arrow
Return

The W transform

delete2021-01-01
delete41
PRE
AI
Y
Yanghua Wang *
DOI:10.1190/GEO2020-0316.1delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Time-frequency spectral analysis methods such as the S transform cannot appropriately present low-frequency anomalies in seismic traces because they generate a time-frequency spectrum with a low resolution in time at low frequencies. I have developed the W transform to improve the time resolution of the spectrum at low frequencies, for an effective detection of seismic anomalies related to hydrocarbon reservoirs in petroleum exploration and abnormal features in near surface geophysics. The W transform has three features: (1) the spectral energy is concentrated around the dominant frequency of a seismic waveform, rather than being shifted toward higher frequencies by the S transform; (2) the implementation is numerically stable because it avoids any potential frequency singularity in the S transform; (3) the Gaussian window function is defined using a nonstationary frequency weight, rather than using a stationary frequency weight in the S transform, because the dominant frequency is a time dependent function. Therefore, the time-frequency spectrum generated by the W transform appropriately represents seismic properties varying with geologic depth, and it has an improved time resolution at low frequencies that makes it suitable for characterizing reservoirs in petroleum geophysics and for detecting karsts in construction engineering.
Keywords:
S-TRANSFORM
FREQUENCY
DECOMPOSITION
SPECTRUM
PHASE
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Geophysics cover
Geophysics
IF:
3.2
Papers:
8.4K
Citations:
3.3W

Organization

I
Imperial College London
Scholars:
8.3W
Papers: 7.3W
Citations: 11.1W
Cited Papers

Cited Papers

CNV analysis in the Lithuanian population
err2016-05-04
err0
errOAAI
errA. Urnikyte; I. Domarkiene; S. Stoma; L. Ambrozaityte; I. Uktveryte; R. Meskiene; V. Kasiulevičius; N. Burokiene; V. Kučinskas
errShare
errSave
Instantons in cutoff theories
err1995-01-01
err0
PREAI
errVincenzo Branchina; Janos Polonyi
errShare
errSave
Study on temperature calibration of a silicon substrate in a temperature programmed desorption analysis
err2001-07-01
err0
PREAI
errN. Hirashita; T. Jimbo; T. Matsunaga; M. Matsuura; M. Morita; I. Nishiyama; M. Nishizuka; H. Okumura; A. Shimazaki; N. Yabumoto
errShare
errSave
<p>Patterns of Glucose Fluctuation are Challenging in Patients Treated for Non-Hodgkin’s Lymphoma</p>
err2020-04-01
err0
errOAAI
errAndreja Marić; Tanja Miličević; Jelena Vučak Lončar; Davor Galušić; Maja Radman
errShare
errSave
err
IF0
err
err0
PREAI
err
errShare
errSave
researcher View more