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The region of West Bohemia and Upper Palatinate belongs to the West Bohemian Massif. The study area is situated at the junction of three different Variscan tectonic units and hosts the ENE-WSW trending Ohre Rift as well as many different fault systems. The entire region is characterized by ongoing magmatic processes in the intra-continental lithospheric mantle expressed by a series of phenomena, including e.g. the occurrence of repeated earthquake swarms and massive degassing of mantle derived CO2 in form of mineral springs and mofettes. Ongoing active tectonics is mainly manifested by Cenozoic volcanism represented by different Quaternary volcanic structures. All these phenomena make the Ohre Rift a unique target area for European intra-continental geo-scientific research. With magnetotelluric (MT) measurements we image the subsurface distribution of the electrical resistivity and map possible fluid pathways. Two-dimensional (2D) inversion results by Munoz et al. (2018) reveal a conductive channel in the vicinity of the earthquake swarm region that extends from the lower crust to the surface forming a pathway for fluids into the region of the mofettes. A second conductive channel is present in the south of their model; however, their 2D inversions allow ambiguous interpretations of this feature. Therefore, we conducted a large 3D MT field experiment extending the study area towards the south. The 3D inversion result matches well with the known geology imaging different fluid/magma reservoirs at crust-mantle depth and mapping possible fluid pathways from the reservoirs to the surface feeding known mofettes and spas. A comparison of 3D and 2D inversion results suggests that the 2D inversion results are considerably characterized by 3D and off-profile structures. In this context, the new results advocate for the swarm earthquakes being located in the resistive host rock surrounding the conductive channels; a finding in line with observations e.g. at the San Andreas Fault, California.
Ice complex deposits are characteristic, ice-rich formations in northern East Siberia and represent an important part in the arctic carbon pool. Recently, these late Quaternary deposits are the objective of numerous investigations typically relying on outcrop and borehole data. Many of these studies can benefit from a 3D structural model of the subsurface for upscaling their observations or for constraining estimations of inventories, such as the local carbon stock. We have addressed this problem of structural imaging by 3D ground-penetrating radar (GPR), which, in permafrost studies, has been primarily used for 2D profiling. We have used a 3D kinematic GPR surveying strategy at a field site located in the New Siberian Archipelago on top of an ice complex. After applying a 3D GPR processing sequence, we were able to trace two horizons at depths below 20 m. Taking available borehole and outcrop data into account, we have interpreted these two features as interfaces of major lithologic units and derived a 3D cryostratigraphic model of the subsurface. Our data example demonstrated that a 3D surveying and processing strategy was crucial at our field site and showed the potential of 3D GPR to image geologic structures in complex ice-rich permafrost landscapes.
Ground-penetrating radar (GPR) is a standard geophysical technique used to image near-surface structures in sedimentary environments. In such environments, GPR data acquisition and processing are increasingly following 3D strategies. However, the processed GPR data volumes are typically still interpreted using selected 2D slices and manual concepts such as GPR facies analyses. In seismic volume interpretation, the application of (semi-)automated and reproducible approaches such as 3D attribute analyses as well as the production of attribute-based facies models are common practices today. In contrast, the field of 3D GPR attribute analyses and corresponding facies models is largely untapped. We have developed and applied a workflow to produce 3D attribute-based GPR facies models comprising the dominant sedimentary reflection patterns in a GPR volume, which images complex sandy structures on the dune island of Spiekeroog (Northern Germany). After presenting our field site and details regarding our data acquisition and processing, we calculate and filter 3D texture attributes to generate a database comprising the dominant texture features of our GPR data. Then, we perform a dimensionality reduction of this database to obtain meta texture attributes, which we analyze and integrate using composite imaging and (also considering additional geometric information) fuzzy c-means cluster analysis resulting in a classified GPR facies model. Considering our facies model and a corresponding GPR facies chart, we interpret our GPR data set in terms of near-surface sedimentary units, the corresponding depositional environments, and the recent formation history at our field site. Thus, we demonstrate the potential of our workflow, which represents a novel and clear strategy to perform a more objective and consistent interpretation of 3D GPR data collected across different sedimentary environments.
Ground-penetrating radar (GPR) is a method that can provide detailed information about the near subsurface in sedimentary and carbonate environments.
The classical interpretation of GPR data (e.g., based on manual feature selection) often is labor-intensive and limited by the experience of the intercally used for seismic interpretation, can provide faster, more repeatable, and less biased interpretations. We have recorded a 3D GPD data set collected across a paleokarst breccia pipe in the Billefjorden area on Spitsbergen, Svalbard. After performing advanced processing, we compare the results of a classical GPR interpretation to the results of an attribute-based classification.
Our attribute classification incorporates a selection of dip and textural attributes as the input for a k-means clustering approach. Similar to the results of the classical interpretation, the resulting classes differentiate between undisturbed strata and breccias or fault zones.
The classes also reveal details inside the breccia pipe that are not discerned in the classical fer that the intrapipe GPR facies result from subtle differences, such as breccia lithology, clast size, or pore-space filling.
