• Journal of the Korean earth science society
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• v.23 no.1
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• pp.15-29
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• 2002

Bayesian inversion for gravity and resistivity data was performed to investigate the cavity structure appearing as a lava tunnel in Cheju Island, Korea. Dipole-dipole DC resistivity data were proposed for a prior information of gravity data and we applied the geostatistical techniques such as kriging and simulation algorithms to provide a prior model information and covariance matrix in data domain. The inverted resistivity section gave the indicator variogram modeling for each threshold and it provided spatial uncertainty to give a prior PDF by sequential indicator simulations. We also presented a more objective way to make data covariance matrix that reflects the state of the achieved field data by geostatistical technique, cross-validation. Then Gaussian approximation was adopted for the inference of characteristics of the marginal distributions of model parameters and Broyden update for simple calculation of sensitivity matrix and SVD was applied. Generally cavity investigation by geophysical exploration is difficult and success is hard to be achieved. However, this exotic multiple interpretations showed remarkable improvement and stability for interpretation when compared to data-fit alone results, and suggested the possibility of diverse application for Bayesian inversion in geophysical inverse problem.

• Transactions of the Society of Information Storage Systems
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• v.3 no.1
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• pp.5-12
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• 2007

This paper investigates the design of disturbance observer for rotational vibration suppression in disk drive systems. The design aims to provide an optimal controller which satisfies both vibration performance and robust stability. It consists of an inversion method, a special filter, and optimization scheme. Firstly a new inversion method is introduced, which provides more accurate inversion compared to conventional zero phase error method. The inversion is to deal with unstable zeros in the plant model. Secondly a special filter for disturbance selection is given, which features adjustable gain and band pass characteristics so that it enables flexible shaping of the loop considering the trade-off between performance and stability margins. And finally the parameters of disturbance observer are optimized in conjunction with external disturbance model. Simulation and experiment on commercial hard disk drives confirm that the design is very effective to such disturbance which is hard to be handled by conventional approach.

• New Physics: Sae Mulli
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• v.68 no.12
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• pp.1331-1337
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• 2018

We present a three-parameter phase shift model whose form is the same as that of Coulombmodified Glauber model obtained from Gaussian nuclear densities. This model is applied to the $^6Li+^{12}C$ and the $^6Li+^{28}Si$ elastic scatterings at $E_{lab}=318MeV$. The calculated differential cross sections provide quite a satisfactory account of the experimental data. The diffractive oscillatory structures observed at forward angles can be explained as being due to the strong interference between the near-side and the far-side scattering amplitudes. The optical potentials for two systems are predicted by using the method of inversion. The calculated inversion potentials are found to be in fairly good agreements with the results determined from the optical model analysis in the surface regions around the strong absorption radius. We also investigate the effects of parameters in the three-parameter phase shift model on the elastic scattering cross sections.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.207-213
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• 2005

This paper deals with an autonomous flight guidance and control algorithm design for TR301 tilt-rotor airplane under development by Korea Aerospace Research Institute for simulation purpose. The objective of this study is to design autonomous flight algorithm in which the tilt-rotor airplane should follow the given waypoints precisely. The approach to this objective in this study is that, first of all, model-based inversion is applied to the highly nonlinear tilt-rotor dynamics, where the tilt-rotor airplane is assumed to fly at helicopter flight mode(nacelle angle=0 deg), and then the control algorithm, based on classical control, is designed to satisfy overall system stabilization and precise waypoint following performance. Especially, model uncertainties due to the tiltrotor model itself and inversion process are adaptively compensated in a simple neural network(Sigma-Phi NN) for performance robustness. The designed algorithm is evaluated in the tilt-rotor nonlinear airplane in helicopter flight mode to analyze the following performance for given waypoints. The simulation results show that the waypoint following responses for this algorithm are satisfactory, and control input responses are within control limits without saturation.

