A new approach for high fidelity seismic data recovery by fractal interpolation

Autor:	Tongjiang He, Hongyan Liu, Yukun Chen, Xinfu Li
Rok vydání:	2012
Předmět:	Synthetic seismogram Computer science business.industry Geology Geotechnical Engineering and Engineering Geology Missing data Field (computer science) Physics::Geophysics Data recovery Geophysics Fractal Seismic tomography business Algorithm Seismic to simulation Remote sensing Interpolation
Zdroj:	Earthquake Science. 25:339-346
ISSN:	1867-8777 1674-4519
Popis:	Recovering accurate data is important for both earthquake and exploration seismology studies, when data are sparsely sampled or partially missing. We present a method that allows for precise and accurate recovery of seismic data using a localized fractal recovery method. This method requires that the data are self-similar on local and global spatial scales. We present examples that show that the intrinsic structure associated with seismic data can be easily and accurately recovered by using this approach. This result, in turn, indicates that seismic data are indeed self-similar on local and global scales. This method is applicable not only for seismic studies, but also for any field studies that require accurate recovery of data from sparsely sampled datasets with partially missing data. Our ability to recover the missing data with high fidelity and accuracy will qualitatively improve the images of seismic tomography.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::01f833b55c56cf1313cc104e000ea168 https://doi.org/10.1007/s11589-012-0859-x Zobrazit plný text záznamu Full text from SpringerLink