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Heat Flow Quality Analysis Toolbox (hfqa_tool)

hfqa_tool is a python package for validating heat-flow data against the IHFC Global Heat Flow Database (GHFDB) schema and assessing data quality according to International Heat Flow Commission standards, including quality scoring based on the methodology described in Fuchs et al., 2024 (https://doi.org/10.1016/j.tecto.2023.229976). This is an updated and fully revised version of Chishti et al. (2025, https://doi.org/10.5880/fidgeo.2025.043)

Input data for Deep Borehole Heat Exchangers (DBHEs) modelling at the Groß Schönebeck research platform, comprising reservoir properties, wellbore trajectories, discretized grids, and well completion design for CMG STARS simulation

This dataset contains a high-fidelity three-dimensional (3D) reservoir model developed for numerical simulation using the CMG STARS reservoir simulator. The model is based on the geological framework of the Groß Schönebeck geothermal research platform and discretized into a Cartesian grid, which provides the numerical basis for thermo-hydraulic reservoir simulations. Key physical parameters, including rock petrophysical and fluid properties, have been incorporated into the model based on the interpretation of subsurface data acquired at the Groß Schönebeck site. The dataset comprises simulator input files developed to model a closed-loop geothermal system using the existing wells E GrSk 3/90 and Gt GrSk 4/05. Two completion depths, 3,600 m and 3,800 m measured depth (MD), were evaluated to investigate the performance of a coaxial deep borehole heat exchanger (DBHE) system. The numerical simulations assess the effects of completion depth, circulation flow rate, and injection temperature on the thermal performance of the closed-loop system.

Input data for Enhanced Geothermal System (EGS) modelling at the Groß Schönebeck research platform, comprising reservoir properties, wellbore trajectories, discretized grids, and fracture models for CMG STARS simulation

This dataset contains a reservoir model developed for high-fidelity numerical simulation using the CMG STARS reservoir simulator. This three-dimensional (3D) subsurface model is based on a geological framework which has been divided into a Cartesian grid. This grid provides the numerical basis for reservoir simulation. Key physical parameters have been incorporated into the model, including rock petrophysical properties, fluid properties and fracture geometries. These parameters have been derived from the interpretation of subsurface data acquired at the Groß Schönebeck geothermal research platform. To improve predictive reliability, the model was calibrated against field-scale hydraulic test data collected between 2011 and 2013. The numerical model is designed to simulate fracture-dominated enhanced geothermal system (EGS) scenarios within the Rotliegend reservoir. Its primary purpose is to evaluate the performance of different well layouts and multi-stage hydraulic fracture designs in terms of reservoir productivity.

CRM-geothermal Database: Geoscientific and Geochemical Data on Geothermal Systems, with Emphasis on Fluids and Critical Raw Materials in Europe and Eastern Africa

The CRM-geothermal database was created within the Horizon Europe CRM-geothermal project (Grant Agreement No. 101058163) to support the assessment of geothermal systems as sources of both renewable energy and critical raw materials (CRMs). The primary purpose of data collection was to compile, harmonise, and make openly available geoscientific and geochemical data relevant to the occurrence, enrichment, and potential co-production of CRMs from geothermal environments in Europe and East Africa. The database integrates legacy data compiled from peer-reviewed literature, national geological and geothermal databases, and previous European research projects (notably REFLECT), together with new data generated by project partners through field sampling and laboratory analyses. Sampling campaigns targeted geothermal wells and surface manifestations in selected regions, including Türkiye, the East African Rift (Kenya, Tanzania, Malawi), Cornwall (UK), and Iceland. Laboratory analyses include major ion chemistry, trace and critical element concentrations, mineralogical composition, and gas data, determined using methods such as ICP-MS, XRF, and XRD. All records were harmonised using a unified metadata schema, standardised units, and consistent reporting formats. Quality control involved automated validation routines and manual expert review. Each record includes spatial coordinates, sampling context, analytical method, references, and a quality flag indicating data origin and traceability. The database is provided as a structured Excel file and contains interconnected datasets on geothermal wells, fluids, rocks, gases, and mineral precipitates. In total, the dataset comprises 9,773 records covering a wide range of geological settings, from volcanic and metamorphic systems to sedimentary basins. The CRM-geothermal database is FAIR-aligned, openly available, and intended for reuse in geothermal research, resource assessment, and studies on the sustainable co-production of geothermal energy and critical raw materials. Method: The CRM-geothermal database was compiled using a combined approach integrating literature-based data collection, database harmonisation, and new data generation through field sampling and laboratory analysis. Legacy data were collected from peer-reviewed scientific publications, national geological and geothermal databases, technical reports, and previous European research projects, with a particular emphasis on the REFLECT project. Relevant parameters were manually extracted, digitised where necessary, and cross-checked against original sources to ensure consistency and traceability. New data were generated within the CRM-geothermal project through targeted sampling campaigns at selected geothermal sites in Europe and Eastern Africa. Samples of geothermal fluids, rocks, gases, and mineral precipitates were collected from wells and surface manifestations following standard geochemical sampling protocols. Laboratory analyses were performed by project partner institutions using established analytical techniques, including inductively coupled plasma mass spectrometry (ICP-MS) for trace and critical elements, X-ray fluorescence (XRF) for bulk chemical composition, and X-ray diffraction (XRD) for mineralogical characterisation. Gas compositions were determined using gas chromatography and noble gas mass spectrometry where applicable. Detection limits and analytical uncertainties follow laboratory-specific standards and are documented where available. All data were harmonised using a unified metadata schema. Units, parameter names, and reporting formats were standardised, and spatial information was converted to WGS 84 decimal degrees. Quality control was applied through automated validation scripts checking metadata completeness, coordinate validity, and numerical plausibility, followed by manual expert review to ensure scientific coherence and correct sample attribution. The final dataset was organised into interconnected thematic tables (wells, fluids, rocks, gases, and scales) and exported as a structured Excel file for dissemination. Each record includes references, analytical method information, and a quality flag indicating data origin and traceability. Technical Info: The CRM-geothermal data publication is provided as a structured multi-sheet Excel (XLSX) file representing a curated snapshot of the CRM-geothermal database at the time of publication. The dataset was generated through controlled export workflows following data validation and harmonisation. The Excel file contains separate worksheets for thematic data tables (wells, fluids, rocks, gases, and mineral precipitates). Each worksheet preserves unique identifiers, standardised metadata fields, and cross-references between related records, allowing the dataset to be used independently of any external system or software platform.

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