We present a new three-dimensional density model of the Central Andes characterizing the structure and composition of the lithosphere together with a geodynamic simulation subjected to continental intraplate shortening. The principal aim of this study is to assess the link between heterogeneities in the lithosphere and different deformation patterns and styles along the orogen-foreland system of the Central Andes. First, we performed a 3D integration of new geological and geophysical data with previous models through forward modelling of Bouguer anomalies. Subsequently, a geodynamic model was set-up and parametrized from the previously obtained 3D structure and composition. We do not find a unambigous correlation between the resulting density configuration and terrane boundaries proposed by other authors. Our models reproduce the observed Bouguer anomaly and deformation patterns in the foreland. We find that thin-skinned deformation in the Subandean fold-and thrust belt is controlled by a thick sedimentary layer and coeval underthrusting of thin crust of the foreland beneath the thick crust of the Andean Plateau. In the adjacent thick-skinned deformation province of the inverted Cretaceous extensional Santa Barbara System sedimentary strata are much thinner and crustal thickness transitions from greater values in the Andean to a more reduced thickness in the foreland. Our results show that deformation processes occur where the highest gradients of lithospheric strength are present between the orogen and the foreland, thus suggesting a spatial correlation between deformation and lithospheric strength.
Based on a numerical model of the Northeast German Basin (NEGB), we investigate the sensitivity of the calculated thermal field as resulting from heat conduction, forced and free convection in response to consecutive horizontal and vertical mesh refinements. Our results suggest that computational findings are more sensitive to consecutive horizontal mesh refinements than to changes in the vertical resolution. In addition, the degree of mesh sensitivity depends strongly on the type of the process being investigated, whether heat conduction, forced convection or free thermal convection represents the active heat driver. In this regard, heat conduction exhibits to be relative robust to imposed changes in the spatial discretization. A systematic mesh sensitivity is observed in areas where forced convection promotes an effective role in shorten the background conductive thermal field. In contrast, free thermal convection is to be regarded as the most sensitive heat transport process as demonstrated by non-systematic changes in the temperature field with respect to imposed changes in the model resolution.
Today, near-surface investigations are frequently conducted using non-destructive or minimally invasive methods of applied geophysics, particularly in the fields of civil engineering, archaeology, geology, and hydrology. One field that plays an increasingly central role in research and engineering is the examination of sedimentary environments, for example, for characterizing near-surface groundwater systems. A commonly employed method in this context is ground-penetrating radar (GPR). In this technique, short electromagnetic pulses are emitted into the subsurface by an antenna, which are then reflected, refracted, or scattered at contrasts in electromagnetic properties (such as the water table). A receiving antenna records these signals in terms of their amplitudes and travel times. Analysis of the recorded signals allows for inferences about the subsurface, such as the depth of the groundwater table or the composition and characteristics of near-surface sediment layers. Due to the high resolution of the GPR method and continuous technological advancements, GPR data acquisition is increasingly performed in three-dimensional (3D) fashion today.
Despite the considerable temporal and technical efforts involved in data acquisition and processing, the resulting 3D data sets (providing high-resolution images of the subsurface) are typically interpreted manually. This is generally an extremely time-consuming analysis step. Therefore, representative 2D sections highlighting distinctive reflection structures are often selected from the 3D data set. Regions showing similar structures are then grouped into so-called radar facies. The results obtained from 2D sections are considered representative of the entire investigated area. Interpretations conducted in this manner are often incomplete and highly dependent on the expertise of the interpreters, making them generally non-reproducible.
A promising alternative or complement to manual interpretation is the use of GPR attributes. Instead of using the recorded data directly, derived quantities characterizing distinctive reflection structures in 3D are applied for interpretation. Using various field and synthetic data sets, this thesis investigates which attributes are particularly suitable for this purpose. Additionally, the study demonstrates how selected attributes can be utilized through specific processing and classification methods to create 3D facies models. The ability to generate attribute-based 3D GPR facies models allows for partially automated and more efficient interpretations in the future. Furthermore, the results obtained in this manner describe the subsurface in a reproducible and more comprehensive manner than what has typically been achievable through manual interpretation methods.
Here, we study the 3-D subduction initiation process induced by the interaction between a hot thermochemical mantle plume and oceanic lithosphere using thermo-mechanical viscoplastic finite difference marker-in-cell models. Our numerical modeling results show that self-sustaining subduction is induced by plume-lithosphere interaction when the plume is sufficiently buoyant, the oceanic lithosphere is sufficiently old and the plate is weak enough to allow the buoyant plume to. pass through it. Subduction initiation occurs following penetration of the lithosphere by the hot plume and the downward displacement of broken, nearly circular segments of lithosphere (proto-slabs) as a result of partially molten plume rocks overriding the proto-slabs. Our experiments show four different deformation regimes in response to plume-lithosphere interaction: a) self-sustaining subduction initiation, in which subduction becomes self-sustaining; b) frozen subduction initiation, in which subduction stops at shallow depths; c) slab break-off, in which the subducting circular slab breaks off soon after formation; and d) plume underplating, in which the plume does not pass through the lithosphere and instead spreads beneath it (i.e., failed subduction initiation). These regimes depend on several parameters, such as the size, composition, and temperature of the plume, the brittle/plastic strength and age of the oceanic lithosphere, and the presence/absence of lithospheric heterogeneities. The results show that subduction initiates and becomes self-sustaining when the lithosphere is older than 10 Myr and the non dimensional ratio of the plume buoyancy force and lithospheric strength above the plume is higher than approximately 2. The outcomes of our numerical experiments are applicable for subduction initiation in the modern and Precambrian Earth and for the origin of plume-related corona structures on Venus. (C) 2016 Elsevier B.V. All rights reserved.
