Puy Ayarza, Mariano Yenes, Yolanda Sánchez Sánchez, Imma Palomeras, José R. Martínez Catalán, Enrique Gil-Arranz, Juan Gómez Barreiro
The renaissance botanical garden of ‘El Bosque’ in Béjar (Salamanca, Spain) presents a pond bounded by a dam in its western part. The latter is formed by two masonry walls interconnected by buttresses. Cubic spaces in between are filled with a variable grain-size material (silty sand) that allows limited water flow. In recent years the southern part of the dam has experienced localized and random subsidence that jeopardizes the entrance to part of the garden. To regain access, a proper and reliable diagnosis of the origin, magnitude and relevance of the subsidence must be made. In this regard, we have undertaken a microgravity survey in the dam area to identify places with an anomalous distribution of the filling material in order to foresee further sinking or potential collapsing areas. The precise positioning (2 mm resolution) and accurate terrain correction needed in this kind of high-resolution gravity surveys (points every 1.5 m) was achieved by creating a detailed Digital Terrain Model (cm resolution) with a remotely piloted aircraft. In addition, we performed three electric resistivity tomography (ERT) profiles at different levels of the garden: i) on the dam itself, ii) right on the foot of the dam and parallel to it (5 m below and ∼17m to the W), and iii) a bit farther, but also parallel to the dam (8 m below and ∼27m to the W). The ERT profiles identified high conductivity in water-saturated areas and determined the paths that rainfall and pond's seepage water follow in the dam and its underground, formed by granites. The geophysical studies were paired with geotechnical analyses of the sunk materials. The study concluded that the thinnest fraction of the dam's filling material (i.e., silts) is being washed away, leaving behind sand with less density and stability, susceptible to collapse. Thus, the observed sinking is related to soil piping, i.e. to soil internal erosion and compaction issues that force the soil material to re-adjust geometrically and volumetrically.
{"title":"Assessing the dam's stability of the pond at the ‘El Bosque’ renaissance garden (Béjar, Spain)","authors":"Puy Ayarza, Mariano Yenes, Yolanda Sánchez Sánchez, Imma Palomeras, José R. Martínez Catalán, Enrique Gil-Arranz, Juan Gómez Barreiro","doi":"10.1002/nsg.12283","DOIUrl":"https://doi.org/10.1002/nsg.12283","url":null,"abstract":"The renaissance botanical garden of ‘El Bosque’ in Béjar (Salamanca, Spain) presents a pond bounded by a dam in its western part. The latter is formed by two masonry walls interconnected by buttresses. Cubic spaces in between are filled with a variable grain-size material (silty sand) that allows limited water flow. In recent years the southern part of the dam has experienced localized and random subsidence that jeopardizes the entrance to part of the garden. To regain access, a proper and reliable diagnosis of the origin, magnitude and relevance of the subsidence must be made. In this regard, we have undertaken a microgravity survey in the dam area to identify places with an anomalous distribution of the filling material in order to foresee further sinking or potential collapsing areas. The precise positioning (2 mm resolution) and accurate terrain correction needed in this kind of high-resolution gravity surveys (points every 1.5 m) was achieved by creating a detailed Digital Terrain Model (cm resolution) with a remotely piloted aircraft. In addition, we performed three electric resistivity tomography (ERT) profiles at different levels of the garden: i) on the dam itself, ii) right on the foot of the dam and parallel to it (5 m below and ∼17m to the W), and iii) a bit farther, but also parallel to the dam (8 m below and ∼27m to the W). The ERT profiles identified high conductivity in water-saturated areas and determined the paths that rainfall and pond's seepage water follow in the dam and its underground, formed by granites. The geophysical studies were paired with geotechnical analyses of the sunk materials. The study concluded that the thinnest fraction of the dam's filling material (i.e., silts) is being washed away, leaving behind sand with less density and stability, susceptible to collapse. Thus, the observed sinking is related to soil piping, i.e. to soil internal erosion and compaction issues that force the soil material to re-adjust geometrically and volumetrically.","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"22 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138531360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sam Stadler, Stephan Schennen, Thomas Hiller, Jan Igel
Abstract Ground‐penetrating radar (GPR) is an effective tool for detecting landmines and improvised explosive devices (IEDs), and its performance is strongly influenced by subsurface properties as well as the characteristics of the target. To complement or replace labour‐intensive experiments on test sites, cost‐efficient electromagnetic wave propagation simulations using the Finite‐Difference Time‐Domain (FDTD) method are being increasingly used. However, to obtain realistic synthetic data, accurate modelling of signal alteration caused by dispersion, scattering of soil material, target contrast, shape, and inner setup, as well as the coupling effects of the antenna to the ground is required. In this study, we present a detailed 3D model of a shielded GPR antenna applied to various scenarios containing metallic and non‐metallic targets buried in different soils. The frequency‐dependent intrinsic material properties of soil samples were measured with the coaxial transmission‐line technique, while a discrete random