Derives wellbore kinematic models from differential geometry and applies a rigorously derived GRU network to LAS and DEV data from 14 Gulfaks wells for trajectory prediction with MAE, RMSE, and R2 evaluation.
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A Geomechanically-Informed Framework for Wellbore Trajectory Prediction: Integrating First-Principles Kinematics with a Rigorous Derivation of Gated Recurrent Networks
Derives wellbore kinematic models from differential geometry and applies a rigorously derived GRU network to LAS and DEV data from 14 Gulfaks wells for trajectory prediction with MAE, RMSE, and R2 evaluation.