Evaluation of the synergetic gas-enrichment and higher-permeability regions for coalbed methane recovery with a fuzzy model

Liu, Huihu, Sang, Shuxun, Wang, Geoff G. X., Li, Yangmin, Li, Mengxi and Liu, Shiqi (2012) Evaluation of the synergetic gas-enrichment and higher-permeability regions for coalbed methane recovery with a fuzzy model. Energy, 39 1: 426-439. doi:10.1016/j.energy.2011.12.027

Author Liu, Huihu
Sang, Shuxun
Wang, Geoff G. X.
Li, Yangmin
Li, Mengxi
Liu, Shiqi
Title Evaluation of the synergetic gas-enrichment and higher-permeability regions for coalbed methane recovery with a fuzzy model
Journal name Energy   Check publisher's open access policy
ISSN 0360-5442
Publication date 2012-03
Sub-type Article (original research)
DOI 10.1016/j.energy.2011.12.027
Volume 39
Issue 1
Start page 426
End page 439
Total pages 14
Editor Abdul Ghani Olabi
Place of publication Oxford, United Kingdom
Publisher Elsevier
Collection year 2013
Language eng
Abstract Determination of the synergetic region with both coalbed methane (CBM) enrichment and higher permeability and its distribution is fundamentally crucial to optimize well design and pattern arrangement for CBM recovery from coal. To address this issue, a predictive model was developed based on fuzzy theory by taking into account the main geological factors that affect the gas enrichment and permeability in coal reservoirs. Following the statistical analysis on a number of geological parameters, Euclid approach degree (a comprehensive evaluation coefficient) and fuzzy matter-elements were determined and integrated into the model. The information entropy method was used to evaluate the effect weight of each geologic factor on overall object of the synergetic gas-enrichment and higher-permeability region. The model was applied to the coal seam No. 3 of a developing coal block in the south of Qinshui basin as an example. The results show that the geological factors such as coal rank, gas saturation, coping thickness, transitional coal structure, and volatile content determine the distributions of the synergetic gas-enrichment and higher-permeability region with higher weight coefficients over 9%. Compared with these key factors, the factors such as coal thickness, gas content, methane concentration, ash content, principal stress difference, fracture density, porosity, and burial depth have only the weight coefficients of <5% and their effects on the synergetic region are very limited. The other factors including reservoir temperature, groundwater level, minimum principal stress, and water content exhibit the moderate impact featured by the weight coefficients varying from 5% to 9%. The model prediction provided a flood/contour map to visualize the synergetic gas-enrichment and higher-permeability regions. With this map, the selected coal block can be classified as extremely favorable, favorable, relatively favorable and unfavorable areas for CBM recovery based on the Euclid approach degree. The extremely favorable and favorable areas mainly distribute in the center and the southwest of the coal block; the relatively favorable area locates in most part of the coal block; unfavorable area dispersedly distributes in the south along the east-west direction. The distribution of the synergetic regions is obviously controlled by the coal structure. The prediction results were verified with the distributions of most CBM wells performed in the same coal block, showing that the model prediction is reasonably agreeable with reality. The model developed in this study can be used as a feasible tool to predict the favorable well locations and optimize the well patterns for CBM recovery.
Keyword Coal reservoir
Coalbed methane
Reservoir evaluation
Fuzzy model
Coalbed methane recovery
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Special Section: Sustainable Energy and Environmental Protection 2010

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Chemical Engineering Publications
Official 2013 Collection
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Citation counts: TR Web of Science Citation Count  Cited 12 times in Thomson Reuters Web of Science Article | Citations
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