media was used to implement the heterogeneity of a gravel based on its grain‐size distribution. Our simulations show very good agreement with experimental validation data collected under controlled conditions. We accurately reproduce the amplitude and frequency content, phase of target signals, subsurface's background noise, antenna crosstalk and its interference with target signals, and the effect of antenna elevation. The approach allows for systematic investigation of the effects of soil, target, and sensor properties on detection performance, providing insight into novel and complex GPR scenarios and the potential for a wide range of simulation possibilities for demining with GPR. These investigations have the potential to improve the safety and effectiveness of landmine and IED detection in the future, such as building a database for training deminers or developing automatic signal pattern recognition algorithms. This article is protected by copyright. All rights reserved
{"title":"Realistic simulation of GPR for landmine and IED detection including antenna models, soil dispersion and heterogeneity","authors":"Sam Stadler, Stephan Schennen, Thomas Hiller, Jan Igel","doi":"10.1002/nsg.12282","DOIUrl":"https://doi.org/10.1002/nsg.12282","url":null,"abstract":"Abstract Ground‐penetrating radar (GPR) is an effective tool for detecting landmines and improvised explosive devices (IEDs), and its performance is strongly influenced by subsurface properties as well as the characteristics of the target. To complement or replace labour‐intensive experiments on test sites, cost‐efficient electromagnetic wave propagation simulations using the Finite‐Difference Time‐Domain (FDTD) method are being increasingly used. However, to obtain realistic synthetic data, accurate modelling of signal alteration caused by dispersion, scattering of soil material, target contrast, shape, and inner setup, as well as the coupling effects of the antenna to the ground is required. In this study, we present a detailed 3D model of a shielded GPR antenna applied to various scenarios containing metallic and non‐metallic targets buried in different soils. The frequency‐dependent intrinsic material properties of soil samples were measured with the coaxial transmission‐line technique, while a discrete random media was used to implement the heterogeneity of a gravel based on its grain‐size distribution. Our simulations show very good agreement with experimental validation data collected under controlled conditions. We accurately reproduce the amplitude and frequency content, phase of target signals, subsurface's background noise, antenna crosstalk and its interference with target signals, and the effect of antenna elevation. The approach allows for systematic investigation of the effects of soil, target, and sensor properties on detection performance, providing insight into novel and complex GPR scenarios and the potential for a wide range of simulation possibilities for demining with GPR. These investigations have the potential to improve the safety and effectiveness of landmine and IED detection in the future, such as building a database for training deminers or developing automatic signal pattern recognition algorithms. This article is protected by copyright. All rights reserved","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"2009 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135636254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Timely and accurate detection of water pipe leakage is critical to preventing the loss of freshwater and predicting potential hazards induced by the change in underground water conditions, thereby developing mitigation strategies to improve the resilience of pipeline infrastructure. Ground Penetrating Radar (GPR) has been widely applied to investigating ground conditions and detecting pipe leakage. However, due to uncertainties of complex underground environments and time‐lapse change, a proper interpretation of GPR data has been a challenging task. This paper aims to leverage hydromechanical (HM) modelling to predict electromagnetic (EM) responses of water leakage detection in diverse leakage cases. A high‐fidelity 3D digital model of an actual pipeline network, hosting pipes with various sizes and materials, was reconstructed to represent the complex geometry and various mediums. The interoperability between the digital model and the numerical models utilised in HM and EM simulations was improved to better capture the irregular pipelines. Based on Kriging interpolation and the volumetric Complex Refractive Index Model (CRIM), a linking technique was employed to replicate material heterogeneity caused by water intrusion. Thus, a framework was developed to accommodate the interoperability among digital modelling, HM modelling, and Finite‐Difference Time‐Domain (FDTD) forward modelling. Moreover, sensitivity studies were conducted to evaluate the influences of different time stages, leak positions, and pipe types on GPR responses. In GPR B‐scans, the presence of hyperbolic motion and horizontal reflections serve as indicators to estimate the location and scale of water leakage. Specifically, a downward‐shifting hyperbola indicates that the pipeline is submerged by leaked water, while the emergence of horizontal reflection is linked to the wetting front of saturated areas. The developed framework can be expanded for complicated applications, such as unknown locations and unforeseen failure modes of pipelines. It will increase the efficiency and accuracy of traditional interpretations of GPR‐based water leakage detection and thus enable automated interpretations by data‐driven methods. This article is protected by copyright. All rights reserved
