3D surface-related multiple elimination: Data reconstruction and application to field data

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. E25-E33 ◽  
Author(s):  
Anatoly Baumstein ◽  
Mohamed T. Hadidi
Keyword(s):  
Field Data ◽  
Higher Order ◽  
Three Dimensions ◽  
Approximate Algorithm ◽  
Data Reconstruction ◽  
Reconstruction Procedure ◽  
The Common ◽  
Marine Data ◽  
Multiple Prediction ◽  
Multiple Elimination

The wide success of 2D surface-related multiple elimination (SRME) in attenuating complex multiples in many cases has spurred efforts to apply the method in three dimensions. However, application of 3D SRME to conventional marine data is often impeded by severe crossline aliasing characteristic of marine acquisition geometries. We propose to overcome this limitation using a dip-moveout (DMO)-based procedure consisting of the following steps: resorting the data into common offsets to improve crossline sampling, performing DMO to eliminate azimuth variations in the common-offset domain, and efficiently implementing inverse shot-record DMO to reconstruct densely sampled shot records required for 3D SRME to predict multiples correctly. We use a field data example to demonstrate that the proposed shot reconstruction procedure leads to kinematically accurate reconstruction of primaries but may not be able to simultaneously position multiples correctly. The mispositioning of multiples becomes a problem when second- and higher-order multiples must be predicted. We propose to resolve this difficulty by using a layer-stripping approach to multiple prediction. Alternatively, an approximate algorithm that relies on adaptive subtraction to compensate for inaccurate positioning of predicted multiples can be used. Application of the latter approach is illustrated with a field data example, and its performance is evaluated quantitatively through a measurement of S/N ratio improvement. We demonstrate that a DMO-based implementation of 3D SRME outperforms conventional 2D SRME and can accurately predict and attenuate complex 3D multiples.

scholarly journals A perspective on 3D surface-related multiple elimination

Geophysics ◽  
2010 ◽  
Vol 75 (5) ◽  
pp. 75A245-75A261 ◽  
Author(s):  
Bill Dragoset ◽  
Eric Verschuur ◽  
Ian Moore ◽  
Richard Bisley
Keyword(s):  
Spatial Distribution ◽  
Field Data ◽  
Data Sets ◽  
Data Interpolation ◽  
It Use ◽  
Data Sparseness ◽  
Multiple Attenuation ◽  
3D Surface ◽  
Multiple Prediction ◽  
Multiple Elimination

Surface-related multiple elimination (SRME) is an algorithm that predicts all surface multiples by a convolutional process applied to seismic field data. Only minimal preprocessing is required. Once predicted, the multiples are removed from the data by adaptive subtraction. Unlike other methods of multiple attenuation, SRME does not rely on assumptions or knowledge about the subsurface, nor does it use event properties to discriminate between multiples and primaries. In exchange for this “freedom from the subsurface,” SRME requires knowledge of the acquisition wavelet and a dense spatial distribution of sources and receivers. Although a 2D version of SRME sometimes suffices, most field data sets require 3D SRME for accurate multiple prediction. All implementations of 3D SRME face a serious challenge: The sparse spatial distribution of sources and receivers available in typical seismic field data sets does not conform to the algorithmic requirements. There are several approaches to implementing 3D SRME that address the data sparseness problem. Among those approaches are pre-SRME data interpolation, on-the-fly data interpolation, zero-azimuth SRME, and true-azimuth SRME. Field data examples confirm that (1) multiples predicted using true-azimuth 3D SRME are more accurate than those using zero-azimuth 3D SRME and (2) on-the-fly interpolation produces excellent results.

Adaptive separation of free-surface multiples through independent component analysis

Geophysics ◽  
2008 ◽  
Vol 73 (3) ◽  
pp. V29-V36 ◽  
Author(s):  
Sam T. Kaplan ◽  
Kristopher A. Innanen
Keyword(s):  
Free Surface ◽  
Independent Component Analysis ◽  
Blind Source Separation ◽  
Field Data ◽  
Component Analysis ◽  
Independent Component ◽  
Separation Technique ◽  
Prediction Formula ◽  
Multiple Prediction ◽  
Multiple Elimination

We present a three-stage algorithm for adaptive separation of free-surface multiples. The free-surface multiple elimination (FSME) method requires, as deterministic prerequisites, knowledge of the source wavelet and deghosted data. In their absence, FSME provides an estimate of free-surface multiples that must be subtracted adaptively from the data. First we construct several orders from the free-surface multiple prediction formula. Next we use the full recording duration of any given data trace to construct filters that attempt to match the data and the multiple predictions. This kind of filter produces adequate phase results, but the order-by-order nature of the free-surface algorithm brings results that remain insufficient for straightforward subtraction. Then we construct, trace by trace, a mixing model in which the mixtures are the data trace and its orders of multiple predictions. We separate the mixtures through a blind source separation technique, in particular by employing independent component analysis. One of the recovered signals is a data trace without free-surface multiples. This technique sidesteps the subtraction inherent in most adaptive subtraction methods by separating the desired signal from the free-surface multiples. The method was applied to synthetic and field data. We compared the field data to a published method and found comparable results.

