Including and using internal multiples in closed-loop imaging — Field data examples

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. R297-R305 ◽  
Author(s):  
Mikhail Davydenko ◽  
D. J. Verschuur
Keyword(s):  
North Sea ◽  
Field Data ◽  
Closed Loop ◽  
Velocity Model ◽  
Measured Data ◽  
Data Interpolation ◽  
Migration Process ◽  
Multiple Reflections ◽  
Additional Illumination ◽  
Internal Multiples

Nowadays, it is more widely accepted that multiple reflections should not be considered as noise, but as signal that can provide additional illumination of the subsurface. However, one of the challenges in seismic imaging is including all multiples in the migration process for field data in a reliable manner. Although including surface multiples in imaging has been demonstrated already on field data in recent years, the proper imaging of internal multiples is less established. We have determined successful field data applications on imaging that takes all internal multiples into account. This is done via so-called full-wavefield migration (FWM), an inversion-based method in which, given the migration velocity model, the angle-dependent reflectivity is iteratively estimated by minimizing the misfit between the modeled and the measured data. Its forward model is based on a multidimensional version of the so-called Bremmer series, which allows modeling of transmission effects and any type of multiple scattering in the subsurface and, thereby, is able to minimize the data misfit correctly. An application of FWM on deepwater field data from the Norwegian North Sea validates its capabilities to explain and image internal multiples. Furthermore, it is demonstrated on the same field data that the FWM framework can also be used for data interpolation and primary/multiple separation.

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.

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 Removal of internal multiples with the common-focus-point (CFP) approach: Part 2 — Application strategies and data examples

Geophysics ◽  
2005 ◽  
Vol 70 (3) ◽  
pp. V61-V72 ◽  
Author(s):  
D. J. Verschuur ◽  
A. J. Berkhout
Keyword(s):  
Physical Model ◽  
Field Data ◽  
Velocity Model ◽  
Data Sets ◽  
Removal Method ◽  
The Past ◽  
Feedback Model ◽  
The Common ◽  
Internal Multiples ◽  
Focus Point

In the past, the surface-multiple-removal method based on the feedback model has been successfully applied to many different field data sets. The extension of surface to internal multiples can be made by replacing shot records with common-focus-point (CFP) gathers, a CFP gather representing focused data with one source in the subsurface and all receivers at the surface (or vice versa for a receiver gather). The internal-multiple-removal algorithm can be formulated in terms of boundary-related and layer-related versions. In the boundary-related version, the internal multiples are removed for one downward-scattering reflector at a time. In the layer-related version, the internal multiples are removed for a sequence of downward-scattering reflectors at a time. An exact velocity model is not required, but proper muting is critical; muting becomes straightforward in the CFP domain. The strategy for applying the two versions of the multiple-removal algorithm is demonstrated on physical-model and field data. One can conclude that the layer-related version is the most appropriate in most situations because it requires less user action and does not need exact knowledge of the multiple-generating boundary.

scholarly journals A field data example of Marchenko multiple elimination

Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. S65-S70 ◽  
Author(s):  
Lele Zhang ◽  
Evert Slob
Keyword(s):  
North Sea ◽  
Seismic Data ◽  
Field Data ◽  
Multiple Reflections ◽  
Coherent Noise ◽  
Data Set ◽  
Model Independent ◽  
Multiple Elimination

Internal multiple reflections have been widely considered as coherent noise in measured seismic data, and many approaches have been developed for their attenuation. The Marchenko multiple elimination (MME) scheme eliminates internal multiple reflections without model information or adaptive subtraction. This scheme was originally derived from coupled Marchenko equations, but it was modified to make it model independent. It filters primary reflections with their two-way traveltimes and physical amplitudes from measured seismic data. The MME scheme is applied to a deepwater field data set from the Norwegian North Sea to evaluate its success in removing internal multiple reflections. The result indicates that most internal multiple reflections are successfully removed and primary reflections masked by overlapping internal multiple reflections are recovered.

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.

Removal of Internal Multiples - Field Data Examples

1997 ◽  
Author(s):  
M.T. Hadidi ◽  
D.J. Verschuur
Keyword(s):  
Field Data ◽  
Internal Multiples
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