scholarly journals Trace Interpolation with Partial CRS-Stacks

2019 ◽  
Author(s):  
Jesper Sören Dramsch
Keyword(s):  
Fresnel Zone ◽  
Synthetic Data ◽  
Sparse Data ◽  
Interpolation Error ◽  
Interpolation Process ◽  
Frequency Bandwidth ◽  
Direct Wave ◽  
Arrival Times ◽  
Data Record ◽  
Data Regularization

This bachelor thesis is about seismic trace interpolation, data regularization and extrapolation using partial CRS stacks. I edit the underlying synthetic data record to create sparse data and prepare for extrapolation. The gaps appear randomly in mid-offset and specifically in near-offset. Subsequently, I compare the results of the interpolation with the traces I deleted from the record, examine data regularization and analyze the extrapolation. The interpolation process preserves arrival times and frequencies very well. Especially the arrival times in near-offset are within minimum tolerance. However some trace contain lowintensity noise over the entire frequency bandwidth. The results show an interpolation error for the direct wave. This error occurs because the linear move-out of the direct wave cannot be approximated by the hyperbolic approach of the partial CRS stack.Data regularization is interpolation for equally spaced intervals. These intervals can be defined precisely and therefore hold the accuracy of the interpolation process.Extrapolation issues a challenge to the partial CRS algorithm. The Fresnel zone defines physical boundaries for the partial CRS apertures. I calculated the extrapolation for more than double of these limitations. Thus, I expect extrapolation artifacts such as amplitude escalation and signal splitting. These expectations are answered by amplitude escalation, smearing and signal splitting, appearing at 1.5 times the Fresnel zone. Nevertheless, extrapolation supplies a reliable extension of the reflection events. For the sake of extrapolation artifacts limitations by the Fresnel zone ought not be breached.In conclusion, I validate seismic trace interpolation and data regularization processes of the partial CRS stack and I point out boundaries of the extrapolation process

Single-station SVD-based polarization filtering of ground roll: Perfection and investigation of limitations and pitfalls

Geophysics ◽  
2012 ◽  
Vol 77 (2) ◽  
pp. V41-V59 ◽  
Author(s):  
Olena Tiapkina ◽  
Martin Landrø ◽  
Yuriy Tyapkin ◽  
Brian Link
Keyword(s):  
Time Window ◽  
Synthetic Data ◽  
Vertical Component ◽  
Horizontal Component ◽  
Frequency Bandwidth ◽  
Polarization Filter ◽  
Data Set ◽  
Single Station ◽  
Ground Roll ◽  
Polarization Filtering

The advent of single receiver point, multi-component geophones has necessitated that ground roll be removed in the processing flow rather than through acquisition design. A wide class of processing methods for ground-roll elimination is polarization filtering. A number of these methods use singular value decomposition (SVD) or some related transformations. We focus on a single-station SVD-based polarization filter that we consider to be one of the best in the industry. The method is comprised of two stages: (1) ground-roll detection and (2) ground-roll estimation and filtering. To detect the ground roll, a special attribute dependent on the singular values of a three-column matrix formed by a sliding time window is used. The ground roll is approximated and subtracted using the first two eigenimages of this matrix. To limit the possible damage to the signal, the filter operates within the record intervals where the ground roll is detected and within the ground-roll frequency bandwidth only. We improve the ground-roll detector to make it theoretically insensitive to ambient noise and more sensitive to the presence of ground roll. The advantage of the new detector is demonstrated on synthetic and field data sets. We estimate theoretically and with synthetic data the attenuation of the underlying reflections that can be caused by the polarization filter. We show that the underlying signal always loses almost all the energy on the vertical component and on the horizontal component in the ground-roll propagation plane and within the ground-roll frequency bandwidth. The only signal component, if it exists, that can retain a significant part of its energy is the horizontal component orthogonal to the above plane. When 2D 3C field operations are conducted, the signal particle motion can deviate from the ground-roll propagation plane and can therefore retain some of its energy due to a set of offline reflections. In the case of 3D 3C seismic surveys, the reflected signal always deviates from the ground-roll propagation plane on the receiver lines that do not contain the source. This is confirmed with a 2.5D 3C synthetic data set. We discuss when the ability of the filter to effectively subtract the ground roll may, or may not, allow us to ignore the inevitable harm that is done to the underlying reflected waves.

