Applications of the synchrosqueezing transform in seismic time-frequency analysis

نویسندگان

  • Roberto H. Herrera
  • Jiajun Han
  • Mirko van der Baan
چکیده

Time-frequency representation of seismic signals provides a source of information that is usually hidden in the Fourier spectrum. The short-time Fourier transform and the wavelet transform are the principal approaches to simultaneously decompose a signal into time and frequency components. Known limitations, such as trade-offs between time and frequency resolution, may be overcome by alternative techniques that extract instantaneous modal components. Empirical mode decomposition aims to decompose a signal into components that are well separated in the time-frequency plane allowing the reconstruction of these components. On the other hand, a recently proposed method called the “synchrosqueezing transform” (SST) is an extension of the wavelet transform incorporating elements of empirical mode decomposition and frequency reassignment techniques. This new tool produces a well-defined timefrequency representation allowing the identification of instantaneous frequencies in seismic signals to highlight individual components. We introduce the SST with applications for seismic signals and produced promising results on synthetic and field data examples.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Synchrosqueezing-based Transform and its Application in Seismic Data Analysis

Seismic waves are non-stationary due to its propagation through the earth. Time-frequency transforms are suitable tools for analyzing non-stationary seismic signals. Spectral decomposition can reveal the non-stationary characteristics which cannot be easily observed in the time or frequency representation alone. Various types of spectral decomposition methods have been introduced by some resear...

متن کامل

Time-Frequency Representation of Microseismic Signals using the Synchrosqueezing Transform

Resonance frequencies can provide useful information on the deformation occurring during fracturing experiments or CO2 management, complementary to the microseismic event distribution. An accurate time-frequency representation is of crucial importance prior to interpreting the cause of resonance frequencies during microseismic experiments. The popular methods of Short-Time Fourier Transform (ST...

متن کامل

The Synchrosqueezing transform for instantaneous spectral analysis

The Synchrosqueezing transform is a time-frequency analysis method that can decompose complex signals into time-varying oscillatory components. It is a form of time-frequency reassignment that is both sparse and invertible, allowing for the recovery of the signal. This article presents an overview of the theory and stability properties of Synchrosqueezing, as well as applications of the techniq...

متن کامل

K-Complex Detection Based on Synchrosqueezing Transform

K-complex is an underlying pattern in the sleep EEG. Due to the role of sleep studies inneurophysiologic and cognitive disorders diagnosis, reliable methods for analysis and detection of this patternare of great importance. In our previous work, Synchrosqueezing Transform (SST) was proposed for analysisof this pattern. SST is an EMD-like tool, which benefits from wavelet transform and reallocat...

متن کامل

Application of Single-Frequency Time-Space Filtering Technique for Seismic Ground Roll and Random Noise Attenuation

Time-frequency filtering is an acceptable technique for attenuating noise in 2-D (time-space) and 3-D (time-space-space) reflection seismic data. The common approach for this purpose is transforming each seismic signal from 1-D time domain to a 2-D time-frequency domain and then denoising the signal by a designed filter and finally transforming back the filtered signal to original time domain. ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014