library(sp)
library(gstat)
library(dplyr)
library(ggplot2)
library(scales)
library(magrittr)

Data = read.csv("D:\\sumurjatibarang.csv")
coordinates(Data) = ~x+y
glimpse(Data)

Data%>%as.data.frame%>%
  ggplot(aes(x,y)) +
  geom_point(aes(size=k.fracture), col="blue", alpha=0.6) +
  ggtitle("permeabilitas (mD)") + coord_equal() + theme_bw()

kfracture.vgm = variogram(log(k.fracture)~1, Data, width = 0.08)
plot(kfracture.vgm)

n = 0.005
kolom = seq(Data@bbox[1,1]-n, Data@bbox[1,2]+n, by=n)
baris = seq(Data@bbox[2,1]-n, Data@bbox[2,2]+n, by=n)
the.grid = expand.grid(x=kolom,y=baris)
coordinates(the.grid) = ~x+y
gridded(the.grid) = T

plot(the.grid, cex=0.5)
points(Data, pch=1, col="red", cex =0.7)

(kfracture.fit = fit.variogram(kfracture.vgm, model = vgm(1,"Exp",0.4,0.1)))
plot(kfracture.vgm, kfracture.fit)

(kfracture.kriged <- krige(log(k.fracture)~1, Data, the.grid, model=kfracture.fit))

spplot(kfracture.kriged["var1.pred"], main = "ordinary kriging predictions 1")