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.

This research identifies and provides a relative ranking of the parameters that control the thermal breakthrough time of a geothermal doublet. The ranking is based on simulations modelled by a three-dimensional model build in COMSOL Multiphysics with a simulation duration of 50 years. The model is a nonisothermal, isotropic, cuboid consisting of a sandstone aquifer surrounded by identical impermeable layers. The ranking is derived based on a solution space covering a minimum, maximum and mean value for each of the simulation parameters. The investigated simulation parameters are the density, porosity, permeability, thermal conductivity and specific heat capacity of both the surrounding rock formations and the aquifer, the depth and thickness of the aquifer, the flow rate, injection temperature and the well spacing. The mean values of the solution space form the base model, from which the parameters will divert separately to monitor the model’s behaviour on the varying parameters. In this research, the breakthrough time is defined as the time at which the production temperature is decreased by 1% to 99% of its initial value. The ranking is based on comparing the proportional change of each parameter from the base model to the change in breakthrough time. The results show that the thickness, flow rate and the well spacing are the most crucial parameters influencing the thermal breakthrough time of a reservoir. Overall, the flow rate has the greatest impact, with a decrease of 16.7 years between a flow rate of 150 m3/hour and 250 m3/hour. In addition, the surrounding rock parameters have a notably smaller impact on the thermal breakthrough time compared to the reservoir rock and process parameters. The surrounding rock parameter with the relatively largest impact on the breakthrough time is the specific heat capacity, which is only a change of 0.2 years between a specific heat capacity of 1150 and 1250 Jkg-1K-1.

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.

In a future scenario, the successful development of geothermal industry will result in the large-scale deployment of new deep geothermal projects. In highly populated areas, such as the Netherlands, such a development will lead to a dense grid of neighbouring licenses. In such a situation a new project requires careful design and planning as the available subsurface space can become scarce, leading to the potential thermal interference with the neighbouring licenses and competing usage of the resources. Interference can cause the reduction of lifetime, produced energy, and the profitability of neighbouring projects. Therefore, it becomes important to consider the thermal interference while designing these systems in such dense areas to be able to obtain maximum energy and profit without hindering neighbours. This research project assesses the question of thermal interferences in neighbouring geothermal systems using a numerical simulation approach regarding what parameters are ideal for optimisation in neighbouring systems and what parameters should be monitored. To generate a numerical model capable of describing and predicting the effect of thermal interference the software package COMSOL Multiphysics 5.4 was used. The physics of fluid flow and heat transfer in porous media is applied to the reservoir model, and the finite element method is used to approximate the solution of these equations. Sensitivity analyses are performed on all input parameters as a post-processed simulation to control their influence on the output performance. The input parameters are divided into two categories; first, operational-controlled parameters: start time, injection temperature, injection/production flow rate, well spacing, well distance to the license border, and second, natural-controlled parameters including permeability and its anisotropy as kx/ky ratio. At the end of the parametric sensitivity analysis, an economic model is used as an instrument to evaluate how these input parameters can affect the long-term project feasibility. In this study, we present the results of global comparisons between each parameter while incorporating all measurement control (lifetime, cumulative energy and NPV). The results from the 3D qualification, the correlation between measurement controls and the reference base case study are used as background for this comparison. Our results show that the injection temperature and well spacing are ideal designed parameters to optimise profitability because the negative effect on the neighbour is only 1% for every 10°C reduction injection temperature and increasing 300 m of well spacing. On the other hand, injection / production flow rate is the most influential parameter that must be monitored in neighbouring production areas.

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.

