• Geophysics and Geophysical Exploration
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• v.23 no.2
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• pp.72-88
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• 2020

Recent rapid advances in computer hardware performance have led to relatively low computational costs, increasing the number of applications of machine-learning techniques to geophysical problems. In particular, deep-learning techniques are gaining in popularity as the number of cases successfully solving complex and nonlinear problems has gradually increased. In this paper, applications of seismic data denoising methods using deep-learning techniques are introduced and investigated. Depending on the type of attenuated noise, these studies are grouped into denoising applications of coherent noise, random noise, and the combination of these two types of noise. Then, we investigate the deep-learning techniques used to remove the corresponding noise. Unlike conventional methods used to attenuate seismic noise, deep neural networks, a typical deep-learning technique, learn the characteristics of the noise independently and then automatically optimize the parameters. Therefore, such methods are less sensitive to generalized problems than conventional methods and can reduce labor costs. Several studies have also demonstrated that deep-learning techniques perform well in terms of computational cost and denoising performance. Based on the results of the applications covered in this paper, the pros and cons of the deep-learning techniques used to remove seismic noise are analyzed and discussed.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.153-160
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• 2008

Seismic modeling is used to simulate wave propagation in the earth. Although the earth's subsurface is usually semi-infinite, we cannot handle the semi-infinite model in seismic modeling because of limited computational resources. For this reason, we usually assume a finite-sized model in seismic modeling. In that case, we need to eliminate the edge reflections arising from the artificial boundaries introducing a proper boundary condition. In this study, we changed three kinds of boundary conditions (sponge boundary condition, Clayton and Engquist's absorbing boundary condition, and Higdon's transparent boundary condition) so that they can be applied in elastic wave modeling for anisotropic media. We then apply them to several models whose Poisson's ratios are different. Clayton and Engquist's absorbing boundary condition is unstable in both isotropic and anisotropic media, when Poisson's ratio is large. This indicates that the absorbing boundary condition can be applied in anisotropic media restrictively. Although the sponge boundary condition yields good results for both isotropic and anisotropic media, it requires too much computational memory and time. On the other hand, Higdon's transparent boundary condition is not only inexpensive, but also reduce reflections over a wide range of incident angles. We think that Higdon's transparent boundary condition can be a method of choice for anisotropic media, where Poisson's ratio is large.

• Geophysics and Geophysical Exploration
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• v.18 no.2
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• pp.74-84
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• 2015

To yield physically meaningful images through elastic reverse-time migration, the wavefield separation which extracts P- and S-waves from reconstructed vector wavefields by using elastic wave equation is prerequisite. For expanding the application of the elastic reverse-time migration to anisotropic media, not only the anisotropic modelling algorithm but also the anisotropic wavefield separation is essential. The anisotropic wavefield separation which uses pseudo-derivative filters determined according to vertical velocities and anisotropic parameters of elastic media differs from the Helmholtz decomposition which is conventionally used for the isotropic wavefield separation. Since applying these pseudo-derivative filter consumes high computational costs, we have developed the efficient anisotropic wavefield separation algorithm which has capability of parallel computing by using GPUs (Graphic Processing Units). In addition, the highly efficient anisotropic elastic reverse-time migration algorithm using MPI (Message-Passing Interface) and incorporating the developed anisotropic wavefield separation algorithm with GPUs has been developed. To verify the efficiency and the validity of the developed anisotropic elastic reverse-time migration algorithm, a VTI elastic model based on Marmousi-II was built. A synthetic multicomponent seismic data set was created using this VTI elastic model. The computational speed of migration was dramatically enhanced by using GPUs and MPI and the accuracy of image was also improved because of the adoption of the anisotropic wavefield separation.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.168-177
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• 2020

