Petroleum Analytics Learning Machine to Forecast Production in the Wet Gas Marcellus Shale-Reference-Cited by-同舟云学术

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Petroleum Analytics Learning Machine to Forecast Production in the Wet Gas Marcellus Shale

Published:2016 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 4th Unconventional Resources Technology Conference
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Author:

Anderson Roger N.,Xie Boyi,Wu Leon,Kressner Arthur A.,Frantz Jr. Joseph H.,Ockree Matthew A.,Brown Kenneth G.

Publisher

American Association of Petroleum Geologists

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Data-Driven Oil Production Prediction Method Based on the Gradient Boosting Decision Tree Regression;Computer Modeling in Engineering & Sciences;2023

2. Multi-Layer LSTM Implementation in Operational Condition Forecasting of a Natural Gas Transmission Pipeline Network;2022 5th International Conference on Information and Communications Technology (ICOIACT);2022-08-24

3. A new production analysis method for shale gas well based on the evaluation of decline parameters in advance;Journal of Natural Gas Science and Engineering;2021-05

4. Transformation, Analysis and Visualization of Distributed Temperature Sensing Data generated by Oil Wells;2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT);2020-10-07

5. Deep-convolutional neural networks in prestack seismic: Two exploratory examples;SEG Technical Program Expanded Abstracts 2018;2018-08-27

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