New numerical method for sand production propensity estimation

• Main Authors: Subbiah, Surej Kumar, Mohamad Hussein, Assef, Samsuri, Ariffin, Jaafar, Mohd. Zaidi, Chen, Ying Ru, Pearce, Andrew, Kumar, Rajeev Ranjan, Paramanathan, Rajendra Nath
• Format: Conference or Workshop Item
• Published: 2023
• Subjects: Q Science (General)
• Online Access: http://eprints.utm.my/108443/; http://dx.doi.org/10.2118/213381-MS
• Institution: Universiti Teknologi Malaysia

The sandstone reservoir rock failure during production may lead to sand production issues and may impact the economics of field development strategy, especially deep-water operation. The lifting cost can be higher as the issue can lead to metal-erosion, well integrity and oil/gas leakage. In the absence of a sand control mechanism (screenless-completions), the production rates often reduced to bound the severity of sanding and its consequences. In nutshell, the wrong decision for the type of completion prior to drilling and production may risk the financial feasibility of the field. Therefore, an accurate prediction of sand production volume/rates is essential during the well planning. Having this information upfront will able the operators to select the best sand-management plan for the well and field economically (best productivity and highest ultimate recovery while keeping the operating cost low. This paper reviews the ingredients required for sand propensity modeling, not limited to onset sanding drawdown but also the sand propensity (volume). A new proposed modeling technique for sand production propensity will be discussed. The new innovative modelling techniques (fully coupled with fluid dynamics) is powered by a new constitutive elastoplastic and damage model. The newly developed failure criteria give better insight for rock mechanical behavior honoring pre and post-failure stages enabling the usage for sand production analysis to estimate the sanding propensity which includes stress stabilization. Validation and comparison between laboratory testing and numerical modeling for sand production volume presented using the newly developed modeling techniques namely perforation cavity geometry stabilization and grid cell removal.