Noise‐adaptive filtering of seismic shot records

Geophysics ◽  
1988 ◽  
Vol 53 (5) ◽  
pp. 638-649 ◽  
Author(s):  
Richard G. Anderson ◽  
George A. McMechan
Keyword(s):  
Fourier Transform ◽  
Adaptive Filtering ◽  
Seismic Data ◽  
Adaptive Filters ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Amplitude Spectrum ◽  
Noise Rejection ◽  
Amplitude Spectra ◽  
Spectral Subtraction Method

Ambient noise can obscure reflections on deep crustal seismic data. We use a spectral subtraction method to attenuate stationary noise. Our procedure, called noise‐adaptive filtering, is to Fourier transform the noise before the first arrivals, subtract the amplitude spectrum of the noise from the amplitude spectrum of the noisy data, and inverse Fourier transform. The phase spectrum is not corrected, but the method attenuates noise if the phase shift between the signal and noise is random. The algorithm can be implemented as a frequency filter, as a frequency‐wavenumber filter, or as two separate frequency and wavenumber filters. Noise‐adaptive filtering is often superior to conventional frequency or frequency‐wavenumber filtering because it adapts to spatial variations in the noise without parameter testing. Noise‐adaptive filters can achieve noise rejection ratios of up to 45 dB; their dynamic range is about 25 dB. These filters work best when the input signal‐to‐noise ratio is on the order of 0 dB and there are significant differences between the frequency‐wavenumber amplitude spectra of the signal and noise. Application of the method to field data can enhance events that are not visible in the input data.

Coherence based on spectral variance analysis

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. O55-O66 ◽  
Author(s):  
Yanting Duan ◽  
Chaodong Wu ◽  
Xiaodong Zheng ◽  
Yucheng Huang ◽  
Jian Ma
Keyword(s):  
Fourier Transform ◽  
Seismic Data ◽  
High Frequency ◽  
Seismic Interpretation ◽  
Variance Analysis ◽  
Frequency Spectra ◽  
Amplitude Spectra ◽  
Frequency Components ◽  
Spectral Variance ◽  
Coherence Estimation

The eigenstructure-based coherence attribute is a type of efficient and mature tool for mapping geologic edges such as faults and/or channels in the 3D seismic interpretation. However, the eigenstructure-based coherence algorithm is sensitive to low signal-to-noise ratio seismic data, and the coherence results are affected by the dipping structures. Due to the large energy gap between the low- and high-frequency components, the low-frequency components play the principal role in coherence estimation. In contrast, the spectral variance balances the difference between the low- and high-frequency components at a fixed depth. The coherence estimation based on amplitude spectra avoids the effect of the time delays resulting from the dipping structures. Combining the spectral variance with the amplitude spectra avoids the effect of dipping structures and enhances the antinoise performance of the high-frequency components. First, we apply the short-time Fourier transform to obtain the time-frequency spectra of seismic data. Next, we compute the variance values of amplitude spectra. Then, we apply the fast Fourier transform to obtain the amplitude spectra of spectral variance. Finally, we calculate the eigenstructure coherence by using the amplitude spectra of spectral variance as the input. We apply the method to the theoretical models and practical seismic data. In the Marmousi velocity model, the coherence estimation using the amplitude spectra of the spectral variance as input shows more subtle discontinuities, especially in deeper layers. The results from field-data examples demonstrate that the proposed method is helpful for mapping faults and for improving the narrow channel edges’ resolution of interest. Therefore, the coherence algorithm based on the spectral variance analysis may be conducive to the seismic interpretation.

Advantageous Apodization Functions for Magnitude-Mode Fourier Transform Spectroscopy

1987 ◽  
Vol 41 (1) ◽  
pp. 93-98 ◽  
Author(s):  
Judy P. Lee ◽  
Melvin B. Comisarow
Keyword(s):  
Fourier Transform ◽  
Time Domain ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Time Domain Signal ◽  
Time Domain Data ◽  
Window Functions ◽  
Fourier Transform Spectra ◽  
The Time Domain ◽  
Ratio Reduction

