P. Rulff
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14 records found
1
Computational electromagnetic geophysics for groundwater system studies
A review of established practices and recent advances
Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies.As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.
On the TU Delft campus, we aim to drill a borehole of around 4.5 km depth to be used for the exploration, observation, and monitoring of subsurface processes that will be part of a larger research infrastructure under development. This so-called urban energy laboratory includes – in addition to the deep multi-use borehole – a well-instrumented geothermal doublet drilled in 2023, reaching to a depth of 2.2 km; a local seismic monitoring system (installed in 2022); an ultra-sensitive portable seismic monitoring array; and a high-temperature aquifer heat storage system (HT-ATES), for which a pilot well was drilled in 2024. With this urban energy laboratory, we want to tackle problems and better understand processes related to multiple and/or competing subsurface uses in urban environments. The deep exploration and monitoring borehole is designed specifically to monitor fluid and/or flux movement in 3D with unprecedented precision, aiming to understand the propagation of the geothermal cold front and reservoir pressures.
During the 3 d International Continental Scientific Drilling Program (ICDP)-sponsored UrbEnLab workshop, 75 scientists from 17 countries met in Delft, the Netherlands, in June 2024 to prioritize the scientific ambitions of the deep exploration and monitoring borehole and to discuss potential techniques that could be applied to tackle them. Assessing the life cycle of a geothermal system situated in a complex heterogeneous sedimentary system was defined as the broad aim, with revealing the detailed flow field established being a key priority. ...
On the TU Delft campus, we aim to drill a borehole of around 4.5 km depth to be used for the exploration, observation, and monitoring of subsurface processes that will be part of a larger research infrastructure under development. This so-called urban energy laboratory includes – in addition to the deep multi-use borehole – a well-instrumented geothermal doublet drilled in 2023, reaching to a depth of 2.2 km; a local seismic monitoring system (installed in 2022); an ultra-sensitive portable seismic monitoring array; and a high-temperature aquifer heat storage system (HT-ATES), for which a pilot well was drilled in 2024. With this urban energy laboratory, we want to tackle problems and better understand processes related to multiple and/or competing subsurface uses in urban environments. The deep exploration and monitoring borehole is designed specifically to monitor fluid and/or flux movement in 3D with unprecedented precision, aiming to understand the propagation of the geothermal cold front and reservoir pressures.
During the 3 d International Continental Scientific Drilling Program (ICDP)-sponsored UrbEnLab workshop, 75 scientists from 17 countries met in Delft, the Netherlands, in June 2024 to prioritize the scientific ambitions of the deep exploration and monitoring borehole and to discuss potential techniques that could be applied to tackle them. Assessing the life cycle of a geothermal system situated in a complex heterogeneous sedimentary system was defined as the broad aim, with revealing the detailed flow field established being a key priority.
The pathways of fluids and mantle-originated carbon dioxide in the seismically active Ohře (Eger) Rift system appearing as mofettes at the surface are currently subject to investigation, especially by the International Continental Scientific Drilling Program “Drilling the Eger Rift”. If the aquifers show significant contrast in electrical resistivity to the host rocks, they can be investigated with geo-electromagnetic methods. However, imaging complex fluid and CO 2 pathways in detail in near-surface structures is challenging, because, in contrast to the background stratigraphy, they are often oriented in near-vertical directions. Therefore, we aim to investigate how the shallow aquifer structures can be examined best with an inductive electromagnetic method. For this purpose, we collected radio-magnetotelluric data in the Hartoušov mofette field and evaluated them by two- and three-dimensional inversions. Data from a nearby magnetotelluric station, drill hole data, gas flux measurements and electrical resistivity tomography models were used to assess the reliability and robustness of our inversion results. We concluded that the near-surface fluid reservoirs are adequately depictable, while the migration paths of gaseous CO 2 cannot be traced properly due to a lack of resistivity contrast. Our model analyses suggest that imaging the given geological setting with fluids and gases ascending in anastomosing pathways benefits from a fine-scale three-dimensional inversion approach because the fluids mostly appear as local conductive reservoir-like anomalies, which can be falsely projected onto the profiles during inversion in two dimensions. The resistivity models contribute with detailed images of the near-surface aquifers to the geodynamic model of the Ohře Rift.
elfe3D v1.0.1
Modelling with the total electric field approach using finite elements in 3D
Geoelectrical and electromagnetic imaging methods applied to groundwater systems
Recent advances and future potentials
Our study examines state-of-the-art approaches in modelling and instrumentation of induced polarisation and electrical resistivity tomography, as well as time- and frequency-domain electromagnetics and ground-penetrating radar methods. We review recent impactful and innovative groundwater case studies where the above-mentioned methods were applied and further developed. Emphasising the combination of geoelectrical and electromagnetic methods, the studies provide insights into the variation of electrical subsurface properties at different scales, contributing to an improved understanding of the hydrological dynamics in the studied areas. Furthermore, we provide an outlook on the potential for applying geoelectrical and electromagnetic imaging techniques for large-scale groundwater investigations in the exascale computing area. ...
