Geological storage of COኼ is a crucial and upcoming technology to reduce anthropogenic greenhouse gas emissions. Due to the buoyant characteristic of injected gas, the security of underground storage is a major concern. To asses the security of COኼ storage, an accurate prediction of the gas plume behaviour is essential. In this study, a fully physical 2D model is developed to describe gas behaviour in a saline aquifer. In particular, we investigate the effect of gas impurities on injectivity, macroscopic dissolution and resulting plume migration. The model includes an investigation of 4-component buoyancy driven multiphase convective flow with miscible convective mixing. For an accurate description of the phase behaviour, a recently developed thermodynamic model based on a combination of cubic Equation of state with activity model has been implemented. The implemented thermodynamic model includes a specific description for the behaviour of water and an activity model describing component behaviour of the aqueous phase making this model more accurate than conventional cubic EoS. The phase behaviour based on this thermodynamic model and a consistent set of physical properties have been implemented in Delft Advance Research Terra Simulator, a new simulation framework developed at TU Delft. The results show that the presence of the gas impurities (tested here) have a negative effect on the solubility of CO2 which in turn reduces the security of gas storage in saline aquifers and increase the risk of leaking. This is the first time when this accurate physical model is applied for large-scale simulation of CO2 sequestration. Additionally a framework regarding the energy cost of the total CO2 sequestration process, from separation to injection, is implemented.

The subsurface of Groningen gas field composed of several faults. The continuous production has been resulting in several micro-seismicity activities, particularly for the past decades. One of the reasons for the production-induced-seismicity is fault reactivation at depth. The fault that initially in the non-active state becomes active and starts slipping due to pore fluid extraction. The modelling of fault reactivation induced by production can be simulated by coupling of flow and geomechanics. The project studies the coupling of flow and geomechanics for an idealistic subsurface model with fault. The flow occurs due to pore pressure depletion and is predicted by solving mass conservation. The corresponding deformation is estimated by momentum balance equation. The observation will be limited to rock deformation that is quantified by effective stress and displacement on the fault due to a pressure change in the subsurface. The simulation is performed using Stanford's Automatic Differentiation General Purpose Reservoir Simulator (ADGPRS). In the proposed model, the flow equation is discretised using finite volume method, and poromechanics is discretised by finite-element Galerkin's approach. Both problems share the same grid model, and there is no error associated with the information exchange. The coupled problem is being solved fully implicitly where flow and mechanics formulation are solved simultaneously. The case study for the simulation is a simplified Groningen subsurface model with a fault zone. The impact of variability in production dynamic on fault reactivation is studied. The variations in production rate and production strategy are applied in different formation configurations. It is found that the correlation between the production rates and the stress state in the subsurface depends on the formation offset. However, the stress field does not depend on continuity of the production scheme. Several aspects including the presence of Gas-Water contact in the model was studied in this project as well.

Parameter and ambiguity estimation in the temporal domain, for arcs of differential phase observations between two persistent scatterers (PS), is a critical part in Persistent Scatterer Interferometry (PSI). Deformation models, used as constraint in the parameter estimation, often do not capture the full extent of the deformation behaviour. This results in a poor separation of signal and noise, and rejection of arcs that do not behave conform the functional model. Previous work assumed that deformation behaviour is stationary and that a full time series can be described with a single set of deformation parameters. In order to develop a more broadly applicable deformation model, this study applies a temporal smoothness constraint during parameter estimation, by assuming that deformation rates are affected by a temporally correlated zero-mean random acceleration. This constraint is implemented using recursive least-squares, similar to Kalman filtering, which also enables efficient updating of arcs when new acquisitions are available. Various kind of deformation types are simulated to create phase observations based on real TerraSAR-X, Radarsat2 and ERS stacks of interferograms. This simulated data is processed using the new recursive estimator and results are compared to that of a batch estimator using a steady-state assumption, to analyse the impact of adding a priori information about the smoothness of the physical signal. Furthermore, a case study on real data is performed on an area where non-linear subsidence has occurred, due to soil remediation. This study presents a mathematical framework for incorporating a priori knowledge about the smoothness of the deformation signal as constraint for parameter and ambiguity estimation. Especially non-linear deformation is better estimated using this method, resulting in a higher success-rate, better separation of signal and noise, and more PS passing quality thresholds. The framework moreover enables efficient updating of existing datasets when new acquisition are available.

