#----------------------------------------------------------------
# Oil Initially In Place
# Monte Carlo simulation for estimating geologic oil reserves... 
# KOSOVA Robert, SHEHU Valentina, NAÇO Adrian,
# XHAFAJ Evgjeni, STANA Alma, YMERI Agim
#----------------------------------------------------------------
# Requiere cargar el paquete triangle: triangle_0.12.tar.gz
library(triangle)
#----------------------------------------------------------------
# 
N=10000
#
# Oilfield area (m2)
Area<-rtriangle(N,1500000, 3500000, 2500000)
#
# Thickness (m)
Thickness<-rtriangle(N,8,30,15)
#
# Porosity ratio (fraction)
Porosity<-rtriangle(N,0.05,0.35,0.22)
#
# Oil Saturation (fraction)
OilSaturation<-rtriangle(N,0.5,0.88,0.75)
#
# Density of oil (ton/m3)
OilDensity<-rtriangle(N,0.5,0.95,0.85)
#
# Formation Volume Factor (m3 reservoir/m3 std conditions)
Boil<-runif(N,1.18,1.22)
#
# Oil Initially In Place
OIIP<-Area*Thickness*Porosity*OilSaturation*OilDensity/Boil
#----------------------------------------------------------------
# OIIP (ton)
summary(OIIP)
#----------------------------------------------------------------
# Intervalo de Confianza 95% para la media
SD=sd(OIIP)
T=qt(p=0.975, df=N-1) 
OIIP_MAX=mean(OIIP)+T*SD/sqrt(N)
OIIP_MIN=mean(OIIP)-T*SD/sqrt(N)
mean(OIIP)
OIIP_MAX
OIIP_MIN
#---------------------------------------------------------------
# Proven reserves P90 (ton)
quantile(OIIP,p=0.1)
# Proven and Possible Reserves (P50) (ton)
quantile(OIIP,p=0.5)
# Proven, Possible and Probable Reserves (P10) (ton)
quantile(OIIP,p=0.9)
#
par(mfrow=c(2,1))
hist(OIIP)
plot(ecdf(OIIP))
#----------------------------------------------------------------