A systematic examination of the efficacy of window functions for reducing the spectral skirt of magnitude-mode Fourier transform spectra is reported. The efficacy is examined for the general case of a damped time-domain signal, with specific cases ranging from undamped to essentially completely damped signals. The choice of the optimal window is dependent upon the required dynamic range and the amount of damping in the time-domain data. For a dynamic range of less than 100:1 and moderate damping, the Hamming window is the window of choice. For larger dynamic ranges or greater damping, the 3-term Blackman-Harris window and the Kaiser-Bessel window are the windows of choice. The 3-term Blackman-Harris window is preferred for a dynamic range of 1,000:1 and the Kaiser-Bessel window is preferred for a dynamic range of 10,000:1. The sensitivity (signal-to-noise ratio) reduction for windows is reported for a damping range from zero to essentially complete damping. All windows examined have the same sensitivity reduction within 25%.

scholarly journals ADAPTIVE SIGNAL DECOMPOSITION AND FILTERING USING BINOMIAL FILTERS APPLIED TO THE GROUND-ROLL ATTENUATION

2016 ◽  
Vol 34 (3) ◽  
Author(s):  
Cristian D. Ariza A. ◽  
Milton J. Porsani
Keyword(s):  
Seismic Data ◽  
Adaptive Filters ◽  
Signal To Noise Ratio ◽  
Seismic Signal ◽  
Noise Signal ◽  
Signal Decomposition ◽  
Signal To Noise ◽  
Ground Roll ◽  
Noise Ratio ◽  
Adaptive Signal

ABSTRACT. The ground-roll is a type of noise normally present in land seismic data. It strongly harms the signal-to-noise ratio, and interferes in several stages of the seismic data processing, strongly affecting the final quality of the obtained seismic images...Keywords: seismic noise, signal-to-noise ratio, adaptive filters, Burg algorithm, seismic signal decomposition.  RESUMO. O ground-roll é um tipo de ruído normalmente presente nos dados sísmicos terrestres. Ele prejudica muito a razão sinal-ruído e interfere em vários est´ágios do processamento de dados sísmicos, afetando fortemente a qualidade final das imagens sísmicas obtidas...Palavras-chave: ruídos sísmicos, relação sinal-ruído, filtragem adaptativo, algoritmo de Burg, decomposição do sinal sísmico.

scholarly journals Adaptive Filtering in Optical Coherent Flexible Bit-Rate Receivers in the Presence of State-of-Polarization Transients and Colored Noise

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Ahmad Abdo ◽  
Claude D’Amours
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Filters ◽  
Colored Noise ◽  
Signal To Noise Ratio ◽  
Rate Of Change ◽  
Recursive Least Squares ◽  
Bit Rate ◽  
Step Size ◽  
Modulation Formats ◽  
State Of Polarization

In this article, we analyze the performance of adaptive filtering in the context of dual-polarization coherent optical flexible bit-rate transceivers. We investigate the ability of different adaptive algorithms to track fast state-of-polarization (SOP) transients in the presence of colored noise. Colored noise exists due to the concatenation of Wavelength Selective Switches (WSSs) and polarization dependent loss (PDL) which can be considered as spatially dependent noise. We consider the use of different modulation formats, and the practical limitation of error signal feedback delay in decision-directed adaptive filters is also taken into account. The back-to-back required signal-to-noise ratio (RSNR) penalty that can be tolerated determines the maximum SOP rate of change that can be tracked by the adaptive filters as well as the filter’s adaptive step size. We show that the recursive least squares algorithm, using the covariance matrix as an aggressive “step size,” has a much better convergence speed compared to the least mean squares (LMS) and normalized LMS (NLMS) algorithms in the presence of colored noise in the fiber. However, the three algorithms have similar tracking capabilities in the absence of colored noise.

Amplitude Spectra of Fitness Landscapes

1998 ◽  
Vol 01 (01) ◽  
pp. 39-66 ◽  
Author(s):  
Wim Hordijk ◽  
Peter F. Stadler
Keyword(s):  
Fourier Transform ◽  
Topological Structure ◽  
Empirical Studies ◽  
Amplitude Spectrum ◽  
Fitness Landscapes ◽  
Configuration Spaces ◽  
Amplitude Spectra ◽  
Different Types ◽  
Reliable Procedure ◽  
The Fourier Transform

Fitness landscapes can be decomposed into elementary landscapes using a Fourier transform that is determined by the structure of the underlying configuration space. The amplitude spectrum obtained from the Fourier transform contains information about the ruggedness of the landscape. It can be used for classification and comparison purposes. We consider here three very different types of landscapes using both mutation and recombination to define the topological structure of the configuration spaces. A reliable procedure for estimating the amplitude spectra is presented. The method is based on certain correlation functions that are easily obtained from empirical studies of the landscapes.