The main objective of this study is to quantify interference effects between production and injection wells for geothermal projects that operate within the same reservoir. The secondary objective is to study the time it takes for the reservoir unit to thermally recharge after production has stopped. Two reservoir simulators are benchmarked to decide which one to use for reaching these objectives. The Ammerlaan, Duijvestijn and DAP doublets, all targeting the the Delft Sandstone Member in the West Netherlands Basin, serve as a case study. A literature review is presented to gain a better understanding of the geological history and the structural setting. A box-model of the study area is created and used to benchmark the two reservoir simulators. A static reservoir model is developed in Petrel through seismic interpretation, structural modelling, facies modelling and petrophysical modelling. Populating this static model with dynamic properties allows us to perform reservoir simulations in Eclipse100 and study the propagation of pressure and temperature. A discrete parameter analysis aims to capture the uncertainties that are associated with reservoir modelling and simulation. In this study, data is used from seismic surveys, wireline logs, core studies, a cuttings study and the monthly production volumes of the Ammerlaan and Duijvestijn doublets. It is shown that interference on temperature has a long term (20-30 years) effect on the Duijvestijn (positively) and the Ammerlaan and DAP doublets (negatively). The combined total energy production of the three doublets over 100 years is small with a decrease of 3% due to temperature interference, compared to when running the doublets in stand-alone configuration. Interference on pressure has a short term (days) effect on the achieved flow rate when the injection well cannot reach its target injection rate and is constraint on the maximum allowable pressure at which it is allowed to inject. This occurs under the low permeability scenarios and can be observed when the pressure wave arrives at the neighbouring injector. The Duijvestijn, Ammerlaan and DAP doublets all benefit from this through a combined increase in energy production of 8% over 100 years of production, averaged over all scenarios. During thermal recharge after production, the average reservoir temperature increases asymptotically. Temperature recharges to 96.1% to 97.4% of the initial reservoir temperature after 1000 years of recharging under different thickness and conductivity scenarios. The absence of a thermal influx at the bottom of the reservoir model is limiting the capacity of the reservoir to recharge to its initial average temperature. Interviews are conducted to investigate the implications that the findings of this research have on the policy measures for geothermal projects. Suggestions for changes in policy are made to optimize the recovery of heat in the subsurface.

Geothermal energy is generally seen as a sustainable source of energy and therefore could be part of the solution for the energy transition. However, there is still a lack of clarity about the conditions under which a geothermal system can be used sustainably. This study investigates the sustainable use of a geothermal system. The geothermal production process in a homogeneous geothermal reservoir with one doublet was simulated using SEAWAT. This model provides the possibility to conduct a sensitivity analysis to examine which parameters play an important role in the geothermal production process. The aim of this analysis was to asses the effect on the well temperature and the thermal recharge, i.e. heat flow from the confining layers towards the reservoir. The tested parameters include four geological uncertainties and two production parameters. From the tested geological uncertainties the thickness of the reservoir has the largest effect on the production profile. Also, it has an impact on the effect of all the other parameters tested, especially on the effect of the confining layers. The confining layers play an important role during the simulation of the production process because they control the thermal recharge, and this enhances the lifetime of the geothermal project. The thinner the reservoir, the larger is the effect of the confining layers and the change in its properties and the more impact the thermal recharge has on the production profile. By examining the effect of the production parameters, the aim was to define a sustainable production design and strategy. It was proven that the production rate has a large impact on the lifetime of a geothermal project, and that an increasing well spacing enhances the sustainable use of a geothermal system. To enhance the sustainable extraction of geothermal energy from a geothermal system the production rate should be kept low. When making a production optimisation two rules of thumb apply to maintain a sustainable production. The first rule says that with a doubling of the reservoir thickness, the production rate can be increased by approximately 50%. The second rule says that with an increase of well spacing of 20%, the production rate can be increased by approximately 50%. Overall, this study emphasizes the positive effect of thermal recharge on the production profile and its enhancement on the sustainable use of a geothermal system. We can conclude that with a sustainable production design and strategy the production from a geothermal system can continue for generations.

