2022
DOI: 10.32604/csse.2022.017733
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Applying Non-Local Means Filter on Seismic Exploration

Abstract: The seismic reflection method is one of the most important methods in geophysical exploration. There are three stages in a seismic exploration survey: acquisition, processing, and interpretation. This paper focuses on a pre-processing tool, the Non-Local Means (NLM) filter algorithm, which is a powerful technique that can significantly suppress noise in seismic data. However, the domain of the NLM algorithm is the whole dataset and 3D seismic data being very large, often exceeding one terabyte (TB), it is impo… Show more

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Cited by 3 publications
(2 citation statements)
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“…The reflection wave method is the primary technique used to detect a goaf. It involves analysing the amplitude and phase characteristics of seismic waves artificially generated and reflected back to the surface upon encountering interfaces with different impedances underground, which can be used to infer information about subsurface geological structures [24,25]. Reflected seismic waves are commonly employed to detect large-scale anomalies, but diffraction or Rayleigh waves can be employed if the target is smaller than the lateral resolution of the reflected wave [26].…”
Section: Seismic Explorationmentioning
confidence: 99%
“…The reflection wave method is the primary technique used to detect a goaf. It involves analysing the amplitude and phase characteristics of seismic waves artificially generated and reflected back to the surface upon encountering interfaces with different impedances underground, which can be used to infer information about subsurface geological structures [24,25]. Reflected seismic waves are commonly employed to detect large-scale anomalies, but diffraction or Rayleigh waves can be employed if the target is smaller than the lateral resolution of the reflected wave [26].…”
Section: Seismic Explorationmentioning
confidence: 99%
“…In the realm of machine learning and particularly in classification tasks, gauging the efficacy and accuracy of a model goes beyond the rudimentary evaluation of its accuracy rate. A more nuanced approach encompasses metrics like precision, recall, the F-score, and the Receiver Operating Characteristic (ROC) curve [41][42][43]. Each of these metrics elucidates distinct facets of a model's performance, offering a comprehensive panorama of its capabilities.…”
Section: B Evaluation Metricsmentioning
confidence: 99%