Migration in orthorhombic media: A prestack time-migration approach

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. C217-C227 ◽  
Author(s):  
Baoqing Tian ◽  
Jiangjie Zhang
Keyword(s):  
Synthetic Data ◽  
Real Data ◽  
High Resolution Imaging ◽  
Model Data ◽  
Data Set ◽  
Realistic Case ◽  
Time Migration ◽  
Novel Approach ◽  
Resolution Imaging ◽  
Prestack Time Migration

High-resolution imaging has become more popular recently in exploration geophysics. Conventionally, geophysicists image the subsurface using the isotropy approximation. When considering the anisotropy effects, one can expect to obtain an imaging profile with higher accuracy than the isotropy approach allows. Orthorhombic anisotropy is considered an ideal approximation in the realistic case. It has been used in the industry for several years. Although being attractive, broad application of orthorhombic anisotropy has many problems to solve. We have developed a novel approach of prestack time migration in the orthorhombic case. The traveltime and amplitude of a wave propagating in orthorhombic media are calculated directly by launching new anisotropic velocity and anisotropic parameters. We validate our methods with synthetic data. We also highlight our methods with model data set and real data. The results found that our methods work well for prestack time migration in orthorhombic media.

scholarly journals Simultaneous time imaging, velocity estimation, and multiple suppression using local event slopes

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCA65-WCA73 ◽  
Author(s):  
Dennis Cooke ◽  
Andrej Bóna ◽  
Benn Hansen
Keyword(s):  
Temporal Frequency ◽  
Synthetic Data ◽  
Migration Velocity ◽  
Velocity Estimation ◽  
Data Set ◽  
Image Domain ◽  
Kirchhoff Migration ◽  
Time Migration ◽  
Prestack Time Migration ◽  
Input Formula

Starting with the double-square-root equation we derive expressions for a velocity-independent prestack time migration and for the associated migration velocity. We then use that velocity to identify multiples and suppress them as part of the imaging step. To describe our algorithm, workflow, and products, we use the terms velocity-independent and oriented. While velocity-independent imaging does not require an input migration velocity, it does require input [Formula: see text]-values (also called local event slopes) measured in both the shot and receiver domains. There are many possible methods of calculating these required input [Formula: see text]-values, perhaps the simplest is to compute the ratio of instantaneous spatial frequency to instantaneous temporal frequency. Using a synthetic data set rich in multiples, we test the oriented algorithm and generate migrated prestack gathers, the oriented migration velocity field, and stacked migrations. We use oriented migration velocities for prestack multiple suppression. Without this multiple suppression step, the velocity-independent migration is inferior to a conventional Kirchhoff migration because the oriented migration will flatten primaries and multiples alike in the common image domain. With this multiple suppression step, the velocity-independent are very similar to a Kirchhoff migration generated using the known migration velocity of this test data set.

scholarly journals Accelerating High-Resolution Seismic Imaging by Using Deep Learning

2020 ◽  
Vol 10 (7) ◽  
pp. 2502 ◽  
Author(s):  
Wei Liu ◽  
Qian Cheng ◽  
Linong Liu ◽  
Yun Wang ◽  
Jianfeng Zhang
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Seismic Imaging ◽  
Training Data ◽  
High Resolution Imaging ◽  
Data Set ◽  
Time Migration ◽  
Resolution Imaging ◽  
Computationally Intensive ◽  
Dimension Space

The emerging applications of deep learning in solving geophysical problems have attracted increasing attention. In particular, it is of significance to enhance the computational efficiency of the computationally intensive geophysical algorithms. In this paper, we accelerate deabsorption prestack time migration (QPSTM), which can yield higher-resolution seismic imaging by compensating absorption and correcting dispersion through deep learning. This is implemented by training a neural network with pairs of small-sized patches of the stacked migrated results obtained by conventional PSTM and deabsorption QPSTM and then yielding the high-resolution imaging volume by prediction with the migrated results of conventional PSTM. We use an encoder-decoder network to highlight the features related to high-resolution migrated results in a high-order dimension space. The training data set of small-sized patches not only reduces the required high-resolution migrated result (for instance, only several inline is required) but leads to a fast convergence in training. The proposed deep-learning approach accelerates the high-resolution imaging by more than 100 times. Field data is used to demonstrate the effectiveness of the proposed method.