The diminishing residual matrices method for surface-consistent statics — A review

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. V257-V274
Author(s):  
Necati Gülünay
Keyword(s):  
Synthetic Data ◽  
Reconstruction Technique ◽  
Data Set ◽  
Arrival Times ◽  
Long Wavelength ◽  
Iterative Reconstruction Technique ◽  
Land Survey ◽  
First Arrival ◽  
Waveform Distortions ◽  
The Individual

The diminishing residual matrices (DRM) method can be used to surface-consistently decompose individual trace statics into source and receiver components. The statics to be decomposed may either be first-arrival times after the application of linear moveout associated with a consistent refractor as used in refraction statics or residual statics obtained by crosscorrelating individual traces with corresponding model traces (known as pilot traces) at the same common-midpoint (CMP) location. The DRM method is an iterative process like the well-known Gauss-Seidel (GS) method, but it uses only source and receiver terms. The DRM method differs from the GS method in that half of the average common shot and receiver terms are subtracted simultaneously from the observations at each iteration. DRM makes the under-constrained statics problem a constrained one by implicitly adding a new constraint, the equality of the contribution of shots and receivers to the solution. The average of the shot statics and the average of the receiver statics are equal in the DRM solution. The solution has the smallest difference between shot and receiver statics profiles when the number of shots and the number of receivers in the data are equal. In this case, it is also the smallest norm solution. The DRM method can be derived from the well-known simultaneous iterative reconstruction technique. Simple numerical tests as well as results obtained with a synthetic data set containing only the field statics verify that the DRM solution is the same as the linear inverse theory solution. Both algorithms can solve for the long-wavelength component of the statics if the individual picks contain them. Yet DRM method is much faster. Application of the method to the normal moveout-corrected CMP gathers on a 3D land survey for residual statics calculation found that pick-decompose-apply-stack stages of the DRM method need to be iterated. These iterations are needed because of time and waveform distortions of the pilot traces due to the individual trace statics. The distortions lessen at every external DRM iteration.

Improving crosshole radar velocity tomograms: A new approach to incorporating high-angle traveltime data

Geophysics ◽  
2007 ◽  
Vol 72 (4) ◽  
pp. J31-J41 ◽  
Author(s):  
James D. Irving ◽  
Michael D. Knoll ◽  
Rosemary J. Knight
Keyword(s):  
Synthetic Data ◽  
High Angle ◽  
Data Set ◽  
Tomographic Images ◽  
Arrival Times ◽  
Angle Data ◽  
Automatic Picking ◽  
Velocity Images ◽  
First Arrival ◽  
Ground Penetrating

To obtain the highest-resolution ray-based tomographic images from crosshole ground-penetrating radar (GPR) data, wide angular ray coverage of the region between the two boreholes is required. Unfortunately, at borehole spacings on the order of a few meters, high-angle traveltime data (i.e., traveltime data corresponding to transmitter-receiver angles greater than approximately 50° from the horizontal) are notoriously difficult to incorporate into crosshole GPR inversions. This is because (1) low signal-to-noise ratios make the accurate picking of first-arrival times at high angles extremely difficult, and (2) significant tomographic artifacts commonly appear when high- and low-angle ray data are inverted together. We address and overcome thesetwo issues for a crosshole GPR data example collected at the Boise Hydrogeophysical Research Site (BHRS). To estimate first-arrival times on noisy, high-angle gathers, we develop a robust and automatic picking strategy based on crosscorrelations, where reference waveforms are determined from the data through the stacking of common-ray-angle gathers. To overcome incompatibility issues between high- and low-angle data, we modify the standard tomographic inversion strategy to estimate, in addition to subsurface velocities, parameters that describe a traveltime ‘correction curve’ as a function of angle. Application of our modified inversion strategy, to both synthetic data and the BHRS data set, shows that it allows the successful incorporation of all available traveltime data to obtain significantly improved subsurface velocity images.

