A geothermal well doublet, designed with two primary aims; one of research and the second of commercial thermal energy supply, is currently being installed on the campus of Delft University of Technology, with the wells being drilled in the second half of 2023. The project includes a comprehensive 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 continuous samples from the heterogenous reservoir being complimented with more distributed side-wall cores, alongside a large suite of open-hole well logs in the reservoir section of both wells. Such investigation is rarely undertaken in geothermal projects. A fiber optic cable will monitor the production well, and will be installed all-the-way down to the reservoir section when the well completion is installed, at approximately 2300m depth. The reservoir is the fluvial 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 a few y ears’ time between the injector and producer to monitor cold-front propagation. The total project is targeted to supply around 25 MW of thermal energy at peak conditions, next to this project a thermal energy storage system is planned to provide a seasonal buffer. The project is a key national research infrastructure and is being incorporated into the European 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 that will allow better decisions to be made in future geothermal projects. This paper presents the implementation and initial data collection from the project, including an initial evaluation of the logging and coring campaigns.@en

The energy transition requires a reduction of CO2 emissions from anthropogenic activity. In Europe, heat amounts to 50% of the total gross energy consumption. In conduction-dominated geological settings, geothermal resources can supply renewable, baseload heat for direct uses, in almost all parts of Europe. In these settings, economic viability can be challenging and should be considered as coupled to the development of geothermal fields. The aim of this paper is to outline the way towards comprehensive uncertainty quantification. A methodology is proposed identifying three main categories of uncertainty sources to be evaluated based on three key performance indicators in a systematic approach. The sources of uncertainty include: a) subsurface characterization, b) development options and c) economics. The performance indicators are : i) cumulative energy generated, ii) system lifetime and iii) economic output. Each of the uncertainty sources and performance indicators are used to demonstrate the importance of a comprehensive approach to uncertainty quantification. Standardization and comprehensive analysis considering the combined uncertainty across the different uncertainty levels and over the key performance indicators is needed to enable more reliable and robust predictions of geothermal developments.@en

Geothermal energy extraction through deep mine systems offers the potential to reduce the cost of geothermal systems while meeting the cooling needs of deep mines. However, the injection of cold water into the subsurface triggers strongly coupled thermo-hydro-mechanical (THM) processes that can affect the stability of underground excavations. This study evaluates the impact of geothermal energy extraction on the temperature and stability of a deep mine. By quantifying the sensitivity of the mine temperature and stability to various parameters, we propose a scheme to optimize geothermal energy production, while achieving rapid mine cooling and maintaining stability. We first evaluate the impact of geothermal operations on mine temperature and stability through THM numerical modeling. The simulations show that poro-elastic stress quickly affects mine stability, while thermal stress has a more significant impact on the long-term stability. We then use Distance-based Generalized Sensitivity Analysis (DGSA) to quantify parameter sensitivity. The analysis identifies the distance between the mine system and the geothermal system as the most influential factor. Other important parameters include the injection rate, injection temperature, well spacing, coefficient of thermal expansion, permeability, Young's modulus, and heat capacity. Finally, we propose a DGSA-based optimization framework that accounts for subsurface uncertainty and validate the optimized results. Our results indicate that, with favorable geological conditions, a rational selection of system design parameters can enhance geothermal energy production while ensuring rapid mine cooling and stability. This study provides essential insights for the optimization of deep mine geothermal systems and supports effective decision-making.

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A geothermal doublet has been installed in a sedimentary reservoir for direct-use heating on the TU Delft campus, targeted to supply around 25 MW of thermal energy at peak conditions. This contribution presents the implementation and initial data collection from the doublet, including an initial evaluation of the logging and coring campaign. Nearly half of Netherlands natural gas consumption is allocated to heating, and the on-campus CO2 emissions from heating exceed 50%. The doublet has been designed with two primary aims of research and commercial heat supply, with the wells being completed in December 2023. The project will be operated by a commercial entity, and built into a larger thermal energy system including a high temperature underground storage system, with the first energy production planned in 2025. The research questions relate to field-scale geothermal operations, e.g. how reliable is the long-term energy production?, how do materials perform in the long-term? and how can geothermal projects be best monitored? The research programme involves 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 heterogenous reservoir, alongside a large suite of open hole well logs in the reservoir and through casing logs in overlying geological units. A fiber-optic cable will monitor distributed pressure throughout the producer reservoir section, at approximately 2300m depth, which will be installed during commissioning. A local seismic monitoring network has been installed in the surrounding area with the aim of monitoring very low-magnitude natural or induced seismicity. The project is a key national research infrastructure and is being incorporated into the European 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 that will allow to make better decisions in future geothermal projects.@en

