-type reservoirs readily form fluctuating and rising fracturing curves and fracturing effects therein are poor. The research results provide guidance for the targeted stimulation measured under different coal structure combinations.

Keywords: Shizhuangnan Block; coal structure combinations; fracturing curves; fracturing effect (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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