3DHIP-Calculator—A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models
Abstract
:1. Introduction
2. Materials and Methods
2.1. Mathematical Background of the HIP Method
2.2. Mathematical Background of the Monte Carlo Method
2.3. Program Description
2.3.1. Pre-Processing: Input Data
2.3.2. Post-Processing: Output Data
- Generate a CDF for each voxel, from which a probability 10% (P10) (very low confidence of the estimation and high values), P50, and P90 (high confidence of the estimation and low values) are extracted. Furthermore, the mean and standard deviation are also calculated.
- Generate a CDF for the entire investigated target (e.g., geological unit, reservoir, etc.) summing the voxel values, and the P10, P50, and P90 are calculated. This approach is only used for the HIP calculation and not for the Hrec one.
- Generate 2D maps using the relationship between the vertical sum of the values calculated in each voxel with respect to the area occupied by the voxel (in km2). The P10, P50, and P90 of HIP and Hrec are then estimated.
- The application allows exporting two ASCII files with all results for further post-processing and generates an automatic report that summarizes the input data and the main results.
2.3.3. Modeling Scenarios Depending on Data Availability
3. Example Case Study—The Reus-Valls Basin (NE, Spain)
3.1. Geological Setting
3.2. The Potential Hot Deep Sedimentary Aquifers
3.2.1. Example 1: Using a Single-Voxel 1D Geological Model
3.2.2. Example 2: Using a 3DGM but Not a 3DTM
3.2.3. Example 3: Using Both a 3DGM and a 3DTM
3.2.4. Example 4: The Use of the Recoverable Heat (Hrec) Values
4. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Property | Units | PDFs | Values | |
---|---|---|---|---|
Petrophysical | Porosity | - | Triangular | Low: 0.07, Max: 0.12, Upp: 0.18 |
Fluid Density | kg/m3 | Normal | Mean: 1020, SD: 5 | |
Fluid specific heat capacity | kJ/kg·°C | Normal | Mean: 4.8, SD: 0.1 | |
Rock density | kg/m3 | Triangular | Low: 2450, Max: 2500, Upp: 2600 | |
Rock specific heat capacity | kJ/kg·°C | Normal | Mean: 0.9, SD: 0.01 | |
Operational | Recovery factor | - | Triangular | Min: 0.08, Max: 0.12, Upp: 0.15 |
Reinjection temperature | °C | - | 30 | |
Conversion efficiency | - | - | 0.85 | |
Plant factor | - | - | 0.95 | |
Mean plant lifetime | years | - | 30 |
Hrec—Recoverable Heat vs. Estimated R—Radius of Influence | Hrec P10 (kWt) | Hrec P50 (kWt) | Hrec P90 (kWt) |
---|---|---|---|
R = 0.5 km | 1337 | 1140 | 927 |
R = 1 km | 6127 | 5185 | 4211 |
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Piris, G.; Herms, I.; Griera, A.; Colomer, M.; Arnó, G.; Gomez-Rivas, E. 3DHIP-Calculator—A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models. Energies 2021, 14, 7338. https://doi.org/10.3390/en14217338
Piris G, Herms I, Griera A, Colomer M, Arnó G, Gomez-Rivas E. 3DHIP-Calculator—A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models. Energies. 2021; 14(21):7338. https://doi.org/10.3390/en14217338
Chicago/Turabian StylePiris, Guillem, Ignasi Herms, Albert Griera, Montse Colomer, Georgina Arnó, and Enrique Gomez-Rivas. 2021. "3DHIP-Calculator—A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models" Energies 14, no. 21: 7338. https://doi.org/10.3390/en14217338
APA StylePiris, G., Herms, I., Griera, A., Colomer, M., Arnó, G., & Gomez-Rivas, E. (2021). 3DHIP-Calculator—A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models. Energies, 14(21), 7338. https://doi.org/10.3390/en14217338