Petrophysical Characterization of Lower Triassic Formation of Southern Hassi R’Mel and Permeability Prediction with Fuzzy Logic Analysis. Algeria

Abstract

Characterization of the shaly sand reservoirs by flow units is a practical way of reservoir zonation. This work represents a petrophysical-based method that uses well loggings and core plug data to delineate flow units within the most productive shaly sand reservoir of Triassic Formation in Hassi R’Mel field of Algeria. In the study of oil reservoirs, the prediction of absolute permeability is a fundamental key in reservoir descriptions and has a direct impact on, amongst others, effective completion designs, successful water injection programs and more efficient reservoir management. Usually simple linear regressions of core porosity and permeability data or empirical relationships using various log responses (e.g. porosity, clay volume and water saturation) have been used to predict permeability. These empirical methods only apply locally and ignore the fact that there is no theoretical basis for a relationship between porosity and permeability. The Triassic Formations of Hassi R’Mel fields are composed of sandstones and shaley sandy with dolomite. The general geologic framework obtained from the logs point out for discriminations within the formation. The plots correlating petrophysical parameters and the frequency histograms suggest the presence of distinctive reservoir trends. Triassic Formation is composed of sandy shales, dolomites and evaporates. Logs from the 8 wells are the starting point for the reservoir characterization. The permeability models are constructed and their reliabilities are compared by the regression coefficients for predictions in un-cored sections. This indicates the presence of several “hydraulic flow units” (HFU) of similar petrophysical characteristics. Analysis of core data from the Hassi R’Mel East (HRE) Field in Algeria indicates such a scenario. The predicted permeabilities for each unit show good correlations with the calculated ones from core plugs. Highly reliable future estimations can be based on the derived methods.