This article presents a probabilistic methodology for estimating oil and gasreserves. This methodology takes into account the uncertainties of importantvariables present in the economic evaluation of reserves, such as oil and gasproduction, prices, and operational costs. In addition, this paper seeks tounderstand the impact of oil price changes in the behavior of costs in the longterm. It also presents a case study that will allow identifying and analyzingthe results of the implementation of the methodology. The results show theimportance of evaluating and quantifying the uncertainties in the economicevaluation of the reserves, as well as the need to consider the effect of oilprice changes in operational costs. It points out, therefore, an alternative toestimate reserves, according to a probabilistic approach, which cansignificantly impact the volume of oil and gas economically recoverable that isdisclosed by an oil company


The estimate of oil and gas reserves is one of the main processes for a companythat operates in the petroleum sector. However, this process is particularlycomplex because it has a high degree of uncertainty in the estimate andprojection of variables present in the economic evaluation of production.

In recent years, there has been an industry's effort to consider and quantifythe uncertainties in predicting oil and gas production. Probabilisticapproaches for assessing the economic variables within the process of reservesestimation, such as prices, investment, and operational costs are alsorecurring themes in the industry. However, the economic evaluation ofproduction and therefore the estimate of reserves, continues to be performedpredominantly by deterministic methods (Finch et al., 2002).

It is also noted an industry's effort in modeling the dependence betweendifferent variables involved in reserves estimation. However, studies thatanalyze the dependence between variables in the development of models of riskanalysis occur mainly in the financial media (Accioly, 2005). Thus, thereserves evaluation still needs an improvement in the consideration of thedependence of variables involved in this process.

Among the variables involved in the evaluation of reserves, the operationalcost appears as an important variable to determine the economic limit ofproduction of an oil field. Therefore, this variable is crucial in the estimateof oil and gas reserves.

One of the exogenous factors that most influence the behavior of operationalcosts is the oil price (Bradley and Wood, 1993). Thus, modeling the dependencebetween price and cost is essential in the process of estimatingreserves.

This paper presents an enhancement for the probabilistic evaluation of thereserves, which takes into account the dependence relation between theoperational cost and the oil price which represent key variables for thereserves estimation.

Criteria and Classification for Reserves Estimation

Procedures for estimating reserves are discussed for over seventy years. However, this issue remains a subject of debate and studies to date. Thisoccurs due to historical revisions in the estimated volumes, emergence of newtechnologies and regulatory laws (Harrel et al., 2005).

In an attempt to unify and standardize the estimation of reserves, criteria andguidelines have been developed and disclosed to the industry for decades. Thejoint effort of some organizations resulted in the development of a singleguide with guidelines for the classification and evaluation of reserves andresources. In 2007 this guide was released and is known in the industry as theSPE/WPC/AAPG/SPEE Petroleum Resources Management System (SPE-PRMS).

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