scholarly journals Marchenko multiple elimination of a laboratory example

2020 ◽  
Vol 221 (2) ◽  
pp. 1138-1144
Author(s):  
Lele Zhang ◽  
Evert Slob
Keyword(s):  
Laboratory Data ◽  
Velocity Model ◽  
Measured Data ◽  
Model Construction ◽  
High Quality ◽  
Data Set ◽  
Acoustic Reflection ◽  
Acoustic Data ◽  
Reflection Data ◽  
Multiple Elimination

SUMMARY The Marchenko multiple elimination (MME) scheme is derived from the coupled Marchenko equations. It is proposed for filtering primary reflections with two-way traveltime from the measured acoustic data. The measured acoustic reflection data are used as its own filter and no model information or adaptive subtraction is required to apply the method. The data obtained after MME are better suited for velocity model construction and artefact-free migration than the measured data. We apply the MME scheme to a measured laboratory data set to evaluate the success of the method. The results suggest that the MME scheme can be the appropriate choice when high-quality pre-processing is performed successfully.

Marchenko multiple elimination and full wavefield migration in a resonant pinch-out model

Geophysics ◽  
2021 ◽  
pp. 1-59
Author(s):  
Evert Slob ◽  
Lele Zhang ◽  
Eric Verschuur
Keyword(s):  
Constant Velocity ◽  
Local Minimum ◽  
Velocity Model ◽  
Dominant Frequency ◽  
Data Sampling ◽  
Multiple Reflections ◽  
Linear Inversion ◽  
Acoustic Reflection ◽  
Reflection Data ◽  
Multiple Elimination

Marchenko multiple elimination schemes are able to attenuate all internal multiple reflections in acoustic reflection data. These can be implemented with and without compensation for two-way transmission effects in the resulting primary reflection dataset. The methods are fully automated and run without human intervention, but require the data to be properly sampled and pre-processed. Even when several primary reflections are invisible in the data because they are masked by overlapping primaries, such as in the resonant wedge model, all missing primary reflections are restored and recovered with the proper amplitudes. Investigating the amplitudes in the primary reflections after multiple elimination with and without compensation for transmission effects shows that transmission effects are properly accounted for in a constant velocity model. When the layer thickness is one quarter of the wavelength at the dominant frequency of the source wavelet, the methods cease to work properly. Full wavefield migration relies on a velocity model and runs a non-linear inversion to obtain a reflectivity model which results in the migration image. The primary reflections that are masked by interference with multiples in the resonant wedge model, are not recovered. In this case, minimizing the data misfit function leads to the incorrect reflector model even though the data fit is optimal. This method has much lower demands on data sampling than the multiple elimination schemes, but is prone to get stuck in a local minimum even when the correct velocity model is available. A hybrid method that exploits the strengths of each of these methods could be worth investigating.

Migration with reduced artifacts from internal multiple reflections

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. A25-A29
Author(s):  
Lele Zhang
Keyword(s):  
Seismic Reflection ◽  
Computational Cost ◽  
Data Sets ◽  
Square Root ◽  
Multiple Reflections ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Recent Developments ◽  
Multiple Elimination

Migration of seismic reflection data leads to artifacts due to the presence of internal multiple reflections. Recent developments have shown that these artifacts can be avoided using Marchenko redatuming or Marchenko multiple elimination. These are powerful concepts, but their implementation comes at a considerable computational cost. We have derived a scheme to image the subsurface of the medium with significantly reduced computational cost and artifacts. This scheme is based on the projected Marchenko equations. The measured reflection response is required as input, and a data set with primary reflections and nonphysical primary reflections is created. Original and retrieved data sets are migrated, and the migration images are multiplied with each other, after which the square root is taken to give the artifact-reduced image. We showed the underlying theory and introduced the effectiveness of this scheme with a 2D numerical example.

Airway area by acoustic reflections measured at the mouth

1980 ◽  
Vol 48 (5) ◽  
pp. 749-758 ◽  
Author(s):  
J. J. Fredberg ◽  
M. E. Wohl ◽  
G. M. Glass ◽  
H. L. Dorkin
Keyword(s):  
High Frequency ◽  
Upper Airway ◽  
Local Area ◽  
Cross Sectional ◽  
Acoustic Reflection ◽  
Acoustic Data ◽  
Reflection Data ◽  
Radiographic Measurements ◽  
Average Coefficient ◽  
Radiographic Data

