An improved matching pursuit method for coal seam identification driven by seismic inversion

Seismic response of multi-type oil and gas reservoirs is easily disturbed by coal seam reflections. Effective identification and removal methods of coal seam seismic response is one of the key technologies to improve the accuracy of seismic interpretation. Conventional identification method of coal seam lacks consideration of the influence of elastic parameters of coal seam, which leads to the issues of inaccurate identification of coal seam and low computational efficiency. In this paper, elastic parameters are considered to have a better indication for the coal seam, we thus propose an improved coal seam identification method driven by seismic inversion. Firstly, the indicator factor of coal seam is constructed based on the rock physical analysis, and the inversion method based on the matching pursuit for the indicator factor is then proposed to describe the distribution of the coal seam. Thus, the prior information of the coal seam position is obtained based on the seismic inversion, which is introduced into the matching pursuit algorithm to improve computational efficiency. Moreover, Empirical Mode Decomposition(EMD)is introduced into the matching pursuit algorithm to improve computational efficiency to some extent. And the instantaneous phase is replaced by the continuous phase to enhance the matching pursuit computational efficiency. An improved matching pursuit coal seam recognition algorithm based on EMD dictionary constrained by coal seam indication factor is proposed. Model tests demonstrate the feasibility of the proposed method for coal seam identification. The test results of the field data show that the method improves the computational efficiency greatly while maintaining the accuracy. In addition, The predicted coal seam has high similarity with the well logs, which are helpful to reservoir and hydrocarbon identification. Therefore, the proposed method has important practical significance.