To improve inversion accuracy of ambient noise surface wave (ANSW) data in the near surface, we propose a kernel fuzzy C-means (KFCM) clustering-constrained inversion scheme. The scheme incorporates a kernel clustering constraint term into the objective function, which is guided by a priori cluster centers during the inversion process. The effectiveness of the proposed method is validated using both synthetic and field data. In the synthetic tests, the KFCM clustering-constrained inversion reduces model-space errors and yields clearer separation of clustered Vs regimes than the fuzzy C-means (FCM) clustering-constrained inversion using the same a priori centers. Compared with Tikhonov smoothing regularization, KFCM better preserves regime boundaries and velocity contrasts. For the field case, the KFCM clustering-constrained inversion accurately delineates two stratigraphic interfaces consistent with the borehole Vs logs, whereas the Tikhonov smoothing-constrained and FCM clustering-constrained inversion methods results show larger deviations with borehole data. The results demonstrate that the KFCM-constrained is an effective and valuable scheme for the inversion of ANSW data in the near surface. It can also be applied to other geophysical data.

In traditional seismic reflection exploration, geological structures are characterized only by interpreting reflection wave events from wave impedance interfaces and then obtaining information of stratigraphic interfaces and structures. Herein, we present a method used to rapidly invert velocities of seismic waves reflected from strata layers. We have named this method “Seismic Reflective Ground Penetrating Mirroring (SRGPM)”. This method consists of three steps, which are: (1) adaptive extraction of respective reflection signals, (2) automatic selection of root mean square velocity, and (3) fast inversion of layer velocity. The validity of the proposed method was verified with field data. The layer velocities and structures of strata can be quickly acquired by SRGPM. Combining this data with prior geological information, the inverted layer velocities can be converted into the uniaxial compressive strengths of the soil layers, providing basic data for evaluation of urban foundations.

Road collapses seriously threaten human safety in cities. The effective and rapid identification of hidden urban road hazards using 3-D ground-penetrating radar (3D-GPR) data is crucial for preventing and controlling road collapse accidents. We propose a novel intelligent identification method for urban road hazards using a backpropagation (BP) artificial neural network based on multiscale gray-level co-occurrence matrix (GLCM) attributes derived from 3D-GPR data. The characteristic differences in multiscale GLCM attributes between hidden hazards and other detected targets are leveraged to construct a road hazard identification model using a BP neural network. This model is applied to identify hazards from 3D-GPR data, enabling rapid localization of hidden urban road hazards. Initially, GPR data are processed using zero-time correction, background suppression, and filtering. Next, labeled data are created using the radar responses of known hazards, wells, pipelines, and strata. Subsequently, after applying gradient enhancement processing to the GPR data, the GLCM attributes are calculated at different scales to distinguish hazards in 3-D space from other target bodies. Finally, a neural network model for hidden hazard identification is constructed using a BP artificial neural network and applied to identify hidden hazards beneath urban roads from GPR measurement data. The results show that the prediction accuracy exceeds 85% using the proposed approach. The combination of multiscale GLCM attributes and BP neural network is valuable and effective for the detection and identification of hidden hazards beneath urban roads.

Joint inversion of surface wave and gravity data can reduce the non-uniqueness of individual inversion and has been applied in research on the Earth’s crust and lithospheric mantle. At present, direct parameter coupling, which requires specifying a functional relationship between shear wave (S-wave) velocity and density, is primarily used; however, it can result in spurious features when the models violate the parameter relationship. Moreover, an appropriate velocity–density function is difficult to derive, and a single physical property relationship may not be suitable for all regions. We present a new joint inversion algorithm for ambient noise surface wave and gravity data, using variation of information (VI) coupling which measures the amount of information one variable contained in another variable based on information theory. The correlation between S-wave velocity and density models is established with a one-to-one relationship with VI. The effectiveness of the algorithm is verified using synthetic and field data. The synthetic data analysis results indicate that density anomalies are accurately captured by joint inversion, whereas they are hardly captured by individual inversion. S-wave velocity models obtained by joint inversion are more accurate than those obtained by individual inversion. The fitting parameter relationship of the joint inversion models is closer to the true model than that of individual inversion. In the field case of the southeastern Tibetan Plateau, the S-wave velocity model of joint inversion has a higher resolution than that of separate inversion. The density model obtained by joint inversion clearly reveals crustal structures, which are severely distorted in the individual inversion model. Joint inversion with VI coupling is an effective and valuable approach for inverting surface wave and gravity data.

