Seismic imaging of deep crust

Geophysics ◽  
1979 ◽  
Vol 44 (10) ◽  
pp. 1637-1660 ◽  
Author(s):  
Robert A. Phinney ◽  
Donna M. Jurdy
Keyword(s):  
Continuation Method ◽  
Synthetic Data ◽  
Direction Of Arrival ◽  
Horizontal Displacement ◽  
Resolving Power ◽  
Common Source ◽  
Imaging Method ◽  
Data Set ◽  
Velocity Models ◽  
Unique Character

We introduce here an integral two‐dimensional (2-D) scheme for the processing of deep crustal reflection profiles. This approach, in which migration occurs before stacking, is tailored to the unique character of the data in which nonvertically propagating energy is as important as vertically propagating energy. Since reflector depths range beyond 30 km, the horizontal displacement of reflections which occurs in migration can be as large as reflector depths; under these circumstances, the common‐midpoint (CMP) stack is inadequate. In our scheme, each common‐source trace gather is transformed into a set of traces (beams) corresponding to set of different incidence angles. A correction for wavefront curvature similar to the normal moveout (NMO) correction yields traces (focused beams) which are focused at image points along the direction of arrival. While the method is equivalent to the Kirchhoff integral migration method, and therefore to any complete continuation method, it gives rise to an intermediate data set which is characterized by the direction of arrival of the upward propagating energy. By a geometrical transformation of the beams and summation, we may synthesize images composed of a specified range of Fourier spatial components. Geologic examples suggest that complex structures in the basement may be most easily characterized by their local direction of layering, a quantity we may determine by this approach. Noise‐free synthetic data examples illustrate the limits of horizontal and vertical resolving power at mid‐crustal depths for any imaging method. Velocity determination is difficult at these depths due to the small NMO and may be possible only by evaluating the effects of velocity models on the imaged data. Examples of the imaged section from the COCORP test profile in Hardeman County, Texas, show a combination of horizontally continuous reflectors and an irregular pattern of scatterers with locally horizontal layering.

Detection of sharp lateral discontinuities through the analysis of surface-wave propagation

Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. EN77-EN90 ◽  
Author(s):  
Paolo Bergamo ◽  
Laura Valentina Socco
Keyword(s):  
Surface Wave ◽  
Fault Location ◽  
Synthetic Data ◽  
Finite Element Method Simulation ◽  
Fault System ◽  
Energy Concentration ◽  
Data Sets ◽  
Data Set ◽  
Shallow Subsurface ◽  
Velocity Models

Surface-wave (SW) techniques are mainly used to retrieve 1D velocity models and are therefore characterized by a 1D approach, which might prove unsatisfactory when relevant 2D effects are present in the investigated subsurface. In the case of sharp and sudden lateral heterogeneities in the subsurface, a strategy to tackle this limitation is to estimate the location of the discontinuities and to separately process seismic traces belonging to quasi-1D subsurface portions. We have addressed our attention to methods aimed at locating discontinuities by identifying anomalies in SW propagation and attenuation. The considered methods are the autospectrum computation and the attenuation analysis of Rayleigh waves (AARW). These methods were developed for purposes and/or scales of analysis that are different from those of this work, which aims at detecting and characterizing sharp subvertical discontinuities in the shallow subsurface. We applied both methods to two data sets, synthetic data from a finite-element method simulation and a field data set acquired over a fault system, both presenting an abrupt lateral variation perpendicularly crossing the acquisition line. We also extended the AARW method to the detection of sharp discontinuities from large and multifold data sets and we tested these novel procedures on the field case. The two methods are proven to be effective for the detection of the discontinuity, by portraying propagation phenomena linked to the presence of the heterogeneity, such as the interference between incident and reflected wavetrains, and energy concentration as well as subsequent decay at the fault location. The procedures we developed for the processing of multifold seismic data set showed to be reliable tools in locating and characterizing subvertical sharp heterogeneities.

