Abstract

Geological structures play a leading role in the occurrence characteristics of coalbed methane (CBM), and curvature attributes are an important geometric seismic attribute that can be used to identify a geological structure. In view of the characteristics of curvature attributes which are easily affected by noise, this paper proposes a method based on variational mode decomposition and correlation coefficients (VMDC) for denoising, and then extracts curvature attributes for geological structure interpretation. The geological models with anticline, syncline and normal fault structure characteristics are constructed, and curvature attributes of geological models without noise and with different percentages of random noise are calculated respectively. According to the time window test results, the 5 × 5 time window is more suitable in the case of no noise, while 9 × 9 time window is more suitable when there is noise. The results also show that both the median filtering and VMDC can suppress random noise, but VMDC can suppress noise better and improve the accuracy of curvature attributes. Mean curvature attributes can effectively identify geological structures such as anticlines, synclines and faults. Gauss curvature is not ideal for identifying geological structures. Both the maximum positive curvature and the minimum negative curvature have obvious responses to some geological structures. The method has been applied to a CBM enrichment area prediction in Qinshui Basin, China, and the geological structure characteristics of this area have been preliminarily interpreted. The known CBM content information verifies the feasibility and effectiveness of the proposed method.

Highlights

  • Coalbed methane (CBM) is one type of coal associated natural gases in coal seams with the methane as the main component

  • In view of the characteristics of curvature attributes which are easy to be affected by noise, this paper proposes a denoising method of seismic data based on variational mode decomposition and correlation coefficients (VMDC) and extracts curvature attributes for geological structure interpretation

  • In order to analyze the influence of different time windows on noise in curvature attributes, 2%, 5%, 10%, and 20% Gaussian random noise is added to the horizon curve

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Summary

Introduction

Coalbed methane (CBM) is one type of coal associated natural gases in coal seams with the methane as the main component. Curvature attribute is a method of structural interpretation using the degree of curvature of seismic reflection data. Huang et al [35] developed a method for seismic data random noise attenuation based on VMD and correlation coefficients. In view of the characteristics of curvature attributes which are easy to be affected by noise, this paper proposes a denoising method of seismic data based on variational mode decomposition and correlation coefficients (VMDC) and extracts curvature attributes for geological structure interpretation. This method is applied to the prediction of the coalbed methane enrichment area

Curvature Attributes
Geological
Time window test of Curvature Attribute
Horizon
Response of Curvature
Response of Curvature Attributes to Geological Structural
11. Horizon curve curvature attributes without noise:
12. Horizon
14. Horizon
Case Study
Findings
Conclusions
Full Text
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