{"title":"A Framework for GPR‐based Water Leakage Detection by Integrating Hydromechanical Modelling into Electromagnetic Modelling","authors":"Huamei Zhu, Feng Xiao, Yimin Zhou, Wallace Wai Lok Lai, Qianbing Zhang","doi":"10.1002/nsg.12281","DOIUrl":"https://doi.org/10.1002/nsg.12281","url":null,"abstract":"Abstract Timely and accurate detection of water pipe leakage is critical to preventing the loss of freshwater and predicting potential hazards induced by the change in underground water conditions, thereby developing mitigation strategies to improve the resilience of pipeline infrastructure. Ground Penetrating Radar (GPR) has been widely applied to investigating ground conditions and detecting pipe leakage. However, due to uncertainties of complex underground environments and time‐lapse change, a proper interpretation of GPR data has been a challenging task. This paper aims to leverage hydromechanical (HM) modelling to predict electromagnetic (EM) responses of water leakage detection in diverse leakage cases. A high‐fidelity 3D digital model of an actual pipeline network, hosting pipes with various sizes and materials, was reconstructed to represent the complex geometry and various mediums. The interoperability between the digital model and the numerical models utilised in HM and EM simulations was improved to better capture the irregular pipelines. Based on Kriging interpolation and the volumetric Complex Refractive Index Model (CRIM), a linking technique was employed to replicate material heterogeneity caused by water intrusion. Thus, a framework was developed to accommodate the interoperability among digital modelling, HM modelling, and Finite‐Difference Time‐Domain (FDTD) forward modelling. Moreover, sensitivity studies were conducted to evaluate the influences of different time stages, leak positions, and pipe types on GPR responses. In GPR B‐scans, the presence of hyperbolic motion and horizontal reflections serve as indicators to estimate the location and scale of water leakage. Specifically, a downward‐shifting hyperbola indicates that the pipeline is submerged by leaked water, while the emergence of horizontal reflection is linked to the wetting front of saturated areas. The developed framework can be expanded for complicated applications, such as unknown locations and unforeseen failure modes of pipelines. It will increase the efficiency and accuracy of traditional interpretations of GPR‐based water leakage detection and thus enable automated interpretations by data‐driven methods. This article is protected by copyright. All rights reserved","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jianyu Ling, Rongyi Qian, Jun Zhang, Zhenning Ma, Xu Liu
Abstract Determining of ground‐penetrating radar (GPR) velocity has always been a critical problem. The GPR velocity estimation method based on common midpoint (CMP) data has been widely used because of its simplicity. However, we found that in sediment investigation and soil assessment, transversal heterogeneity is universal, which violates the basic assumption of velocity estimation through CMP data. Due to the rapid change of underground media and the limitation of the scope of some surveying areas, the CMP survey line will inevitably be selected in the area where the velocity changes laterally, making it difficult to obtain accurate velocity. To address this problem, we propose a velocity correction method. First, we determined the characteristics of CMP data and the corresponding velocity spectra acquired in transversely heterogeneous media through numerical simulations. Subsequently, we found that the simulated CMP data could determine the location of changes in the underground medium and that the velocity obtained from the semblance analysis could be corrected according to the location where the medium changes laterally. We then used models wherein the thickness, relative permittivity, and proportion of abnormal parts varied independently or simultaneously to verify the proposed velocity correction method. The results show that our method can control the GPR velocity error within 3.44% and the precision is about 0.002 m/ns. Finally, we conducted a sediment investigation experiment on a channel bar in the lower reaches of the Yarlung Zangbo River. We determined the interface at which the sediment changed transversely and obtained the corresponding electromagnetic (EM) velocity using the proposed method. This study provides a reliable method for determining the GPR velocity in transversal heterogeneous media, which is of great significance for various practical applications. This article is protected by copyright. All rights reserved
{"title":"GPR velocity correction method in transversely heterogeneous media based on CMP data","authors":"Jianyu Ling, Rongyi Qian, Jun Zhang, Zhenning Ma, Xu Liu","doi":"10.1002/nsg.12278","DOIUrl":"https://doi.org/10.1002/nsg.12278","url":null,"abstract":"Abstract Determining of ground‐penetrating radar (GPR) velocity has always been a critical problem. The GPR velocity estimation method based on common midpoint (CMP) data has been widely used because of its simplicity. However, we found that in sediment investigation and soil assessment, transversal heterogeneity is universal, which violates the basic assumption of velocity estimation through CMP data. Due to the rapid change of underground media and the limitation of the scope of some surveying areas, the CMP survey line will inevitably be selected in the area where the velocity changes laterally, making it difficult to obtain accurate velocity. To address this problem, we propose a velocity correction method. First, we determined the characteristics of CMP data and the corresponding velocity spectra