Next Article in Journal
Nonlinear Synergetic Governor Controllers for Steam Turbine Generators to Enhance Power System Stability
Previous Article in Journal
A Predictive Power Control Strategy for DFIGs Based on a Wind Energy Converter System
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Energies 2017, 10(8), 1090; doi:10.3390/en10081090

An Improved Time-Frequency Analysis Method for Hydrocarbon Detection Based on EWT and SET

1
Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China
2
Postdoctoral Station of Geophysics, Chengdu University of Technology, Chengdu 610059, China
*
Author to whom correspondence should be addressed.
Received: 6 July 2017 / Revised: 21 July 2017 / Accepted: 24 July 2017 / Published: 26 July 2017
View Full-Text   |   Download PDF [2918 KB, uploaded 26 July 2017]   |  

Abstract

Oil and gas reservoirs can cause increased attenuation of seismic waves, which can be revealed by time-frequency analysis for direct detection of hydrocarbons. In this paper, a new method applying the empirical wavelet transform (EWT) in association with the synchroextracting transform (SET), named EWT-SET, is proposed as an improved time-frequency analysis method for hydrocarbon detection. The SET is a novel time-frequency analysis method which can be considered as a post-processing procedure of short-time Fourier transform and can improve the energy concentration of the time-frequency representation by retaining only the time-frequency information most related to the signal time-varying features. Given the potential limitations of SET for broadband nonstationary seismic signals, using the EWT-SET method which applies SET to the signal after EWT decomposition, not only effectively extracts time-varying features of seismic signals but also improves the performance of SET in concentrating instantaneous energy. The preliminary model tests demonstrate that EWT-SET can effectively depict the location and extent of attenuation anomalies related to hydrocarbons with changing thicknesses of the gas-bearing layer. Application to field data further confirms the capacity for hydrocarbon detection of the presented method. Thus, the EWT-SET method shows significant application prospects and promotion value for hydrocarbon detection. View Full-Text
Keywords: hydrocarbon detection; time-frequency analysis; synchroextracting transform (SET); empirical wavelet transform (EWT) hydrocarbon detection; time-frequency analysis; synchroextracting transform (SET); empirical wavelet transform (EWT)
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Chen, H.; Kang, J.; Chen, Y.; Xu, D.; Hu, Y. An Improved Time-Frequency Analysis Method for Hydrocarbon Detection Based on EWT and SET. Energies 2017, 10, 1090.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top