Geothermal energy is a relatively sustainable energy source of which the essence is to extract heat from hot subsurface rocks. Circulating fluids serve as the transport agent of heat. The contact area between the fluids and the rocks is where the relevant heat transfer occurs, i.e., where the water is heated up. In some geothermal reservoirs, this circulation occurs naturally through porous matrix (mainly sediments) or through heavily fractured formations. Enhanced geothermal systems (EGS) are potentially favorable reservoirs where subsurface permeability is increased by means of artificial stimulation techniques. These stimulation techniques often involve hydraulic fracturing where a limited existing fracture network is expanded or “enhanced” by injecting fluids under high pressure conditions. While the geometry of the generated fractures influences permeability, the effect on heat exchange has received less attention. This thesis discusses the effects of fracture geometry on the heat transfer between solid and fluid. Along with laboratory experiments, numerical simulations were conducted. All investigations were performed on igneous granite rocks. Tensile fractures were generated to allow a fluid flow along the otherwise impermeable rock samples. Several parameters were varied throughout the experiments and simulations including volumetric flow rate, fracture aperture, rock temperature and fracture geometry and surface area in order to investigate their impact on heat transfer processes. Flow rate variations in the experiments have shown that higher flow rates cause the fluid to absorb less heat per unit volume and cause the rock to cool down more extensively, therefore thermal depletion of the reservoir is likely to occur within a shorter time frame. The dependency of exchanged heat on fracture aperture variations (in the range of 0.05 to 0.5 mm) did not yield a clear trend within the experiments, but does so in numerical simulations. Aperture variations in the numerical simulations did not cause notable differences in transferred heat as long as the volumetric flow rate is kept constant. However, as the fluid velocity is kept constant the amount of fluid flushed along the fracture per unit time is affected by varying apertures. This causes a difference in heat transfer as well. Increased fracture surface areas alone (more extensive topology/roughness) have shown a minimal impact on the heat production while a more extensive fracture network (additional branches) has shown notable enhancement in the amount of heat produced. Cooling behavior of the rock has shown correlations with Newton’s law of cooling and suggests a limitation of heat production by the heat conduction occurring within the rock. Experimental findings cannot directly be compared with natural reservoir conditions. The reason for this is a thermal equilibrium that is achieved at each flow experiment, i.e., the heat withdrawn equals the heat resupplied by a heater. In natural reservoirs this is often not the case where a cold front propagates towards the production well and determines the lifetime of how long heat can efficiently be produced from a certain rock mass. This results in an unsteady heat conduction where the heat withdrawn does not equal the heat resupplied.

Time-varying network data are essential in several real-world applications, such as temperature forecasting and earthquake classification. Spatial and temporal dependencies characterize these data and, therefore, conventional machine learning tools often fail to learn these joint correlations from data. On the one hand, hybrid models to learn from time-varying network data combine several specialized models able to capture these dependencies separately, thus ignoring their joint spatio-temporal interactions. On the other hand, state-of-the-art approaches for jointly learning time-varying network data do not exploit the useful prior provided by a graph-time product graph. This prior structural knowledge can aid learning and help the models improve their performance. For this reason, we propose a novel neural network architecture to learn from time-varying network data using product graphs and graph convolutions, thus exploiting this prior during learning. In particular, our architecture (i) learns the most suitable graph-time product graph to represent the time-varying network data and model the graph-time interactions; (ii) performs graph convolutions over this product graph to learn the graph-time interactions from data; (iii) employs graph-time pooling to reduce the dimensionality over layers. To the best of our knowledge, no research has yet attempted to capture spatial and temporal dependencies using graph convolutions over product graphs. Results on synthetic and real-world data show that the proposed method is useful in learning from time-varying network data for both regression and classification tasks. For classification, we cure a real-world dataset for earthquake classification and compare the proposed approach with state-of-the-art models. Results indicate that graph-aware models outperform graph-unaware models on this task. For regression, we evaluate the proposed method on two real-world temperature datasets and compare our architecture with graph-aware and graph-unaware models. Results on the smaller dataset show that linear models outperform neural-network models. On the larger dataset, we find that prior knowledge about graph-time interactions seems to be less beneficial in case of abundance of data. For the synthetic experiments, we find that (i) learning the structure of the graph-time product graph from data improves the performance compared to adopting a fixed type of product graph; (ii) learning sparser graph-time product graphs further improves the performance; (iii) the proposed graph-time pooling technique contributes to the model's generalization capabilities.

