Forecasting oil production in unconventional reservoirs using long short term memory network coupled support vector regression method: A case study-Reference-Cited by-同舟云学术

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Forecasting oil production in unconventional reservoirs using long short term memory network coupled support vector regression method: A case study

Published:2023-12 Issue:4 Volume:9 Page:647-657
ISSN:2405-6561
Container-title:Petroleum
language:en
Short-container-title:Petroleum

Author:

Wen Shuqin,Wei Bing,You Junyu,He Yujiao,Xin Jun,Varfolomeev Mikhail A.^ORCID

Publisher

Elsevier BV

Subject

Geochemistry and Petrology,Geology,Energy Engineering and Power Technology,Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference40 articles.

1. Numerical modelling of cyclic CO2 injection in unconventional tight oil resources; trivial effects of heterogeneity and hysteresis in Bakken formation;Assef;Fuel,2019

2. Hybrid CO2-N2 huff-n-puff strategy in unlocking tight oil reservoirs;Li;Fuel,2022

3. Enhanced oil recovery by low-salinity water spontaneous imbibition (LSW-SI) in a typical tight sandstone formation of mahu sag from core scale to field scale;Wei;Petroleum,2021

4. Geological concepts, characteristics, resource potential and key techniques of unconventional hydrocarbon: on unconventional petroleum geology;Zou;Petrol. Explor. Dev.,2013

5. Development characteristics and orientation of tight oil and gas in China;Sun;Petrol. Explor. Dev.,2019

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