We proposes a method of gravity inversion based on an adaptive mesh-free approach by using a modified radial basis function . It can parametrize the density distribution by using a mesh-free approach. The subsurface space is generally discretized into regular grid cells, while mesh-free methods can avoid the expensive mesh generation and manipulation required in traditional approaches. Scattered points are introduced in most mesh-free methods to discretize the given equations. To deal with the problem of unstructured nodal discretization, we use a mesh-free discretization strategy to establish a mapping of subsurface grid cells to a cloud of discrete points. The nodes are adaptively refined during the inversion process to better recover abnormal bodies. In addition, the hybrid basis function and the modified radial basis function are used to improve the accuracy and stability of the solution. We verify the effectiveness of the proposed method by using several synthetic and empirical tests.

How to cite: Liu, Y., Huang, Y., and Lü, Q.: Adaptive Mesh-free Approach for Gravity Inversion, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5159, https://doi.org/10.5194/egusphere-egu24-5159, 2024.

High-resolution measurement techniques for distributed and fast soil water dynamics could advance the understanding of subsurface infiltration processes on the plot scale when it can combine high spatial and temporal resolution with a high repeatability of the measured data.

Ground-penetrating radar (GPR) is a promising geophysical tool to image and quantify subsurface flow processes in a non-invasive fashion. In the literature, different strategies to collect time-lapse GPR data have been presented. However, so far, no standardized data acquisition and analysis strategy has been established to monitor subsurface changes related to water infiltration and to compare the outcomes of different experiments.

Here, we present a 4D-GPR measurement strategy to monitor infiltration experiments by combining an irrigation pad (to simulate moderate rain fall events) with a manually operated 3D GPR measurement platform (equipped with a two-channel GPR antenna array and positioning guides). For investigating the repeatability and resolution limits of our measurement strategy, we conducted a systematic field experiment with two recurrent irrigations at two nearby spots at a selected field plot. Our results show that we can reliably monitor non-uniform subsurface flow processes with a spatial resolution < 5 cm and a temporal resolution below 10 minutes.

Because of these so far unreached spatial and temporal resolution capabilities we consider our 4D-GPR measurement strategy as a first step toward a standardized strategy for monitoring infiltration processes. Furthermore, such detailed knowledge about the resolution and repeatability limits of 4D-GPR measurements opens new options for further interpretation approaches, for example without assumptions about a horizontally stratified subsurface model.

How to cite: Stephan, S., Jackisch, C., Tronicke, J., and Allroggen, N.: High-resolution 4D GPR data acquisition strategy to monitor fast and small-scale subsurface flow processes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12500, https://doi.org/10.5194/egusphere-egu24-12500, 2024.

Interpreting independent geophysical data sets can be challenging due to ambiguity and non-uniqueness. To address this, joint inversion techniques have been developed to produce less ambiguous multi-physical subsurface images. Recently, a novel cooperative inversion approach that uses minimum entropy constraints has been proposed. The major feature of this approach is that it can produce sharper boundaries inside the model domain. We implemented this approach in an open-source software framework and systematically investigated its capabilities and applicability on electrical resistivity tomography (ERT), seismic refraction tomography (SRT), and magnetic data.

First, we conducted a synthetic 2D ERT and SRT data study to demonstrate the approach and investigate the influence of the equations’ parameters that must be calibrated as well as to justify extensions of the method. The results show that the use of the joint minimum entropy (JME) stabilizer outclasses separate, conventional smoothness-constrained inversions and provides improved images.

Next, we used the method to analyze 3D ERT and magnetic field data from Rockeskyller Kopf, Germany. Independent inversion of the magnetic field data already suggested a subsurface volcanic diatreme structure, but the joint inversion using JME not only confirmed the expected structure, but also provided improved details in the subsurface image. The multi-physical images of both methods are consistent in many regions of the model as they produce similar boundaries. Due to the sensitivity of the ERT measurements to hydrogeological conditions in the subsurface, some structures are only visible in the ERT data. These features seem not to be enforced on the magnetic susceptibility model, which highlights another advantage and the flexibility of the approach.

