Unconventional Gas Well Aggregator

 

 

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Another approach to calculating undiscovered volumes is to aggregate the EUR of undrilled discoveries.  This method is appropriate for relatively mature plays, for which there is a large dataset, or for plays for which a company has a series of appropriate analogs. Crystal Ball® and @Risk® versions of the tool are available.

 

 Here’s an example of the input screen for such a method.  The user either models the uncertainty in undeveloped area (and  notional spacing), or the number of undrilled locations, volume characteristics for future wells (more below the image), commercial minimum size, and chance characteristics.  Paragraphs of embedded help text are included.  Stochastic analysis and extraction of outputs is fully automated.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A key feature of this tool is that, rather than modeling a single future EUR distribution, ranges are modeled for what the future family of undrilled locations will yield, bracketed by an absolute upper and lower ranges.  On each iteration, a hybrid distribution is modeled between these bracketing distributions and each well on that iteration is sampled from that hybrid.  This avoids the serious flaw, found in most calculators on the market, of sampling, on each iteration, from a single distribution, and therefore repeatedly returning an aggregate result that reflects the mean of that distribution.  In essence, this assumes that (even if the predicted individual EUR outcomes are modeled with a very wide range) the user can almost perfectly predict the future results for the family of undrilled locations.  For references on this flaw, contact EAI

 

Another key feature is the ability to model the extremities of the distributions as non-lognormal.  The practice of modeling  many natural phenomenon with lognormal distributions is common in prospect and play analysis.  While a significant portion of an EUR distribution tends to be ‘well behaved’ in log-probability space, the upper and lower populations (particularly the lower end of the distribution is generally poorly represented by lognormality.  This tool permits more appropriate modeling of the lower and upper portions of the EUR distribution.

ExplAnalysis, Llc