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Tunnel resistivity deep learning inversion method based on physics-driven and signal interpretability 基于物理驱动和信号可解释性的隧道电阻率深度学习反演方法
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2024-03-09 DOI: 10.1002/nsg.12294
Benchao Liu, Yuting Tang, Yongheng Zhang, Peng Jiang, Fengkai Zhang
Data-driven deep learning technology has a strong non-linear mapping ability and has good development potential in geophysical inversion problems. Traditional inversion techniques offer broad generality, but they can remain trapped in local minima, particularly for three-dimensional tunnelling resistivity inversion. In this work, we present an inversion methodology that combines traditional physics-driven and deep learning data-driven inversion approaches. To further support deep neural networks' dependability on unseen data, the interpretability of their working mechanism is explored. We execute migration learning based on small sample data after identifying the critical parameters that restrict the effectiveness of inversion by analysing the feature maps of various model data. We demonstrate, using both synthetic examples and field data, that the proposed method can improve the accuracy in detecting water-bearing anomalies (caves and faults), which are typically encountered during tunnel excavation.
数据驱动的深度学习技术具有很强的非线性绘图能力,在地球物理反演问题上具有很好的发展潜力。传统反演技术具有广泛的通用性,但可能会陷入局部最小值的困境,尤其是在三维隧道电阻率反演方面。在这项工作中,我们提出了一种结合传统物理驱动和深度学习数据驱动的反演方法。为了进一步支持深度神经网络对未知数据的依赖性,我们探索了其工作机制的可解释性。我们通过分析各种模型数据的特征图,确定了限制反演有效性的关键参数,然后基于小样本数据执行迁移学习。我们利用合成示例和实地数据证明,所提出的方法可以提高探测含水异常(洞穴和断层)的准确性,而这些异常通常是在隧道挖掘过程中遇到的。
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引用次数: 0
Studying GPR's direct and reflected waves 研究 GPR 的直接波和反射波
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2024-03-07 DOI: 10.1002/nsg.12292
Eleni Tokmaktsi, Nectaria Diamanti, Georgios Vargemezis, Antonios Giannopoulos, A. Peter Annan
As the transmitter and receiver (Tx and Rx, respectively) are located in close proximity during a typical ground-penetrating radar (GPR) survey, the powerful signal generated by the Tx and which is then recorded by the Rx at various time delays, can be saturated at early times (i.e., this is the direct wave (DW) signal reaching the Rx). This often causes the masking of shallow targets, complicating data interpretation. In this study, our aim is to examine the spatial distribution of the electromagnetic signals around the Tx, attempting to locate areas where the DW becomes minimum, whereas the signal strength from subsurface targets (i.e., reflected wave – RW) remains ideally unchanged. The position of these local minima in the DW signal could give rise to advantageous Tx–Rx configurations, where clear reflections from subsurface targets lying at shallow depths can be obtained with the least possible involvement of the DW. To perform such a study, we carried out static field measurements over a flat lying reflector as well as numerical simulations in a reflection, common-offset mode around a transmitting antenna. In the field, we also collected wide-angle reflection–refraction data to determine the GPR wave velocity in the uppermost layer. GPR signals were recorded by the Rx around the Tx in three concentric circles of various radii (i.e., varying the Tx/Rx separation), using a specific angular step and varying the Tx/Rx polarization each time. The synthetic data were produced using a three-dimensional finite-difference time-domain modelling tool. Field and numerically simulated data were analysed and compared to study the behaviour of both the DW and RW events around the Tx when changing the Tx/Rx distance, their respective angular position, as well as their relative polarization/orientation.