Utilizing existing deep mining systems for geothermal extraction not only facilitates the development of geothermal systems but also helps meeting the cooling requirements for deep mining operations. In this study, a thermo-hydro-mechanical model of geothermal extraction in deep mines is developed to investigate the evolution of mine galleries stability and temperature, and the temperature changes in geothermal production wells. The uncertainty in system responses is predicted through the Bayesian Evidential Learning framework. Due to our limited understanding of the material properties and the scarcity of measurement data, uncertainties emerge in the forward simulations. Ideally, a comprehensive uncertainty analysis would be conducted to predict all possible outcomes and assess any risks. However, In light of the intractability of performing comprehensive uncertainty analyses in scenarios with vast unknown data, particularly due to the computational overhead of multiple inverse problemsolving, we employ the Bayesian Evidential Learning framework, which provides a feasible and rapid alternative for approximating prediction post-distributions and choosing the most informative data sets. Before implementing BEL, we employed Latin Hypercube Sampling to create 500 sets of realizations for forward simulations, and subsequently utilized global sensitivity analysis to evaluate the data's informational value, aiming to diminish the uncertainty in predictions. In this paper, the BEL framework is utilized to achieve two: firstly, to stochastically predict the responses of the system (stability and temperature) within the BEL framework, using machine learning to discover direct correlations between predictors (sensitive parameters) and targets (system responses). Subsequently, newly collected data can be utilized to predict the approximate posterior distributions of the corresponding gallery stability, temperature, and production well temperature, thus circumventing traditional data inversion steps. This framework can be adjusted to accommodate any predictions related to subsurface conditions; hence, our second goal involves predicting the system's long-term responses within the BEL based on shortterm data collection, forecasting posterior distributions from the acquired short-term data, and validating the efficacy of this approach. Our study indicates that in practical engineering, by (1) obtaining data of material properties and (2) key responses of short-term simulation, it is possible to predict the critical responses of the system in long-term geothermal extraction, thereby maximizing the information content of any measurement data while minimizing budget constraints and computational costs.@en

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.@en

With the increasing demand for mineral and alternative energy resources, as well as the gradual depletion of shallow resources, the exploitation and utilization of mineral resources and geothermal energy in deep strata is an effective way to solve the problem of resource shortage [1]. In recent years, as a new type of resource mining mode, the co-mining of deep mineral and geothermal energy has developed rapidly [2, 3]. This method can make use of the original equipment of the mine for geothermal exploitation. However, the deep co-mining system faces two significant challenges: the first is the significant uncertainty inherent in subsurface properties, while the second is the high levels of geostress and temperature associated with deep mining. These challenges are adding some constraints on the practicality of exploiting such systems and limit the feasibility of deep resource co-mining, so that modelling efforts are needed for actual risk assessment.
Consequently, we developed a Thermo-Hydro-Mechanical (THM) coupling framework for geothermal energy exploitation in deep mines using COMSOL to quantitatively characterize the temperature field of the geothermal system and predict the stress field of the mining system, considering the joint effects of large uncertainties and THM coupling. Through SGeMS, the uncertainty and spatial heterogeneity distribution of porosity are first generated. Then, the uncertainty of the hydraulic parameter [4] (permeability), mechanical parameter [5] (elastic modulus), and thermal parameter [6] (heat capacity and heat conductivity) was derived from the porosity. 500 samples were generated within a given uncertainty range, by means of Monte Carlo simulations. The spatial and temporal distributions of the temperature field of the geothermal system, and the stress field of the mining system were simulated, for each sample with COMSOL. Using the distance-based global sensitivity analysis [6], the most sensitive parameters for deep mining are identified, the heat storage capacity of the system and evolution of the maximum stress ratio are evaluated, including uncertainty.@en

