As of 2040, Energy Information Administration (EIA) expects an increase of 28% in world energy consump- tion. The majority of this consumption is projected to account from developing countries such as India, China and other third world countries since the economy is increasing rapidly. [3] In order to overcome this fast increase, the human kind cannot rely only on fossil fuels and other sustain- able technologies like solar, wind, geothermal are required. However, the emmision of CO2 is also increasing from 6000 million metric tons carbon in year 2000 to 10000 million metrics tons in 2010. That’s why many countries such as Denmark, Norway, Germany, The Netherlands etc., are moving away from traditional fuel sources to the new energy. One of these energy is Geothermal energy. Despite the fact that geothermal is a clean energy and almost CO2 emission free, it does have some challenges mainly, scaling and corrosion. Moreover, thats not the only problem associated with this. Scaling is site spe- cific which is a major problem in the wells.

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.

Evaluating an adequate computer model representing the characteristics of a subsurface reservoir is of great importance in the oil and gas industry. With recent data acquisition developments, high-resolution geological models can be generated for the subsurface reservoirs; however, uncertainties of geological data and too many details in the model have brought up remarkable limitations for application of high-fidelity geo-models in reservoir management. To generate efficient low-resolution models, which are relatively representative of the reservoir dynamic behaviour, data-driven models are proposed. The data-driven models are trained principally based on the production history of the reservoir with primary knowledge of structural information. The Data-driven Discrete Well Affinity (DiWA) model is designed to generate efficient proxy models that require basic geological information and full production history of the reservoir. Since it benefits the computational power of the Delft Advanced Terra Simulator (DARTS) and adjoint gradient-based optimization, the DiWA model has become an efficient framework in terms of accuracy and computational costs. This research shows that the DiWA model can relatively reconstruct the reference reservoir parameters out of an ensemble of priors, and the final results can be improved utilizing closer prior knowledge to the true response. Additionally, it is demonstrated that the performance of the DiWA model in a complex, realistic oil field can be enhanced using a comprehensive objective function, applying appropriate well controls, understanding the underlying driving mechanisms, using sufficient degrees of freedom, and applying consistent boundary conditions.

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.

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.

A pilot for a large scale, fully integrated chain of CO2 capture, transport and storage (CCS) has been initiated in the port of Rotterdam. The initiative aims to demonstrate the technical and economic feasibility of CCS and show that it can be deployed on a large scale for power plants and energy-intensive industries that emit large volumes of CO2. The partially-depleted Q16-Maas gas condensate field could potentially be used to permanently store the captured greenhouse gas (CO2). The case study shows the potential that this field has for CO2 storage and also examines other options for life-cycle extension. The case study is based on macroscopic scale reservoir behaviour and simulated in the fully compositional simulator, Eclipse 300. Gas reservoirs have a proven track record for safely trapping gaseous phases in the subsurface over long geological timescales. As long as initial reservoir conditions, mainly pressure (=296,5 bar), are not exceeded, CO2 in supercritical phase should be safely stored. According to literature, with increasing storage time, the CO2 is even trapped more securely, although this process may take hundreds to thousands of years. The results of the case study show that approximately 1.1 million tonnes of pure CO2 can be stored in Q16-Maas field. By side-tracking the original well and producing the attic gas in the reservoir, 160 million cubic meters of additional gas can be recovered, along with condensate. If the side-tracked well is then converted to a CO2-injection well, the CO2 storage capacity is increased to 1.4 million tonnes. This injectable CO2 volume is less than the two million tonnes originally estimated and this is due to the influx of water from a strong aquifer that has partially filled the void left by depleting the gas field. The possibility of enhanced gas and condensate recovery using CO2 has also been investigated in this case study, as the use of CO2 for miscible floods in hydrocarbon reservoirs has been proven and used successfully as a tertiary recovery method. The reservoir simulation of the Q16-Maas field shows that there is no additional hydrocarbon recovery by CO2 flooding. Sidetracking to and producing from an updip location in the reservoir is equally as productive. The reason for this is attributed to presence of a strong water aquifer, together with the varying reservoir quality and thickness prevents the successful application of CO2 enhanced hydrocarbon recovery. The total cost of transport and storage (OPEX and CAPEX) was estimated to be 71.5 million euro. Assuming CO2 storage volume of 1.4 million tonnes, the project would need to receive roughly 50 euro/tonne in order to breakeven for storing and transporting the CO2, the capturing is not included.

