Reflection multi‐scale envelope inversion

Chen, Guoxin; Wu, Ru‐Shan; Chen, Sheng‐Chang

doi:10.1111/1365-2478.12624

Cited by 32 publications

(7 citation statements)

References 38 publications

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“…The performance of the conventional EI and FWI on the salt model in numerical experiments also verified this inference. Based on the above analysis, a new direct envelope Fréchet derivative was proposed (Chen, ; Chen & Wu, ; Chen, Wu, & Chen, , ; Chen, Wu, Wang, & Chen, ; Wu & Chen, , , ; Wu et al, ) to derive the sensitivity operator of the EI using the WAE

\begin{matrix} lefttrue \\ \frac{\partial σ_{W}}{\partial v} = \sum_{italicSRT} r_{W} (t) \frac{\partial r_{W}}{\partial e_{W} (t)} \frac{\partial e_{W_{syn}} (t)}{\partial v}, \\ = \sum_{italicSRT} r_{W} (t) \frac{1}{τ_{W}} \int_{- τ_{W} / 2}^{τ_{W} / 2} d t^{'} W (t - t^{'}) \frac{\partial e_{syn}^{2} (t^{'})}{\partial v}, \end{matrix}

where

\partial e_{W_{syn}} ((), t) / \partial v

is the new envelope Fréchet derivative.…”

Section: Theory and Methodsmentioning

confidence: 99%

“…In addition to the data domain, multiscale inversion strategies can also be implemented in the model domain based on the theoretical analyses by Mora (). There are three main methods that can be used depending on the implementation strategy, including angle domain filtering (Alkhalifah, , ; Luo & Xie, ; Wu & Alkhalifah, , ; Xie, ; Yao et al, ), wavefield decomposition (Tang & Lee, ; F. Wang et al, , ; Wu & Alkhalifah, ), and reflection waveform inversion (Brossier et al, ; Chen, Wu, & Chen, ; Irabor & Warner, ; Xu et al, ; Yao & Wu, ; Zhou et al, ). However, no matter which multiscale inversion strategy is adopted, the low‐frequency information is still indispensable for the FWI to obtain a globally optimal solution.…”

Section: Introductionmentioning

confidence: 99%

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Multiscale Direct Envelope Inversion: Algorithm and Methodology for Application to the Salt Structure Inversion

Chen

2019

Earth and Space Science

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For the full‐waveform inversion, obtaining a globally optimal solution is difficult when the seismic data do not contain sufficient low‐frequency information and the inversion object is a salt structure with a large‐scale salt dome. The large salt dome presents difficulty for the inversion of the salt structure; however, it also confers a convenience that can be utilized: A large salt dome makes the events in the seismic record sparse and isolated. We use the envelope to obtain the arrival time of the events in the seismic data and apply multiscale strategies to extract the low‐frequency information of the seismic data that relates to the long‐wavelength components of the subsurface. In calculating the gradient, the envelope Fréchet derivative is used to take advantage of the multiscale envelope for the characteristics of the salt structure. Therefore, the multiscale direct envelope inversion using the window‐averaged envelope and the direct envelope Fréchet derivative is proposed. To further improve the computational efficiency and inversion quality of the multiscale direct envelope inversion, several auxiliary strategies are proposed: A joint misfit function is designed to make the inversion method more adaptable, and an offset weighting factor is introduced to implement the multioffset inversion method to improve the inversion quality of subsalt. We analyze the antinoise performance of the multiscale direct envelope inversion. The SEG/EAGE salt model is used to test the application effect of the multiscale direct envelope inversion. The antinoise ability and insensitivity to low‐frequency data of the method are verified in the numerical experiments.

