Fracture flow channeling stemming from heterogeneous aperture distribution is a widely observed phenomenon in enhanced geothermal systems (EGSs) and has been considered a main cause of unsatisfying thermal extraction performance. Many numerical studies have been performed to quantify the impact of flow channeling on thermal performance, while the dynamic evolution of flow channeling under complex thermo-hydro-mechanical-chemical (THMC) coupled processes remains underexplored. This study develops a 3D field-scale THMC coupled EGS model with heterogeneous fracture apertures to systematically investigate the individual and joint effects of thermoelastic process and mineral reaction on fracture flow channeling and long-term thermal performance. The results demonstrate that during long-term injection of undersaturated water, the thermoelastic process leads to aperture enlargement in low-temperature zones, intensifying flow channeling, whereas the mineral dissolution preferentially enlarges fracture aperture in high-temperature zones, leading to flow dispersion. These two mechanisms exhibit strong physicochemical feedbacks: the mineral dissolution counteracts thermoelastic-induced flow channeling by enlarging heat exchange zones and homogenizing thermal stress distributions, while the thermoelastic process enhances the effect of mineral dissolution by narrowing heat exchange zones. Parametric analyses further reveal that reservoirs with higher rock elastic modulus and lower fracture stiffness are more susceptible to severe thermoelastic-induced flow channeling, whereas higher injection temperatures, lower injection concentrations, and greater reactive mineral content enhance the mitigating effect of mineral dissolution. These findings suggest that long-term thermal performance of EGSs can be optimized by selecting reservoirs with low elastic modulus, high fracture stiffness, and abundant reactive minerals, combined with high-temperature, undersaturated injection strategies.

We develop a new coupled hydro-mechanical-chemical (HMC) model to investigate the stress-controlled evolution of dissolution cavities along a hectometer-scale heterogeneous fracture. The fracture is conceptualized to consist of numerous patches associated with spatially-variable, stress and dissolution-dependent local stiffnesses and apertures. We consider the complete coupling relationships among mechanical deformation, fluid flow, and chemical dissolution within the fracture. More specifically, our model captures non-linear fracture deformational responses and their consequences on localized flow pattern and dissolutional aperture growth, as well as the feedback of dissolution to mechanical weakening and stress redistribution. We elucidate how geomechanical processes affect the aperture and flow patterns and the formation of small to large dissolution cavities. Our simulation results show that stress retards the permeability increase with the extent of retardation positively related to a dimensionless penetration length lp′. Stress induces the splitting of the dissolution front, promoting localized flow and branched dissolution. At low lp′ (wormhole dissolution regime), stress also promotes the sustained growth of dissolution branches. Hence, there is no apparent increase in global flow heterogeneity. At high lp′, stress transitions the system from uniform dissolution into wormhole formation. Wormholes initiate from remote stiffer regions and converge toward the inlet. Our results have important implications for understanding various dissolution phenomena in subsurface fractured rocks, ranging from karstification to reservoir acidization.

Efficient geothermal resource development remains challenging due to inherent geological uncertainty and limited subsurface data. A proof-of-concept for a digital twin for a fluvial geothermal reservoir, similar to the Delft campus geothermal project, is presented. This digital twin has the aim to integrate geological scenario modeling, production simulation, uncertainty analysis, and data assimilation to mitigate operational risks, reduce maintenance costs, extend reservoir longevity, and enhance the overall sustainability of this project. In this contribution, we assess the efficiency of the ensemble smoother with multiple data assimilation (ESMDA) for subsurface property inversion of a fluvial geothermal system. First, we developed an efficient method that allows for the swift creation of multiple geological scenarios of channelized reservoir geometries, fully constrained to well information, using Rapid Reservoir Modeling (RRM). Next, we generated an ensemble containing multiple geological realizations for a given scenario representing the geothermal system using stochastic reservoir modelling. For a single scenario and its ensemble of stochastically generated property distributions, heat flow and production rates were simulated using the Delft Advanced Research Terra Simulator (DARTS). One of the ensemble members and its simulated production data were taken as the “truth” (or reference) case. ESMDA was then employed to invert the property distribution within the fluvial channels of all other ensemble members, using the “observed” temperature and pressure data along the injection and production well from the “truth” case. We also consider the presence of a monitoring borehole to analyze how additional monitoring data impacts the convergence of ESMDA. The simulation results of the posterior models demonstrated a significant reduction in root mean square error for temperature and pressure data which align more closely with the “observations” compared to the prior models. This outcome confirms the feasibility of applying ESMDA for data assimilation in fluvial geothermal systems, such as the Delft campus geothermal project.