Growing interest has been expressed the last decades regarding the Late Cenozoic, gas-bearing sediments of Southern North Sea Basin. Comprising the shallow subsurface of the Dutch offshore sector, these sediments have been deposited by Eridanos fluvio-deltaic system, draining the Fennoscandian and Baltic shield through the present Baltic Sea. Three successful producing fields - A12-FA (2007), F02a-B-Pliocene (2009) and B13-FA (2011)- and five under development have triggered the conduction of several studies in the offshore area. However the deltaic environment has been characterized as highly complex owing to its influence by the onset of Northern Hemisphere Glaciation and thus the processes that governed the system have not become entirely understood. Enhanced cooling followed by the waxing and waning of the glaciers during warmer periods had an immediate impact on sediment supply, accommodation space and mineralogical input. Although the sediments have been studied in terms of chrono-biostratigraphy, no systematic investigation with respect to the three main aforementioned factors as well as the regional sequence stratigraphy and its link to the reservoir deposits has been made up to date. Therefore, this study employed sequence stratigraphy as a method to examine Eridanos conditions of deposition, investigate the interplay between accommodation space and sediment supply and explore the nature of the gas-bearing reservoir sediments. The adopted methodology is comprised of two basic pillars, observation and interpretation. The first records as clearly as possible the observations arise from the sequence analysis while the second extracts the meaningful information and interprets it in terms of temporal and spatial concepts. Using 2D seismic and well log data the basic observations were the stratal terminations, stacking patterns, seismic facies and the shoreline trajectory. Seismic and well log interpretation showed that the delta experienced multiple events of sea level fall which forced the shoreline to regress basinward and caused sediment erosion or non-deposition. These events are bounded by nine time-significant surfaces of subaerial unconformities which constitute the depositional sequences. Normal regression comprised the dominant depositional trend, combined with aggrading-prograding patterns, leading to characteristic alternations of highstand and lowstand system tracts. Three main depositional environments which correspond to open marine turbidites (submarine lobes), delta front and delta top were identified from well logs, core descriptions and the seismic facies analysis. The study suggests that the shallow gas is located in the alternations of silty-sandstones and claystones of the delta plain which comprise the vertical stacking of parasequence topsets within the highstand- lowstand system tracts. Reconstruction of the relative sea level changes and sedimentation rates was made based on a technique introduced by this study. It uses the average thickness of each seismic unit in order to interpolate time between the three known absolute ages obtained by the literature. The graphs showed that the accommodation space was generated by a low rate of sea level rise while sedimentation rates were increasing over time. However the scarcity of time constrains in combination with the uncertainty in the estimation of seismic volumes resulted in a low resolution outcome. A comparison between the findings of this study and those of the existing literature was made. The overall depositional trends and conditions seem to be in accordance with the other surveys. Nonetheless the proposed interplay between accommodation and supply can be assigned as local since the examined area is limited compare to areas studied in literature. Limitations are traced in the quality of the 2D seismic data hampering the observation regarding the relation between the reflectors and the surfaces. Consequently, the study offers an insight into the conditions under which the gas-bearing deltaic sediments were deposited and tries to place them in the established sequence stratigraphic framework. Also it provides information regarding the distribution of the deltaic environments and identification of the reservoir rocks within each setting. The resulting interpretation can be used for prediction of the reservoir formations since the genetically-related packages where they were identified are distributed in a predictable manner within a sedimentary basin.

The production and injection of fluids from and in reservoirs leads to changes in the in-situ stress in the subsurface. This can cause reservoir compaction, subsidence, fault reactivation and / or seismicity. As these effects may greatly influence society it is of importance to find accurate methods to describe them so they can be predicted or even better, mitigated. This thesis discusses a new analytical approach to calculate stress in the subsurface which incorporates the effects of differential compaction on the initiation of fault reactivation. This new approach is named Differential Compaction Loading (DCL) and the reason for its development is due to discrepancies observed between calculations using the Mohr-Coulomb failure criterion, also known as Poro-elastic Loading (PEL), and field observations. Geomechanical modelling was performed to assess fault failure sensitivity to a range of geometrical aspects as well as reservoir and fault properties. From this analysis, focusing on the reactivation pressure at which failure first occurs, an empirical sense of sensitivity was established. It was found that for the examined variations in the geometry the fault dip angle resulted in the largest spread in reactivation pressure. For the examined reservoir and fault properties, the friction angle was found to have the largest sensitivity. With these results it was possible to improve the estimates of essential parameters within the analytical approach, yielding a better fit between analytical and modelled solutions. These solutions lie closer to field observations. Hence, the new method of DCL shows a great improvement in calculation of stresses in the subsurface, compared to the method of PEL. This calibrated analytical approach allows for a quick assessment of the fault stability within a reservoir. Additionally, through the results from the geomechanical model new insights were obtained into the way stresses change and behave when a reservoir is depleted. The rotation of the principal stresses for each level of depletion was quantified and a new definition of the critical fault angle, the dip angle which will fail first, was derived. This links the depletion pressure and related rotation angle directly to a value of the new critical fault angle when DCL is present. Ultimately, these new insights into fault failure behaviour of boundary faults could be a useful tool in the step towards prediction and mitigation of production or injection related seismicity.

As implementation of deep geothermal energy projects in the Netherlands increases, reservoir simulation for these geothermal systems stands to play a key role in understanding how these systems will behave and how large scale projects can be optimised to save cost and reduce risk. In this thesis, an extensive simulation study has been conducted using a new Operator based linearisation simulator (DARTS) on a geological model of the Delft Sandstone Member within the West Netherlands Basin (a prolific geothermal reservoir). The first section of the study outlines the construction of a representative geological model of the Delft Sandstone in Petrel using core, well log and seismic data. The model is quality checked by comparing derived model values with both values recorded in the literature and data from well tests. Following this, a sensitivity and uncertainty study was conducted which examines the effect of changing a wide range of model values and inputs on the thermal performance of production wells. A well placement study was then implemented, examining how well configuration, orientation and distance can affect well performance. Finally, a considerable section of the thesis investigates the role of non-reservoir lithologies in geothermal reservoir simulation and how the heat transfer from these lithologies can be accounted for utilising multi-scale upscaling. The findings of the uncertainty and sensitivity analysis suggest that the primary uncertainty for simulation in the Delft Sandstone is the porosity and intrinsically linked permeability, with the value and spatial distribution of these properties having the largest effect on thermal performance of wells (10’s of years difference in thermal breakthrough). From the well placement study, it was found that different well configurations performed variably according to local reservoir conditions (especially reservoir dip) and that optimum configuration should be decided on a case-by-case basis. It was also found that both well separation/interference and orientation have a key role in controlling the thermal productivity of wells. Finally, the section on non-reservoir lithologies finds that firstly, thermal recharge of injected water from these rocks can have a very large effect on thermal breakthrough time (10’s of years for low N/G reservoir) and must not be ignored in geothermal simulations and secondly, of the three multi-scale upscaling methods implemented to more efficiently simulate conductive heat flux from the non-reservoir rocks, only multiple sub-region upscaling shows significant promise in terms of accurately accounting for heat flux and significantly reducing the number of grid cells. However, the quality of the solution for this method is still strongly linked to fluid flow rate, with higher rates resulting in better solutions.

