This paper presents original research on how to improve the predictive ability of type wells used in evaluating unconventional resource drilling programs by extending traditional Monte Carlo calculations. The paper addresses three critical questions engineers must answer before constructing a type well: which well to use in the construction, the relative importance (weighting) appropriate for each well, and how to adapt the results to reflect certainty (e.g. P10, P50 or P90).

The proposed method involves determining the aggregated distribution of estimated ultimate recovery (EUR) for the specified number of wells by running a statistically significant number of Monte Carlo trials. From this distribution, one can determine mean EURs for the desired type well certainties, such as P50 or P90. Additional Monte Carlo trials yielding the desired mean EUR will help determine which wells to average. Monte Carlo sampling results in several hundred trials that match the desired EURs. The relative frequency of well selection from these trials defines the weighting factor and thus the relative importance of each well. Type wells result from a weighted averaging of history and production from the selected wells.

Engineers can use this new methodology to prepare production profile forecasts for the evaluation of multi-well unconventional resource drilling programs. They can also gain an understanding of the impact aggregation will have on their evaluation work.

Our research concludes that current type well construction practices may not be appropriate for evaluating future drilling because the production profiles for the wells used to build the type well may differ from the production profiles of the planned wells. This paper presents a new method to obtain more representative type wells. The method proves accurate for any ranking criterion (EUR, net present value, payout time) as long as one can identify the ranking parameter for each well.

This paper contributes to the technical knowledge base by:

  • identifying deficiencies in current type well methodology and proposing methodology to remove those deficiencies,

  • proposing a method to meet selected certainty criteria and aggregate properly using Monte Carlo simulation, and

  • introducing the concept that type wells do not need to be based on EURs, and in fact may be more valuable if they are based on more relevant criteria.

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