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.

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.

scholarly journals Data-driven wavefield focusing and imaging with multidimensional deconvolution: Numerical examples for reflection data with internal multiples

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. WA107-WA115 ◽  
Author(s):  
Filippo Broggini ◽  
Roel Snieder ◽  
Kees Wapenaar
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Imaging Techniques ◽  
Velocity Model ◽  
Single Scattering ◽  
Data Driven ◽  
Multiple Reflections ◽  
Prestack Migration ◽  
Reflection Data ◽  
Internal Multiples

Standard imaging techniques rely on the single scattering assumption. This requires that the recorded data do not include internal multiples, i.e., waves that have bounced multiple times between reflectors before reaching the receivers at the acquisition surface. When multiple reflections are present in the data, standard imaging algorithms incorrectly image them as ghost reflectors. These artifacts can mislead interpreters in locating potential hydrocarbon reservoirs. Recently, we introduced a new approach for retrieving the Green’s function recorded at the acquisition surface due to a virtual source located at depth. We refer to this approach as data-driven wavefield focusing. Additionally, after applying source-receiver reciprocity, this approach allowed us to decompose the Green’s function at a virtual receiver at depth in its downgoing and upgoing components. These wavefields were then used to create a ghost-free image of the medium with either crosscorrelation or multidimensional deconvolution, presenting an advantage over standard prestack migration. We tested the robustness of our approach when an erroneous background velocity model is used to estimate the first-arriving waves, which are a required input for the data-driven wavefield focusing process. We tested the new method with a numerical example based on a modification of the Amoco model.

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.

Ground-penetrating radar data diffraction focusing without a velocity model

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. H13-H24
Author(s):  
Nikos Economou ◽  
Antonis Vafidis ◽  
Maksim Bano ◽  
Hamdan Hamdan ◽  
Jose Ortega-Ramirez
Keyword(s):  
Ground Penetrating Radar ◽  
Constant Velocity ◽  
Electromagnetic Waves ◽  
Ground Truth ◽  
Velocity Model ◽  
Migration Velocity ◽  
Dominant Frequency ◽  
Limited Information ◽  
Velocity Range ◽  
Ground Penetrating

Ground-penetrating Radar (GPR) sections commonly suffer from strong scattered energy and weak reflectors with distorted lateral continuity. This is mainly due to the gradual variation of moisture with depth, dense lateral sampling of common-offset GPR traces (which are considered as zero-offset data), along with the small wavelength of the electromagnetic waves that is comparable to the size of the shallow subsurface dielectric heterogeneities. Focusing of the diffractions requires efficient migration that, in the presence of highly heterogeneous subsurface formations, can be improved by a detailed migration velocity model. Such a velocity model is difficult to develop because the common-offset antenna array is mostly used for its reduced time and cost in the data acquisition and processing stages. In such cases, migration processes are based on limited information from velocity analysis of clear diffractions, cores, or other ground truth knowledge, often leading to insufficient imaging. We have developed a methodology to obtain GPR sections with focused diffractions that is based on multipath summation, using weighted stacking (summation) of constant-velocity migrated sections over a predefined velocity range. The success of this method depends on the assignment of an appropriate weight, for each constant-velocity migrated section to contribute to the final stack, and the optimal width of the velocity range used. Additionally, we develop a postmultipath summation processing step, which consists of time-varying spectral whitening, to deal with the decrease of the dominant frequency due to attenuation effects and the additional degraded resolution expected by the constant migration summed images. This imaging strategy leads to GPR sections with sufficiently focused diffractions, enhancing the lateral and the temporal resolution, without the need to explicitly build a migration velocity model.

