Work

Production Forecasting in Shale Reservoirs Using LSTM Method in Deep Learning

Year: 2020

Type: conference-paper

Source: Unconventional Resources Technology Conference (URTeC)

DOI: 10.15530/urtec-2020-2878

Authors: Cenk Temizel, Celal Hakan Canbaz, Onder Saracoglu, Dike Putra, Ali Baser, Tomi Erfando, Shanker Krishna, Luigi Saputelli

Institutions: Saudi Aramco (United States), Ege University, Middle East Technical University, Islamic University of Riau, Pandit Deendayal Energy University

Language: English

Topic: Reservoir Engineering and Simulation Methods

Subfield: Fuel Technology

Field: Energy

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W3044355331

FWCI: 12.24

Cites:

Cited by: 63

Related to: 10