API Reference

Bases: BaseAquifer

Aquifer with statistically distributed thickness and permeability.

Used as input to ThermoGISDoublet when reservoir properties are uncertain. Thickness follows a normal distribution and permeability a log-normal distribution. Pass p_values to ThermoGISDoublet.simulate to sample realisations at specific percentile levels.

Parameters:

Name	Type	Description	Default
thickness_mean	float or array	Mean aquifer thickness [m]. Must be >= 0.	required
thickness_sd	float or array	Standard deviation of aquifer thickness [m]. Must be >= 0.	required
ln_permeability_mean	float or array	Mean of the natural log of permeability [ln(mD)].	required
ln_permeability_sd	float or array	Standard deviation of the natural log of permeability [ln(mD)].	required
porosity	float or array	Aquifer porosity [-], between 0 and 1.	required
ntg	float or array	Net-to-gross ratio [-], between 0 and 1.	required
depth	float or array	Aquifer depth [m].	required
temperature	float or array	Reservoir temperature [°C]. If not provided, it is calculated from depth using the temperature gradient and surface temperature in UTCSettings when passed to ThermoGISDoublet.	required
mask	float or array	Mask array. Cells where the mask is not NaN are excluded from the simulation. Defaults to NaN (no masking).	required

Source code in pythermogis/aquifer.py

class StochasticAquifer(BaseAquifer):
    """Aquifer with statistically distributed thickness and permeability.

    Used as input to ``ThermoGISDoublet`` when reservoir properties are
    uncertain. Thickness follows a normal distribution and permeability a
    log-normal distribution. Pass ``p_values`` to ``ThermoGISDoublet.simulate``
    to sample realisations at specific percentile levels.

    Parameters
    ----------
    thickness_mean : float or array
        Mean aquifer thickness [m]. Must be >= 0.
    thickness_sd : float or array
        Standard deviation of aquifer thickness [m]. Must be >= 0.
    ln_permeability_mean : float or array
        Mean of the natural log of permeability [ln(mD)].
    ln_permeability_sd : float or array
        Standard deviation of the natural log of permeability [ln(mD)].
    porosity : float or array
        Aquifer porosity [-], between 0 and 1.
    ntg : float or array
        Net-to-gross ratio [-], between 0 and 1.
    depth : float or array
        Aquifer depth [m].
    temperature : float or array, optional
        Reservoir temperature [°C]. If not provided, it is calculated from
        ``depth`` using the temperature gradient and surface temperature in
        ``UTCSettings`` when passed to ``ThermoGISDoublet``.
    mask : float or array, optional
        Mask array. Cells where the mask is not ``NaN`` are excluded from the
        simulation. Defaults to ``NaN`` (no masking).
    """

    thickness_mean: FloatOrArray
    thickness_sd: FloatOrArray
    ln_permeability_mean: FloatOrArray
    ln_permeability_sd: FloatOrArray

    @field_validator("thickness_mean", "thickness_sd", mode="after")
    @classmethod
    def check_non_negative(cls, value: FloatOrArray, info) -> FloatOrArray:
        if isinstance(value, xr.DataArray):
            if (value < 0.0).any():
                raise ValueError(
                    f"{info.field_name} must always be >= 0.0; "
                    f"negative values are not allowed"
                )
        elif value < 0.0:
            raise ValueError(
                f"{info.field_name} must always be >= 0.0; "
                f"negative values are not allowed"
            )
        return value

    def calculate_temperature(
        self, temperature_gradient: float, surface_temperature: float
    ) -> None:
        self.temperature = calculate_temperature_from_gradient(
            self.depth, self.thickness_mean, temperature_gradient, surface_temperature
        )