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Information Seminar Paper

Title

EVALUATION OF DIFFERENT PERMEABILITY ESTIMATION METHODS IN A HETEROGENEOUS CARBONATE RESERVOIR IN SOUTH WEST OF IRAN

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Abstract

 IN THE FIELD UNDER STUDY, CORES, AND THUS PERMEABILITY MEASUREMENTS FROM CORE PLUGS ARE AVAILABLE FROM THE MAJORITY OF PENETRATED RESERVOIR HORIZONS. PERMEABILITIES ARE ALSO RESULTING FROM INTERPRETATIONS OF WELL TESTS, AND MEASUREMENTS OF PERMEABILITY ON TWO DIFFERENT SCALES ARE THUS AVAILABLE. EXISTING PERMEABILITIES ARE DISCRETE MEASUREMENTS. IN ORDER TO SUCCESSFULLY MODEL FLUID FLOW IN RESERVOIRS, CONTINUOUS ESTIMATES OF PERMEABILITY ARE NEEDED. THIS IS MOST COMMONLY OBTAINED THROUGH ESTABLISHMENT OF A POROSITY-PERMEABILITY RELATIONSHIP. LOG POROSITIES MAY THEN BE UTILIZED FOR PRODUCTION OF CONTINUOUS PERMEABILITY CURVES. SEVERAL METHODS WERE USED FOR DETERMINATION OF PERMEABILITY FROM LOGS, INCLUDING THE FACIES-BASED PERMEABILITY PREDICTION, EXPERIMENTAL METHODS, FUZZY LOGIC, NEURAL NETWORKS AND SIMPLE K VERSUS PHI REGRESSION. AMONG ALL PERMEABILITY MODELING METHODS APPLIED IN THE FIELD UNDER STUDY, THAT IS A HETEROGENEOUS CARBONATE RESERVOIR IN SOUTH WEST OF IRAN, IT TURNED OUT THAT ARTIFICIAL NEURAL NETWORK WITH 6 INPUT LOGS AND AFTER THAT FACIES-BASED PERMEABILITY PREDICTION METHOD HAVE THE HIGHEST DEGREE OF ASSOCIATION.

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