scholarly journals Identification of image artifacts from internal multiples

Geophysics ◽  
2007 ◽  
Vol 72 (2) ◽  
pp. S123-S132 ◽  
Author(s):  
Alison E. Malcolm ◽  
Maarten V. de Hoop ◽  
Henri Calandra
Keyword(s):  
Synthetic Data ◽  
Velocity Model ◽  
Single Scattering ◽  
Image Artifacts ◽  
Coherent Noise ◽  
First Order ◽  
Inverse Scattering Series ◽  
The Common ◽  
Internal Multiples ◽  
Seismic Images

First-order internal multiples are a source of coherent noise in seismic images because they do not satisfy the single-scattering assumption fundamental to most seismic processing. There are a number of techniques to estimate internal multiples in data; in many cases, these algorithms leave some residual multiple energy in the data. This energy produces artifacts in the image, and the location of these artifacts is unknown because the multiples were estimated in the data before the image was formed. To avoid this problem, we propose a method by which the artifacts caused by internal multiples are estimated directly in the image. We use ideas from the generalized Bremmer series and the Lippmann-Schwinger scattering series to create a forward-scattering series to model multiples and an inverse-scattering series to describethe impact these multiples have on the common-image gather and the image. We present an algorithm that implements the third term of this series, responsible for the formation of first-order in-ternal multiples. The algorithm works as part of a wave-equation migration; the multiple estimation is made at each depth using a technique related to one used to estimate surface-related multi-ples. This method requires knowledge of the velocity model to the depth of the shallowest reflector involved in the generation of the multiple of interest. This information allows us to estimate internal multiples without assumptions inherent to other methods. In particular, we account for the formation of caustics. Results of the techniques on synthetic data illustrate the kinematic accuracy of predicted multiples, and results on field data illustrate the potential of estimating artifacts caused by internal multiples in the image rather than in the data.

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.

scholarly journals Relating source-receiver interferometry to an inverse-scattering series to derive a new method to estimate internal multiples

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. Q27-Q40 ◽  
Author(s):  
Katrin Löer ◽  
Andrew Curtis ◽  
Giovanni Angelo Meles
Keyword(s):  
Inverse Scattering ◽  
Computational Cost ◽  
Synthetic Data ◽  
Data Set ◽  
Inverse Scattering Series ◽  
Internal Multiples ◽  
Multiple Prediction ◽  
New Formula ◽  
3D Applications ◽  
Insight Into

We have evaluated an explicit relationship between the representations of internal multiples by source-receiver interferometry and an inverse-scattering series. This provides a new insight into the interaction of different terms in each of these internal multiple prediction equations and explains why amplitudes of estimated multiples are typically incorrect. A downside of the existing representations is that their computational cost is extremely high, which can be a precluding factor especially in 3D applications. Using our insight from source-receiver interferometry, we have developed an alternative, computationally more efficient way to predict internal multiples. The new formula is based on crosscorrelation and convolution: two operations that are computationally cheap and routinely used in interferometric methods. We have compared the results of the standard and the alternative formulas qualitatively in terms of the constructed wavefields and quantitatively in terms of the computational cost using examples from a synthetic data set.

Reflector spectrum for relating seismic arrivals to reflectors

Geophysics ◽  
2012 ◽  
Vol 77 (6) ◽  
pp. T239-T246
Author(s):  
Hong Liang ◽  
Yi Luo ◽  
Panos G. Kelamis ◽  
Arthur B. Weglein
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
Forward Modeling ◽  
Modeling Method ◽  
Relative Contribution ◽  
Sonic Log ◽  
Minimum Number ◽  
Internal Multiples ◽  
Seismic Images

When interpreting seismic images or suppressing multiples in seismic data, it is important to identify the reflectors from which the multiples, especially the internal multiples, originated. We evaluated a method to relate all seismic arrivals, including primaries and multiples, to their originating reflectors. We used the reflectivity forward modeling method to isolate reflectors and determine the contribution of an individual reflector to arrivals in a seismic trace. Repeating this process for all reflectors produced a reflector spectrum, which shows quantitatively the relative contribution of each reflector to all arrivals in a trace. Then we modified the reflector spectrum to relate seismic arrivals only to their shallowest reflectors. We applied the reflector spectrum and the modified reflector spectrum to a velocity model constructed from a field sonic log. We provided an indication of the minimum number of reflectors responsible for multiples and demonstrated that internal multiples originate from many reflectors distributed throughout the model, rather than from a few major ones.

