Y. Chen
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Fluvial clastic sequence is the typical reservoir rock to develop the project of Direct Use Geothermal Systems (DUGS). However, limited and unknown subsurface data bring challenges to accurately characterize the geology of the fluvial depositional environment and to capture the details of the sand body distribution and connectivity. In this work, we utilize the process-based modeling (PBM) approach (Flumy) and object-based modeling approach (OBM) (Fluvsim) to develop a robust framework to evaluate the heterogeneity representation of the fluvial depositional environment. An ensemble of geological models with different global net-to-gross ratios (N/G) is created using PBM and OBM. The generated high-resolution models aim to cover a wide range of N/G from 30% to 80% which is typical for Dutch geothermal sediments. For the given models, a static analysis using the Lorenz coefficient shows a large range of variability in heterogeneity levels for both PBM and OBM models. This wide range of heterogeneity levels leads to a broad variation in thermal breakthrough time during 100 years of thermal production. We also find that the OBM and PBM converge to nearly the same distribution of predicted thermal breakthrough time when the overall N/G is 80%.
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Fluvial clastic sequence is the typical reservoir rock to develop the project of Direct Use Geothermal Systems (DUGS). However, limited and unknown subsurface data bring challenges to accurately characterize the geology of the fluvial depositional environment and to capture the details of the sand body distribution and connectivity. In this work, we utilize the process-based modeling (PBM) approach (Flumy) and object-based modeling approach (OBM) (Fluvsim) to develop a robust framework to evaluate the heterogeneity representation of the fluvial depositional environment. An ensemble of geological models with different global net-to-gross ratios (N/G) is created using PBM and OBM. The generated high-resolution models aim to cover a wide range of N/G from 30% to 80% which is typical for Dutch geothermal sediments. For the given models, a static analysis using the Lorenz coefficient shows a large range of variability in heterogeneity levels for both PBM and OBM models. This wide range of heterogeneity levels leads to a broad variation in thermal breakthrough time during 100 years of thermal production. We also find that the OBM and PBM converge to nearly the same distribution of predicted thermal breakthrough time when the overall N/G is 80%.
Journal article
(2026)
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Yuan Chen, Guillaume Rongier, James Robert Mullins, Denis Voskov, Alexandros Daniilidis
Low-enthalpy geothermal doublets for direct-use heating are highly sensitive to subsurface heterogeneity and operational uncertainty. This study quantifies these uncertainties for the Delft campus geothermal system using an integrated workflow that couples geological modeling with GPU-accelerated, high-spatial-resolution reservoir simulation. Ensembles of three-dimensional regional-scale facies models of the Delft Sandstone Member, with and without conditioning to Geothermie Delft (GTD) well data, were generated using object-based modeling and sequential indicator simulation. Porosity was modeled by sequential Gaussian simulation, and permeability was derived from a nuclear magnetic resonance-based porosity–permeability correlation calibrated to GTD well data, yielding higher permeability than core-based correlations for porosity below 15%. Lorenz coefficients indicate strong variability in property distributions, resulting in a wide spread of production temperatures. In total, 2000 geological realizations were simulated over 50 years using the GPU-enabled open-source Delft Advanced Research Terra Simulator (open-DARTS) under maximum and 2025-demand production schemes. Conditioning to GTD wells adds considerable data worth by constraining uncertainty in production well bottom-hole temperature (BHT) and pressure (BHP), while keeping injection pressure within Dutch regulatory limits. SIS models exhibit greater temperature and pressure variability than OBM models due to lower sand-body continuity. Despite large 80% confidence intervals, P50 production temperatures remain comparable for conditioned models. Distance-based generalized sensitivity analysis identifies net-to-gross ratio and the porosity–permeability correlation as dominant controls on thermal response. The 2025-demand scheme delays cold-front propagation. Results demonstrate that ensemble-based, GPU-accelerated high-spatial-resolution simulations enable robust and efficient uncertainty quantification for direct-use geothermal systems, highlighting the importance of well conditioning and reservoir heterogeneity characterization in constraining thermal responses.
...
