Multi-wave Imaging Research Articles

Multi-Wave Imaging Methods for Distributed Acoustic Sensing Vertical Seismic Profile Assisted by Artificial Intelligence Processing

Multi-Wave Imaging Methods for Distributed Acoustic Sensing Vertical Seismic Profile Assisted by Artificial Intelligence Processing

Vector Decomposition of Elastic Seismic Wavefields Using Self-Attention Deep Convolutional Generative Adversarial Networks

Vector decomposition of P- and S-wave modes from elastic seismic wavefields is a key step in elastic reverse-time migration (ERTM) to effectively improve the multi-wave imaging accuracy. Most previously developed methods based on the apparent velocities or the polarization characteristics of different wave modes are unable to accurately achieve the vector decomposition of P- and S-wave modes. To effectively overcome the shortcomings of conventional methods, we develop a vector decomposition method of P- and S-wave modes using self-attention deep convolutional generative adversarial networks (SADCGANs) to effectively separate the horizontal and vertical components of P- and S-wave modes from elastic seismic wavefields and accurately preserve their amplitude and phase characteristics for isotropic elastic media. For an elastic model, we use many time slices for a given source position to train the neural network, and use other time slices not in this training dataset to test the neural network. Numerical examples of different models demonstrate the effectiveness and feasibility of our developed method and indicate that it provides an effective intelligent data-driven vector decomposition method of P- and S-wave modes.

A fast and accurate elastic reverse-time migration method based on decoupled elastic wave equations

The extrapolation and decomposition of different mode waves are very important to efficiently obtain multi-wave depth images for elastic reverse-time migration (ERTM). To achieve this goal successfully, we firstly develop an efficient and accurate staggered-grid finite-difference method (SFDM) based on decoupled elastic wave equations. This developed SFDM uses two sets of difference operator lengths for decoupled elastic wave equations to respectively perform the extrapolation of decoupled P- and S-wavefields and employs the least squares (LS) to minimize the objective functions respectively constructed from the time-space dispersion equations of P- and S-waves to generate their corresponding difference coefficients. This developed method can theoretically be regarded as the optimal SFDM based on least squares (LSSFDM), and it can provide the high-precision separated wavefields of different mode waves simultaneously and reduce the computing time effectively for elastic wave modeling under the given accuracy requirements. The modeling results of different models illustrate that our developed LSSFDM based on decoupled elastic wave equations can generate the decomposed P- and S-wavefields and suppress their numerical dispersions effectively. Secondly, we present a fast and accurate ERTM method based on this developed LSSFDM to successfully achieve the multi-wave imaging results, including PP, PS, SP and SS images. The ERTM examples of different models demonstrate that our ERTM based on this developed LSSFDM can accurately obtain the high-precision depth images of multimode waves and effectively reduce the computing time of wavefield extrapolation.

Detection of geological anomalies in coal mining working faces using a scattered-wave imaging method

A concealed geological structure encountered during the excavation of a coal working face could connect the working face to high-pressure water in limestone strata, which can result in a serious or catastrophic water inrush accident. However, existing geophysical detection methods used to ensure the geological safety of working faces cannot detect small geological anomalies reliably. Based on the generalized theory of scattered waves, we have developed a novel and superior scattered wave imaging method for the detection at the roadway lateral wall, capable of wave vector extraction and multiwave imaging. In this method, the waves scattered from a geological anomaly can be dynamically and accurately extracted by the polarized filter function during the mapping processes of common scattering point (CSP) gathers. A numerical simulation was performed to study the seismic wave response characteristics of a small collapse column in a coal working face. The P and channel waves of the model were extracted and imaged using the novel imaging method. A field study of three-component seismic detection was performed in the Xuzhuang Coal Mine, demonstrating that the joint imaging of body and channel waves can detect small drop faults invisible to channel wave imaging alone. These results indicate that the proposed method can effectively image anomalous bodies on working faces in complex and noisy mine wavefields using multiwave information, providing a new approach for the reliable and timely detection of hazardous geological features hidden in working faces.

Inverse conductivity Problem with Internal Data

This paper concerns the reconstruction of a scalar coefficient of a second-order elliptic equation in divergence form posed on a bounded domain from internal data. This theory finds applications in multi-wave imaging, greedy methods to approximate parameter-dependent elliptic problems, and image treatment with partial differential equations. We first show that the inverse problem for smooth coefficients can be rewritten as a linear transport equation. Assuming that the coefficient is known near the boundary, we study the well-posedness of associated transport equation as well as its numerical resolution using discontinuous Galerkin method. We propose a regularized transport equation that allow us to derive rigorous convergence rates of the numerical method in terms of the order of the polynomial approximation as well as the regularization parameter. We finally provide numerical examples for the inversion assuming a lower regularity of the coefficient, and using synthetic data.