Drought and subsidence are two out of several water-related urban climate adaptation challenges many cities in the Netherlands currently face. Drought is expected to increase in frequency and extent due to climate change. Therefore, drought is likely to further pressurize (subsiding) urban areas in the coming decades. Although the impact of drought on soft soils and hence subsidence is described in academic literature, in-practice analyzes are limited. Given the expectation of increased drought impacts, as well as the current urge for new housing developments to combat housing scarcity, this research focuses on in-practice drought impacts on subsidence in two soft-soil urban areas in the Netherlands. This research’s objective is to gain insight into drought-induced subsidence in soft-soil urban areas in the Netherlands, in order to better understand drought impacts on subsidence rates in future housing developments on comparable soils. With a better understanding more appropriate site preparation strategies can be applied. The objective is endeavoured by an in-practice analysis of two study areas: a 90s neighbourhood in Diemen and a recently finished urban area in Kampen. Firstly, variations in relative surface levels, observed by InSAR (2015-2019), are compared for dry and wet periods. Afterwards, this subsidence data is separated based upon local characteristics (soil structure, pavement type, vegetation percentage and vicinity of surface water) to analyze their influence on drought-induced subsidence. Lastly, an expert questionnaire is conducted on suggestions for both mitigation and adaptation strategies. Subsidence is not a linear process in time: surface level movements vary due to the soil’s wetting and drying. The extent of soil compaction in dry periods is found to increase with intenser droughts. The extent of soil swell in wet periods is approximately similar for varying wetness extents. This research found that the severe drought of 2018 thereby caused a soil compaction to such extent it could not be balanced with subsequent winter swell, and hence resulted in approximately 1 to 1.5 millimeter of drought-induced subsidence. Drought-induced subsidence is thus a net result of the (change in) seasonal surface level fluctuation. This net result is assumed to be consequence of extensive groundwater level drops, although the exact share of processes and subsidence mechanisms could not be estimated. Moreover, surface level movements are found to be prone to a lag and difference in duration (hysteresis) in comparison to the start and duration of dry and wet periods. Various local characteristics are found to influence drought-induced subsidence. In general more compressible soils show slightly larger surface level movement between dry and wet periods. The (sand) cover thickness is found to be influential on which subsidence mechanisms are triggered during a drought: a cover thickness resulting in groundwater levels to drop to present clay/ peat layers causes shrinkage and/ or peat oxidation additional to clinch. Unpaved surfaces are found to fluctuate more extensively than paved surfaces, but this does not necessarily result in more irreversible subsidence. Furthermore, abundant vegetation might result in extra irreversible subsidence due to its extensive water usage in dense urban areas. Lastly, in the analyzed soft-soil areas the surface waters seem to influence groundwater levels and hence surface level movements only on short distance. Suggestions on feasible enhancing site preparation strategies are given based upon research results and experts’ opinions. The suggested mitigation strategies consist of two approaches in order to hamper the variations in effective stresses and hence minimize the seasonal surface level fluctuation. The first approach focuses on preventing extensive groundwater level variations: increasing storage and infiltration of water, reversed drainage, building crawl-space free and choosing vegetation types based on their water usage. Additionally, it is suggested to apply a sufficient cover thickness (at raises) if soft soil layers are near the surface. This prevents that future extensive groundwater drops within these layers, and thereby limits (seasonal) shrinkage and/ or peat oxidation. The second approach focuses on reducing the top soil’s weight, via lightweight materials or self-carrying constructions. Adapting to drought-induced subsidence starts with measuring/ monitoring surface level movements in order to analyze spatial and temporal trends. Additionally, drought is to be considered to greater extent in subsidence modelling in order to improve subsidence estimations. This can be done by applying variable or lower groundwater levels in estimations of the (change in) effective stresses, at calculations of consolidation or creep. Lastly, urban utility management should focus on long-term costs via e.g. Life Cycle Analysis, and on overlapping maintenance cycles of surface level raising and e.g. sewer pipe replacements. The most important conclusion derived on urban drought-induced subsidence is that despite individual drought impact on subsidence is limited to 1 to 1.5 millimeters, its seasonal occurrence continuously affects surface levels. Moreover, due to climate change drought is expected to increasingly impact surface levels in Dutch soft-soil urban areas in the coming decades. The suggested strategies mainly hamper variations in soil stresses, via fluctuating groundwater levels, and hence drought impacts on soft soils. These strategies help to limit future soil movements and hence result in more climate adaptable soft-soil urban areas. The focus of this research is on qualitative analyses of in-practice data such that significant processes have been disclosed, rather than statistically verifying the results. Consequently, the research initiates further specific studies on statistical verification of drought-induced subsidence, and moreover topics on its mechanisms; its spatial and temporal variation; its measurement and modelling; the influences of local characteristics hereupon; and the effectiveness of the suggested enhanced site preparation strategies.