Long-term geothermal production is subject to considerable uncertainty due to limited data availability and inherent geological heterogeneity. While observation and data acquisition improve our understanding of the reservoir, they also contribute significantly to project costs. It is essential to identify the most informative observation strategy. In this study, we apply a previously developed scenario-based data assimilation framework that integrates rapid geological modelling, efficient numerical simulation, and Ensemble Smoother with Multiple Data Assimilation (ESMDA) to constrain uncertainties in reservoir properties and production forecasts to a synthetic but geologically realistic fluvial geothermal system and conduct a data worth analysis to evaluate the impact of different observations (production temperature and injection pressure, well temperature and pressure profiles, etc.) on uncertainty reduction. Results show that production temperature and injection pressure alone, though cost-effective, are insufficient to significantly reduce uncertainties in reservoir performance forecasts. In contrast, well temperature and pressure profiles exhibit substantially higher data worth, leading to much better-constrained predictions. Moreover, incorporating a monitoring borehole further constrains uncertainty by capturing subsurface dynamics between the injector and producer. These findings underscore the importance of monitoring pressure and temperature profiles in the wells of a geothermal doublet.

Fluvial reservoirs are a major target for geothermal energy production. Interpreting the 3D reservoir architectures from 2D seismic datasets, which usually are acquired for geothermal systems, is difficult. In particular, small-scale geological factors like sandbody connectivity are challenging to resolve. This study addresses these issues through a novel workflow that incorporates 3D geological and 2D seismic modelling methods to assess the seismic responses of stratigraphic attributes in fluvial geothermal reservoirs where data availability is low.

Two synthetic fluvial reservoir scenarios were built, ranging from a single channelised deposit to a geologically more plausible model ensemble of fluvial deposits, which represents the reservoir heterogeneities that could be present at the geothermal doublet at Delft University of Technology. Acoustic finite-difference modelling was combined with seismic imaging to create 2D depth images. Our results reveal how seismic resolution determines our ability to correctly identify sandbody connectivity and capture inner channel details. Whereas channel bodies can be detected, the best frequency spectra for observing certain geological features remain unclear. These findings emphasise that quantitative multi-scale analysis, advanced imaging techniques, and survey design optimisation are central to improving seismic characterisation of fluvial geothermal systems in future research.

Rate of penetration has been considered as an important factor in the entire drilling industry, which can largely determine the overall costs of drilling a well. This paper proposed a novel real-time prediction of rate of penetration by combining the Attention-based Bidirectional-Long Short-Term Memory and Long Short-Term Memory (Att-Bi-LSTM-LSTM). Eight parameters, which are total vertical depth, weight on bit, revolutions per minute, mud flow rate, density, viscosity, drill-bit outer-diameter, lithology, and rate of penetration, are adopted as datasets. The drilling speed of the well is trained and validated through the drilling data while a sliding window is introduced for the real-time update. In addition, the presented prediction model is compared with other traditional prediction methods. Finally, the prospect of field application and further study is discussed and suggested. The results indicate that the proposed model shows good accuracy and robustness. Moreover, compared with the traditional methods, the model exhibits good superiority with smaller absolute and relative errors. For field applications, the model proposed in this paper attempts to provide a solution to the prediction of real-time rate of penetration. The results are expected to provide guidance for the further study on the increase of drilling speed and reduction of well costs.

