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Production forecasting frequently asked questions and examples
The examples below are motivated by a set of frequently asked questions (FAQs), in turn highlighting common errors seen in forecasting, and are summarized by learning points that demonstrate why a consistent forecast definition is a pre-requisite for a lean forecasting process, applicable to resource estimation, business planning and decision making.
It is not a requirement to use these definitions or the proposed forecasting principles but it is considered best practice; the examples will show that, the closer a company applies these definitions and principles, the leaner the overall forecasting, resource estimation and business planning process will be. Lean in this context means “getting it right the first time” and avoiding waste and unnecessary re-work.
FAQ 1
Does my forecast always have to result in a high (P10)/best (P50)/low (P90) estimate of the ultimate recovery?
There are many situations, where the model objectives dictate another objective function than ultimate recovery; however, the forecaster should always plan for making a P10/P50/P90 forecast that is consistent with the resource estimates in addition to the primary objectives of the study. This should be done whether the customer asks for it or not.
Example 1
A reservoir engineer was requested to provide forecasting support for an exploration lease sale. A number of offshore blocks were on offer and he made a Monte Carlo simulation, based on seismically derived volumes, reservoir property trends, range of well count, development/operating costs and infrastructure requirements to point of sale. The objective functions were NPV and EMV for a significant number of prospects in these offshore blocks. This was exactly the information the exploration department had requested to determine the optimal bid value of these block.
Unfortunately, the exploration department also kept a database of all the prospects where they stored the so-derived prospect volumes as low (P90), best (P50), high (P10) estimates, consistent with PRMS definitions for prospective volumes (assuming the company would win the lease sale and get these block). The reservoir engineer’s volumetric ranges were input into this database.
Subsequently, an exploration review was carried out on this database and the reviewers discovered inconsistencies in the volume estimates: ranges were not wide enough, the best (P50) EUR was bigger than the high (P10) EUR and the best (P50) EUR was smaller than the low (P90) EUR in some prospects Fig 1.1. The reservoir engineer was not involved in this review, and it took several days and lots of rework to discover the root cause of the inconsistent EUR volume estimate, which was, of course, due to choosing the inappropriate objective function in the Monte Carlo analysis. Ie. For a given prospect, the realization that results in the P50 NPV will generally NOT result in the P50 EUR.
Consequence
Lesson learned
FAQ 2
Example 2
References
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Noteworthy papers in OnePetro
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Noteworthy books
Society of Petroleum Engineers (U.S.). 2011. Production forecasting. Richardson, Tex: Society of Petroleum Engineers. WorldCat or SPE Bookstore
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External links
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See also
Production forecasting glossary
Sandbox:Production forecasting building blocks
Sandbox:Production forecasting expectations
Sandbox:Production forecasting flowchart
Sandbox:Production forecasting in the financial markets