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pythermogis calculation methods

introduction

pythermogis is a Python package that provides API access to pre-drill doublet simulations and economic calculations implemented in ThermoGIS. ThermoGIS is a web-based information system for geothermal prospectivity that has originally been developed to support Geothermal development in the Netherlands, and has promoted a very successful geothermal energy development for direct heating. Over the past two decades, 84 deep geothermal wells in a depth range of 1500-3000 m have been drilled serving mostly as injection and production wells in a geothermal doublet configuration (marked by complete reinjection of produced brines, Van Wees et al., 2012; Mijnlieff, 2020), with a total 6.9 PJ/y of geothermal heat produced in 2023 (Van der Molen and Tolsma, 2024). The Netherlands is currently one of the leading countries in Europe in terms of installed geothermal capacity for direct heating. In the EU27, Netherlands ranks first in terms of exploited geothermal heating and cooling per surface area, and third in terms of the number of installed geothermal plants for geothermal district heating (EGEC, 2024). The first successful deep geothermal system was completed less than 20 years ago in 2007.

At the heart of pythermogis and ThermoGIS is the DoubletCalc1D doublet technical performance assesment tool (van Wees et al., 2012), which is a software tool developed by TNO that calculates how much geothermal water can be pumped at a given pump power, taking into account well engineering aspects and specific subsurface conditions, including aquifer temperature, and reservoir flow properties.

pythermogis is very flexible and can be applied for:

  • site-specific analysis
  • grid input based reservoir properties
  • uncertainties in input distributions of reservoir properties, e.g. to analyse Probaility of Succes (POS)

Approach

The geothermal power which can be produced takes into account the production flow rate Q, and the cooling of the produced brine in the heat conversion process:

E = 𝜂 Q C ΔT

where:

  • E is the converted power [W]
  • 𝜂 is the conversion efficiency [-], which depends on the heat conversion system
  • Q is the flow rate of the produced brine [m³/s]
  • C is the volumetric heat capacity of the brine or circulation fluid [J m⁻³ K⁻¹]
  • ∆T is the temperature difference between the producer and injector at the topside at the heat exchanger [K]

Doublet flow and thermal performance

Achievable flow rates are calculated with doublet model, as it has been incorporated in ThermoGIS The doublet engineering (i.e. Well spacing at reservoir depth) is optimized for the specified lifetime, and the allowed temperature drop at the producer well.

Geothermal Resources

  • geothermal resources: The geothermal resource is considered as a permeable subsurface layer, which can be corresponding a permeable sedimentary rock or fractured basement or magmatic rock. The geothermal resource parameters include reservoir depth, thickness, temperature, brine compositions, and reservoir flow properties such as permeability and porosity.

Energy Conversion

  • Energy converion The technical performance calculation is linked with an energy conversion scenario module, allowing to take into account various scenarios for geothermal energy utilization, and associated conversion efficiency 𝜂:

  • Direct heating with and without Heat Pump

  • Adsorption/absorption chiller
  • Organic Rankine Cycle or ORC for power

Economic Model

  • economic model: The economic model performs a UTC (Unit Technical Cost) calculation, incorporating a discounted cash flow approach:
  • CAPEX (Capital Expenditure) and OPEX (Operational Expenditure) are calculated based on the well design, reservoir properties, and energy conversion scenario.
  • The UTC is calculated as the ratio of the total discounted cost to the total discounted energy produced over the lifetime of the geothermal system.
  • The economic model allows for sensitivity analysis on key parameters such as reservoir properties, asscoiated flow rate, and conversion efficiency.

Key Performance indicators

  • key performance indicators: The key performance indicators (KPIs) are calculated based on the technical performance and economic model, providing insights into the feasibility and profitability of geothermal projects. These include next to minput parameters:
  • net power (power in MWth or MWe)
  • Unit Technical Costs (UTC in €ct/kWh)
  • Net present value (NPV in million €)

References

  1. EGEC, 2024. Geothermal Market report 2023. https://www.egec.org/media-publications/egec-releases-the-2023-geothermal-market-report/ .
  2. Van Wees et al., 2012. Geothermal aquifer performance assessment for direct heat production–Methodology and application to Rotliegend aquifers. Netherlands Journal of Geosciences, 91(4), 651-665. https://doi.org/10.1017/S0016774600000433
  3. Mijnlieff, 2020. Introduction to the geothermal play and reservoir geology of the Netherlands. Netherlands Journal of Geosciences.https://doi.org/10.1017/njg.2020.2
  4. Van der Molen and Tolsma, 2024. Van der Molen, J., Tolsma, S., 2024. Aardwarmte in Nederland- 2023: een recordjaar, maar toch teleurstellend (in Dutch), www.tno.nl .