We tested the hypothesis that features of upper airway and tracheal geometry can be inferred from acoustic reflection data recorded at the mouth. In six subjects we computed inferences of airway cross-sectional area vs. distance and compared them with measurements obtained from orthogonal radiographic projections of the trachea. The acoustic data show local area maxima at the uvula and hypopharynx and local minima at the oropharynx and the glottis. With subjects breathing air the inferred tracheal areas markedly exceeded the radiographic measurements. With subjects breathing 80% He-20% O2 there was good intrasubject agreement between acoustic and radiographic data in spite of large intersubject variability. The average coefficient of variation of tracheal area determinations for five trials in all subjects was 0.16. These studies suggest that features of airway geometry between the mouth and carina can be determined accurately and noninvasively in individual subjects from high-frequency reflection data measured at the mouth.

scholarly journals Reconstructing the primary reflections in seismic data by Marchenko redatuming and convolutional interferometry

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. Q15-Q26 ◽  
Author(s):  
Giovanni Angelo Meles ◽  
Kees Wapenaar ◽  
Andrew Curtis
Keyword(s):  
Velocity Model ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Surface Reflection ◽  
Reflection Data ◽  
Reference Velocity ◽  
Time Migration ◽  
Recorded Data

State-of-the-art methods to image the earth’s subsurface using active-source seismic reflection data involve reverse time migration. This and other standard seismic processing methods such as velocity analysis provide best results only when all waves in the data set are primaries (waves reflected only once). A variety of methods are therefore deployed as processing to predict and remove multiples (waves reflected several times); however, accurate removal of those predicted multiples from the recorded data using adaptive subtraction techniques proves challenging, even in cases in which they can be predicted with reasonable accuracy. We present a new, alternative strategy to construct a parallel data set consisting only of primaries, which is calculated directly from recorded data. This obviates the need for multiple prediction and removal methods. Primaries are constructed by using convolutional interferometry to combine the first-arriving events of upgoing and direct-wave downgoing Green’s functions to virtual receivers in the subsurface. The required upgoing wavefields to virtual receivers are constructed by Marchenko redatuming. Crucially, this is possible without detailed models of the earth’s subsurface reflectivity structure: Similar to the most migration techniques, the method only requires surface reflection data and estimates of direct (nonreflected) arrivals between the virtual subsurface sources and the acquisition surface. We evaluate the method on a stratified synclinal model. It is shown to be particularly robust against errors in the reference velocity model used and to improve the migrated images substantially.

Nonlinear inversion of seismic reflection data in a laterally invariant medium

Geophysics ◽  
1990 ◽  
Vol 55 (3) ◽  
pp. 284-292 ◽  
Author(s):  
A. Pica ◽  
J. P. Diet ◽  
A. Tarantola
Keyword(s):  
Conjugate Gradient ◽  
Velocity Model ◽  
Stratified Medium ◽  
Single Shot ◽  
Nonlinear Inversion ◽  
Reverse Time ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Seismic Waveforms ◽  
Reflection Data

Interpretation of seismic waveforms can be expressed as an optimization problem based on a non‐linear least‐squares criterion to find the model which best explains the data. An initial model is corrected iteratively using a gradient method (conjugate gradient). At each iteration, computation of the direction of the model perturbation requires the forward propagation of the actual sources and the reverse‐time propagation of the residuals (misfit between the data and the synthetics); the two wave fields thus obtained are then correlated. An extra forward propagation is required to compute the amplitude of the perturbation along the conjugate‐gradient direction. The number of propagations to be simulated numerically in each iteration equals three times the number of shots. Since a 2-D finite‐difference code is employed to solve forward‐ and backward‐propagation problems, the method is general and can handle arbitrary 2-D source‐receiver configurations and lateral heterogeneities. Using conventional velocity analysis to derive an initial velocity model, the method is implemented on a real marine data set. The data set which has been selected corresponds approximately to a horizontally stratified medium. Consequently, a single‐shot gather has been used for inversion. In spite of some simplifying assumptions used for wave‐field propagation (acoustic approximation, point source), and using synthetics generated by a nearby sonic log to calibrate amplitudes, our final synthetics match the input data very well and the inversion result has clear similarities to the log.

