Customizing Doublet Simulation Parameters

To adjust properties of the simulation, you can pass a utc_properties instance to the calculate_doublet_performance function. A utc_properties instance is a JClass implementation of the Java UTCProperties class. It is generated by using the utc_properties_builder, upon which custom properties can be set, and used to build an instance of the utc_properties.

be aware: The number of parameters is large, and the default values are set to the ThermoGIS base case. A comprehensive list of parameters is given in UTC properties.

There are two ways to set the properties of the simulation, by either:

1. Using the utc_properties_builder class to set the properties of the simulation, and then building the utc_properties instance.
2. Using the instantiate_utc_properties_from_xml function to parse a configuration file, which will return a utc_properties instance.

customizing the thermoGIS techno-economic properties

The default and custom properties in Pythermogis can be found in thetests/resources/scenarios directory. The default properties are defined in the doublet_techno-econ_basecase.xml file, see also UTC properties for more information on the default properties and the ThermoGIS documentation.

🧰 Running Doublet simulations with custom simulation parameters

Common properties to change include:

• setUseHeatPump(Boolean): if true, include a heat-pump when modelling
• setUseStimulation(Boolean): if true, apply reservoir stimulation when simulating a doublet
• setSurfaceTemperature(float): The temperature of the surface
• setTempGradient(float): The gradient at which temperature increases with depth, in C/km
• setDhReturnTemp(float): The goal of the direct heat return temperature
• setStimKhMax(float): The maximum transmissivity above which no stimulation will occur (if UseStimulation = True)

Here is an example, where the default utc_properties is used, but the UseHeatPump option is set to True. this is achievied by instantiating a utc_properties_builder class, running .useHeatPump(True) on that class, and then building the utc_properties themselves, with the .build() method of the utc_properties_builder.

from pythermogis import calculate_doublet_performance, instantiate_utc_properties_builder
import xarray as xr

input_data = xr.Dataset({
    "thickness": 300,
    "ntg": 0.5,
    "porosity": 0.5,
    "depth": 2000,
    "permeability": 300,
})

utc_properties = instantiate_utc_properties_builder().setUseHeatPump(True).build()
results = calculate_doublet_performance(input_data, utc_properties=utc_properties)
print(results)

🧰 Running Doublet simulations with XML configuration files

below is an example of how to run a doublet simulation with custom properties defined in an XML file.

If you have a valid configuration file, you can parse a utc_properties class using the method: instantiate_utc_properties_from_xml. Examples of valid configuration files are found in tests/resources/test_input/scenarios. The vast majority of the parameters in the xml are not used by this python API; but are required by the ThermoGIS java code, unfortunately they are still needed in the xml file to enable parsing.

from src.pythermogis import calculate_doublet_performance_stochastic, instantiate_utc_properties_from_xml
import xarray as xr

input_data = xr.Dataset({
    "thickness_mean": 300,
    "thickness_sd": 50,
    "ntg": 0.5,
    "porosity": 0.5,
    "depth": 5000,
    "ln_permeability_mean": 5,
    "ln_permeability_sd": 0.5,
})

utc_properties = instantiate_utc_properties_from_xml("path/to/valid/xml/file")
results = calculate_doublet_performance_stochastic(input_data, utc_properties=utc_properties)
print(results)