Autor/Autorin: Bejvani Mohammad
Mohammad Bejvani received the B.Sc. degree in physics from The Bahonar University of Kerman, Kerman, Iran, in 2011, and the M.Sc. degree in geophysics from The University of Tehran, Tehran, Iran, in 2014. His research interests include seismic signal processing, seismic imaging, and inverse problem. He is a member of the EAGE, and SEG societies.
This literature describes concepts and results related to application of time-frequency analysis for automatic detection of traveltime of seismic signals. Firstly, short-time Fourier transform is introduced as one of time-frequency methods, that has more capability than Fourier transform and gives us sensible feature of signal. Optimal window-length computing methods, such as optimization method and chirp rate method in order to enhancing resolution, have been investigated, analytically. Output results and their comparisons endorse effective role of window-length as an important parameter. Like automated first-break picking methods that use instantaneous attributes, we utilize short-time Fourier transform in order to extraction of a local attribute for automatic picking of arrival time. Furthermore, using this tool, we can calculate instantaneous traveltime that help us to identify seismic events in a trace. This procedure leads to detection of reflectors and seismic horizons in the prestack and poststack seismic gathers and sections.
This literature describes concepts and results related to application of time-frequency analysis for automatic detection of traveltime of seismic signals. Firstly, short-time Fourier transform is introduced as one of time-frequency methods, that has more capability than Fourier transform and gives us sensible feature of signal. Optimal window-length computing methods, such as optimization method and chirp rate method in order to enhancing resolution, have been investigated, analytically. Output results and their comparisons endorse e ective role of window-length as an important parameter. Like automated first-break picking methods that use instantaneous attributes, we utilize short-time Fourier transform in order to extraction of a local attribute for automatic picking of arrival time. Furthermore, using this tool, we can calculate instantaneous traveltime that help us to identify seismic events in a trace. This procedure leads to detection of reflectors and seismic horizons in the prestack and poststack seismic gathers and sections.
Über den Autor
Mohammad Bejvani received the B.Sc. degree in physics from The Bahonar University of Kerman, Kerman, Iran, in 2011, and the M.Sc. degree in geophysics from The University of Tehran, Tehran, Iran, in 2014. His research interests include seismic signal processing, seismic imaging, and inverse problem. He is a member of the EAGE, and SEG societies.
Klappentext
This literature describes concepts and results related to application of time-frequency analysis for automatic detection of traveltime of seismic signals. Firstly, short-time Fourier transform is introduced as one of time-frequency methods, that has more capability than Fourier transform and gives us sensible feature of signal. Optimal window-length computing methods, such as optimization method and chirp rate method in order to enhancing resolution, have been investigated, analytically. Output results and their comparisons endorse e¿ective role of window-length as an important parameter. Like automated first-break picking methods that use instantaneous attributes, we utilize short-time Fourier transform in order to extraction of a local attribute for automatic picking of arrival time. Furthermore, using this tool, we can calculate instantaneous traveltime that help us to identify seismic events in a trace. This procedure leads to detection of reflectors and seismic horizons in the prestack and poststack seismic gathers and sections.