Multiple prediction and subtraction from apparent slowness relations in 2D synthetic and field ocean-bottom cable data

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. V89-V99 ◽  
Author(s):  
Juanjuan Cao ◽  
George McMechan
Keyword(s):  
Seismic Data ◽  
Field Data ◽  
Time Window ◽  
Fixed Time ◽  
Higher Order ◽  
Common Source ◽  
Spatial Average ◽  
Ocean Bottom ◽  
Multiple Reflections ◽  
Multiple Prediction

A target-oriented algorithm is developed for the prediction of multiples recorded on ocean-bottom cables by utilizing apparent slowness relations in common-source and common-receiver gathers. It is based on combining offsets and times of direct waves and primary reflections to predict multiples by matching apparent slownesses at all source and receiver locations; all higher-order multiples can be predicted by matching apparent slownesses alternately in common-source and common-receiver gathers. No knowledge of the subsurface velocity is required. Traveltimes of the direct waves and primary reflections need to be picked from common-source gathers. The subtraction of multiples involves flattening the predicted times of the multiple events, subtracting a local spatial average trace from each trace, within a fixed time window containing the wavelet of the multiple, and then shifting the data back to its original times. Tests of synthetic and field data indicate that the proposed method predicts multiples very well and removes them from seismic data efficiently with negligible affect on the primary reflections, as long as the primary and multiple reflections do not overlap in time and slowness over substantial windows in the domain in which the removal is done.

scholarly journals 3D surface-related multiple prediction: A sparse inversion approach

Geophysics ◽  
2005 ◽  
Vol 70 (3) ◽  
pp. V31-V43 ◽  
Author(s):  
E. J. van Dedem ◽  
D. J. Verschuur
Keyword(s):  
Input Data ◽  
Synthetic Data ◽  
Data Set ◽  
3D Surface ◽  
Parametric Inversion ◽  
Sparse Inversion ◽  
Marine Data ◽  
Multiple Prediction ◽  
Multiple Elimination

The theory of iterative surface-related multiple elimination holds for 2D as well as 3D wavefields. The 3D prediction of surface multiples, however, requires a dense and extended distribution of sources and receivers at the surface. Since current 3D marine acquisition geometries are very sparsely sampled in the crossline direction, the direct Fresnel summation of the multiple contributions, calculated for those surface positions at which a source and a receiver are present, cannot be applied without introducing severe aliasing effects. In this newly proposed method, the regular Fresnel summation is applied to the contributions in the densely sampled inline direction, but the crossline Fresnel summation is replaced with a sparse parametric inversion. With this procedure, 3D multiples can be predicted using the available input data. The proposed method is demonstrated on a 3D synthetic data set as well as on a 3D marine data set from offshore Norway.

Advantages of Complementary Stereo Images as Viewed with the Low-Temperature Field-Emission SEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1314-1315
Author(s):  
William P. Wergin ◽  
Eric F. Erbe
Keyword(s):  
Fold Increase ◽  
Horizontal Displacement ◽  
Three Dimensions ◽  
Stereo Image ◽  
Stereo Pair ◽  
Sem Micrograph ◽  
Left And Right ◽  
The Common ◽  
The Brain ◽  
Pair Analysis

The eye-brain complex allows those of us with normal vision to perceive and evaluate our surroundings in three-dimensions (3-D). The principle factor that makes this possible is parallax - the horizontal displacement of objects that results from the independent views that the left and right eyes detect and simultaneously transmit to the brain for superimposition. The common SEM micrograph is a 2-D representation of a 3-D specimen. Depriving the brain of the 3-D view can lead to erroneous conclusions about the relative sizes, positions and convergence of structures within a specimen. In addition, Walter has suggested that the stereo image contains information equivalent to a two-fold increase in magnification over that found in a 2-D image. Because of these factors, stereo pair analysis should be routinely employed when studying specimens.Imaging complementary faces of a fractured specimen is a second method by which the topography of a specimen can be more accurately evaluated.

scholarly journals N-soliton solutions and the Hirota conditions in (1 + 1)-dimensions