• Economic and Environmental Geology
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• v.27 no.5
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• pp.479-489
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• 1994

In this paper, the iterative least-squares inversion method is used to determine shapes and density contrasts of 2-D structures from the gravity data. The 2-D structures are represented by their cross-sections of N-sided polygons with density contrasts which are constant or varying with depth. Gravity data are calculated by theoretical formulas for the above structure models. The data are considered as observed ones and used for inversions. The inversions are performed by the following processes: I) polygon's vertices and density contrast are initially assumed, 2) gravity are calculated for the assumed model and error between the true (observed) and calculated gravity are determined, 3) new vertices and density contrast are determined from the error by using the damped least-squares inversion method, and 4) final model is determined when the error is very small. Results of this study show that the shape and density contrast of each model are accurately determined when the density contrast is constant or vertical density gradient is known. In case where the density gradient is unknown, the inversion gives incorrect results. But the shape and density gradient of the model are determined when the surface density contrast is known.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.118-123
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• 2007

A robust objective function in the frequency domain is applied to the acoustic full waveform inversion. The proposed objective function is defined as $l_1$-norm of residual wavefields in the frequency domain. Generally, the full waveform inversion is extremely sensitive to a number of factors such as parameterization, initial model, noise and so on. The numerical tests were performed for checking the sensitivity to attenuation and several noises. For the comparison with other objective functions, the conventional least-squares method and the logarithmic method were tested under the same condition. The synthetic data examples show that the proposed algorithm is more robust than the well-known methods.

• Geophysics and Geophysical Exploration
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• v.11 no.3
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• pp.177-183
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• 2008

The sub-salt imaging technique becomes more crucial to detect the hydro-carbonates in petroleum exploration as the target reservoirs get deeper. However, the weak reflections from the sub-salt structures prevent us from obtaining high fidelity sub-salt image. As an effort to overcome this difficulty, we applied the waveform inversion by implementing multi-grid technique to the sub-salt imaging. Through the comparison between the conventional waveform inversion using fixed grid and the multi-grid technique, we confirmed that the waveform inversion using multi-grid technique has advantages over the conventional fixed grid waveform inversion. We showed that the multi-grid technique can complement he velocity estimation result of the waveform inversion for imaging the sub-salt structures, of which velocity model cannot be obtained correctly by the conventional fixed grid waveform inversion.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.51-56
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• 2008

The waveform inversion for isotropic media has ever been studied since the 1980s, but there has been few studies for anisotropic media. We present a seismic waveform inversion algorithm for 2-D heterogeneous transversely isotropic structures. A cell-based finite difference algorithm for anisotropic media in time domain is adopted. The steepest descent during the non-linear iterative inversion approach is obtained by backpropagating residual errors using a reverse time migration technique. For scaling the gradient of a misfit function, we use the pseudo Hessian matrix which is assumed to neglect the zero-lag auto-correlation terms of impulse responses in the approximate Hessian matrix of the Gauss-Newton method. We demonstrate the use of these waveform inversion algorithm by applying them to a two layer model and the anisotropic Marmousi model data. With numerical examples, we show that it's difficult to converge to the true model when we assumed that anisotropic media are isotropic. Therefore, it is expected that our waveform inversion algorithm for anisotropic media is adequate to interpret real seismic exploration data.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.562-572
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• 2003

A matched-target model inversion method was developed for a passive sonar to estimate the position of moving targets. Based on the well known matched-field processing in underwater acoustics, the method finds target position by matching the measured target directions and frequencies with the corresponding values of the proposed target model. For the efficient and accurate estimations, the parameter searching was accomplished using a hybrid optimizing method, which first starts with a global optimization such as generic algorithm or simulated annealing then applies a local optimization of a simple down hill algorithm. The suggested method was testified using simulations for three different moving scenarios. The simulation results showed that the method is robust in convergence, even under the situation of over 5 times standard deviation of Gaussian distribution of measured error, and is practical in calculation time as well.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.84-93
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• 2023

The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.