However, the results of both the synthetic and field data use cases suggest that careful parameter tests are required prior to cooperative inversion to obtain a suitable hyperparameters and reference model. Our work implies that minimum entropy constrained cooperative inversion is a promising tool for geophysical imaging provided that proper settings are chosen while it also identifies some objectives for future research to improve the approach.

How to cite: Ziegon, A. H., Boxberg, M. S., and Wagner, F. M.: Minimum entropy constrained cooperative inversion with application to electrical resistivity, seismic and magnetic field and synthetic data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12370, https://doi.org/10.5194/egusphere-egu24-12370, 2024.

Electrical resistivity tomography (ERT) offers noninvasive monitoring capabilities for a wide range of environmentally relevant subsurface processes. Its sensitivity to fluid content and temperature changes positions it as an important tool for capturing dynamic processes such as the transport of groundwater pollutants, CO₂ or radionuclides. Particularly crucial is its ability to achieve this without intrusively accessing to the site, making it highly valuable in closed repositories like high-level radioactive waste (HLW) storage sites.

In highly sensitive and complex environments, as in the case of closed repositories, it is critical to maximize the information content of the planned (geo)physical measurements while keeping the costs to a minimum. Several past studies presented approaches to optimize both the sensor positions and the measurement configurations of ERT surveys for static or moving targets in the subsurface. This study extends Optimal Experimental Design (OED) strategies for geoelectrical measurements using information of active time-dependent transport processes in the subsurface. We present three different approaches for process monitoring and apply them to a simulated diffusive-advective transport process in a synthetic model over several time steps. The methods aim at focusing the survey only on the relevant part of the model, in this case the model region that is affected by the transport process. All presented approaches account for uncertain model input parameters by introducing an uncertainty factor in the ranking function. We present a purely model-driven and a purely data-driven active time-dependent OED approach. The first method utilizes the already acquired data from previous time steps to create predictive focusing masks for the next data set, the latter purely relies on model predictions to focus the survey. Moreover, we delineate a hybrid approach using both the simulated transport distance and the already acquired datasets. All three OED methods are compared to each other as well as to datasets that were acquired using standard electrode configurations.

The results of our synthetic study show that the adaptively designed, time-dependent OED approaches result in increased image quality compared to both standard surveys as well as time-independent OED methods. For slow transport processes or small monitoring intervals, the purely data-driven approach is most suitable, since no model predictions, and thus no possible model parametrization uncertainties, are incorporated. For faster transport processes or monitoring strategies with larger acquisition intervals, the strategies that (partly) incorporate model predictions provide the most promising results.

How to cite: Menzel, N., Uhlemann, S., and Wagner, F. M.: Optimal Experimental Design strategies for geoelectrical monitoring of fluid transport processes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9128, https://doi.org/10.5194/egusphere-egu24-9128, 2024.

The application of Electrical Resistivity Tomography (ERT) for the investigation of architectural heritage has numerous limitations. In most cases, we are referring to historic stone buildings and monuments built from limestone, sandstone, or granite blocks, where many features may complicate the interpretation of electrical resistivity data. First of all, there is incomplete or missing information about principles of building construction and the materials used. Another challenge is the heterogeneity of the masonry as a material due to the presence of many joints between the stone blocks, which may be filled with cementitious materials or be completely or partially empty. For medium-scale studies with limited penetration depth, the presence of air in the joints between stone blocks may affect the electrical resistivity distribution and interfere with the detection of the archaeologically relevant anomalies associated, in particular, with the presence of air cavities. Systematic studies of the applicability of the Electrical Resistivity Tomography in such blocky structures are lacking. In this study, the effect caused by masonry geometry was assessed using numerical 3D modelling of the electrical resistivity distribution in a simplified blocky structure consisting of rows of masonry blocks by incorporating joints between them. The purpose is to study how the presence of air-filled joints affects the ability of the ERT method to detect voids in masonry structures depending on the position and size of these voids. The analysis of numerical models provides insights to facilitate the interpretation of ERT results in historical monuments and other structures constructed from stone blocks.

