The evaluation of potential for the exploration and development of coalbed methane resources based on an improved uncertainty measure optimization model

The recognition criteria of credible degree in uncertainty measure theory are improved based on the concept of distance discriminant and used to evaluate the potential for exploration and development of coalbed methane. This paper uses a systematic approach to establish a mathematical model based on entropy weight and improved uncertainty measure theory. In this model, uncertainty influence factors were analyzed qualitatively and quantitatively using data for the Muli coalfield of Qinghai province, China. The uncertainty measure function is based on experimental data, and the weight of index is determined by entropy weight theory. Optimization credible degree recognition criteria were used to evaluate the potential for coalbed methane exploration and development of six mines in the Muli coalfield. These data indicate that evaluation results obtained using entropy weight and improved uncertainty measure theory have practical application and can effectively assess the exploration and development potential of coalbed methane in a coal basin.

[1]  Xu Wu,et al.  Study and Application of Safety Risk Evaluation Model for CO2 Geological Storage Based on Uncertainty Measure Theory , 2015 .

[2]  Xiang Dong,et al.  Quasi-static Axial Compressive Properties of Al-Mg-Si Alloy Profiles Aged for Different Times , 2012 .

[3]  Hu Si,et al.  Environmental evaluation for sustainable development of coal mining in Qijiang, Western China , 2010 .

[4]  Prashant Singh,et al.  Geological and Petrological Considerations for Coal Bed Methane Exploration: A Review , 2011 .

[5]  Sevket Durucan,et al.  Analytical models for coal permeability changes during coalbed methane recovery: Model comparison and performance evaluation , 2014 .

[6]  A. Busch,et al.  CBM and CO2-ECBM related sorption processes in coal: A review , 2011 .

[7]  Neil Sherwood,et al.  The influence of petrological properties and burial history on coal seam methane reservoir characterisation, Sydney Basin, Australia , 2007 .

[8]  Hujun He,et al.  Study and Application on Stability Classification of Tunnel Surrounding Rock Based on Uncertainty Measure Theory , 2014 .

[9]  Christopher R. Clarkson,et al.  Predicting Sorption-Induced Strain and Permeability Increase With Depletion for Coalbed-Methane Reservoirs , 2010 .

[10]  Debadutta Mohanty,et al.  Thermodynamics, kinetics and modeling of sorption behaviour of coalbed methane – A review , 2016 .

[11]  Luke D. Connell,et al.  An analytical coal permeability model for tri-axial strain and stress conditions , 2010 .

[12]  Yaning Zhao,et al.  Prediction of coalbed methane content based on uncertainty clustering method , 2016 .