Application of Digitalization in Real-Time Analysis of Drilling Dynamics Using Along-String Measurement (ASM) Data along Wired Pipes

An automated drilling system requires a real-time evaluation of the bit during to optimize operation and determine when stop switch bits. Furthermore, in dynamic modeling drill strings, it is necessary take into account interactions between bits rock. To address this challenge, hybrid approach that combines physics-based models with data analytics has been developed handle downhole measurements real time. First, experimental findings were used formulate mathematical cutter–rock interaction accordance their geometrical characteristics, rock properties, parameters. Specifically, these represent normal contact forces polycrystalline diamond compact cutters (PDCs). Experimental are analyzed utilizing deep learning, nonlinear regression, genetic algorithms fit equations points. Following this, recursive least square was implemented as analytic method integrate data, models, models. Drilling captured by along-string measurement (ASM) estimate cutting forces, torque, specific energy at bit. The unique aspect research our developing detailed model takes all design parameters account. In addition, applicability algorithm demonstrated assessments dynamics, digital enable prediction events problems related