Study on Wellbore Stability of Shallow Sediments in Deepwater Drilling
Jun Zhang1, *, Chi Ai1, Bo Zeng2, Yuwei Li1, Jia Zeng1
Identifiers and Pagination:Year: 2017
First Page: 48
Last Page: 63
Publisher Id: TOPEJ-10-48
Article History:Received Date: 10/11/2016
Revision Received Date: 07/01/2017
Acceptance Date: 09/02/2017
Electronic publication date: 31/03/2017
Collection year: 2017
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The deepwater shallow formation has low fracture pressure and narrow safe window of mud density, which results in a high risk of wellbore instability in this kind of formation.
Without considering the plastic state of shallow formation around the borehole or the influence of in-situ stress difference on wellbore stability, the prediction accuracy of the traditional wellbore stability analysis models are relatively low. This paper can provide a reliable method to accurately predict the safe window of drilling fluid density.
In this paper, the shallow formation around the borehole is divided into plastic zone and elastic zone considering it under non-uniform in-situ stress. The collapse pressure formula of shallow formation is derived by taking the shrinkage rate of the borehole as the instability criterion. The fracturing pressure calculation model of shallow sediment under non-uniform in-situ stress is derived by combining the theory of excess pore pressure and hydraulic fracturing.
The calculated results indicate that the horizontal in-situ stress difference has a significant effect on the shape of the plastic zone, the shrinkage rate of borehole, collapse pressure and fracturing pressure. The calculated results are in good agreement with the field test results, and the prediction accuracy of this model is higher than that of other traditional models.