SUMMARY We present a novel strategy for performing joint inversion with guided fuzzy c-means (GFCM) clustering coupling and apply it to electrical resistivity tomography (ERT) and ambient noise surface wave (ANSW) data. To accurately extract a priori clustering information, we use density peak clustering (DPC) rather than fuzzy c-means (FCM). The number and centres of resistivity and shear-wave velocity a priori clusters are extracted by DPC and then used to guide the joint inversion with the GFCM clustering coupling of ERT and ANSW data. Synthetic and field data are used to evaluate the flow and algorithm of DPC-GFCM clustering joint inversion. The results of synthetic examples show that the models recovered by the DPC-GFCM clustering joint inversion are nearly the same as the true models and are more accurate than those inverted using individual inversion and FCM-GFCM clustering joint inversion. In the field case, the depths of the stratigraphic interfaces shown in the resistivity and shear-wave velocity models inverted by DPC-GFCM clustering joint inversion are nearly consistent with those from the drilling data. In contrast, the strata recovered by the individual inversion and FCM-GFCM clustering joint inversion significantly differ from the drilling results. Both the synthetic and field examples verify the effectiveness of the DPC-GFCM clustering coupling method used for the joint inversion of ERT and ANSW data acquired from the near surface with strong heterogeneity. This novel approach can also be applied to other types of geophysical data.

Estimating resistivity distributions within dam structures accurately using electrical resistivity tomography (ERT) poses a significant challenge due to the limited 2D acquisition scheme, the 3D heterogeneity of near-surface materials, and the dynamic nature of fluid transport. To address this challenge, we present a new strategy by simultaneously inverting multiple collinear ERT datasets acquired from various standard electrode arrays. This strategy incorporates the coupling of the intrinsic parameter relationship into the objective function, constraining the inversion solution space by balancing the distinct resolution characteristics associated with the electrode arrays involved in the joint inversion process. Using synthetic Karst and infiltration models, we demonstrate that our strategy can yield accurate inversion results for both the Wenner and dipole-dipole datasets. Application of this strategy to a field case at Nanshan Dam in southeast China, which involves Wenner, Wenner-Schlumberger, and dipole-dipole surveys, successfully delineates preferential fluid seepage pathways. These findings are further corroborated by consistent inferred reflectors in Ground Penetrating Radar (GPR) profiles. The synthetic and field examples highlight the effectiveness of our strategy in achieving accurate and unified resistivity estimates by integrating multiple ERT datasets.

We present a novel joint inversion strategy for electrical resistivity tomography (ERT) and seismic first-arrival traveltime data with guided fuzzy c-means (GFCM) clustering coupling to increase the accuracy of inversion results and improve the characterization of heterogeneous near-surface materials. The physical parameter correlation between the resistivity and seismic velocity is enforced using a GFCM clustering coupling term in the objective function, which also includes misfit and regularization terms. The physical property models estimated by joint inversion are guided by the clustering centers of a priori petrophysical parameters. A limited-memory quasi-Newton approach is used to optimize the objective function. To validate the proposed approach and describe its implementation in detail, tests were first performed using two synthetic models. The stratigraphic structures recovered by joint inversion with GFCM clustering coupling are more consistent with the true model than those inverted by individual inversion, cross-gradient and fuzzy c-means (FCM) joint inversion. Furthermore, the physical parameters estimated using GFCM joint inversion are significantly more accurate than those estimated using individual inversion and the other two joint inversion methods. The joint inversion algorithm was applied to field data from the Liangzhu site in Hangzhou, China. The depth and shape of the stratigraphic interface imaged by GFCM joint inversion are consistent with the drilling results. However, when using individual inversion and the other two joint inversion methods, the recovered stratigraphic structures have some differences with the drilling data. Therefore, GFCM joint inversion is an effective and reliable method for near-surface fine imaging.

