Li et al., 2016 - Google Patents
A method for low-frequency noise suppression based on mathematical morphology in microseismic monitoringLi et al., 2016
View PDF- Document ID
- 10852808307721052995
- Author
- Li H
- Wang R
- Cao S
- Chen Y
- Huang W
- Publication year
- Publication venue
- Geophysics
External Links
Snippet
The frequency of microseismic data is higher than that of conventional seismic data. The range of effective frequency is usually from 100 to 500 Hz, and low-frequency noise is a common disturbance in downhole monitoring. Conventional signal analysis techniques …
- 230000001629 suppression 0 title description 21
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
- G01V1/364—Seismic filtering
- G01V1/366—Seismic filtering by correlation of seismic signals
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/30—Noise handling
- G01V2210/32—Noise reduction
- G01V2210/322—Trace stacking
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/30—Noise handling
- G01V2210/32—Noise reduction
- G01V2210/324—Filtering
- G01V2210/3246—Coherent noise, e.g. spatially coherent or predictable
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/67—Wave propagation modeling
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/50—Corrections or adjustments related to wave propagation
- G01V2210/56—De-ghosting; Reverberation compensation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/282—Application of seismic models, synthetic seismograms
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/12—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with electromagnetic waves
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V99/00—Subject matter not provided for in other groups of this subclass
- G01V99/005—Geomodels or geomodelling, not related to particular measurements
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/08—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices
- G01V3/082—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation operating with magnetic or electric fields produced or modified by objects or geological structures or by detecting devices operating with fields produced by spontaneous potentials, e.g. electrochemical or produced by telluric currents
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
- G01V3/38—Processing data, e.g. for analysis, for interpretation, for correction
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Li et al. | A method for low-frequency noise suppression based on mathematical morphology in microseismic monitoring | |
Mousavi et al. | Automatic noise-removal/signal-removal based on general cross-validation thresholding in synchrosqueezed domain and its application on earthquake data | |
Huang et al. | Mathematical morphological filtering for linear noise attenuation of seismic data | |
Bonar et al. | Denoising seismic data using the nonlocal means algorithm | |
Dong et al. | Desert low-frequency noise suppression by using adaptive DnCNNs based on the determination of high-order statistic | |
Han et al. | Microseismic and seismic denoising via ensemble empirical mode decomposition and adaptive thresholding | |
Chen et al. | Random noise attenuation using local signal-and-noise orthogonalization | |
Chen et al. | Random noise attenuation by fx empirical-mode decomposition predictive filtering | |
Lu et al. | Seismic spectral decomposition using deconvolutive short-time Fourier transform spectrogram | |
Bekara et al. | Random and coherent noise attenuation by empirical mode decomposition | |
Liu et al. | A 1D time-varying median filter for seismic random, spike-like noise elimination | |
Han et al. | Empirical mode decomposition for seismic time-frequency analysis | |
Liu et al. | Random noise attenuation using f-x regularized nonstationary autoregression | |
Neelamani et al. | Coherent and random noise attenuation using the curvelet transform | |
Yuan et al. | Ground-roll attenuation using generative adversarial networks | |
Chen | Fast waveform detection for microseismic imaging using unsupervised machine learning | |
Chen et al. | Robust reduced-rank filtering for erratic seismic noise attenuation | |
Li et al. | Weak signal detection using multiscale morphology in microseismic monitoring | |
Kaur et al. | Seismic ground‐roll noise attenuation using deep learning | |
Gómez et al. | A simple method inspired by empirical mode decomposition for denoising seismic data | |
Bekara et al. | Local singular value decomposition for signal enhancement of seismic data | |
Van den Ende et al. | A self-supervised deep learning approach for blind denoising and waveform coherence enhancement in distributed acoustic sensing data | |
Huang et al. | Damped multichannel singular spectrum analysis for 3D random noise attenuation | |
Höcker et al. | Fast structural interpretation with structure-oriented filtering | |
Naghizadeh et al. | Multicomponent f-x seismic random noise attenuation via vector autoregressive operators |