Using Nonparametric Optimal Transformations—Field Applications in the Middle East

Abstract

Accurate prediction of formation fracture gradient is essential to many petroleum-engineering operations. Proper planning and execution of deep abnormal pressure wells, stimulation treatment, and reservoir exploitation require, among other factors, good estimates of fracture gradient. It has been proven in the literature that most of the available fracture gradient correlations do not provide reliable results when exposed to data away from the geographical region where they were initially developed.

A new approach for fracture gradient prediction based on nonparametric optimal transformations is presented. The transformations are totally data driven and do not assume any a priori functional form. The model presents the fracture gradient as a function of pore pressure gradient, rock density, and depth. The data set used in the study consists of more than 21,000 points taken from 16 wells drilled in seven different geologic prospects covering more than 200 mi². The excellent results obtained from the proposed model establish a new simple tool for fracture gradient calculation that is based on readily accessible parameters. The proposed model is illustrated and validated using several examples from different fields in the Middle East. The results of the various cases confirm that the computed and the measured fracture gradient values are in excellent agreement with an average absolute relative error of 6% and a standard deviation of 0.05 psi/ft.

Keywords:

• nonparametric transformation
• data-driven model
• fracture gradient
• pore pressure gradient
• rock density
• depth

ACKNOWLEDGMENT

The authors would like to express their sincere appreciation to Prof. A. Datta-Gupta of Texas A&M University for his valuable suggestions in preparing the nonparametric model.