Deterministic Versus Probabilistic Volumetric estimation reserve

The aspect of uncertainty in hydrocarbon reserves estimation cannot be

overemphasized since the estimation of reserves is done under conditions of uncer￾tainties. There are basically two methods of returning the results of reserves estima￾tion for any of the techniques such as volumetric, material balance, decline curve etc.

employed for reserves estimation. These methods are the deterministic and proba￾bilistic methods. Thus, if a single best estimate of reserves is made based on known

geological, engineering and economic data, the method is called deterministic whose

procedure is to select a single value for each parameter to input into an appropriate

equation (volumetric, material balance, decline curve etc.), to obtain a single answer.

In volumetric method, all input parameters are exactly known and variability is

sometimes ignored.

On the other hand, when the known geological, engineering, and economic data

are used to generate a range of estimates and their associated probabilities; the

method of estimation is called probabilistic. This method is more rigorous and less

commonly used; it utilizes a distribution curve for each input parameter and through

the use of Monte Carlo Simulation. In this method, all input parameters are not

exactly known and variability cannot be ignored.

Since the oil and gas business is associated with some inherent uncertainties, it

implies that a quality control and assurance should be made before making any

decision to develop the hydrocarbon prospect because a wrong evaluation of the

hydrocarbon initial in place leads to a wrong decision which in turn leads to an entire

failure of the field development. However, a comparison of the deterministic and

probabilistic methods can provide quality assurance for estimating hydrocarbon

reserves. This means that when the values of the reserves calculated deterministi￾cally and probabilistically agree with minimal deviation or tolerance of error, then

confidence on the calculated reserves is increased. On the contrary, when there is a

significant difference in value, then the assumptions made need to be reexamined.

A Monte-Carlo technique is employed to evaluate hydrocarbons in place where

each input parameter required for the reserves estimation are represented by statis￾tical distributions. Monte-Carlo methods are mainly used in three distinct problem

classes, such as optimization, numerical integration and generating draws from a

probability distribution. There are basically five types of statistical distribution used

with this method.