A 0.15μ Vrms Super-Sensitivity Photoacoustic Imager Based on Coherent Detection for Deep in-Vivo Imaging

Among various multi-wave imaging methods, the photoacoustic imaging (PAI) has attracted more attention because it can achieve higher resolution and contrast through combining advantages of light excitation and ultrasound detection. However, due to low restricted laser fluence, large scattering and attenuation in tissue, and low energy conversion efficiency, high sensitivity is still imperative in the receiver to read out PA signals. A new photoacoustic receiver with mixed-signal coherent detection technique is developed and fabricated for the first time. Co-working with the early-late acquisition and tracking technique, the receiver can lock into the weak PA signal automatically. For the receiver system on chip (SoC), a high performance analog front-end (AFE) with a low noise amplifier (LNA), low-pass filter (LPF), programmable-gain amplifier (PGA), multiplier, successive-approximation analog-to-digital converter (SAR ADC) and digital-to-analog converter (DAC) are implemented on chip. Noise shaping (NS) technique is implemented in the SAR ADC to enhance the signal-to-noise ratio (SNR). Measurement results show that, the LNA achieves 0.23mPa√(mW/Hz) noise efficiency factor (NEF) with the aid of resonant noise matching (RNM) technique, and the NS-SAR ADC can obtain 62.2dB signal-to-noise-and-distortion ratio (SNDR) in 10MHz bandwidth under 100MS/s sampling rate. The single channel receiver can achieve 138dB dynamic range and 0.15μVrms sensitivity. The output SNR can be improved by about 6dB after enabling the 4 channels. The power consumption of a single channel is 28.8mW. The contrast-to-noise ratio (CNR) of the images at 1cm depth is 44dB.

Clinical theranostics applications of photo-acoustic imaging as a future prospect for cancer.

Photoacoustic imaging (PAI) of biological tissue has been a fast developing biomedical multi-wave imaging modality, after its introduction in the mid90s. PAI couples laser excitation to acoustic detection. Especially, in recent years its significant advantages in onco-surgery has attracted much attention due to its ability to detect malignant tissues. Monitoring cancer angiogenesis, assessment of blood oxygen saturation, functional brain imaging, evaluation of cortical blood volume, detection of skin/conjunctival melanoma depth, assessment of met-hemoglobin, investigating tumor hypoxia andcancer lymph node metastases are some of its promising applications. Moreover, as a real-time monitoring strategy, PAI allows intraoperative imaging of micro-metastases and residual islands in onco-surgery. Herein, we provide a brief introduction to biophysics and fundamentals of PAI, potential novel endogenous and exogenous contrast agents, and novel techniques to develop engineered and targeted contrast agents with theranostic applications. We also summarize the clinical trial pipelines for PAI. Furthermore, we discuss the potential obstacles and limitation of PAI theranostic agents for further clinical applications and strategies to overcome these hurdles.

Direct algorithm for reconstructing small absorbers in thermoacoustic tomography problem from a single data

This work deals with the inverse thermoacoustic tomography (TAT) problem. It is a biomedical, multi-wave imaging technique, based on the photoacoustic effect (generation of sound from light) that was discovered in 1880 by Alexander Graham Bell. The inverse problem we are concerned in is the inverse source problem of recovering small absorbers in a bounded domain without following the quantitative thermoacoustic tomography approach. In our work, we follow a direct algebraic algorithm, that was first developed in Badia and Ha-Duong (2001 Inverse Problems 17 1127), which allows us to reconstruct the number of absorbers, their locations, and some information about the conductivity coefficient directly from the wave equation with constant sound speed, and using a single data, without the knowledge of the coupling Grüneisen’s coefficient measuring the strength of the photoacoustic effect. Finally, we establish the corresponding Hölder stability result.

Research on vertical cable seismic multiples imaging processing

Vertical cable seismic (VCS) is a kind of reflection seismic exploration technique. Multi-node hydrophone array set perpendicular to the seabed and records wave field inspired by air gun. Vertical cable seismic exploration can make up for the disadvantages of the harsh conditions of towed cable seismic exploration. VCS technique is also convenient to be used in monitoring the underground geologic changes in the stage of gas hydrates development. In this paper, VCS data collected near the gas hydrates test and mining area of the South China Sea was processed and obtained multi-wave imaging profiles. It is shown that the VCS data has such advantages as high signal-to-noise ratio, high fidelity, and so on compared to the towed cable data, especially in the imaging of underground steep dip angle geological structures.