Migration moveout analysis and depth focusing

Geophysics ◽  
1993 ◽  
Vol 58 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Claude F. Lafond ◽  
Alan R. Levander
Keyword(s):  
Heterogeneous Media ◽  
A Priori ◽  
Complex Structure ◽  
Tomographic Reconstruction ◽  
Synthetic Data ◽  
Real Data ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Data Set ◽  
Velocity Models

Prestack depth migration still suffers from the problems associated with building appropriate velocity models. The two main after‐migration, before‐stack velocity analysis techniques currently used, depth focusing and residual moveout correction, have found good use in many applications but have also shown their limitations in the case of very complex structures. To address this issue, we have extended the residual moveout analysis technique to the general case of heterogeneous velocity fields and steep dips, while keeping the algorithm robust enough to be of practical use on real data. Our method is not based on analytic expressions for the moveouts and requires no a priori knowledge of the model, but instead uses geometrical ray tracing in heterogeneous media, layer‐stripping migration, and local wavefront analysis to compute residual velocity corrections. These corrections are back projected into the velocity model along raypaths in a way that is similar to tomographic reconstruction. While this approach is more general than existing migration velocity analysis implementations, it is also much more computer intensive and is best used locally around a particularly complex structure. We demonstrate the technique using synthetic data from a model with strong velocity gradients and then apply it to a marine data set to improve the positioning of a major fault.

scholarly journals Sensitivity analysis of the backprojection imaging method for seismic event location

2021 ◽  
Vol 11 (1) ◽  
pp. 21-32
Author(s):  
Cristian Alexis Murillo Martínez ◽  
William Mauricio Agudelo
Keyword(s):  
Sensitivity Analysis ◽  
Signal To Noise Ratio ◽  
Synthetic Data ◽  
Spatial Location ◽  
Noise Removal ◽  
Image Resolution ◽  
Imaging Method ◽  
Velocity Models ◽  
Event Location ◽  
Location Methods

Accuracy of earthquake location methods is dependent upon the quality of input data. In the real world, several sources of uncertainty, such as incorrect velocity models, low Signal to Noise Ratio (SNR), and poor coverage, affect the solution. Furthermore, some complex seismic signals exist without distinguishable phases for which conventional location methods are not applicable. In this work, we conducted a sensitivity analysis of Back-Projection Imaging (BPI), which is a technique suitable for location of conventional seismicity, induced seismicity, and tremor-like signals. We performed a study where synthetic data is modelled as fixed spectrum explosive sources. The purpose of using such simplified signals is to fully understand the mechanics of the location method in controlled scenarios, where each parameter can be freely perturbed to ensure that their individual effects are shown separately on the outcome. The results suggest the need for data conditioning such as noise removal to improve image resolution and minimize artifacts. Processing lower frequency signal increases stability, while higher frequencies improve accuracy. In addition, a good azimuthal coverage reduces the spatial location error of seismic events, where, according to our findings, depth is the most sensitive spatial coordinate to velocity and geometry changes.

Practical aspects and applications of 2D stereotomography

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 1008-1021 ◽  
Author(s):  
Frederic Billette ◽  
Soazig Le Bégat ◽  
Pascal Podvin ◽  
Gilles Lambaré
Keyword(s):  
Estimation Method ◽  
Synthetic Data ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Common Source ◽  
Depth Migration ◽  
Reflection Seismic ◽  
Velocity Models ◽  
Automatic Picking ◽  
Iterative Inversion

Stereotomography is a new velocity estimation method. This tomographic approach aims at retrieving subsurface velocities from prestack seismic data. In addition to traveltimes, the slope of locally coherent events are picked simultaneously in common offset, common source, common receiver, and common midpoint gathers. As the picking is realized on locally coherent events, they do not need to be interpreted in terms of reflection on given interfaces, but may represent diffractions or reflections from anywhere in the image. In the high‐frequency approximation, each one of these events corresponds to a ray trajectory in the subsurface. Stereotomography consists of picking and analyzing these events to update both the associated ray paths and velocity model. In this paper, we describe the implementation of two critical features needed to put stereotomography into practice: an automatic picking tool and a robust multiscale iterative inversion technique. Applications to 2D reflection seismic are presented on synthetic data and on a 2D line extracted from a 3D towed streamer survey shot in West Africa for TotalFinaElf. The examples demonstrate that the method requires only minor human intervention and rapidly converges to a geologically plausible velocity model in these two very different and complex velocity regimes. The quality of the velocity models is verified by prestack depth migration results.