High-resolution imaging: a wavelet stretch correction in de-absorption prestack time migration approach

2020 ◽  
Vol 51 (4) ◽  
pp. 446-455
Author(s):  
Jin Wang ◽  
Jincheng Xu ◽  
Jiangfeng Zhang ◽  
Qiancheng Liu ◽  
Linong Liu
Keyword(s):  
High Resolution ◽  
High Resolution Imaging ◽  
Time Migration ◽  
Resolution Imaging ◽  
Prestack Time Migration

Prestack time migration of nonplanar data: Improving topography prestack time migration with dip-angle domain stationary-phase filtering and effective velocity inversion

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. S235-S246 ◽  
Author(s):  
Jincheng Xu ◽  
Jianfeng Zhang
Keyword(s):  
Stationary Phase ◽  
Real Data ◽  
Data Set ◽  
Near Surface ◽  
Velocity Inversion ◽  
Effective Velocity ◽  
Time Migration ◽  
Static Corrections ◽  
Prestack Time Migration ◽  
Dip Angle

We have developed a modified prestack time migration (PSTM) approach that can directly image nonplanar data by using two effective velocity parameters above and below a datum. The proposed extension improves the so-called topography PSTM by introducing a dip-angle domain stationary-phase migration (or filtering) and combining effective velocity inversion with the residual static corrections. The stationary-phase migration to constrain the imaging aperture within Fresnel zones significantly improves the signal-to-noise ratio (S/N) of the image gathers, especially in the presence of steeply dipping structures. This helps to extract an accurate residual moveout from the common shot and receiver image gathers, and the surface-consistent residual statics hidden in these image gathers can be simultaneously obtained from an inversion process. As a result, the final migrated images show higher S/N and are better focused than the conventional topography PSTM. The proposed technique can handle rugged topography, especially in the presence of high near-surface velocities, without the need for prior elevation static corrections. The SEG foothills overthrust model and a real data set acquired on a piedmont zone are used to validate the modified topography PSTM. Synthetic and field data examples are obtained with good results.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

High-resolution imaging: An approach by incorporating stationary-phase implementation into deabsorption prestack time migration

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. S317-S331 ◽  
Author(s):  
Jianfeng Zhang ◽  
Zhengwei Li ◽  
Linong Liu ◽  
Jin Wang ◽  
Jincheng Xu
Keyword(s):  
Stationary Phase ◽  
Fresnel Zone ◽  
Computational Cost ◽  
Computational Effort ◽  
Propagation Path ◽  
Time Migration ◽  
Resolution Imaging ◽  
Prestack Time Migration ◽  
Dip Angle ◽  
Absorption And Dispersion

We have improved the so-called deabsorption prestack time migration (PSTM) by introducing a dip-angle domain stationary-phase implementation. Deabsorption PSTM compensates absorption and dispersion via an actual wave propagation path using effective [Formula: see text] parameters that are obtained during migration. However, noises induced by the compensation degrade the resolution gained and deabsorption PSTM requires more computational effort than conventional PSTM. Our stationary-phase implementation improves deabsorption PSTM through the determination of an optimal migration aperture based on an estimate of the Fresnel zone. This significantly attenuates the noises and reduces the computational cost of 3D deabsorption PSTM. We have estimated the 2D Fresnel zone in terms of two dip angles through building a pair of 1D migrated dip-angle gathers using PSTM. Our stationary-phase QPSTM (deabsorption PSTM) was implemented as a two-stage process. First, we used conventional PSTM to obtain the Fresnel zones. Then, we performed deabsorption PSTM with the Fresnel-zone-based optimized migration aperture. We applied stationary-phase QPSTM to a 3D field data. Comparison with synthetic seismogram generated from well log data validates the resolution enhancements.

Clustering Mashups by Integrating Structural and Semantic Similarities Using Fuzzy AHP

2021 ◽  
Vol 18 (1) ◽  
pp. 34-57
Author(s):  
Weifeng Pan ◽  
Xinxin Xu ◽  
Hua Ming ◽  
Carl K. Chang
Keyword(s):  
Semantic Similarity ◽  
Clustering Algorithm ◽  
Latent Dirichlet Allocation ◽  
Fuzzy Ahp ◽  
Real Data ◽  
Structural Similarity ◽  
Analytic Hierarchy ◽  
Data Set ◽  
Novel Approach ◽  
Hierarchy Process

