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Title: Control systems and methods to enable autonomous drilling

Abstract

A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy. Near-bit depth-of-cut estimations are performed using a machine learning prediction deployed in an embedded processor to provide high-speed ROP estimates. The sensing capability is coupled with a near-bit clutching mechanism to support drilling dysfunction mitigation.

Inventors:
; ; ; ; ; ; ;
Issue Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1892729
Patent Number(s):
11280173
Application Number:
17/157,614
Assignee:
National Technology & Engineering Solutions of Sandia, LLC (Albuquerque, NM)
Patent Classifications (CPCs):
E - FIXED CONSTRUCTIONS E21 - EARTH DRILLING E21B - EARTH DRILLING, e.g. DEEP DRILLING
DOE Contract Number:  
NA0003525
Resource Type:
Patent
Resource Relation:
Patent File Date: 01/25/2021
Country of Publication:
United States
Language:
English

Citation Formats

Buerger, Stephen, Mazumdar, Anupam, Spencer, Steven James, Blada, Timothy James, Su, Jiann-Cherng, Wright, Elton K., Foris, Adam, and Raymond, David W. Control systems and methods to enable autonomous drilling. United States: N. p., 2022. Web.
Buerger, Stephen, Mazumdar, Anupam, Spencer, Steven James, Blada, Timothy James, Su, Jiann-Cherng, Wright, Elton K., Foris, Adam, & Raymond, David W. Control systems and methods to enable autonomous drilling. United States.
Buerger, Stephen, Mazumdar, Anupam, Spencer, Steven James, Blada, Timothy James, Su, Jiann-Cherng, Wright, Elton K., Foris, Adam, and Raymond, David W. Tue . "Control systems and methods to enable autonomous drilling". United States. https://www.osti.gov/servlets/purl/1892729.
@article{osti_1892729,
title = {Control systems and methods to enable autonomous drilling},
author = {Buerger, Stephen and Mazumdar, Anupam and Spencer, Steven James and Blada, Timothy James and Su, Jiann-Cherng and Wright, Elton K. and Foris, Adam and Raymond, David W.},
abstractNote = {A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy. Near-bit depth-of-cut estimations are performed using a machine learning prediction deployed in an embedded processor to provide high-speed ROP estimates. The sensing capability is coupled with a near-bit clutching mechanism to support drilling dysfunction mitigation.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Mar 22 00:00:00 EDT 2022},
month = {Tue Mar 22 00:00:00 EDT 2022}
}

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