Summary of Vpi-mlogs: a Web-based Machine Learning Solution For Applications in Petrophysics, by Anh Tuan Nguyen
VPI-Mlogs: A web-based machine learning solution for applications in petrophysics
by Anh Tuan Nguyen
First submitted to arxiv on: 6 Oct 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The abstract discusses machine learning applications in petrophysics, specifically highlighting the research and deployment of effective prediction models by the Vietnam Petroleum Institute (VPI). The VPI-MLogs platform is a web-based solution that integrates data preprocessing, exploratory data analysis, visualization, and model execution using Python. This tool enables users to work with petrophysical logs more effectively, bridging the gap between common knowledge and petrophysical insights. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper explores machine learning techniques in petrophysics, focusing on a web-based platform developed by VPI. The VPI-MLogs system integrates various tools, including data preprocessing, analysis, visualization, and model execution using Python. This application helps users understand and work with petrophysical logs more efficiently. |
Keywords
* Artificial intelligence * Machine learning
