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Thin coalbed methane reservoir identification by geostatistics inversion

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Abstract

On the basis of conventional impedance inversion,geostatistics inversion can improve the vertical resolution of inversion results.This paper shows an example of thin coalbed methane(CBM) reservoir prediction based on 3D seismic data in E Basin,China.The lateral variogram is derived from the sparse spike impedance inversion and impedance values cross wells are interpolated by random simulation.By consistent iteration with seismic data,geostatistics inversion results are obtained,which match very well logging data.These results describe precisely distributional characteristics of thin CBM reservoirs.This new idea for thin CBM reservoir prediction is more accurate than conventional post-stack inversion.

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What this paper is about

On the basis of conventional impedance inversion,geostatistics inversion can improve the vertical resolution of inversion results.This paper shows an example of thin coalbed methane(CBM) reservoir prediction based on 3D seismic data in E Basin,China.The lateral variogram is derived from the sparse spike impedance inversion and impedance values cross wells are interpolated by random simulation.By consistent iteration with seismic data,geostatistics inversion results are obtained,which match very well logging data.These results describe precisely distributional characteristics of thin CBM reservoirs.This new idea for thin CBM reservoir prediction is more accurate than conventional post-stack inversion.

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Available abstract

On the basis of conventional impedance inversion,geostatistics inversion can improve the vertical resolution of inversion results.This paper shows an example of thin coalbed methane(CBM) reservoir prediction based on 3D seismic data in E Basin,China.The lateral variogram is derived from the sparse spike impedance inversion and impedance values cross wells are interpolated by random simulation.By consistent iteration with seismic data,geostatistics inversion results are obtained,which match very well logging data.These results describe precisely distributional characteristics of thin CBM reservoirs.This new idea for thin CBM reservoir prediction is more accurate than conventional post-stack inversion.

Key concepts: Inversion (geology), Variogram, Seismic inversion, Geostatistics, Geology, Coalbed methane, Reservoir modeling, Structural basin

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