Low-enthalpy geothermal doublets for direct-use heating are highly sensitive to subsurface heterogeneity and operational uncertainty. This study quantifies these uncertainties for the Delft campus geothermal system using an integrated workflow that couples geological modeling with GPU-accelerated, high-spatial-resolution reservoir simulation. Ensembles of three-dimensional regional-scale facies models of the Delft Sandstone Member, with and without conditioning to Geothermie Delft (GTD) well data, were generated using object-based modeling and sequential indicator simulation. Porosity was modeled by sequential Gaussian simulation, and permeability was derived from a nuclear magnetic resonance-based porosity–permeability correlation calibrated to GTD well data, yielding higher permeability than core-based correlations for porosity below 15%. Lorenz coefficients indicate strong variability in property distributions, resulting in a wide spread of production temperatures. In total, 2000 geological realizations were simulated over 50 years using the GPU-enabled open-source Delft Advanced Research Terra Simulator (open-DARTS) under maximum and 2025-demand production schemes. Conditioning to GTD wells adds considerable data worth by constraining uncertainty in production well bottom-hole temperature (BHT) and pressure (BHP), while keeping injection pressure within Dutch regulatory limits. SIS models exhibit greater temperature and pressure variability than OBM models due to lower sand-body continuity. Despite large 80% confidence intervals, P50 production temperatures remain comparable for conditioned models. Distance-based generalized sensitivity analysis identifies net-to-gross ratio and the porosity–permeability correlation as dominant controls on thermal response. The 2025-demand scheme delays cold-front propagation. Results demonstrate that ensemble-based, GPU-accelerated high-spatial-resolution simulations enable robust and efficient uncertainty quantification for direct-use geothermal systems, highlighting the importance of well conditioning and reservoir heterogeneity characterization in constraining thermal responses.
The authors regret that during a post-publication review of the numerical model, we identified that rock thermal conductivity and rock heat capacity were not transferred properly for the ensemble run and were set to zero for the energy conservation equation. This resulted in earlier thermal breakthroughs because conductive heat transfer between the reservoir and the surrounding rock matrix was not accounted for. After correcting the model and rerunning the simulations, we found that the correction affects only the reported numerical values. The overall trends, relative comparisons between scenarios, interpretations, and scientific conclusions presented in the paper remain unchanged. The inclusion of rock thermal conductivity primarily delays thermal breakthrough and therefore we extend the simulation time from 30 years to 80 years in base case to capture long-term thermal behavior. The sensitivity analysis indicates that the ranking of parameter importance remains consistent, whereas the magnitude of the importance scores increase after introducing the rock thermal conductivity and rock heat capacity.
...
The authors regret that during a post-publication review of the numerical model, we identified that rock thermal conductivity and rock heat capacity were not transferred properly for the ensemble run and were set to zero for the energy conservation equation. This resulted in earlier thermal breakthroughs because conductive heat transfer between the reservoir and the surrounding rock matrix was not accounted for. After correcting the model and rerunning the simulations, we found that the correction affects only the reported numerical values. The overall trends, relative comparisons between scenarios, interpretations, and scientific conclusions presented in the paper remain unchanged. The inclusion of rock thermal conductivity primarily delays thermal breakthrough and therefore we extend the simulation time from 30 years to 80 years in base case to capture long-term thermal behavior. The sensitivity analysis indicates that the ranking of parameter importance remains consistent, whereas the magnitude of the importance scores increase after introducing the rock thermal conductivity and rock heat capacity.
Preprint
(2026)
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Yuan Chen, Guillaume Rongier, James Robert Mullins, Denis Voskov, Alexandros Daniilidis
Low-enthalpy geothermal doublets for direct-use heating are highly sensitive to subsurface heterogeneity and operational uncertainty. This study quantifies these uncertainties for the Delft campus geothermal system using an integrated workflow that couples geological modeling with GPU-accelerated, high-spatial-resolution reservoir simulation. Ensembles of three-dimensional regional-scale facies models of the Delft Sandstone Member, with and without conditioning to Geothermie Delft (GTD) well data, were generated using object-based modeling and sequential indicator simulation. Porosity was modeled by sequential Gaussian simulation, and permeability was derived from a nuclear magnetic resonance–based porosity–permeability correlation calibrated to GTD well data, yielding higher permeability than core-based correlations for porosity below 15%. Lorenz coefficients indicate strong variability in property distributions, resulting in a wide spread of production temperatures. In total, 2000 geological realizations were simulated over 50 years using the GPU-enabled open-source Delft Advanced Research Terra Simulator (open-DARTS) under maximum and 2025-demand production schemes. Conditioning to GTD wells reduces uncertainty in production bottom-hole temperature (BHT) and pressure (BHP) while maintaining injection pressure below Dutch regulatory limits. SIS models exhibit greater temperature and pressure variability than OBM models due to lower sand-body continuity. Despite large 80% confidence intervals, P50 production temperatures remain comparable for conditioned models. Distance-based generalized sensitivity analysis identifies net-to-gross ratio and the porosity–permeability correlation as dominant controls on thermal response. The 2025-demand scheme delays cold-front propagation. Results demonstrate that ensemble-based, GPU-accelerated high-spatial-resolution simulations enable robust and efficient uncertainty quantification for direct-use geothermal systems, highlighting the importance of well conditioning and reservoir heterogeneity characterization in constraining thermal responses.