在典型的探地雷达(GPR)勘测过程中,由于发射器和接收器(分别为 Tx 和 Rx)距离很近,Tx 产生的强大信号在不同的时间延迟后被 Rx 记录,在早期可能会饱和(即到达 Rx 的直接波(DW)信号)。这往往会造成浅层目标的掩蔽,使数据解读变得复杂。在这项研究中,我们的目的是检查 Tx 周围电磁信号的空间分布,试图找出 DW 信号变为最小值的区域,而来自地下目标的信号强度(即反射波 - RW)在理想情况下保持不变。DW 信号中这些局部最小值的位置可能会产生有利的 Tx-Rx 配置,在这种配置下,可以获得来自浅层地下目标的清晰反射波,而 DW 的参与则尽可能少。为了进行这样的研究,我们对平躺的反射器进行了静态现场测量,并在发射天线周围以反射、共偏移模式进行了数值模拟。在现场,我们还收集了广角反射-折射数据,以确定最上层的 GPR 波速。GPR 信号由 Rx 围绕 Tx 以三个不同半径的同心圆(即改变 Tx/Rx 间距)记录,每次使用特定的角度步长并改变 Tx/Rx 极化。合成数据使用三维有限差分时域建模工具生成。对现场数据和数值模拟数据进行了分析和比较,以研究在改变 Tx/Rx 距离、各自的角度位置以及相对极化/方位时,Tx 周围的 DW 和 RW 事件的表现。
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引用次数: 0
Efficient and high‐resolution surface‐wave dispersive energy imaging using a proposed spatial smoothing propagation method 利用拟议的空间平滑传播方法实现高效、高分辨率面波色散能量成像
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2024-03-04 DOI: 10.1002/nsg.12291
Tao He, Suping Peng, Henggao Geng
Surface‐wave information from seismic data can be used for near‐surface analysis, static computation and noise suppression. The multichannel analysis of surface waves method is a useful approach for obtaining the shear wave velocity of the near surface; however, rapidly generating an image of dispersive energy in the presence of coherent noise is a challenge. In this study, we propose the imaging of the dispersive energy of the Rayleigh wave using a spatial smoothing propagation method. In this method, forward and backward spatial smoothing algorithms were used to restore the rank of the covariance matrix in strong coherent noise. Subsequently, an image of the dispersive energy was rapidly generated by the propagation method using a linear operation equivalent to the eigenvalue decomposition. The proposed method was evaluated using both synthetic and field data. The results showed that the method was easy to use and has higher resolution representation, efficiency and noise robustness compared with conventional methods.
地震数据中的面波信息可用于近地表分析、静力计算和噪声抑制。多道面波分析方法是获取近地表剪切波速度的有效方法;然而,在存在相干噪声的情况下快速生成色散能量图像是一项挑战。在本研究中,我们提出了利用空间平滑传播方法对雷利波的色散能量进行成像。在这种方法中,使用了前向和后向空间平滑算法来恢复强相干噪声中协方差矩阵的秩。随后,利用相当于特征值分解的线性运算,通过传播方法快速生成色散能量图像。利用合成数据和现场数据对所提出的方法进行了评估。结果表明,与传统方法相比,该方法易于使用,具有更高的分辨率、效率和噪声鲁棒性。
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引用次数: 0
ERT Data Assimilation to Characterize Aquifer Hydraulic Conductivity Heterogeneity through a Heat-tracing Experiment ERT 数据同化,通过热追踪实验确定含水层水力传导异质性的特征
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-12-22 DOI: 10.1002/nsg.12288
Benyamin Shariatinik, Erwan Gloaguen, Jasmin Raymond, Louis-Charles Boutin, Gabriel Fabien-Ouellet
Geothermal Energy Systems such as heat pump relying on aquifers uses renewable sources of energy that are accessible in urban areas. It is necessary to characterize the subsurface hydraulic properties prior to the installation of such systems. In this context, heat tracing experiment is a typical field test that can help with characterization of the subsurface. During a heat tracing experiment, monitoring with downhole temperature sensors, water-level pressure transducers and electrical resistivity tomography (ERT) can be used to help to characterize the hydrogeological properties. Previous monitoring tools have shortcomings such as low-resolution data and over-smoothing, thus they fail to reproduce the heterogeneity of hydrogeological properties. Ensemble Kalman filter (EnKF) is a promising tool that can overcome the over-smoothing problem to replicate the hydrogeological property heterogeneity. In this work, we proposed a new procedure to assimilate time-lapse cross-borehole ERT data into a numerical model of groundwater flow and heat transfer, where the ground water is extracted, and heated water is reinjected into an unconfined sandy-gravel aquifer. The finite element model (FEFLOW 7.3) of groundwater flow and heat transfer is integrated with petrophysical relationship and electrical forward modeling (Resipy) to estimate cross-borehole ERT measurements. Then, the estimated apparent resistivity is assimilated to update the hydraulic conductivity model using EnKF. The results of the application of the proposed approach to a experimental site located in Quebec City (Canada) demonstrate that the heterogeneity of K is correctly reproduce since the updated K model is reasonably consistent with the lithological log. In addition, the proposed approach was able to replicate the cross-borehole ERT field and temperature measurements. The comparison between prior and posterior distribution of K with slug test results shows that the EnKF made the final (assimilated) distribution of K move toward K values inferred with slug tests.