scholarly journals Estimation of the Relative Arrival Time of Microseismic Events Based on Phase-Only Correlation

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2527 ◽  
Author(s):  
Peng Wang ◽  
Xu Chang ◽  
Xiyan Zhou
Keyword(s):  
Arrival Time ◽  
Linear Equations ◽  
Time Lag ◽  
Synthetic Data ◽  
Information Criterion ◽  
Peak Position ◽  
Arrival Times ◽  
Time Frequency ◽  
Microseismic Events ◽  
Microseismic Event

The arrival time of a microseismic event is an important piece of information for microseismic monitoring. The accuracy and efficiency of arrival time identification is affected by many factors, such as the low signal-to-noise ratio (SNR) of the records, the vast amount of real-time monitoring records, and the abnormal situations of monitoring equipment. In order to eliminate the interference of these factors, we propose a method based on phase-only correlation (POC) to estimate the relative arrival times of microseismic events. The proposed method includes three main steps: (1) The SNR of the records is improved via time-frequency transform, which is used to obtain the time-frequency representation of each trace of a microseismic event. (2) The POC functions of all pairs of time-frequency representations are calculated. The peak value of the POC function indicates the similarity of the traces, and the peak position in the time lag axis indicates the relative arrival times between the traces. (3) Using the peak values as weighting coefficients of the linear equations, consistency processing is used to exclude any abnormal situations and obtain the optimal relative arrival times. We used synthetic data and field data to validate the proposed method. Comparing with Akaike information criterion (AIC) and cross-correlation, the proposed method is more robust at estimating the relative arrival time and excluding the influence of abnormal situations.

scholarly journals Interferometric identification of surface-related multiples

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. Q41-Q52 ◽  
Author(s):  
Boris Boullenger ◽  
Deyan Draganov
Keyword(s):  
Synthetic Data ◽  
Original Data ◽  
Data Set ◽  
Interferometric Method ◽  
Feedback Information ◽  
Arrival Times ◽  
Surface Reflection ◽  
Reflection Data ◽  
Multiple Prediction ◽  
Virtual Events

The theory of seismic interferometry predicts that crosscorrelations of recorded seismic responses at two receivers yield an estimate of the interreceiver seismic response. The interferometric process applied to surface-reflection data involves the summation, over sources, of crosscorrelated traces, and it allows retrieval of an estimate of the interreceiver reflection response. In particular, the crosscorrelations of the data with surface-related multiples in the data produce the retrieval of pseudophysical reflections (virtual events with the same kinematics as physical reflections in the original data). Thus, retrieved pseudophysical reflections can provide feedback information about the surface multiples. From this perspective, we have developed a data-driven interferometric method to detect and predict the arrival times of surface-related multiples in recorded reflection data using the retrieval of virtual data as diagnosis. The identification of the surface multiples is based on the estimation of source positions in the stationary-phase regions of the retrieved pseudophysical reflections, thus not necessarily requiring sources and receivers on the same grid. We have evaluated the method of interferometric identification with a two-layer acoustic example and tested it on a more complex synthetic data set. The results determined that we are able to identify the prominent surface multiples in a large range of the reflection data. Although missing near offsets proved to cause major problems in multiple-prediction schemes based on convolutions and inversions, missing near offsets does not impede our method from identifying surface multiples. Such interferometric diagnosis could be used to control the effectiveness of conventional multiple-removal schemes, such as adaptive subtraction of multiples predicted by convolution of the data.

scholarly journals Electroseismic investigation of the shallow subsurface: Field measurements and numerical modeling

