3D Reverse-Time Migration Imaging for Multiple Cross-Hole Research and Multiple Sensor Settings of Cross-Hole Seismic Exploration.

The two-dimensional (2D) cross-hole seismic computed tomography (CT) imaging acquisition method has the potential to characterize the target zone optimally compared to surface seismic surveys. It has wide applications in oil and gas exploration, engineering geology, etc. Limited to 2D hole velocity profiling, this method cannot acquire three-dimensional (3D) information on lateral geological structures outside the profile. Additionally, the sensor data received by cross-hole seismic exploration constitute responses from geological bodies in 3D space and are potentially affected by objects outside the well profiles, distorting the imaging results and geological interpretation. This paper proposes a 3D cross-hole acoustic wave reverse-time migration imaging method to capture 3D cross-hole geological structures using sensor settings in multi-cross-hole seismic research. Based on the analysis of resulting 3D cross-hole images under varying sensor settings, optimizing the observation system can aid in the cost-efficient obtainment of the 3D underground structure distribution. To verify this method's effectiveness on 3D cross-hole structure imaging, numerical simulations were conducted on four typical geological models regarding layers, local high-velocity zones, large dip angles, and faults. The results verify the model's superiority in providing more reliable and accurate 3D geological information for cross-hole seismic exploration, presenting a theoretical basis for processing and interpreting cross-hole data.

Research on the 3D Reverse Time Migration Technique for Internal Defects Imaging and Sensor Settings of Pressure Pipelines.

Although pressure pipelines serve as a secure and energy-efficient means of transporting oil, gas, and chemicals, they are susceptible to fatigue cracks over extended periods of cyclic loading due to the challenging operational conditions. Their quality and efficiency directly affect the safe operation of the project. Therefore, a thorough and precise characterization approach towards pressure pipelines can proactively mitigate safety risks and yield substantial economic and societal benefits. At present, the current mainstream 2D ultrasound imaging technology faces challenges in fully visualizing the internal defects and topography of pressure pipelines. Reverse time migration (RTM), widely employed in geophysical exploration, has the capability to visualize intricate geological structures. In this paper, we introduced the RTM into the realm of ultrasonic non-destructive testing, and proposed a 3D ultrasonic RTM imaging method for internal defects and sensor settings of pressure pipelines. To accurately simulate the extrapolation of wave field in 3D pressure pipelines, we set the absorbing boundary and double free boundary in cylindrical coordinates. Subsequently, using the 3D ultrasonic RTM approach, we attained higher-precision 3D imaging of internal defects in the pressure pipelines through suppressing imaging artifacts. By comparing and analyzing the imaging results of different sensor settings, the design of the observation system is optimized to provide a basis for the imaging and interpretation of actual data. Both simulations and actual field data demonstrate that our approach delivers top-notch 3D imaging of pipeline defects (with an imaging range accuracy up to 97.85%). This method takes into consideration the complexities of multiple scattering and mode conversions occurring at the base of the defects as well as the optimal sensor settings.

Convolutional Neural-Network-Based Reverse-Time Migration with Multiple Reflections.

Reverse-time migration (RTM) has the advantage that it can handle steep dipping structures and offer high-resolution images of the complex subsurface. Nevertheless, there are some limitations to the chosen initial model, aperture illumination and computation efficiency. RTM has a strong dependency on the initial velocity model. The RTM result image will perform poorly if the input background velocity model is inaccurate. One solution is to apply least-squares reverse-time migration (LSRTM), which updates the reflectivity and suppresses artifacts through iterations. However, the output resolution still depends heavily on the input and accuracy of the velocity model, even more than for standard RTM. For the aperture limitation, RTM with multiple reflections (RTMM) is instrumental in improving the illumination but will generate crosstalks because of the interference between different orders of multiples. We proposed a method based on a convolutional neural network (CNN) that behaves like a filter applying the inverse of the Hessian. This approach can learn patterns representing the relation between the reflectivity obtained through RTMM and the true reflectivity obtained from velocity models through a residual U-Net with an identity mapping. Once trained, this neural network can be used to enhance the quality of RTMM images. Numerical experiments show that RTMM-CNN can recover major structures and thin layers with higher resolution and improved accuracy compared with the RTM-CNN method. Additionally, the proposed method demonstrates a significant degree of generalizability across diverse geology models, encompassing complex thin layers, salt bodies, folds, and faults. Moreover, The computational efficiency of the method is demonstrated by its lower computational cost compared with LSRTM.