Seabed multiple reflections (seabed multiples) are the main cause of misinterpretations of primary reflections in both shot gathers and stack sections. Accordingly, seabed multiples need to be suppressed throughout data processing. Conventional model-driven methods, such as prediction-error deconvolution, Radon filtering, and data-driven methods, such as the surface-related multiple elimination technique, have been used to attenuate multiple reflections. However, the vast majority of processing workflows require time-consuming steps when testing and selecting the processing parameters in addition to computational power and skilled data-processing techniques. To attenuate seabed multiples in seismic reflection data, input gathers with seabed multiples and label gathers without seabed multiples were generated via numerical modeling using the Marmousi2 velocity structure. The training data consisted of normal-moveout-corrected common midpoint gathers fed into a U-Net neural network. The well-trained model was found to effectively attenuate the seabed multiples according to the image similarity between the prediction result and the target data, and demonstrated good applicability to field data.

• Geophysics and Geophysical Exploration
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• v.7 no.3
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• pp.207-212
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• 2004

This article reviews recent developments in three-dimensional (3-D) magntotelluric (MT) imaging. The inversion of MT data is fundamentally ill-posed, and therefore the resultant solution is non-unique. A regularizing scheme must be involved to reduce the non-uniqueness while retaining certain a priori information in the solution. The standard approach to nonlinear inversion in geophysis has been the Gauss-Newton method, which solves a sequence of linearized inverse problems. When running to convergence, the algorithm minimizes an objective function over the space of models and in the sense produces an optimal solution of the inverse problem. The general usefulness of iterative, linearized inversion algorithms, however is greatly limited in 3-D MT applications by the requirement of computing the Jacobian(partial derivative, sensitivity) matrix of the forward problem. The difficulty may be relaxed using conjugate gradients(CG) methods. A linear CG technique is used to solve each step of Gauss-Newton iterations incompletely, while the method of nonlinear CG is applied directly to the minimization of the objective function. These CG techniques replace computation of jacobian matrix and solution of a large linear system with computations equivalent to only three forward problems per inversion iteration. Consequently, the algorithms are efficient in computational speed and memory requirement, making 3-D inversion feasible.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.68-77
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• 2008

We have developed an inversion algorithm for loop-loop electromagnetic (EM) data, based on the localised non-linear or extended Born approximation to the solution of the 2.5D integral equation describing an EM scattering problem. Source and receiver configuration may be horizontal co-planar (HCP) or vertical co-planar (VCP). Both multi-frequency and multi-separation data can be incorporated. Our inversion code runs on a PC platform without heavy computational load. For the sake of stable and high-resolution performance of the inversion, we implemented an algorithm determining an optimum spatially varying Lagrangian multiplier as a function of sensitivity distribution, through parameter resolution matrix and Backus-Gilbert spread function analysis. Considering that the different source-receiver orientation characteristics cause inconsistent sensitivities to the resistivity structure in simultaneous inversion of HCP and VCP data, which affects the stability and resolution of the inversion result, we adapted a weighting scheme based on the variances of misfits between the measured and calculated datasets. The accuracy of the modelling code that we have developed has been proven over the frequency, conductivity, and geometric ranges typically used in a loop-loop EM system through comparison with 2.5D finite-element modelling results. We first applied the inversion to synthetic data, from a model with resistive as well as conductive inhomogeneities embedded in a homogeneous half-space, to validate its performance. Applying the inversion to field data and comparing the result with that of dc resistivity data, we conclude that the newly developed algorithm provides a reasonable image of the subsurface.

• Geophysics and Geophysical Exploration
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• v.3 no.2
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• pp.53-60
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• 2000

The server/client systems using the web protocol and distribution computing environment by network was applied to the MT data processing based on the Java technology. Using this network based system, users can get consistent and stable results because the system has standard analysing methods and has been tested from many users through the internet. Users can check the MT data processing at any time and get results during exploration to reduce the exploration time and money. The pure/enterprised Java technology provides facilities to develop the network based MT data processing system. Web based socket communication and RMI technology are tested respectively to produce the effective and practical client application. Intrinsically, the interpretation of MT data performing the inversion and data process requires heavy computational ability. Therefore we adopt the MPI parallel processing technique to fit the desire of in situ users and expect the effectiveness for the control and upgrade of programing codes.

