The estimation of probabilistic distribution of reserves is increasingly being used in the oil industry. However, this is not an easy assignment because of the amount of information required and costs associated. Even more complicated is the task of evaluating distribution of reserves departing from production trends. The historic analysis of production has usually used a deterministic approach in the form of Decline Curve Analysis (DCA).
In this paper we present a quick and efficient application for estimating probabilistic distribution of reserves combining the usually available production information with the power of stochastic methods through the use of decline curve analysis: PREP (Probabilistic Reserves Estimation Package). The computational tool developed uses a Monte Carlo-type technique under an efficient optimization algorithm to calculate the DCA parameters. More than 200 realizations can be generated and evaluated in a few seconds for diverse production scenarios and information such as standard errors, confidence intervals, expectation curves can be visualized to uncertainty diagnosis.
We have applied the proposed tool on several fields located in the Valle Superior del Magdalena Basin in Colombia, South America. The Valle Superior del Magdalena Basin is estimated to contain over 1,400 million barrels of oil-in-place of which only 14.7% have been produced. The results obtained have had strong economic impact on reservoir management decisions.