Mashup technology has become a promising way to develop and deliver applications on the web. Automatically organizing Mashups into functionally similar clusters helps improve the performance of Mashup discovery. Although there are many approaches aiming to cluster Mashups, they solely focus on utilizing semantic similarities to guide the Mashup clustering process and are unable to utilize both the structural and semantic information in Mashup profiles. In this paper, a novel approach to cluster Mashups into groups is proposed, which integrates structural similarity and semantic similarity using fuzzy AHP (fuzzy analytic hierarchy process). The structural similarity is computed from usage histories between Mashups and Web APIs using SimRank algorithm. The semantic similarity is computed from the descriptions and tags of Mashups using LDA (latent dirichlet allocation). A clustering algorithm based on the genetic algorithm is employed to cluster Mashups. Comprehensive experiments are performed on a real data set collected from ProgrammableWeb. The results show the effectiveness of the approach when compared with two kinds of conventional approaches.

scholarly journals Bayesian inversion of magnetotelluric data considering dimensionality discrepancies

2020 ◽  
Vol 223 (3) ◽  
pp. 1565-1583
Author(s):  
Hoël Seillé ◽  
Gerhard Visser
Keyword(s):  
Learning Algorithm ◽  
Synthetic Data ◽  
Real Data ◽  
Error Model ◽  
Bayesian Inversion ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Likelihood Functions ◽  
Training Images ◽  
Phase Tensor

SUMMARY Bayesian inversion of magnetotelluric (MT) data is a powerful but computationally expensive approach to estimate the subsurface electrical conductivity distribution and associated uncertainty. Approximating the Earth subsurface with 1-D physics considerably speeds-up calculation of the forward problem, making the Bayesian approach tractable, but can lead to biased results when the assumption is violated. We propose a methodology to quantitatively compensate for the bias caused by the 1-D Earth assumption within a 1-D trans-dimensional Markov chain Monte Carlo sampler. Our approach determines site-specific likelihood functions which are calculated using a dimensionality discrepancy error model derived by a machine learning algorithm trained on a set of synthetic 3-D conductivity training images. This is achieved by exploiting known geometrical dimensional properties of the MT phase tensor. A complex synthetic model which mimics a sedimentary basin environment is used to illustrate the ability of our workflow to reliably estimate uncertainty in the inversion results, even in presence of strong 2-D and 3-D effects. Using this dimensionality discrepancy error model we demonstrate that on this synthetic data set the use of our workflow performs better in 80 per cent of the cases compared to the existing practice of using constant errors. Finally, our workflow is benchmarked against real data acquired in Queensland, Australia, and shows its ability to detect the depth to basement accurately.

3D seismic imaging of volcanogenic massive sulfide deposits in the Flin Flon mining camp, Canada: Part 2 — Forward modeling

Geophysics ◽  
2012 ◽  
Vol 77 (5) ◽  
pp. WC81-WC93 ◽  
Author(s):  
Michal Malinowski ◽  
Ernst Schetselaar ◽  
Donald J. White
Keyword(s):  
Synthetic Data ◽  
Massive Sulfide ◽  
Ore Deposits ◽  
Earth Model ◽  
Seismic Modeling ◽  
Volcanogenic Massive Sulfide ◽  
Data Set ◽  
Rock Interaction ◽  
Time Migration ◽  
Flin Flon

We applied seismic modeling for a detailed 3D geologic model of the Flin Flon mining camp (Canada) to address some imaging and interpretation issues related to a [Formula: see text] 3D survey acquired in the camp and described in a complementary paper (part 1). A 3D geologic volumetric model of the camp was created based on a compilation of geologic data constraints from drillholes, surface geologic mapping, interpretation of 2D seismic profiles, and 3D surface and grid geostatistical modeling techniques. The 3D modeling methodology was based on a hierarchical approach to account for the heterogeneous spatial distribution of geologic constraints. Elastic parameters were assigned within the model based on core sample measurements and correlation with the different lithologies. The phase-screen algorithm used for seismic modeling was validated against analytic and finite-difference solutions to ensure that it provided accurate amplitude-variation-with-offset behavior for dipping strata. Synthetic data were generated to form zero-offset (stack) volume and also a complete prestack data set using the geometry of the real 3D survey. We found that the ability to detect a clear signature of the volcanogenic massive sulfide with ore deposits is dependent on the mineralization type (pyrite versus pyrrhotite rich ore), especially when ore-host rock interaction is considered. In the presence of an increasing fraction of the host rhyolite rock within the model volume, the response from the lower impedance pyrrhotite ore is masked by that of the rhyolite. Migration tests showed that poststack migration effectively enhances noisy 3D DMO data and provides comparable results to more computationally expensive prestack time migration. Amplitude anomalies identified in the original 3D data, which were not predicted by our modeling, could represent potential exploration targets in an undeveloped part of the camp, assuming that our a priori earth model is sufficiently accurate.

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