地球物理调查和地质资料的综合分析表明,现今蒙古高原的地壳构造主要是由于古亚洲洋和蒙古-鄂霍茨克洋两次大洋闭合和拼合造山作用形成的.其中古亚洲洋闭合作用主要发生在蒙古高原的西部和南部,造成阿尔泰碰撞造山带地壳隆升、乌布斯-巴彦洪戈尔地壳沉降,也牵连到杭爱山地块发生次级的地壳隆升.蒙古高原的东部,中生代古蒙-鄂洋封闭时没有发生强烈的碰撞,上、下阿穆尔地体和锡林浩特地体就完全拼合成陆地.这种类型的拼合造山,速度缓慢的陆-陆俯冲起主要作用.当然,速度缓慢的陆-陆俯冲作用同样会造成众多的地壳变形和岩浆侵入,使大陆增生.蒙-鄂洋的闭合没有发生明显的地壳缩短加厚,而是发生大规模幔源岩浆侵入,使地壳熔解和结晶基底快速克拉通化.在蒙古下方的上地幔,有反映上地幔羽毛状热流体上涌的痕迹残留.

Investigation of water pipeline leakage is a matter of great significance for water resources management. Among various approaches, ground-penetrating radar (GPR) attracts increasing attention as a fast and noninvasive technique. However, this method suffers from uncertainties in the stage of interpretation because diffractions from the leak region often are too weak to be identified. To address this problem, we have developed the use of diffraction imaging to enhance imaging and characterization of water leakage. Numerical seepage simulation allows us to establish an equivalent computational analog for a known leak condition. After the collection of parallel GPR survey lines, we apply diffraction separation and imaging techniques on 2D and 3D data. Although the actual situation is generally well reproduced by 2D and 3D results, 3D diffraction imaging provides improved mapping of leakage compared with its 2D counterpart. We then apply the method to field data collected at a training base for water pipeline leakage control in Shaoxing, China. The prediction from imaging results corresponds well with the true position and type of leakage. The laboratory and field experiments substantiate the viability of GPR diffraction imaging and illustrate the potential of using GPR to detect small water leaks.

Cross-hole seismic tomography is a high-precision method that can obtain the velocity structure between boreholes. At present, single-component geophones are mainly used for P-wave velocity estimation. However, S waves have a shorter wavelength than P waves, incurring a high-resolution tomography image. In this paper, we apply three-component cross-hole seismic tomography to shallow geological survey. First, three-component geophone is used to collect cross-hole seismic data. Secondly, the apparent velocity polarization method is used to separate the P and S wavefields from the recorded three-component waveform data. Then, a damped least-squares traveltime tomography is used to calculate the cross-hole P- and S-wave velocity structures. Finally, the distribution of Poisson's ratio between the boreholes is derived from the inverted P- and S-wave velocities. Numerical model experiments show that this method can solve some typical shallow subsurface problems, such as the detection of karst features and boulders. The proposed method is used to detect an underground air-raid shelter located in Hangzhou, Zhejiang Province, China, and the P- and S-wave velocities and the Poisson's ratio are obtained with high precision. The tomography image of the air-raid shelter agrees well with its known location. and the calculated Poisson's ratio distribution shows that the air-raid shelter may be partially filled with mucky clay. Three-component cross-hole seismic tomography achieves a high data acquisition efficiency and can simultaneously obtain shallow subsurface stratum velocities and Poisson's ratio with high precision. Thus, this technique can be used for shallow-subsurface surveys.

电阻率层析成像是一种广泛应用在水文、考古和地质等浅地表勘探领域的地球物理方法.为了增强电阻率层析成像的分辨率、应对复杂的地质问题,本文提出基于雅可比矩阵的不同电极阵列直流电阻率数据的加权联合反演算法,并以温纳和偶极-偶极电极阵列数据为例,在理论模型和古墓探测的野外实例中测试该算法的有效性.结果表明,加权联合反演结果的横向和纵向分辨率都优于单一电极阵列的反演结果,并在实例中缓解"U形"电极阵列的固有缺陷、减少反演模糊性、更好地约束墓室宽度的反演结果.

