Recent progress of quantitative prediction of tectonic coal thickness

MA Li; CHEN Tongjun; WANG Xin; MA Guodong

doi:10.3969/j.issn.1001-1986.2018.05.011

Volume 46 Issue 5

Oct. 2018

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COAL GEOLOGY & EXPLORATION > 2018 > 46(5): 66-72. > DOI: 10.3969/j.issn.1001-1986.2018.05.011

MA Li, CHEN Tongjun, WANG Xin, MA Guodong. Recent progress of quantitative prediction of tectonic coal thickness[J]. COAL GEOLOGY & EXPLORATION, 2018, 46(5): 66-72. DOI: 10.3969/j.issn.1001-1986.2018.05.011

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Recent progress of quantitative prediction of tectonic coal thickness

MA Li¹,
CHEN Tongjun^2,3, ,,
WANG Xin⁴,
MA Guodong^2,3

1. Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Land and Resources, Xi'an 710021, China;
2. Key Laboratory of CBM Resource & Reservoir Formation Process, Ministry of Education, Xuzhou 221008, China;
3. School of Resource and Earth Science, China University of Mining and Technology, Xuzhou 221116, China;
4. School of Computer Science, China University of Mining and Technology, Xuzhou 221116, China

Funds:

National Natural Science Foundation of China(41774128,41704115,41430317)

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Received Date: May 11, 2018
Published Date: October 24, 2018

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Abstract

Abstract

TDCs(Tectonically deformed coal) are obviously different from normal coal in physical characteristics. It is one of the key factors needed to be considered in CBM(coalbed methane) reservoir modeling. In order to figure out the issue of TDC thickness prediction, we analyzed the recent progress in TDC identification and thickness prediction using well logs and seismic attribution as inputs. Compared with the interactive recognition using well logs, the method for identifying TDCs based on wavelet multi-scale analysis and cluster analysis has higher accuracy and better reliability. Combining with seismic attributes and machine learning algorithms, one can produce a deterministic prediction of TDC thickness with more accuracy. Combining with seismic attributes and geostatistical stochastic simulation, one can produce a non-deterministic prediction of TDC thickness with higher reliability. Although the prediction of TDC thickness has been proceeded for many years, the prediction of TDC types and spatial characteristics still need further study.
- tectonic coal,
- identification,
- well log,
- seismic attribute,
- prediction

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