Our study examines state-of-the-art approaches in modelling and instrumentation of induced polarisation and electrical resistivity tomography, as well as time- and frequency-domain electromagnetics and ground-penetrating radar methods. We review recent impactful and innovative groundwater case studies where the above-mentioned methods were applied and further developed. Emphasising the combination of geoelectrical and electromagnetic methods, the studies provide insights into the variation of electrical subsurface properties at different scales, contributing to an improved understanding of the hydrological dynamics in the studied areas. Furthermore, we provide an outlook on the potential for applying geoelectrical and electromagnetic imaging techniques for large-scale groundwater investigations in the exascale computing area.
We adopt a preconditioned non-linear conjugate gradient algorithm to enable three-dimensional inversion of impedance tensor and vertical magnetic transfer function data produced by multiple sets of two independent active sources. Forward simulations are performed with a finite-element solver. Increased sensitivities at source locations can optionally be counteracted with a weighting function in the regularization term to reduce source-related anomalies in the resistivity model. We investigate the capabilities of the inversion code using one synthetic and one field example. The results demonstrate that we can produce reliable subsurface models, although data sets from single pairs of independent sources remain challenging. ...
We adopt a preconditioned non-linear conjugate gradient algorithm to enable three-dimensional inversion of impedance tensor and vertical magnetic transfer function data produced by multiple sets of two independent active sources. Forward simulations are performed with a finite-element solver. Increased sensitivities at source locations can optionally be counteracted with a weighting function in the regularization term to reduce source-related anomalies in the resistivity model. We investigate the capabilities of the inversion code using one synthetic and one field example. The results demonstrate that we can produce reliable subsurface models, although data sets from single pairs of independent sources remain challenging.
We use a new approach integrating capacitive electrodes in composite borehole casings. Tests in shallow boreholes have shown comparable results to standard electrodes. Integrating the capacitive sensors in the composite borehole casing is rather time- and cost-intense requiring pre-drilling installation and specially designed electronics. Therefore, we want to optimise the electrode placement along the borehole trajectory. We simulate vertical electric fields at closely spaced receivers along the borehole trajectory for different subsurface scenarios originating from resistivity changes introduced by injecting and extracting hot fluids. Applying the Ramer–Douglas–Peucker algorithm, we determine which electrode locations and combinations are optimal to record resulting variations in the vertical electric field component. The proposed methodology for optimal electrode placement is promising to improve monitoring efficiency in geothermal applications, ensuring sustainable and effective operation over extended periods. ...
We use a new approach integrating capacitive electrodes in composite borehole casings. Tests in shallow boreholes have shown comparable results to standard electrodes. Integrating the capacitive sensors in the composite borehole casing is rather time- and cost-intense requiring pre-drilling installation and specially designed electronics. Therefore, we want to optimise the electrode placement along the borehole trajectory. We simulate vertical electric fields at closely spaced receivers along the borehole trajectory for different subsurface scenarios originating from resistivity changes introduced by injecting and extracting hot fluids. Applying the Ramer–Douglas–Peucker algorithm, we determine which electrode locations and combinations are optimal to record resulting variations in the vertical electric field component. The proposed methodology for optimal electrode placement is promising to improve monitoring efficiency in geothermal applications, ensuring sustainable and effective operation over extended periods.
Using edge-based vector finite-element approximations on tetrahedral meshes and a preconditioned non-linear conjugate gradient algorithm, we invert for impedance tensor elements generated by a set of two coincident perpendicularly oriented horizontal electric or horizontal magnetic dipole sources. Depending on the number and locations of sources and the choice of impedance tensor components used for inversion, the sensitivity patterns can differ significantly. Measurement setups with a small number of sources, but many receiver stations at the surface covering near-field, transition zone and far-field, are often deployed for land-based controlled-source electromagnetic measurements. Such a setup can result in accumulated sensitivities close to the sources and receivers, which implies strongest model updates in these regions and can mislead the inverse algorithm to a search direction, where no physically meaningful model can be produced nor the data are fitted.
