Drilling Monitoring System: Mud Motor Condition and Performance Evaluation

Condition monitoring of bottom hole assembly (BHA) is essential during the different lifecycle stages of the drilling process, whether during the planning, implementation, or post-job failure analysis. Mud motor condition evaluation can assist in preventing mud motor damage and increasing drilling efficiency. This paper aims to develop a monitoring system that combines field data, data analytics and physics-based modelling to evaluate mud motor condition and performance. The drilling monitoring system is a set of modelling and analysis tools that utilize actual drilling data, power section performance data and drillstring design to recreate the drilling process. An unprocessed drilling dataset is required to assess the drilling operations (rotating or sliding mode, rotating off-bottom, backreaming, connections) and reconstruct the borehole trajectory from the measured survey and duty cycle (rotating and sliding mode). Interaction of the BHA and the borehole generate side forces and bending moments along the length of the BHA that are evaluated at each depth increment during the drilling process. Generated power and efficiency of the mud motor are calculated and incorporated into the dynamic simulation. The case study investigates two motor runs in vertical and inclined sections. Dynamic modelling and extensive data analytics assist in visualizing and correlating the input and output variables during the drilling process. The continuous evaluation of the differential pressure on the motor is the primary parameter that is investigated. The motor condition is established with a continuous wear-off test while drilling and correlation matrices to indicate a constant motor state for 135 hours. The system accurately monitors the motor's operating efficiency, with the additional advantage that the mud motor and drill bit performance are differentiated. Precise adjustments of the drilling parameters for the optimum depth of cut positively impact motor efficiency. In addition, an interesting observation shows that accurate modelling of downhole and surface torque provides significant insights regarding bit state. The results demonstrate that with the current methodology decrease in drilling efficiency is detected and is associated with bit wear. The work enables the evaluation of the mud motor condition and performance by utilizing a monitoring system and actual drilling data. The drilling monitoring system is a modelling analysis tool that can provide continuous feedback to the drilling operators about the condition of the BHA. Hence, it enables a real-time optimization process to manage mud motor condition and enhance drilling efficiency.