How to cite: Pugacheva, P. and Allam, H.: Application of 3D Forward Modelling to Improve the Interpretation of Electrical Resistivity Tomography Results in Architectural Heritage Monuments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18216, https://doi.org/10.5194/egusphere-egu24-18216, 2024.

Seismic velocity change is a good indicator reflecting the stress state variation of the underground media. Therefore, seismogenic process could be effectively revealed by the velocity change calculation. Based on the seismic ambient noise interferometry, we study the co-seismic velocity change and post-seismic recovery process of the 21 May 2021 M_S6.4 Yangbi earthquake using the continuous records from 16 stations within 50km of the epicenter. The results show that the relative velocity changes between the station pairs (dv/v_pair) decrease significantly after the mainshock. The amplitude ranges from -0.29% to -0.02% and decreases with the increase of station spacing. The relative velocity changes of each station (dv/v_station) obtained by linear regression range from -0.16% to -0.02%, and are generally negatively correlated with the epicenter distance. It is notable that the measured co-seismic velocity changes are mainly originated from the shallow media (≤2km). Such changes are considered to be caused by both static and dynamic strain, but the primary controlling factor is rock fragmentation and large-scale adjustment of stress produced by strong ground motion. In addition, dv/v_station located at the northern stations far from the epicenter have the largest drop values, demonstrating that they are more sensitive to stress disturbances. This may be related to the distribution of thermal fluids below these stations. The results of velocity changes indicate that around the study area the seismic velocity reached its minimum value within a few days after the mainshock. The value then gradually recovered, reaching the pre-seismic level around August, which characterizes the healing process of broken rocks. In this study, ambient noise interferometry has been effectively applied to measure the velocity changes during and after the Yangbi earthquake, and the results show that co-seismic velocity changes are jointly controlled by various factors including the fracture degree of the fault zone, dynamic strain, and the existence of fluids.

How to cite: An, Y., Wang, W., Yang, W., Jiang, H., Yang, J., Li, X., and Pan, R.: Using ambient noise to study the co-seismic and post-seismic velocity changes of the 2021 Yangbi MS 6.4 earthquake in Yunnan, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8256, https://doi.org/10.5194/egusphere-egu24-8256, 2024.

Reflection seismic data were acquired in the Sudret area of Gotland in the time window 6 to 13 November, 2023. Objectives of the survey were to obtain images of the subsurface down to the Precambrian basement in the vicinity of two coreholes that had been drilled earlier down to about 800 m. These images would provide a better understanding of the sedimentary strata and local structure near these holes. For these purposes a sparse 3D survey was acquired that covered a c. 300 m by 700 m rectangular area with high fold, including the locations where the boreholes were drilled. A longer c. 2.8 km 2D profile was also acquired adjacent to the 3D survey that ran roughly in the N-S direction. In addition, distributed acoustic sensing (DAS) measurements were performed in the two coreholes. We report here on some results from the 3D survey and from the DAS measurements.

A Bobcat source with a 500 kg weight drop hammer with base plate was used as a source and 410 5Hz nodal units were available for recording. In total, 704 receiver locations were occupied with acquisition along 19 source lines, implying that 294 units had to be moved during the survey and that the source lines had to be shot twice. DAS data were recorded over the depth interval 17 m above sea level to 475 m below sea level in the Nore-1 corehole. In Nore-2 the depth interval was 17 m above sea level to 720 m below sea level. The fiber optic cable was sampled at 2.45 m intervals and data were recorded at a sampling frequency of 4000 Hz. Due to borehole irregularities it was not possible to get the fiber optic cables all the way to the bottom of the coreholes.