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.

For many decades, conventional gravitational separators have been the backbone of the fluid separation in the oil and gas industry. The stricter environment regulation for purification of the recycled water, together with a tighter profitable margin of the produced oil, requires more efficient and faster separators. Inline swirl separator uses centrifugal acceleration up to hundreds of gravitational accelerations to perform separation in a much faster time. However, its efficiency is still lower than the industry expectations. There are essential geometric parameters such as swirl intensity and the collector tube, and vital operating conditions such as flow-rate at the entrance and mass flow-rate at each exit that impact the dynamics behavior of swirl flow in the pipe. The dynamic behavior of the swirl flow determines the efficiency of the apparatus. Thus, the main objective is to understand the dynamics of the single-phase swirl flow in the pipe and determine an inline swirl separator that presents sufficient efficiency. The first part of the study focuses on a better understanding of the dynamic behavior of the swirl flow in a pipe. The second part utilizes the results from the first stage to determine an inline swirl separator that presents sufficient efficiency. The performed numerical study suggests that the dynamic behavior of swirl flows in a pipe is determined by the intensity of the swirl flow, which is quantified by the swirl number. The swirl intensity shapes the axial velocity profile at the core of the vortex. When the swirl number increases beyond a critical number, a columnar vortex appears, with a reverse flow along with the center of the entire tube. The swirl intensity decays along the wall of the pipe; the swirl intensity and the decay of it form the shape of the axial velocity profile. In case the disturbance of the flow results in a stagnation point at the vortex axis, it may develop a vortex breakdown. The vortex breakdown in high Reynolds numbers ( Reb > 100,000) is a function of the swirl number, and the instability at the vortex core increases by increasing the swirl intensity. Furthermore, the results show that the stability of the vortex is a function of the Reynolds number. Considerable reduction of the Reynolds number kicks in the effect of viscous forces, which stabilize the vortex core. Reynolds and swirl numbers determine the dynamic of the low Reynolds number but turbulent, swirl flow. Therefore, the industry needs to rely on Reynolds Averaged Navier-Stokes (RANS) simulations; Direct Numerical Simulation predictions obtained at much lower Reynolds numbers may not predict the occurrence of the vortex breakdown inside the pipe. These findings show that there are essential design considerations, which determine the efficiency of the swirl separator. Thus, a combination of the geometry parameters and the swirl flow characteristics should be considered to avoid the reverse flow zone and vortex breakdown inside the inline separator. One of the vital elements of the inline swirl separator is the collector tube. The study shows that the collector tube at the neutral flow split, with no bias of the mass flow-rate at each outlet, changes the velocity to the extent that he reverse flow zone for Sw=0.5 is eliminated. Pressure actuators can control the flow; therefore, controlling the flow split at both outlets. The numerical results show that an additional percentage of flow split enhances efficiency by eliminating the reverse flow zone for the higher swirl numbers. Additionally, the study reveals the counter effect of the extreme flow splits, which hinders the efficiency of the inline swirl separator. These optimal settings for the geometry of this research were found at swirl number 1.6 and flow split of 50%.

