Production Profile

 library(ggplot2)

Pi <- 2000      ### The initial rate of production
Duration = 10   ### the duration of the production needed to be estiamted
DR <- 0.2       ### Decline rate nominated per year.
i = 0
Cump = Pi*365
df <- c(i,Pi,Cump)
while (i < Duration) {
  
  Pi = Pi- (Pi*DR)
  Cump = Cump+Pi*365
df <- rbind(df,data.frame(i+1, round(Pi,0),Cump))

i=i+1
}

#df
names(df)[1] <- "Time"
names(df)[2] <- "Production"
names(df)[3] <- "Cumulative.Production"

knitr::kable(df, caption = "Table of Production data expected in field Duration")

p<- ggplot(df, aes(Time,Production))+geom_point()+geom_line(colour = "blue")+xlab("Time in Years")+ ylab(" Production in STBPD")

Cumprd<- ggplot(df, aes(Time,Cumulative.Production))+geom_point()+geom_line(colour = "red")+xlab("Time in Years")+ ylab(" Cumulative Production in STBP")
plotly::ggplotly(p)

plotly::ggplotly(Cumprd)

library(plotly)
# two <-ggplot(df, aes(Time,Production))+geom_point()+geom_line(aes(y= Cumulative.Production),colour = "blue")+scale_y_continuous(
#     "Production STBPD", sec.axis = sec_axis(~ .*365, name = "Cumulative Production"))
# 
# plotly::ggplotly(two)

ay <- list(

  overlaying = "y",
  side = "right")
  
 plot_ly() %>%
  add_trace(x = df$Time, y = df$Production, name = "Production STBPD", mode = 'lines+markers') %>%
  add_trace(x = df$Time, y = df$Cumulative.Production, name = "Cumulative productive STB", mode = 'lines+markers', yaxis = "y2") %>%
  layout(
    title = "Field Development Plan", yaxis2 = ay,
    xaxis = list(title="Time in Years")
  )

Cum.p<- print(paste('The total production is' , sum(df$Production)*365))