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\begin{matrix} lefttrue \\ \frac{\partial σ_{W}}{\partial v} = \sum_{italicSRT} r_{W} (t) \frac{\partial r_{W}}{\partial e_{W} (t)} \frac{\partial e_{W_{syn}} (t)}{\partial v}, \\ = \sum_{italicSRT} r_{W} (t) \frac{1}{τ_{W}} \int_{- τ_{W} / 2}^{τ_{W} / 2} d t^{'} W (t - t^{'}) \frac{\partial e_{syn}^{2} (t^{'})}{\partial v}, \end{matrix}

where

\partial e_{W_{syn}} ((), t) / \partial v

is the new envelope Fréchet derivative.…”

Section: Theory and Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiscale Direct Envelope Inversion: Algorithm and Methodology for Application to the Salt Structure Inversion

Chen

2019

Earth and Space Science

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“…As the correspondence between low-frequency seismic data and low-wavenumber/large-scale structures is linear in the Born single scattering (Wu and Zheng, 2014), due to the lack of low-frequency content (<5 Hz) in most reflection seismic data, most developments in FWI have been focusing on how to recover large-scale structural information when low-frequency data are not available. These developments include, for example, the Laplace FWI (Shin and Cha, 2008;Shin and Ha, 2008;Kim et al, 2013), envelope inversion Luo and Wu, 2015;Chen et al, 2018), intensity inversion (Liu et al, 2018;Liu et al, 2020), and the FWI using deep learning techniques (Richardson, 2018).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Inversion of Layered Velocity and Density Profiles Using Direct Waveform Inversion (DWI): 1D Case

2022

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To better interpret the subsurface structures and characterize the reservoir, a depth model quantifying P-wave velocity together with additional rock’s physical parameters such as density, the S-wave velocity, and anisotropy is always preferred by geologists and engineers. Tradeoffs among different parameters can bring extra challenges to the seismic inversion process. In this study, we propose and test the Direct Waveform Inversion (DWI) scheme to simultaneously invert for 1D layered velocity and density profiles, using reflection seismic waveforms recorded on the surface. The recorded data includes primary reflections and interbed multiples. DWI is implemented in the time-space domain then followed by a wavefield extrapolation to downward continue the source and receiver. By explicitly enforcing the wavefield time-space causality, DWI can recursively determine the subsurface seismic structure in a local layer-by-layer fashion for both sharp interfaces and the properties of the layers, from shallow to deep depths. DWI is different from the layer stripping methods in the frequency domain. By not requiring a global initial model, DWI also avoids many nonlinear optimization problems, such as the local minima or the need for an accurate initial model in most waveform inversion schemes. Two numerical tests show the validity of this DWI scheme serving as a new strategy for multi-parameter seismic inversion.

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“…Wang et al (2017) combined the elastic properties and the traveltime-based misfit function together to update both P-and S-wave velocities. Bozdag et al (2011), Wu et al (2014) and Chen et al (2018) introduced a reflection multiscale envelope inversion method so that the signal's envelope carries ultra-low frequency information missing in the original signal. Furthermore, a set of methods have been developed to exclude the cycle-skipped events in different domains (Bunks et al, 1995;Asnaashari et al, 2012;Bi and Lin, 2014;AlTheyab and Schuster, 2015).…”

Section: Introductionmentioning

confidence: 99%

Multiscale reflection phase inversion with migration deconvolution

Chen

Feng

et al. 2020

GEOPHYSICS

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Reflection full-waveform inversion (RFWI) can recover the low-wavenumber components of the velocity model along with the reflection wavepaths. However, this requires an expensive least-squares reverse time migration (LSRTM) to construct the perturbation image that can still suffer from cycle-skipping problems. As an inexpensive alternative to LSRTM, we use migration deconvolution (MD) with RFWI. To mitigate cycle-skipping problems, we develop a multiscale reflection phase inversion (MRPI) strategy that boosts the low-frequency data and should only explain the phase information in the recorded data, not its magnitude spectrum. We also use the rolling-offset strategy that gradually extends the offset range of data with an increasing number of iterations. Numerical results indicate that the MRPI + MD method can efficiently recover the low-wavenumber components of the velocity model and is less prone to getting stuck in local minima compared to conventional RFWI.

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Reflection multi‐scale envelope inversion

Cited by 32 publications

References 38 publications

Multiscale Direct Envelope Inversion: Algorithm and Methodology for Application to the Salt Structure Inversion

Multiscale Direct Envelope Inversion: Algorithm and Methodology for Application to the Salt Structure Inversion

Simultaneous Inversion of Layered Velocity and Density Profiles Using Direct Waveform Inversion (DWI): 1D Case

Multiscale reflection phase inversion with migration deconvolution

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