Velocity model building in a crosswell acquisition geometry with image-trained artificial neural networks

Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. U31-U46
Author(s):  
Wenlong Wang ◽  
Jianwei Ma
Keyword(s):  
Wave Equations ◽  
Model Building ◽  
Velocity Model ◽  
P Wave ◽  
Common Source ◽  
Data Set ◽  
Velocity Models ◽  
Velocity Model Building ◽  
Artificial Neural ◽  
The Cost

We have developed an artificial neural network to estimate P-wave velocity models directly from prestack common-source gathers. Our network is composed of a fully connected layer set and a modified fully convolutional layer set. The parameters in the network are tuned through supervised learning to map multishot common-source gathers to velocity models. To boost the generalization ability, the network is trained on a massive data set in which the velocity models are modified from natural images that are collected from an online repository. Multishot seismic traces are simulated from those models with acoustic wave equations in a crosswell acquisition geometry. Shot gathers from different source positions are transformed as channels in the network to increase data redundancy. The training process is expensive, but it only occurs once up front. The cost for predicting velocity models is negligible once the training is complete. Different variations of the network are trained and analyzed. The trained networks indicate encouraging results for predicting velocity models from prestack seismic data that are acquired with the same geometry as in the training set.

Visibility analysis for optimal imaging of target areas and its application to a Gulf of Mexico deep-water data set

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB119-WB126 ◽  
Author(s):  
Elive Menyoli ◽  
Shengwen Jin ◽  
Shiyong Xu ◽  
Stuart Graber
Keyword(s):  
Gulf Of Mexico ◽  
Synthetic Data ◽  
Target Area ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Visibility Analysis ◽  
Velocity Models ◽  
Time Migration ◽  
Subsalt Imaging

Marine wide-azimuth data in the Gulf of Mexico, reverse time migration (RTM) and anisotropic velocity models have led to significant improvement in subsalt imaging. However, imaging of some steeply dipping subsalt targets such as three-way closures against salt is still difficult. This can be attributed to poor illumination and noise contaminations from various shot records. We apply the visibility analysis method that quantitatively determines which shot records contribute most energy on a specific subsalt prospect area. As a result we selectively migrate only those shot records thereby reducing noise contamination from low energy contributing shot records, improving signal continuity and better trap definition in the target area. Like conventional illumination analysis, the computation takes into account the overburden velocity distribution, acquisition geometry, target reflectivity and dip angle. We used 2D and 3D synthetic data examples to test the concepts and applicability of the method. A Gulf of Mexico case study example using wide-azimuth data demonstrated its use in an industry scale project. It is shown that for the particular 60°–65° subsalt target of interest only 30% of the wide-azimuth shot records are sufficient for the imaging. By reducing noise, the image results show significant improvement in the subsalt area compared to the full shot record RTM volume.

Occam’s inversion to generate smooth, two‐dimensional models from magnetotelluric data

Geophysics ◽  
1990 ◽  
Vol 55 (12) ◽  
pp. 1613-1624 ◽  
Author(s):  
C. deGroot‐Hedlin ◽  
S. Constable
Keyword(s):  
Joint Inversion ◽  
Synthetic Data ◽  
Real Data ◽  
Theoretical Models ◽  
Resolving Power ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Occam’S Inversion ◽  
Non Gaussian ◽  
True Structure

Magnetotelluric (MT) data are inverted for smooth 2-D models using an extension of the existing 1-D algorithm, Occam’s inversion. Since an MT data set consists of a finite number of imprecise data, an infinity of solutions to the inverse problem exists. Fitting field or synthetic electromagnetic data as closely as possible results in theoretical models with a maximum amount of roughness, or structure. However, by relaxing the misfit criterion only a small amount, models which are maximally smooth may be generated. Smooth models are less likely to result in overinterpretation of the data and reflect the true resolving power of the MT method. The models are composed of a large number of rectangular prisms, each having a constant conductivity. [Formula: see text] information, in the form of boundary locations only or both boundary locations and conductivity, may be included, providing a powerful tool for improving the resolving power of the data. Joint inversion of TE and TM synthetic data generated from known models allows comparison of smooth models with the true structure. In most cases, smoothed versions of the true structure may be recovered in 12–16 iterations. However, resistive features with a size comparable to depth of burial are poorly resolved. Real MT data present problems of non‐Gaussian data errors, the breakdown of the two‐dimensionality assumption and the large number of data in broadband soundings; nevertheless, real data can be inverted using the algorithm.

