• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.157-170
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• 2023

In South Korea, carbon capture and storage (CCS) techniques have attracted considerable attention as part of efforts to achieve the 2030 Korean Nationally Determined Contribution. However, owing to delays in large-scale CCS projects in South Korea, interest in cross-border CCS projects, wherein CO₂ captured in South Korea is stored in overseas CCS facilities, has increased. In this study, we investigated the development status of the CarbonNet project in the Gippsland Basin, Australia. First, we provide a brief overview of sedimentary basins and CCS projects in Australia. Subsequently, we review the geological history of the Gippsland Basin, the site of the large-scale CCS project. Finally, we summarize the site selection process for the CarbonNet project and discuss the suitability of the Pelican site for large-scale CCS projects.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.199-210
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• 2023

The physical properties of rocks in reservoirs change after CO₂ injection, we modeled a reservoir with a transition zone within which the physical properties change linearly. The function of the Wolf reflection coefficient consists of the velocity ratio of the upper and lower layers, the frequency, and the thickness of the transition zone. This function can be used to estimate the thickness of a reservoir or seafloor transition zone. In this study, we propose a method for predicting the thickness of the transition zone using deep learning. To apply deep learning, we modeled the thickness-dependent Wolf reflection coefficient on an artificial transition zone formation model consisting of sandstone reservoir and shale cap rock and generated time-frequency spectral images using the continuous wavelet transform. Although thickness estimation performed by comparing spectral images according to different thicknesses and a spectral image from a trace of the seismic stack did not always provide accurate thicknesses, it can be applied to field data by obtaining training data in various environments and thus improving its accuracy.

• Geophysics and Geophysical Exploration
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• v.27 no.1
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• pp.51-56
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• 2024

In this paper, the vector gravity and gravity gradient tensor of an elliptical disk are derived. The vector gravity of an elliptical disk is defined by differentiating the gravitational potential due to the elliptical disk expressed by a double integral with respect to each axial direction. The vector gravity defined by the double integral is then transformed into a line integral of a closed curve along the elliptical disk boundary using the complex Green's theorem. Finally, vector gravity due to the elliptical disk is derived by 1D parametric numerical integration along the elliptical disk boundary. The xz, yz, zz components of the gravity gradient tensor due to the elliptical disk are obtained by differentiating the vector gravity with respect to vertical direction. The xx, yy, xy components are derived by differentiating the horizontal components of the vector gravity in the form of a double integral with respect to horizontal directions and then using the complex Green's theorem.

• Geophysics and Geophysical Exploration
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• v.27 no.1
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• pp.57-68
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• 2024

Offshore wind power is increasingly regarded as a viable solution for reducing greenhous emissions due to the construction of wind farms and their superior power generation efficiency. Submarine power cables play a crucial role in transmitting the electricity generated offshore to land. To monitor cables and identify points of failure, analyzing the location or depth of burial of submarine cables is necessary. This study reviewed the technology and research for detecting submarine power cables, which were categorized into seismic/acoustic, electromagnetic, and magnetic exploration. Seismic/acoustic waves are primarily used for detecting submarine power cables by installing equipment on ships. Electromagnetic and magnetic exploration detects cables by installing equipment on unmanned underwater vehicles, including autonomous underwater vehicles (AUV) and remotely operated vihicles (ROV). This study serves as a foundational resource in the field of submarine power cable detection.

• Ocean Systems Engineering
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• v.14 no.1
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• pp.85-99
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• 2024

Ocean surface currents have an essential role in the Earth's climate system and significantly impact the marine ecosystem, weather patterns, and human activities. However, predicting ocean surface currents remains challenging due to the complexity and variability of the oceanic processes involved. This review article provides an overview of the current research status, challenges, and opportunities in the prediction of ocean surface currents. We discuss the various observational and modelling approaches used to study ocean surface currents, including satellite remote sensing, in situ measurements, and numerical models. We also highlight the major challenges facing the prediction of ocean surface currents, such as data assimilation, model-observation integration, and the representation of sub-grid scale processes. In this article, we suggest that future research should focus on developing advanced modeling techniques, such as machine learning, and the integration of multiple observational platforms to improve the accuracy and skill of ocean surface current predictions. We also emphasize the need to address the limitations of observing instruments, such as delays in receiving data, versioning errors, missing data, and undocumented data processing techniques. Improving data availability and quality will be essential for enhancing the accuracy of predictions. The future research should focus on developing methods for effective bias correction, a series of data preprocessing procedures, and utilizing combined models and xAI models to incorporate data from various sources. Advancements in predicting ocean surface currents will benefit various applications such as maritime operations, climate studies, and ecosystem management.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.129-143
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• 2024

In magnetotelluric (MT) surveys, small inhomogeneities near the surface cause a static shift in which apparent resistivities shift regardless of frequency. As the static shift in MT data leads to errors in subsurface structure interpretation, many studies have been conducted over the past few decades to mitigate or remove the distortions it caused. The most representative method involves removing static shifts from the data before inversion. Conversely, static shifts can be corrected during inversion or included in the inversion process. In addition, other geophysical data can be used to remove static shifts. However, the correction methods are limited to one-dimensional (1D) static responses, and limitations remain in two- or three-dimensional (2D or 3D) interpretation of distorted MT data owing to static shifts. This study provides a foundation for future studies on static shift by analyzing several previously published methods.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.144-153
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• 2024

