Wellbore collapse as a result of severe borehole breakouts represents a major problem in many cases. In order to quantify the risk associated to wellbore collapse a reliable estimate of the collapse volume is necessary. In this study, a novel approach determining the depth/area/volume of collapse failure by using image processing approach is presented. Since image processing can be applied to any result set, the proposed approach is independent of any failure criterion (such as Mohr Coulomb, Mogi-Coulomb and Modified Lade criteria) and very versatile. For hydrocarbon fields where Mechanical Earth Modeling (MEM) approaches capable of predicting the spatial distribution of horizontal stresses exist, the presented image processing approach is utilized to generate an automated log of collapse volume while drilling. Based on this log, mud pressure adjustments can be undertaken while drilling a new well based on collapse volume. The main contribution of this work is the estimation of a real-time collapse volume log while drilling. It can help the drilling engineers in evaluating the mud weight effect on the hole cleaning efficiency to avoid stuck pipe problems. In addition, knowledge of the collapse volume provides better estimates on the required mud and cement volumes.
Collapse Volume Log Estimation Using Image Processing Approach
Alkamil, Ethar H. K., Flori, Ralph E., and Andreas Eckert. "Collapse Volume Log Estimation Using Image Processing Approach." Paper presented at the 52nd U.S. Rock Mechanics/Geomechanics Symposium, Seattle, Washington, June 2018.
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