Arps decline_fit prediction — decline

Generate a list of estimates for the Arps decline model according to the class of 'decline_fit_lst' and 'time_lst' objects

decline_fit(decline_fit_lst, time_lst)

Arguments

decline_fit_lst	a list object of class 'decline_fit'
time_lst	a list object of class 'time'

Value

a list of estimates for the parameters of the Arps model according to the class of 'decline_fit_lst' and 'time_lst' objects

Examples

dcl_time_hyp <- decline_time(1:10000, unit = "day")
prod_data <- 4500 / (1 + 0.002 * 0.834 * dcl_time_hyp$t) ^ (1 / 0.834)
dcl_fit_param_hyp <- decline_fit_param(input_unit = "Field", output_unit = "Field",
fluid = "gas", model = "hyperbolic", fit_data = "rate", prod_data = prod_data,
initial_param = c(1000, 0.01, 1.0), lower = c(0, 1e-6, 1e-6), upper = NULL,
control = list(maxiter = 100))
dcl_fit_hyp <- decline_fit(dcl_fit_param_hyp, dcl_time_hyp)

dcl_fit_hyp
#> $input_unit
#> [1] "Field"
#> 
#> $output_unit
#> [1] "Field"
#> 
#> $fluid
#> [1] "gas"
#> 
#> $qi
#> [1] 4500
#> 
#> $Di
#> [1] 0.002
#> 
#> $b
#> [1] 0.834
#> 
#> attr(,"nls.out")
#> Nonlinear regression via the Levenberg-Marquardt algorithm
#> parameter estimates: 4499.99996179776, 0.00199999997462462, 0.834000032753601 
#> residual sum-of-squares: 2.352e-15
#> reason terminated: Relative error between `par' and the solution is at most `ptol'.
#> attr(,"class")
#> [1] "hyperbolic" "decline"