Elastic least-squares reverse time migration using the energy norm

Rocha, Daniel Guimarães Pedro; Sava, Paul

doi:10.1190/geo2017-0465.1

Cited by 24 publications

(6 citation statements)

References 69 publications

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“…Unlike the 3-D elastic image-domain tomography applied herein, E-FWI aims to match waveforms in the data domain and thus represents the most stringent test for elastic model building techniques to pass. However, a successful E-FWI analysis could generate a significantly higher-resolution velocity model that could lead to further imaging and resolution improvements for resolving the thin hydrate units, especially when coupled with an elastic LSRTM approach …”

Section: Discussionmentioning

confidence: 99%

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Advanced Distributed Acoustic Sensing Vertical Seismic Profile Imaging of an Alaska North Slope Gas Hydrate Field

et al. 2022

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Gas hydrates are found in significant quantities on the North Slope of Alaska in subpermafrost sand units and intermixed in lower portions of permafrost within the hydrate stability window. While conventional surface seismic data and established imaging methods can indicate the presence of gas hydrate reservoirs, producing high-resolution images of (seismically) thin layers remains challenging due to the preferential attenuation of the higher-frequency data components. An alternative strategy is to use distributed acoustic sensing (DAS) involving cementing optical fibers into boreholes to measure seismic wavefield energy closer to the strata of interest using vertical seismic profiling (VSP). DAS VSP imaging takes advantage of the shorter travel paths and reduced attenuation to generate higher-resolution near-well images. We illustrate these benefits on a DAS VSP data set acquired at the Hydrate-01 stratigraphic test well located in the Prudhoe Bay Unit of Alaska where significant gas hydrate deposits have been detected in two subpermafrost sand layers that are intended for long-duration production testing. Our DAS data preprocessing workflow effectively isolates the upgoing compressional-wave (P-wave) reflections required for subsurface acoustic imaging. After applying three-dimensional (3-D) tomography to improve the quality of the 3-D migration velocity model, we use 3-D reverse-time migration (RTM) to develop high-quality images of the two target sands and minor near-well faulting. We validate our RTM images through highly accurate well-ties with previously acquired petrophysical log data. This study demonstrates that combining 3-D RTM imaging with DAS VSP data provides significant value to gas hydrate and similar projects, and it suggests that more advanced inversion approaches such as (elastic) least-squares RTM could recover higher-resolution and more quantitative estimates of subsurface reflectivity, which would be valuable for refining the understanding of gas hydrate systems.

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Section: Discussionmentioning

confidence: 99%

“…However, a successful E-FWI analysis could generate a significantly higher-resolution velocity model that could lead to further imaging and resolution improvements for resolving the thin hydrate units, especially when coupled with an elastic LSRTM approach. 40…”

Section: ■ Discussionmentioning

confidence: 99%

Advanced Distributed Acoustic Sensing Vertical Seismic Profile Imaging of an Alaska North Slope Gas Hydrate Field

et al. 2022

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“…Dai et al (2010) regarded the conventional RTM as an inversion problem under the framework of least squares, used the iterative method to obtain the reflection coefficient model, and developed a least-squares reverse time migration (LSRTM) method. Since the LSRTM can obtain the imaging results with high precision, high-amplitude preservation, and high resolution, it has become a research hotspot in the field of geophysics (Dai et al, 2012;Guo and Li, 2014;Huang et al, 2014;Yao and Jakubowicz, 2016;Ren et al, 2017;Rocha and Sava, 2018;Gong et al, 2019;Yang and Zhu, 2019;Li et al, 2020). Dai et al (2012) proposed multisource LSRTM based on phase encoding, which improved the computational efficiency of the algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Ren et al (2017) developed elastic LSRTM, which provided more abundant and effective information for accurate imaging of complex media. Rocha and Sava (2018) proposed elastic LSRTM using the energy norm to improve imaging accuracy and speed up the convergence. Gong et al ( 2019) applied a sparsitypromoting constraint to the LSRTM and obtained better imaging, especially for the metallogenetic geological model containing small-scale scatters.…”

Section: Introductionmentioning

confidence: 99%

Least-Squares Reverse Time Migration Using the Gradient Preconditioning Based on Transmitted Wave Energy

Xie

Song

et al. 2021

Front. Earth Sci.

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A gradient preconditioning approach based on transmitted wave energy for least-squares reverse time migration (LSRTM) is proposed in this study. The gradient is preconditioned by using the energy of “approximate transmission wavefield,” which is calculated based on the non-reflecting acoustic equation. The proposed method can effectively avoid a huge amount of calculation and storage required by the Hessian matrix or approximated Hessian matrix and can overcome the influence of reflected waves, multiples, and other wavefields on the gradient in gradient preconditioning based on seismic wave energy (GPSWE). The numerical experiments, compared with that using GPSWE, show that LSRTM using the gradient preconditioning based on transmitted wave energy (GPTWE) can significantly improve the imaging accuracy of deep target and accelerate the convergence rate without trivial increased calculation.

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“…LSM is a linearized waveform inversion that has been used to find the image that best predicts, in a least-squares sense, the recorded seismic data [47,48]. When LSM uses an RTM engine, it is referred to as least-squares reverse-time migration (LSRTM) [49][50][51].…”

Section: Introductionmentioning

confidence: 99%

Least-squares reverse time migration (LSRTM) for damage imaging using Lamb waves

Rocha

Leser

et al. 2019

Smart Mater. Struct.

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Large-area monitoring and accurate damage quantification are two primary goals of ultrasonic, guided wave-based structural health monitoring (SHM). Reverse-time migration (RTM) is an effective damage imaging technique for both metallic and composite plates. In geophysics, incorporating least-squares inversion into migration can generate images with higher resolution and suppressed artifacts in comparison with conventional RTM. Development of a least-squares reverse time migration (LSRTM) technique is promising for SHM since it could expand the imaging area for a given sensor array while maintaining a relatively high resolution. An LSRTM technique is introduced in this research for damage imaging in an isotropic plate using A 0 mode Lamb waves. A finite difference algorithm based on the Mindlin plate theory was used to simulate the flexural wave propagation. To form the theoretical foundations for guided wavebased LSRTM, a forward modeling operator and its adjoint are defined. The damage images from both numerical simulations and experiments show that LSRTM can enhance imaging resolution and reduce artifacts.

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Elastic least-squares reverse time migration using the energy norm

Cited by 24 publications

References 69 publications

Advanced Distributed Acoustic Sensing Vertical Seismic Profile Imaging of an Alaska North Slope Gas Hydrate Field

Advanced Distributed Acoustic Sensing Vertical Seismic Profile Imaging of an Alaska North Slope Gas Hydrate Field

Least-Squares Reverse Time Migration Using the Gradient Preconditioning Based on Transmitted Wave Energy

Least-squares reverse time migration (LSRTM) for damage imaging using Lamb waves

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