Fractures and caves are the main flow and storage channels for the karst geothermal reservoirs, and the water-rock reaction within them significantly affects the thermal performance. Most previous studies concentrated on the fractures, disregarding the impact of the pore water-rock reaction. The objective of this study is to explore the importance of pore water-rock reactions and identify the influence of various parameters when considering pore and fracture water-rock reactions. A 3D thermal-hydraulic-chemical coupling model considering dual media of pores and fractures was developed. The importance of pore water-rock reactions is demonstrated, and quantitatively characterize the effect of injection temperature (T_in), injection rate (Q_in), injection concentration (c_in), and ratio of the reaction-specific surface area between pore and fracture (A_p/A_f) on the thermal performance. Results indicate that the pore water-rock reaction drastically affects the hydraulic conductivity and pressure difference, even leading to an opposite trend. The influence of water-rock reaction in pores on fracture deformation is regulated by A_p/A_f, which augments with A_p/A_f. The relative contribution of A_p/A_f to production temperature, net thermal power, pressure difference, and hydraulic conductivity are 12.8%, 4.1%, 6.8%, and 13.7%, respectively. This study provides a significant guide for accurate production prediction and exploitation of karst-based geothermal reservoirs.

The development of hot dry rocks (HDRs) is of great significance to adjusting energy structure, alleviating energy shortage, reducing pollution, etc. Low-permeability granite is the predominant rock type in deep HDRs, making fractures the primary pathways for fluid circulation and heat extraction. The production of HDRs is significantly influenced by variable fracture conductivity, but current conductivity characterization primarily relies on the elastic deformation of the matrix, neglecting the impact of damage. Accordingly, we propose an experimental method and a supporting apparatus, which is used to unveil the conductivity evolution characteristics resulting from the comprehensive effects of damage and elastic deformation. The experimental results demonstrate that when subjected to confining force squeezing inward, the fracture conductivity experiences varying degrees of decrease compared to its initial state before the experiment. By utilizing the conductivity evolution rate as the evaluation criterion and conducting grey correlation analysis, it has been determined that temperature exerts the most significant influence on the conductivity evolution, followed by injection flow, and lastly, confining pressure. Moreover, rock particle types and production cycles also have different degrees of effect. After considering the comprehensive effects of damage-elastic deformation at the field-scale, the damage has a positive effect on conductivity enhancement. Our study provides a new approach for the characterization of fracture conductivity evolution for deep geothermal projects.

Nearly half of the Netherlands’ natural gas consump tion is allocated to heating, with direct -use geothermal heating being one of the available low-carbon energy solutions. A geothermal well doublet, designed with the two primary aims of research and commercial heat supply, is currently being installed on the campus of Delft University of Technology. The project is a key national research infrastructure and is being incorporated into the European sustainable and distributed infrastructure (EPOS: European Plate Observing System, https://www.epos-eu.org/), such that accessibility and data availability will be as wide as possible. All observations will be included in a digital-twin framework, which will allow us to make better decisions in future geothermal projects. The project includes a comprehens ive research program, involving the installation of a wide range of instruments alongside an extensive logging and coring program and monitoring network. The doublet has been cored, with substantial continuous samples from the heterogeneous reservoir, alongside a large suite of well logs in both the reservoir and overlying geological units. Such investigation is rarely undertaken in geothermal projects. A fiber-optic cable will monitor the producer well all the way down to the reservoir section, at approximately 2300m depth, in the Lower Cretaceous Delft Sandstone that is used as a geothermal reservoir in a series of existing and planned doublets in the West Netherlands Basin. A local seismic monitoring network has been installed in the surrounding area with the aim of monitoring very low-magnitude natural or induced seismicity. A vertical observation well with electromagnetic sensors will be drilled in the near future between the injector and producer to monitor cold-front propagation. This paper presents the initial modeling for the project and steps towards the production of a digital twin. Two modeling examples in the paper will emp hasize current operational challenges relevant to the project.

During the development of subsurface geothermal energy, geological complexity and uncertainty pose challenges when developing and managing a geothermal resource. We are therefore developing a digital twin for subsurface geothermal energy that will be applied to the geothermal project on the TU Delft campus. This digital twin combines geological modelling, property modelling, reservoir simulation, and data assimilation. A core principle of our approach is to consider multiple geological models of the reservoir and use real-time production data to update them to constrain uncertainties and adapt operational strategies.

