Machine learning -based prediction of the shale barrier size and spatial location using key features of SAGD production curves

Kim, Min; Shin, Hyundon

doi:10.1016/j.petrol.2020.107205

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Machine learning -based prediction of the shale barrier size and spatial location using key features of SAGD production curves

Kim, Min;
Shin, Hyundon

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22

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26

키워드

Artificial neural network (ANN); Hyperparameters tuning; Multiple linear regression (MLR); Random forest; Shale barrier (SB); Steam-assisted gravity drainage (SAGD); ASSISTED-GRAVITY-DRAINAGE; STEAM-CHAMBER; RESERVOIR PARAMETERS; NEURAL-NETWORKS; INTEGRATION; SIMULATION; INSIGHTS; DESIGN; GROWTH; MODEL

제목: Machine learning -based prediction of the shale barrier size and spatial location using key features of SAGD production curves

저자: Kim, Min; Shin, Hyundon

DOI: 10.1016/j.petrol.2020.107205

발행일: 2020-08

유형: Article

저널명: Journal of Petroleum Science and Engineering

권: 191