地热能源系统(如依靠含水层的热泵)使用的是城市地区可以利用的可再生能源。在安装此类系统之前,有必要确定地下水的水力特性。在这种情况下,热跟踪实验是一种典型的现场测试,可帮助确定地下水的特性。在热跟踪实验过程中,可使用井下温度传感器、水位压力传感器和电阻率层析成像(ERT)进行监测,以帮助确定水文地质特性的特征。以往的监测工具存在低分辨率数据和过度平滑等缺陷,因此无法再现水文地质特性的异质性。集合卡尔曼滤波器(EnKF)是一种很有前途的工具,它可以克服过度平滑问题,从而再现水文地质属性的异质性。在这项工作中,我们提出了一种新的程序,将延时跨钻孔 ERT 数据同化到地下水流和热传导的数值模型中。地下水流动和传热有限元模型(FEFLOW 7.3)与岩石物理关系和电正演模型(Resipy)相结合,估算跨钻孔 ERT 测量值。然后,利用 EnKF 同化估算的视电阻率,更新水力传导模型。在位于加拿大魁北克市的一个实验点应用该方法的结果表明,由于更新后的 K 模型与岩性记录相当一致,K 的异质性得到了正确再现。此外,所提出的方法还能够复制跨钻孔 ERT 场和温度测量结果。K 的先验分布和后验分布与岩浆测试结果的比较表明,EnKF 使 K 的最终(同化)分布趋向于岩浆测试推断的 K 值。
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引用次数: 0
Investigating soil layers with ground penetrating radar in the modern Yellow River Delta of China 利用地面穿透雷达对中国现代黄河三角洲的土壤层进行调查
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-12-16 DOI: 10.1002/nsg.12289
Ping WANG, Xinju LI, Xiangyu MIN, Shuo XU, Guangming ZHAO, Deqiang FAN
Soil layers affect the vertical movement of moisture and salt, eventually resulting in land cover and land use pattern changes. This study explored the ability of ground penetrating radar (GPR) to detect soil layers in the modern Yellow River Delta of China and assessed its accuracy. It was found that soil moisture and salt had a strong dampening effect on the electromagnetic wave signal which resulted in blurred GPR images of the soil profile below 1 m. The cultivated soil layers of different crop types such as rice, wheat, corn, and cotton were accurately identified in GPR images. To estimate an individual soil layer thickness, the propagation velocity of the electromagnetic wave was calculated using soil mass moisture content, and the propagation time was confirmed by comparing the GPR image with the amplitude-time plot of the soil profile. The estimated thickness was 1.02 times the thickness determined in the field and the average estimation error was 0.04 m, which was 24.09% of the soil layer thickness determined in the field. The second derivative value of envelope amplitude energy with time (SDEA) was used to describe the amplitude change in the soil layers. The SDEA has negative logarithmic and power function relationships with soil mass moisture content and electrical conductivity, respectively. The present results provide a reference database for future quantitative soil investigation in the sedimentary plain area using GPR.
