Application of Machine Learning Method of Data-Driven Deep Learning Model to Predict Well Production Rate in the Shale Gas Reservoirs

Application of Machine Learning Method of Data-Driven Deep Learning Model to Predict Well Production Rate in the Shale Gas Reservoirs

Reservoir modeling to predict shale reservoir productivity is considerably uncertain and time consuming. Since we need to simulate the physical phenomenon of multi-stage hydraulic fracturing. To overcome these limitations, this paper presents an alternative proxy model based on data-driven deep lear...

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Bibliographic Details
Main Authors: Dongkwon Han, Sunil Kwon
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Energies
Subjects:
shale reservoir
proxy model
data-driven
deep neural network
principal component analysis
variable importance analysis
Online Access:https://www.mdpi.com/1996-1073/14/12/3629

Internet

https://www.mdpi.com/1996-1073/14/12/3629

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