• Geophysics and Geophysical Exploration
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• v.9 no.3
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• pp.241-249
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• 2006

Due to the long tectonic history and the very complex geologic formations in Korea, the anisotropic characteristics of subsurface material may often change very greatly and locally. The algorithms commonly used, however, may not give sufficiently precise computational results of traveltime data particularly for the complex and strong anisotropic model, since they are based on the two-dimensional (2D) earth and/or weak anisotropy assumptions. This study is intended to develope a three-dimensional (3D) modeling algorithm to precisely calculate the first arrival time in the complex anisotropic media. Considering the complex geology of Korea, we assume 3D TTI (tilted transversely isotropy) medium having the arbitrary symmetry axis. The algorithm includes the 2D non-linear interpolation scheme to calculate the traveltimes inside the grid and the 3D traveltime mapping to fill the 3D model with first arrival times. The weak anisotropy assumption, moreover, can be overcome through devising a numerical approach of the steepest descent method in the calculation of minimum traveltime, instead of using approximate solution. The performance of the algorithm developed in this study is demonstrated by the comparison of the analytic and numerical solutions for the homogeneous anisotropic earth as well as through the numerical experiment for the two layer model whose anisotropic properties are greatly different each other. We expect that the developed modeling algorithm can be used in the development of processing and inversion schemes of seismic data acquired in strongly anisotropic environment, such as migration, velocity analysis, cross-well tomography and so on.

• Geophysics and Geophysical Exploration
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• v.19 no.3
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• pp.111-120
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• 2016

In order to enhance the connectivity of fracture network as fluid path in enhanced/engineered geothermal system (EGS), the exact locating of hydraulic fractured zone is very important. Hydraulic fractures can be tracked by locating of microseismic events which are occurred during hydraulic fracture stimulation at each stage. However, since the subsurface velocity is changed due to hydraulic fracturing at each stage, in order to find out the exact location of microseismic events, we have to consider the velocity change due to hydraulic fracturing at previous stage when we perform the mapping of microseimic events at the next stage. In this study, we have modified 3D locating algorithm of microseismic data which was developed by Kim et al. (2015) and have developed 3D velocity update algorithm using occurred microseismic data. Eikonal equation which can efficiently calculate traveltime for complex velocity model at anywhere without shadow zone is used as forward engine in our inversion. Computational cost is dramatically reduced by using Fresnel volume approach to construct Jacobian matrix in velocity inversion. Through the numerical test which simulates the geothermal survey geometry, we demonstrated that the initial velocity model was updated by using microseismic data. In addition, we confirmed that relocation results of microseismic events by using updated velocity model became closer to true locations.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.85-92
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• 2008

Magnetotelluric (MT) methods are widely applied as an effective exploration technique to geothermal surveys. Two-dimensional (2-D) analysis is frequently used to investigate a complicated subsurface structure in a geothermal region. A 2-D finite-element method (FEM) is usually applied to the MT analysis, but we must pay attention to the accuracy of so-called auxiliary fields. Rodi (1976) proposed an algorithm of improving the accuracy of auxiliary fields, and named it as the MOM method. Because it introduces zeros into the diagonal elements of coefficient matrix of the FEM total equation, a pivoting procedure applied to the symmetrical band matrix makes the numerical solution far less efficient. The MOM method was devised mainly for the inversion analysis, in which partial derivatives of both electric and magnetic fields with respect to model parameters are required. In the case of forward modeling, however, we do not have to resort to the MOM method; there is no need of modifying the coefficient matrix, and the auxiliary fields can be elicited from the regular FEM solution. The computational efficiency of the MOM method, however, can be greatly improved through a sophisticated rearrangement of the total equation.