Real-Time Fatigue Risk Assessment of BHA Connectors Using Combined Physics and Data-Driven Approach
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https://orcid.org/0009-0000-9481-4379
Yaou Wang Wei Chen Jennifer Gilliam
Abstract
Drilling operations depend not only on controlling surface parameters but also on keeping bottom-hole assembly (BHA) components structurally sound. The BHA is the lower portion of the drill string in a drilling operation – the part that actually contacts the wellbore and guides the drilling process. Failures, especially at the connection between the flow diverter and the drive shaft behind the mud-motor power section, can cause major non-productive time (NPT), high costs, and poor performance. These failures are often linked to combined surface and downhole rotational speeds and high bending moments, which are common during directional drilling. To reduce this risk, we present a new method for real-time health monitoring and remaining useful life (RUL) estimation of these connections. The method combines physics-based fatigue modeling with machine-learning estimators, making it possible to track connector use across time and jobs using serialized component data. The system processes real-time drilling parameters to estimate downhole rotational speed (RPM) and bending moment. When measurement-while-drilling (MWD) data are available, direct RPM values are used; otherwise, a predictive model based on temperature, flow rate, and differential pressure is applied. Bending moment is inferred from drilling parameters and BHA design. The framework then calculates fatigue damage with connector-specific S–N (stress–number of cycles) curves and updates both current and cumulative RUL values. This helps operators make proactive decisions and lowers the risk of expensive failures. Tests with historical drilling data show strong agreement between predicted damage and observed connector failures, proving that the approach works in the field. The solution is already integrated into a commercial platform and used by field teams. Case studies show it reduces unexpected failures, cuts non-productive time, and improves the efficiency of directional drilling.
How to Cite
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drilling, fatigue failure, real-time monitoring, BHA integrity
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