In-Wall Imaging for the Reconstruction of Obstacles by Reverse Time Migration.

In this paper, the reverse time migration (RTM) method is applied to the single-frequency reconstruction of embedded obstacles in a wall to perform an introductory study for in-wall imaging. The aim is to determine the geometrical properties of an object embedded in a wall by the use of an information function provided via the RTM method. The method is based on the computation of that information function separately at each point on a reconstruction domain. It is defined as the correlation levels between the incident fields emitted from sources and the back-propagation of the scattered field. The problem is taken from a broader perspective in order to show and confirm the effectiveness of the method. For this purpose, numerical experiments within a fundamental scenario are determined in a particular order to perform an essential Monte Carlo simulation. The paper uses a comparative study to make an objective evaluation of the achievement level of the method in in-wall imaging. The results reveal that the method is at the applicable level of achievement.

Frequency-Domain Reverse-Time Migration with Analytic Green's Function for the Seismic Imaging of Shallow Water Column Structures in the Arctic Ocean.

Seismic oceanography can provide a two- or three-dimensional view of the water column thermocline structure at a vertical and horizontal resolution from the multi-channel seismic dataset. Several seismic imaging methods and techniques for seismic oceanography have been presented in previous research. In this study, we suggest a new formulation of the frequency-domain reverse-time migration method for seismic oceanography based on the analytic Green's function. For imaging thermocline structures in the water column from the seismic data, our proposed seismic reverse-time migration method uses the analytic Green's function for numerically calculating the forward- and backward-modeled wavefield rather than the wave propagation modeling in the conventional algorithm. The frequency-domain reverse-time migration with analytic Green's function does not require significant computational memory, resources, or a multifrontal direct solver to calculate the migration seismic images as like conventional reverse-time migration. The analytic Green's function in our reverse-time method makes it possible to provide a high-resolution seismic water column image with a meter-scale grid size, consisting of full-band frequency components for a modest cost and in a low-memory environment for computation. Our method was applied to multi-channel seismic data acquired in the Arctic Ocean and successfully constructed water column seismic images containing the oceanographic reflections caused by thermocline structures of the water mass. From the numerical test, we note that the oceanographic reflections of the migrated seismic images reflected the distribution of Arctic waters in a shallow depth and showed good correspondence with the anomalies of measured temperatures and calculated reflection coefficients from each XCDT profile. Our proposed method has been verified for field data application and accuracy of imaging performance.

An Ultrasonic Reverse Time Migration Imaging Method Based on Higher-Order Singular Value Decomposition.

An ultrasonic reverse time migration imaging method, based on high-order singular value decomposition, is proposed in the study to solve the problems of low signal-to-noise ratio (SNR) and excessive artifacts in defect ultrasonic detection imaging results of materials with high noise levels. In this method, based on the 3D structural properties of the ultrasonic full-matrix capture data, higher-order singular value decomposition is directly performed with the 3D data. The method overcomes the difficulty in selecting the number of singular values in the original singular value decomposition noise-reduction algorithm and realizes the one-step noise reduction processing of all the signals. Subsequently, the reverse time migration imaging is performed in the frequency domain, and high-quality acoustic images are obtained. The effects of the number of array elements, the center frequency of the excitation signal, and the number of defects on the denoising effect of the algorithm are investigated. It was experimentally demonstrated that the method could suppress the interference of noise signals and significantly improve the imaging SNR compared with total focusing method and the reverse time migration.

3-D Multi-Component Reverse Time Migration Method for Tunnel Seismic Data.