acquired in transversely heterogeneous media through numerical simulations. Subsequently, we found that the simulated CMP data could determine the location of changes in the underground medium and that the velocity obtained from the semblance analysis could be corrected according to the location where the medium changes laterally. We then used models wherein the thickness, relative permittivity, and proportion of abnormal parts varied independently or simultaneously to verify the proposed velocity correction method. The results show that our method can control the GPR velocity error within 3.44% and the precision is about 0.002 m/ns. Finally, we conducted a sediment investigation experiment on a channel bar in the lower reaches of the Yarlung Zangbo River. We determined the interface at which the sediment changed transversely and obtained the corresponding electromagnetic (EM) velocity using the proposed method. This study provides a reliable method for determining the GPR velocity in transversal heterogeneous media, which is of great significance for various practical applications. This article is protected by copyright. All rights reserved","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"1 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136157069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Numerical modelling of Ground Penetrating Radar (GPR) has been widely used for predicting and assessing its performance. Since the transmitter and the receiver are the most essential components of a GPR system, an accurate representation of them should be included in a model. Simulating a real system is particularly challenging, especially when it comes to commercial GPR systems. A three‐dimensional model based on a 2000 MHz “palm” antenna from Geophysical Survey Systems, Inc. (GSSI) is presented in this paper. The geometric features of the transducers were modelled via visual inspection while their unknown dielectric properties were estimated using global optimisers in order to minimise the differences between real and synthetic measurements. In particular, the antenna was calibrated in free space and on top of a metal plate. Subsequently, the resulting model was successfully tested in various case studies to assess its performance. Models of two units of the same transducer were developed, showing that units of the same system in general are not identical. The results, support the premise that global optimisers can be used to provide information on key aspects of the dielectric structure of the transducer and allow us to accurately model its behaviour in various environments. This article is protected by copyright. All rights reserved
{"title":"Developing a Realistic Numerical Equivalent of a GPR Antenna Transducer Using Global Optimisers","authors":"Ourania Patsia, Antonios Giannopoulos, Iraklis Giannakis","doi":"10.1002/nsg.12280","DOIUrl":"https://doi.org/10.1002/nsg.12280","url":null,"abstract":"Abstract Numerical modelling of Ground Penetrating Radar (GPR) has been widely used for predicting and assessing its performance. Since the transmitter and the receiver are the most essential components of a GPR system, an accurate representation of them should be included in a model. Simulating a real system is particularly challenging, especially when it comes to commercial GPR systems. A three‐dimensional model based on a 2000 MHz “palm” antenna from Geophysical Survey Systems, Inc. (GSSI) is presented in this paper. The geometric features of the transducers were modelled via visual inspection while their unknown dielectric properties were estimated using global optimisers in order to minimise the differences between real and synthetic measurements. In particular, the antenna was calibrated in free space and on top of a metal plate. Subsequently, the resulting model was successfully tested in various case studies to assess its performance. Models of two units of the same transducer were developed, showing that units of the same system in general are not identical. The results, support the premise that global optimisers can be used to provide information on key aspects of the dielectric structure of the transducer and allow us to accurately model its behaviour in various environments. This article is protected by copyright. All rights reserved","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"94 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135218420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matthew John Couchman, Brian Barrett, Asger Eriksen
Abstract Ground penetrating radar (GPR) is a commonly used tool for railway trackbed inspection due to its ability to collect information about subsurface materials at high resolution and high speed. Although GPR recording systems allow for the collection of vast quantities of data (hundreds of kilometres per day), accurate ground truth information is difficult to obtain. Models of trackbed can be used to generate synthetic radargrams to provide a better understanding and predictability of GPR responses to a wide range of trackbed conditions. In this research, we produced models of ballast using randomly shaped 3D particles, with a range of particle size distributions to represent various stages of ballast breakdown. Additionally, void spaces are partially filled with a constant dielectric material to represent ballast contamination. We used gprMax to simulate the GPR response for a 2 GHz horn antenna over the trackbed models. These simulations resulted in radargrams that are visually indistinct from real recorded data in known conditions. These radargrams, along with their formative models, have provided valuable insights into how variations in trackbed conditions can impact GPR data.