This paper focuses on the efficient exploration of geological scenarios and design of geological modelling for the digital twin. We use the Rapid Reservoir Modelling (RRM) platform, which is tailored to quickly create 3D models in data-poor situations. We have developed a novel methodology where RRM is used to design templates of individual layers for a given geological scenario. These templates are then extracted and stacked to create different 3D geological scenarios constrained by NTG and well logs. The resulting model ensemble is geologically consistent and captures a diverse range of heterogeneity, providing a robust starting point for exploring the performance of a geothermal reservoir under geological uncertainty in a digital twin.

In the long-term mining of geothermal resources in hot dry rock (HDR), the change of thermal stress and pore pressure will increase fracture conductivity evolution, further improving production performance. The optimization and decision-making of the development scheme based on the impact of damage from fractures have yet to be reported. The damage to fractures is essential in designing and adjusting geothermal resource development schemes, particularly in selecting optimal schemes. Therefore, the production performances of HDR resources under different parameters are analyzed to establish a database. Then, minimizing flow resistance, maximizing net power, and maximizing economic benefits are set as optimization goals. Various injection-mining parameters and fracture characteristics are treated as decision variables. Multi-objective optimization and multi-attribute decision analysis is conducted to obtain optimal schemes. Finally, optimal schemes are evaluated and compared, considering damage and non-damage scenarios. Results show that the NSGA-II algorithm is more suitable for optimizing geothermal development questions. Net power and economic benefits of the optimal scheme considering damage increase by 45.84 % and 21.35 % compared to the control scheme with damage. For the non-damage scenario, the above values increased by 31.55 % and 5.15 %, respectively. Compared to not considering the damage, higher mass flow and well spacing of optimal scheme can be selected for the case when damaged. Moreover, the parametric design of the optimal scheme becomes more conservative as the production cycle increases.

The chemical reaction in the reservoir causes fracture deformation during the heat extraction of enhanced geothermal systems (EGS), affecting thermal performance. The reaction rate is sensitive to temperature, concentration, and reaction-specific surface area. While previous research mainly focuses on the influence of temperature and concentration on fracture deformation, conversely, the effect of fracture morphology(aperture and tortuosity) is ignored. In this study, the deformation characteristics of rough and flat fractures are compared, and the influences of aperture and tortuosity on fracture deformation are analyzed. According to the influence law, the fracture deformation relationship equation between the aperture deformation rate with tortuosity and aperture is fitted. Results show that the deformation of rough fracture is significantly higher than that of flat fracture, and the variations of fracture aperture increase with the aperture and tortuosity. Furthermore, the influence of tortuosity (the variation of aperture increased by 47.97% when the tortuosity increased from 1 to 1.5) is greater than the aperture (that increased by 4.8% when the aperture increased from 0.2 to 1). The rate of aperture change is a logarithmic function of tortuosity and a power function of the aperture. These results provide significant references for the study of EGS, subsurface karst et al.

Fracture distribution plays a significant role in the behavior of subsurface environments, affecting such activities as geothermal production, exploitation and management of groundwater resources, and long-term storage of nuclear waste and carbon dioxide. A key challenge in these and other applications is to estimate the fracture network properties from sparse and noisy observations. We evaluate the utility of cross-borehole thermal experiments for this task, using both physics-based particle-tracking (PBPT) heat-transfer approach and its deep neural network (DNN) surrogates. Synthetic data are provided by the PBPT simulations and used to train and test the DNN surrogates over a full range of the fracture network properties. We propose regionalized and step-by-step training techniques to reduce the computational cost of expensive PBPT forward solves over large ranges of the (to-be-estimated) parameters. Our numerical experiments suggest the feasibility of training a regionalized DNN surrogate over parameter ranges for which the PBPT solves are fast and extrapolating its predictions to parameter ranges with few additional data. We analyze the balance between computational cost and model accuracy, and provide both PBPT and DNN models for applications to others kinds of data.

