76 | Page Reserve Prediction for One Iraqi Exploration Oil Field Using Probabilistic Monte Carlo Method Yahya Jirjees Tawfeeq Petroleum Engineering Department, University of Kirkuk, Iraq Abstract The estimation of the hydrocarbon reserve is an essential task for any production and exploration operations.Any exploration and production projects economic viability are based on the accuracy of their reserves estimates, which are made utilizing various input parameters as example porosity, water saturation and formation factor.These parameters can be derived from petrophysical data and well testes data.Because of uncertainties in the estimate of such parameter, both deterministic and stochastic methods must be used for estimating reserves. The input parameters for deterministic methods are certain individual value and thus the output represents single value. Because reservoir parameters are not standardized across entire reservoir, uncertainty reduce as data set increases. In such cases, stochastic approaches used, since random sampling can produce millions of random numbers and by properly analyzing this data set, these problems can be resolved very quickly.Simulation of Monte Carlo is an epitome of a stochastic method of this kind for estimating hydrocarbon resources.The success of a Monte Carlo simulation stochastic hydrocarbon reserve estimate depends on selecting model parameters andprecise controlling and understanding of model parameters that are important for successful outcomes. This study predicted how statistical distribution of porosity and water saturation affect the original simulated oil values for one Iraqi oil field, and discussed the results. Keywords:Monte Carlo simulation, Original oil in-place, Reserve estimation, Volumetric method,Probabilistic method. 1. INTRODUCTION Monte Carlo is a popular statistical method used over a half hundred years ago.It has been widely used in the oil industry for decades.It was used for pressure transient analysis as early as 1969[1].For various other industries such as reserve estimates [2], material balance analyses [3], risk workout assessments [4] and property estimates [5], the Monte Carlo method has been used.This method is replacement to both determinist assessment and scenario method which presents negative, most probable, and optimistic status