Magnetoacoustic microscopic imaging of conductive objects and nanoparticles distribution

Magnetoacoustic tomography has been demonstrated as a powerful and low-cost multi-wave imaging modality. However, due to limited spatial resolution and detection efficiency of magnetoacoustic signal, full potential of the magnetoacoustic imaging remains to be tapped. Here we report a high-resolution magnetoacoustic microscopy method, where magnetic stimulation is provided by a compact solenoid resonance coil connected with a matching network, and acoustic reception is realized by using a high-frequency focused ultrasound transducer. Scanning the magnetoacoustic microscopy system perpendicularly to the acoustic axis of the focused transducer would generate a two-dimensional microscopic image with acoustically determined lateral resolution. It is analyzed theoretically and demonstrated experimentally that magnetoacoustic generation in this microscopic system depends on the conductivity profile of conductive objects and localized distribution of superparamagnetic iron magnetic nanoparticles, based on two different but related implementations. The lateral resolution is characterized. Directional nature of magnetoacoustic vibration and imaging sensitivity for mapping magnetic nanoparticles are also discussed. The proposed microscopy system offers a high-resolution method that could potentially map intrinsic conductivity distribution in biological tissue and extraneous magnetic nanoparticles.

Eddy current thermography imaging for condition-based maintenance of overlay welded components under multi-degradation

This paper presents a new multi-wave imaging method for the condition-based maintenance of offshore hydraulic systems containing overlay welded components under multi-degradation. These components suffer from combined tribocorrosion interacting with static and cyclic loading, for which effective mathematical models have not yet been established. In this paper, we propose eddy current thermography imaging for real-time structural health monitoring to enable condition-based maintenance of these critical components. The main challenge for the structural health monitoring of these components is that defects are often embedded at the substrate-coating interfacial regions that have irregular shapes in anisotropic and heterogeneous material as a result of the welding process. The eddy current thermography imaging method utilizes coupled electromagnetic–thermal fields and diffusion waves for robust detection of these hidden defects. A mathematical algorithm and software based on the discrete Fourier transform of thermal videos registered by an infrared detector was developed to characterize and visualize defects. The detectability of this method was investigated using a real cobalt superalloy overlay welded onto a carbon steel piston rod, in which an artificial volumetric defect was made at the interfacial region. The probability of detection and condition-based maintenance using the detected defect data is discussed based on the P-F curve and the probability of failure graphs.

Reconstruction for multi-wave imaging in attenuating media with large damping coefficient

In this article we study the reconstruction problem in TAT/PAT on an attenuating media. Namely, we prove a reconstruction procedure of the initial condition for the damped wave equation via Neumann series that works for arbitrary large smooth attenuation coefficients extending the result of Homan in (2013 Inverse Problems Imaging 7 1235–50). We also illustrate the theoretical result by including some numerical experiments at the end of the paper.

Multiwave imaging in an enclosure with variable wave speed

In this paper we consider the mathematical model of thermo- and photo-acoustic tomography for the recovery of the initial condition of a wave field from knowledge of its boundary values. Unlike the free-space setting, we consider the wave problem in a region enclosed by a surface where an impedance boundary condition is imposed. This condition models the presence of physical boundaries such as interfaces or acoustic mirrors which reflect some of the wave energy back into the enclosed domain. By recognizing that the inverse problem is equivalent to a statement of boundary observability, we use control operators to prove the unique and stable recovery of the initial wave profile from knowledge of boundary measurements. Since our proof is constructive, we explicitly derive a solvable equation for the unknown initial condition. This equation can be solved numerically using the conjugate gradient method. We also propose an alternative approach based on the stabilization of waves. This leads to an exponentially and uniformly convergent Neumann series reconstruction when the impedance coefficient is not identically zero. In both cases, if well-known geometrical conditions are satisfied, our approaches are naturally suited for variable wave speed and for measurements on a subset of the boundary.

Multi-wave imaging in attenuating media

We consider a mathematical model of thermoacoustic tomography andother multi-wave imaging techniques with variable sound speed andattenuation. We find that a Neumann series reconstruction algorithm,previously studied under the assumption of zero attenuation, stillconverges if attenuation is sufficiently small. With completeboundary data, we show the inverse problem has a unique solution, andmodified time reversal provides a stable reconstruction. We alsoconsider partial boundary data, and in this case study thosesingularities that can be stably recovered.

A Multiwave Imaging Approach for Elastography

Interactions between waves can be turned into profit to break diffraction limits and invent new kinds of medical images. It consists in productively combining two very different waves -- one to provide contrast, another to provide spatial resolution -in order to build a new kind of image, Multiwave imaging provides a unique image of the most interesting contrast with the most interesting resolution. We will show in this paper how this general concept of multiwave imaging allow to perform high resolution and quantitative elasticity imaging of the human body. Here, the two waves are sonic shear waves and ultrasonic compressional waves. A comparison with static elastography (a single wave technique) will show the interest of multiwave imaging and various clinical examples will be presented to illustrate the efficiency of this approach. Keywords: Ultrasound, elastography, ultrafast imaging, cancer, elasticity, shear wave imaging, radiology, medical imaging

Multiwave imaging and super resolution

Interactions between different kinds of waves can yield medical images that beat the single-wave resolution limit.