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Application of Seismic Inversion in the Prediction of Coal Bed Methane Reservoir: A Case Study


In recent years, coal bed methane (CBM) exploration and development in China has become a hot topic. Methane (CH4), as the main ingredient of CBM's, occurs in the coal seam mainly in an adsorbed state. The LP group of the CBM reservoir with the depth of about 1200m is newly discovered in Sichuan Basin, China. This CBM reservoir deposited in a relatively stable environment, with features of low density and low P-wave velocity, and is largely different in acoustic impedance from its neighbor layers. In the seismic section, the reflection of the reservoir appears as a strong energy, continuous events with high signal to noise ratio. Identification of the vertical and lateral distribution of CBM reservoirs is one of the most important tasks in CBM exploration. The available data in the study area are 3D seismic data of 255 sq.km. and more than 50 wells. The goal of this study is to map the reservoir distribution and improve strategies for the gas field development. The logging data with crossplot analysis shows that the CBM reservoir presents low P-wave impedance and high Gamma Ray, and obviously the coal can be differentiated from sandstone and mudstone by P-wave impedance. Therefore, seismic inversion has been applied to obtain high-resolution P-wave impedance using both seismic and well log data, and then further to describe the CBM reservoir. In order to obtain more reliable P-wave impedance cube, the following prepared works should be done carefully, such as well data processing and normalization, fine synthetic seismogram calibration, delicate horizon tracking and interpretation, and reasonable geological modeling and so on. Based on the above, the sequential indicator simulation method has been applied to get the volume of coal's probability density, and the volume is used to indicate the distribution of the coal in vertical and horizontal, which can give more precise and higher resolution result of the CBM reservoir than the seismic data's. The main product of this study is a map that described the spatial distribution of coal bed methane reservoir using the seismic inversion and sequential indicator simulation method. This in turn allows for optimizing locations of both vertical and horizontal wells.