As an alternative to the industry standard processing of total field data, a Basin-hopping inversion can be used. Another alternative is the use of vector field magnetometers, which can be processed with a Gauss-Newton inversion. Both the Basin-hopping and Guass-Newton inversion consist of a two step inversion. First, an inversion to estimate the centre location and magnetic dipole moment of a point source is carried out, the so called point-source inversion. Second, the retrieved magnetic dipole moment can be used to reconstruct the magnetic moment with a prolate spheroid model, which is called the prolate-spheroid inversion. First, both the TMI and vector data inversion are tested on 3000 noise-free synthetic datasets located in the North Sea where a prolate spheroid with varying shape, orientation and magnetic susceptibility creates an anomaly field. The largest global root mean square (GNRMS) error for the point-source inversion of the Gauss-Newton vector data inversion has a value in the order 10−9 whereas the Basin-hopping inversion for the TMI data returns for only 61% of the cases a GNRMS error in the order 10−7 or lower. The result of the point-source inversion serves as a plateau for the prolate spheroid inversion; when the point-source inversion does not reach the set level of accuracy, it cannot be determined if the prolate spheroid model describes the true object well. For both the TMI and vector data, the UXO was correctly classified in 72% of the 3000 datasets.  Second, comparing the current industry standard to the Basin-hopping point-source inversion only gave inconclusive results. The estimated centre location of both methods are within a 0.15 m radius but the disagreement in magnetic moment leaves an advice on which technique would work better indecipherable.

The Marchenko method is being developed to compute redatuming operators from the reflection response based on a new normalization option at the data level. These operators can be used to retrieve the two-way focusing functions in terms of pressure and velocity, respectively, without effects from the ghost, and free-surface and internal multiples. To compute these operators an estimate of the first arrival of the redatuming operator is required. This can be done using the same model as is used for traditional migration. We then propose to delay the need for such a model and remove free-surface and internal multiples in one step while retaining the primary reflections at the original two-way traveltime. We modify the amplitude by removing the transmission effects at both sides of the equations. The resulting data becomes full focusing functions in terms of pressure and velocity at two-way traveltime, respectively. New datasets can then be generated by picking the value at each focusing level and storing it which are free of the ghost effects, free surface and internal multiples.

The data assimilation process for geothermal reservoirs often relies on well data which primarily offers insights into the immediate vicinity of the borehole. However, integrating geophysical methods can provide valuable information beyond well proximity, possibly enhancing reservoir predictions. Electromagnetic methods can be sensitive to the decreasing conductivity from heat extraction in geothermal reservoirs. A scheme to incorporate electromagnetic data into a data assimilation process for geothermal reservoirs is presented and implemented in this study. First, an ensemble of prior models representing the reservoir uncertainty is used to determine the moments of the resulting temperature field using a forward geothermal simulation. Source and receiver locations are determined by maximizing the distance of the path through the expected temperature changes while ensuring that the source and receiver are not excessively distant. Subsequently, a conductivity model is implemented using an empirical relationship. The expected electric field response can then be simulated using an electromagnetic forward model. To assimilate the data, the Ensemble Smoother with the Multiple Data Assimilation (ES-MDA) method is employed. The findings demonstrate that the incorporation of electromagnetic data provides more information regarding the temperature field, which when combined with the localized data from the production well improves the temperature forecast accuracy of both the production well and the entire reservoir model.

In the last decade, technological advances in the field of multicopters enabled a widespread use of drones that include professional research applications covering a wide field from civil engineering to geosciences and agriculture. In recreational spheres drones became popular for sport and leisure activities like private photography. In geophysics, multicopters opened new doors for easier and cheaper airborne surveying especially with electromagnetic sensors such as geomagnetometers and georadar. In this study we developed an airborne geomagnetic mapping system by combining commercially available components. Our setup consists of a DJI M600 drone with a SENSYS Magdrone R3 sensor mounted on the drone’s landing gear. First measurements showed that data processing requires correcting for the multicopter’s varying orientation during the flight, which impacts the magnetic recordings. The correction of this so-called heading error can be addressed using a scalar calibration scheme, which was originally developed for satellite missions. The calibration is performed by a specific maneuver in flight and compensates the vehicles magnetic influence on the magnetic recordings. We demonstrate how a high data quality can be achieved using a newly developed calibration algorithm for our drone-sensor-setup and how geomagnetic data can be processed in such a way that a reliable qualitative interpretation is achievable. In a case study we conducted an airborne geomagnetic mission in Forel (FR, Switzerland) at a military bombing range near Payerne, which is used as a training facility for target practices. The study area consists of an inaccessible swamp and shallow water zone, where ammunition was documented to be shot and dumped throughout the last century. The results show that our setup allows to reliably locate magnetic anomalies as they are produced by dropped ammunition. Therefore, fast and safe geomagnetic surveying is possible, and it can aid in future not only for UXO detection but also for identifying abandoned landfills and geological structures.