土层会影响水分和盐分的垂直移动,最终导致土地覆盖和土地利用模式的变化。本研究探讨了地面穿透雷达(GPR)探测中国现代黄河三角洲土壤层的能力,并评估了其准确性。研究发现,土壤水分和盐分对电磁波信号有很强的阻尼作用,导致 1 米以下土壤剖面的 GPR 图像模糊不清。为了估算单个土层的厚度,利用土壤质量含水量计算了电磁波的传播速度,并通过比较 GPR 图像和土壤剖面的振幅-时间图确认了传播时间。估算厚度是实地测定厚度的 1.02 倍,平均估算误差为 0.04 米,是实地测定土层厚度的 24.09%。包络振幅能量随时间的二次导数值(SDEA)用于描述土层的振幅变化。SDEA 与土壤质量含水量和导电率分别存在负对数和幂函数关系。本研究结果为今后使用 GPR 对沉积平原地区的土壤进行定量调查提供了参考数据库。
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引用次数: 0
Foreword ‐ Special Section on Geophysics for Infrastructure Planning, Monitoring and BIM 前言--地球物理学用于基础设施规划、监测和 BIM 专节
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-12-01 DOI: 10.1002/nsg.12287
Alireza Malehmir Alireza, Arre Verweerdarre, Beatriz Benjumae Moreno
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引用次数: 0
Modelling and inferring fracture curvature from borehole GPR data: Case study from the Bedretto Laboratory, Switzerland 从井眼GPR数据建模和推断裂缝曲率:来自瑞士Bedretto实验室的案例研究
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-11-27 DOI: 10.1002/nsg.12286
Daniel Escallon, Alexis Shakas, Hansruedi Maurer
Fracture curvature has been observed from the millimetre to the kilometre scales. Nevertheless, characterizing curvature remains challenging due to data sparsity and geometric ambiguities. As a result, most numerical models often assume planar fractures to ease computations. To address this limitation, we present a novel approach for inferring fracture geometry from travel-time data of electromagnetic or seismic waves. Our model utilizes co-kriging interpolation of control points in a 3D surface mesh to simulate fracture curvature effectively, resulting in an unstructured triangular grid. We then refine the fracture surface into a structured grid with equidistant elements so that both small-scale heterogeneities and large-scale curvature can be modelled. To constrain the fracture geometry, we perform a deterministic travel-time inversion to optimally place these control points. We validate our methodology with synthetic data and address its limitations. Finally, we infer the geometry of a large (more than 200 m) fracture observed in single-hole ground-penetrating radar (GPR) field data. The fracture surface closely agrees with borehole televiewer observations and is also constrained far from the boreholes. Our modelling approach can be trivially adapted to multi-offset GPR or active seismic data.
裂缝曲率已被观察到从毫米到公里的尺度。然而,由于数据稀疏性和几何模糊性,曲率的表征仍然具有挑战性。因此,为了简化计算,大多数数值模型通常假设为平面裂缝。为了解决这一限制,我们提出了一种从电磁波或地震波的走时数据推断裂缝几何形状的新方法。我们的模型利用三维表面网格控制点的协同克里格插值来有效地模拟裂缝曲率,从而得到一个非结构化的三角形网格。然后,我们将裂缝表面细化为具有等距元素的结构化网格,以便可以对小尺度非均质性和大尺度曲率进行建模。为了约束裂缝的几何形状,我们进行了确定性的走时反演,以最佳地放置这些控制点。我们用合成数据验证了我们的方法,并解决了它的局限性。最后,我们对单孔探地雷达(GPR)现场数据观测到的一条大于200米的大裂缝的几何形状进行了推断。裂缝表面与井眼电视观测结果非常吻合,也受限于远离井眼。我们的建模方法可以很容易地适用于多偏移GPR或活动地震数据。
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引用次数: 0
Prediction of S-wave velocity models from surface waves using deep learning 利用深度学习从表面波预测s波速度模型
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-11-21 DOI: 10.1002/nsg.12284
Sangin Cho, Sukjoon Pyun, Byunghoon Choi, Ganghoon Lee, Seonghyung Jang, Yunseok Choi
Surface wave (SW) methods extract dispersion properties of wavefields propagating through a seismic array (1D or 2D). This is achieved by analysing the phase velocity versus frequency (or wavelength) data. Afterwards, an inversion process is performed to construct near-surface S-wave velocity models. Among the SW methods, multichannel analysis of SWs (MASW) is commonly used for engineering applications, analysing dispersion characteristics by generating a dispersion image. However, classical MASW depends on the manual picking of dispersion curves, which can lead to subjective outcomes and require time and effort to obtain precise results. To avoid these pitfalls, many studies, including deep-learning techniques, have focused on automating the process. Similarly, we propose a deep-learning-based algorithm that estimates the S-wave velocity directly from the dispersion image of SWs. This algorithm consists of a convolutional neural network (CNN) designed to directly yield S-wave velocity profiles and a fully connected network (multi-layer perceptron) added to regularize predictions. Unlike typical SW techniques, the proposed approach does not incorporate prior information such as layer count and thickness. To ensure successful training, we modified the loss function to exploit the normalized mean squared error. The training dataset was generated by modelling synthetic shot gathers and transforming them into dispersion images for various 1D stratified velocity structures. After a sample is fed to the CNN network for inversion, the inversion network's output subsequently goes through an additional simple neural network (NN) to regularize the predicted S-wave velocity model (which is the post-processing step). The combined usage of deep-learning-based SW inversion with NN-based post-processing was assessed using test data. The proposed algorithm achieved an average relative error of approximately 7.49% in predicting the S-wave velocity and was successfully applied to the field data. Additionally, we discuss its performance on noisy data as well as its applicability to out-of-training data. Numerical examples demonstrated that the proposed method is robust to noise, whereas it requires additional training to handle data beyond the distribution of the training data.