The efficient operation and management of a geothermal project can be largely affected by geological, physical, operational and economic uncertainties. Systematic uncertainty quantification (UQ) involving these parameters helps to determine the probability of the focused outputs, e.g., energy production, Net Present Value (NPV), etc. However, how to efficiently assess the specific impacts of different uncertain parameters on the outputs of a geothermal project is still not clear. In this study, we performed a comprehensive UQ to a low-enthalpy geothermal reservoir using the GPU implementation of the Delft Advanced Research Terra Simulator (DARTS) framework with stochastic Monte Carlo samplings of uncertain parameters. With processing the simulation results, large uncertainties have been found in the production temperature, pressure drop, produced energy and NPV. It is also clear from the analysis that salinity influences the producing energy and NPV via changing the amount of energy carried in the fluid. Our work shows that the uncertainty in NPV is much larger than that in produced energy, as more uncertain factors were encompassed in NPV evaluation. An attempt to substitute original 3D models with upscaled 2D models in UQ demonstrates significant differences in the stochastic response of these two approaches in representation of realistic heterogeneity. The GPU version of DARTS significantly improved the simulation performance, which guarantees the full set (10,000 times) UQ with a large model (circa 3.2 million cells) finished within a day. With this study, the importance of UQ to geothermal field development is comprehensively addressed. This work provides a framework for assessing the impacts of uncertain parameters on the concerning system output of a geothermal project and will facilitate analyses with similar procedures.

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The subsurface provides multiple resources, the exploitation of which has a lasting impact on future potential provision. Establishing sustainability in terms of fundamental principles, and fitting these principles into a practical framework, is an ongoing endeavour focused mainly on surface activities. The principles of ecological economics lead to six challenges that summarize the current limitations of implementing science-based sustainable management of geological resources in the medium to deep subsurface: integrating value pluralism, defining sustainable scale, evaluating interferences in the subsurface, guaranteeing environmental justice, optimizing environmental and economic efficiency and handling uncertainties. Assessing and managing geological reservoirs is particularly challenging because of slow resource regeneration, complex spatial and temporal inter-actions, concealment and naturally dictated opportunities. In answer to the challenges, visions are proposed that outline how an indicator framework is needed for guidance, how indicators require reservoir models with extended spatial and temporal scope, how differences in social values in relation to the environment are to be considered and how real option games combined with life cycle assessment can be used for optimizing effi-ciency. These individual solutions relate to different facets of the same problem, and can be integrated into one overarching solution that takes the form of dynamic multi-criteria decision analysis.

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Focus is on comparing stochastic, process-based and deterministic methods for modelling heterogeneity in hydraulic properties of fluvial geothermal reservoirs. Models are considered a generalized representation of a fluvial sequence in the upper part of the Gassum Formation in northern Denmark. Two ensemble realizations of process-based and stochastic heterogeneity were simulated using the state-of-the-art numerical modelling software, Delft Advanced Research Terra Simulator (DARTS), to assess differences on a statistically relevant sample size. Simulator settings were optimized to achieve two orders of magnitude improvement in simulation time. Our general findings show that the stochastic and process-based methods produce nearly identical results in terms of predicted breakthrough time and production temperature decline for high net-to-gross ratios (N/G). Simple homogenous and layered models overestimate breakthrough and underestimate temperature decline. More complex representation of facies in process-based models show smaller variance in results and stay within the limits of ensemble runs compared to simpler facies representation. Results indicate that a multivariate Gaussian based stochastic representation of heterogeneity provides comparable thermal response to a process-based model in fluvial systems of similar quality.

