Geothermal energy relies heavily on accurate interpretation of subsurface data to optimize the prediction of the yield and lifetime of a reservoir. Subjective bias remains an overlooked source of uncertainty, even though its significant influence on subsurface data interpretation has been repeatedly proven. This thesis aims to address this subjective bias by providing structured justification for image log and outcrop fracture interpretations. The GRT-1 well at Rittershoffen, France, and the Buntsandstein outcrops in the Vosges region, France, are used as case studies.

A standardized protocol is introduced to provide a structured summary of the expected fractures in the system based on their driving geological processes. The interpreted fractures of three separate interpretations of the GRT-1 well are then linked to these driving processes, after which a composite log of the matching fractures between these is developed. The most prominent and reliable fracture drivers are determined to be the Early Oligocene ENE/SWS extension and the Miocene NW/SE compression. The majority of the picked fractures could be linked to at least one fracture driving process. An overlap in far-field driving processes might indicate reactivation of older fractures.

The protocol offers a promising framework to structure the interpretation of image logs and outcrops. Consequently, discussions on the reliability and justification of the interpretations can be held more constructively, resulting in a more reliable fracture characterization. It is recommended that the protocol be both tested across diverse geological settings and refined to enable more detailed predictions of expected fracture systems.

The presence of wells in reservoir simulations can be represented by utilizing a well model within the finite volume framework of the simulator. A commonly applied approach is the Peaceman well inflow model, which places wells at the center of a specified grid cell of the reservoir model. Nonetheless, several studies have investigated the ability of placing wells off-center. Capturing the exact well position can significantly impact the reservoir response of the simulation model, particularly for heterogeneous reservoirs, as spatial heterogeneity plays a more pronounced role when wells are no longer located at the center of the grid cell. Furthermore, exact well position modeling would allow for more realistic well presentation within the reservoir simulator. Although the performed studies have successfully modeled
wells off-center, they are course-grid approaches. Therefore, this study investigates the application of an unstructured grid-based well model to accurately account for both the exact well location within a grid block and the surrounding reservoir heterogeneity in the calculation of a steady-state well index.

To achieve this, an improved well inflow model is established using Gmsh (three-dimensional finite element mesh generator) and the open Delft Advanced Research Terra Simulator (open-DARTS). The model implements an unstructured grid on a locally structured reservoir geometry, where typically five structured blocks are integrated. The model is verified against the Peaceman well inflow model for a center position and values match the Peaceman well model with a 5% accuracy. The model is validated for different well placements, permeability profiles and a considered number of structured reservoir blocks. Additionally, the validation study includes an accuracy assessment of the model against a full unstructured approach. The improved well index model is finally applied to the wells of the Geothermie Delft (GTD) project, enabling well index estimations based on true well trajectories.

Validation of the model shows that both well placement and local reservoir permeability impact the computed well index. A comparison of the proposed well index evaluation with the fully unstructured model indicates that incorporating more surrounding reservoir blocks within the well index calculation leads to closer correspondence with the fully unstructured approach. Additionally, the study reveals that the spatial discretization method within the finite volume framework used in open-DARTS influences well index values and can result in errors, depending on the choice of discretization approach. Finally, the results of the application of the proposed approach to the real trajectory of wells in the Geothermie TU Delft (GTD) project demonstrate that the improved well index model generally yields lower well index estimations than the Peaceman well model. The effect of this difference is further tested by simulating the full reservoir with the newly obtained well index values. These results depict that the well pressure profile for both the injector and producer varies depending on the well model, especially for later simulation times. The improved well model captures more variations in the pressure profile, emphasizing its capability for more accurate well modeling.

CO2 emissions are a major driver of global warming, contributing significantly to the level of climate change. One promising solution to mitigate this issue is Carbon Capture and Storage, which involves capturing CO2 emissions from industrial sources and securely storing them in reservoirs or aquifers. The study investigates the impact of large-scale reservoir heterogeneity on the efficiency of the CO2 storage by using reservoir models inspired by the Sobrarbe Deltaic Complex outcrop in Ainsa, Spain. Utilizing Google Earth, RRM (Rapid Reservoir Modeling), and CMG software, different reservoir realizations were created, incorporating various levels of petrophysical properties and impermeable layers within the reservoir. The models simulated 100 years of CO2 injection and monitoring. Results indicate that the Base Model, characterized by continuous impermeable layers and high porosity and permeability values, represented the highest cumulative trapped CO2, capturing approximately 3 billion kg of CO2. Models with patchy impermeable layers and lower petrophysical properties values represented lower CO2 trapping efficiency. The results highlight the critical role of reservoir heterogeneity in determining the storage potential and pressure stability of CO2 storage projects, offering valuable insight into the feasibility of carbon storage initiatives.

Natural fractures play a crucial role in many sustainable subsurface applications, particularly in reservoirs with low primary porosity and permeability. Therefore, fracture analysis has become a fundamental aspect of geosciences, often starting with fracture interpretation from borehole image logs. It has been widely recognized that interpretations come with uncertainties; nevertheless, there is a current lack of both quantitative and qualitative understanding regarding differences among interpretations. This study aims to address this gap, by performing a statistical analysis on five interpretations of the same well, highlighting their differences and similarities. Based on the results from the analysis, a workflow was created to reduce uncertainties in fracture interpretations from image logs.

