SCALE CORRECTION FOR Permeability

data = read.csv("karpur.csv")
data$phi.core = data$phi.core / 100
head(data)

plot(data$phi.N, data$phi.core , xlab = "Porosity log" , ylab = "Porosity core" ) 

porosity_model <- lm( phi.core~phi.N + Facies - 1, data = data)
summary(porosity_model)

Call:
lm(formula = phi.core ~ phi.N + Facies - 1, data = data)

Residuals:
      Min        1Q    Median        3Q       Max 
-0.103530 -0.011573 -0.000206  0.010463  0.102852 

Coefficients:
          Estimate Std. Error t value Pr(>|t|)    
phi.N     0.013364   0.018060    0.74     0.46    
FaciesF1  0.314805   0.002777  113.37   <2e-16 ***
FaciesF10 0.207680   0.005072   40.95   <2e-16 ***
FaciesF2  0.175233   0.009390   18.66   <2e-16 ***
FaciesF3  0.231939   0.004955   46.81   <2e-16 ***
FaciesF5  0.272953   0.003914   69.74   <2e-16 ***
FaciesF7  0.225164   0.008730   25.79   <2e-16 ***
FaciesF8  0.305884   0.005019   60.94   <2e-16 ***
FaciesF9  0.264448   0.004825   54.81   <2e-16 ***
---
Signif. codes:  
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.02326 on 810 degrees of freedom
Multiple R-squared:  0.9928,    Adjusted R-squared:  0.9928 
F-statistic: 1.246e+04 on 9 and 810 DF,  p-value: < 2.2e-16

corrected_porosity <- predict(porosity_model, data)

permeability_model <- lm( k.core~corrected_porosity + Facies - 1 , data = data)
summary(permeability_model)

Call:
lm(formula = k.core ~ corrected_porosity + Facies - 1, data = data)

Residuals:
    Min      1Q  Median      3Q     Max 
-5613.4  -596.9  -130.3   475.0 10449.1 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)
corrected_porosity  -412352      89814  -4.591 5.11e-06
FaciesF1             132659      28386   4.673 3.47e-06
FaciesF10             87869      18969   4.632 4.21e-06
FaciesF2              73980      16049   4.610 4.69e-06
FaciesF3              97910      21087   4.643 4.00e-06
FaciesF5             118916      24729   4.809 1.81e-06
FaciesF7              95868      20496   4.677 3.40e-06
FaciesF8             130990      27786   4.714 2.86e-06
FaciesF9             111324      24050   4.629 4.28e-06
                      
corrected_porosity ***
FaciesF1           ***
FaciesF10          ***
FaciesF2           ***
FaciesF3           ***
FaciesF5           ***
FaciesF7           ***
FaciesF8           ***
FaciesF9           ***
---
Signif. codes:  
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1546 on 810 degrees of freedom
Multiple R-squared:  0.7652,    Adjusted R-squared:  0.7626 
F-statistic: 293.2 on 9 and 810 DF,  p-value: < 2.2e-16

corrected_permeability <- predict(permeability_model, data = data)

par(mfrow = c(1,5))
boxplot(depth~Facies , data = data, ylim = rev(c(5667,6083)),col="black")
plot(data$phi.core, data$depth, ylim = rev(c(5667,6083)), xlim = c(0.1570,0.3630)
     ,lwd = 2 , xlab = "Porosity core" , ylab = "depth" , type = "l",col="black")

plot(corrected_porosity, data$depth, ylim = rev(c(5667,6083)), xlim = c(0.1775,0.3203)
     ,lwd = 2 , xlab = "Coreccted Porosity core" , ylab = "depth" , type = "l",col="black")
plot(data$k.core, data$depth, ylim = rev(c(5667,6083)), xlim = c(0.42,15600.00)
     ,lwd = 2 , xlab = "Permeability core" , ylab = "depth" , type = "l",col="black")

plot(corrected_permeability, data$depth, ylim = rev(c(5667,6083)), xlim = c(101.7,3445.3)
     ,lwd = 2 , xlab = "Corrected Permeability core" , ylab = "depth" , type = "l", col="black")