Abstract
Model-based production analysis using analytical or numerical models is not a new phenomenon and is considered a robust technique for analyzing and forecasting production data; however, its application to unconventional reservoir systems often proves problematic due to model non-uniqueness resulting from long-term transient flow regimes. This non-uniqueness, an unavoidable fact when analyzing inverse problems, is worsened by the uncertainty surrounding input model parameters when attempting to describe reservoir systems with a great deal of complexity (e.g. very low permeability, geomechanical effects, near-critical fluids, natural fracturing, etc.). The problem facing the engineer presents itself when different combinations of input parameters yield nearly identical history matches but very different time-rate profiles and estimated ultimate recovery (EUR) values when forecasting future production for a particular well.
A systematic framework that covers the full range of uncertainty for all relevant input parameters would clearly mitigate the ambiguity of production analysis and forecasting under uncertain conditions. In this work it is proposed that experimental design, which is a statistical technique used to describe or optimize a process by systematically analyzing the effect of the various controllable and uncontrollable factors of a system on an output (e.g. EUR), can provide such a framework. In this work, a methodology combining model-based production analysis with experimental design is used to history match and forecast fractured vertical and multi-fractured horizontal oil wells in the Vaca Muerta Shale with high-frequency time-rate-pressure data. The primary objectives of this work are to provide a comprehensive overview of the Vaca Muerta shale, outline experimental design as it relates to model-based production analysis, quantify uncertainties in model input parameters, and finally history match and forecast two wells that are producing in the Vaca Muerta Shale.
