Sciact
  • EN
  • RU

Elastic Full-Waveform Inversion Using Migration-Based Depth Reflector Representation in the Data Domain Full article

Journal Geosciences
ISSN: 2076-3263
Output data Year: 2021, Volume: 11, Number: 2, Article number : 76, Pages count : DOI: 10.3390/geosciences11020076
Tags FWI; macro velocity; waveform inversion; optimisation; reflected waves
Authors Tcheverda Vladimir 1,2 , Gadylshin Kirill 1,2
Affiliations
1 Institute of Computational Mathematics and Mathematical Geophysics, SB RAS, 630090 Novosibirsk, Russia
2 Institute of Petroleum Geology and Geophysics SB RAS, 630090 Novosibirsk, Russia

Abstract: The depth velocity model is a critical element for providing seismic data processing success, as it is responsible for the times of waves’ propagation and, therefore, prescribes the location of geological objects in the resulting seismic images. Constructing a deep velocity model is the most time-consuming part of the entire seismic data processing, which usually requires interactive human intervention. This article introduces the consistently numerical method for reconstructing a depth velocity model based on the modified version of the elastic Full Waveform Inversion (FWI). The specific feature of this approach to FWI is the decomposition of the space of admissible velocity models into subspaces of propagator (macro velocity) and reflector components. In turn, the latter transforms to the data space reflectivity on the base of migration transformation. Finally, we perform minimisation in two different spaces: (1) Macro velocity as a smooth spatial function; (2) Migration transforms data space reflectivity to the spatial reflectivity. We present numerical experiments confirming less sensitiveness of the modified version of FWI to the lack of the low time frequencies in the data acquired. In our computations, we use synthetic data with valuable time frequencies from 5 Hz.
Cite: Tcheverda V. , Gadylshin K.
Elastic Full-Waveform Inversion Using Migration-Based Depth Reflector Representation in the Data Domain
Geosciences. 2021. V.11. N2. 76 . DOI: 10.3390/geosciences11020076 WOS Scopus РИНЦ OpenAlex
Dates:
Submitted: Sep 9, 2020
Accepted: Feb 3, 2021
Published online: Feb 9, 2021
Identifiers:
Web of science: WOS:000622591300001
Scopus: 2-s2.0-85101000185
Elibrary: 46748994
OpenAlex: W3127829207
Citing:
DB Citing
Scopus 4
OpenAlex 5
Web of science 3
Altmetrics: