Acoustic encoded full-waveform inversion method research in areas with a rugged surface

2016 ◽  
Author(s):  
Yutong Han ◽  
Jianping Huang ◽  
Zhenchun Li ◽  
Yundong Guo
Keyword(s):  
Waveform Inversion ◽  
Inversion Method ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Rugged Surface

scholarly journals Application of an Improved Ultrasound Full-Waveform Inversion in Bone Quantitative Measurement

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 260
Author(s):  
Meng Suo ◽  
Dong Zhang ◽  
Yan Yang
Keyword(s):  
Nonlinear Equations ◽  
Waveform Inversion ◽  
Optimal Solution ◽  
Inversion Method ◽  
Full Waveform Inversion ◽  
Inversion Algorithm ◽  
Elastic Wave Equation ◽  
Full Waveform ◽  
Ultrasonic Propagation ◽  
Joint Velocity

Inspired by the large number of applications for symmetric nonlinear equations, an improved full waveform inversion algorithm is proposed in this paper in order to quantitatively measure the bone density and realize the early diagnosis of osteoporosis. The isotropic elastic wave equation is used to simulate ultrasonic propagation between bone and soft tissue, and the Gauss–Newton algorithm based on symmetric nonlinear equations is applied to solve the optimal solution in the inversion. In addition, the authors use several strategies including the frequency-grid multiscale method, the envelope inversion and the new joint velocity–density inversion to improve the result of conventional full-waveform inversion method. The effects of various inversion settings are also tested to find a balanced way of keeping good accuracy and high computational efficiency. Numerical inversion experiments showed that the improved full waveform inversion (FWI) method proposed in this paper shows superior inversion results as it can detect small velocity–density changes in bones, and the relative error of the numerical model is within 10%. This method can also avoid interference from small amounts of noise and satisfy the high precision requirements for quantitative ultrasound measurements of bone.

2D time-domain visco-acoustic full waveform inversion method

2015 ◽  
Author(s):  
Haishan Li* ◽  
Wuyang Yang ◽  
Enli Wang ◽  
Xueshan Yong
Keyword(s):  
Time Domain ◽  
Waveform Inversion ◽  
Inversion Method ◽  
Full Waveform Inversion ◽  
Full Waveform

Characterization of Railway Subgrade Using an Elastic Wave Full-Waveform Inversion Method

2020 ◽  
Vol 23 (4) ◽  
pp. 347-358
Author(s):  
Boyoung Kim ◽  
Jun Won Kang ◽  
Yeong-Tae Choi ◽  
Seung Yup Jang
Keyword(s):  
Elastic Wave ◽  
Waveform Inversion ◽  
Inversion Method ◽  
Full Waveform Inversion ◽  
Full Waveform

Improvement of GPR Full-waveform inversion images using Cone Penetration Test data

Geophysics ◽  
2021 ◽  
pp. 1-74
Author(s):  
Zhen Zhou ◽  
Anja Klotzsche ◽  
Jessica Schmäck ◽  
Harry Vereecken ◽  
Jan van der Kruk
Keyword(s):  
Waveform Inversion ◽  
Cone Penetration Test ◽  
Small Scale ◽  
Inversion Method ◽  
Full Waveform Inversion ◽  
Penetration Test ◽  
Cone Penetration ◽  
Full Waveform ◽  
Effective Source

Detailed characterization of aquifers is critical and challenging due to the existence of heterogeneous small-scale high-contrast layers. For an improved characterization of subsurface hydrological characteristics, crosshole ground penetrating radar (GPR) and Cone Penetration Test (CPT) measurements are performed. In comparison to the CPT approach that can only provide 1D high resolution data along vertical profiles, crosshole GPR enables measuring 2D cross-sections between two boreholes. Generally, a standard inversion method for GPR data is the ray-based approach that considers only a small amount of information and can therefore only provide limited resolution. In the last decade, full-waveform inversion (FWI) of crosshole GPR data in time domain has matured, and provides inversion results with higher resolution by exploiting the full recorded waveform information. However, the FWI results are limited due to complex underground structures and the non-linear nature of the method. A new approach that uses CPT data in the inversion process is applied to enhance the resolution of the final relative permittivity FWI results by updating the effective source wavelet. The updated effective source wavelet possesses a priori CPT information and a larger bandwidth. Using the same starting models, a synthetic model comparison between the conventional and updated FWI results demonstrates that the updated FWI method provides reliable and more consistent structures. To test the method, five experimental GPR cross-section results are analyzed with the standard FWI and the new proposed updated approach. Both synthetic and experimental results indicate the potential of improving the reconstruction of subsurface aquifer structures by combining conventional 2D FWI results and 1D CPT data.

scholarly journals Optimal coding of blended seismic sources for 2D full waveform inversion in time

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Katherine Flórez ◽  
Sergio Alberto Abreo Carrillo ◽  
Ana Beatriz Ramírez Silva
Keyword(s):  
Waveform Inversion ◽  
Velocity Model ◽  
Computational Time ◽  
Inversion Method ◽  
Single Shot ◽  
Full Waveform Inversion ◽  
Velocity Models ◽  
Full Waveform ◽  
Seismic Image ◽  
Blended Data

Full Waveform Inversion (FWI) schemes are gradually becoming more common in the oil and gas industry, as a new tool for studying complex geological zones, based on their reliability for estimating velocity models. FWI is a non-linear inversion method that iteratively estimates subsurface characteristics such as seismic velocity, starting from an initial velocity model and the preconditioned data acquired. Blended sources have been used in marine seismic acquisitions to reduce acquisition costs, reducing the number of times that the vessel needs to cross the exploration delineation trajectory. When blended or simultaneous without previous de-blending or separation, stage data are used in the reconstruction of the velocity model with the FWI method, and the computational time is reduced. However, blended data implies overlapping single shot-gathers, producing interference that affects the result of seismic approaches, such as FWI or seismic image migration. In this document, an encoding strategy is developed, which reduces the overlap areas within the blended data to improve the final velocity model with the FWI method.

scholarly journals Full-waveform inversion of incoherent dynamic traction in a bounded 2D domain of scalar wave motions

2020 ◽  
Author(s):  
Bruno Guidio ◽  
Chanseok Jeong
Keyword(s):  
Numerical Solutions ◽  
Waveform Inversion ◽  
Sampling Rate ◽  
Measurement Data ◽  
Inversion Method ◽  
Full Waveform Inversion ◽  
Computational Domain ◽  
Control Parameters ◽  
Frequency Content ◽  
Full Waveform

This paper presents a full-waveform inversion method for reconstructing the temporal and spatial distribution of unknown, incoherent dynamic traction in a heterogeneous, bounded solid domain from sparse, surficial responses. This work considers SH wave motions in a two-dimensional (2D) domain. The partial-differential-equation (PDE)-constrained optimization framework is employed to search a set of control parameters, by which a misfit between measured responses at sensors on the top surface induced by targeted traction and their computed counterparts induced by estimated traction is minimized. To mitigate the solution multiplicity of the presented inverse problem, we employ the Tikhonov (TN) regularization on the estimated traction function. We present the mathematical modeling and numerical implementation of both optimize-then-discretize (OTD) and discretize-then-optimize (DTO) approaches. The finite element method (FEM) is employed to obtain the numerical solutions of state and adjoint problems. Newton's method is utilized for estimating an optimal step length in combination with the conjugate-gradient scheme, calculating a desired search direction, throughout a minimization process. Numerical results present that the complexity of a material profile in a domain increases the error between reconstructed traction and its target. Second, the OTD and DTO approaches lead to the same inversion result. Third, when the sampling rate of the measurement is equal to the timestep for discretizing estimated traction, the ratio of the size of measurement data to the number of the control parameters can be as small as 1:12 in the presented work. Fourth, it is acceptable to tackle the presented inverse modeling of dynamic traction without the TN regularization. Fifth, the inversion performance is more compromised when the noise of a larger level is added to the measurement data, and using the TN regularization does not improve the inversion performance when noise is added to the measurement.Sixth, our minimizer suffers from solution multiplicity less when it identifies dynamic traction of lower frequency content than that of higher frequency content. The wave responses in a computational domain, induced by targeted traction and its reconstructed one, are in excellent agreement with each other. Thus, if the presented dynamic-input inversion algorithm is extended in realistic 3D settings, it could reconstruct seismic input motions in a truncated domain and, then, replay the wave responses in a computational domain.

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