Open AccessA High-resolution GPR horizon extraction method based on local reflection and global correlation
Author(s) -
Dan Zhu,
Zhibin Shi,
Xiaokai Wang,
Wenchao Chen
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/660/1/012025
Subject(s) - ground penetrating radar , horizon , computer science , dynamic time warping , reflection (computer programming) , geology , noise (video) , radar , algorithm , artificial intelligence , pattern recognition (psychology) , mathematics , image (mathematics) , geometry , telecommunications , programming language
Horizon extraction is a very basic and important part of ground penetrating radar (GPR) interpretation. Most GPR horizon extraction methods are based on local reflection of the GPR event such as the trace correlation algorithm, and hidden Markov model algorithm. These methods use only local structural characteristics of the GPR data and often fail to pick the layer correctly across discontinuous caused by faults and noise. In order to overcome shortcomings of the above methods, a novel method based on gradient structure tensor algorithm (GST) and dynamic time warping algorithm (DTW) is used in this paper to extract the horizon accurately which has been proved to be effective in the complex seismic data. GPR electromagnetic wave and seismic wave have certain similarity in kinematics and dynamics, we apply this method to realistic GPR data and prove its effectiveness.