Enhancing resolution of nonstationary seismic data by molecular-Gabor transform

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. V31-V41 ◽  
Author(s):  
Lingling Wang ◽  
Jinghuai Gao ◽  
Wei Zhao ◽  
Xiudi Jiang
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Optimization Problem ◽  
Gabor Transform ◽  
Frequency Bandwidth ◽  
Time Frequency ◽  
Text Model ◽  
Amplitude Compensation

We propose an adaptive spectrum-broadening method (ASBM) to improve the resolution of nonstationary seismic data. This method assumes that a seismic trace can be split into segments, each of which can be considered as approximately stationary. We construct a set of specific windows, called molecular-Gabor (MG) windows, by solving an optimization problem, such that the seismic trace in each of the MG windows is stationary. A time-frequency (t-f) transform, called MG transform, can be obtained from a MG frame constructed using the MG windows. For a seismic trace, we first transform it into the t-f domain, then spectrum-broadening and/or amplitude compensation are performed in each of the MG windows. Subsequently, a high-resolution version of the nonstationary seismic trace will be obtained after the inverse MG transform. Applications of this method to synthetic and field data show that the ASBM works well for a general earth [Formula: see text]-model that varies with traveltime. It can restore the attenuated energy and expand the frequency bandwidth of a nonstationary seismic trace effectively. One significant advantage of our method is that it automatically estimates all the parameters that are optimal for each trace.

Poststack velocity analysis by separation and imaging of seismic diffractions

Geophysics ◽  
2007 ◽  
Vol 72 (6) ◽  
pp. U89-U94 ◽  
Author(s):  
Sergey Fomel ◽  
Evgeny Landa ◽  
M. Turhan Taner
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Small Scale ◽  
Velocity Analysis ◽  
High Resolution Imaging ◽  
Diffracted Waves ◽  
Resolution Imaging ◽  
Seismic Reflections ◽  
Optimal Focusing

Small geologic features manifest themselves in seismic data in the form of diffracted waves, which are fundamentally different from seismic reflections. Using two field-data examples and one synthetic example, we demonstrate the possibility of separating seismic diffractions in the data and imaging them with optimally chosen migration velocities. Our criteria for separating reflection and diffraction events are the smoothness and continuity of local event slopes that correspond to reflection events. For optimal focusing, we develop the local varimax measure. The objectives of this work are velocity analysis implemented in the poststack domain and high-resolution imaging of small-scale heterogeneities. Our examples demonstrate the effectiveness of the proposed method for high-resolution imaging of such geologic features as faults, channels, and salt boundaries.

scholarly journals High-resolution coherency functionals for velocity analysis: An application for subbasalt seismic exploration

Geophysics ◽  
2013 ◽  
Vol 78 (5) ◽  
pp. U53-U63 ◽  
Author(s):  
Andrea Tognarelli ◽  
Eusebio Stucchi ◽  
Alessia Ravasio ◽  
Alfredo Mazzotti
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Signal To Noise Ratio ◽  
Synthetic Seismograms ◽  
Seismic Exploration ◽  
Velocity Analysis ◽  
Signal To Noise ◽  
Geologic Setting ◽  
Analytic Signals

We tested the properties of three different coherency functionals for the velocity analysis of seismic data relative to subbasalt exploration. We evaluated the performance of the standard semblance algorithm and two high-resolution coherency functionals based on the use of analytic signals and of the covariance estimation along hyperbolic traveltime trajectories. Approximate knowledge of the wavelet was exploited to design appropriate filters that matched the primary reflections, thereby further improving the ability of the functionals to highlight the events of interest. The tests were carried out on two synthetic seismograms computed on models reproducing the geologic setting of basaltic intrusions and on common midpoint gathers from a 3D survey. Synthetic and field data had a very low signal-to-noise ratio, strong multiple contamination, and weak primary subbasalt signals. The results revealed that high-resolution coherency functionals were more suitable than semblance algorithms to detect primary signals and to distinguish them from multiples and other interfering events. This early discrimination between primaries and multiples could help to target specific signal enhancement and demultiple operations.

Fault interpretation from high‐resolution seismic data in the northern Negev, Israel

Geophysics ◽  
1991 ◽  
Vol 56 (7) ◽  
pp. 1064-1070 ◽  
Author(s):  
Ilan Bruner ◽  
Eugeny Landa
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Dynamic Properties ◽  
Fault Zones ◽  
Diffracted Waves ◽  
Fault Interpretation ◽  
Low Amplitude ◽  
Seismic Lines ◽  
Sense Reverse

Detection and investigation of fault zones are important tools for tectonic analysis and geological studies. A fault zone inferred on high‐resolution seismic lines has been interpreted using a method of detection of diffracted waves utilizing the main kinematic and dynamic properties of the wavefield. The application of the method to field data from the northern Negev in Israel shows that it provides a good estimate of results and, when used in conjunction with the final stacked data, can give the suspected location of the fault, its sense (reverse or normal), and the amount of “low amplitude” displacement (in an order of the wavelength or even less).

