#__all__ = ['tf', 'gradient', 'horner']
import numpy as np
'''
List of functions:
tf - formation temperature
gradient -
horner -
'''
def tf(t0, gradient, depth):
'''
tf(t0, depth, gradient)
*Input parameters:
- t0 - annual surface mean temperature [C] or [F]
- gradient - [C/m] or [F/ft]
- depth - at which temperature will be calculated [m] or [ft]
*Returns:
- tf - formation temperature [C] or [ft] based on temperature gradient
'''
tf = t0 + depth * gradient
return tf
def gradient(t0, tf, depth):
'''
gradient(t0, tf, depth)
*Input parameters
- t0 - annual surface mean temperature [C] or [F]
- tf - formation temperature [C] or [ft]
- depth - at which temperatures will be calculated [m] or [ft]
*Returns:
- gradient - [C/m] or [F/ft]
'''
gradient = (tf - t0) / depth
return gradient
def horner(circulation_time, times, temp):
'''
horner_bht_temp (circulation_time, times, temp)
*Input parameters:
- circulation_time - hours from last circulation;
- times - total time since circulation stopped at 1st Run, 2nd Run and so on ...
- temp - a list o temperatures coresponding to 1st Run, 2nd Run and so on ...
*Returns:
- horner_temp - formation temperature estimated by Horner method (thermometer readings
from different runs)
*Exemple of usage:
horner(6, (7.0,11.5,19.5), (100,105,108))
where:
circulation_time = 6 # time since circulation stopped (hours)
times = (7.0,11.5,19.5) # total time since circulation stopped at 1st, 2nd, 3rd RUN (hours)
temp=(100,105,108) # temperatures recorded at 1st, 2nd, 3rd RUN (Celsius degrees)
'''
horner_time = np.array(times) / (circulation_time + np.array(times))
slope,intercept = np.polyfit (np.log(horner_time), temp, 1)
horner_temp=round(slope*np.log(1) +intercept,2)
return horner_temp
