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.
Funder
the Fundamental Research Funds for the Central Universities
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)
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