This research describes how thermal fractures impact the near-wellbore (NWB) region of a depleted gasfield in a carbon sequestration project. As CO2 is usually injected in its supercritical phase, the injection fluid is injected on high pressures and low temperatures. This is in high contrast with the depleted gasfields, which have a low reservoir pressure. The increase in pressure and decrease in temperature causes a thermoporoelastic response, resulting in a reduction of stress inside the reservoir. Once the fracture initiation stress, the so-called fracture stress, is reached, thermal fractures form. Thermal fractures form only due to extensive cooling of the reservoir. The fractures impact the NWB region; due to opening of fractures there is a drop in pressure in the bottomhole pressure (BHP). This increases the reservoir's injectivity. This research uses CMG GEM to model this. The simulation uses a homogeneous box dual permeability model with the model being initialized as a generalized depleted gas reservoir in the North Sea. To model the fractures, the Barton Bandis model is used. This model changes the permeability in a fracture cell once fracture conditions are met. From this model, the moment of fracturing (fracture time), the fracture halflength and the injectivity of the reservoir is researched by performing a sensitivity analysis on key parameters. It is found that the thermal fractures propagate conform to the propagation of the coldest part of the thermal front. The thermal front propagates further once the fracture conditions are met sooner due to fluid highways or when the pressure build up in the reservoir is slower. The sensitivity on the geomechanical parameters showed that only the stress conditions in the reservoir changed, causing the injection constant to change and thus a different fracture time. The way the reservoir reacted to the initiation of fractures was the same; the injectivity was improved similarly for each parameter. The effective permeability (thickness and permeability) determines, together with the injection rate, the way the pressure builds up in the reservoir changes the increase of injectivity due to fracturing slightly. Increasing the reservoir volume causes a slower pressure build-up inside of the reservoir, allowing the thermal front to propagate further and thus longer fracture lengths. Lastly, the sensitivity on the thermal effects showed that a higher difference between the reservoir and injection temperature causes the fracture to be less dependent on the increase of pressure to fracture, resulting in earlier fracturing and longer fracture halflength. The pressure build-up is not changed, so the injectivity remains similar to the basecase scenario. All in all, this thesis gives an insight on how key parameters impact thermal fracture behavior. It also shows what range of parameters can be expected. Combining these two gives an insight on what parameters the focus should be on to better describe the behavior of thermal fractures, to economize the operation by leaving out or including extensive data collection on key parameters. This helps to improve the injection strategy with CO2 injection projects in depleted gasfields.

Displacement control is of utmost importance in deep excavation design and is usually based on numerical modelling, e.g. Finite Element Method (FEM). Numerical methods tend to be more conservative when analysing soil behaviour during deep excavation, whereas for practical and economic reasons this is not favoured. The inverse analysis allows for the identification of the soil parameter set that can provide the measurements observed in the monitoring when it is applied in the model. When performed in a probabilistic concept, it reduces parameter uncertainty and enables the stochastic prediction of future soil behaviour. In this thesis, capabilities and limitations of difference advanced constitutive models are investigated. The Generalized Hardening Soil Small strain model (GHS) presents a positive aspect in modelling soil behaviour during deep excavation with its various stress/strain dependency settings. Because of the uncertainties originating from the size of the domain and limitations of site investigation, the soil parameters can only be shown as probability distributions. In order to make that distribution more accurate, comparative selection of several inverse analysis optimization algorithms is performed. Thereafter, choice of the relevant parameters is done based on the conducted sensitivity analysis and engineering judgement. Having the most competitive optimization approach selected, remote scripting with Python is used to utilise Finite Element (FE) modelling in the 2D Plaxis software. The input parameters are iteratively updated with response observation (diaphragm wall deflections) using the Ensemble Kalman filter optimisation algorithm based on a chosen excavation stage. The re-calibrated parameters are checked with the data, which was used to create synthetic measurements made using the same FE, to perform reliability assessment of the developed Python-based algorithm and investigate its capabilities and limitations. The further development of the presented optimisation method is expected to increase certainty in setting alarm thresholds in the applications of the Observational Method.