Anisotropic 3D full-waveform inversion

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. R59-R80 ◽  
Author(s):  
Michael Warner ◽  
Andrew Ratcliffe ◽  
Tenice Nangoo ◽  
Joanna Morgan ◽  
Adrian Umpleby ◽  
...  
Keyword(s):  
High Velocity ◽  
Field Data ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Full Waveform Inversion ◽  
Low Velocity ◽  
Data Set ◽  
Reflection Data ◽  
Full Waveform ◽  
Gas Cloud

We have developed and implemented a robust and practical scheme for anisotropic 3D acoustic full-waveform inversion (FWI). We demonstrate this scheme on a field data set, applying it to a 4C ocean-bottom survey over the Tommeliten Alpha field in the North Sea. This shallow-water data set provides good azimuthal coverage to offsets of 7 km, with reduced coverage to a maximum offset of about 11 km. The reservoir lies at the crest of a high-velocity antiformal chalk section, overlain by about 3000 m of clastics within which a low-velocity gas cloud produces a seismic obscured area. We inverted only the hydrophone data, and we retained free-surface multiples and ghosts within the field data. We invert in six narrow frequency bands, in the range 3 to 6.5 Hz. At each iteration, we selected only a subset of sources, using a different subset at each iteration; this strategy is more efficient than inverting all the data every iteration. Our starting velocity model was obtained using standard PSDM model building including anisotropic reflection tomography, and contained epsilon values as high as 20%. The final FWI velocity model shows a network of shallow high-velocity channels that match similar features in the reflection data. Deeper in the section, the FWI velocity model reveals a sharper and more-intense low-velocity region associated with the gas cloud in which low-velocity fingers match the location of gas-filled faults visible in the reflection data. The resulting velocity model provides a better match to well logs, and better flattens common-image gathers, than does the starting model. Reverse-time migration, using the FWI velocity model, provides significant uplift to the migrated image, simplifying the planform of the reservoir section at depth. The workflows, inversion strategy, and algorithms that we have used have broad application to invert a wide-range of analogous data sets.

A consistent and uniform research earthquake catalog for the AlpArray region

2020 ◽  
Author(s):  
Irene Molinari ◽  
Matteo Bagagli ◽  
Tobias Diehl ◽  
Edi Kissling ◽  
John Clinton ◽  
...  
Keyword(s):  
Velocity Model ◽  
Alpine Region ◽  
P Wave ◽  
Phase Identification ◽  
Earthquake Catalog ◽  
Secondary Phases ◽  
High Quality ◽  
Data Set ◽  
Arrival Times ◽  
Initial Location

<p>We take advantage of the new large seismic data set provided by the AlpArray Seismic Network (AASN) as part of the AlpArray research initiative (www.alparray.ethz.ch), to provide consistent and precise hypocenter locations and uniform magnitude calculations across the greater Alpine region. The AASN is composed of more than 650 broadband seismic stations, 300 of which are temporary. The uniform station coverage provides an unique occasion to study the laterally strongly variable seismicity that is presently monitored and reported by a dozen individual observatories. A homogeneous earthquake catalog in terms of location and magnitude is a prerequisite to improve our understanding of seismo-tectonics and the seismic hazard in the greater Alpine region.</p><p>Our catalog covers four years of seismicity with a targeted magnitude of completeness of 2.5 from 2016 to 2019 and results from scanning ∼1000 broadband stations (∼60 TB of data). First, we detect and analyse events in the region using the STA/LTA based detector of the SeisComP3 monitoring system in off-line mode. Later, after an initial location has been obtained, we apply a high-quality semi-automated re-picking approach defining the consistent phase arrival times in combination with timing uncertainties and phase identification assessment. This automatic re-picking framework is implemented with the QUAKE library (Bagagli et al., 2019), an object-oriented Python package that exploit different waveform information both frequency- and energy- related by taking advantage of different well-established picking algorithms. The QUAKE picker has been tuned and tested against a consistent phases reference data set (P-, S- and secondary phases) of ∼2500 phases manually picked for 10 events (M≥ 2.5) homogeneously distributed in the region.</p><p>Subsequently, the high-quality automatic picks of selected well-locatable earthquakes are used to calculate a minimum 1D P-wave velocity model for the region with appropriate stations corrections. Finally, all events are relocated with the NonLinLoc algorithm in combination with the updated 1D model and a final estimate of the magnitude is given. We compare our locations and magnitudes with existing regional and local earthquake catalogs (ISC, EMSC, national catalogs) to assess and discuss the completeness and quality of the derived AlpArray research catalog.</p>

Imaging discontinuities on seismic sections

Geophysics ◽  
1988 ◽  
Vol 53 (3) ◽  
pp. 334-345 ◽  
Author(s):  
Ernest R. Kanasewich ◽  
Suhas M. Phadke
Keyword(s):  
Fault Location ◽  
Synthetic Data ◽  
Velocity Model ◽  
Data Set ◽  
Amplitude Correction ◽  
Reflection Data ◽  
Common Depth Point ◽  
Diffraction Patterns ◽  
A New Technique ◽  
Seismic Sections

