scholarly journals High frequency refraction/ reflection full-waveform inversion case study from North West Shelf offshore Australia

2018 ◽  
Vol 2018 (1) ◽  
pp. 1-5
Author(s):  
David Dickinson ◽  
Fabio Mancini ◽  
Xiang Li ◽  
Kai Zhao
Keyword(s):  
High Frequency ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
North West ◽  
Full Waveform

A refraction/reflection full-waveform inversion case study from North West Shelf offshore Australia

2017 ◽  
Author(s):  
David Dickinson ◽  
Fabio Mancini ◽  
Xiang Li ◽  
Kai Zhao ◽  
Shuo Ji
Keyword(s):  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
North West ◽  
Full Waveform

High-frequency acoustic land full-waveform inversion: a case study from the Sultanate of Oman

First Break ◽  
2019 ◽  
Vol 37 (1) ◽  
pp. 75-81 ◽  
Author(s):  
A. Sedova ◽  
G. Royle ◽  
T. Allemand ◽  
G. Lambaré ◽  
O. Hermant
Keyword(s):  
High Frequency ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Sultanate Of Oman ◽  
Full Waveform

Towards High-frequency Full Waveform Inversion - A Case Study

2014 ◽  
Author(s):  
B. Qin ◽  
V. Prieux ◽  
H. Bi ◽  
A. Ratcliffe ◽  
J.P. Montel ◽  
...  
Keyword(s):  
High Frequency ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Full Waveform

Time-lapse full waveform inversion based on curvelet transform: Case study of CO2 storage monitoring

2021 ◽  
Vol 110 ◽  
pp. 103417
Author(s):  
Dong Li ◽  
Suping Peng ◽  
Xingguo Huang ◽  
Yinling Guo ◽  
Yongxu Lu ◽  
...  
Keyword(s):  
Co2 Storage ◽  
Waveform Inversion ◽  
Curvelet Transform ◽  
Time Lapse ◽  
Full Waveform Inversion ◽  
Full Waveform

Denoising for full-waveform inversion with expanded prediction-error filters

Geophysics ◽  
2021 ◽  
pp. 1-54
Author(s):  
Milad Bader ◽  
Robert G. Clapp ◽  
Biondo Biondi
Keyword(s):  
High Frequency ◽  
Prediction Error ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Frequency Data ◽  
Signal To Noise ◽  
Frequency Signal ◽  
Full Waveform

Low-frequency data below 5 Hz are essential to the convergence of full-waveform inversion towards a useful solution. They help build the velocity model low wavenumbers and reduce the risk of cycle-skipping. In marine environments, low-frequency data are characterized by a low signal-to-noise ratio and can lead to erroneous models when inverted, especially if the noise contains coherent components. Often field data are high-pass filtered before any processing step, sacrificing weak but essential signal for full-waveform inversion. We propose to denoise the low-frequency data using prediction-error filters that we estimate from a high-frequency component with a high signal-to-noise ratio. The constructed filter captures the multi-dimensional spectrum of the high-frequency signal. We expand the filter's axes in the time-space domain to compress its spectrum towards the low frequencies and wavenumbers. The expanded filter becomes a predictor of the target low-frequency signal, and we incorporate it in a minimization scheme to attenuate noise. To account for data non-stationarity while retaining the simplicity of stationary filters, we divide the data into non-overlapping patches and linearly interpolate stationary filters at each data sample. We apply our method to synthetic stationary and non-stationary data, and we show it improves the full-waveform inversion results initialized at 2.5 Hz using the Marmousi model. We also demonstrate that the denoising attenuates non-stationary shear energy recorded by the vertical component of ocean-bottom nodes.

Reflection Full Waveform Inversion of Walkaway VSP – Abu Dhabi Case Study

2020 ◽  
Author(s):  
A. Shigematsu ◽  
Y. Nakamura ◽  
A. Kato ◽  
T. Mouri ◽  
G. Sakata ◽  
...  
Keyword(s):  
Waveform Inversion ◽  
Abu Dhabi ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Walkaway Vsp
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