Localized anisotropic tomography with well information in VTI media

Geophysics ◽  
2010 ◽  
Vol 75 (5) ◽  
pp. D37-D45 ◽  
Author(s):  
Andrey Bakulin ◽  
Marta Woodward ◽  
Dave Nichols ◽  
Konstantin Osypov ◽  
Olga Zdraveva
Keyword(s):  
Vertical Velocity ◽  
Seismic Data ◽  
Model Building ◽  
Synthetic Data ◽  
Resolution Limit ◽  
Data Set ◽  
Anisotropic Models ◽  
Velocity Models ◽  
First Case ◽  
Well Data

We develop a concept of localized seismic grid tomography constrained by well information and apply it to building vertically transversely isotropic (VTI) velocity models in depth. The goal is to use a highly automated migration velocity analysis to build anisotropic models that combine optimal image focusing with accurate depth positioning in one step. We localize tomography to a limited volume around the well and jointly invert the surface seismic and well data. Well information is propagated into the local volume by using the method of preconditioning, whereby model updates are shaped to follow geologic layers with spatial smoothing constraints. We analyze our concept with a synthetic data example of anisotropic tomography applied to a 1D VTI model. We demonstrate four cases of introducing additionalinformation. In the first case, vertical velocity is assumed to be known, and the tomography inverts only for Thomsen’s [Formula: see text] and [Formula: see text] profiles using surface seismic data alone. In the second case, tomography simultaneously inverts for all three VTI parameters, including vertical velocity, using a joint data set that consists of surface seismic data and vertical check-shot traveltimes. In the third and fourth cases, sparse depth markers and walkaway vertical seismic profiling (VSP) are used, respectively, to supplement the seismic data. For all four examples, tomography reliably recovers the anisotropic velocity field up to a vertical resolution comparable to that of the well data. Even though walkaway VSP has the additional dimension of angle or offset, it offers no further increase in this resolution limit. Anisotropic tomography with well constraints has multiple advantages over other approaches and deserves a place in the portfolio of model-building tools.

scholarly journals Application of DOI index to analysis of selected examples of resistivity imaging models in Quaternary sediments

2014 ◽  
Vol 31 (2) ◽  
pp. 109-114 ◽  
Author(s):  
Michał Glazer ◽  
Maciej Jan Mendecki ◽  
Mateusz Mycka
Keyword(s):  
Cross Sections ◽  
Synthetic Data ◽  
Geological Structure ◽  
Imaging Method ◽  
Quaternary Sediments ◽  
Data Set ◽  
Resistivity Imaging ◽  
Geological Information ◽  
High Utility ◽  
Index Maps

AbstractInterpretation of resistivity cross sections may be in many cases unreliable due to the presence of artifacts left by the inversion process. One way to avoid erroneous conclusions about geological structure is creation of Depth of Investigation (DOI) index maps, which describe durability of prepared model with respect to variable parameters of inversion. To assess the usefulness of this interpretation methodology in resistivity imaging method over quaternary sediments, it has been used to one synthetic data set and three investigation sites. Two of the study areas were placed in the Upper Silesian Industrial District region: Bytom - Karb, Chorzów - Chorzow Stary; and one in the Southern Pomeranian Lake District across Piława River Valley. Basing on the available geological information the results show high utility of DOI index in analysis of received resistivity models, on which areas poorly constrained by data has been designated.

An efficient reverse time migration method using local nearly analytic discrete operator

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. S15-S23 ◽  
Author(s):  
Jingshuang Li ◽  
Dinghui Yang ◽  
Faqi Liu
Keyword(s):  
Finite Difference ◽  
Numerical Dispersion ◽  
Imaging Method ◽  
Discrete Operator ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Velocity Models ◽  
Time Migration ◽  
Nearly Analytic Discrete Operator

In recent years, reverse time migration (RTM), the most powerful depth imaging method, has become the preferred imaging tool in many geologic settings because of its ability to handle complex velocity models including steeply dipping interfaces. Finite difference is one of the most popular numerical methods applied in RTM in the industry. However, it often encounters a serious issue of numerical dispersion, which is typically suppressed by reducing the propagation grid sizes, resulting in large computation and memory increment. Recently, a nearly analytic discrete operator has been developed to approximate the partial differential operators, from which many antidispersion schemes have been proposed, and are confirmed to be superior to conventional algorithms in suppressing numerical dispersion. We apply an optimal nearly analytic discrete (ONAD) method to RTM to improve its accuracy and performance. Numerical results show that ONAD can be used effectively in seismic modeling and migration based on the full wave equations. This method produces little numerical dispersion and requires much less computation and memory compared to the traditional finite-difference methods such as Lax-Wendroff correction method. The reverse time migration results of the 2D Marmousi model and the Sigsbee2B data set show that ONAD can improve the computational efficiency and maintain image quality by using large extrapolation grids.

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