Pore geometric modeling for petrophysical interpretation of downhole formation evaluation data

Abstract

[1] An accurate description of water-or oil-bearing reservoirs strongly depends on a robust determination of their petrophysical parameters, e.g., porosity, permeability and fluid distribution. Downhole logging measurements are the primary means to formation evaluation; however, they do not directly provide the petrophysical properties of interest. To interpret well logging data, a range of empirical models are usually employed. These empirical relationships, however, lack scientific basis and usually represent generalizations of the observed trends. Since macroscopic rock properties vary depending on their microstructure, we suggest using a pore-scale approach to establish links between various petrophysical properties of sedimentary rocks. We outline a method for computing formation permeability using the proposed rock models. The method utilizes NMR (Nuclear Magnetic Resonance) logging data for the information about porosity and grain size. We also present an approach for prediction of acoustic velocities of model rocks. The proposed methodology is applied to the field data, and the corresponding interpretation results are included in this paper.Citation: Gladkikh, M., D. Jacobi, and F. Mendez (2007), Pore geometric modeling for petrophysical interpretation of downhole formation evaluation data, Water Resour. Res., 43, W12S08,

Applications of 2D-NMR maps and geometric pore scale modeling for petrophysical evaluation of a gas well

“…The approach presented in this paper is based on the previous research [4][5][6][7][8][9][10][11][12][13][14]. We simulate physical processes at the pore scale in simple but physically representative model rocks.…”

“…8). Modified Delaunay tessellation subdivides the pore space into tetrahedral pores, and surface-to-volume ratio is easily computed for each pore [4]. Figure 9 shows a typical tetrahedral cell resulting from the Delaunay tessellation of a sphere packing.…”

“…Logging data are incorporated to provide more information about the formation so that more accurate rock models are constructed [4]. This approach provides a complete description of pore space geometry and physical properties of rock constituents.…”

“…The approach is applied to compute capillary pressure curves [10][11][12], absolute and relative permeabilities [4,[8][9][10], electrical resistivity [6,10], acoustic velocities [4,7], and NMR transverse relaxation spectrum [4]. Corresponding algorithms have been described in the previous publications.…”

“…Pendular water indicates that the reservoir is at irreducible water saturation or has a very low water production. To explain this phenomenon, we use a pore scale model [4], which simulates drainage process in a model rock and predicts T2 response of the wetting phase at irreducible water saturation.…”