First-arrival picking through fuzzy c-means and robust locally weighted regression

Gao, Lei; Liu, Dang; Luo, Guan Feng; Song, Guo Jie; Min, Fan

doi:10.1007/s11600-021-00636-z

Artykuł - szczegóły

Tytuł artykułu

First-arrival picking through fuzzy c-means and robust locally weighted regression

Autorzy

Gao Lei , Liu Dang , Luo Guan Feng , Song Guo Jie , Min Fan

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-021-00636-z

Warianty tytułu

Języki publikacji

Abstrakty

First-arrival picking is a crucial step in seismic data processing. Because of the diverse background noises and irregular near-surface conditions, it is difcult to pick frst arrivals. In addition, existing algorithms are usually sensitive to parameter settings. Therefore, this paper proposes the frst-arrival picking through fuzzy c-means and robust locally weighted regression (FPFR) algorithm consisting of two subroutines. The pre-picking subroutine obtains initial frst arrivals through fuzzy c-means clustering and adaptive cluster-selection techniques. The smoothing subroutine handles background noises and near-ground conditions through adaptive parameter regression technique. The experiment is conducted on six feld seismic datasets and one synthetic dataset. Results show that FPFR is more accurate than three state-of-the-art methods.

Słowa kluczowe

fuzzy c-means optimization model first arrival picking robust locally weighted regression

rozmyta metoda c-średnich model optymalizacji

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2021

Tom

Vol. 69, no. 5

Strony

1623--1636

Opis fizyczny

Bibliogr. 43 poz.

Twórcy

autor

Gao Lei

gaolei@swpu.edu.cn

School of Computer Science, Southwest Petroleum University, Chengdu 610500, China

autor

Liu Dang

201922000382@stu.swpu.edu.cn

School of Computer Science, Southwest Petroleum University, Chengdu 610500, China

autor

Luo Guan Feng

201921000417@stu.swpu.edu.cn

School of Computer Science, Southwest Petroleum University, Chengdu 610500, China

autor

Song Guo Jie

cylsgj@126.com

School of Sciences, Southwest Petroleum University, Chengdu 610500, China

autor

Min Fan

minfan@swpu.edu.cn

School of Computer Science, Southwest Petroleum University, Chengdu 610500, China
Institute for Artifcial Intelligence, Southwest Petroleum University, Chengdu 610500, China

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Bibliografia

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