A fast algorithm for multiple elimination and transmission compensation in primary reflections

2020 ◽  
Vol 221 (1) ◽  
pp. 371-377 ◽  
Author(s):  
Lele Zhang ◽  
Evert Slob
Keyword(s):  
Computational Cost ◽  
Initial Estimate ◽  
Transmission Losses ◽  
Multiple Reflections ◽  
Excellent Performance ◽  
Numerical Examples ◽  
Acoustic Reflection ◽  
Time Value ◽  
Order Of Magnitude ◽  
Multiple Elimination

SUMMARY The transmission compensated primary reflections can be obtained from the single-sided acoustic reflection response in the two-way traveltime domain. This is achieved by eliminating free-surface and internal multiple reflections and compensating for transmission losses in primary reflections without model information. The substantial computational cost of the proposed scheme can be reduced by an order of magnitude with a fast implementation version. This is achieved by using the previously computed filter functions as initial estimate for every new truncation time value. We evaluate the success of the scheme with simple and complex 2-D numerical examples. We find that the scheme has excellent performance in most cases, except for the case where strong reflectors are present. In such case, the current scheme suffers from lack of convergence.

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.

LONG-PERIOD SURFACE-RELATED MULTIPLE SUPPRESSION IN 2D MARINE SEISMIC DATA USING PREDICTIVE DECONVOLUTION AND COMBINATION OF SURFACE-RELATED MULTIPLE ELIMINATION AND PARABOLIC RADON FILTERING

2021 ◽  
Author(s):  
Pimpawee Sittipan ◽  
Pisanu Wongpornchai
Keyword(s):  
Seismic Data ◽  
Seismic Reflection ◽  
Petroleum Reservoirs ◽  
The United States ◽  
Multiple Reflections ◽  
Long Period ◽  
Predictive Deconvolution ◽  
Short Period ◽  
Marine Seismic ◽  
Multiple Elimination

Some of the important petroleum reservoirs accumulate beneath the seas and oceans. Marine seismic reflection method is the most efficient method and is widely used in the petroleum industry to map and interpret the potential of petroleum reservoirs. Multiple reflections are a particular problem in marine seismic reflection investigation, as they often obscure the target reflectors in seismic profiles. Multiple reflections can be categorized by considering the shallowest interface on which the bounces take place into two types: internal multiples and surface-related multiples. Besides, the multiples can be categorized on the interfaces where the bounces take place, a difference between long-period and short-period multiples can be considered. The long-period surface-related multiples on 2D marine seismic data of the East Coast of the United States-Southern Atlantic Margin were focused on this research. The seismic profile demonstrates the effectiveness of the results from predictive deconvolution and the combination of surface-related multiple eliminations (SRME) and parabolic Radon filtering. First, predictive deconvolution applied on conventional processing is the method of multiple suppression. The other, SRME is a model-based and data-driven surface-related multiple elimination method which does not need any assumptions. And the last, parabolic Radon filtering is a moveout-based method for residual multiple reflections based on velocity discrimination between primary and multiple reflections, thus velocity model and normal-moveout correction are required for this method. The predictive deconvolution is ineffective for long-period surface-related multiple removals. However, the combination of SRME and parabolic Radon filtering can attenuate almost long-period surface-related multiple reflections and provide a high-quality seismic images of marine seismic data.

scholarly journals Study on the limitations of travel-time inversion applied to sub-basalt imaging

Solid Earth ◽  
2013 ◽  
Vol 4 (2) ◽  
pp. 543-554 ◽  
Author(s):  
I. Flecha ◽  
R. Carbonell ◽  
R. W. Hobbs
Keyword(s):  
Oil Industry ◽  
Velocity Model ◽  
Time Inversion ◽  
Wide Angle ◽  
Seismic Reflection Data ◽  
Additional Information ◽  
Velocity Models ◽  
Reflection Data ◽  
Travel Time Inversion ◽  
Tomographic Inversions

Abstract. The difficulties of seismic imaging beneath high velocity structures are widely recognised. In this setting, theoretical analysis of synthetic wide-angle seismic reflection data indicates that velocity models are not well constrained. A two-dimensional velocity model was built to simulate a simplified structural geometry given by a basaltic wedge placed within a sedimentary sequence. This model reproduces the geological setting in areas of special interest for the oil industry as the Faroe-Shetland Basin. A wide-angle synthetic dataset was calculated on this model using an elastic finite difference scheme. This dataset provided travel times for tomographic inversions. Results show that the original model can not be completely resolved without considering additional information. The resolution of nonlinear inversions lacks a functional mathematical relationship, therefore, statistical approaches are required. Stochastic tests based on Metropolis techniques support the need of additional information to properly resolve sub-basalt structures.

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