Estimation of petro-physical parameters based on interpolation between cross-sectional well logs

Abstract

This paper presents a quick, resource efficient and computer simulation based implementation for the estimation of petro-physical parameters between two nearby wells by using four interpolation algorithms i.e. Ordinary Kriging, Nearest Neighbor, Moving Average and Weighted Average on cross sectional well logs. Many researchers have presented their work on estimating formation parameters based on existing well logs using multilayer perceptron and radial basis function etc. But those estimated parameters are calculated from the existing logs of drilled formation. However we used interpolation algorithms between two well logs (in cross sectional view) to estimate new well log data in between wells and then formation parameters are determined using the estimated well log data. The results of all four algorithms are computed and compared with each other to find average estimation error for estimated formation parameters. This paper discusses an effective, less time consuming and resource efficient estimation of a formation logs to indicate a producible formation by calculating petro-physical parameters.

Keywords

Interpolation, Permeability, Estimation error, Artificial neural networks, Algorithm design and analysis, Conductivity