Abstract

SummaryThis paper introduces a new magnetic resonance fluid (MRF) characterization method. The MRF method is based on two key ingredients—a new microscopic constituent viscosity model (CVM) and a new multifluid relaxation model. The CVM provides a link between nuclear magnetic resonance (NMR) relaxation times and molecular diffusion coefficients in hydrocarbon mixtures such as crude oils. The multifluid relaxation model accounts for the T2 decay of spin-echo signals that arises from intrinsic spin-spin interactions, surface relaxation, and attenuation due to molecular diffusion of fluid molecules in a magnetic field gradient. The MRF method exploits the fact that the molecular diffusion coefficients of brine, oil, and gas molecules typically have values that are well separated from one another. Thus, the diffusion attenuation of a suite of measured NMR signals contains sufficient information to allow differentiation of brine, oil, and gas. The method involves the simultaneous inversion of a suite of spin-echo measurements with the new MRF multifluid relaxation model.The application of the MRF method to magnetic resonance logging data can provide a detailed formation evaluation. The information provided includes total porosity, bulk volume of irreducible water, brine and hydrocarbon saturation, hydrocarbon-corrected permeability, and oil viscosity.This paper discusses the theory underlying the CVM and validates the model by testing its predictions on hydrocarbon mixtures including live and dead crude oils. The robustness and accuracy of the multifluid inversion is demonstrated by a Monte Carlo simulation of a model carbonate rock that contains brine, oil, gas, and oil-base mud filtrate (OBMF). The MRF method is applied to suites of spin-echo measurements acquired in the laboratory on partially saturated rocks and shown to provide accurate fluid saturation and oil viscosity estimates.Since the completion of this work, field test results have shown that the MRF method provides a powerful and unique new formation evaluation tool.

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