Internal multiple prediction using inverse scattering series withsparsity promotionPart II: Application strategy and field data examples

Geophysics ◽  
2021 ◽  
pp. 1-52
Author(s):  
Ole Edvard Aaker ◽  
Adriana Citlali Ramírez ◽  
Emin Sadikhov
Keyword(s):  
Inverse Scattering ◽  
Field Data ◽  
Norwegian Sea ◽  
Prediction Quality ◽  
Inverse Scattering Series ◽  
Exploration And Production ◽  
Internal Multiples ◽  
Multiple Prediction ◽  
Seismic Images

Incorrect imaging of internal multiples can lead to substantial imaging artefacts. It is estimatedthat the majority of seismic images available to exploration and production companies have had nodirect attempt at internal multiple removal. In Part I of this article we considered the role of spar-sity promoting transforms for improving practical prediction quality for algorithms derived fromthe inverse scattering series (ISS). Furthermore, we proposed a demigration-migration approach toperform multidimensional internal multiple prediction with migrated data and provided a syntheticproof of concept. In this paper (Part II) we consider application of the demigration-migration approach to field data from the Norwegian Sea, and provide a comparison to a post-stack method (froma previous related work). Beyond application to a wider range of data with the proposed approach,we consider algorithmic and implementational optimizations of the ISS prediction algorithms tofurther improve the applicability of the multidimensional formulations.

Improving seismic image using the common-horizon panel

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. S449-S458
Author(s):  
Lu Liu
Keyword(s):  
Time Lag ◽  
Velocity Model ◽  
Migration Velocity ◽  
Quantitative Information ◽  
Time Shift ◽  
Velocity Models ◽  
Seismic Image ◽  
The Common ◽  
Seismic Images ◽  
Zero Time

Generating high-quality seismic images requires accurate velocity models. However, velocity errors are predictably brought into the models. To mitigate the influences of velocity errors, we have used the common-horizon panel (CHP) for migration velocity analysis. CHP provides quantitative information to adjust mispositioned interfaces or correct deformed wavefields, which leads to improved image quality. It is generated by extrapolating seismic gathers to a selected target horizon and applying the time-shift imaging condition. Compared with the commonly used common-image gathers, the events in CHPs are more trackable because geologic interfaces are typically continuous in space. For a correct velocity model, the panel indicates a flat event at zero time lag, whereas in the case of an erroneous velocity model, the event becomes kinematically oscillating. This distinguishing difference provides a practical criterion to verify whether the migration velocity model is correct and to estimate the velocity or wavefield errors based on how much the event deviates from zero time lag. Tests on synthetic and field data sets have shown that the seismic images are improved by using the proposed CHP technique.

Postmap migration of crosswell reflection seismic data

Geophysics ◽  
2002 ◽  
Vol 67 (1) ◽  
pp. 135-146 ◽  
Author(s):  
Joongmoo Byun ◽  
James W. Rector III ◽  
Tamas Nemeth
Keyword(s):  
Constant Velocity ◽  
Guided Waves ◽  
Synthetic Data ◽  
Velocity Model ◽  
Lateral Resolution ◽  
Velocity Variation ◽  
Coherent Noise ◽  
Image Domain ◽  
Seismic Reflection Data ◽  
Specific Implementation

Vertical seismic profiling/common depth point (VSP‐CDP) mapping is often preferred to crosswell migration when imaging crosswell seismic reflection data. The principal advantage of VSP‐CDP mapping is that it can be configured as a one‐to‐one operation between data in the acquisition domain and data in the image domain and therefore does not smear coherent noise such as tube waves, guided waves, and converted waves as crosswell migration could. However, unlike crosswell migration, VSP‐CDP mapping cannot collapse diffractions; therefore, the lateral resolution of reflection events suffers. We present a migration algorithm that is applied to the crosswell data after they have been mapped. By performing crosswell migration in two distinct steps—mapping followed by diffraction stacking—noise events can be identified and filtered in the mapped domain without smearing effects commonly associated with conventional crosswell migration operators. Tests on noise‐free synthetic crosswell data indicate that the two‐step migration yields results nearly identical with conventional crosswell migration. Our specific implementation of the two‐step migration algorithm maps the data using an estimate of the interwell velocity field and then performs diffraction stacking using a constant‐velocity assumption. The migrated results are confined to the mapped region to reduce edge effects commonly associated with conventional crosswell migration. Results from synthetic data indicate that the constant‐velocity assumption used for diffraction stacking is remarkably robust, even for models with large vertical velocity variation. It is, however, important that the data are mapped with the correct interwell velocity model. After applying postmap migration to two field data sets mapped by VSP‐CDP mapping, better fault resolution was achieved and the lateral resolution was improved significantly.

scholarly journals Internal multiple prediction and removal using Marchenko autofocusing and seismic interferometry

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. A7-A11 ◽  
Author(s):  
Giovanni Angelo Meles ◽  
Katrin Löer ◽  
Matteo Ravasi ◽  
Andrew Curtis ◽  
Carlos Alberto da Costa Filho
Keyword(s):  
Green's Functions ◽  
Green’S Functions ◽  
Velocity Model ◽  
Seismic Interferometry ◽  
Reverse Time ◽  
Coherent Noise ◽  
Surface Reflection ◽  
Reflection Data ◽  
Time Migration ◽  
Internal Multiples