...
Low-enthalpy geothermal doublets for direct-use heating are highly sensitive to subsurface heterogeneity and operational uncertainty. This study quantifies these uncertainties for the Delft campus geothermal system using an integrated workflow that couples geological modeling with GPU-accelerated, high-spatial-resolution reservoir simulation. Ensembles of three-dimensional regional-scale facies models of the Delft Sandstone Member, with and without conditioning to Geothermie Delft (GTD) well data, were generated using object-based modeling and sequential indicator simulation. Porosity was modeled by sequential Gaussian simulation, and permeability was derived from a nuclear magnetic resonance–based porosity–permeability correlation calibrated to GTD well data, yielding higher permeability than core-based correlations for porosity below 15%. Lorenz coefficients indicate strong variability in property distributions, resulting in a wide spread of production temperatures. In total, 2000 geological realizations were simulated over 50 years using the GPU-enabled open-source Delft Advanced Research Terra Simulator (open-DARTS) under maximum and 2025-demand production schemes. Conditioning to GTD wells reduces uncertainty in production bottom-hole temperature (BHT) and pressure (BHP) while maintaining injection pressure below Dutch regulatory limits. SIS models exhibit greater temperature and pressure variability than OBM models due to lower sand-body continuity. Despite large 80% confidence intervals, P50 production temperatures remain comparable for conditioned models. Distance-based generalized sensitivity analysis identifies net-to-gross ratio and the porosity–permeability correlation as dominant controls on thermal response. The 2025-demand scheme delays cold-front propagation. Results demonstrate that ensemble-based, GPU-accelerated high-spatial-resolution simulations enable robust and efficient uncertainty quantification for direct-use geothermal systems, highlighting the importance of well conditioning and reservoir heterogeneity characterization in constraining thermal responses.
Direct Use Geothermal Systems (DUGS) are rapidly and densely deployed to meet the growing demand for renewable energy with less carbon emissions globally. The simulation of DUGS can provide a reservoir-scale understanding of geothermal resource assessment, where the geothermal system's lifetime and the injection well Bottom Hole Pressure (BHP) are used as performance indicators. However, there are inherent errors from numerical simulations of any engineering problems, due to approximating continuous partial differential equations by their discretized approximation in time and space. In this work, we establish an optimal numerical setup with reduced errors across the homogeneous, stratified and heterogeneous models for the simulation of a geothermal system. Next, we develop a standardized method for calculating recoverable Heat In Place (HIP) and an analytical solution for evaluating the HIP recovery factor across various geological models using a single forward simulation. We present reference examples on the design of DUGS simulations using the open-source software Delft Advanced Research Terra Simulator (open-DARTS). The open-DARTS platform enables accurate and efficient sensitivity and uncertainty analysis. Using Distance-Based Generalized Sensitivity Analysis (DGSA), we identify reservoir depth and discharge rate as the most influential parameters for geothermal projects across all three types of geological models.
...
Direct Use Geothermal Systems (DUGS) are rapidly and densely deployed to meet the growing demand for renewable energy with less carbon emissions globally. The simulation of DUGS can provide a reservoir-scale understanding of geothermal resource assessment, where the geothermal system's lifetime and the injection well Bottom Hole Pressure (BHP) are used as performance indicators. However, there are inherent errors from numerical simulations of any engineering problems, due to approximating continuous partial differential equations by their discretized approximation in time and space. In this work, we establish an optimal numerical setup with reduced errors across the homogeneous, stratified and heterogeneous models for the simulation of a geothermal system. Next, we develop a standardized method for calculating recoverable Heat In Place (HIP) and an analytical solution for evaluating the HIP recovery factor across various geological models using a single forward simulation. We present reference examples on the design of DUGS simulations using the open-source software Delft Advanced Research Terra Simulator (open-DARTS). The open-DARTS platform enables accurate and efficient sensitivity and uncertainty analysis. Using Distance-Based Generalized Sensitivity Analysis (DGSA), we identify reservoir depth and discharge rate as the most influential parameters for geothermal projects across all three types of geological models.
