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- Title
Prediction of Cuttings Transport Behavior under Drill String Rotation Conditions in High-Inclination Section.
- Authors
Sun, Shihui; Feng, Jinyu; Hou, Zhaokai; Yu, Guoqing
- Abstract
Cuttings are likely to accumulate and eventually form a cuttings bed in the highly-deviated section, which usually lead to high friction and torque, slower rate of penetration, pipe stuck and other problems. It is therefore necessary to study cuttings transport mechanism and improve hole cleaning efficiency. In this study, the cuttings-transport behaviors with pipe rotation under turbulent flow conditions in the highly deviated eccentric section were numerically simulated based on Euler solid–fluid model and Realizable k – ε model. The resulted numerical results were compared with available experimental data in reported literature to validate the algorithm, and good agreement was found. Under the conditions of drill string rotation, cuttings bed surface tilts in the direction of rotation and distributes asymmetrically in annulus. Drill string rotation, drilling fluid flow rate, cuttings diameter, cuttings injection concentration and drilling fluid viscosity affect the axial velocity of drilling fluid; whereas drilling fluid tangential velocity is mainly controlled by the rotational speed of drill string. Increase in value of drill string rotation, drilling fluid flow rate or hole inclination will increase cuttings migration velocity. Notably, drill string rotation reduces cuttings concentration and solid–fluid pressure loss, and their variations are dependent on inclination, cuttings injection concentration, cuttings diameter, drilling fluid velocity and viscosity. However, when a critical rotation speed is reached, no additional contribution is observed. The results can provide theoretical support for optimizing hole cleaning and realizing safety drilling of horizontal wells and extended reach wells.
- Subjects
DRILL stem; DRILLING fluids; ROTATIONAL motion; FORECASTING; FLUID flow; TURBULENT flow; PIPE; TORQUE
- Publication
International Journal of Pattern Recognition & Artificial Intelligence, 2020, Vol 34, Issue 10, pN.PAG
- ISSN
0218-0014
- Publication type
Article
- DOI
10.1142/S0218001420590351