Trend and dynamic analysis on temporal drilling data and their data-driven models-Reference-Cited by-同舟云学术

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Trend and dynamic analysis on temporal drilling data and their data-driven models

Published:2023-04 Issue: Volume:223 Page:211530
ISSN:2949-8910
Container-title:Geoenergy Science and Engineering
language:en
Short-container-title:Geoenergy Science and Engineering

Author:

Sui Dan,Sahebi Hamed

Publisher

Elsevier BV

Reference34 articles.

1. Hybrid data driven drilling and rate of penetration optimization;Alali;J. Pet. Sci. Eng.,2021

2. Machine learning methods applied to drilling rate of penetration prediction and optimization - A review;Barbosa;J. Pet. Sci. Eng.,2019

3. First principles and machine learning virtual flow metering: A literature review;Bikmukhametov;J. Pet. Sci. Eng.,2020

4. A review on application of data-driven models in hydrocarbon production forecast;Cao;J. Pet. Sci. Eng.,2022

5. A novel interval-halving framework for automated identification of process trends;Dash;AIChE J.,2004

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