Numerous semi-continuous reflection horizons are observed in the c. upper 500 ms after stacking. A particularly strong reflection at 350 ms likely originates from the top of the Ordovician. Cambrian sandstones are also reflective, as well as shallow sandstone layers in the upper 150 ms. Normal moveout (NMO) velocities are relatively constant at about 3500 m/s. However, depth conversion using this velocity places the reflectivity deeper than what is expected from the cores. The DAS data allow the vertically propagating P-wave velocity to be measured at 3100 m/s. Using this velocity for depth conversion provides more reasonable depths to the main horizons. Since the NMO velocities are largely controlled by the horizontal velocity of the rock the difference between these and the DAS velocity can be explained by the rocks in the area having significant anisotropy (about 10%).

How to cite: Juhlin, C., Brodic, B., Erlström, M., Hedin, P., Sopher, D., Wang, Z., and Wilczynski, Z.: 3D reflection seismic surveying and borehole DAS measurements to image the sedimentary structure in the Sudret area of Gotland, Sweden, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3801, https://doi.org/10.5194/egusphere-egu24-3801, 2024.

Exploring the shallow crustal structure of Mars can offer valuable insights into the planet’s geological evolution and climate history. The ambient wavefield data and marsquake records from NASA’s InSight mission have enabled the characterization of both fine-scale near-surface structures (less than 200 meters) and large-scale crustal structures (greater than a few kilometers) on Mars. However, the exploration of intermediate-scale structures has remained limited. In this study, we introduce a novel varying-parameter approach that integrates principal component analysis with receiver function techniques. This method allows for the effective extraction of P-wave particle motions across various frequencies from the InSight low-frequency marsquake data, facilitating the inversion for the S-wave velocity structure within the topfew kilometers beneath the lander. Our resulting models reveal a distinct discontinuity at a depth of approximately 0.7 km, marked by a sharp increase in S-wave velocity from about 1.4 km/s to roughly 1.9 km/s. This discontinuity is characterized by a sharp transition, approximately 0.1 km thick, rather than a wider gradient zone. Our models are generally consistent with existing data on Mars’ near-surface and large-scale crustal structures, effectively bridging these datasets. When combined with previous geological and seismic observations, the newly identified discontinuity may signify the top of less affected basaltic bedrock, and the overlying structures are interpreted as a composite of Noachian- to early Hesperian-aged sediments and Hesperian to Amazonian basalts. These insights provide new perspectives on the stratification at the InSight landing area, enhancing our understanding of Martian geological history.

How to cite: Wang, X., Chen, L., and Wang, X.: Shallow Crustal Structures of Mars Beneath the InSight Landing Site Revealed by Frequency-Dependent P-wave Particle Motions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15635, https://doi.org/10.5194/egusphere-egu24-15635, 2024.

Numerous very high-resolution seismic lines (Sparker/single-channel seismic reflection) were acquired in the Eastern Channel, along the the Opal Coast, between the Bay of Somme and Cape Gris-Nez, during the oceanographic missions GEOBAS (2016-2020), TREMOR 1 (2014), TREMOR 2 (2017) and MARCOPALE (2023). In this sector, numerous sandy banks are observed, especially the Bassure of Baas. These geophysical data were analyzed as part of the TURBODUNES project, by comparing two reflectors, respectively the sea floor and the base of the dunes (corresponding to the top of the deformed Cretaceous and Eocene bedrocks). The difference between the two signals makes it possible to identify areas with dunes and areas where dunes are absent. Assuming a constant boat speed, the extraction of signals provides spatial information on the height of the dunes. We carry out analyzes of these signals using different methods, including Fourier spectral analysis, empirical mode decomposition and structure functions. Empirical mode decomposition is a method which allows a one-dimensional series to be decomposed into a sum of several series, called “modes”, each having a characteristic wavelength. This makes it possible to quantitatively characterize the shape of the dunes via different modes, each having a wavelength ranging between 25 and 400 m. The lines for which dunes are absent nevertheless have profiles with strong multi-scale variability, with scale-invariant Fourier spectra with a slope of -2, for scales between 2.5 m and approximately 1 km.