Recent research is increasingly focused on utilizing seismic waves for structure health monitoring (SHM). Specifically, seismic interferometry, a technique applied in geophysical surveys using ambient noise, is widely applied in SHM. This method involves analyzing the response of buildings to propagating seismic waves. This enables the estimation of changes in structural stiffness and the evaluation of the location and presence of damage. Analysis of seismic interferometry applied to SHM, along with case studies, indicates its highly effective application for assessing structural stability and monitoring building conditions. Seismic interferometry is thus recognized as an efficient approach for evaluating building integrity and damage detection in SHM and monitoring applications.

• Geophysics and Geophysical Exploration
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• v.27 no.3
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• pp.171-180
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• 2024

The processing of seismic data involves analyzing earthquake wave data to understand the internal structure and characteristics of the Earth, which requires high computational power. Recently, machine learning (ML) techniques have been introduced to address these challenges and have been utilized in various tasks such as noise reduction and velocity model construction. However, most studies have focused on specific seismic data processing tasks, limiting the full utilization of similar features and structures inherent in the datasets. In this study, we compared the efficacy of using receiver-wise time-series data ("receiver array") and synchronized receiver signals ("time array") from shotgathers for pretraining a Bidirectional Encoder Representations from Transformers (BERT) model. To this end, shotgather data generated from a synthetic model containing faults was used to perform noise reduction, velocity prediction, and fault detection tasks. In the task of random noise reduction, both the receiver and time arrays showed good performance. However, for tasks requiring the identification of spatial distributions, such as velocity estimation and fault detection, the results from the time array were superior.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.1-8
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• 2010

Seismic reflection surveying is one of the most widely used and effective techniques for coal seam structure delineation and risk mitigation for underground longwall mining. However, the ability of the method can be compromised by the presence of volcanic cover. This problem arises within parts of the Bowen and Sydney Basins of Australia and seismic surveying can be unsuccessful. As a consequence, such areas are less attractive for coal mining. Techniques to improve the success of seismic surveying over basalt flows are needed. In this paper, we use elastic wave-equation-based forward modelling techniques to investigate the effects and characteristics of seismic wave propagation under different settings involving changes in basalt properties, its thickness, lateral extent, relative position to the shot position and various forms of inhomogeneity. The modelling results suggests that: 1) basalts with high impedance contrasts and multiple flows generate strong multiples and weak reflectors; 2) thin basalts have less effect than thick basalts; 3) partial basalt cover has less effect than full basalt cover; 4) low frequency seismic waves (especially at large offsets) have better penetration through the basalt than high frequency waves; and 5) the deeper the coal seams are below basalts of limited extent, the less influence the basalts will have on the wave propagation. In addition to providing insights into the issues that arise when seismic surveying under basalts, these observations suggest that careful management of seismic noise and the acquisition of long-offset seismic data with low-frequency geophones have the potential to improve the seismic results.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.375-387
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• 2013

Accuracy assessment of tide models in polar ocean has to be performed to accurately analyze tidal response of glaciers by using Double-Differential Interferometric SAR (DDInSAR) technique. In this study, we used 120 DDInSAR images generated from 16 one-day tandem COSMO-SkyMed DInSAR pairs obtained for 2 years and in situ tide height for 11 days measured by a pressure type wave recorder to assess the accuracy of tide models such as TPXO7.1, FES2004, CATS2008a and Ross_Inv in Terra Nova Bay, East Antarctica. Firstly, we compared the double-differential tide height (${\Delta}\dot{T}$) for Campbell Glacier Tongue extracted from the DDInSAR images with that predicted by the tide models. Tide height (T) from in situ measurement was compared to that of the tide models. We also compared 24-hours difference of tide height ($\dot{T}$) from in situ tide height with that from the tide models. The root mean square error (RMSE) of ${\Delta}\dot{T}$, T and $\dot{T}$ decreased after the inverse barometer effect (IBE)-correction of the tide models, from which we confirmed that the IBE of tide models should be corrected requisitely. The RMSE of $\dot{T}$ and ${\Delta}\dot{T}$ were smaller than that of T. This was because $\dot{T}$ is the difference of tide height during temporal baseline of the DInSAR pairs (24 hours), in which the errors from mean sea level of the tide models and in situ tide, and the tide constituents of $S_2$, $K_2$, $K_1$ and $P_1$ used in the tide models were canceled. This confirmed that $\dot{T}$ and ${\Delta}\dot{T}$ predicted by the IBE-corrected tide models can be used in DDInSAR technique. It was difficult to select an optimum tide model for DDInSAR in Terra Nova Bay by using in situ tide height measured in a short period. However, we could confirm that Ross_Inv is the optimum tide model as it showed the smallest RMSE of 4.1 cm by accuracy assessment using the DDInSAR images.