Geothermal is an important renewable energy source, but the high cost of drilling limits its popularization. The oilfield area is rich in geothermal resources and has a large number of high-temperature abandoned wells. It is an economic and effective method to transform the abandoned wells into geothermal wells. At present, the heat extraction research of abandoned wells mostly focuses on single-well closed systems, while the most common in oilfields is the well patterns open system, which involves the flow and heat extraction of oil-water multiphase. More, the main utilization mode of oilfield geothermal is heating, which is an intermittent operation, and the existence of the heat recovery period makes the solution process more complicated compared to continuous production. Therefore, the numerical simulation of oil-water two-phase and the scheme optimization under intermittent operation are the key problems in the current oilfields geothermal research, that is, it should be made clear what the effects of operation parameters are and how to get the optimization design for the intermittent mining of heat-oil cogeneration from abandoned wells. For this reason, the oil-water two-phase heat-flow coupling model and economic evaluation model are established. Then, database is established through parameter sensitivity analysis, and multi-objective optimization research is carried out on the lifetime and economic benefits using Non Sorting Genetic Algorithm II (NSGA-II). The results show that economic benefit and end-point temperature of the optimized scheme are enhanced by 6.75 million US dollars and 7.10 K after 15-year production, respectively. The heat-oil cogeneration performance is superior, so the influence of oil phase cannot be ignored in the heating process of the well patterns system for oilfield geothermal production.

The multi-physics coupling process during the heat extraction from enhanced geothermal system, encompassing thermo(T)-hydro(H)-mechanical(M)-chemical(C) interactions, plays a pivotal role in changing geothermal reservoir characteristics. However, a comprehensive quantitative assessment of these multi-physics behaviors has been lacking. In this study, a novel approach was proposed to calculate the magnitude of mechanical, chemical, strong mechanical-chemical coupling, and weak mechanical-chemical coupling effects on the variations of reservoir characteristics. In particular, mechanical-chemical coupling effects are quantified for the first time. They are obtained by the fracture aperture difference results across five distinct coupling models (thermo-hydro, thermo-hydro-chemical, thermo-hydro-mechanical, partially-coupled four-field, and fully-coupled four-field models). The findings indicate that mechanical effects lead to an increase in fracture aperture, while chemical effects contribute to its reduction under underbalanced injection conditions. Strong mechanical-chemical coupling effects, exhibiting a negative correlation with chemical effects, conversely result in a diminished fracture aperture. The influences of these effects are investigated from the temporal and spatial perspectives. Temporally, mechanical effects dominate early production while chemical effects become prominent in later stages. Spatially, there mainly exists two zones when stable production: a mechanical-controlled region surrounding injection wells, and a chemical-controlled area distant from the injection wells. Furthermore, sensitivity analysis of injection concentration indicates its alternation changes the reservoir traits and production performance by modifying the magnitudes of chemical and mechanical-chemical coupling effects. This quantification of multi-physics effects offers insights into optimizing injection strategies for better geothermal development. The approach could hold promising potential in other geo-energy scenarios like carbon and hydrogen storage in reservoirs.

Fracture networks, fluid flow and heat extraction within fractures constitute pivotal aspects of enhanced geothermal system advancement. Conventional hydraulic fracturing in dry hot rock reservoirs typically requires high breakdown pressure and only produces a single major fracture morphology. Thus, it is imperative to explore better fracturing methods and consider more reasonable coupling mechanisms to improve the prediction efficiency. Cyclic fracturing using liquid nitrogen instead of water can generate more complex fracture networks and improve the fracturing performance. The simulation of fluid flow and heat transfer processes in the fracture network is crucial for an enhanced geothermal system, which requires a more comprehensive coupled thermo-hydro-mechanical-chemical model for matching, especially the characterization of coupling mechanism between the chemical and mechanical field. Based on the results of field engineering, laboratory experiments and numerical simulation, the optimum engineering scheme can be obtained by a multi-objective optimization and decision-making method. Furthermore, combining it with the deep-learning-based proxy model to achieve dynamic optimization with time is a meaningful future research direction.

