Received date: 2016-06-15
Revised date: 2016-10-27
Online published: 2017-02-10
With the rapid economic development and sustained growth in demand for clean energy,the contradiction of China’s energy supply shortage is increasingly highlighted.The wild distribution of China’s coal-bed methane (CBM) resources accelerates the exploration and development of CBM.It is the need of national energy security,and conforms to the new energy strategy of CNPC.Because the biggest difference between the CBM and the conventional gas is that the gas adsorption in coal pore surface,and CBM has the distinctive feature of reservoir distribution characteristics and controlling factors,compared with the conventional natural gas exploration,the exploration aiming for CBM reservoir physical & gas-bearing property,has higher requirement on data quality,prediction method and information content.Basic research on the rock physics is the starting point and foothold of CBM prediction method.Considering the diversity of sedimentary coal seam in china,by selecting the coal sample with different coal rank,different coal rock and different coal quality,through the laboratory testing parameters and actual drilling data analysis,we confirmed that the modulus properties are more sensitive to the tons of coal containing gas,and between the p-wave velocity and density,the density is more sensitive to the tons of coal containing gas than P-wave velocity.According to this,we established the CBM seismic three-parameter elastic modulus (lame constant relative variation,shear modulus relative variation,density relative variation) inversion method.Through the instance of Southern Sichuan,we proved that the relative modulus variation can effectively predict the enrichment of CBM enrichment region.Prediction of 5 wells agrees with the production,which improve the success rate of the deployment CBM well.
Guo Xiao-long，Li Xuan，Dai Chun-meng，Bian Hai-jun，Xu Xu-hua，Xu Jing . Research on CBM geophysical prediction[J]. Natural Gas Geoscience, 2017 , 28(2) : 287 -295 . DOI: 10.11764/j.issn.1672-1926.2016.12.010
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