AN INTEGRATED WORKFLOW TO ESTIMATE PERMEABILITY THROUGH QUANTIFICATION OF ROCK FABRIC USING JOINT INTERPRETATION OF NUCLEAR MAGNETIC RESONANCE AND ELECTRIC MEASUREMENTS

摘要

Variable depositional cycles and severe diagenesis areamong the main contributing factors to the complexpore network encountered in formations such ascarbonates. This complexity is often not taken intoaccount reliably in conventional models forpermeability assessment. Conventional methods forpermeability assessment, including electrical-basedmodels (e.g., Katz and Thompson) and NuclearMagnetic Resonance (NMR)-based models (e.g.,Coates and Schlumberger-Doll-Research), eitherrequire pore-scale characterization of pore network orextensive calibration efforts such as detection of cutoffvalues and assessment of constant model parameters.Joint evaluation of dielectric permittivity, resistivity,and NMR measurements enables capturing porenetworkconnectivity, tortuosity, and throat-sizedistribution for real-time and reliable permeabilityevaluation, which significantly improves permeabilityassessment. Such joint interpretation enables taking intoaccount pore structure in assessment of permeability.The objectives of this paper include (a) estimatingparameters that quantify rock fabric features (e.g.,tortuosity, effective pore size, throat-size distribution)by joint interpretation of electrical resistivity, dielectricpermittivity, and NMR measurements, (b) developing anew workflow for permeability assessment thatincorporates the quantified rock fabric parameters, and(c) validating the reliability of the new permeabilitymodel in core-scale domain using electrical resistivity,dielectric permittivity, NMR, Mercury InjectionCapillary Pressure (MICP), and permeabilitymeasurements. To achieve the aforementionedobjectives, we introduce a workflow to estimate rockfabric properties as inputs for permeability assessment.NMR measurements will be used to estimate theporosity and the effective pore size. Dielectricpermittivity and resistivity measurements to estimatetortuosity constriction factor. Then, we calculate thepore-throat-size distribution from the estimatedconstriction factor and effective pore size. Finally, theaforementioned quantitative rock fabric parameters willbe used to estimate permeability without core-based orimage-based calibration efforts.We successfully validated the introduced workflow onfive core-scale samples from different lithofacies takenfrom three carbonate formations. Estimates of porethroatradius obtained from the new method were inagreement with those from MICP measurements. Weuse the estimated pore- and pore-throat radii, tortuosity,and constriction factor for quantification of rock fabricin reliable permeability assessment. The proposedworkflow significantly reduced the relative error inpermeability estimates by 92%, compared to theconventional permeability models (i.e., calibratedporosity-permeability correlations). Furthermore, thenew method eliminates the need for cutoffs andexcessive calibration efforts in permeability assessmentby honoring and quantifying rock fabric.