In routine seismic processing, normal moveout (NMO) corrections are performed to enhance the reflected signals on common‐depth‐point or common‐midpoint stacked sections. However, when faults are present, reflection interference from the two blocks and the diffractions from their edges hinder fault location determination. Destruction of diffraction patterns by poststack migration further inhibits proper imaging of diffracting centers. This paper presents a new technique which helps in the interpretation of diffracting edges by concentrating the signal amplitudes from discontinuous diffracting points on seismic sections. It involves application to the data of moveout and amplitude corrections appropriate to an assumed diffractor location. The maximum diffraction amplitude occurs at the location of the receiver for which the diffracting discontinuity is beneath the source‐receiver midpoint. Since the amplitudes of these diffracted signals drop very rapidly on either side of the midpoint, an appropriate amplitude correction must be applied. Also, because the diffracted signals are present on all traces, one can use all of them to obtain a stacked trace for one possible diffractor location. Repetition of this procedure for diffractors assumed to be located beneath each surface point results in the common‐fault‐ point (CFP) stacked section, which shows diffractor locations by high amplitudes. The method was tested for synthetic data with and without noise. It proves to be quite effective, but is sensitive to the velocity model used for moveout corrections. Therefore, the velocity model obtained from NMO stacking is generally used for enhancing diffractor locations by stacking. Finally, the technique was applied to a field reflection data set from an area south of Princess well in Alberta.

Three-dimensional seismic-while-drilling (SWD) migration in the angular frequency domain

Geophysics ◽  
2005 ◽  
Vol 70 (6) ◽  
pp. S111-S120
Author(s):  
Fabio Rocca ◽  
Massimiliano Vassallo ◽  
Giancarlo Bernasconi
Keyword(s):  
Frequency Domain ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Vertical Axis ◽  
Velocity Model ◽  
Angular Frequency ◽  
Data Set ◽  
Surface Reflection ◽  
Reflection Data ◽  
Seismic Depth Migration

Seismic depth migration back-propagates seismic data in the correct depth position using information about the velocity of the medium. Usually, Kirchhoff summation is the preferred migration procedure for seismic-while-drilling (SWD) data because it can handle virtually any configuration of sources and receivers and one can compensate for irregular spatial sampling of the array elements (receivers and sources). Under the assumption of a depth-varying velocity model, with receivers arranged along a horizontal circumference and sources placed along the central vertical axis, we reformulate the Kirchhoff summation in the angular frequency domain. In this way, the migration procedure becomes very efficient because the migrated volume is obtained by an inverse Fourier transform of the weighted data. The algorithm is suitable for 3D SWD acquisitions when the aforementioned hypothesis holds. We show migration tests on SWD synthetic data, and we derive solutions to reduce the migration artifacts and to control aliasing. The procedure is also applied on a real 3D SWD data set. The result compares satisfactorily with the seismic stack section obtained from surface reflection data and with the results from traditional Kirchhoff migration.

scholarly journals Adaptive overburden elimination with the multidimensional Marchenko equation

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. T265-T284 ◽  
Author(s):  
Joost van der Neut ◽  
Kees Wapenaar
Keyword(s):  
Field Data ◽  
Synthetic Data ◽  
Velocity Model ◽  
Thin Layers ◽  
Multiple Reflections ◽  
Data Set ◽  
Marchenko Equation ◽  
Recorded Data ◽  
Internal Multiples ◽  
Multiple Elimination

Iterative substitution of the multidimensional Marchenko equation has been introduced recently to integrate internal multiple reflections in the seismic imaging process. In so-called Marchenko imaging, a macro velocity model of the subsurface is required to meet this objective. The model is used to back-propagate the data during the first iteration and to truncate integrals in time during all successive iterations. In case of an erroneous model, the image will be blurred (akin to conventional imaging) and artifacts may arise from inaccurate integral truncations. However, the scheme is still successful in removing artifacts from internal multiple reflections. Inspired by these observations, we rewrote the Marchenko equation, such that it can be applied early in a processing flow, without the need of a macro velocity model. Instead, we have required an estimate of the two-way traveltime surface of a selected horizon in the subsurface. We have introduced an approximation, such that adaptive subtraction can be applied. As a solution, we obtained a new data set, in which all interactions (primaries and multiples) with the part of the medium above the picked horizon had been eliminated. Unlike various other internal multiple elimination algorithms, the method can be applied at any specified target horizon, without having to resolve for internal multiples from shallower horizons. We successfully applied the method on synthetic data, where limitations were reported due to thin layers, diffraction-like discontinuities, and a finite acquisition aperture. A field data test was also performed, in which the kinematics of the predicted updates were demonstrated to match with internal multiples in the recorded data, but it appeared difficult to subtract them.

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