Results 151 to 160 of about 6,445 (232)

Investigation into the variation characteristics and influencing factors of coalbed methane gas content in deep coal seams. [PDF]

Sci Rep
Zhu Q, Du X, Zhang T, Yu H, Liu X.
europepmc   +1 more source

Microporous Adsorbents for CH₄ Capture and Separation from Coalbed Methane with Low CH₄ Concentration: Review. [PDF]

Nanomaterials (Basel)
Wei X, Xia Y, Wei S, Chen Y, Yang S.
europepmc   +1 more source

Gas content, geochemical characteristics and implications of coalbed methane from the Deep Area of Qi'Nan Coalmine in Huaibei Coalfield. [PDF]

Sci Rep
Wei Q, Chen S, Yi W, Gui H, Jiang W, Li F, Li S.   +6 more
europepmc   +1 more source

Critical depth prediction based on in-situ stress and gas content model of deep coalbed methane in Liupanshui Coalfield in China. [PDF]

Sci Rep
Lv F, Yang R, Gao W, Zhao L, Liu Y, Yan Z, Shi F, Zhang B, Tang J, Yi T.   +9 more
europepmc   +1 more source

Methane Adsorption During Pore Evolution and Its Microscale Impact on Coalbed Methane Recovery: A Case Study of Middle- and High-Rank Coals in the Western Guizhou. [PDF]

ACS Omega
Xu A, Han S, Wei Y, Zhou P, Zhang J, Guo Z.   +5 more
europepmc   +1 more source

National Coalbed Methane Database

, 2000
F M Dawson, W J McDougall, T C Anderson, D E Pearson, T M Molnar   +4 more
openaire   +1 more source

Genesis and Accumulation Modes of Coalbed Methane at the Eastern Margin of Ordos Basin, China: Evidence from Its Geochemistry. [PDF]

ACS Omega
Li Z, Chen S, Tang D, Zhi Y.
europepmc   +1 more source

Study on the Spontaneous Combustion Law of Coal Body around a Borehole Induced by Pre-extraction of Coalbed Methane. [PDF]

ACS Omega
Guo J, Zhang X, Liu Y, Cai G, Liu H, Chen C, Wang L.   +6 more
europepmc   +1 more source

Optimized Random Forest Method for 3D Evaluation of Coalbed Methane Content Using Geophysical Logging Data. [PDF]

ACS Omega
Guo J, Zhang Z, Guo G, Xiao H, Zhao Q, Zhang C, Lv H, Zhu Z, Wang C.   +8 more
europepmc   +1 more source

Enhanced coalbed methane well production prediction framework utilizing the CNN-BL-MHA approach. [PDF]

Sci Rep
Li X, Li X, Xie H, Feng C, Cai J, He Y.
europepmc   +1 more source