面波(SW)方法提取通过地震阵列(一维或二维)传播的波场色散特性。这是通过分析相速度与频率(或波长)数据来实现的。然后进行反演,建立近地表横波速度模型。在声波分析方法中,多通道声波分析(MASW)通常用于工程应用,通过生成色散图像来分析色散特性。然而,经典的MASW依赖于人工挑选色散曲线,这可能导致主观结果,并且需要时间和精力来获得精确的结果。为了避免这些陷阱,包括深度学习技术在内的许多研究都将重点放在了自动化过程上。同样,我们提出了一种基于深度学习的算法,该算法直接从SWs的色散图像中估计s波速度。该算法由一个卷积神经网络(CNN)和一个全连接网络(多层感知器)组成,该网络旨在直接产生s波速度剖面,并添加了一个正则化预测。与典型的软件技术不同,所提出的方法不包含诸如层数和厚度之类的先验信息。为了确保训练成功,我们修改了损失函数来利用归一化均方误差。训练数据集是通过对合成射击集进行建模,并将其转换为各种一维分层速度结构的离散图像而生成的。将样本馈送到CNN网络进行反演后,反演网络的输出随后通过一个附加的简单神经网络(NN)对预测的横波速度模型进行正则化(这是后处理步骤)。使用测试数据评估了基于深度学习的SW反演与基于神经网络的后处理的结合使用。该算法预测横波速度的平均相对误差约为7.49%,并成功应用于现场数据。此外,我们还讨论了它在噪声数据上的性能以及对非训练数据的适用性。数值算例表明,该方法对噪声具有较强的鲁棒性,但在处理训练数据分布之外的数据时需要进行额外的训练。
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引用次数: 0
Electrical resistivity tomography through reinforced concrete floor 钢筋混凝土地面电阻率层析成像
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-11-20 DOI: 10.1002/nsg.12285
Lichun Yang, Dikun Yang, Quan Yuan
The electrical resistivity tomography (ERT) method is often challenged by the presence of reinforced concrete (RC) in urban and industrial environments, because the embedded metallic wire mesh can severely distort the distribution of subsurface currents. We investigate one typical scenario in real applications, in which an RC floor overlays the natural topsoil or rock. Our synthetic forward simulations show that the embedded wire mesh behaves like a local good conductor in data of small source-receiver separations and acts like an equal-potential object that keeps the potential from decaying at large source-receiver separations. Routine ERT inversions that ignore the RC cannot work properly because the thin and highly conductive wire mesh may be manifested as large uninterpretable low-resistivity anomalies in the imaging results. Two remedies are adopted to improve the ERT resolution in such cases. First, we find a top layer with high conductivity in our model to adequately represent the wire mesh; then, we initiate the inversion with the top-layer model as the starting and reference model. This warm-start approach overcomes the difficulty of recovering the large conductivity contrast between metallic objects and regular earth materials. Second, underground electrodes are added to the survey array, so more information from depth can be obtained to fight against the dominance of current channelling in the wire mesh. Finally, our strategies are used to invert a real ERT dataset from an indoor manufacturing plant, where RC covers the entire floor of the building and electrodes are in contact with the soil through open holes in the floor. Our simulation and field data inversion verify our findings and demonstrate the effectiveness of our solutions in improving the resolution of ERT when the survey is carried out over RC floor in urban and industrial environments.