The study of outcrop modeling is located at the interface between two fields of expertise, Sedimentology and Computing Geoscience, which respectively investigates and simulates geological heterogeneity observed in the sedimentary record. During the last past years, modeling tools and techniques were constantly improved. In parallel, the study of Phanerozoic carbonate deposits emphasized the common occurrence of a random facies distribution along single depositional domain. Although both fields of expertise are intrinsically linked during outcrop simulation, their respective advances have not been combined in literature to enhance carbonate modeling studies. The present study re-examines the modeling strategy adapted to the simulation of shallow-water carbonate systems, based on a close relationship between field sedimentology and modeling capabilities. In the present study, the evaluation of three commonly used algorithms Truncated Gaussian Simulation (TGSim), Sequential Indicator Simulation (SISim), and Indicator Kriging (IK), were performed for the first time using visual and quantitative comparisons on an ideally suited carbonate outcrop. The results show that the heterogeneity of carbonate rocks cannot be fully simulated using one single algorithm. The operating mode of each algorithm involves capabilities as well as drawbacks that are not capable to match all field observations carried out across the modeling area. Two end members in the spectrum of carbonate depositional settings, a low-angle Jurassic ramp (High Atlas, Morocco) and a Triassic isolated platform (Dolomites, Italy), were investigated to obtain a complete overview of the geological heterogeneity in shallow-water carbonate systems. Field sedimentology and statistical analysis performed on the type, morphology, distribution, and association of carbonate bodies and combined with palaeodepositional reconstructions, emphasize similar results. At the basin scale (x 1 km), facies association, composed of facies recording similar depositional conditions, displays linear and ordered transitions between depositional domains. Contrarily, at the bedding scale (x 0.1 km), individual lithofacies type shows a mosaic-like distribution consisting of an arrangement of spatially independent lithofacies bodies along the depositional profile. The increase of spatial disorder from the basin to bedding scale results from the influence of autocyclic factors on the transport and deposition of carbonate sediments. Scale-dependent types of carbonate heterogeneity are linked with the evaluation of algorithms in order to establish a modeling strategy that considers both the sedimentary characteristics of the outcrop and the modeling capabilities. A surface-based modeling approach was used to model depositional sequences. Facies associations were populated using TGSim to preserve ordered trends between depositional domains. At the lithofacies scale, a fully stochastic approach with SISim was applied to simulate a mosaic-like lithofacies distribution. This new workflow is designed to improve the simulation of carbonate rocks, based on the modeling of each scale of heterogeneity individually. Contrarily to simulation methods applied in literature, the present study considers that the use of one single simulation technique is unlikely to correctly model the natural patterns and variability of carbonate rocks. The implementation of different techniques customized for each level of the stratigraphic hierarchy provides the essential computing flexibility to model carbonate systems. Closer feedback between advances carried out in the field of Sedimentology and Computing Geoscience should be promoted during future outcrop simulations for the enhancement of 3-D geological models.
The in-phase response collected by portable loop-loop electromagnetic induction (EMI) sensors operating at low and moderate induction numbers (<= 1) is typically used for sensing the magnetic permeability (or susceptibility) of the subsurface. This is due to the fact that the in-phase response contains a small induction fraction and a preponderant induced magnetization fraction. The magnetization fraction follows the magneto-static equations similarly to the magnetic method but with an active magnetic source. The use of an active source offers the possibility to collect data with several loop-loop configurations, which illuminate the subsurface with different sensitivity patterns. Such multiconfiguration soundings thereby allows the imaging of subsurface magnetic permeability/susceptibility variations through an inversion procedure. This method is not affected by the remnant magnetization and theoretically overcomes the classical depth ambiguity generally encountered with passive geomagnetic data. To invert multiconfiguration in-phase data sets, we propose a novel methodology based on a full-grid 3-D multichannel deconvolution (MCD) procedure. This method allows us to invert large data sets (e.g. consisting of more than a hundred thousand of data points) for a dense voxel-based 3-D model of magnetic susceptibility subject to smoothness constraints. In this study, we first present and discuss synthetic examples of our imaging procedure, which aim at simulating realistic conditions. Finally, we demonstrate the applicability of our method to field data collected across an archaeological site in Auvergne (France) to image the foundations of a Gallo-Roman villa built with basalt rock material. Our synthetic and field data examples demonstrate the potential of the proposed inversion procedure offering new and complementary ways to interpret data sets collected with modern EMI instruments.