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Today's oil companies around the world produce reconciliations on various disclosures such as proved reserves, probable reserves, future net reserves, standardized measure of discounted future net reserves, and many kinds of sensitivities as a means to measuring a company's performance over time. The reconciliation process consists of attributing the relative importance of change that has impacted reserves or value to different categories like technical revisions, improved recovery, purchase and sales, economic parameters, and many others. Reconciliations provide very useful benchmark information on a company's performance, as well as the required disclosures to various regulatory agencies. However, are the results good enough to rely on for important decision making? Are the results repeatable? Are they worth the effort?

Currently, reconciliations are a very time consuming and a predominantly manual process that lacks consistent standardization. For the most part, oil companies construct in-house methodology for producing reconciliation analysis that is the most expedient for the data and the tools they have on hand. There is no global consensus on how to perform reconciliation calculations nor is there a clear definition of what the terms (such as "Technical Revisions") really mean. Various software solutions have taken different approaches to solving this problem, but they can yield dramatically different results. A standardized approach would lead to consistency in the values reported, thus providing a more useful measure of performance. A standardized approach to reconciliations further opens the door for automation, which greatly reduces the time and manpower needed for this task.

Two Predominant Methods of Calculating Reconciliation Results
The goal of a reconciliation analysis is to quantify those factors that have impacted company reserves or value over a given time period and determine the relative importance of those factors. For example: Over the last year, was it changes in price, operating costs, or reservoir performance that most impacted the company's present worth? To what degree were these factors important and were there any other factors that had significant impact?

There are two widely used methods for determining the impact of these change factors. For discussion purposes, I call them Incremental Logging and Isolation Sensitivities.

Incremental Logging has most likely been around the longest and has lended itself to the highest degree of automation. It is very simple and consists of tracking the change to the bottom line, also known as the Reconciliation Basis, every time any kind of change is performed on a company evaluation. An example of this would be tracking the resulting positive or negative change in present worth when the oil price in a given field was changed. Subsequent to that, a change in reservoir performance prediction yields a further positive or negative change to company present worth at the end of the year.

Similarly, the resulting change to Net BOE from recalculated economic limits could be tracked with each change to price or reservoir performance. The main problem with Incremental Logging is that the results are order-biased. This method does a poor job of separating the components of price and reservoir. When the initial change to price is tracked, the result is a change due only to Price. But when the second (or third, or any other factor is tracked), the result is due to the sum of all changes made to that point, not just the individual factor. Thus, the relative impact of a change is biased according to the order it was tracked. Using this method yields consistent results only if the types of changes (price, opcosts, projections) are made in the exact same order each time.

The second method of determining the impact of change factors is called Isolation Sensitivities. This method employs pulling a variable out of one revision and substituting it into the other. Then, the economic and reservoir forecasts are recalculated and compared against the original.

Isolation Sensitivities do not rely on tracking the changes as they are made in real time like the Incremental Logging method does. They only rely on the state of the reserves or cash flow evaluation at the beginning of the reconciliation period and at the end of the reconciliation period. Because of this, there is no bias associated with the order in which the calculations are run and consistent results can be expected.

Interrelated Change
The inherent problem with both of these methods is that they cannot deal adequately with the change in value or reserves that is associated with multiple interrelated change factors. When a reservoir forecast is increased to yield a higher volume, and then the prices are also changed, the sum of the impact of both changes is less than what the total change ends up being. There is an amount of change due to the increased price that acts not only on the original volume, but on the changed volume as well. Incremental Logging lumps all the interrelated change to that point into whatever change is being tracked at the time. Isolation Sensitivities do a good job of separating each individual change and its associated impact, but, when you sum all the individual changes they do not equal the total amount of net change.

Isolation Sensitivities and a Standard Method for Distributing Interrelated Change
A method that would yield consistent and reproducible results would most likely be one utilizing Isolation Sensitivities and a defined procedure for distributing the interrelated change to its components. Such a method would eliminate any order based bias, and it could be defined to the degree that different companies would be able to reproduce consistent results even if those results were generated by different software applications or in-house procedures.

In this manner, the value of change associated with each factor is inflated or deflated in a proportionate amount so that the sum of all individual changes equals the total net change.

Conclusion
One of the realities in performing Reconciliation analysis for Oil and Gas companies today is that various methods are very often used within the same company just to get the job done. If the results are intuitively adverse to what the engineers or scientists know to be true, reconciliation calculations can be run in a different order or method until arriving at a solution that "feels" right with regard to what factors have the greatest impact on the changing status of the corporate reserves. This is neither an efficient nor unbiased way to measure a company's performance over time. It also can be unavoidably misleading to disclose reconciliation information when the method for arriving at those reports is undefined. Standardization of reconciliation methods can help the industry provide corporate benchmarks in a much more efficient manner and better communicate those findings.

Note: This summary was taken from a 40 page document called Standardized Order and Calculation Method to Reconcile Reserves, which was the basis of a short presentation at the SPEE 2008 Annual Meeting. It represents the opinions of the author on the subject.

Labels: methods of calculation, oil gas, Russia, standards for reconciliation

posted by The Rogtec Team @ 11:43 

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