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The Kingdom of Saudi Arabia (KSA) has vast geothermal energy resources. When developed, these markedly strengthen the country's goals of achieving a carbon-neutral economy. To demonstrate the feasibility and techno-economic performance of small-scale, hydrothermal well doublet systems for direct use in KSA, we perform reservoir and wellbore flow and heat-transport simulations as well as an economic analysis. The maximum permissible flowrate is constrained to avoid thermoelastic fracturing in the near-wellbore region. Reservoir conditions of a sedimentary basin along the Red Sea coast (near Al Wajh) provide an ideal study case to which we add economic parameters considered representative for KSA. We derive a Levelized Cost of Heat (LCOH) ranging from 49 to 128 $/MWh for 50-mD hydrothermal doublet systems with an optimal well spacing of 600 m and a flowrate ranging from 110 kg/s to 50 kg/s. LCOH is strongly influenced by decreasing reservoir transmissivity. Also, a minimum injection temperature is required to avoid thermoelastic fracturing. Our economic analysis further highlights that capacity factor and well-drilling cost have the greatest impact on LCOH. Thus, this study provides a guide and workflow to conduct techno-economic investigations for decision-making, risk mitigation, optimizing geothermal-energy-extraction and economic-performance conditions of hydrothermal doublet systems.

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The Kingdom of Saudi Arabia (KSA) has vast geothermal energy resources. When developed, these markedly strengthen the country's goals of achieving a carbon-neutral economy. To demonstrate the feasibility and techno-economic performance of small-scale, hydrothermal well doublet systems for direct use in KSA, we perform reservoir and wellbore flow and heat-transport simulations as well as an economic analysis. The maximum permissible flowrate is constrained to avoid thermoelastic fracturing in the near-wellbore region. Reservoir conditions of a sedimentary basin along the Red Sea coast (near Al Wajh) provide an ideal study case to which we add economic parameters considered representative for KSA. We derive a Levelized Cost of Heat (LCOH) ranging from 49 to 128 $/MWh for 50-mD hydrothermal doublet systems with an optimal well spacing of 600 m and a flowrate ranging from 110 kg/s to 50 kg/s. LCOH is strongly influenced by decreasing reservoir transmissivity. Also, a minimum injection temperature is required to avoid thermoelastic fracturing. Our economic analysis further highlights that capacity factor and well-drilling cost have the greatest impact on LCOH. Thus, this study provides a guide and workflow to conduct techno-economic investigations for decision-making, risk mitigation, optimizing geothermal-energy-extraction and economic-performance conditions of hydrothermal doublet systems.

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High-Temperature – Aquifer Thermal Energy Storage (HT-ATES) can significantly increase Renewable Energy Sources (RES) capacity and storage temperature levels compared to traditional ATES, while improving efficiency. Combined assessment of subsurface performance and surface District Heating Networks (DHN) is key, but poses challenges for dimensioning, energy flow matching, and techno-economic performance of the joint system. We present a novel methodology for dimensioning and techno-economic assessment of an HT-ATES system combining subsurface, DHN, operational CO ₂ emissions, and economics. Subsurface thermo-hydraulic simulations consider aquifer properties (thickness, permeability, porosity, depth, dip, artesian conditions and groundwater hydraulic gradient) and operational parameters (well pattern and cut-off temperature). Subject to subsurface constraints, aquifer permeability and thickness are major control variables. Transmissivity ≥2.5 × 10 ⁻¹² m³ is required to keep the Levelised Cost Of Heat (LCOH) below 200 CHF/MWh and capacity ≥25 MW is needed for the HT-ATES system to compete with other large-scale DHN heat sources. Addition of Heat Pumps (HP) increases the LCOH, but also the nominal capacity of the system and yields higher cumulative avoided CO ₂ emissions. The methodology presented exemplifies HT-ATES dimensioning and connection to DHN for planning purposes and opens-up the possibility for their fully-coupled assessment in site-specific assessments.

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Geothermal energy is gaining momentum as a renewable energy source. Reservoir simulation studies are often used to understand the underlying physics interactions and support decision making. Uncertainty related to geothermal systems can be substantial for subsurface and operational parameters and their interaction with regards to the output in terms of lifetime, energy and economic output. Specifically, for geothermal systems with the fault acting as the main fluid pathway the relevant field development uncertainties have not been comprehensively addressed. In this study we show how the produced energy, system lifetime and NPV are affected considering a range of subsurface and operational parameters as uncertainty sources utilizing an ensemble of 16,200 3D Hydraulic-Thermal (HT) reservoir simulations, conceptually based on the Rittershoffen field. A well configuration with oblique angles with respect to the main permeability anisotropy axes results in higher system lifetime, generated energy and NPV. A well spacing of 600 m consistently yields a higher economic efficiency (€/MWh) under all uncertainty parameters considered. More robust development options could be utilized in the absence of fault permeability characterization to ensure improved output prediction under uncertainty. Studies based on the methodology presented can improve investment efficiency for field development under subsurface and operational uncertainty.

