• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.37-51
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• 2023

The ground roll is the most common coherent noise in land seismic data and has an amplitude much larger than the reflection event we usually want to obtain. Therefore, ground roll suppression is a crucial step in seismic data processing. Several techniques, such as f-k filtering and curvelet transform, have been developed to suppress the ground roll. However, the existing methods still require improvements in suppression performance and efficiency. Various studies on the suppression of ground roll in seismic data have recently been conducted using deep learning methods developed for image processing. In this paper, we introduce three models (DnCNN (De-noiseCNN), pix2pix, and CycleGAN), based on convolutional neural network (CNN) or conditional generative adversarial network (cGAN), for ground roll suppression and explain them in detail through numerical examples. Common shot gathers from the same field were divided into training and test datasets to compare the algorithms. We trained the models using the training data and evaluated their performances using the test data. When training these models with field data, ground roll removed data are required; therefore, the ground roll is suppressed by f-k filtering and used as the ground-truth data. To evaluate the performance of the deep learning models and compare the training results, we utilized quantitative indicators such as the correlation coefficient and structural similarity index measure (SSIM) based on the similarity to the ground-truth data. The DnCNN model exhibited the best performance, and we confirmed that other models could also be applied to suppress the ground roll.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.177-185
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• 2019

Ground roll is a surface wave which is usually observed in the land seismic data. It is one of the typical coherent noise. During the reflection data processing, ground roll is removed because it is considered as noise. This removal process often causes the loss of reflection signals if the ground roll overlaps reflection signals. In this study, we look over Karhunen-Loeve Transform (KLT) and analyze its effects to suppress the ground roll appropriately while reducing the reflection loss. Numerical tests in homogeneous elastic media show that the ground roll has been properly rejected. However, the field data application reveals that there is no significant suppression of ground roll when compared to band-pass filtering. This can be considered that it is hard to calculate horizontally aligned gathers in the field data because the ground roll contains a wide range of frequency bands. On the contrary, the result of singular value decomposition (SVD) filtering shows that the ground roll has been significantly reduced. It is thought that the SVD filtering performs better in the ground roll suppression than KLT because it is easy to calculate the horizontally aligned gathers in the SVD filtering.

• The Journal of Engineering Geology
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• v.28 no.3
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• pp.465-473
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• 2018

The application of singular value decomposition (SVD) filtering is examined for attenuation of the ground-roll in land seismic data. Prior to the SVD computation to seek singular values containing the highly correlatable reflection energy, processing steps such as automatic gain control, elevation and refraction statics, NMO correction, and residual statics are performed to enhance the horizontal correlationships and continuities of reflections. Optimal parameters of SVD filtering are effectively chosen with diagnostic display of inverse NMO (INMO) corrected CSP (common shot point) gather. On the field data with dispersion of ground-roll overwhelmed, continuities of reflection events are much improved by SVD filtering than f-k filtering by eliminating the ground-roll with preserving the low-frequency reflections. This is well explained in the average amplitude spectra of the f-k and SVD filtered data. The reflectors including horizontal layer of the reservoir are much clearer on the stack section, with laminated events by SVD filtering and subsequent processing steps of spiking deconvolution and time-variant spectral whitening.

• Journal of Power System Engineering
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• v.13 no.1
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• pp.26-32
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• 2009

This study is about roll characteristics evaluation to show the advantage of using MR(magneto-rheological) dampers for steering of a SUV(sports utility vehicle). Roll characteristics is very important to observe the roll-propensity of the SUV. ADAMS/Car program was used to simulate the basic steering motion, using 63 D.O.F. vehicle model. Sky-Hook and Ground-Hook control algorithms were used as a semi-active suspension system controller. The roll characteristics from the steering motion were compared between the simulation results from the semi-active suspension system and the passive suspension system.

• Aerospace Engineering and Technology
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• v.2 no.1
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• pp.124-132
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• 2003

The function and performance test of the developed sub-system should be conducted before integrating into the total system. For the successful achievement of the flight test, the integration tests of sub-systems must be performed to eliminate and prevent abnormal conditions, which may happen due to ground problems, Electro-Magnetic Interference noises, and so on. This paper describes the certification test procedure and results for the roll axis attitude control system of Korea Sounding Rocket-III.