Methods for quantifying the uncertainty of production forecasts: a comparative study

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Abstract
This paper presents a comparison study in which several partners have applied methods to quantify uncertainty on production forecasts for reservoir models conditioned to both static and dynamic well data. A synthetic case study was set up, based on a real field case. All partners received well porosity/permeability data and ‘historic’ production data. Noise was added to both data types. A geological description was given to guide the parameterization of the reservoir model. Partners were asked to condition their reservoir models to these data and estimate the probability distribution of total field production at the end of the forecast period. The various approaches taken by the partners were categorized. Results showed that for a significant number of approaches the truth case was outside the predicted range. The choice of parameterization and initial reservoir models gave the largest influence on the prediction range, whereas the choice of reservoir simulator introduced a bias in the predicted range.