# An explainable ensemble machine learning model to elucidate the influential drilling parameters based on rate of penetration prediction
> Feng Z.

URL kanonis: https://discover.unhas.ac.id/publications/an-explainable-ensemble-machine-learning-model-to-elucidate-the-influential-dril
Jurnal / Konferensi: Geoenergy Science and Engineering
Tahun terbit: 2023
DOI: https://doi.org/10.1016/j.geoen.2023.212231
ISSN: 29498910
Kuartil SJR: Q1
Citations: 24

## Authors
- Feng Z.

## Abstract
Sourced directly from Elsevier Scopus. No OpenAlex abstract available.

## Keywords
- Drilling
- Rate of penetration
- Drill
- Volumetric flow rate
- Torque
- Petroleum engineering
- Computer science
- Drill bit
- Drilling fluid
- Drill pipe
- Machine learning
- Artificial intelligence
- Geology
- Mechanical engineering
- Engineering
- Mechanics
- Physics
- Thermodynamics

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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