The hazards of unexploded ordnance threaten the increasing marine construction activities nowadays, which increases the importance of unexploded ordnance detection. Research has shown that transient electromagnetic methods can successfully be used to detect unexploded ordnance on land. New equipment is being developed to make marine unexploded ordnance detection also possible. This study aims to determine which targets can be detected and which not in a marine environment through a numerical feasibility study. Building on an existing geophysical simulation framework, it asks: Under which conditions can we detect a conductor on or below the seafloor using a time domain loop source? Through the three-dimensional modelling of Maxwell’s equations, responses were computed for hollow rectangular targets of different burial depths, sizes, wall thicknesses, andwall conductivities. For the analysis of these responses two quantities were introduced, a net effect and a measurability. Evaluation of these quantities demonstrated the individual impact of the tested parameters on these quantities as well as the relative significance of the influence of these parameters. The results included derived relations for the influence of individual parameters on the net effect, as well as limits on the measurability of targets. Arectangular conductor of 0.1 by 0.1 by 0.4 metres or smaller with a wall thickness of 10 millimetre, buried more than 2 metres under the seafloor is not measurable under the noise assumptions made. The relative significance of the parameters was found to be from most to least significant: burial depth, size, wall conductivity, and wall thickness.

Geophysical methods are widely used for hydrocarbon exploration and time-lapse measurements. One method that can be applied in place of or in addition to the routinely used seismic method, is the Controlled-Source ElectroMagnetic (CSEM) method. The work described in this thesis explores various aspects to improve the land CSEM method for exploration and monitoring purposes. Therefore, three separate active land CSEM field experiments, a baseline and two repeat surveys, were carried out over a period of nearly two years at the Dutch Schoonebeek oil field, where heavy oil is produced by injecting steam to reduce the viscosity of the oil. Steam injection and oil production have to be closely monitored to prevent breakthrough of steam to production wells and to detect possible unwanted leakage or contamination of groundwater such that further measures can be taken.@en

Monitoring time-lapse changes inside the subsurface is of great significance to many geotechnical applications, such as storage of gasses in underground geological formations. Minute differences in the seismic wavefield between an initial baseline and a subsequent monitor survey have to be detected in order to observe fluid flow inside subsurface reservoirs. This problem becomes even more challenging when the reservoir is situated underneath a series of complex, highly reflective layers. Such an overburden will generate strong multiple reflections that will interfere with the reflections of the target zone. Ideally, a methodology is designed in order to remove these internal multiples to allow a clear view of the reservoir response for time-lapse analysis. The Marchenko method can redatumthe seismic wavefield to arbitrary depth levels or points in the subsurface, while accounting for all orders of internal multiple reflections. This method, therefore, has great potential to solve some of the time-lapse issues, as it is able to closely examine specific zones of interest in the subsurface without distortions from surrounding layers. Time-lapse studies are often hampered by irregular or imperfect sampling, whereas the Marchenko method relies on densely sampled, co-located sources and receivers. It is, therefore, important that the Marchenko method is able to handle more complex acquisition geometries. This can either be achieved by interpolating the reflection data as a pre-processing step or by correcting for errors inside the Marchenko scheme. Here, point-spread functions are introduced that describe the imperfections in the reflection data. These imperfections distort the focusing and Green’s functions retrieved from the Marchenko method. Next, each iteration of theMarchenko scheme is extended to deblur the imperfect focusing and Green’s functions by multidimensional deconvolution with these point-spread functions. Additionally, a slight modification is required to ensure stability of the new scheme. This new iterative Marchenko scheme is computationally more expensive, but removes all sampling artifacts. Finally, the migrated images of the target zone show significant improvements, when using either the new scheme or interpolation as pre-processing step...@en

