Multidimensional inverse-scattering series internal multiple prediction in the coupled plane-wave domain

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. V73-V82 ◽  
Author(s):  
Jian Sun ◽  
Kristopher A. Innanen
Keyword(s):  
Plane Wave ◽  
Inverse Scattering ◽  
Radon Transforms ◽  
Seismic Reflection Data ◽  
Arrival Times ◽  
Computational Expense ◽  
Reflection Data ◽  
Inverse Scattering Series ◽  
Text Prediction ◽  
Multiple Prediction

The inverse-scattering series internal multiple prediction and attenuation algorithm predicts multiples using certain combinations of input seismic reflection data events, which are computed in the wavenumber/pseudodepth or plane-wave/vertical traveltime (i.e., [Formula: see text]) domains. Significant differences can arise in the algorithms’ output and computational expense depending on which domain is used. Many of these are traceable to the response of the algorithm to the users’ choice of the search-limiting parameter [Formula: see text]. The question of which domain is optimal can be addressed with benchmark synthetics. The compactness of the input to the plane-wave domain algorithm leads to the expectation that it will have a reduced computational expense. Also, the lack of increase in the dominant period (i.e., the “width”) of input events as the horizontal slowness increases leads to the expectation that it will respond well to a constant [Formula: see text]. Both of these expectations are borne out with a 1.5D benchmark example. A 2D plane-wave prediction requires the data to be transformed to the [Formula: see text], or coupled plane-wave, domain, involving source- and receiver-side horizontal slownesses. An implementation of this transform leads to the first numerical examples of full 2D inverse series [Formula: see text] prediction. The arrival times, relative amplitudes, and moveout patterns of multiples from dipping horizons are seen in a benchmark synthetic example to be faithfully determined in the plane-wave formulation; waveform mismatches are, however, observed, which are traceable to the numerics of the forward and inverse transforms. High-resolution Radon transforms are a good candidate to improve the match.

A plane-wave formulation and numerical analysis of elastic multicomponent inverse scattering series internal multiple prediction

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. V255-V269 ◽  
Author(s):  
Jian Sun ◽  
Kristopher A. Innanen
Keyword(s):  
Numerical Analysis ◽  
Plane Wave ◽  
Inverse Scattering ◽  
Simulated Data ◽  
Velocity Model ◽  
Prediction Algorithm ◽  
Inverse Scattering Series ◽  
Elastic Data ◽  
Reference Medium ◽  
Multiple Prediction

Internal multiple prediction and removal is a critical component of seismic data processing prior to imaging, inversion, and quantitative interpretation. Inverse scattering series methods predict multiples without identification of generators, and without requiring a velocity model. Land environments present several challenges to the inverse scattering series prediction process. This is particularly true for algorithm versions that explicitly account for elastic conversions and incorporate multicomponent data. The theory for elastic reference medium inverse scattering series internal multiple prediction was introduced several decades ago, but no numerical analysis or practical discussion of how to prepare data for it currently exists. We have focused our efforts on addressing this gap. We extend the theory from 2D to 3D, analyze the properties of the input data required by the existing algorithm, and, motivated by earlier research results, reformulate the algorithm in the plane-wave domain. The success of the prediction process relies on the ordering of events in either pseudodepth or vertical traveltime being the same as the ordering of reflecting interfaces in true depth. In elastic-multicomponent cases, it is difficult to ensure that this holds true because the events to be combined may have undergone multiple conversions as they were created. Several variants of the elastic-multicomponent prediction algorithm are introduced and examined for their tendency to violate ordering requirements (and create artifacts). A plane-wave domain prediction, based on elastic data that have been prepared (1) using variable, “best-fit” velocities as reference velocities, and (2) with an analytically determined vertical traveltime stretching formula, is identified as being optimal in the sense of generating artifact-free predictions with relatively small values of the search parameter [Formula: see text], while remaining fully data driven. These analyses are confirmed with simulated data from a layered model; these are the first numerical examples of elastic-multicomponent inverse scattering series internal multiple prediction.

Internal multiple prediction using inverse-scattering series with sparsity promotion — Part 1: Background, analysis, and synthetic modeling

Geophysics ◽  
2021 ◽  
pp. 1-94
Author(s):  
Ole Edvard Aaker ◽  
Adriana Citlali Ramírez ◽  
Emin Sadikhov
Keyword(s):  
Plane Wave ◽  
Inverse Scattering ◽  
Seismic Data ◽  
Data Completeness ◽  
Inverse Scattering Series ◽  
Recent Developments ◽  
Internal Multiples ◽  
Multiple Prediction ◽  
Synthetic Modeling ◽  
The Way

The presence of internal multiples in seismic data can lead to artefacts in subsurface images ob-tained by conventional migration algorithms. This problem can be ameliorated by removing themultiples prior to migration, if they can be reliably estimated. Recent developments have renewedinterest in the plane wave domain formulations of the inverse scattering series (ISS) internal multipleprediction algorithms. We build on this by considering sparsity promoting plane wave transformsto minimize artefacts and in general improve the prediction output. Furthermore, we argue forthe usage of demigration procedures to enable multidimensional internal multiple prediction withmigrated images, which also facilitate compliance with the strict data completeness requirementsof the ISS algorithm. We believe that a combination of these two techniques, sparsity promotingtransforms and demigration, pave the way for a wider application to new and legacy datasets.

