Precise casing-wear prediction is important for improving well integrity and longevity, while simultaneously making casing designs more cost-effective. Currently, there are no known and commonly accepted guidelines available in the industry. Several studies have been presented in literature over the past couple of decades that proposed various methods for estimating the downhole wear in casings. However, the results of all such efforts have been mixed. Predicted values of casing wear using wear models failed to accurately match the wear logs from the wells when scaled up to the field level. This has led to a perception in the industry that existing casing-wear prediction methods lack the desired accuracy.
Many of these suspicions are unwarranted and have emerged because of inconsistencies in accurately applying the casing-wear model. Kumar and Samuel (2015) have previously presented a comprehensive treatise on all the uncertainties involved in casing-wear analysis and the underlying modeling method and parameters. This article proposes a new modeling method for casing-wear prediction using stiff-string analysis, aiming to reduce the existing uncertainties in downhole wear estimation. In addition to estimating more accurate side forces, the stiff-string model also predicts the contact position of the drillstring at any given depth in the casing. These contact positions, at any given casing depth cross-section, are used to model the development of multiple wear grooves around the cross-section, as various wellbore operations are conducted through the casing. Further details of this modeling method have been presented in this study.
The proposed model has been validated using measured wear-log data from an offshore well in the North Sea. The value of the maximum wear-groove depth, along with its respective azimuthal location at that casing cross-section measured using the wear logs, were compared with the simulated values for the entire logged-casing section....
Solving the Casing-Wear Puzzle Using Stiff-String Model
Robello Samuel, Aniket Kumar, and Adolfo Gonzales, Halliburton, and Sylvester Marcou and Anne Mette Rød, Statoil
01 July 2016