CPC E21B 49/003 (2013.01) [G05B 13/027 (2013.01); E21B 2200/20 (2020.05)] | 14 Claims |
8. A method, comprising:
measuring drilling performance metrics while performing drilling operations in an offset well using an instrumented cutter of a drill bit comprising an on-cutter sensor;
transmitting the drilling performance metrics to a computing device;
training a machine learning (ML) model hosted by the computing device using processed drilling performance metrics, surface drilling parameters, and characteristics of the instrumented cutter to obtain a trained ML model;
using the trained ML model to optimize the surface drilling parameters and predict drill bit performance while performing drilling operations in a current well;
processing the drill performance metrics, surface drilling parameters, and the characteristics of the instrumented cutter by:
aggregating drill performance metrics from a plurality of on-cutter sensors of the instrumented cutter; and
transforming the drill performance metrics, the surface drilling parameters, and characteristics of the instrumented cutter to remove noise using a Fast Fourier Transform.
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