{"title":"Synthetic modelling of railway trackbed for improved understanding of ground penetrating radar responses due to varying conditions","authors":"Matthew John Couchman, Brian Barrett, Asger Eriksen","doi":"10.1002/nsg.12272","DOIUrl":"https://doi.org/10.1002/nsg.12272","url":null,"abstract":"Abstract Ground penetrating radar (GPR) is a commonly used tool for railway trackbed inspection due to its ability to collect information about subsurface materials at high resolution and high speed. Although GPR recording systems allow for the collection of vast quantities of data (hundreds of kilometres per day), accurate ground truth information is difficult to obtain. Models of trackbed can be used to generate synthetic radargrams to provide a better understanding and predictability of GPR responses to a wide range of trackbed conditions. In this research, we produced models of ballast using randomly shaped 3D particles, with a range of particle size distributions to represent various stages of ballast breakdown. Additionally, void spaces are partially filled with a constant dielectric material to represent ballast contamination. We used gprMax to simulate the GPR response for a 2 GHz horn antenna over the trackbed models. These simulations resulted in radargrams that are visually indistinct from real recorded data in known conditions. These radargrams, along with their formative models, have provided valuable insights into how variations in trackbed conditions can impact GPR data.","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135944300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Ground penetrating radar (GPR) technology is widely used in tunnel engineering detection. however, various factors, such as environmental interference and low signal‐to‐noise ratio characteristics of the echo data, limit the detection accuracy. A noise and interference suppression algorithm based on improved singular value decomposition is proposed in this paper. Compared with traditional filtering methods, the proposed method has the advantages of thorough denoising, no clutter, efficient improvement of profile resolution, and less dependence on parameters. The main features of the proposed algorithm are as follows: (1) Given the global characteristics of the noise disturbance on the signal space, the minimum mean square error (MMSE) estimation is employed to approximate the effective signal, introducing the correction factor to suppress the larger singular value from the noise output in the reconstructing process of the effective signal subspace, and to eliminate the strong direct wave interference to avoid producing false signals. (2) A positive difference sequence search algorithm (PDS) based on rank order variance, as well as the method of selecting correction factors are proposed to improve the processing accuracy. In order to verify the design, the tunnel lining simulation model and the actual tunnel lining detection data are used. The results show good performance for noise and interference suppression, providing technical support for improving GPR data quality and tunnel detection accuracy. This article is protected by copyright. All rights reserved
{"title":"Noise reduction algorithm of gpr data based on mmse‐pds","authors":"Dejun Ma, Meng Fan, Xianlei Xu, Baode Fan","doi":"10.1002/nsg.12279","DOIUrl":"https://doi.org/10.1002/nsg.12279","url":null,"abstract":"Abstract Ground penetrating radar (GPR) technology is widely used in tunnel engineering detection. however, various factors, such as environmental interference and low signal‐to‐noise ratio characteristics of the echo data, limit the detection accuracy. A noise and interference suppression algorithm based on improved singular value decomposition is proposed in this paper. Compared with traditional filtering methods, the proposed method has the advantages of thorough denoising, no clutter, efficient improvement of profile resolution, and less dependence on parameters. The main features of the proposed algorithm are as follows: (1) Given the global characteristics of the noise disturbance on the signal space, the minimum mean square error (MMSE) estimation is employed to approximate the effective signal, introducing the correction factor to suppress the larger singular value from the noise output in the reconstructing process of the effective signal subspace, and to eliminate the strong direct wave interference to avoid producing false signals. (2) A positive difference sequence search algorithm (PDS) based on rank order variance, as well as the method of selecting correction factors are proposed to improve the processing accuracy. In order to verify the design, the tunnel lining simulation model and the actual tunnel lining detection data are used. The results show good performance for noise and interference suppression, providing technical support for improving GPR data quality and tunnel detection accuracy. This article is protected by copyright. All rights