In order to mitigate the influence of strong sensitivities near sources and receivers on the inversion process, we apply an efficient preconditioner and customisable weights in the model regularisation matrix. The preconditioner is updated with the Broyden-Fletcher-Goldfarb-Shanno algorithm using the diagonal of the approximate Hessian matrix as start preconditioner. The latter is computationally expensive to obtain, but aims at finding a favourable search direction for the inverse algorithm already in early iterations and distributing the model update more evenly in the domain. To account for the sensitivity loss with depth, we implemented a depth weighting functional in the model regularisation term. The approach is based on counteracting the exponential and geometrical decay of the electromagnetic fields with depth and distance from the sources. In practical, we increase the smoothing in the shallow part of the model close to the source locations, where no structure is expected. We present synthetic examples indicating that this approach is an efficient way of helping the inversion to converge, obtaining a reliable model and resolving structure at depth. ...
Using edge-based vector finite-element approximations on tetrahedral meshes and a preconditioned non-linear conjugate gradient algorithm, we invert for impedance tensor elements generated by a set of two coincident perpendicularly oriented horizontal electric or horizontal magnetic dipole sources. Depending on the number and locations of sources and the choice of impedance tensor components used for inversion, the sensitivity patterns can differ significantly. Measurement setups with a small number of sources, but many receiver stations at the surface covering near-field, transition zone and far-field, are often deployed for land-based controlled-source electromagnetic measurements. Such a setup can result in accumulated sensitivities close to the sources and receivers, which implies strongest model updates in these regions and can mislead the inverse algorithm to a search direction, where no physically meaningful model can be produced nor the data are fitted.
In order to mitigate the influence of strong sensitivities near sources and receivers on the inversion process, we apply an efficient preconditioner and customisable weights in the model regularisation matrix. The preconditioner is updated with the Broyden-Fletcher-Goldfarb-Shanno algorithm using the diagonal of the approximate Hessian matrix as start preconditioner. The latter is computationally expensive to obtain, but aims at finding a favourable search direction for the inverse algorithm already in early iterations and distributing the model update more evenly in the domain. To account for the sensitivity loss with depth, we implemented a depth weighting functional in the model regularisation term. The approach is based on counteracting the exponential and geometrical decay of the electromagnetic fields with depth and distance from the sources. In practical, we increase the smoothing in the shallow part of the model close to the source locations, where no structure is expected. We present synthetic examples indicating that this approach is an efficient way of helping the inversion to converge, obtaining a reliable model and resolving structure at depth.
Having two modelling codes and their developers available at the same place, gives us the unique opportunity to compare the approaches in a very detailed way. Our spectral-element as well as our finite-element solution is based on Galerkin’s weighted residual method and we solve the electromagnetic diffusion equations for the total electric field on the element edges.
The main differences between both codes are the choice and order of the interpolation functions and the discretisation of the modelling domain employing hexahedral and tetrahedral elements. While the tetrahedral meshes used in our finite-element approach are known for being able to properly resolve complex structures in the subsurface, this issue is addressed in the spectral-element method by utilising curvilinear instead of orthogonal hexahedral elements.
In this contribution, we focus on the comparison of both approaches for a simple 1D model and a complex 3D model in terms of accuracy, effort in mesh generation and computational resources such as simulation time and memory requirement. Moreover, we contrast the influence of mesh discretisation on the solution for the two methods as well as the order of approximation. A preliminary test simulation of a model consisting of a conductive body buried within a resistive background covered by a thin conductive layer yielded comparable results in terms of accuracy. It also revealed significant differences concerning the mesh discretisation meaning the solution's dependency on the meshing of the model domain. ...
Having two modelling codes and their developers available at the same place, gives us the unique opportunity to compare the approaches in a very detailed way. Our spectral-element as well as our finite-element solution is based on Galerkin’s weighted residual method and we solve the electromagnetic diffusion equations for the total electric field on the element edges.
The main differences between both codes are the choice and order of the interpolation functions and the discretisation of the modelling domain employing hexahedral and tetrahedral elements. While the tetrahedral meshes used in our finite-element approach are known for being able to properly resolve complex structures in the subsurface, this issue is addressed in the spectral-element method by utilising curvilinear instead of orthogonal hexahedral elements.
