Results 51 to 60 of about 4,173 (187)
Applied SciencesSeismic signal denoising stands as a vital process that enables precise seismic data analysis because noise interference blocks the detection of weak but valuable seismic signals.
Qinghua Zhang +4 more
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Dictionary Learning with Convolutional Structure for Seismic Data Denoising and Interpolation
Geophysics, 2021 Seismic data inevitably suffers from random noise and missing traces in field acquisition. This limits the utilization of seismic data for subsequent imaging or inversion applications. Recently, dictionary learning has gained remarkable success in seismic data denoising and interpolation.
Murad Almadani +3 more
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GeoFWI: A Large Velocity Model Data Set for Benchmarking Full Waveform Inversion Using Deep Learning
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.Abstract Full waveform inversion (FWI) plays an increasingly important role in the field of seismic imaging due to its strong ability to estimate subsurface properties. Specifically, data‐driven FWI (DDFWI) establishes a straightforward mapping relationship between seismic data and the corresponding velocity model, yielding promising results.
Chao Li +5 more
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Journal of Petroleum Exploration and Production TechnologyDenoising micro-seismic signals is paramount for ensuring reliable data for localizing mining-related seismic events and analyzing the state of rock masses during mining operations.
Jianxian Cai +4 more
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Three-dimensional seismic denoising based on deep convolutional dictionary learning
Results in Applied MathematicsDictionary learning (DL) has been widely used for seismic data denoising. However, it is associated with the following challenges. First, learning a dictionary from one dataset cannot be applied to another dataset and requires setting learning and ...
Yuntong Li, Lina Liu
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Research on Precise Identification of Rock Strength Based on Bolt Drilling Parameters
Energy Science &Engineering, Volume 14, Issue 3, Page 1353-1371, March 2026.Drilling detection test platform. ABSTRACT During roadway excavation, the presence of weak interlayers and fractured rock masses significantly affects roof stability. To achieve timely and effective roadway support, it is crucial to identify and predict different rock types based on drilling signals from roof bolters.
Qiang Zhu +4 more
wiley +1 more source
Celebrating the Physics in Geophysics
, 2005 As 2005, the International Year of Physics, comes to an end, two physicists working primarily in geophysical research reflect on how geophysics is not an applied physics.
Anderson +4 more
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Deglitching Martian Seismic Data: Application to Marsquake Detection
Earth and Space Science, Volume 13, Issue 3, March 2026.Abstract NASA's InSight mission investigates the interior structure of Mars. The data is characterized by multiple non‐seismic signals with varying attributes, including high‐energy instrumental noise, known as glitches, which frequently exhibit large linear polarization.
Jair Zampieri +2 more
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Efficient Seismic Denoising Transformer with Gradient Prediction and Parameter-Free Attention [PDF]
Jisuanji kexue yu tansuoSuppression of random noise can effectively improve the signal-to-noise ratio (SNR) of seismic data. In recent years, convolutional neural network (CNN)-based deep learning methods have shown significant performance in seismic data denoising.
GAO Lei, QIAO Haowei, LIANG Dongsheng, MIN Fan, YANG Mei
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An Attention-Based Residual Neural Network for Efficient Noise Suppression in Signal Processing
Applied Sciences, 2023 The incorporation of effective denoising techniques is a crucial requirement for seismic data processing during the acquisition phase due to the inherent susceptibility of the seismic data acquisition process to various forms of interference, such as ...
Tianwei Lan +3 more
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