How to cite: Gaullier, V., Schmitt, F., and Laurencin, M.: Statistical analyzes of the shapes of marine sand dunes off the Opal Coast (Eastern English Channel), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19047, https://doi.org/10.5194/egusphere-egu24-19047, 2024.

Pressure (P) or shear (S)-wave velocity models of the near-surface can be simultaneously estimated along coincident arrays from P-wave refraction tomography and surface-wave (SW) dispersion inversion methods. Over the past decade, this approach has been integrated into the hydrogeophysics toolbox to image spatial variations of VP/VS (or Poisson) ratio, as its evolution is strongly associated with water content (or saturation) contrasts. The relevance of this method has been verified in various Critical Zone (CZ) observatories, each with distinct hydrogeological characteristics such as continuous multi-layered hydrosystems or fractured environments with strong discontinuities. It has also proven successful in other contexts and application scales, including a hydrothermal site or partially saturated glass beads in a laboratory experiment. However, we identified two major issues: (1) the combined use of P-wave traveltime tomography and SW dispersion inversion involves distinct characteristics of the wavefield and different assumptions about the medium, providing VP and VS models with different sensitivity, resolution, investigation depth, and posterior uncertainties; (2) the involved inversion processes use a small number of layers that cannot properly describe the continuous variations of subsurface hydrological properties. In particular, we noted that VP/VS (or Poisson) ratio was only consistent with strong saturation contrasts and often faced difficulties in retrieving water content variations in the unsaturated zone. This underscores the need to use petrophysical approaches to build alternative forward models and improve inversion processes. Adapted rock physics models have thus recently been developed to take capillary suction effects into account in the effective stress of the soil. In this study, we first present several datasets obtained from various contexts in which SW dispersion variations have been observed and related to changes in water content and/or water table depths. We then suggest using the previously cited rock physics models to simulate these data and show how it helps in understanding the involved hydrofacieses and processes. We finally address the relevance of surface-wave dispersion inversion approaches involving such forward models and discuss the possible use of additional attributes of the seismic wavefield to constrain interpretations.

How to cite: Bodet, L., Sanchez Gonzalez, R., Cunha Teixeira, J., Dangeard, M., Gesret, A., and Rivière, A.: Measuring and modelling seismic surface-wave dispersion variations in various hydrogeological contexts, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12013, https://doi.org/10.5194/egusphere-egu24-12013, 2024.

The dispersion curves of surface waves have been widely used for the retrieval of subsurface structures. Because the surface-wave dispersion is not sensitive to Vp, classical dispersion inversion can only retrieve Vs structures. To retrieve Vp, the dispersion of guided-P waves, which belong to leaky waves, should be considered. Due to the difficulty in forward modeling, the quantitative analysis of the leaky-wave dispersion curves has been rarely reported. In this study, we first derive the sensitivity analysis method of the leaky-wave dispersion based on previously proposed the semi-analytical spectral element method. Then the quantitative sensitivity analysis of leaky-wave dispersion curves is carried out, which confirms the ability of guided-P wave dispersion to constrain the velocity structures. With the theoretical analysis, we propose a joint inversion method based on surface and guided-P wave dispersion curves, which can simultaneously retrieve Vp and Vs. To verify the effectiveness, the proposed joint inversion has been applied to different kinds of field data including ocean bottom seismometer data with active sources and the seismic data of Nevada in the United States in 2008. Both of the inversion tests show that the joint inversion of surface- and leaky-wave dispersion can effectively constrain the velocity structure of Vp and Vs at the same time, which helps to obtain more complete and accurate models than the traditional surface wave dispersion inversion.

How to cite: Shi, C., Chen, X., and Li, Z.: Constraining Vp and Vs structures using the dispersion of surface and leaky waves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15191, https://doi.org/10.5194/egusphere-egu24-15191, 2024.

