Nonlinear estimation of missing logs from existing well log data

Abstract

Estimation of petrophysical properties of rocks from well log data plays a very important role in reservoir characterization and simulation. However, it is very common for petrophysicists to face the problem that well log data sets are not available or complete. In this work, we present a methodology that can be used to estimate missing well log data from the existing log data by using genetic algorithms.