Ground-penetrating radar (GPR) is a non-destructive method that images the subsurface using radar. A transmitter generates a radar pulse. This signal propagates into the ground where it reflects against subsurface heterogeneities, and travels back to the surface. A receiver records the reflected signal. The reflected signal contains information about the subsurface. GPR is useful for pavement- and structures- inspection, object-detection, and characterization of the subsurface. For example, many forms of pavement damage of highways originate in the bottom layers and are invisible until the pavement cracks come to surface. GPR can indicate pavement damage before it is visible at the surface, so that preventive actions can be performed where necessary. We work towards developing GPR without the need to transmit any signal. Instead, we use signals that are already available in the air, such as mobile phone signals. A technique called electromagnetic interferometry selects those signals that are measured before they enter the ground and after they reflect. It extracts the path from receiver to subsurface and back to the receiver. The result looks as if the receiver has transmitted a signal, while no signal was transmitted by that receiver. This receiver is called a virtual source. By repeating this step for many receiver combinations we create a virtual dataset. This virtual data provides a well-interpretable image of the subsurface.@en

In this thesis, I study coupled poroelastic waves and electromagnetic fields in layered media. The focus is two-fold: 1. Increase the theoretical and physical understanding of the seismo-electromagnetic phenomenon by analytically-based numerical modeling. 2. Investigate the potential of seismo-electromagnetic interferometry. After presenting the governing equations that form the basis of the theoretical framework, I capture this system into a matrix-vector representation of the wave equation. I first use literature eigenvector sets, which I normalize with respect to power-flux. I then derive new, alternative power-flux normalized eigenvector sets that I prove to be numerically more stable and accurate. The eigenvector sets form the basis of the analytically-based numerical modeling code `ESSEMOD' that I developed to model seismo-electromagnetic wave/field propagation/diffusion in layered-Earth media. The alternative eigenvector set models scenarios with no seismo-electromagnetic coupling correctly, where the literature eigenvector sets fail. In addition, the alternative set properly deals with scenarios where both small amplitude signals and large amplitude signals occur in the record, whereas the literature eigenvector sets result in noise levels masking the small events. The same holds for scenarios with a small seismo-electromagnetic coupling coefficient. I design an effective global reflection scheme that properly describes the primary and multiple reflections in the models. I implement the correct boundary conditions to account for scenarios with a free-surface, and also for scenarios containing fluid/porous medium/fluid transitions. To transform all the seismo-electromagnetic source-receiver combinations in a numerically effective way back from the horizontal wavenumber-frequency domain to the space-frequency domain, I derive and implement explicit Fourier-Bessel transformations. I then validate the developed modeling code in numerous ways. First of all, I compare the results of seismo-EM layer-code modeling in a homogeneous medium with explicit homogeneous space Green's function expressions. This comparison provides a clear validation that the layer-code models the dynamic responses in homogeneous scenarios correctly. Next, I check numerical consistency by carrying out reciprocity checks. I study homogeneous space models, models containing a free-surface and models with interfaces. As a next step, I validate the modeling results of seismo-EM layer-code modeling for typical seismo-electromagnetic laboratory configurations, i.e. models containing fluid/porous medium/fluid transitions. I first compare the purely electromagnetic part of the seismo-EM layer-code with an independently developed purely electromagnetic layered-Earth code. The results match perfectly in both phase and amplitude for full transmission and pure reflection experiments, as well as for a combination of both. I then carry out a seismo-electromagnetic reciprocity test for a fluid halfspace overlying a porous medium halfspace, proving that the coupled poroelastic and electromagnetic fields are modeled consistently and yield the expected results. As a final validation step, I compare ESSEMOD with an independently developed seismo-electromagnetic layered-Earth modeling code. The results display an almost perfect match in both phase and relative amplitudes, and a constant amplitude correction factor of 4 needs to be applied to let the absolute amplitudes match. I then carry out a small feasibility test to study the potential of the seismo-electromagnetic effect for exploration purposes. I investigate different source-receiver combinations for the same model, and focus on the signal strength recorded at different distances from the target depth level. I conclude that for the source-receiver combinations studied, the electric field due to a volume injection monopole source, as well as the magnetic field due to a seismic bulk force source, yield the strongest converted signals. The receiver-distance from the target of interest plays an important role in the signal measurability. The closer the receivers to the target, the higher the signal strengths. However, when the receivers are located too close to the target, the coseismic reflected fields can mask the interface response fields that we are mainly interested in. Next, I study if nature itself can help us to overcome the very low signal-to-noise ratio of seismo-electromagnetic converted fields, by investigating the effects of thin-bed geological structures on the seismo-electromagnetic signal. To investigate the effects of bed-thinning on the seismo-electromagnetic interference patterns, I numerically simulate seismo-electromagnetic wave propagation through horizontally layered media with different amounts and thicknesses of thin-beds. I demonstrate seismo-electromagnetic sensitivity to changes in medium parameters on a spatial scale much smaller than the seismic resolution. By simulating moving oil/water contacts during production, where the oil layer is gradually being thinned, seismo-electromagnetic signals are proven very sensitive to oil/water contacts. I now explore the application of interferometric techniques to the seismo-electromagnetic system, which might eventually lead to an improved signal-to-noise ratio of the weak converted fields. I derive the theory for interferometric retrieval of 2D SH-TE seismo-electromagnetic Green's functions. Using both a circular source configuration and a line source configuration, I show that it is possible to correctly retrieve the dynamic seismo-electromagnetic 2D SH-TE response in a homogeneous medium, using seismic boundary sources only. Using seismo-EM layer-code data, I then show that it is also possible to correctly retrieve the direct shear wave-related causal coseismic field in a homogeneous medium, in both phase and amplitude. To obtain a perfect match in absolute amplitudes, I apply a single linear scaling factor. I finally carry out interferometric experiments in a model containing a single interface at 800 m depth, proving that it is possible to correctly retrieve all 2D SH-TE causal seismic-related direct and reflected coseismic fields, as well as interface response fields, by cross-correlation interferometry, using seismic boundary sources only. These results are promising for the application of 3D seismo-electromagnetic interferometry using seismo-EM layer-code modeling, and later on, in the field. Next, I present an alternative way to effectively decompose fields into their up- and downgoing components and different field types, using recordings at multiple depth levels. I present the theory of this MDL decomposition scheme, followed by successful decomposition of synthetic elastodynamic data sets. I additionally study the implications of laterally-varying media on the horizontal wavenumber-frequency domain MDL decomposition scheme. I demonstrate successful decomposition, using an acoustic approximation and applying a combined multi-component / MDL decomposition approach, of a field data set recorded in Annerveen, in the North of the Netherlands. I address how to effectively use the MDL decomposition scheme in a unified fashion, applied to all wave phenomena including seismo-electromagnetic phenomena. I then make a step towards seismo-electromagnetic inversion, presenting an effective way to carry out a seismo-electromagnetic sensitivity analysis using resolution functions. I start by explaining the theory of resolution functions using a seismo-electromagnetic example. I define the seismo-electromagnetic resolution function for inversion for a bulk density perturbation. I demonstrate the effectiveness of this method by first carrying out a purely electromagnetic sensitivity analysis for a point perturbation in conductivity, located in an isotropic homogeneous half-space. These results are compared with literature results based on analytical homogeneous space Green's function expressions. The result using the seismo-EM layer-code is nearly identical to the literature result. The position of the scatterer is correctly resolved. At the end of this section, I present the results of the fully-coupled seismo-electromagnetic senstivity analysis for a bulk density contrast for a specific source-receiver combination, using single-frequency multi-component line data. I show that the coupled seismo-electromagnetic system is sensitive to a perturbation in bulk density and that the position of the perturbation can be correctly recovered. I finalize this thesis by discussing potential seismo-electromagnetic applications, as well as by providing a brief outlook for future research.@en

