U.S. Department of EnergyOffice of Scientific and Technical Information
Microhole drilling technology utilizing a golden section search algorithm
Abstract
A fundamental issue in microhole drilling is that delivering high weight-on-bit (WOB), high torque rotational horsepower to a conventional drill bit does not scale down to the hole sizes necessary to realize the envisioned cost savings An optimization algorithm called a golden section search (GSS) was used to systematically identify the preferred WOB for a given set of conditions. This research focused on implementing and evaluating two low WOB drilling technologies for microhole drilling: - Laser-assisted mechanical drill, which was tested in the laboratory - Lightly modified commercial off-the-shelf (COTS) percussive hammer, which was tested in a limited field test. Data were collected for microhole GSS using WOB optimization via simulation as well as at the Blue Canyon Dome Site in Socorro, NM. Information on the attached files and folders are as follows: - the .tdms files are LabView data files, which can be opened within Excel using a .tdms add-in or using a Matlab .tdms converter - the .tdms_index files are part of the .tdms file structure - sampling rate, column headers, and length data within the .tdms files follow SOP when utilizing Excel and/or Matlab as described above
- Authors:
-
- Sandia National Laboratories
- Publication Date:
- Other Number(s):
- 1360
- Research Org.:
- DOE Geothermal Data Repository; Sandia National Laboratories
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)
- Collaborations:
- Sandia National Laboratories
- Subject:
- 15 GEOTHERMAL ENERGY; Blue Canyon Dome; GSS; New Mexico; New Mexico Tech Energetic Materials Research and Testing Center; Socorro; WOB; algorithm; drilling; exploration; feasibility; geothermal; golden section search; microholes; monitoring; optimization; percussive hammer; slimholes; technical assessment; weight-on-bit
- OSTI Identifier:
- 1995008
- DOI:
- https://doi.org/10.15121/1995008
Citation Formats
Su, Jiann, Mazumdar, Anirban, Buerger, Stephen, Foris, Adam, and Faircloth, Brian. Microhole drilling technology utilizing a golden section search algorithm. United States: N. p., 2021.
Web. doi:10.15121/1995008.
Su, Jiann, Mazumdar, Anirban, Buerger, Stephen, Foris, Adam, & Faircloth, Brian. Microhole drilling technology utilizing a golden section search algorithm. United States. doi:https://doi.org/10.15121/1995008
Su, Jiann, Mazumdar, Anirban, Buerger, Stephen, Foris, Adam, and Faircloth, Brian. 2021.
"Microhole drilling technology utilizing a golden section search algorithm". United States. doi:https://doi.org/10.15121/1995008. https://www.osti.gov/servlets/purl/1995008. Pub date:Wed Jun 23 04:00:00 UTC 2021
@article{osti_1995008,
title = {Microhole drilling technology utilizing a golden section search algorithm},
author = {Su, Jiann and Mazumdar, Anirban and Buerger, Stephen and Foris, Adam and Faircloth, Brian},
abstractNote = {A fundamental issue in microhole drilling is that delivering high weight-on-bit (WOB), high torque rotational horsepower to a conventional drill bit does not scale down to the hole sizes necessary to realize the envisioned cost savings An optimization algorithm called a golden section search (GSS) was used to systematically identify the preferred WOB for a given set of conditions. This research focused on implementing and evaluating two low WOB drilling technologies for microhole drilling: - Laser-assisted mechanical drill, which was tested in the laboratory - Lightly modified commercial off-the-shelf (COTS) percussive hammer, which was tested in a limited field test. Data were collected for microhole GSS using WOB optimization via simulation as well as at the Blue Canyon Dome Site in Socorro, NM. Information on the attached files and folders are as follows: - the .tdms files are LabView data files, which can be opened within Excel using a .tdms add-in or using a Matlab .tdms converter - the .tdms_index files are part of the .tdms file structure - sampling rate, column headers, and length data within the .tdms files follow SOP when utilizing Excel and/or Matlab as described above},
doi = {10.15121/1995008},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jun 23 04:00:00 UTC 2021},
month = {Wed Jun 23 04:00:00 UTC 2021}
}