Conference paper
(2024)
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I. Saifullin, D. Voskov, Y. Chen, A. Novikov, M. Wapperom, M. Khait, X. Tian, X. Lyu, S. De Hoop, L. Orozco, A. Palha
The open Delft Advanced Research Terra Simulator (open-DARTS) framework is an open-source reservoir simulation software. The open-DARTS focused on energy transition applications, such as geothermal energy production and carbon sequestration. It enables the modeling of compositional thermal flow, coupled with a geomechanical solver based on the Finite Volume discretization and adjoints method for inverse modeling. The open-DARTS supports different grid types (structured, corner-point geometry, and unstructured), discrete fracture networks, contact mechanics, and various thermal-chemical interactions. The recently proposed generic nonlinear formulation supports the most general nonlinear PDEs designed for various energy transition applications. The open-DARTS has been implemented in C++ and Python to optimize hardware utilization while ensuring flexibility. The most computationally expensive part is written in C++ and compiled into libraries, which are subsequently exposed to Python using pybind11. This allows the extension and overriding of C++ functions by user-defined Python code. For example, using only a Python interface, one can adjust a timestep strategy, nonlinear solver, or properties output. Besides, the Python interface of open-DARTS provides straightforward coupling with other Python-based numerical modeling packages, including the meshing, file storage, caching, and visualization modules. The open-DARTS core uses the advantages of C++ language, such as efficient low-level memory management, object-oriented programming, compile-time polymorphism, and parallelization with OpenMP. One of the advantages of open-DARTS is the Operator-Based Linearization (OBL) technique, which can resolve challenges associated with complex physics and reduce the computation time, especially for ensemble-based simulations. We would also like to share our experience on the project, repository, and the development workflow configuration using gitlab.com, including the build system (cmake), handling merge requests, automated testing in CI/CD pipelines, documentation management (gitlab.io), wiki utilization, and release publishing. Additionally, Python’s integration into open-DARTS offers the advantage of straightforward installation via PyPI and simplifies defining requirements for users who prefer to avoid compiling code from source files.
...
The open Delft Advanced Research Terra Simulator (open-DARTS) framework is an open-source reservoir simulation software. The open-DARTS focused on energy transition applications, such as geothermal energy production and carbon sequestration. It enables the modeling of compositional thermal flow, coupled with a geomechanical solver based on the Finite Volume discretization and adjoints method for inverse modeling. The open-DARTS supports different grid types (structured, corner-point geometry, and unstructured), discrete fracture networks, contact mechanics, and various thermal-chemical interactions. The recently proposed generic nonlinear formulation supports the most general nonlinear PDEs designed for various energy transition applications. The open-DARTS has been implemented in C++ and Python to optimize hardware utilization while ensuring flexibility. The most computationally expensive part is written in C++ and compiled into libraries, which are subsequently exposed to Python using pybind11. This allows the extension and overriding of C++ functions by user-defined Python code. For example, using only a Python interface, one can adjust a timestep strategy, nonlinear solver, or properties output. Besides, the Python interface of open-DARTS provides straightforward coupling with other Python-based numerical modeling packages, including the meshing, file storage, caching, and visualization modules. The open-DARTS core uses the advantages of C++ language, such as efficient low-level memory management, object-oriented programming, compile-time polymorphism, and parallelization with OpenMP. One of the advantages of open-DARTS is the Operator-Based Linearization (OBL) technique, which can resolve challenges associated with complex physics and reduce the computation time, especially for ensemble-based simulations. We would also like to share our experience on the project, repository, and the development workflow configuration using gitlab.com, including the build system (cmake), handling merge requests, automated testing in CI/CD pipelines, documentation management (gitlab.io), wiki utilization, and release publishing. Additionally, Python’s integration into open-DARTS offers the advantage of straightforward installation via PyPI and simplifies defining requirements for users who prefer to avoid compiling code from source files.
A research and production geothermal project on the TU Delft campus
Initial modeling and establishment of a digital twin
Conference paper
(2024)
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Denis Voskov, Hemmo Abels, Philip J. Vardon, Liliana Vargas Meleza, Eric Verschuur, Andrea Vondrak, Auke Barnhoorn, Yuan Chen, Alexandros Daniilidis, David Bruhn, Guy Drijkoningen, Sebastian Geiger, Susanne Laumann, Guofeng Song
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.
...
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.