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Geothermal energy is gaining momentum as a renewable energy source. Reservoir simulation studies are often used to understand the underlying physics interactions and support decision making. Uncertainty related to geothermal systems can be substantial for subsurface and operational parameters and their interaction with regards to the output in terms of lifetime, energy and economic output. Specifically, for geothermal systems with the fault acting as the main fluid pathway the relevant field development uncertainties have not been comprehensively addressed. In this study we show how the produced energy, system lifetime and NPV are affected considering a range of subsurface and operational parameters as uncertainty sources utilizing an ensemble of 16,200 3D Hydraulic-Thermal (HT) reservoir simulations, conceptually based on the Rittershoffen field. A well configuration with oblique angles with respect to the main permeability anisotropy axes results in higher system lifetime, generated energy and NPV. A well spacing of 600 m consistently yields a higher economic efficiency (€/MWh) under all uncertainty parameters considered. More robust development options could be utilized in the absence of fault permeability characterization to ensure improved output prediction under uncertainty. Studies based on the methodology presented can improve investment efficiency for field development under subsurface and operational uncertainty.

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Direct Use Geothermal Systems (DUGS) are increasing their installed capacity worldwide and denser developments with multiple doublets are becoming more common. Interference between doublets therefore becomes an additional concern to subsurface uncertainties. Faults can be either barriers or conduits to flow and can affect the fluid pathways inside the reservoir. The interference between two doublets that are separated by a fault has not been previously studied for DUGS. In this work considering subsurface uncertainty in a full factorial design using 5184 3D reservoir simulations we show that a fault can reduce the system lifetime of a two-doublet system by more than 40 % if one doublet is at close proximity to it. Further, we identify that the fault can also improve both the system lifetime and generated Net Present Value (NPV) with appropriate development decisions. Contrary to previous results that did not consider reservoir architecture, a tramline well configuration is preferable when the doublets have the fault in the centre, while a checkerboard configuration is preferable as the distance to the fault decreases. The Heat In Place (HIP) recovery shows a linear relationship with flow rate and well spacing that is not affected by the fault distance or flow properties. The dimensions of the Influence Area (IA) previously considered are insufficient to capture the temperature drop at the producer wells and the fault position can increase this discrepancy. Our results show the importance of fault characterisation and well positioning with respect to a fault considering subsurface uncertainty and how this can affect denser field development of DUGS. Our findings suggest to integrate faults and the relative positioning of well doublets with respect to a fault more strongly in field development plans. Such considerations should also be included in future optimization plans of multi-well geothermal systems. Moreover, the regulatory framework should be revised to achieve a better match between the IA boundary and the production well temperature drop to enable better planning for denser development of DUGS.@en

The installed capacity of geothermal systems for direct use of heat is increasing worldwide. As their number and density is increasing, the their interaction with subsurface faults becomes more important as they could lead to safety risks from induced seismicity. Assessment and management of such risks is essential for the further development and extension of geothermal energy for heating. At the same time, the economic output of geothermal systems can be marginal and is hence often supported by subsidy schemes. A combined assessment of fault stability and economic output could help operators to balance economic and safety aspects, but this is currently not common practice. In this study we present a methodology to assess field development plans based on fault stability and Net Present Value (NPV) using reservoir simulations of a fluvial, heterogeneous sandstone representative of the majority of direct-use Dutch geothermal systems. We find that the highest friction coefficient leading to exceedance of the Mohr–Coulomb failure criteria in this sandstone is 0.17; such values could be encountered in clay-rich fault gouges. Similar or lower fault permeability compared to the reservoir results in no changes and an increase respectively of both NPV and fault stability with larger Fault-to-Well Distance (FWD). Fault permeability higher than the reservoir permeability results in a minor increase in NPV with smaller FWD. Our results demonstrate that a combined analysis of thermal, hydraulic, mechanical and economic assessment supports a responsible and viable development of geothermal resources at a large scale. The importance of a high spatial density of supporting stress data will be essential for a better understanding and quantification of economic and fault stability effects of geothermal operations.