Extended stable factor method for the inverse Q-filter

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. T155-T163
Author(s):  
Yong Li ◽  
Gulan Zhang ◽  
Jing Duan ◽  
Chengjie He ◽  
Hao Du ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Time Frequency ◽  
Stable Factor ◽  
Factor Method ◽  
Data Application ◽  
Two Parameters ◽  
Limit Assumption

The commonly used stable factor methods for the inverse [Formula: see text]-filter achieve good performance in seismic data processing; however, the constant gain-limit assumption in these methods is not associated with the effective frequency band of seismic data and cannot obtain desirable results with high resolution and high signal-to-noise ratio (S/N). Our extended stable factor method for the inverse [Formula: see text]-filter extends these methods by introducing two parameters and constant or self-adaptive gain limit to achieve the desirable high-resolution and high-S/N result. The extended stable factor method for the inverse [Formula: see text]-filter can be implemented in the frequency or time-frequency domain; the latter implementation achieves a higher S/N. Analysis of synthetic signals and field seismic data application illustrate that our method can produce a desirable high-resolution and high-S/N result.

Probing the subsurface karst features using time-frequency decomposition

2016 ◽  
Vol 4 (4) ◽  
pp. T533-T542 ◽  
Author(s):  
Yangkang Chen
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Single Frequency ◽  
Frequency Interval ◽  
Data Set ◽  
Time Frequency ◽  
Frequency Decomposition ◽  
Inherent Frequency ◽  
Resolution Mapping ◽  
Resource Exploration

The high-resolution mapping of karst features is of great importance to hydrocarbon discovery and recovery in the resource exploration field. Currently, however, there are few effective methods specifically tailored for such a task. The 3D seismic data can reveal the existence of karsts to some extent, but a precise characterization cannot be obtained. I have developed an effective framework for accurately probing the subsurface karst features using a well-developed time-frequency decomposition algorithm. More specifically, I have introduced a frequency interval analysis approach for obtaining the best karsts detection result using an optimal frequency interval. A high-resolution time-frequency transform was preferred in the proposed framework to capture the inherent frequency components hidden behind the amplitude map. Although the single-frequency slice could not provide a reliable karst depiction result, the summation over the selected frequency interval could obtain a high-resolution and high-fidelity delineation of subsurface karsts. I used a publicly available 3D field seismic data set as an example to indicate the performance of the proposed method.

Mask filtering to the Wigner-Ville distribution

Geophysics ◽  
2021 ◽  
pp. 1-30
Author(s):  
Haifa Alsalmi ◽  
Yanghua Wang
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Energy Concentration ◽  
Cross Term ◽  
Time Frequency ◽  
Stationary Signals ◽  
Spectral Analysis Method ◽  
The Cross ◽  
Data Adaptive ◽  
3D Seismic Data

The Wigner-Ville distribution (WVD) is a high-resolution time-frequency spectral analysis method for non-stationary signals, and yet it suffers from cross-term interference among signal components. We proposed applying a masking filter directly to the WVD time-frequency spectrum to suppress the cross-term interference. Conventional methods for suppressing the interference include the smoothed-pseudo WVD (SP-WVD) method, which incorporates smooth filtering in both time and frequency directions. We exploited the SP-WVD spectrum as a reference to design the masking filter, and thus the mask filtered WVD (MF-WVD) procedure is data adaptive. The MF-WVD method preserves the high-resolution energy concentration in the spectrum portrayed by the standard WVD, while suppressing the cross-term interference cleanly like in the SP-WVD method. Applying the MF-WVD method to field 3D seismic data generates high-resolution spectral cubes for various frequencies, and these spectral cubes may be used intuitively for detecting reservoir-related characteristics.

scholarly journals Seismic Reflection Coefficient Inversion Using Basis Pursuit Denoising in the Joint Time-Frequency Domain

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5025
Author(s):  
Xuegong Zhao ◽  
Hao Wu ◽  
Xinyan Li ◽  
Zhenming Peng ◽  
Yalin Li
Keyword(s):  
High Resolution ◽  
Reflection Coefficient ◽  
Objective Function ◽  
Frequency Domain ◽  
Seismic Data ◽  
Seismic Reflection ◽  
Seismic Inversion ◽  
Frequency Resolution ◽  
Basis Pursuit ◽  
Time Frequency

