The project ahead wellpath trajectory models are built on assumptions of static earth model and wellpath error models which may not be valid all the time. But the data will provide additional support to suppress the assumption and improve the models. So, an optimized project ahead model that combines geometry, bottomhole assembly (BHA) dynamics and dynamic earth model is needed for a practical project ahead prediction. This paper presents a coupled model with embedded uncertainty not only for projecting ahead the path but also steering to achieve the path. This paper presents the results that can be used under uncertainty through planning, through realtime project ahead, most importantly by integrating all the above four models.

Planning and executions are two primary approaches to intelligent decision making at the edge when the well is constructed. Execution enables us to take immediate actions far into the future, but it requires accurate well trajectory models, and the current and past realtime data. When it comes to the edge decision whether it is manual or semi-automated or fully automated it requires tighter coupling of engineering models through microservices and reinforced learning from the data and feedback from the driller. Four major types of models are considered in this paper to arrive at the dynamic path as the well is drilled. 1. Soft landing path based on dogleg as constraint 2. Minimum well profile energy that can be achieved 3. Mechanical drillahead model based on the steering tool 4. Productivity coupled earth model for various input parameters from earth model to operational parameters during drilling.

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