In this thesis, we discuss two pattern recognition techniques, template matching, and neural networks. We discuss how these techniques have been used for the development of two earthquake detection algorithms. The first algorithm is based on template matching and the second is based on deep learning. The algorithms are designed for the detection of small <0.5M events in the subsurface of Zeerijp, Groningen. These two algorithms have been compared to assess their earthquake detectability and practicality. The systems have been compared using field data from Zeerijp. The algorithm based on deep learning (a neural network) produced too many false positives considering the amount of seismic data we would like to use it for. The algorithm based on template matching did not produce any false positives during testing. The template matching system has been fed six months of continuous seismic data fromZeerijp. This resulted in the detection of at least 22 new events.

Subsidence of the ground surface, caused by hydrocarbon production, compaction of soft ground layers or other subsidence causes, is a timely topic in the Netherlands. Geodetic measurements of the surface can help us improve our knowledge of the subsurface; this process is called geomechanical inversion. Improved knowledge on the subsurface is needed for example to improve deformation predictions and to safeguard subsurface and surface infrastructure. Related works in this domain use derivatives of geodetic measurements as input for their inversion methodologies, but not the measurements themselves. Performing geomechanical inversion with derivatives of geodetic measurements introduces correlations in the covariance matrix of the data, making error propagation into the geomechanical estimates more complex. Defining a direct relationship between measurements and geomechanical estimates and subsequently inverting this relationship, makes the error propagation less complex. This thesis presents a new methodology that can be used to estimate reservoir geomechanical parameters through direct inversion using measurements from optical leveling campaigns. In the context of this thesis, a direct inversion is an inversion of a linear relationship between data and measurements. In this thesis, we propose and test a workflow for the estimation of a simplified set of geomechanical parameters. Part of the workflow is an extensive testing procedure of the geodetic data. A Geertsma nucleus-of-strain model is used to express a source parameter term in function of optical leveling measurements. This source parameter term is a lumped term and consists of a volume term, a pressure term, and several elastic rock parameter terms. This system is inverted using a Tikhonov regularization with a spatial penalty term. The methodology is applied to optical leveling data from a case study (the Norg and Roden gas fields in the northern Netherlands) and shows promising results. The RMS between modeled and measured subsidence for the most promising parameterization is 3.0 mm. The proposed methodology leads to geomechanical estimates with formal quality description, that could improve geomechanical models and subsequently leads to a better understanding of the subsurface and better subsidence predictions. The geomechanical parameter that is estimated is lumped and without additional information, it is impossible to differentiate between individual compaction parameter terms. Feeding the problem more information might also relax the need for regularization but can lead to the introduction of bias. We believe that the framework proposed in this work can be a good starting point for further research that uses geodetic measurements directly as input for a geomechanical inversion.

Geothermal energy can be a great solution for the downscaling fossil fuel society, but it can potentially lead to seismic hazards. A doublet system, with a cold water injection well and a hot water production well, alters the stress situation in the subsurface, which can result in (micro)fracturing and fault reactivation. Even in water filled reservoirs, aquifers, with relatively good permeabilities, the acting in-situ stress on already existing fault can be changed such that there can be a seismic hazard. The three dominant phenomena that influence the fault reactivation and are triggered by geothermal water injection and production are the direct pore pressure change, poro-elastic stress change and thermo-elastic stress change. To predict and subsequently diminish or limit the seismic hazards in geothermal operations, Seismic Risk Analysis (SRA) are to be completed before such operations can take place in an often seismic risky location, like densely populated areas. In the current (Dutch) geothermal environment mainly three SRA’s are used; “Methodiek voor risicoanalyse ontrent geinduceerde beving door gaswinning” by the Staatstoezicht op de Mijnen (SodM), “Defining the Framework for Seismic Hazard Assessment in Geothermal Projects V0.1” by Q-con/IF-technology [6] and an Excel-model created by TNO/Geomech. By investigating and reviewing these three SRA’s in this thesis their shortcoming and limitations are exposed, for example their lack of physical foundation and explanatory results. From the foundation of the currently excising SRA’s a new alternative SRA, which corresponds in some steps with the older SRA’s, is created in this thesis. In order to successfully finish the new SRA one of the three steps should be completed, starting with SRA Step 1. In this first step of the new SRA a new Physical Screening Model (PSM) is created. When completing the SRA an indication of what type of seismic monitoring there should be done during production. This PSM is a fairly quick and simple in its use but provides sufficient informative data to investigate the seismic hazard for most geothermal operations in the Netherlands. In four different steps in the PSM, the potential reactivation of faults over the whole reservoir during production will be evaluated. With the spatio-temporal evolution of ΔP, Δσporo, ΔT (PSM Step 1) this model can predict fault reactivation at any place and time inside the reservoir, while it can also look at which parameter dominated this reactivation. In this thesis the physical background and results of the PSM will be explained step by step. Eventually there are three final results from the PSM; a Mohr plot that predicts if certain faults (at certain locations) are stable or not and the maximum Moment magnitude (Mw) in combinations with the Peak Ground Velocity (PGV), which predict the severity of a possible event. Sensitivity analyses and case studies done with the PSM in this thesis show the influence of dominating parameters, like permeability and injection rate, and what results can be expected when using this model.