Over the years, modelling frameworks have been proposed to describe and predict the degradation of municipal solid waste in landfills. These frameworks, however, fail to couple the kinetic solutions to the real-time equilibrium state of the system. Because of this, fundamental processes such as pH changes, NH4+ adsorption to the waste surface and changes to the fluid composition are often not (or inadequate) taken into account. In this study, we propose a degradation model that couples a kinetic solver to the chemical equilibrium software, ORCHESTRA. For this, a tool is developed that allows seamless operability between ORCHESTRA and the Python environment. The modelling framework is used to simulate the degradation of solid organic matter in a batch reactor following a simplified, but comprehensive, reaction network. Reaction rates are based on Monod kinetics that includes a wide variety of inhibition functions. The Freundlich equation is used to capture NH4+ adsorption to the waste surface. Results from various case studies show that the modelling framework is suitable for coupling real-time landfill chemistry to degradation kinetics. We found that NH4+ concentrations play a dominant role in the presented model. While low NH4+ concentrations limit biomass growth by substrate inhibition, high concentrations (>0.002 4 mol/L) affect the hydrolysis rate by toxicity inhibition. This translates to a model that is sensitive to a variety of input parameters such as the initial C/N ratio, the Kd (degree of adsorption) value and the initial organic fraction. A comparison with literature studies, however, implies that the model lacks fundamental processes such as gas and fluid transport or changes in volume and temperature. In addition to this, we discuss that the Freundlich isotherms may be inappropriate to capture adsorption in a coupled framework as no ion exchange is taken into account. Models that do so, such as the NICA-Donnan model, could improve the model results significantly.

The storage of carbon dioxide is now regarded as a critical industrial application aimed at mitigating its accumulation in the atmosphere. Reservoirs and aquifers have been identified as viable alternative locations. This report seeks to examine the impact of sedimentological heterogeneity on the development and migration of CO2 plumes over time. The study uses the Roda Sandstone Formation as a case study, primarily due to the presence of carbonate-cemented layers within the Gilbert-delta lobes, which contribute to reservoir heterogeneity commonly observed in subsurface formations. The utilization of a sketch-based modeling approach was employed in constructing the geo-models represented by Rapid Reservoir Modeling (RRM) software since the Roda Sandstone is an exposed section in Isabena Valley in Spain. Furthermore, various realizations are constructed using different parameters of the cemented layers to comprehensively comprehend all potential scenarios. The aforementioned observations pertain to variations in the thickness and lateral continuity of the cemented layers. Additionally, dynamic modeling is also performed by injecting CO2 into the reservoir for 50 years. The simulator utilized for dynamic modeling is the Delft Advanced Research Terra Simulator (DARTS). The findings demonstrate that reservoirs with moderate sedimentological heterogeneity are actually better sites to store CO2 due to the capacity and effectiveness of the storage.

Society relies on large amounts of energy to progress and allow for a high standard of living. The recent severe climate changes require advanced technologies related to cleaner energy resources. One such technology beneficial for accelerating this current energy transition is geothermal energy. This type of energy is often found in fractured and karstified carbonate aquifers. Understanding the reservoir properties and reducing the risks of such subsurface-related activities is vital. This thesis attempts to understand the complex fractured carbonate reservoirs better and improve the numerical simulation capabilities toward large-scale uncertainty quantification.@en

Numerical simulation is based on space and time discretization providing a trade-off between accuracy and computational performance. The operator-based Linearization (OBL) approach introduces an additional discretization domain for the physical description of fluid and rock. Delft Advanced Research Terra Simulator (DARTS) is a general-purpose reservoir simulation platform entirely built around the OBL approach. DARTS provides unique flexibility capabilities, allowing to customize physical description and control simulation process using the high-level Python programming language. Fully Implicit Method provides unconditional simulation stability, while the partial derivatives required for Jacobian assembly are computed analytically through OBL. At the same time, DARTS ensures exceptional simulation performance addressing it at three levels. Inexpensive linearization combined with a reduction in the nonlinearity is controlled by OBL discretization resolution form algorithmic level. Efficient C++ backend for critical kernels and state-of-the-art linear solver with two-stage CPR preconditioner composes the software level. Finally, the ability to perform the entire simulation loop on the GPU platform owing to the OBL approach constitutes the hardware level. The DARTS framework has already served as a platform for several academic and industrial research projects for different geo-energy applications including geothermal, CO2 sequestration and petroleum.@en