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Direct Use Geothermal Systems (DUGS) are increasing their installed capacity worldwide and denser developments with multiple doublets are becoming more common. Interference between doublets therefore becomes an additional concern to subsurface uncertainties. Faults can be either barriers or conduits to flow and can affect the fluid pathways inside the reservoir. The interference between two doublets that are separated by a fault has not been previously studied for DUGS. In this work considering subsurface uncertainty in a full factorial design using 5184 3D reservoir simulations we show that a fault can reduce the system lifetime of a two-doublet system by more than 40 % if one doublet is at close proximity to it. Further, we identify that the fault can also improve both the system lifetime and generated Net Present Value (NPV) with appropriate development decisions. Contrary to previous results that did not consider reservoir architecture, a tramline well configuration is preferable when the doublets have the fault in the centre, while a checkerboard configuration is preferable as the distance to the fault decreases. The Heat In Place (HIP) recovery shows a linear relationship with flow rate and well spacing that is not affected by the fault distance or flow properties. The dimensions of the Influence Area (IA) previously considered are insufficient to capture the temperature drop at the producer wells and the fault position can increase this discrepancy. Our results show the importance of fault characterisation and well positioning with respect to a fault considering subsurface uncertainty and how this can affect denser field development of DUGS. Our findings suggest to integrate faults and the relative positioning of well doublets with respect to a fault more strongly in field development plans. Such considerations should also be included in future optimization plans of multi-well geothermal systems. Moreover, the regulatory framework should be revised to achieve a better match between the IA boundary and the production well temperature drop to enable better planning for denser development of DUGS.@en

As the code was actively developed during the time of publication, the published data suffer from an error with regards to the discount factor applied during the NPV calculation. The published data NPV has been calculated for periods of 100 days, while the discount rate applied was the quoted Annual Discount Rate (ADR) value of the manuscript, namely 7%. When the NPV is calculated at intervals shorter periods than a year, the discount rate needs to be adjusted accordingly. This adjusted Periodic Discount Rate (PDR) should be calculated according to the following equation: [Formula presented] For our data this means that the PDR should be 0.018697 or 1.8697% for each period of 100 days for which the NPV is calculated. This was not done for the published data, due to different versions of the code being used. As a result, the time value of money was discounted much more than it should be (7% each 100 days when it should be 1.8697% per 100 days), leading to lower NPV values. This affects section 3.3 “Lifetime and NPV” of the published article (Figures 9, 10 and 11). We have re-performed the processing after having addressed this issue and plotted the corrected data in the updated figures below. While the qualitative conclusions that were drawn from the published figures are not significantly different from the corrected ones, the quantitative NPV values of the corrected figures differ substantially. Figure 9 Published. [Figure presented] Figure 9 Corrected. [Figure presented] Figure 10 Published. [Figure presented] Figure 10 Corrected. [Figure presented] Figure 11 Published. [Figure presented] Figure 11 Corrected. [Figure presented]

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Understanding fractures and fracture networks is essential for the investigation and use of subsurface reservoirs. The aim is to predict the fractures and the fracture network when there is no direct access to subsurface images available. This article presents a universal workflow to numerically compute a discrete fracture network by combining the 1D scanline survey method, processed with the newly written SkaPy script, together with the multiple point statistic method (MPS). This workflow is applied to a potential geothermal site in Mexico called Acoculco. We use Las Minas outcrops and quarries as surface analogues for the Acoculco reservoir, as Las Minas and Acoculco are both formed by the influence of a plutonic intrusion into the Jurassic-Cretaceous carbonate sequence of the Sierra Madre Oriental in the Trans-Mexican volcanic belt (TMVB). The intrusion is associated with contact metamorphism and metasomatic phenomena, providing the basis for the mining activities at Las Minas. The results obtained using this workflow demonstrate the feasibility of the approach, which presents a solution combining the efficiency of data processing and an interpretation-driven approach to build realistic discrete fracture networks. This workflow can be used in the process of estimating the permeability of a fracture controlled reservoir, with using only scanline surveys data as input. This is essential in the process of evaluating the feasibility to develop an enhanced geothermal system.@en