Seismic reflection coefficient inversion in the joint time-frequency domain is a method for inverting reflection coefficients using time domain and frequency domain information simultaneously. It can effectively improve the time-frequency resolution of seismic data. However, existing research lacks an analysis of the factors that affect the resolution of inversion results. In this paper, we analyze the influence of parameters, such as the length of the time window, the size of the sliding step, the dominant frequency band, and the regularization factor of the objective function on inversion results. The SPGL1 algorithm for basis pursuit denoising was used to solve our proposed objective function. The applied geological model and experimental field results show that our method can obtain a high-resolution seismic reflection coefficient section, thus providing a potential avenue for high-resolution seismic data processing and seismic inversion, especially for thin reservoir inversion and prediction.

Gabor deconvolution: Estimating reflectivity by nonstationary deconvolution of seismic data

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. W15-W30 ◽  
Author(s):  
Gary F. Margrave ◽  
Michael P. Lamoureux ◽  
David C. Henley
Keyword(s):  
Fourier Transform ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Numerical Approach ◽  
Gabor Transform ◽  
Minimum Phase ◽  
Approximate Factorization ◽  
Time Frequency ◽  
Complex Valued

We have extended the method of stationary spiking deconvolution of seismic data to the context of nonstationary signals in which the nonstationarity is due to attenuation processes. As in the stationary case, we have assumed a statistically white reflectivity and a minimum-phase source and attenuation process. This extension is based on a nonstationary convolutional model, which we have developed and related to the stationary convolutional model. To facilitate our method, we have devised a simple numerical approach to calculate the discrete Gabor transform, or complex-valued time-frequency decomposition, of any signal. Although the Fourier transform renders stationary convolution into exact, multiplicative factors, the Gabor transform, or windowed Fourier transform, induces only an approximate factorization of the nonstationary convolutional model. This factorization serves as a guide to develop a smoothing process that, when applied to the Gabor transform of the nonstationary seismic trace, estimates the magnitude of the time-frequency attenuation function and the source wavelet. By assuming that both are minimum-phase processes, their phases can be determined. Gabor deconvolution is accomplished by spectral division in the time-frequency domain. The complex-valued Gabor transform of the seismic trace is divided by the complex-valued estimates of attenuation and source wavelet to estimate the Gabor transform of the reflectivity. An inverse Gabor transform recovers the time-domain reflectivity. The technique has applications to synthetic data and real data.

High-resolution characterization of geologic structures using the synchrosqueezing transform

2017 ◽  
Vol 5 (1) ◽  
pp. T75-T85 ◽  
Author(s):  
Naihao Liu ◽  
Jinghuai Gao ◽  
Zhuosheng Zhang ◽  
Xiudi Jiang ◽  
Qi Lv
Keyword(s):  
High Resolution ◽  
Frequency Analysis ◽  
Seismic Data ◽  
Proper Time ◽  
Frequency Resolution ◽  
Heisenberg Uncertainty Principle ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Basic Wavelet ◽  
Synchrosqueezing Transform

The main factors responsible for the nonstationarity of seismic signals are the nonstationarity of the geologic structural sequences and the complex pore structure. Time-frequency analysis can identify various frequency components of seismic data and reveal their time-variant features. Choosing a proper time-frequency decomposition algorithm is the key to analyze these nonstationarity signals and reveal the geologic information contained in the seismic data. According to the Heisenberg uncertainty principle, we cannot obtain the finest time location and the best frequency resolution at the same time, which results in the trade-off between the time resolution and the frequency resolution. For instance, the most commonly used approach is the short-time Fourier transform, in which the predefined window length limits the flexibility to adjust the temporal and spectral resolution at the same time. The continuous wavelet transform (CWT) produces an “adjustable” resolution of time-frequency map using dilation and translation of a basic wavelet. However, the CWT has limitations in dealing with fast varying instantaneous frequencies. The synchrosqueezing transform (SST) can improve the quality and readability of the time-frequency representation. We have developed a high-resolution and effective time-frequency analysis method to characterize geologic bodies contained in the seismic data. We named this method the SST, and the basic wavelet is the three-parameter wavelet (SST-TPW). The TPW is superior in time-frequency resolution than those of the Morlet and Ricker wavelets. Experiments on synthetic and field data determined its validity and effectiveness, which can be used in assisting in oil/gas reservoir identification.

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