• Bulletin of the Korean Chemical Society
• /
• v.18 no.12
• /
• pp.1281-1285
• /
• 1997

The time-dependent tracking inversion method is developed to extract the potential of the excited state from frequency-domain measurements, such as the absorption profile. Based on the relay of the regularized inversion procedure and time-dependent wave-packet propagation, the algorithm extract the underlying potential piece by piece by tracking the time-dependent data which can be synthesized from frequency-domain measurements. We have demonstrated the algorithm to extract the potential of excited state for a model diatomic molecule. Finally, we describe the merits of the time-dependent tracking inversion method compared to the time-dependent inversion and discuss several extensions of the algorithm.

• The Journal of the Acoustical Society of Korea
• /
• v.24 no.6
• /
• pp.334-342
• /
• 2005

In this Paper. a time-domain geoacoustic inversion was performed using the bulb signals measured during MがU. 04 experiment conducted in the East Sea of Korea in 2004. An obiective function was defined as a direct cross-correlation between the measured and the simulated signals in time domain. The ray theory was used to model the wave propagation in time domain and optimizations were Performed using VFSA (very fast simulated annealing) algorithm. Comparison of inversion results with those from transmission loss matching (an accompanying paper in this issue of the Journal of the Acoustical Society of Korea) shows that Parameters are consistently inverted. Direct time series comparisons between the measured signals and the simulated signals are Presented based on inversion results.

• Geophysics and Geophysical Exploration
• /
• v.15 no.3
• /
• pp.129-135
• /
• 2012

The simultaneous-source full waveform inversion improves the applicability of full waveform inversion by reducing the computational cost. Since this technique adopts simultaneous multi-source for forward modeling, unwanted events remain in the residual seismograms when the receiver geometry of field acquisition is different from that of numerical modeling. As a result, these events impede the convergence of the full waveform inversion. In particular, the streamer-type data with limited offsets is the most difficult data to apply the simultaneous-source technique. To overcome this problem, the global-correlation-based objective function was suggested and it was successfully applied to the simultaneous-source full waveform inversion in time domain. However, this method distorts residual wavefields due to the modified objective function and has a negative influence on the inversion result. In addition, this method has not been applied to the frequency-domain simultaneous-source full waveform inversion. In this paper, we apply a timedamping function to the observed and modeled data, which are used to compute global correlation, to minimize the distortion of residual wavefields. Since the damped wavefields optimize the performance of the global correlation, it mitigates the distortion of the residual wavefields and improves the inversion result. Our algorithm incorporates the globalcorrelation-based full waveform inversion into the frequency domain by back-propagating the time-domain residual wavefields in the frequency domain. Through the numerical examples using the streamer-type data, we show that our inversion algorithm better describes the velocity structure than the conventional global correlation approach does.

• Korean Journal of Optics and Photonics
• /
• v.17 no.3
• /
• pp.262-267
• /
• 2006

We proposed a PPLN fabrication setup that measures the voltage and current applied to $LiNbO_3$ in real time during application of a DC electric field. Because the duration for transferring a sufficient electron charge to $LiNbO_3$ increases, we are able to control the electron charge flow transferred to $LiNbO_3$ efficiently. We divided the domain inversion process of PPLN into 5 states: Nucleation (state 1), Spread of the domain inversion region under the electrode(state 2), Accumulation of the electron charge at the insulator/$LiNbO_3$ interface(state 3), Domain inversion under the insulator layer after breakdown(state 4), and Lowering the electric field applied to $LiNbO_3$ (state 5). We have found that the Threshold Point is essential for the domain inversion and that the domain inversion process must be stopped within state 3 for the optimum PPLN. Using these results, we could fabricate a stable and reproducible PPLN efficiently.

• Geophysics and Geophysical Exploration
• /
• v.24 no.4
• /
• pp.164-170
• /
• 2021

Frequency-domain and time-domain induced polarization methods can provide spectral information about subsurface media. Analysis of spectral characteristics has been studied mainly in the frequency-domain, however, time-domain induced polarization research has recently become popular. In this study, assuming a homogeneous half-space model, an inversion method was developed to extract Cole-Cole parameters from the measured secondary potential or electrical resistivity. Since the Cole-Cole parameters of chargeability, time constant, and frequency index are not independent of each other, various problems, such as slow convergence rate, initial model problem, local minimum problem, and divergence, frequently occur when conventional nonlinear inversion is applied. In this study, we developed an effective inversion method using the initial model close to the true model by introducing a grid search method. Finally, the validity of the developed inversion method was verified using inversion experiments.

• Geophysics and Geophysical Exploration
• /
• v.14 no.3
• /
• pp.214-219
• /
• 2011

We perform the frequency-domain waveform inversion based on the residual-selection strategy. In the residual-selection strategy, we classify time-domain residual wavefields into several groups according to the order of absolute amplitudes. Because the residual wavefields are normalized after regularization of the gradient directions within each group, the residual-selection strategy plays a role in enhancing the small-amplitude wavefields, which contributes to improving the deep parts of inverted subsurface images. After classifying residuals in the time domain, they are transformed to the frequency domain. Waveform inversion is performed in the frequency domain using the back-propagation technique which has been popularly used in reverse-time migration. The residual-selection strategy is applied to the SEG/EAGE salt and IFP Marmousi models. Numerical results show that the residual-selection strategy yields better results than the conventional frequency-domain waveform inversion.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.44 no.3 s.357
• /
• pp.20-25
• /
• 2007

The periodic domain-inversion in the selective areas of $Ti:LiNbO_3$ Mach-Zender waveguides was performed and band-pass modulators and single sideband (SSB) modulators were fabricated by using domain-reversal. The domain wall velocity was precisely controlled by real-time analysis of a poling-induced response current under an applied voltage. The domain wall velocity was significantly affected by the crystal orientation of the domain wall propagation which influenced the final domain geometry. In a certain case, the decomposition of $LiNbO_3$ crystal was observed, for example, under the condition of too fast domain wall propagation. The fabricated band-pass modulator with a periodic domain-inversion structure showed the maximum modulation efficiency at 30.3 GHz with 5.1 GHz 3dB-bandwidth, and SSB modulator was measured to show 33 dB USB suppression over LSB at 5.8 GHz RF.

• Geophysics and Geophysical Exploration
• /
• v.24 no.4
• /
• pp.149-157
• /
• 2021

Given that induced polarization (IP) and direct current (DC) resistivity surveys are similar in terms of data acquisition, most DC resistivity systems are equipped with a time-domain IP data acquisition function. In addition, the time-domain IP data include the DC resistivity values. As such, IP and DC resistivity data are intimately linked, and the inversion of IP data is a two-step process based on DC resistivity inversions. Nevertheless, IP surveys are rarely applied, in contrast to DC resistivity surveys, as proper inversion software is unavailable. In this study, through numerical modeling and inversion experiments, we analyze the problems with the conventional inverse mapping technique used to invert time-domain IP data. Furthermore, we propose a modified inverse mapping technique that can effectively suppress inversion artifacts. The performance of the technique is confirmed through inversions applied to synthetic IP data.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2007.06a
• /
• pp.118-123
• /
• 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
• /
• v.26 no.2
• /
• pp.84-93
• /
• 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.