reserved","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136079760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seismic interferometry (SI) retrieves the Green's function between two receiver locations using their recordings from a boundary of sources. When using sources and receivers only at the surface, the virtual‐source gathers retrieved by SI contain pseudo‐physical reflections as well as ghost (non‐physical) reflections. These ghost reflections are the results of the cross‐correlation or auto‐correlation of primary reflections from two different depth levels, and they contain information about the seismic properties of specific layers in the subsurface. We investigated the application of ghost reflections for layer‐specific characterisation of the shallow subsurface using SI by auto‐correlation. First, we showed the technique's potential using synthetic data for a subsurface model with a lateral change in velocity, a gradient in depth for velocity, a thickness change, and a velocity change of the target layer. Then, we applied the technique to shallow subsurface field data. We also focused on improving the retrieval of ghost reflections by removing the free‐surface multiples and muting undesired events in active‐source gathers before applying SI. Our results demonstrate that the ghost reflections can be used advantageously to characterise the layer that causes them to appear in the results of SI. Consequently, they can also provide valuable information for imaging and monitoring shallow subsurface structures.This article is protected by copyright. All rights reserved
{"title":"The utilisation of ghost reflections retrieved by seismic interferometry for layer‐specific characterisation of the shallow subsurface","authors":"Faezeh Shirmohammadi, Deyan Draganov, Ranajit Ghose","doi":"10.1002/nsg.12275","DOIUrl":"https://doi.org/10.1002/nsg.12275","url":null,"abstract":"Seismic interferometry (SI) retrieves the Green's function between two receiver locations using their recordings from a boundary of sources. When using sources and receivers only at the surface, the virtual‐source gathers retrieved by SI contain pseudo‐physical reflections as well as ghost (non‐physical) reflections. These ghost reflections are the results of the cross‐correlation or auto‐correlation of primary reflections from two different depth levels, and they contain information about the seismic properties of specific layers in the subsurface. We investigated the application of ghost reflections for layer‐specific characterisation of the shallow subsurface using SI by auto‐correlation. First, we showed the technique's potential using synthetic data for a subsurface model with a lateral change in velocity, a gradient in depth for velocity, a thickness change, and a velocity change of the target layer. Then, we applied the technique to shallow subsurface field data. We also focused on improving the retrieval of ghost reflections by removing the free‐surface multiples and muting undesired events in active‐source gathers before applying SI. Our results demonstrate that the ghost reflections can be used advantageously to characterise the layer that causes them to appear in the results of SI. Consequently, they can also provide valuable information for imaging and monitoring shallow subsurface structures.This article is protected by copyright. All rights reserved","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135252793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Indresh Kumar, V. Ramesh Babu, B. V. L. Kumar, J. K. Dash, A. K. Chaturvedi
Abstract Induced polarization (IP) effect is widely used in the search of disseminated minerals all over the world. Spectral parameters computed from time‐domain IP data play a significant role in characterizing the sources, but mineral identification still remains a challenge. In this paper, the Levenberg–Marquardt method of inversion is adopted in estimating the spectral parameters from time‐domain IP data to identify the polarizable sources. The algorithm is tested on synthetic time‐domain IP data for its robustness to variable noise levels. Model sensitivity analyses on synthetic data were also studied with respect to acquisition time and each individual model parameter. Error analyses on extracted parameters indicated that these are well resolved and correlated if the relaxation time is within the range of acquisition time. The parameters remain poorly resolved/unresolved for smaller values of chargeability and frequency dependence. The algorithm has also been tested over known case histories of time‐domain IP data and compared the estimated spectral parameters with those of published results. The inferences drawn from computed spectral parameters on field‐observed IP transients are in good correlation with other data sets and borehole information. The methodology has successfully shown its usefulness in identifying large polarizable sources occurring at shallow levels from time‐domain IP data.