Migration imaging is a key step in tunnel seismic data processing. Due to the limitation of tunnel space, tunnel seismic data are small-quantity, multi-component, and have a small offset. Kirchhoff migration based on the ray theory is limited to the migration aperture and has low migration imaging accuracy. Kirchhoff migration can no longer meet the requirements of high-precision migration imaging. The reverse time migration (RTM) method is used to realize cross-correlation imaging by reverse-time recursion principle of the wave equation. The 3-D RTM method cannot only overcome the effect of small offset, but also realize multi-component data imaging, which is the most accurate migration method for tunnel seismic data. In this paper, we will study the 3-D RTM method for multi-component tunnel seismic data. Combined with the modeled data and the measured data, the imaging accuracy of the 3-D Kirchhoff migration and 3-D RTM is analyzed in detail. By comparing single-component and multi-component Kirchhoff migration and RTM profile, the advantages of the multi-component RTM method are summarized. Compared with the Kirchhoff migration method, the 3-D RTM method has the following advantages: (1) it can overcome the effect of small offset and expand the range of migration imaging; (2) multi-component data can be realized to improve the energy of anomalous interface; (3) it can make full use of multiple waves to realize migration imaging and improve the resolution of the anomalous interface. The modeled data and the measured data prove the advantages of the 3-D multi-component RTM method.

Locating Mine Microseismic Events in a 3D Velocity Model through the Gaussian Beam Reverse-Time Migration Technique.

Microseismic (MS) source location is a fundamental and critical task in mine MS monitoring. The traditional ray tracing-based location method can be easily affected by many factors, such as multi-ray path effects, waveform focusing and defocusing of wavefield propagation, and low picking precision of seismic phase arrival. By contrast, the Gaussian beam reverse-time migration (GBRTM) location method can effectively and correctly model the influences of multi-path effects and wavefield focusing and defocusing in complex 3D media, and it takes advantages of the maximum energy focusing point as the source location with the autocorrelation imaging condition, which drastically reduces the requirements of signal-to-noise ratio (SNR) and picking accuracy of P-wave arrival. The Gaussian beam technique has been successfully applied in locating natural earthquake events and hydraulic fracturing-induced MS events in one-dimensional (1D) or simple two-dimensional (2D) velocity models. The novelty of this study is that we attempted to introduce the GBRTM technique into a mine MS event location application and considered utilizing a high-resolution tomographic 3D velocity model for wavefield back propagation. Firstly, in the synthetic test, the GBRTM location results using the correct 2D velocity model and different homogeneous velocity models are compared to show the importance of velocity model accuracy. Then, it was applied and verified by eight location premeasured blasting events. The synthetic results show that the spectrum characteristics of the recorded blasting waveforms are more complicated than those generated by the ideal Ricker wavelet, which provides a pragmatic way to evaluate the effectiveness and robustness of the MS event location method. The GBRTM location method does not need a highly accurate picking of phase arrival, just a simple detection criterion that the first arrival waveform can meet the windowing requirements of wavefield back propagation, which is beneficial for highly accurate and automatic MS event location. The GBRTM location accuracy using an appropriate 3D velocity model is much higher than that of using a homogeneous or 1D velocity model, emphasizing that a high-resolution velocity model is very critical to the GBRTM location method. The average location error of the GBRTM location method for the eight blasting events is just 17.0 m, which is better than that of the ray tracing method using the same 3D velocity model (26.2 m).

Data-driven retrieval of primary plane-wave responses.

Seismic images provided by reverse time migration can be contaminated by artefacts associated with the migration of multiples. Multiples can corrupt seismic images, producing both false positives, that is by focusing energy at unphysical interfaces, and false negatives, that is by destructively interfering with primaries. Multiple prediction/primary synthesis methods are usually designed to operate on point source gathers and can therefore be computationally demanding when large problems are considered. A computationally attractive scheme that operates on plane-wave datasets is derived by adapting a data-driven point source gathers method, based on convolutions and cross-correlations of the reflection response with itself, to include plane-wave concepts. As a result, the presented algorithm allows fully data-driven synthesis of primary reflections associated with plane-wave source responses. Once primary plane-wave responses are estimated, they are used for multiple-free imaging via plane-wave reverse time migration. Numerical tests of increasing complexity demonstrate the potential of the proposed algorithm to produce multiple-free images from only a small number of plane-wave datasets.