The created workflow was then applied to two wells in the Geneva Basin, Switzerland; associated with a geothermal project aiming to produce heat and electricity from the Upper Cretaceous limestone rocks. Research has shown that these rocks form a tight reservoir, and fluid flow will rely on the presence of fracture networks. In the two wells, a total of eight fracture sets were defined based on movement and relative chronology, and used to reconstruct the fracture history of the basin. This led to the identification of four Mesozoic to Cenozoic stress regimes: 1) a normal or strike-slip regime, 2) a NE-SW reverse regime, 3) a normal regime, and 4) a NW-SE reverse regime. The latter is considered the main deformation event of the region: the Late Miocene fold-and-thrust tectonics. In the Geneva Basin, this event is represented by a pair of NE-SW striking conjugates, which forms the majority of observed fractures. The fifth fracture set is believed to be fault-related and was only observed in one of the wells.

Beyond the regional implications, this study emphasizes the importance of uncertainty reduction in the early stages of fracture analysis, and its effects on establishing a reliable fracture history.

Interpretation of the thermal properties of soils is an important challenge in the field of geo-engineering, for example the development of geothermal energy solutions and for the design of electricity cable routes used for offshore wind farms. Of the thermal properties, the thermal conductivity is of most interest to find, as this determines the long-term thermal response of the soil. The soil volumetric heat capacity is of secondary interest, as this mainly influences the short-term thermal response.

To find the thermal properties of offshore soils, a new in-situ test is being developed, called the heat flow cone penetration test (HF-CPT). This test uses a module that can be attached to a cone penetration test (CPT) which contains a heating element and temperature sensors. In this test, the penetration trough the soil is stopped at a required depth, the heating element is then activated, and the thermal response of the probe is measured. This thesis presents an interpretation method that can predict the thermal conductivity of soils based on the thermal response of the HF-CPT. The interpretation method is validated by conducting laboratory tests in four different materials: moist sand, saturated sand, kaolin clay and a water-agar mixture. With the interpretation method, excellent results are found with the laboratory tests conducted in saturated sand, kaolin clay and the water-agar mixture.

The interpretation method is suitable for offshore testing, as the runtime of the method is short and the storage space is low. The interpretation method gives an accurate prediction for testing duration of about 300 seconds, which is fast when compared to other in-situ tests to measure the thermal conductivity of the soil. With this interpretation method, the HF-CPT can become a successful new in-situ test to determine the thermal conductivity of offshore soils. This way, the thesis contributes to the implementation of geothermal energy solutions and offshore cable routes for wind farms.

Currently, a large part of the energy used to provide heat to heating network comes from gas boilers, a combustion process where 2.2kg of CO2 is emitted for every m^3 of gas. Deep geothermal energy is implemented more in The Netherlands over the last couple of years as a substitute to the conventional boilers and this is a technique that is proven to be working. However, one problem with geothermal energy is the fact that only base load extraction is possible, whereas the heating demand varies throughout the year. During winter there is an energy shortage while during summer there is a surplus. Hence, seasonal heat storage is seen as a promising technique to increase the portion of green energy in heating networks.

High-Temperature Aquifer Thermal Energy Storage (HT-ATES) can bridge the gap between the supply and demand, storing excess produced heat during summer and supplying during the winter months. This research focuses on both the technical aspects as well as the business case of the implementation of such a system in a heating network. Technical simulations are performed where the fluid transport and heat loss processes are modelled. The output of these simulations is used to compare the business cases of a heating network with and without HT-ATES implementation, based on the Levelized Cost Of Heat (LCOH) and total annual CO2 emissions in an economics tool developed in Python. All simulations are based on the situation at the TU Delft Campus, where plans are made for a HT-ATES in the Maassluis formation.

The base case shows a thermal recovery efficiency of 0.75 in cycle four. The LCOH for a project with a lifetime of 30 years is 52 €/MWh (14 €/GJ) when HT-ATES is implemented, compared to 61 €/MWh (17 €/GJ) in the case where only geothermal energy and gas boilers are used to supply the heat. Total CO2 emission reductions are 31%. Based on these values, one can conclude that the situation where HT-ATES is included is the economic scenario.

On top of the case study, a parameter sensitivity study is performed. The results show that storage volume, storage reservoir permeability and temperature differences between the wells are the key geological and operational parameters when assessing the project feasibility. Economic parameters such as the discount rate and gas prices also have a considerable impact on the economic results. The results of the sensitivity analysis shows that the project in Delft is feasible as long as the future average gas price remains above 21 €/MWh and the discount rate does not exceed 18.3%, while keeping the other variables constant.

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.

For this thesis, a probabilistic techno-economic model is developed for deep, direct use geothermal projects in the Netherlands. As a case study, data from the future DAP doublet (TU Delft) is inserted wherein multiple scenarios are researched that model variations in well capacity, energy prices, project design, government policies, brine gas content and heat demand available. For the case study, the model considers technical and economic uncertainties over a period of 50 years. These uncertainties are incorporated in the form of probability distributions and 15000 Monte Carlo iterations. By modeling these scenarios, an overview is developed of the economic performance of a deep district heating project based on the Net Present Value (NPV), Levelized Cost of Heat (LCOH), Internal Rate of Return (IRR), Profitability Index (PI) and payback time. Additionally, an evaluation of the effectiveness of the Dutch subsidy scheme is researched combined with the main financial obstacles associated with geothermal exploitation. The reference scenario of the case study resulted in a 90% probability of a positive NPV with a median PI of 1.5. Higher returns are delivered from scenarios where the subsidy policies were altered in a way that they are more suitable for district heating purposes. A scenario where high constant demand was simulated combined with an extra initial investment for the purpose of heat storage, resulted in the best performing scenario overall. Considering the demand available for this case study, the fixed operational cost, SDE base sum and gas/water ratio are the most important parameters in terms of NPV sensitivity. In order to achieve the desired growth of the Dutch geothermal sector, focus should be aimed at the realization of sufficient heat network deployment, heat storage options and more project specific subsidies.