Sign‐bit amplitude recovery with applications to seismic data

Geophysics ◽  
1982 ◽  
Vol 47 (11) ◽  
pp. 1527-1539 ◽  
Author(s):  
J. T. O’Brien ◽  
W. P. Kamp ◽  
G. M. Hoover
Keyword(s):  
Seismic Data ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Recovery Process ◽  
Signal To Noise ◽  
Common Depth Point ◽  
Seismic Recording ◽  
Noise Ratio ◽  
Correct Application ◽  
Complete Amplitude

Sign‐bit digital recording means that only the sign of the analog signal is recorded with one bit. In conventional seismic recording, 16 to 20 binary bits are acquired per sample point. The economic advantages of sign‐bit acquisition are immediately obvious. Complete amplitude recovery, comparable to full‐gain recording, can be achieved by correct application of sign‐bit techniques. We describe the amplitude recovery process in a semiintuitive manner to promote the understanding necessary for proper application of the technique. The dynamic range requirements in seismic applications are discussed. Sign‐bit digitization is a completely viable technique for recording seismic data, provided that two conditions are fulfilled. First, in real time, the coherent‐signal‐to‐randomnoise‐ratio must be ⩽1.0. Second, the data must be recorded with sufficient redundancy. Redundancy is achieved by source repetition, sweep correlation, and high‐fold common‐depth‐point stacking, usually in combination. Failure to abide by these two restrictions results in (1) incomplete amplitude recovery, i.e., clipped data, and (2) insufficient dynamic range in the recovered signal. We derive the requirement that the signal‐to‐noise ratio be less than one; we also discuss the consequences of violating that requirement, namely clipping, at various points in the processing sequence. The amount of information lost is proportional to the degree of clipping; a small amount can be tolerated. Calculated expectation values show that (subject to the requirement that the signal‐to‐noise ratio be less than 1.0) an unbiased estimator can be chosen. The variance of these estimators is approximately the same as that for full‐gain seismic techniques. With sufficient redundancy, the variance can be made as small as necessary to achieve the required dynamic range. With proper attention to these findings, sign‐bit digitized data are found to be a totally viable tool.

An Over 120dB Dynamic Range Linear Response Single Exposure CMOS Image Sensor with Two-stage Lateral Overflow Integration Trench Capacitors

2020 ◽  
Vol 2020 (7) ◽  
pp. 143-1-143-6 ◽  
Author(s):  
Yasuyuki Fujihara ◽  
Maasa Murata ◽  
Shota Nakayama ◽  
Rihito Kuroda ◽  
Shigetoshi Sugawa
Keyword(s):  
Linear Response ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Signal To Noise ◽  
Single Exposure ◽  
Two Stage ◽  
Noise Ratio ◽  
Maximum Signal

This paper presents a prototype linear response single exposure CMOS image sensor with two-stage lateral overflow integration trench capacitors (LOFITreCs) exhibiting over 120dB dynamic range with 11.4Me- full well capacity (FWC) and maximum signal-to-noise ratio (SNR) of 70dB. The measured SNR at all switching points were over 35dB thanks to the proposed two-stage LOFITreCs.

Realization of Enhanced LMS Filter Using Carry Skip Adder And Quantum Dot Cellular Automation In VLSI For Removing Impulse Noises In Medical Image

2019 ◽  
Vol 14 ◽  
Author(s):  
K.R. Shankarkumar ◽  
Gokul Kumar
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Filters ◽  
Pass Band ◽  
Least Mean Square ◽  
Low Pass ◽  
Parallel Prefix ◽  
Loop Feedback ◽  
Band Pass ◽  
The Difference ◽  
Prefix Adder