Reverse time migration and genetic algorithms Combined for Reconstruction in Transluminal Shear Wave Elastography: An In Silico Case Study.

A new reconstruction approach that combines Reverse Time Migration (RTM) and Genetic Algorithms (GAs) is proposed for solving the inverse problem associated with transluminal shear wave elastography. The transurethral identification of the first thermal lesion generated by transrectal High Intensity Focused Ultrasound (HIFU) for the treatment of prostate cancer, was used to preliminarily test in silico the combined reconstruction method. The RTM method was optimised by comparing reconstruction images from several cross-correlation techniques, including a new proposed one, and different device configurations in terms of the number and arrangement of emitters and receivers of the conceptual transurethral probe. The best results were obtained for the new proposed cross-correlation method and a device configuration with 3 emitters and 32 receivers. The RTM reconstructions did not completely contour the shape of the HIFU lesion, however, as planned for the combined approach, the areas in the RTM images with high level of correlation were used to narrow down the search space in the GA-based technique. The GA-based technique was set to find the location of the HIFU lesion and the increment in stiffness and viscosity due to thermal damage. Overall, the combined approach achieves lower level of error in the reconstructed values, and in a shorter computational time, compared to the GA-based technique alone. The lowest errors were accomplished for the location of HIFU lesion, followed by the contrast ratio of stiffness between thermally treated tissue and non-treated normal tissue. The homologous ratio of viscosity obtained higher level of error. Further investigation considering diverse scenarios to be reconstructed and with experimental data is required to fully evaluate the feasibility of the combined approach.

Imaging of annulus-formation interface using reverse time migration based on ultrasonic pitch-catch measurements: Case studies from an experimental well and a field well.

Cased-hole logging using ultrasonic pitch-catch modality is a proven technique for cement bond evaluation in cased holes. However, complex measuring environments such as tool and casing eccentering makes it difficult to precisely separate and pick the third interface echoes from full ultrasonic Lamb waves, leading to ambiguous identification of annulus-formation interface. To overcome this problem, we propose an improved cased-hole reverse time migration approach for ultrasonic pitch-catch measurements to image the annulus-formation interface. The missing ultrasonic Lamb waveforms between far and near receivers due to insufficient spatial sampling are reconstructed based on the optimized theoretical phase velocity of zero-order anti-symmetric Lamb mode waves. Additionally, we apply the hybrid illumination imaging condition to mitigate the imaging noises around the true reflectors and sources. Data examples from a physical experimental well and a field well demonstrate that the proposed approach is an effective method for characterizing the annulus-formation interface without requiring precise knowledge of the velocity distribution in the region behind the casing. Furthermore, test on an experimental well has indicated that the method has the potential to detect the absence of cement in the annulus medium.

Ultrasonic imaging of delamination in thick CFRP laminates using an energy-compensation reverse time migration method.

In ultrasonic reflection method, the precision of defect detection in thick carbon fiber reinforced plastics (CFRP) is compromised by acoustic energy attenuation. An energy-compensation reverse time migration (ECRTM) method is proposed to identify multiple defects accurately. Forward and backward wavefields are formed using the finite element method within an anisotropic acoustic model based on the Christoffel equation and Bond transformation. To enhance the imaging quality of CFRP laminates, a novel cross-correlation imaging condition is introduced to compensate for energy dissipation caused by geometric diffusion and variations of the far-field radiation intensity at the emitter with the propagation direction. Employing ultrasonic detection technology with a multi-element array, numerical and experimental research on defect imaging was conducted, considering delamination with various sizes and positions in a multidirectional CFRP laminate. In comparison to other ultrasonic imaging methods, the near-surface artifacts in RTM images are mitigated by the far-field radiation directivity factor, while the deep information is enhanced by the geometric diffusion compensation factor in the ECRTM images. As a result, the precise position of delamination in CFRP laminates is achievable, demonstrating superior imaging capabilities, especially for deep delamination.