Failure of subsea wind turbine cables are the main cause for wind farm downtimes. Furthermore, 80% of insurance payouts to wind farms come from cable repairs and maintenance. Cable tracking is part of the wind farm cables maintenance scheme. Surveys are required for localisation and determining the depth of burial of the cables. Conventional surveying methods have shortcomings when it comes to localising offshore buried power cables, which can be resolved by using electromagnetic methods. From the measured magnetic field created by the cable, its position and burial depth can be inverted. Forward modelling the magnetic response of cables improves the understanding of their electromagnetic behaviour in one dimensional complex submarine environments. Maxwell's equations are the cornerstones of understanding the behaviour of electromagnetic fields, forming the basis of the models. Implementing numerical modelling packages like Empymod accommodate for boundary conditions in one-dimensional layered media to more accurately investigate the magnetic response of electric cables. Land measurements show that Empymod's numerical models can model cables in the accuracy range of 2-15% depending on the distance. New numerical model analyses show the influence of water depth, underlying layers, depth of burial, geometrical complexities and adjacent cables on the magnetic field. Surrounding resistivity contrasts together with changes in water depth change the measured magnitude of the magnetic field by up to 10%. Geometrical complexities have large effects on the magnetic field, sometimes completely changing the expected response. Therefore, twisted and irregularly shaped cables can pose problems when inverting for their position during surveys.

