bluebonnet.forecast.forecast¶
Fit and forecast production from hydrofractured reservoirs.
Classes¶
Set the upper and lower limits for the fitting curve. |
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Forecaster for production decline models. |
Module Contents¶
- class bluebonnet.forecast.forecast.Bounds[source]¶
Set the upper and lower limits for the fitting curve.
- Parameters:
M (tuple of floats) – (min, max) for resource in place
tau (tuple of floats) – (min, max) for time-to-BDF
- M: tuple[float, float]¶
Minimum and maximum resource in place
- tau: tuple[float, float]¶
Minimum and maximum time-to-boundary dominated flow
- class bluebonnet.forecast.forecast.ForecasterOnePhase[source]¶
Forecaster for production decline models.
- Parameters:
rf_curve (Callable) – the recovery factor over scaled time, as a callable (interpolators are best). So
rf_curve(time_scaled) -> recovery_factorbounds (Bounds) – the minimum and maximum values that the rf_curve accepts (watch the limits for the rf_curve function)
- rf_curve: collections.abc.Callable¶
function or interpolator with recovery factor over scaled time
- forecast_cum(time_on_production: numpy.typing.NDArray[numpy.float64], M: float | None = None, tau: float | None = None)[source]¶
Forecast cumulative production.
- Parameters:
time_on_production (ndarray) – time since the well started producing (days or years, ideally, since months are uneven)
M (float) – the resource in place (Mstb, Mscf, or other standard units)
tau (float) – the time until BDF/depletion flow (days or years, same units as time on prod)
- fit(time_on_production: numpy.ndarray, cum_production: numpy.ndarray, tau: float | None = None)[source]¶
Fit well production to the physics-based scaling model.
- Parameters:
time_on_production (ndarray) – time since the well started producing (days or years, ideally, since months are uneven)
cum_production (ndarray) – the cumulative production over time (Mstb, Mscf, or other standard units)
tau ([Optional float]) – the time-to-depletion (BDF), using the same units as time on prod. If not provided, will find best tau.