Improving Accuracy in Studying the Interactions of Seismic Waves with Bottom Sediments
| Autor: | Nikita Goreyavchev, Roman Kushnarev, Georgy Mitrofanov |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
010504 meteorology & atmospheric sciences
Factor decomposition lcsh:Naval architecture. Shipbuilding. Marine engineering Ocean Engineering Spectral domain marine engineering seismic 010502 geochemistry & geophysics 01 natural sciences Seismic wave seismic data processing lcsh:Oceanography Wavelet Quality (physics) factor models lcsh:VM1-989 correction of amplitude and waveform Range (statistics) lcsh:GC1-1581 Seabed Geology 0105 earth and related environmental sciences Water Science and Technology Civil and Structural Engineering Remote sensing Factor analysis |
| Zdroj: | Journal of Marine Science and Engineering Volume 9 Issue 2 Journal of Marine Science and Engineering, Vol 9, Iss 229, p 229 (2021) |
| ISSN: | 2077-1312 |
| DOI: | 10.3390/jmse9020229 |
| Popis: | 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 problem 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 percent. 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. |
| Databáze: | OpenAIRE |
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