Open AccessImproving magnetotelluric data processing methods
Author(s) -
D. V. Epishkin
Publication year - 2016
Publication title -
vestnik moskovskogo universiteta. seriâ 4, geologiâ
Language(s) - English
Resource type - Journals
ISSN - 0579-9406
DOI - 10.33623/0579-9406-2016-4-40-46
Subject(s) - magnetotellurics , jackknife resampling , computer science , robustness (evolution) , estimator , data processing , code (set theory) , signal processing , noise (video) , algorithm , data mining , database , artificial intelligence , engineering , computer hardware , mathematics , electrical engineering , statistics , digital signal processing , biochemistry , chemistry , set (abstract data type) , image (mathematics) , electrical resistivity and conductivity , gene , programming language
A magnetotelluric data processing code has been developed, which demonstrates high robustness to intense electromagnetic noise occurring in measured MT data. Key features of the code are specific approach for estimating different transfer functions and capability to utilize all four channels acquired at remote reference station. The code utilizes various techniques to reduce estimate errors, including robust Huber estimator, jackknife approach, improved remote reference technique and compensating for overestimation of power spectra. The proposed code has shown high efficiency in processing of low signal-to-noise data.