The fractures are the main flow and heat transfer channel for fluids in deep high-temperature enhanced geothermal systems (EGS). The deformation of the fracture controlled by reactive flow is a common phenomenon during geothermal development, which might lead to a reduction in the system's thermal performance and operating life. While most previous research focuses on the influence of fracture deformation on system heat extraction performance, conversely the fracture deformation mechanism caused by the reactive flow is ignored. In this paper, a coupled thermal-hydraulic-chemical-deformation (THCD) model is established to investigate the fracture deformation mechanism. The deformation behavior of quartz and anorthite is compared, and the Damkohler number (Da) is adopted to explore the reaction mechanism. Meanwhile, the influence mechanism of concentration and temperature on fracture deformation is also analyzed. Results show that the Da at the fracture surface is 10⁻¹² -10⁻⁸, which means that the deformation of the fracture is controlled by the reaction rate. Compared with the concentration, the influence of temperature on fracture deformation is complex, and there is an inflection point. The inflection point is governed by the mineral reaction kinetics. These results provide significant references for the efficient heat extraction of the EGS.

Oil shale in-situ conversion is an effective and promising exploitation method. The most concerned problem of oil shale in-situ conversion is how to exploit maximum oil and gas by injecting the least energy. However, the relationship between injection energy utilization efficiency and productivity under different operational conditions remain unclear. In this paper, based on a multiphase flow, heat transfer and chemical reaction numerical model, evolution of kerogen pyrolysis with reservoir temperature distribution is thoroughly analyzed. Aims at injection energy utilization efficiency and productivity, effects of injection energy rate, well shut-in measure, reservoir pressure and well spacing on the production performance of the oil shale in-situ exploitation are investigated. Results show that the useless heating region exists during kerogen pyrolysis, which significantly reduces the energy utilization efficiency. A shut-in measure can slightly improve the energy utilization efficiency but lower oil output, thus not a very effective measure to solve the useless heating problem. Under the same energy injection rate, a higher injection temperature and lower injection flow rate will simultaneously obtain higher oil production rate, oil output, and energy utilization efficiency. Furthermore, a larger reservoir pressure and well spacing of 40 m–50 m are recommended to obtain higher oil production rate and output. Results provide meaningful suggestions for optimizing operational parameters in view of injection energy utilization efficiency and oil output.

Hot dry rocks (HDRs), as an essential renewable energy source, its development has received widespread attention, especially for heat extraction. The fracture is the main seepage and heat transfer channel of circulating fluid in dense HDR reservoirs, and its conductivity evolution significantly affects the production performance. Most existing studies have focused on the change of fracture conductivity under elastic deformation without considering the additional conductivity induced by rock damage. However, the additional conductivity may have significant implications for rational design and timely adjustment of the production scheme. Therefore, a three-dimensional model at the field-scale is established, and it is used to analyze the effect of additional conductivity on production performance and economic efficiency. To simplify the calculation, the actual forms of damage are equivalent to the macroscopic physical evolution of the matrix. Results show that the rock is mainly tensile failure affected by thermal stress during production. The occurrence of damage will increase the reservoir permeability and porosity, reduce Young's modulus, and then reduce the differential pressure and production temperature, with a maximum reduction of 2.21 MPa and 14.21 °C in the control case, respectively. The effects of injection temperature, Young's modulus, and injection mass flow on the production performance are significant, followed by Poisson's ratio. In contrast, production pressure and fracture initial permeability had less influence. The maximum differential economic benefit of the control case is up to 2.289 million RMB. This research proves the necessity of damage study during the long-term production of HDRs.

The efficient development of hydrothermal resource is an important focus in the global geothermal industry. A novel hydrothermal open-loop geothermal system in a multi-lateral horizontal well is presented to achieve the simultaneous exploitation of multi-layer reservoirs and accelerate the large-scale development of the hydrothermal resource. To investigate the detailed performance of the novel geothermal system, a novel 3D fluid flow and heat transfer numerical model is established based on the local thermal non-equilibrium and dual porosity theories. The flow and temperature fields are analyzed, while the pressure and temperature interferences between the lateral wellbores of the multi-lateral horizontal well system are comprehensively investigated. The influences of the injection flow rate, lateral-wellbore number, spacing between the injection segment and the main wellbore, fracture aperture on the heat extraction are studied. Furthermore, the thermal characteristics of the novel geothermal system and traditional doublet well system are compared for the first time. The investigation indicates that the flow impedance of the novel geothermal system can decrease by 75.38%, and its energy efficiency reaches 8 times that of the doublet well system. The findings can provide a key reference for scientific research and application of the novel and traditional geothermal systems.