Application of Co-Kriging and Ordinary Kriging for Selecting Additional Well Locations

TL;DR

This paper compares ordinary kriging and co-kriging methods to interpolate Well Performance Index (WPI) across Cana Field, aiding in selecting optimal new well locations based on the best-performing model.

Contribution

It introduces the application of co-kriging with clean fluid volume as a superior method for predicting WPI and guiding drilling decisions in oil field development.

Findings

Co-kriging with clean fluid volume outperforms other models in prediction accuracy.

Interpolation maps effectively identify promising locations for new wells.

The approach supports data-driven decision making in oil field development.

Abstract

Well performance index (WPI), which is an indicator on how much producing potential a well has, is proposed for Cana Field using the available information from the completion database. I used ordinary kriging and co-kriging to create interpolation maps for WPI across the region. The interpolation results can be used to predict WPI values for locations that have not gone through drilling programs, thus guiding operator to find the next drilling locations. Different kriging models' performance are compared using cross-validation. It is shown co-kriging with clean fluid volume has the best performance. Recommendations are given regarding new well locations.