CGAxis Models Volume 69 Trees VIII
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The Domino Effect by Braziel E. Russell

The Domino Effect by Braziel E. Russell

Author:Braziel, E. Russell [Braziel, E. Russell]
Language: eng
Format: azw
Publisher: NTA Press
Published: 2016-01-03T05:00:00+00:00

However, if the well is produced too fast, it can impair the well's long-term productivity. Producers must balance economics with production engineering to arrive at just the right flow rates. Making the calculations to determine these flow numbers is part science and part art. Developing the production plan in a producer organization typically falls to reservoir engineers, whose job it is to estimate well production, production decline, and well life. Reservoir engineers use complex geophysical models to arrive at these estimates. Such models and the data required to use them for particular wells and plays are rarely available outside production companies.

There are various methods of approximating the results from these complex models that the rest of us—analysts and investors with access only to publicly available data—must be content to use. Public production data is usually derived from producer presentations to investors or from data published by state oil and gas resource departments. This state data is collected by a number of data vendors who provide access, along with useful software designed to help analysts forecast production.

The minimum data elements required to estimate production are the following:

1. The IP rate,

2. the decline rate over time (usually either monthly or annually), and

3. the life of the well.

Given these three variables, the question is then how to smooth out the decline curve so that it most accurately represents the actual decline rate experienced at most wells. There are a number of methodologies used to make this calculation. If you are interested in the details, see The Domino Effect website at

The technique used in The Domino Effect Production Economics Model is the Arps Curve. This method was developed by a mining engineer named J. J. Arps and detailed in his 1944 paper, "Analysis of Decline Curves."1 Effectively, the Arps method fits a hyperbolic curve to a series of decline rates. For our purposes here, suffice to say it is a way to mathematically smooth out a production curve so it looks like the downward sloping line in Figure 9.2 (downward sloping line, left axis).

Estimated Ultimate Recovery (EUR) and BOE

The bottom line for a production estimate is the Estimated Ultimate Recovery, or EUR, which is the total volume of recoverable hydrocarbons from a well. EUR is simply the cumulative production forecast for the well over its life. In the Permian/Midland Basin, typical EURs have risen healthily as producers have moved closer to the sweet spots in the play, shifted from vertical to horizontal wells, and have continuously improved their drilling techniques.

For a multiple-commodity well, EUR is frequently measured in barrels of oil equivalent, or BOE. It puts volumes of crude oil, natural gas, and NGLs on an equal footing by converting all output into a volume equivalent to crude oil. The official Internal Revenue Service definition of BOE is the energy (on a Btu basis) obtained from burning one barrel of oil. Practically speaking, BOE is the volume of crude oil production in barrels plus the volume of natural gas production (measured in thousands of cubic feet, or Mcf) converted to equivalent barrels of crude oil.


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