电阻率层析成像(ERT)方法经常受到城市和工业环境中钢筋混凝土(RC)存在的挑战,因为嵌入的金属丝网会严重扭曲地下电流的分布。我们研究了实际应用中的一个典型场景,即RC地板覆盖在天然表土或岩石上。我们的综合正演模拟表明,在小的源接收机距离数据中,嵌入式金属丝网表现得像一个局部的良好导体,而在大的源接收机距离数据中,它表现得像一个等电位物体,防止电位衰减。忽略RC的常规ERT反演无法正常工作,因为细而高导电性的钢丝网可能在成像结果中表现为无法解释的大的低电阻率异常。在这种情况下,采用两种补救措施来改善ERT决议。首先,我们在模型中找到一个具有高导电性的顶层,以充分代表金属丝网;然后,以顶层模型作为起始模型和参考模型启动反演。这种热启动方法克服了恢复金属物体和常规地球材料之间大电导率对比的困难。其次,将地下电极添加到测量阵列中,因此可以从深度获得更多信息,以对抗导线网中电流通道的主导地位。最后,我们的策略用于反演来自室内制造工厂的真实ERT数据集,其中RC覆盖了建筑物的整个楼层,电极通过地板上的开孔与土壤接触。我们的模拟和现场数据反演验证了我们的发现,并证明了我们的解决方案在提高ERT分辨率方面的有效性,当在城市和工业环境中对RC地板进行调查时。
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引用次数: 0
High-frequency wide-angle reflection and refraction method for structural engineering ground-penetrating radar surveys 结构工程探地雷达测量中的高频广角反射和折射法
IF 1.6 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-11-20 DOI: 10.1002/nsg.12277
Davide Campo
Electromagnetic wave velocity in ground-penetrating radar (GPR) constant offset data can be estimated via the diffraction hyperbola fitting method. This method is applicable when radargrams contain diffraction events (hyperbolic patterns) caused by scatters in the host smaller or equal to the dominant wavelength. An alternative method for velocity estimation, if no intrusive information is available for a direct correlation, requires the collection of multi-offset data. The method is quite common for broad geophysical applications; however, it seems not to be fully utilized for engineering applications, such as slabs/walls where thickness estimation and depth of the embedded features are critical requirements for structural assessments. This method would also overcome the limitations in velocity calibration in environments with no hyperbolic signal signatures. The aim of this study is to explore multi-offset high-frequency GPR applications, specifically the wide-angle reflection and refraction method, for structural engineering, to understand whether it is feasible, possible limitations, and advantages. Numerical models reproducing reinforced concrete elements and a cavity wall were analysed to understand the wave behaviour and predict the response prior to testing on real cases. The main purpose is to explore how reinforcing bars can affect the velocity spectra derived from semblance analysis and what the response would be in a case of multi-layered structure with increasing velocity with depth (cavity wall). The comparison with real cases showed that, despite some intrinsic limitations, high-frequency multi-offset approach could be part of standard workflow for all those surveys where no other velocity estimation method is feasible.
利用衍射双曲线拟合方法可以估计出探地雷达等偏置数据中的电磁波速度。这种方法适用于当雷达图中包含由小于或等于主波长的散射引起的衍射事件(双曲模式)时。如果没有直接相关的干扰信息,另一种速度估计方法需要收集多偏移量数据。这种方法在广泛的地球物理应用中是很常见的;然而,它似乎没有完全用于工程应用,例如板/墙,其中嵌入特征的厚度估算和深度是结构评估的关键要求。该方法还克服了在无双曲信号特征环境下速度标定的局限性。本研究的目的是探索多偏移高频探地雷达在结构工程中的应用,特别是广角反射和折射方法,以了解其是否可行,可能存在的局限性和优势。模拟钢筋混凝土构件和空腔墙的数值模型进行了分析,以便在实际情况下进行测试之前了解波浪行为并预测响应。主要目的是探讨钢筋如何影响由相似分析得出的速度谱,以及在多层结构中速度随深度增加(空腔壁)的响应。与实际案例的比较表明,尽管存在一些固有的局限性,高频多偏移量方法可以作为所有测量的标准工作流程的一部分,而其他速度估计方法是不可行的。
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引用次数: 0
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Near Surface Geophysics
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