• Geophysics and Geophysical Exploration
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• v.23 no.1
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• pp.38-49
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• 2020

Full-waveform inversion (FWI) is an optimization process of fitting observed and modeled data to reconstruct high-resolution subsurface physical models. In acoustic FWI (AFWI), pressure data acquired using a marine streamer has mainly been used to reconstruct the subsurface P-wave velocity models. With recent advances in marine seismic-acquisition techniques, acquiring multi-component data in marine environments have become increasingly common. Thus, AFWI strategies must be developed to effectively use marine multi-component data. Herein, we proposed an AFWI strategy using horizontal and vertical particle-acceleration data. By analyzing the modeled acoustic data and conducting sensitivity kernel analysis, we first investigated the characteristics of each data component using AFWI. Common-shot gathers show that direct, diving, and reflection waves appearing in the pressure data are separated in each component of the particle-acceleration data. Sensitivity kernel analyses show that the horizontal particle-acceleration wavefields typically contribute to the recovery of the long-wavelength structures in the shallow part of the model, and the vertical particle-acceleration wavefields are generally required to reconstruct long- and short-wavelength structures in the deep parts and over the whole area of a given model. Finally, we present a sequential-inversion strategy for using the particle-acceleration wavefields. We believe that this approach can be used to reconstruct a reasonable P-wave velocity model, even when the pressure data is not available.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.214-216
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• 2022

Distributed acoustic sensing (DAS), an increasingly growing acquisition technique in the oil and gas exploration and seismology fields, has been used to record seismic signals using optical cables as receivers. With the development of imaging methods for DAS data, full waveform inversion (FWI) is been applied to DAS data to obtain high-resolution property models such as P- and S-velocity. However, because the DAS systems measure strain from the phase distortion between two points along optical cables, DAS data must be transformed from strain to particle velocity for FWI algorithms. In this study, a plane-wave FWI algorithm based on the relationship between strain and horizontal particle velocity in the plane-wave assumption is proposed to apply FWI to DAS data. Under the plane-wave assumption, strain equals the horizontal particle velocity, which is scaled by the velocity at the receiver position. This relationship was confirmed using a numerical experiment. Furthermore, 4-layer and modified Marmousi-2 velocity models were used to verify the applicability of the proposed FWI algorithm in various survey environments. The proposed FWI was implemented in land and marine survey environments and provided high-resolution P- and S-velocity models.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.227-241
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• 2022

Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.432-435
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• 1997

This Paper proposes a novel sinusoidal converter which improves input power factor and input current waveform without any complicated switching modulation such as a pulse width modulation or a complicated feed-back control. It is composed of a full bridge diode, a pair of capacitors, a pair of inductors and a pair of switching devices. The configuration and control strategy are both simple however, the sinusoidal converter effectively reduces reactive power and hamonics included in a input line current. Excellent behavior of the proposed converter is verified by theoretical analysis and experimental results.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.951-954
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• 1999

A direct digital frequency synthesizer is designed in full custom method using 0.65${\mu}{\textrm}{m}$ CMOS n-well technology The chip provides the capability of the parallel operation using up to 4 chips with an operation frequency of 440MHz. The generated waveform can be modulated by various modulation techniques such as QPSK, 256 . 64. 32 . 16 QAM and FM.

• 한국지구물리탐사학회:학술대회논문집
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• 2011.10a
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• pp.41-44
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• 2011

• 한국지구물리탐사학회:학술대회논문집
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• 2010.10a
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• pp.185-188
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• 2010

• Geophysics and Geophysical Exploration
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• v.24 no.1
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• pp.6-19
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• 2021

Subsurface physical properties can be obtained and imaged by seismic exploration, and various algorithms have been developed for this purpose. In this regard, root mean square error (RMSE) has been widely used to quantitatively evaluate the accuracy of the developed algorithms. Although RMSE has the advantage of being numerically simple, it has limitations in assessing structural similarity. To supplement this, full-reference image quality assessment (FR-IQA) techniques, which reflect the human visual system, are being investigated. Therefore, we selected six FR-IQA techniques that could evaluate the obtained physical properties. In this paper, we used the full-waveform inversion, because the algorithm can provide the physical properties. The inversion results were applied to the six selected FR-IQA techniques using three benchmark models. Using salt models, it was confirmed that the inversion results were not satisfactory in some aspects, but the value of RMSE decreased. On the other hand, some FR-IQA techniques could definitely improve the evaluation.

• Journal of IKEEE
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• v.12 no.4
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• pp.239-245
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• 2008

In this paper, a dc-dc power converter scheme with the FPGA based technology is proposed to apply for solar power system which has many features such as the good waveform, high efficiency, low switching losses, and low acoustic noises. The circuit configuration is designed by the conventional control type converter circuit using the isolated dc power supply. This new scheme can be more widely used for industrial power conversion system and many other purposes. Also, I proposed an efficient photovoltaic power interface circuit incorporated with a FPGA based DC-DC converter and a sine-pwm control method full-bridge inverter. The FPGA based DC-DC converter operates at high switching frequency to make the output current a sine wave, whereas the full-bridge inverter operates at low switching frequency which is determined by the ac frequency. As a result, we can get a 1.72% low THD in present state using linear control method. Moreover, we can use stepping control method, we can obtain the switching losses by Sp measured as 0.53W. This paper presents the design of a single-phase photovoltaic inverter model and the simulation of its performance.

• Proceedings of the KIPE Conference
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• 2003.07a
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• pp.23-26
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• 2003

This paper presents a novel hybrid type multilevel inverter in order to improve the waveshape of output voltage. The proposed multilevel inverter is consist of two full-bridge modules for level creation and one full-bridge module for PWM operation. The generated levels are total 11-level: 9-level by the level inverter and 2-level by the PWM inverter. The operational principles and analysis are explained and validity of the proposed system is verified through the experimental results using a prototype.