Ancient burnt soils are valuable records in environmental and archaeological studies, and thus it is important to prospect such buried historical remains. By far, the study on geophysical exploration of the burnt soil is still rare. To investigate the effectiveness of geophysical methods for investigating such ancient relics, we designed a controlled field experiment at Liangzhu city site in Hangzhou, China, where there are plenty of Neolithic burnt remains in the shallow subsurface. We acquired common-offset ground penetrating radar (GPR) and electrical resistivity tomography (ERT) data, performed archaeological drilling and measured the physical properties of soil cores. The GPR and ERT data were first analyzed individually and compared with the borehole logs. We observe that the major reflected energy in the GPR data come from the vicinity of the burnt soil layer, while the energy below that is generally weak. The conductivity estimated from the ERT data is overall small in the shallow part but has a sudden increase from the lower interface of the burnt soil layer. The slopes estimated from two types of geophysical data show local similarities and complementarity, based on which we propose a novel workflow for geophysical data fusion based on the technique of predictive painting. The scheme can generate easy-to-understand images of soil layers with low computational costs, and its extension to 3D case is conceptually straightforward. It is also feasible to extend our work to large-scale surveys of ancient burnt soils.

Accurate understanding of near-surface structures of the solid earth is challenging, especially in urban areas where active source seismic surveys are constrained and difficult to perform. The analysis of anthropogenic seismic noise provides an alternative way to image the shallow subsurface in urban environments. We have developed an application of using traffic noise with seismic interferometry to investigate near-surface structures in Hangzhou City, Eastern China. Noise data were recorded by dense linear arrays with approximately 5 m spacing deployed along two crossing roads. We analyze the characteristics of traffic-induced noise using 36 h continuous recordings. Coherent Rayleigh surface waves between 2 and 20 Hz are retrieved based on crosscorrelations within 1 h time windows. Robust phase-velocity dispersion curves are extracted from virtual shot gathers using multichannel analysis of surface waves and coincide with the results from active seismic data, noise beamforming analysis, and measurements with the spatial autocorrelation method. S-wave velocity profiles are derived for the top 100 m of the subsurface at the array locations. The estimated S-wave velocities from traffic noise correspond to the velocities estimated from logging data. The 2D S-wave velocity maps reveal different soil deposits and bedrock structures in the estuarine sedimentary area. The results demonstrate the accuracy and efficiency of delineating near-surface structures from traffic-induced noise, which has great potential for monitoring subsurface changes in urban areas.

随着中国经济的快速发展和城市化进程的加快,有限的土地资源和城市发展之间的矛盾越来越突出,城市地下空间的安全、合理利用和地质环境保护具有重要的战略意义.为了解决G20、亚运会以及数字经济为杭州市快速发展带来的人口快速增长与土地资源有限的瓶颈问题,针对以杭州为代表的南方丘陵地区地下空间精细探测需求,开展了弹性波法、电法与电磁法等多种地球物理方法的可行性研究.结果 表明:不同勘探方法在探测深度、分辨率以及勘探效率上具有明显的差异性,需要根据地下地质状况以及地表条件选择合适的勘探方法进行探测,这对类似丘陵地区城市地下空间开发及利用具有指导意义和参考价值.

Geophysical techniques are used to detect mounds and burial chambers, but detecting the shape and layout of large mausoleums containing main tombs and ancillary facilities is a developing field. The shape and layout of mausoleums are closely related to cultural practices. In this study, integrated geophysical technologies were used to survey a large-scale mausoleum in Hangzhou, China. The layout of the main tomb was deduced from magnetic gradient measurements, and the depth and scale were inferred from electrical resistivity tomography (ERT). The location and burial depth of ancillary facilities, including the mausoleum path, were characterized using the depth (time) slice of ground-penetrating radar (GPR) three-dimensional (3D) attribute analysis. An integrated interpretation of geophysical results combined with archaeological documents provides the plan and section layouts of the mausoleum. Based on integrated analyses and archaeological documents, the age of the mausoleum was inferred (middle to late Southern Song Dynasty). Subsequent test excavations partly confirmed the results and showed that the combination of geophysical technologies and archaeological documents are effective and valuable for detecting large-scale mausoleums.

遥感与地球物理考古探测数据类型多样,然而各种探测数据因缺少综合管理和分析平台,使综合分析更加困难,从而限制了考古探测技术应用效果.在了解遥感与地球物理考古探测技术的基础上,本文对当前遥感地球物理考古探测数据管理系统进行逻辑和业务需求分析,构建基于ArcGIS Engine开发引擎和Visual Studio 2017平台的遥感与地球物理考古探测数据综合管理系统.系统通过分层次设计功能模块,实现考古探测数据的编辑、解释、分析以及数据之间的交互和管理.实际应用表明,对于遥感地球物理考古探测技术与地理信息技术相结合的思路和研究,能够提升遥感与地球物理考古探测数据的综合分析能力,促进考古探测技术的有效应用.