{"title":"Computation of spectral parameters from time‐domain induced polarization data for mineral identification","authors":"Indresh Kumar, V. Ramesh Babu, B. V. L. Kumar, J. K. Dash, A. K. Chaturvedi","doi":"10.1002/nsg.12276","DOIUrl":"https://doi.org/10.1002/nsg.12276","url":null,"abstract":"Abstract Induced polarization (IP) effect is widely used in the search of disseminated minerals all over the world. Spectral parameters computed from time‐domain IP data play a significant role in characterizing the sources, but mineral identification still remains a challenge. In this paper, the Levenberg–Marquardt method of inversion is adopted in estimating the spectral parameters from time‐domain IP data to identify the polarizable sources. The algorithm is tested on synthetic time‐domain IP data for its robustness to variable noise levels. Model sensitivity analyses on synthetic data were also studied with respect to acquisition time and each individual model parameter. Error analyses on extracted parameters indicated that these are well resolved and correlated if the relaxation time is within the range of acquisition time. The parameters remain poorly resolved/unresolved for smaller values of chargeability and frequency dependence. The algorithm has also been tested over known case histories of time‐domain IP data and compared the estimated spectral parameters with those of published results. The inferences drawn from computed spectral parameters on field‐observed IP transients are in good correlation with other data sets and borehole information. The methodology has successfully shown its usefulness in identifying large polarizable sources occurring at shallow levels from time‐domain IP data.","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135302183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sophie Marie Stephan, Niklas Allroggen, Jens Tronicke
ABSTRACT Cost‐effective computing capabilities have paved the road for the use of numerical modelling to develop advanced methods and applications of ground‐penetrating radar (GPR). Realistic synthetic data and the corresponding modelling techniques, respectively, should consider all subsurface and above‐ground aspects that influence GPR wave propagation and the characteristics of recorded signals. Critical aspects that can be realized in modern GPR modelling tools include heterogeneous and frequency‐dependent material properties, complex structures and interface geometries as well as three‐dimensional antenna models, including the interaction between the antenna and the subsurface. However, realistic noise related to the electronic components of a GPR system or ambient electromagnetic noise is often not considered, or simplified by assuming a white Gaussian noise model which is added to the modelled data. We present an approach to include realistic noise scenarios as typically observed in GPR field data into the flow of modelling synthetic GPR data. In our approach, we extract the noise from recorded GPR traces and add it to the modelled GPR data via a convolution‐based process. We illustrate our methodology using a modelling exercise, where we contaminate a synthetic two‐dimensional GPR dataset with frequency‐dependent noise recorded in an urban environment. Comparing our noise‐contaminated synthetic data with field data recorded in a similar environment illustrates that our method allows the generation of synthetic GPR with realistic noise characteristics and further highlights the limitations of assuming pure white Gaussian noise models.
{"title":"Adding realistic noise models to synthetic ground‐penetrating radar data","authors":"Sophie Marie Stephan, Niklas Allroggen, Jens Tronicke","doi":"10.1002/nsg.12273","DOIUrl":"https://doi.org/10.1002/nsg.12273","url":null,"abstract":"ABSTRACT Cost‐effective computing capabilities have paved the road for the use of numerical modelling to develop advanced methods and applications of ground‐penetrating radar (GPR). Realistic synthetic data and the corresponding modelling techniques, respectively, should consider all subsurface and above‐ground aspects that influence GPR wave propagation and the characteristics of recorded signals. Critical aspects that can be realized in modern GPR modelling tools include heterogeneous and frequency‐dependent material properties, complex structures and interface geometries as well as three‐dimensional antenna models, including the interaction between the antenna and the subsurface. However, realistic noise related to the electronic components of a GPR system or ambient electromagnetic noise is often not considered, or simplified by assuming a white Gaussian noise model which is added to the modelled data. We present an approach to include realistic noise scenarios as typically observed in GPR field data into the flow of modelling synthetic GPR data. In our approach, we extract the noise from recorded GPR traces and add it to the modelled GPR data via a convolution‐based process. We illustrate our methodology using a modelling exercise, where we contaminate a synthetic two‐dimensional GPR dataset with frequency‐dependent noise recorded in an urban environment. Comparing our noise‐contaminated synthetic data with field data recorded in a similar environment illustrates that our method allows the generation of synthetic GPR with realistic noise characteristics and further highlights the limitations of assuming pure white Gaussian noise models.","PeriodicalId":49771,"journal":{"name":"Near Surface Geophysics","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135648621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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