Classical analysis of radar profiles generally relies on a visual inspection and interpretation of profiles and sometimes on inverse modelling of the acquired data. Both methods suffer severe limitations due to the antenna resolution, thereby preventing the identification of tiny structures, especially in forensic applications. Here we describe a forward modelling technique, which allows to reproduce individual traces (A-scans) of radar profiles through superposition of Ricker wavelets. The method allows to detect ultra-thin layers, well beyond the Ricker and Rayleigh vertical resolution of GPR antennas. This approach starts from an estimation of the instrumental uncertainty of common monostatic antennas and takes into account of the frequency-dependent attenuation, which causes spectral shift of the dominant frequency acquired by the receiver antenna. The forward modelling procedure loads a single trace from a radar profile and allows to build a synthetic A-scan by fitting a sequence of Ricker wavelets with user-defined amplitude, polarity, and arrival time to the acquired trace. The resulting synthetic trace can be used to create a reflectivity diagram that plots reflection amplitudes and polarities versus depth. Often a reflectivity diagram shows intervals bounded by reflectors of opposite polarity, associated with layers having higher or lower velocity than the surrounding material, respectively. These intervals may result from very subtle features that represent interesting survey targets, for example buried bones, small cracks, thin lens of liquid contaminants, etc. and could be confused with individual reflectors through the simple visual inspection of a radar profile. Our quantitative approach can be used in several applications of GPR methods, especially in forensic, paleontological, civil engineering, heritage protection, and soil stratigraphy applications.

How to cite: Schettino, A., Ghezzi, A., and Tassi, L.: Trace Modelling: A Quantitative Approach to the Interpretation of Ground Penetrating Radar Profiles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11360, https://doi.org/10.5194/egusphere-egu24-11360, 2024.

In seismic exploration, three-dimensional near-surface tomography is key to solving complex statics problem and is an important prerequisite for migration imaging. To this end, this paper starts with the principles of ray tracing theory and tomographic inversion methods. Based on a comprehensive comparative analysis of the advantages and disadvantages of traditional ray tracing methods and numerical algorithms for tomographic inversion, using the first arrival times in three-dimensional seismic data, a high-precision three-dimensional ray tracing method based on multi-retracing technology and a tomographic inversion method constrained by prior information such as small refraction and micro logging throughout the process are proposed. First, this paper use near-surface survey information such as micro logging and small refraction to constrain the establishment of an initial velocity model and constrain tomographic inversion to improve the vertical inversion accuracy of the model. Secondly, to address the loss of shallow layer information due to excessive shot-to-detector distances, this paper introduces a virtual detector point technique. By adding one or more virtual detector points between known shot points and detector points within a close offset range, the density of rays at near offsets is increased, thereby improving the lateral tomographic imaging accuracy of the near-surface. At the same time, various constraints are introduced during the inversion process, including the range of velocity restriction, inversion slowness correction size constraints, internal iteration number constraints of tomographic inversion, dual-grid inversion, velocity extrapolating and smoothing, etc., greatly improving the accuracy of inversion and the quality of tomographic imaging. Given the large computational volume of three-dimensional data and the high memory consumption of large sparse matrices, this paper employs compressed storage and tomographic matrix solving techniques, greatly saving memory space and enhancing computational efficiency. The test results on theoretical models and actual data show that the ray tracing method used in this paper provides essentially correct ray propagation paths, consistent with geological laws. The final inversion results effectively reveal the velocity and thickness of near-surface low-speed layers and deceleration layers, demonstrating the correctness and effectiveness of the inversion method proposed in this paper.

Keywords: Velocity modeling, Ray tracing, Tomographic inversion, Micro logging, Small refraction

How to cite: cheng, R.: Method for near-surface three-dimensional velocity modeling based on first-arrival, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4659, https://doi.org/10.5194/egusphere-egu24-4659, 2024.