Permeability prediction in argillaceous sandstone reservoirs using fuzzy logic analysis: A case study of triassic sequences, Southern Hassi R'Mel Gas Field, Algeria

Abstract

Discriminating the argillaceous sandstone reservoirs into several hydraulic flow units (HFUs) is a useful reservoir zonation technique. This study introduces a statistical method for analyzing petrophysical data sets, including borehole-logs and core data, to discriminate the main Triassic gas-producing argillaceous sandstone reservoirs in Hassi R'Mel Northern Field in Algeria into some HFUs.These Triassic Formations consist mainly of argillaceous sandstone, sandy shales, dolostones, and evaporite intercalations. Integration between the X-Y plot of porosity and permeability data, and their frequency distribution histograms introduced a diagnostic reservoir mathematical model for predicting both parameters. On the other side, the petrophysical model framework that based on log responses indicates the ability to cluster log responses of the Triassic Hassi R'Mel formations into many clusters and components. The reservoir characterization workflow of Hassi R'Mel formations started with processing the log responses of eight logged boreholes, and some high reliable mathematical models (R2 = 0.943) were introduced to estimate permeability in the un-cored intervals. Besides, applying a fuzzy logic technique enabled a reservoir zonation of the Southern Hassi R'Mel Gas Field into several HFUs with various reservoir properties. Predicted permeability values of each flow unit indicate high reliable relationships established between the measured and calculated permeability using the fuzzy logic technique.