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History matching of naturally fractured reservoirs based on the recovery curve method
275 viewed

History matching of naturally fractured reservoirs based on the recovery curve method

Ghaedi, M

History matching of naturally fractured reservoirs based on the recovery curve method

Ghaedi, M ; Sharif University of Technology

275 Viewed
  1. Type of Document: Article
  2. DOI: 10.1016/j.petrol.2014.12.002
  3. Abstract:
  4. The discrete fracture network (DFN) and Multiple-Continua concept are among the most widely used methods to model naturally fractured reservoirs. Each faces specific limitations. The recently introduced recovery curve method (RCM) is believed to be a compromise between these two current methods. In this method the recovery curves are used to determine the amount of mass exchanges between the matrix and fracture mediums. Two recovery curves are assigned for each simulation cell, one curve for gas displacement in the presence of the gravity drainage mechanism, and another for water displacement in the case of the occurrence of the imbibition mechanism. These curves describe matrix-fracture mass transfer more realistically and therefore can be of great use when obtaining historical production data.This paper presents the potential of the RCM within the framework of history matching of naturally fractured reservoirs to determine the appropriate recovery curves. In particular, the phase contact positions of a sector model, extracted from a real fractured reservoir, are matched throughout the production history using the RCM. Therefore, the main contribution of this work is using the historical data of contact positions to obtain a better description of the matrix-fracture communication. The distribution of an ensemble of the history matched models was illustrated by Boxplot, and the Genetic Algorithm (GA) and the Neighborhood-Bayes technique (NAB) were utilized for optimization and uncertainty quantification, respectively. The calculated recovery curves results are in good agreement with the production history of the model and the Bayesian credible interval (P10-P90) of the proposed method is satisfactory. This work also confirmed the potential applicability of the combined GA and NAB method for optimization and uncertainty quantification purposes
  5. Keywords:
  6. Genetic algorithm ; Matrix-fracture interaction ; Naturally fractured reservoir ; Neighborhood-bayes algorithm ; End effectors ; Fracture ; Genetic algorithms ; Mass transfer ; Molecular biology ; Porosity ; Recovery ; Uncertainty analysis ; Bayes algorithms ; Dual porosity ; Fracture interactions ; History matching ; Naturally fractured reservoirs ; Petroleum reservoirs ; Bayesian analysis ; Enhanced oil recovery ; Hydrocarbon reservoir ; Matrix ; Optimization
  7. Source: Journal of Petroleum Science and Engineering ; Volume 126 , 2015 , Pages 211-221 ; 09204105 (ISSN)
  8. URL: http://www.sciencedirect.com/science/article/pii/S0920410514004069