Big Data Analysis for Monitoring of Kick Formation in Complex Underwater Drilling Projects-Reference-Cited by-同舟云学术

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Big Data Analysis for Monitoring of Kick Formation in Complex Underwater Drilling Projects

Published:2018-09 Issue:5 Volume:32 Page:04018030
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Xie Haiyan¹,Shanmugam Arun Kumar²,Issa Raja R. A.³

Affiliation:

1. Associate Professor, Dept. of Technology, Illinois State Univ., Turner 5100, Normal, IL 61790 (corresponding author).

2. Graduate Student, Dept. of Technology, Illinois State Univ., Turner 5100, Normal, IL 61790.

3. Holland Professor, Rinker School of Construction Management, Univ. of Florida, Gainesville, FL 32611.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000773

Reference39 articles.

1. The expanding role of mud logging;Ablard P.;Oilfield Rev.,2012

2. Neural Networks in Civil Engineering: 1989–2000

3. Dynamic Fuzzy Wavelet Neural Network Model for Structural System Identification

4. Reservoir permeability prediction by neural networks combined with hybrid genetic algorithm and particle swarm optimization

5. Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application

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3. Predictive big data analytics for drilling downhole problems: A review;Energy Reports;2023-12

4. An enhanced data-driven framework for early kick detection based on imbalanced multivariate time series classification;Neural Computing and Applications;2023-05-22

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