期刊
FUEL
卷 139, 期 -, 页码 257-267出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2014.08.054
关键词
Coal rank; Adsorption capacity; Permeability; Pore structure
资金
- National Natural Science Foundation of China [41272175]
- National Basic Research Program of China (973) [902009CB219600]
- Key Project of the National Science Technology [2011ZX05034]
- Fundamental Research Funds for the Central Universities [2652013056]
- Chinese Scholarship Council
The coal and coalbed methane (CBM) resources are abundant in western Guizhou and eastern Yunnan, South China. However, commercial CBM production in this region has not been achieved. Reservoir properties are the prerequisites in determining the possibility of CBM exploration and its development potential. Thus, to help to select the most favorable block and to prioritize CBM development in the study area, a comprehensive program of experimental work has been carried out to study the physical properties of coal reservoirs in different blocks. Experimental results show that the properties of coal reservoir change significantly with respect to coal rank, and the coal rank in the study area is very uneven, with the vitrinite reflectance (R-o) of coal samples ranging from 0.68% to 3.31%. In detail, low rank coals have well developed seepage pores but undeveloped adsorption pores, resulting in the low adsorption capacity and high porosity and permeability. With burial depth increase, the metamorphic degree and compaction degree of coals grow accordingly, as a result pores and fractures are gradually closed under stress, leading to a sharp reduction of porosity and permeability in medium rank coals. However, most of the high rank coals in the study area have experienced a large number of tectonic thermal events, which not only increased the metamorphism degree and adsorption capacity, but also improved the porosity and permeability of the coal reservoirs. Based on experimental results, the CBM potentials of coal reservoirs in different blocks in the study area were evaluated using multi-objective and multi-level fuzzy optimization model, and the most prospective zones for CBM production were suggested. (C) 2014 Elsevier Ltd. All rights reserved.
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