Geophysics ◽  
1997 ◽  
Vol 62 (1) ◽  
pp. 97-105 ◽  
Author(s):  
Oleg V. Mikhailov ◽  
Matthijs W. Haartsen ◽  
M. Nafi Toksöz
Keyword(s):  
Porous Media ◽  
Field Experiment ◽  
Synthetic Data ◽  
Field Measurements ◽  
Field Studies ◽  
Amplitude Variation With Offset ◽  
Waveform Modeling ◽  
Arrival Times ◽  
Shallow Subsurface ◽  
High Fluid

Recent studies have demonstrated that electroseismic phenomena in porous media have the potential to detect zones of high fluid mobility and fluid chemistry contrasts in the subsurface. However, there have only been a few field studies of these phenomena since they were first observed 60 years ago. None of these studies were able to support observations with an explicit comparison to results of full waveform modeling. In this paper, we demonstrate that the electroseismic phenomena in porous media can be observed in the field, explained, and modeled numerically, yielding a good agreement between the field and the synthetic data. We first outline the design of our field experiment and describe the procedure used to reduce noise in the electroseismic data. After that, we present and interpret the field data, demonstrating how and where different electroseismic signals originated in the subsurface. Finally, we model our field experiment numerically and demonstrate that the numerical results correctly simulate arrival times, polarity, and amplitude variation with offset behavior of the electroseismic signals measured in the field.

Application of a new 2D time-domain full-waveform inversion scheme to crosshole radar data

Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. J53-J64 ◽  
Author(s):  
Jacques R. Ernst ◽  
Alan G. Green ◽  
Hansruedi Maurer ◽  
Klaus Holliger
Keyword(s):  
Time Domain ◽  
Waveform Inversion ◽  
Synthetic Data ◽  
Radar Data ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Arrival Times ◽  
Full Waveform ◽  
First Arrival ◽  
Radar Wave

Crosshole radar tomography is a useful tool in diverse investigations in geology, hydrogeology, and engineering. Conventional tomograms provided by standard ray-based techniques have limited resolution, primarily because only a fraction of the information contained in the radar data (i.e., the first-arrival times and maximum first-cycle amplitudes) is included in the inversion. To increase the resolution of radar tomograms, we have developed a versatile full-waveform inversion scheme that is based on a finite-difference time-domain solution of Maxwell’s equations. This scheme largely accounts for the 3D nature of radar-wave propagation and includes an efficient method for extracting the source wavelet from the radar data. After demonstrating the potential of the new scheme on two realistic synthetic data sets, we apply it to two crosshole field data sets acquired in very different geologic/hydrogeologic environments. These are the first applications of full-waveform tomography to observed crosshole radar data. The resolution of all full-waveform tomograms is shown to be markedly superior to that of the associated ray tomograms. Small subsurface features a fraction of the dominant radar wavelength and boundaries between distinct geological/hydrological units are sharply imaged in the full-waveform tomograms.

Resolution limits in ray tomography due to wave behavior: Numerical experiments

Geophysics ◽  
1993 ◽  
Vol 58 (5) ◽  
pp. 727-735 ◽  
Author(s):  
Paul R. Williamson ◽  
M. H. Worthington
Keyword(s):  
Fresnel Zone ◽  
Synthetic Data ◽  
Original Model ◽  
Data Sets ◽  
Diffraction Tomography ◽  
Feature Size ◽  
Resolution Limits ◽  
Minimum Feature Size ◽  
Experimental Geometry ◽  
Fresnel Zones

Several factors limit the resolution obtained in ray tomography. Of these the least thoroughly discussed in the geophysical literature is the effect of the ray approximation itself; scattering is ignored and the information contained in a seismic trace is reduced to one traveltime pick. Frequency domain comparisons of ray tomography with diffraction tomography have suggested that the minimum feature size resolvable by ray tomography is of the order of the width of the first Fresnel zone. We investigate resolution in the spacetime domain with a numerical experiment. Four synthetic data sets were generated with a finite‐difference program corresponding to crosshole tomographic surveys at two hole separations and two frequencies. The scale of resolution achieved in tomograms derived from these is then assessed by calculating their semblance to filtered versions of the original model and reconstructions from data sets obtained by tracing rays through the original models. The results broadly confirm the relation of resolution to Fresnel zones. It is therefore possible that such limits on resolution may be at least as significant as those due to other factors such as experimental geometry.