: Filtering is an important step in the field of image processing to suppress the required parts or to remove any artifacts present in it. There are different types of filters like low pass, high pass, Band pass, IIR, FIR and adaptive filtering etc.., in these filters adaptive filters is an important filter because it is used to remove the noisy signal and images. Least Mean Square filter is a type of an adaptive filtering which is used to remove the noises present in the medical images. The working of LMS is based on the minimization of the difference between the error images using a closed loop feedback. Therefore presented technique called as Q-CSKA. Here the CSKA performs its operation in stages which is based on the nucleus stage. In the traditional CSKA the nucleus stage is depend on the parallel prefix adder in this work it is replaced by the QCA adder. The QCA adder utilizes the less area compared to PPA and it can be realized in Nanometer range also. For multiplexers, And OR Invert, OR and Invert logic is used to reduce the area and delay. Due to these advantages of the QCA, AOI-OAI logic the proposed method outperformed the LMS implementation in area, power, and accuracy and delay, this based five type image noise of medical pictures related to the best technique is out comes. It helps to medicinal practitioner to resolve the symptoms of patient with ease.

scholarly journals Detectivity optimization to detect of ultraweak light fluxes with an EM-CCD as binary photon counter array

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ibtissame Khaoua ◽  
Guillaume Graciani ◽  
Andrey Kim ◽  
François Amblard
Keyword(s):  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Photon Counting ◽  
Detection Methods ◽  
Strong Nonlinearity ◽  
Wide Range ◽  
Depth Analysis ◽  
Spatially Extended ◽  
Extended Sources ◽  
Photon Counting Mode

AbstractFor a wide range of purposes, one faces the challenge to detect light from extremely faint and spatially extended sources. In such cases, detector noises dominate over the photon noise of the source, and quantum detectors in photon counting mode are generally the best option. Here, we combine a statistical model with an in-depth analysis of detector noises and calibration experiments, and we show that visible light can be detected with an electron-multiplying charge-coupled devices (EM-CCD) with a signal-to-noise ratio (SNR) of 3 for fluxes less than $$30\,{\text{photon}}\,{\text{s}}^{ - 1} \,{\text{cm}}^{ - 2}$$ 30 photon s - 1 cm - 2 . For green photons, this corresponds to 12 aW $${\text{cm}}^{ - 2}$$ cm - 2 ≈ $$9{ } \times 10^{ - 11}$$ 9 × 10 - 11 lux, i.e. 15 orders of magnitude less than typical daylight. The strong nonlinearity of the SNR with the sampling time leads to a dynamic range of detection of 4 orders of magnitude. To detect possibly varying light fluxes, we operate in conditions of maximal detectivity $${\mathcal{D}}$$ D rather than maximal SNR. Given the quantum efficiency $$QE\left( \lambda \right)$$ Q E λ of the detector, we find $${ \mathcal{D}} = 0.015\,{\text{photon}}^{ - 1} \,{\text{s}}^{1/2} \,{\text{cm}}$$ D = 0.015 photon - 1 s 1 / 2 cm , and a non-negligible sensitivity to blackbody radiation for T > 50 °C. This work should help design highly sensitive luminescence detection methods and develop experiments to explore dynamic phenomena involving ultra-weak luminescence in biology, chemistry, and material sciences.

scholarly journals Ab initiostructure determination of nanocrystals of organic pharmaceutical compounds by electron diffraction at room temperature using a Timepix quantum area direct electron detector

2016 ◽  
Vol 72 (2) ◽  
pp. 236-242 ◽  
Author(s):  
E. van Genderen ◽  
M. T. B. Clabbers ◽  
P. P. Das ◽  
A. Stewart ◽  
I. Nederlof ◽  
...  
Keyword(s):  
Electron Diffraction ◽  
Room Temperature ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Direct Methods ◽  
Liquid Nitrogen Temperature ◽  
High Dynamic Range ◽  
Electron Diffraction Data ◽  
High Signal

Until recently, structure determination by transmission electron microscopy of beam-sensitive three-dimensional nanocrystals required electron diffraction tomography data collection at liquid-nitrogen temperature, in order to reduce radiation damage. Here it is shown that the novel Timepix detector combines a high dynamic range with a very high signal-to-noise ratio and single-electron sensitivity, enablingab initiophasing of beam-sensitive organic compounds. Low-dose electron diffraction data (∼0.013 e− Å−2 s−1) were collected at room temperature with the rotation method. It was ascertained that the data were of sufficient quality for structure solution using direct methods using software developed for X-ray crystallography (XDS,SHELX) and for electron crystallography (ADT3D/PETS,SIR2014).

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