Note: PDF files are meant to be opened with evince (don’t complain about animations if you use Adobe Reader :frowning: ) OpenFOAM cases are packaged in a ready-to-mesh-and-run state, and python scripts are meant to show the typical work-flow - not to provide fully-featured applications. Instead of real pore (complex) geometry, assemble the porous material to a network of spheres (pores) connected by cylinders (throats), and solve the flow there, using PpenPNM - also a Python Library.Directly simulate a viscous flow through medium’s pores using OpenFOAM (The most trusted method).To formulate a better understanding of this concept, we’ve tried to use common simulation approaches to determine the permeability of a piece of porous material (a 2-D $1.024mm \times 0.728mm$ image generated with porespy - a Python Library -): We’ve also tried to show how field-based methods (Well tests and logs) are used to estimate permeability. This paper features the most-common permeability tests methods (Principle: apply pressure gradients, measure the outgoing flow rate, and use Darcy’s law to determine permeability). Thus, results from mathematical predictions are always treated with caution The most accurate method to estimate permeability of a sample rock to a certain test fluid is to actually measure it (More precisely, calculate it from measured data). With their “very limited” porosity range, these models fail in predicting the permeability of many rock sample especially if they require the determination of grain shape descriptors (sphericity, roundness … etc). With a great focus on granular reservoirs, this presentation introduces key concepts regarding this interesting property of rocks, including the most effective way of comparing two reservoirs in respect to their permeability: The use of permeability coefficient In addition, we’ve tried to present the most important factors affecting rock permeability, and how they affect it.īased on these factors, several mathematical models -adhering to certain conditions- were formed we’ve picked two well-known well-accepted models to feature: Kozeny-Carman (relatively simple porosity-permeability relationship) Happel-Brenner (more complex porosity-permeability relationship). The engineering knowledge have accumulated over the years to explain, optimize and use the behavior of reservoirs in this matter.
One of the most important properties of hydrocarbon reservoirs is their capacity of passing fluids ie, their permeability to fluids in question. Should be able to benefit from this presentation and related files (The way I presented it: Split it up to parts and give each part to the appropriate audience).
#Ies ve simulation software#
OpenFOAM and Network-based software ( OpenPNM for example) are our chosen open-source software toolkits for permeability simulation. Permeability and Filtration coefficients are some must-know factors for oil/gas reservoir management and optimization.