综合地球物理技术在采空区的探测中发挥了重要作用.目前通常采用单方法反演、仅对不同方法反演结果进行对比解释的综合勘探方式,单方法反演的多解性严重降低了其探测精度.如何提高采空区的探测精度,对采空区进行有效探测一直被认为是地球物理技术面临的首要难题.为了提高地震与电法技术的探测精度,基于交叉梯度联合反演理论,设计了地震初至折射走时数据和高密度电法数据的联合反演算法流程,对采空区理论模型和野外实际数据进行了联合反演处理.结果发现通过两者的联合反演,不仅可以提高采空区电阻率反演模型的成像效果,而且能够获得地震单方法反演难以成像的采空区低速异常体,从而提高了地震与电法技术对采空区的探测精度.表明地震与电法探测数据联合反演是一种提高采空区探测精度的有效方法.

Ground penetrating Radar (GPR) is an efficient tool for subsurface geophysical investigations, particularly at shallow depths. The non-destructiveness, cost efficiency, and data reliability are the important factors that make it an ideal tool for the shallow subsurface investigations. Present study encompasses; variations in central frequency of transmitting and receiving GPR antennas (Tx-Rx) have been analyzed and frequency band adjustment match filters are fabricated and tested accordingly. Normally, the frequency of both the antennas remains similar to each other whereas in this study we have experimentally changed the frequencies of Tx-Rx and deduce the response. Instead of normally adopted three pairs, a total of nine Tx-Rx pairs were made from 50MHz, 100MHz, and 200MHz antennas. The experimental data was acquired at the designated near surface geophysics test site of the Zhejiang University, Hangzhou, China. After the impulse response analysis of acquired data through conventional as well as varied Tx-Rx pairs, different swap effects were observed. The frequency band and exploration depth are influenced by transmitting frequencies rather than the receiving frequencies. The impact of receiving frequencies was noticed on the resolution; the more noises were observed using the combination of high frequency transmitting with respect to low frequency receiving. On the basis of above said variable results we have fabricated two frequency band adjustment match filters, the constant frequency transmitting (CFT) and the variable frequency transmitting (VFT) frequency band adjustment match filters. By the principle, the lower and higher frequency components were matched and then incorporated with intermediate one. Therefore, this study reveals that a Tx-Rx combination of low frequency transmitting with high frequency receiving is a better choice. Moreover, both the filters provide better radargram than raw one, the result of VFT frequency band adjustment filter is much better than CFT frequency band adjustment filter.

2D高密度电法在古墓葬勘探中应用较多,但二维剖面解释局限性愈发突出.以2D平行或等角度放射状测线为基础的拟3D高密度电法能够一定程度上给出三维信息,但对地表条件要求较高,灵活性稍差.3D高密度电法能够给出详细的3D探测信息,但施工效率偏低,且难以适应复杂地表环境.为解决复杂地表环境古墓葬探测问题,提出了一种多方位拟3D高密度电法技术,并在一个位于密集竹林中的大型古墓葬调查中进行了应用研究.结合地表条件布设多个方位的2D高密度电法测线,将多个方位的2D反演数据合并为拟3D数据体,进行可视化解释获得了内部结构的3D信息.结果表明,该技术能够适应复杂环境,拟三维数据不仅能补充二维解释缺失的信息,且与钻探结果基本吻合.

The main object is to identify the position of rammed earth site using geophysical technology. Firstly, geophysical investigation was finished in known area where culture relics and their positions are known. And the known position information was obtained using drilling and exaction before. Secondly, the effective geophysical technologies were selected through comparison between geophysical exploration results and drilling and exaction data in the known area. At last, the geophysical technologies were used in unknown area and the culture relic positions were inferred using geophysical image. The results show that horizontal positions of ancient construction base and road can be discerned from magnetic and ground electromagnetic method (GEM2) image. But the exploration precision of GEM2 is lower than that of magnetic method. The depth can be found using ground penetration radar (GPR) phase attribute. It is concluded that geophysical technology is effective for investigating rammed earth construction base and ancient road. The space position of culture relics can be identified by combination application of magnetic and GPR.