Detection of defects in highly attenuating materials using ultrasonic least-squares reverse time migration with preconditioned stochastic gradient descent.

Accurate detection and characterization of defects in high-density polyethylene (HDPE) pipe materials are very important in assessing the structural integrity of critical structures in the nuclear industry. One specific challenge here is the presence of the viscoelastic attenuation of this material, which can lead to resolution degradation and loss of detail in ultrasound imaging. In this work, an effective ultrasonic imaging technique using the least-squares reverse time migration with preconditioned stochastic gradient descent (LSRTM-PSGD) is developed to improve image quality. Compared with standard ultrasonic imaging methods which only consider the direct ray path of ultrasound, least-squares reverse time migration (LSRTM) is a powerful wave-equation-based approach and it has the ability to account for rapid spatial velocity variations and to utilize all wavefield information. The LSRTM is an inversion method, which iteratively updates the reflectivity model by minimizing the modeled data and measured data. The proposed LSRTM-PSGD combines the advantages of stochastic gradient descent (SGD) and adaptive learning rate. The SGD updates the parameter on each transmitter and the fluctuation of SGD can enable it to reach a better minimum, thus improving the imaging quality. Compared with the conventional LSRTM algorithm using a fixed step size, the proposed LSRTM-PSGD algorithm can use the adaptive moment estimation to calculate the adaptive learning rate for the parameter, thereby updating the parameter appropriately. The performance of the LSRTM-PSGD algorithm is tested with experimental data. The results show high-quality reconstructed images with good resolution for defect identification in HDPE pipe materials, especially for deep defects.

Imaging a defect in layered media with different shaped interfaces using reverse time migration without velocity model known a priori.

In this work, the highly accurate image of a defect in the layered media using a reverse time migration (RTM) is obtained without priori information of the interface geometry and acoustic velocity of the lower medium. The interface of layered media is reconstructed by RTM, and its profile is determined using the reconstructed image within the range of -6 to 0 dB. At the assumed acoustic velocity of the lower medium, the minimum variance of the possible position distribution of a defect is evaluated to be an acoustic velocity of the lower medium by processing the travel times of the defect scattered echoes. The velocity model of the layered media is reconstructed by the mapped interface and the calibrated acoustic velocity of the lower medium, and a defect in the layered media is imaged by RTM. The proposed method is verified by utilizing the silicone rubber-water layered media with horizontal, titled, and circular arc interfaces. The obtained results for the interface geometry, acoustic velocity of the lower medium, and location of defect are consistent with the actual values. Therefore, a defect in the layered media can be accurately located and imaged without the velocity model of layered media known a priori via the RTM method.

A reverse time migration-based multistep angular spectrum approach for ultrasonic imaging of specimens with irregular surfaces.

We develop a new ultrasonic imaging framework for non-destructive testing of an immersed specimen featuring an irregular top surface and demonstrate its capability of accurately depicting the lower surfaces of multiple damages hidden in the specimen. Central to the framework is a multistep angular spectrum approach (ASA), via which the forward propagation wavefields of wave sources and backward propagation wavefields of the received wave signals are calculated. Upon applying a zero-lag cross-correlation imaging condition of reverse time migration (RTM) to the obtained forward and backward wavefields, the image of the specimen with an irregular surface can be reconstructed, in which hidden damages, if any and regardless of quantity, are visualized. The effectiveness and accuracy of the framework are examined using numerical simulation, followed with experiment, in both of which multiple side-drilled holes, at different locations in aluminum blocks with various irregular surfaces, are characterized. Results have proven that multiple damages in a specimen with an irregular surface can be individually localized, and the lower surface of each damage can further be imaged accurately, thanks to the RTM-based algorithm in which multiple wave reflections from the specimen bottom are taken into wavefield extrapolation. The proposed imaging approach presents higher computational efficiency, compared to conventional RTM, and enhanced imaging contrast over prevailing total focusing methods.

Multi-mode reverse time migration damage imaging using ultrasonic guided waves.