The position of installed submarine power cables is often not accurately known for several reasons. The precise knowledge of the cable position is important for the maintenance process and necessitates the need for cable tracking systems. Current systems are in many cases imprecise and have a short sensing distance, limited to a few meters. A device with better accuracy and sensing range is in demand for enhancing the cable maintenance process. Three new inversion algorithms are introduced which invert the passive electromagnetic _eld created from an injected signal in the target cable. The cable is treated like a line source. This can be seen as an inverse source location _nding problem, while the source time signature is known. The algorithms are tested on synthetic data, modeling a power cable in homogeneous sea water with noise. Several parameters like sensor array, dip angle of the cable and relative position to the system are analyzed. The inuence of soil and the sea surface are studied on synthetic data created from a numerical three-layer forward model. Additionally, a prototype is developed, and di_erent processing schemes are presented and compared. The system is tested with di_erent inversion algorithms on a _eld cable on land. A solution is found which can determine the cable position accurately in sea water with noise terms for a distance up to 6 m. However, this system is highly sensor array dependent. A second inversion method gives a smaller sensing range of 5m but can be used with more versatility. In a di_erent modeled scenario without noise terms, the cable is buried in marine sediments and air is on top of a layer of sea water. The sensors are in the sea water layer. The soil has a great impact on the accuracy of the inversion. In some cable-system-orientations, the absolute error caused by the layered earth exceeds 1 m. The prototype is successfully tested on a _eld cable for di_erent scenarios. An inverted cable position in a global reference frame can be obtained by including a motion sensor.

Nearly-simultaneous-source (blended) acquisition differs from conventional acquisition in that seismic wavefields originating from different sources are allowed to overlap in the recorded seismic traces. This allows more flexibility in deciding the number of shots, the shot density and the effective acquisition time of a survey, but it adds the complication of having to handle blended wavefields. This thesis explores an inversion-based deblending method for wavefield separation in the marine setting. As deblending is usually an underdetermined problem, extra information in the form of additional constraints and regularization is needed to obtain a unique solution with minimal blending-noise leakage. To this end, the proposed method uses the focal transform in combination with sparsity-promoting regularization to discriminate against solutions to the blending equation that are valid, but contain excessive amounts of blending noise. The focusing operation provided by the focal transform will tend to focus the coherent signal to be extracted but will not focus equally well incoherent blending noise. Sparse solutions will tend to retain the high-amplitude focused events but not the lower-amplitude blending noise. A key feature that makes sparse solutions possible is the ability to describe curved events in a subsurface-consistent manner, using few focal domain coefficients. The focal transform can be defined in multiple ways, using one-way or two-way wavefield propagation operators. In the implementations described in this thesis, I use a crude velocity model, based on picked normal-moveout (NMO) stacking velocities, to construct focal operators that can focus surface data onto a set of depth levels where significant reflectors are found. This choice of velocity model is suboptimal for focusing purposes, but is a pragmatic compromise, given that a more detailed velocity model may not be available at the deblending phase of the processing workflow. In principle the focusing and defocusing operations involve the entire dataset, which makes the focal transform computationally expensive to evaluate. An investigated remedy is to use acquisition-specific subsets of the input data to split the problem in smaller chunks, combined with a suitable flavor of the focal transform and focal grid. Another method extension that I discuss is that of using a focal-curvelet hybrid transform for deblending. The main advantage is that events with linear moveout tend to be more sparsely represented in a curvelet basis. However, this comes at the cost of extra computational effort and some difficulty in balancing the contribution of the two transforms to the final solution. I test these approaches on both synthetic and field data, with examples on towed streamer and ocean-bottom-node acquisitions. While in most cases a perceptible amount of blending-noise leakage remains present in the results, a significant amount of blending noise is suppressed. In some cases the deblending process is able to uncover weak events previously masked by strong blending noise. When the hybrid transform is used, the results show a better recovery of events that are filtered out when the focal transform is used alone. Curved near offset events are in some cases also recovered with higher fidelity compared to using the curvelet transform alone. A significant challenge is the sometimes limited focusing for field data and synthetics as a result of trying to approximate the kinematics of complex 3D velocity models with flat-layered models and stacking velocities. The computational cost of the method is also a challenge. While working with data and focal domain subsets helps, additional measures are needed before applying focal deblending on realistically-sized field data. I make several suggestions for modifications of the method and propose extensions for future research.@en