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.

Precision analysis of first‐break times in grid models

Geophysics ◽  
1998 ◽  
Vol 63 (3) ◽  
pp. 1062-1065 ◽  
Author(s):  
Thomas Gruber ◽  
Stewart A. Greenhalgh
Keyword(s):  
Numerical Models ◽  
Grid Point ◽  
Tomographic Reconstruction ◽  
Velocity Model ◽  
Model Parameters ◽  
Seismic Reflection Data ◽  
Arrival Times ◽  
Velocity Models ◽  
Reflection Data ◽  
Inversion Techniques

Rectangular grid velocity models and their derivatives are widely used in geophysical inversion techniques. Specifically, seismic tomographic reconstruction techniques, whether they be based on raypath methods (Bregman et al., 1989; Moser, 1991; Schneider et al., 1992; Cao and Greenhalgh, 1993; Zhou, 1993) or full wave equation methods (Vidale, 1990; Qin and Schuster, 1993; Cao and Greenhalgh, 1994) for calculating synthetic arrival times, involve propagation through a grid model. Likewise, migration of seismic reflection data, using asymptotic ray theory or finite difference/pseudospectral methods (Stolt and Benson, 1986; Zhe and Greenhalgh, 1997) involve assigning traveltimes to upward and downward propagating waves at every grid point in the model. The traveltimes in both cases depend on the grid specification. However, the precision level of such numerical models and their dependence on the model parameters is often unknown. In this paper, we describe a two‐dimensional velocity model and derive an error bound for first‐break times calculated with such a model. The analysis provides clear guidelines for grid specifications.

Enhancing Internal Multiple Prediction by Using the Inverse Scattering Series

2020 ◽  
Author(s):  
J. Wu ◽  
Z. James Wu ◽  
F. Xavier de Melo ◽  
C. Lapilli ◽  
C. Kostov
Keyword(s):  
Inverse Scattering ◽  
Inverse Scattering Series ◽  
Multiple Prediction

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.

Using the inverse scattering series to predict the wavefield at depth and the transmitted wavefield without an assumption about the phase of the measured reflection data or back propagation in the overburden

Geophysics ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. SI125-SI137 ◽  
Author(s):  
A. B. Weglein ◽  
B. G. Nita ◽  
K. A. Innanen ◽  
E. Otnes ◽  
S. A. Shaw ◽  
...  
Keyword(s):  
Inverse Scattering ◽  
Back Propagation ◽  
Single Frequency ◽  
Data Mapping ◽  
Reflection Data ◽  
Construction Techniques ◽  
Starting Point ◽  
Transmission Data ◽  
Inverse Scattering Series ◽  
Reference Medium

The starting point for the derivation of a new set of approaches for predicting both the wavefield at depth in an unknown medium and transmission data from measured reflection data is the inverse scattering series. We present a selection of these maps that differ in order (i.e., linear or nonlinear), capability, and data requirements. They have their roots in the consideration of a data format known as the T-matrix and have direct applicability to the data construction techniques motivating this special issue. Of particular note, one of these, a construction of the wavefield at any depth (including the transmitted wavefield), order-by-order in the measured reflected wavefield, has an unusual set of capabilities (e.g., it does not involve an assumption regarding the minimum-phase nature of the data and is accomplished with processing in the simple reference medium only) and requirements (e.g., a suite of frequencies from surface data are required to compute a single frequency of the wavefield at depth when the subsurface is unknown). An alternative reflection-to-transmission data mapping (which does not require a knowledge of the wavelet, and in which the component of the unknown medium that is linear in the reflection data is used as a proxy for the component of the unknown medium that is linear in the transmission data) is also derivable from the inverse scattering series framework.

Harmonic distortion on a seismic reflection profile across the Quebec Appalachians: relation to Bouguer gravity and implications for crustal structure

1984 ◽  
Vol 21 (3) ◽  
pp. 346-353 ◽  
Author(s):  
Frederick A. Cook
Keyword(s):  
Seismic Reflection ◽  
Far East ◽  
Harmonic Distortion ◽  
High Amplitude ◽  
Seismic Reflection Profile ◽  
Bouguer Gravity ◽  
Seismic Reflection Data ◽  
Arrival Times ◽  
Amplitude Noise ◽  
Reflection Data

Seismic reflection data obtained across the Quebec Appalachians using the VIBROSEIS (trademark Conoco) technique were recorded with parameters that allowed harmonic distortion arrivals to interfere with layered reflections. The data exhibit reflections from layered miogeoclinal rocks dipping eastward beneath the allochthonous rocks of the orogen; the layering appears to terminate beneath the Notre Dame Anticlinorium. However, as the apparent termination of the layers also occurs at the arrival times of high-amplitude noise harmonics, it may have no geological significance. Precambrian Grenville crust, which probably underlies the layered sediments, extends at least as far east as the apparent termination, and may extend much farther. Examination of the Bouguer gravity field in relation to the seismic reflection data shows that a major gravity change is due to density differences that occur considerably west of the eastern limit of Precambrian Grenville crust. The gravity thus shows no correlation with surface structures proposed as suture zones. An actualistic model incorporates subduction of a passive (Atlantic-type) margin beneath an arc terrain during the Ordovician.

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.

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