Modeling GPR radiation and reflection characteristics for a complex temperate glacier bed

Geophysics ◽  
2003 ◽  
Vol 68 (2) ◽  
pp. 559-565 ◽  
Author(s):  
Mark L. Moran ◽  
Roy J. Greenfield ◽  
Steve A. Arcone
Keyword(s):  
Field Data ◽  
Specular Reflection ◽  
Bottom Topography ◽  
Synthetic Data ◽  
Simulated Data ◽  
Dipole Orientation ◽  
Arrival Times ◽  
Reflection Data ◽  
General Importance ◽  
Out Of Plane

We demonstrate that ground penetrating radar (GPR) reflection data from a temperate glacier are accurately modeled using a Helmholtz‐Kirchhoff diffraction integration technique that incorporates the radiation characteristics of point dipoles on a half‐space interface. This is accomplished by comparing field data to simulated data. Our 40‐MHz field data are from a 100 × 340 m (x‐ and y‐dimensions, respectively) survey grid containing 51 parallel survey lines. The field data were collected with the dipole oriented perpendicular to the survey line (x‐dipole). The synthetic data used isotropic, x‐dipole, and y‐dipole antennas, and reflections were calculated using a bed topography previously defined by 3D Kirchhoff migration. The comparisons between the real and synthetic waveforms show excellent agreement, including reflection arrival times, amplitude trends, interference patterns, and false layering from out‐of‐plane reflections. The location of reflectors determined from exploding reflector rays explains that bed reflections rapidly sink below background noise levels when reflections originate in the antenna's E‐plane. This occurs in both the simulated data and field data. Our results are of general importance for radio‐glaciology because they demonstrate that inappropriate dipole orientation with respect to the specular reflection point can lead to more than 12‐dB reduction in bottom reflection strength. Furthermore, a complicated bottom topography readily generates secondary, out‐of‐plane reflections that are easily confused with basal till layers.

First-arrival picking with a U-net convolutional network

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. U45-U57 ◽  
Author(s):  
Lianlian Hu ◽  
Xiaodong Zheng ◽  
Yanting Duan ◽  
Xinfei Yan ◽  
Ying Hu ◽  
...  
Keyword(s):  
Seismic Data ◽  
Synthetic Data ◽  
Training Data ◽  
Convolutional Network ◽  
Data Set ◽  
Waveform Data ◽  
Near Surface ◽  
Arrival Times ◽  
Seismic Waveform ◽  
First Arrival

In exploration geophysics, the first arrivals on data acquired under complicated near-surface conditions are often characterized by significant static corrections, weak energy, low signal-to-noise ratio, and dramatic phase change, and they are difficult to pick accurately with traditional automatic procedures. We have approached this problem by using a U-shaped fully convolutional network (U-net) to first-arrival picking, which is formulated as a binary segmentation problem. U-net has the ability to recognize inherent patterns of the first arrivals by combining attributes of arrivals in space and time on data of varying quality. An effective workflow based on U-net is presented for fast and accurate picking. A set of seismic waveform data and their corresponding first-arrival times are used to train the network in a supervised learning approach, then the trained model is used to detect the first arrivals for other seismic data. Our method is applied on one synthetic data set and three field data sets of low quality to identify the first arrivals. Results indicate that U-net only needs a few annotated samples for learning and is able to efficiently detect first-arrival times with high precision on complicated seismic data from a large survey. With the increasing training data of various first arrivals, a trained U-net has the potential to directly identify the first arrivals on new seismic data.

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