Summary
Probabilistic methods have introduced inconsistent interpretations of how they should be applied while still complying with reserves certification guidelines. The objective of this paper is to present and discuss some pitfalls commonly encountered in the application of probabilistic methods to evaluate reserves. Several regulatory guidelines that should be followed during the generation of recoverable hydrocarbon distributions are discussed. An example also is given to understand the evolution of reserves categories as a function of probabilities.
Most of the conflicting reserves interpretations can be attributed to the constraints of regulatory bodies [e.g., the U.S. Securities and Exchange Commission (SEC)] and the current SPE/World Petroleum Congresses (WPC) reserves definitions in which reserves categories are expressed in terms of the probabilities of being achieved. For example, proved reserves are defined as those hydrocarbon volumes with at least a 90% probability of being equaled or exceeded (P90). Unfortunately, these definitions alone fall short as guidance on how to derive the distributions from which these percentiles will be calculated. This may lead to distributions that do not comply with the remaining guidelines. While a P90 can be calculated from a noncomplying distribution, proved reserves may not be assigned at this percentile level.
Introduction
In 1997, new reserves definitions were drafted and introduced by SPE and WPC. For the first time, these reserves definitions included some language to address the increased interest in probabilistic analysis to estimate hydrocarbon reserves. Proved reserves were defined, in part, as those volumes of recoverable hydrocarbons with " . . . a high degree of confidence that the quantities will be recovered. If probabilistic methods are used, there should be at least a 90% probability that the quantities actually recovered will equal or exceed the estimate."1 The interpretation of this definition may be that satisfying the P90 criteria is sufficient to define proved reserves. We will discuss later in this paper why defining proved reserves as the P90 of any distribution is not always appropriate. Also, the definitions do not specify at what level the evaluator should apply the P90 test (i.e., is it at the field level or the total portfolio level?). These points are further clarified in the 2001 update of the SPE/WPC definitions.2
Probable reserves were then described in the SPE/WPC definitions as those recoverable hydrocarbon volumes that " . . . are more likely than not to be recoverable. In this context, when probabilistic methods are used, there should be at least a 50% probability that the quantities actually recovered will equal or exceed the sum of estimated proved plus probable reserves."1
Possible reserves were defined as those recoverable hydrocarbon volumes that " . . . are less likely to be recoverable than probable reserves. In this context, when probabilistic methods are used, there should be at least a 10% probability that the quantities actually recovered will equal or exceed the sum of estimated proved plus probable plus possible reserves."1
The SEC does not recognize probable and possible reserves. The SEC's guidelines for reporting proved reserves are set forth in its Regulation S-X, Rule 4-10 and subsequent clarifying bulletins. In Regulation S-X, Rule 4-10, there are no guidelines for the interpretation of probabilistic analysis. The regulation defines proved reserves as those recoverable hydrocarbon volumes with " . . . reasonable certainty to be recoverable in future years from known reservoirs . . ."3
Both the SPE/WPC and SEC proved reserves definitions have several other requirements that are usually applicable to deterministic methods that may conflict with probabilistic analysis if not properly incorporated. Evaluators of reserves should exercise caution when using probabilistic methods to ensure compliance with the reserves definitions adopted by the SEC and SPE/WPC. Caution is required because there are certain situations in which indiscriminate application of probabilistic methods may produce results that are inconsistent with the reserves definitions. For example, the SEC definition of proved reserves does not explicitly recognize the use of the probabilistic method and in no way allows for the probabilistic method to be used in such a manner as to violate any term of that definition.
In this paper, we will first present a short definition of probabilistic analysis and the risks and benefits of using this technique. Next, we will address some significant shortcomings in the current reserves definitions and then present some examples on how some of these shortcomings can be addressed in the evaluation of reserves.
Discussion of Probabilistic Analysis of Reserves
The probabilistic analysis of reserves relies on the use of probabilistic techniques to estimate the uncertainty of the recoverable hydrocarbon volumes. In its purest sense, these probabilistic methods are used to collect and organize, evaluate, present, and summarize data. These methods provide the tools to analyze large amounts of representative data so that the significance of that data's variability and dependability can be measured and understood.
Probabilistic analysis should be considered an important tool for internal analysis, allowing companies to understand and rank their hydrocarbon reserves and resources and the associated risks. This method provides the tools to identify the upside and the downside hydrocarbon potential to better organize the company's portfolio and to allocate capital and manpower resources more efficiently. However, it should be understood that the objectives of a hydrocarbon-property ranking study and an SPE/WPC or SEC reserves reporting evaluation might be different. For example, companies may have their own guidelines to group and analyze hydrocarbon assets to allocate company resources or for property acquisitions. These company guidelines may vary from project to project or from year to year (depending on pricing assumptions) and may be different from those guidelines provided in the SPE/ WPC and SEC definitions. It then becomes the primary challenge of the evaluator to reconcile both evaluations.
Spatio-temporal variations in hexachlorobenzene partitioning in a near shore Antarctic marine environment from a one-dimensional coupled ecosystem-chemical distribution model
