Towards improved methods for determining porous media multiphase flow functions
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The mathematical modeling and simulation of the flow of fluid through porous media are important in many areas. Relative permeability and capillary pressure functions are macroscopic properties that are defined within the mathematic model. Accurate determinations of these functions are of great importance. An established inverse methodology provides the most accurate estimates of the unknown functions from the available data. When the inverse method is used to determine the flow functions, the media properties, absolute permeability and porosity are typically represented by single average values for the entire sample. Fortunately, an advanced core analysis tools utilizing nuclear magnetic resonance (NMR) spectroscopy and imaging (MRI) to determine complete distributions of porosity and permeability has been developed. The process for determining multiphase properties from experimental data is implemented with the computer program SENDRA. This program is built around a two-dimension, two-phase simulator. In this thesis, the computer code is extended to represent all three spatial coordinate directions so that the porosity and permeability distributions in three-dimensional space can be taken into account. Taking the sample's heterogeneity into account is expected to obtain more accurate multiphase property. Three synthetic experiments are used to show the erroneous estimation of flow functions associated with the homogeneity assumption. A proposal approach is used to predict the relative permeability of wetting phase using NMR relaxation data. Several sets of three-dimensional NMR experiments are performed. Three-dimensional saturation distribution and relaxation are determined. Relative permeability of wetting phase are calculated by applying an empirical relation. This approach provides a in situ measurement of relative permeability of wetting phase from NMR data.
Xue, Song (2005). Towards improved methods for determining porous media multiphase flow functions. Master's thesis, Texas A&M University. Texas A&M University. Available electronically from