Comparaci\'on de tres t\'ecnicas distintas con datos reales de pozo, en la determinaci\'on de la permeabilidad

TL;DR

This study compares three different techniques—statistical fuzzy logic, fractal theory, and empirical models—for predicting permeability from porosity data in a real well, finding the statistical method most effective overall.

Contribution

The paper evaluates and compares the effectiveness of three distinct permeability prediction techniques using real well data, highlighting the superior performance of the statistical fuzzy logic approach.

Findings

Statistical fuzzy logic yields the best overall permeability predictions.

Fractal theory and Tixier's empirical model perform similarly in this case.

Using 25% of data, fractal theory provides the most accurate predictions.

Abstract

We have used three different techniques for permeability prediction from porosity data in well PX12 at El Lago de Maracaibo. One of these techniques is statistical and is based in Fuzzy Logic. Another has been developed by H. Pape et al, based in Fractal Theory and the Kozeny-Carman equations, and the other one is an empirical model obtained in 1949 by Tixier. We have used 100% of the permeability-porosity data to obtain the predictor equations in each case. We have found bet- ter results with the statistical approach. The results obtained from the fractal model and the Tixier equations are similar in this case. We have also taken randomly 25% of the data to obtain the pre- dictor equations. In this case the best results are those obtained with fractal theory.