The Role of Elasto-Plasticity in Cavity Shape and Sand Production in Oil and Gas Wells
Summary Previous experimental observations have shown the formation of distinct failure patterns and cavity shapes under different stress and flow conditions. With isotropic stress, spiral failure patterns with localized shear bands are likely to form. On the other hand, under anisotropic stress, V-shaped cavities, dog-ear cavities, or slit-mode cavities are usually observed. However, the mechanisms for the development of these sanding cavities have not been fully articulated. In addition, to accurately predict the onset of sanding and to predict the sand-production rate, it is crucial to capture the physics of the formation of these cavities during sand production. This paper presents a fully coupled poro-elasto-plastic, 3D sand-production model for sand-production prediction around openhole and perforated wellbores in a weakly consolidated formation. Sanding criteria are based on a combination of shear failure, tensile failure, and compressive failure from the Mohr-Coulomb theory and strain-hardening/softening. After the failure criteria are met, an algorithm for the entrainment of the sand based on the calculation of hydrodynamic forces is implemented to predict sand erosion and transport. Dynamic mesh refinement has been implemented to effectively capture the strain-localization regions. The model has been validated with multiple analytical solutions. In addition, it is applied to compare with previous sand-production experiments that have explored the different cavity shapes formed under different conditions. The model is capable of not only explaining the mechanisms responsible for each type of cavity shape but also predicting the cavity shape that will be formed under a specific set of conditions. Parametric studies for these cases provide an additional insight into the important role that the post-yield, poro-elasto-plastic properties of the sand play in controlling the sanding mechanisms and cavity development. This allows us to predict, much more accurately, the onset of sanding and the sanding rate.