A hybrid approach for litho-facies characterization in the framework of sequence stratigraphy: a case study from the South Pars gas field, the Persian Gulf basin
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The Upper Dalan and Kangan formations with dominant lithology of limestone and dolomite associated with anhydrite nodules and interbeds form the Permo-Triassic succession of South Pars gas field (SPGF) and host the largest none-associated gas reservoir in the world. The current study focuses on preparing a comprehensive litho-facies model in the framework of sequence stratigraphy. For this purpose, Self-Organizing Map Neural Network (SOM-ANN) and hierarchical cluster analysis (HCA) were utilized as effective tools to prepare the preliminary data for litho-facies mapping. Neural networks (self-organizing maps) and hierarchical clustering approaches were applied to characterize litho-facies in un-cored but logged wells. Particularly, the powerful visualization tools of the SOM-ANN which provide more information in comparison to HCA facilitate the task of establishing an order of priority between the distinguished electro-facies groups. The mentioned method of SOM-ANN clustering algorithm showed a good performance in petrophysical data clustering and litho-facies determination. Based on the porosity and permeability maps at different depth levels, the target reservoir is ranked and classified into four litho-facies and six electro-facies. They include litho-facies 3 with good reservoir quality (equivalent of electro-facies 4–6), litho-facies 4 with moderate reservoir quality (equivalent of electro-facies 2) and litho-facies 1 and 2 with poor to bad reservoir quality (equivalent of electro-facies 1 and 3).The main litho-facies assemblages are indicative of deposition within tidal flat, lagoon, shoal and off-shoal environments. The most shoal litho-facies with best reservoir quality occurs in the high energy sub-environment within upper transgression position (HST) of the 3rd-order cycle in K4 and K2 reservoir units. Distribution of the petrophysical characteristics was analyzed in detail in the framework of electro-facies and sequence stratigraphy. The methodology is illustrated by using a case study from SPGF, Iran.
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