Groundwater extraction could be a crucial driver of subsidence; a phenomenon that has had, and still has, implications for the landscape, infrastructure, and environment. Vitens, a Dutch drinking water company, expects an increase of 10% in drinking water demand in 2040 for the Netherlands. This may intensify Subsidence due to Groundwater Extraction (SGE) in the future. The objective of this research is to quantify the historical and future effects of groundwater extraction on subsidence at Vitens extraction site ”Groenekan” in the Province of Utrecht. In this thesis, a methodology is developed to assess whether Vitens can responsibly expand Groenekan groundwater extraction from 5.0 Mm3/yr to 10.0 Mm3/yr. The groundwater extraction is situated in a rural polder landscape where two subsidence-sensitive soil layers are present: a 1 m thick Holocene peat/clay top layer and a 12 m thick aquitard (Waalre clay) at a depth of -48 m NAP. Under this aquitard, Vitens currently extracts ∼5.0 Mm3/yr of drinking water from the second aquifer. Next, a groundwater model is used to study the lowering of the groundwater level and hydraulic head due to the extraction. Subsequently, the effect of both lowerings has been quantified for four subsidence processes, 1) Biochemical Degradation of Organic Material (BDOM), 2) shrinkage, 3) consolidation, and 4) creep. Groundwater lowering affects all four processes, whereas head lowerings only affect consolidation and creep. Occurred subsidence from the start of the groundwater extraction and for eight future scenarios is calculated with the aid of the groundwater model output, analytical approaches and a 2D subsidence model. The cumulative subsidence of these four processes is labelled as SGE. From 1961 to 2023, the groundwater level at Groenekan is lowered with 33 and 60 cm for 5.0 and 10.0 Mm3/yr extraction discharges respectively. In the second aquifer, hydraulic head lowerings of 1.5 to 2.9 m with a symmetrical influence circle are observed at Groenekan. In a radius of 500 m around Groenekan, significant groundwater level lowerings are found, which enforces compaction processes in the form of BDOM and shrinkage. For the period 1961 to 2023, assuming a 1 m thick clean peat Holocene top layer reveals ∼16 cm of potential BDOM. However, potentially ∼11 or ∼18 cm of shrinkage would occur over the same period assuming a clean clay or organic clay Holocene soil type respectively. Compression of the Holocene and Waalre layers due to consolidation and creep has contributed ∼10 times less to SGE around Groenekan compared to compaction due to BDOM and shrinkage. Within a 500 m radius of Groenekan, SGE is noticeable; beyond that, SGE is negligible. The maximum total subsidence through compression is ∼1.0 cm over a period of 62 years (from the start in 1961 to 2023). Generally, consolidation contributes 75% to the total subsidence due to compression, whereas creep is responsible for 25% of the compression. Sensitivity analyses reveal that the Holocene soil type and the thickness of the soft soils are the most sensitive parameters in calculating the final subsidence. Clean peat soil gives a high potential subsidence rate, whereas sand soils hardly subside. Variations in groundwater level and head lowerings are found to be least sensitive. Within the Groenekan system, the 1 metre Holocene thickness is the limiting factor in the groundwater level lowering, since no additional subsidence effects are found if the groundwater level drops below the Holocene layer. The future scenario of 10.0 Mm3/yr + an extreme climate shows ∼1.2 cm of consolidation and creep in the Holocene and Waalre layers over the period 1961 to 2100 (139 years). The base scenario of 5.0 Mm3/yr gives of ∼0.9 cm of subsidence, which results in ∼0.3 cm of additional subsidence. This extra subsidence value is negligible over a period of 139 years compared to other locations in the Netherlands with dozens of centimeters of subsidence. Though, BDOM and shrinkage can potentially cause centimetres of subsidence in the Holocene on the long-term due to groundwater level lowering. In conclusion, expansion of Groenekan from 5.0 to 10.0 Mm3/yr is considered to be responsible from a subsidence perspective as long as BDOM and shrinkage are exercised with extreme caution. Future studies on the effects of extended droughts and the surface water system on the groundwater level are suggested to better distinguish the total subsidence from SGE. Lastly, it is recommended to Vitens to extract groundwater from deep, confined aquifers with a sandy top layer for maximal SGE mitigation.