Published December 2017 | Version v1
Journal article

Properties of an improved Gabor wavelet transform and its applications to seismic signal processing and interpretation

  • 1. Northwestern Polytechnical University, School of Marine Science and Technology (China)

Description

This paper presents an analytical study of the complete transform of improved Gabor wavelets (IGWs), and discusses its application to the processing and interpretation of seismic signals. The complete Gabor wavelet transform has the following properties. First, unlike the conventional transform, the improved Gabor wavelet transform (IGWT) maps time domain signals to the time-frequency domain instead of the time-scale domain. Second, the IGW's dominant frequency is fixed, so the transform can perform signal frequency division, where the dominant frequency components of the extracted sub-band signal carry essentially the same information as the corresponding components of the original signal, and the subband signal bandwidth can be regulated effectively by the transform's resolution factor. Third, a time-frequency filter consisting of an IGWT and its inverse transform can accurately locate target areas in the time-frequency field and perform filtering in a given time-frequency range. The complete IGW transform's properties are investigated using simulation experiments and test cases, showing positive results for seismic signal processing and interpretation, such as enhancing seismic signal resolution, permitting signal frequency division, and allowing small faults to be identified.

Additional details

Identifiers

Publishing Information

Journal Title
Applied Geophysics (Online)
Journal Volume
14
Journal Issue
4
Journal Page Range
p. 529-542
ISSN
1993-0658

INIS

Country of Publication
China
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
50040625
Subject category
S58: GEOSCIENCES;
Descriptors DEI
FILTERS; FREQUENCY RANGE; MAPS; PROCESSING; RESOLUTION; SEISMIC DETECTION; SEISMICITY; SIGNALS; SIMULATION
Descriptors DEC
DETECTION

Optional Information

Copyright
Copyright (c) 2017 Editorial Office of Applied Geophysics and Springer-Verlag GmbH Germany, part of Springer Nature