Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Improving accuracy in studying the interactions of seismic waves with bottom sediments. / Mitrofanov, Georgy; Goreyavchev, Nikita; Kushnarev, Roman.
в: Journal of Marine Science and Engineering, Том 9, № 2, 229, 02.2021, стр. 1-14.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Improving accuracy in studying the interactions of seismic waves with bottom sediments
AU - Mitrofanov, Georgy
AU - Goreyavchev, Nikita
AU - Kushnarev, Roman
N1 - Funding Information: Funding: This research was funded by the Russian Foundation for Basic Research (RFBR), project number 19-35-90087. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/2
Y1 - 2021/2
N2 - The emerging tasks of determining the features of bottom sediments, including the evolution of the seabed, require a significant improvement in the quality of data and methods for their processing. Marine seismic data has traditionally been perceived to be of high quality compared to land data. However, high quality is always a relative characteristic and is determined by the prob-lem being solved. In a detailed study of complex processes, the interaction of waves with bottom sediments, as well as the processes of seabed evolution over short time intervals (not millions of years), we need very high accuracy of observations. If we also need significant volumes of research covering large areas, then a significant revision of questions about the quality of observations and methods of processing is required to improve the quality of data. The article provides an example of data obtained during high-precision marine surveys and containing a wide frequency range from hundreds of hertz to kilohertz. It is shown that these data, visually having a very high quality, have variations in wavelets at all analyzed frequencies. The corresponding variations reach tens of per-cent. The use of the method of factor decomposition in the spectral domain made it possible to significantly improve the quality of the data, reducing the variability of wavelets by several times.
AB - The emerging tasks of determining the features of bottom sediments, including the evolution of the seabed, require a significant improvement in the quality of data and methods for their processing. Marine seismic data has traditionally been perceived to be of high quality compared to land data. However, high quality is always a relative characteristic and is determined by the prob-lem being solved. In a detailed study of complex processes, the interaction of waves with bottom sediments, as well as the processes of seabed evolution over short time intervals (not millions of years), we need very high accuracy of observations. If we also need significant volumes of research covering large areas, then a significant revision of questions about the quality of observations and methods of processing is required to improve the quality of data. The article provides an example of data obtained during high-precision marine surveys and containing a wide frequency range from hundreds of hertz to kilohertz. It is shown that these data, visually having a very high quality, have variations in wavelets at all analyzed frequencies. The corresponding variations reach tens of per-cent. The use of the method of factor decomposition in the spectral domain made it possible to significantly improve the quality of the data, reducing the variability of wavelets by several times.
KW - Correction of amplitude and waveform
KW - Factor models
KW - Marine engineering seismic
KW - Seismic data processing
UR - http://www.scopus.com/inward/record.url?scp=85102030505&partnerID=8YFLogxK
U2 - 10.3390/jmse9020229
DO - 10.3390/jmse9020229
M3 - Article
AN - SCOPUS:85102030505
VL - 9
SP - 1
EP - 14
JO - Journal of Marine Science and Engineering
JF - Journal of Marine Science and Engineering
SN - 2077-1312
IS - 2
M1 - 229
ER -
ID: 28070380