Standard seismic processing steps such as velocity analysis and reverse time migration (imaging) usually assume that all reflections are primaries: Multiples represent a source of coherent noise and must be suppressed to avoid imaging artifacts. Many suppression methods are relatively ineffective for internal multiples. We show how to predict and remove internal multiples using Marchenko autofocusing and seismic interferometry. We first show how internal multiples can theoretically be reconstructed in convolutional interferometry by combining purely reflected, up- and downgoing Green’s functions from virtual sources in the subsurface. We then generate the relevant up- and downgoing wavefields at virtual sources along discrete subsurface boundaries using autofocusing. Then, we convolve purely scattered components of up- and downgoing Green’s functions to reconstruct only the internal multiple field, which is adaptively subtracted from the measured data. Crucially, this is all possible without detailed modeled information about the earth’s subsurface. The method only requires surface reflection data and estimates of direct (nonreflected) arrivals between subsurface virtual sources and the acquisition surface. The method is demostrated on a stratified synclinal model and shown to be particularly robust against errors in the reference velocity model used.

scholarly journals Imaging vertical structures using Marchenko methods with vertical seismic-profile data

Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. S103-S113 ◽  
Author(s):  
Angus Lomas ◽  
Satyan Singh ◽  
Andrew Curtis
Keyword(s):  
Synthetic Data ◽  
Arbitrary Point ◽  
Seismic Profile ◽  
Single Scattering ◽  
Variable Density ◽  
Vertical Seismic Profile ◽  
The Earth ◽  
Imaging Result ◽  
Fault Structures ◽  
Internal Multiples

Marchenko methods use seismic data acquired at or near the surface of the earth to estimate seismic signals as if the receiver (now a virtual receiver) was at an arbitrary point inside the subsurface of the earth. This process is called redatuming, and it is central to subsurface imaging. Marchenko methods estimate the multiply scattered components of these redatumed signals, which is not the case for most other redatuming techniques that are based on single-scattering assumptions. As a result, images created using Marchenko redatumed signals contain a reduction in the artifacts that usually contaminate migrated seismic images due to improper handling of internal multiples. We exploit recent theoretical advances that enable virtual sources and virtual receivers to be placed at arbitrary points inside the subsurface as a means to incorporate vertical seismic profile (VSP) data into Marchenko methods. The advantage of including this type of data is that the additional acquisition boundary increases subsurface illumination, which in turn enables vertical interfaces and steeply dipping structures to be imaged. We develop this methodology using two synthetic data sets. The first is created using a simple variable density but constant velocity subsurface model. In this example, we find that our newly devised VSP Marchenko imaging methodology enables imaging of horizontal and vertical structures and that optimal results are achieved by combining these images with those created using standard Marchenko imaging. A second example demonstrates that the method can be applied to more realistic subsurface structures, in this case a modified version of the Marmousi 2 model. We determine the applicability of the methods to image fault structures with the final imaging result containing reduced contamination due to internal multiples and an improvement in the imaging of fault structures when compared to other standard imaging methods alone.

Suppressing unwanted internal reflections in prestack reverse-time migration

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. E79-E82 ◽  
Author(s):  
Robin P. Fletcher ◽  
Paul J. Fowler ◽  
Phil Kitchenside ◽  
Uwe Albertin
Keyword(s):  
Wave Equation ◽  
High Velocity ◽  
Synthetic Data ◽  
Velocity Model ◽  
Image Artifacts ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Damping Term ◽  
Time Migration ◽  
Directional Damping

Prestack reverse-time migration, a wave-equation technique using two-way propagation, correctly handles multiarrivals and enables imaging of overturned reflections. However, image artifacts occur when backscattered waves cross-correlate. These artifacts are particularly strong where high-velocity contrasts occur. A method for removing unwanted internal reflections during propagation of both the source and receiver wavefields is presented. This method applies a directional damping term to the wave equation in areas of the velocity model where unwanted reflections occur. Tests on synthetic data show good suppression of image artifacts.

Seismic demigration/migration in the curvelet domain

Geophysics ◽  
2008 ◽  
Vol 73 (2) ◽  
pp. S35-S46 ◽  
Author(s):  
Hervé Chauris ◽  
Truong Nguyen
Keyword(s):  
Input Data ◽  
Plane Waves ◽  
Synthetic Data ◽  
Velocity Model ◽  
Local Velocity ◽  
Data Set ◽  
Migration Operator ◽  
Local Plane ◽  
Seismic Images

Curvelets can represent local plane waves. They efficiently decompose seismic images and possibly imaging operators. We study how curvelets are distorted after demigration followed by migration in a different velocity model. We show that for small local velocity perturbations, the demigration/migration is reduced to a simple morphing of the initial curvelet. The derivation of the expected curvature of the curvelets shows that it is easier to sparsify the demigration/migration operator than the migration operator. An application on a 2D synthetic data set, generated in a smooth heterogeneous velocity model and with a complex reflectivity, demonstrates the usefulness of curvelets to predict what a migrated image would become in a locally different velocity model without the need for remigrating the full input data set. Curvelets are thus well suited to study the sensitivity of a prestack depth-migrated image with respect to the heterogeneous velocity model used for migration.

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