Data Mining Effective for Casing-Failure Prediction and Prevention

Recent casing failures in the Granite Wash play in the western Anadarko Basin have sparked deep concerns for operators in North Texas and Oklahoma. Hydrostatic tests made in the field show that current API standards do not assure adequate joint and bursting strength to meet deep-well requirements. This paper is part of an ongoing effort to minimize the likelihood of failure using data-mining and machine-learning algorithms.

Introduction

Casing failure has long presented a challenge to the industry. The combined effects of design, dynamic borehole conditions, metallurgy, and handling have been challenging to quantify and predict accurately.