The United Nations’ Paris Agreement forces nations and industries to transition from conventional hydrocarbon-based energy sources to more sustainable and less-emitting alternatives such as geothermal energy. Geothermal doublets are used to provide a source of green heat to greenhouses and residential buildings. In industry, reservoir simulators are used to make predictions about the energy production and thermal lifetime of such a geothermal project; however they can be computational expensive. Upscaling approximates the expensive fine-grid simulation and reduces the necessary computational power, but is by definition not mathematically exact. This thesis tests a newly derived thermal dispersion-based upscaling method, referred to as Taylor-based upscaling, and compares it to conventional arithmetic upscaling and a reference fine-grid simulation. The upscaling methods are applied on reservoir descriptions from the Margretheholm-1A and the HON-GT-01 reservoirs, and simulations are done using Delft Advanced Research Terra Simulator (DARTS). The reservoirs are modelled as 2D layer-cake models in the form of a geothermal doublet with a fine longitudinal resolution, 1000 grid blocks between injector and producer, to minimize numerical dispersion. The results are presented as 2D-temperature profiles and breakthrough-curves. The deviations are quantified in the form of L2-norm calculations and by comparing the amount of days it takes for each upscaling method to reach a 1◦C or 5◦C drop in production temperature. The results show that arithmetic upscaling underestimates the spreading of the cold-temperature front leading to later breakthrough, whereas Taylor-based upscaling overestimates this spreading. For the Margretheholm-1A reservoir Taylor-based upscaling mimics the fine-grid reference simulation better compared to arithmetic upscaling, whereas arithmetic averaging performs better for the HON-GT-01 reservoir. Increasing the vertical thermal conductivity (kz ) leads to Taylor-based upscaling coming closer to the fine-grid reference simulation; however different reservoir descriptions require a different kz adjustment. In conclusion, the Taylor-based upscaling method does not outperform conventional arithmetic upscaling for all reservoir descriptions. Also, no universal rule was found for increasing the kz -value to improve the Taylor-based upscaling method.

Transition to cleaner energy while sustaining the heat demand necessity has always been an emphasized topic in the recent years. With the slowly declining utilization and production of natural gas in Netherlands, geothermal energy shows a promising future in providing sustainable power for heating and various applications. For majority of economically feasible geothermal project, either natural fractures or hydraulic fractures are present. These fractures served as a preferential fluid pathway between geothermal well couplets, which determines crucial parameters such as breakthrough time and project life. In this study, the main focus is the impact of stochastic distribution of fracture aperture with or without pressure dependence and gravity effect on geothermal energy production. The simulation conditions as well as reservoir physical model are collected from analogous enhanced geothermal systems (EGS)that are classified as deep geothermal energy projects. The test cases include base case, case with no pressure or stress dependence, case with half well doublet distance, and case with gravity that has well positioned in the dip or strike direction in relative to the fault orientation. The ensemble simulation of 100 realization is run for each scenario considered. The relevant parameters analyzed are pressure difference between well couplet, production temperature, NPV, and most importantly, net cumulative energy production. It is found out that the geothermal energy production greatly relies on the fracture aperture distribution with or without pressure dependence. For base case, the range of energy production is from 1.50E13 to 3.75E13 KJ with temperature variation of 35 K between the minimum and maximum value. Without pressure dependence, only pressure difference between injector and producer slightly changes, and production temperature as well net energy pro-duction remains nearly identical. For the case with half of original well-spacing, the spread of energy production distribution reduces from 1.50E13 to 3.25E13 KJ. The diminishing energy production results from less total enthalpy in the flow path with shorter distance, yet the outcome of energy production still demonstrates a considerable range. By taking account of gravity effect and populate the reservoir with non-uniform pressure and temperature distribution with corresponding gradient, the net energy production drops to approximately two times less than the base case. However, the ratio of maximum energy production to the minimum over100 realization is similar to that of the base case. Last but not least, two types of well orientation, along the strike and along the dip of fracture plane, are considered to observe the impact of gravity-assisted flow. It is concluded that with the current model setting, the low temperature gradient of injector in the dip configuration case overweighs the effect of gravity assistance, resulting in a smaller net energy production than the strike case. This project concludes that the fracture aperture heterogeneity is an important factor in predicting the outcome of deep geothermal production. The gravity is another crucial component to portray accurate flow behavior between the wells, but it does not result in additional increase in the range of energy production outcome in comparison to the base come with the simulation conditions applied.

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.

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.