The sensitivity of Lamb wave modes to a particular defect or instance of damage is dependent on various factors (e.g., the local strain energy density due to that wave mode). As a result, different modes will be more useful than others for damage detection and quantification, dependent on damage type and location. For example, prior work in the field has shown that out-of-plane modes may have a higher sensitivity than in-plane modes to surface defects in plates. The excitability of a certain data acquisition system and the corresponding resolution for damage imaging also varies with frequency. The aim of the present work was to develop a multi-mode damage imaging technique that enables characterization of damage type and size, general sensitivity to unknown damage types, higher resolution imaging, and detectability regardless of the data acquisition system used. A reverse-time migration (RTM) imaging algorithm was combined with a numerical simulator-the three-dimensional (3D) elastodynamic finite integration technique (EFIT)-to provide multi-mode damage imaging. The approach was applied to two simulated case studies featuring damaged isotropic plates. Sensitivities of damage type to wave mode were investigated by separating the A0 and S0 Lamb wave modes obtained from the resultant RTM wavefields.

All-optical extravascular laser-ultrasound and photoacoustic imaging of calcified atherosclerotic plaque in excised carotid artery.

Photoacoustic (PA) imaging may be advantageous as a safe, non-invasive imaging modality to image the carotid artery. However, calcification that accompanies atherosclerotic plaque is difficult to detect with PA due to the non-distinct optical absorption spectrum of hydroxyapatite. We propose reflection-mode all-optical laser-ultrasound (LUS) imaging to obtain high-resolution, non-contact, non-ionizing images of the carotid artery wall and calcification. All-optical LUS allows for flexible acquisition geometry and user-dependent data acquisition for high repeatability. We apply all-optical techniques to image an excised human carotid artery. Internal layers of the artery wall, enlargement of the vessel, and calcification are observed with higher resolution and reduced artifacts with nonconfocal LUS compared to confocal LUS. Validation with histology and X-ray computed tomography (CT) demonstrates the potential for LUS as a method for non-invasive imaging in the carotid artery.

Ultrasonic wavefield inversion and migration in complex heterogeneous structures: 2D numerical imaging and nondestructive testing experiments.

Delaminations, cracks and other defects in engineered structures often lie close to the theoretical resolution limit for ultrasonic waves. While ultrasonic waveform tomography has succeeded in detecting such features, recovery is difficult because it requires computationally expensive high-frequency numerical wave simulations and an accurate understanding of large-scale background variations of the engineered structure. Without such knowledge, small defects may be incorrectly imaged or go undetected altogether. To reduce computational cost and improve detection of small defects, a useful approach is to divide the waveform tomography procedure into two steps: first, a low-frequency model-building step aimed at recovering background structure, and second, a high-frequency imaging step targeting defects. The first is naturally formulated as waveform inversion for wavespeed parameters and the second as time reversal migration for reflectivity. Through synthetic test cases, we show that the two-step workflow appears more promising in most cases than a single-step inversion. In particular, we find that new workflow succeeds in the challenging scenario where the defect lies along preexisting layer interface in a composite bridge deck and in related experiments involving noisy data or inaccurate source parameters.

Defect detection around rebars in concrete using focused ultrasound and reverse time migration.

Experimental and numerical investigations have been performed to assess the feasibility of damage detection around rebars in concrete using focused ultrasound and a Reverse Time Migration (RTM) based subsurface imaging algorithm. Since concrete is heterogeneous, an unfocused ultrasonic field will be randomly scattered by the aggregates, thereby masking information about damage(s). A focused ultrasonic field, on the other hand, increases the possibility of detection of an anomaly due to enhanced amplitude of the incident field in the focal region. Further, the RTM based reconstruction using scattered focused field data is capable of creating clear images of the inspected region of interest. Since scattering of a focused field by a damaged rebar differs qualitatively from that of an undamaged rebar, distinct images of damaged and undamaged situations are obtained in the RTM generated images. This is demonstrated with both numerical and experimental investigations. The total scattered field, acquired on the surface of the concrete medium, is used as input for the RTM algorithm to generate the subsurface image that helps to identify the damage. The proposed technique, therefore, has some advantage since knowledge about the undamaged scenario for the concrete medium is not necessary to assess its integrity.