In this contribution, we focus on the comparison of both approaches for a simple 1D model and a complex 3D model in terms of accuracy, effort in mesh generation and computational resources such as simulation time and memory requirement. Moreover, we contrast the influence of mesh discretisation on the solution for the two methods as well as the order of approximation. A preliminary test simulation of a model consisting of a conductive body buried within a resistive background covered by a thin conductive layer yielded comparable results in terms of accuracy. It also revealed significant differences concerning the mesh discretisation meaning the solution's dependency on the meshing of the model domain.
Magnetotellurics in the Eger Rift
An overview of subsurface imaging of different tectonic features
3D CSEM Forward Modelling
Testing Adaptive Mesh Refinement Approaches on an Ore Body Model
In mineral exploration, ore bodies often exhibit a strong resistivity contrast and sometimes a non-negligible contrast in magnetic permeability to their host rock. Accurate 3D modelling of electromagnetic measurement setups is therefore needed for feasibility studies and incorporation of the forward modelling in inversion approaches. To obtain sufficiently accurate solutions in time- and memory efficient computations, one option is to employ guided mesh refinement strategies.
The so called goal-oriented adaptive mesh refinement method aims at designing a mesh, which is fine where necessary and coarse where discretisation errors do not influence the accuracy of the solution at the points of interest, typically the receiver sites. We apply the total electric field approach and first order Nédélec basis functions as interpolation functions defined on the edges of the finite elements to solve the electromagnetic diffusion equations. Thus, we achieve continuity of the electric and magnetic fields inside the elements and tangential to the edges and faces. However, the continuity of the normal components of current density and magnetic flux density across element interfaces cannot be ensured, resulting in small errors in the solution. We calculate these so called “face-jumps” and use them in combination with the elemental residuals and the dual solution of the problem to obtain error estimators that guide our adaptive refinement approach. The dual problem simulates influence sources at the receiver sites to weight the elemental error estimators with their influence to the solution accuracy at the receivers.
We utilise a model of an iron ore body in central Sweden with a known magnetic permeability contrast and unknown electrical resistivity to study the behaviour of our implemented adaptive mesh refinement approaches. This is combined with a feasibility study to investigate the detectability of the ore body with CSEM.
From literature examples on magnetotelluric forward modelling we know, that the error estimator based on the continuity of the normal current density shows robust performance, when modelling for electrical resistivity. We observe the same behaviour after adapting it to the controlled-source problem. The error estimator using the continuity of the magnetic flux density seems mathematically most promising to improve the mesh, when variations in magnetic permeability are significant. Numerical experiments with the ore body model indicate, that best results can be achieved, when mesh refinement guided by both error estimators is applied. ...
In mineral exploration, ore bodies often exhibit a strong resistivity contrast and sometimes a non-negligible contrast in magnetic permeability to their host rock. Accurate 3D modelling of electromagnetic measurement setups is therefore needed for feasibility studies and incorporation of the forward modelling in inversion approaches. To obtain sufficiently accurate solutions in time- and memory efficient computations, one option is to employ guided mesh refinement strategies.
The so called goal-oriented adaptive mesh refinement method aims at designing a mesh, which is fine where necessary and coarse where discretisation errors do not influence the accuracy of the solution at the points of interest, typically the receiver sites. We apply the total electric field approach and first order Nédélec basis functions as interpolation functions defined on the edges of the finite elements to solve the electromagnetic diffusion equations. Thus, we achieve continuity of the electric and magnetic fields inside the elements and tangential to the edges and faces. However, the continuity of the normal components of current density and magnetic flux density across element interfaces cannot be ensured, resulting in small errors in the solution. We calculate these so called “face-jumps” and use them in combination with the elemental residuals and the dual solution of the problem to obtain error estimators that guide our adaptive refinement approach. The dual problem simulates influence sources at the receiver sites to weight the elemental error estimators with their influence to the solution accuracy at the receivers.
We utilise a model of an iron ore body in central Sweden with a known magnetic permeability contrast and unknown electrical resistivity to study the behaviour of our implemented adaptive mesh refinement approaches. This is combined with a feasibility study to investigate the detectability of the ore body with CSEM.
From literature examples on magnetotelluric forward modelling we know, that the error estimator based on the continuity of the normal current density shows robust performance, when modelling for electrical resistivity. We observe the same behaviour after adapting it to the controlled-source problem. The error estimator using the continuity of the magnetic flux density seems mathematically most promising to improve the mesh, when variations in magnetic permeability are significant. Numerical experiments with the ore body model indicate, that best results can be achieved, when mesh refinement guided by both error estimators is applied.