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Wen-Xiu Ma
Keyword(s):  
Common Factors ◽  
Soliton Solutions ◽  
Higher Order ◽  
Kdv Equations ◽  
The Common ◽  
Bilinear Formulation ◽  
Generalized Kdv Equations ◽  
Hirota Bilinear

Abstract We analyze N-soliton solutions and explore the Hirota N-soliton conditions for scalar (1 + 1)-dimensional equations, within the Hirota bilinear formulation. An algorithm to verify the Hirota conditions is proposed by factoring out common factors out of the Hirota function in N wave vectors and comparing degrees of the involved polynomials containing the common factors. Applications to a class of generalized KdV equations and a class of generalized higher-order KdV equations are made, together with all proofs of the existence of N-soliton solutions to all equations in two classes.

MIXED CONFORMING ELEMENTS FOR THE LARGE-BODY LIMIT IN MICROMAGNETICS

2013 ◽  
Vol 24 (01) ◽  
pp. 113-144 ◽  
Author(s):  
MARKUS AURADA ◽  
JENS M. MELENK ◽  
DIRK PRAETORIUS
Keyword(s):  
Mixed Finite Element ◽  
Large Body ◽  
Mixed Finite Element Method ◽  
Adaptive Strategy ◽  
Posteriori Error ◽  
Higher Order ◽  
Three Dimensions ◽  
Macroscopic Model ◽  
Error Estimator ◽  
Discrete Problem

We introduce a stabilized conforming mixed finite element method for a macroscopic model in micromagnetics. We show well-posedness of the discrete problem for higher order elements in two and three dimensions, develop a full a priori analysis for lowest order elements, and discuss the extension of the method to higher order elements. We introduce a residual-based a posteriori error estimator and present an adaptive strategy. Numerical examples illustrate the performance of the method.

Surface-related multiple elimination on wide-tow marine data

2002 ◽  
Vol 21 (8) ◽  
pp. 787-790 ◽  
Author(s):  
Mohamed T. Hadidi ◽  
Anatoly I. Baumstein ◽  
Young C. Kim
Keyword(s):  
Marine Data ◽  
Multiple Elimination

scholarly journals Zika mosquito vectors: the jury is still out

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2546 ◽  
Author(s):  
Walter S. Leal
Keyword(s):  
Aedes Aegypti ◽  
Yellow Fever ◽  
Culex Quinquefasciatus ◽  
Zika Virus ◽  
Field Data ◽  
Vector Competence ◽  
Sexual Transmission ◽  
Mosquito Vectors ◽  
Yellow Fever Mosquito ◽  
The Common

After a 40-year hiatus, the International Congress of Entomology (ICE 2016) convened in Orlando, Florida (September 25-30, 2016). One of the symposia at ICE 2016, the Zika Symposium, covered multiple aspects of the Zika epidemic, including epidemiology, sexual transmission, genetic tools for reducing transmission, and particularly vector competence. While there was a consensus among participants that the yellow fever mosquito, Aedes aegypti, is a vector of the Zika virus, there is growing evidence indicating that the range of mosquito vectors might be wider than anticipated. In particular, three independent groups from Canada, China, and Brazil presented and discussed laboratory and field data strongly suggesting that the southern house mosquito, Culex quinquefasciatus, also known as the common mosquito, is highly likely to be a vector in certain environments.

scholarly journals The Yang-Mills heat equation with finite action in three dimensions

2022 ◽  
Vol 275 (1349) ◽  
Author(s):  
Leonard Gross
Keyword(s):  
Heat Equation ◽  
Three Dimensional ◽  
Strong Solutions ◽  
Three Dimensions ◽  
Dimensional Manifold ◽  
Uniqueness Of Solutions ◽  
Reconstruction Procedure ◽  
Content Type ◽  
Yang Mills ◽  
Gauge Functions

The existence and uniqueness of solutions to the Yang-Mills heat equation is proven over R 3 \mathbb {R}^3 and over a bounded open convex set in R 3 \mathbb {R}^3 . The initial data is taken to lie in the Sobolev space of order one half, which is the critical Sobolev index for this equation over a three dimensional manifold. The existence is proven by solving first an augmented, strictly parabolic equation and then gauge transforming the solution to a solution of the Yang-Mills heat equation itself. The gauge functions needed to carry out this procedure lie in the critical gauge group of Sobolev regularity three halves, which is a complete topological group in a natural metric but is not a Hilbert Lie group. The nature of this group must be understood in order to carry out the reconstruction procedure. Solutions to the Yang-Mills heat equation are shown to be strong solutions modulo these gauge functions. Energy inequalities and Neumann domination inequalities are used to establish needed initial behavior properties of solutions to the augmented equation.

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