The goal of rNodal is to provide nodal analysis for oil and gas wells.

You can install rNodal from github with:

# install.packages("devtools")
devtools::install_github("f0nzie/rNodal")

This is a basic example which shows you how to solve a common problem:

## basic example code

zFactor is a R package. Calling from CRAN.

We will use zFactor for gas compressibility calculations.

# use the new library zFactor
library(zFactor)

z.HallYarborough(pres.pr = 4.5, temp.pr = 1.4)
#> [1] 0.7373812
z.DranchukAbuKassem(pres.pr = 4.5, temp.pr = 1.4)
#> [1] 0.7396345
z.BeggsBrill(pres.pr = 4.5, temp.pr = 1.4)
#> [1] 0.7343367
z.Ann10(pres.pr = 4.5, temp.pr = 1.4)
#> [1] 0.736032
z.Papp(pres.pr = 4.5, temp.pr = 1.4)
#> [1] 0.7299354

Start by looking at the examples in the vignettes. We will use in this example VLP Brown - Example C13.

This is example C.13 in the Kermit Brown book.

We enter the well data with the function setWellInput:

input.example.C13 <- setWellInput(field.name = "HAGBR.MOD",
                                    well.name = "Brown_C13", 
                                    depth.wh = 0, depth.bh = 2670, 
                                    diam.in = 1.995, 
                                    GLR = 500, liq.rt = 1000, wcut = 0.6, 
                                    thp = 500, tht = 120, bht = 150, 
                                    API = 22, gas.sg = 0.65, 
                                    wat.sg = 1.07, if.tens = 30)
                                    
                                    

The field name and well name are used for archival purposes.

The parameters of the model consist of:

vlp.model: the correlation or mechanistical model

segments: the number of segments to split the well

tol: the tolerance of the delta-P iterations

well.model <- setVLPmodel(vlp.model = "hagbr.mod", 
                           segments = 11, 
                                tol = 0.000001)
                                
                                
                                

To run the model is necessary to provide:

well.input: all the well parameters as entered in the first step

well.model: the VLP model as entered in the second step

runVLP(well.input = input.example.C13, well.model))

The results are given in the form of a dataframe where the rows represent the number of segment plus one and the columns are the calculations or variables.