An advanced prediction model of shale oil production profile based on source-reservoir assemblages and artificial neural networks

Y Liu, J Zeng, J Qiao, G Yang, W Cao - Applied Energy, 2023 - Elsevier
Over the past decade, hydrocarbon production from shale oil reservoirs has become
increasingly common, and successful shale oil exploration and development depends …

An integrated machine learning-based approach to identifying controlling factors of unconventional shale productivity

G Hui, Z Chen, Y Wang, D Zhang, F Gu - Energy, 2023 - Elsevier
The controlling factors of unconventional shale productivity by comprehensive analysis of
mineralogy, petrophysics, geochemistry, and geomechanics have not been well understood …

Forecasting, sensitivity and economic analysis of hydrocarbon production from shale plays using artificial intelligence & data mining

S Esmaili, A Kalantari-Dahaghi… - SPE Canada …, 2012 - onepetro.org
Our understanding of the complexities of the flow mechanism in Shale plays has not kept up
with our industry's interest in these prolific and hydrocarbon rich formations. Furthermore …

An AI-based workflow for estimating shale barrier configurations from SAGD production histories

J Zheng, JY Leung, RP Sawatzky… - Neural Computing and …, 2019 - Springer
An artificial intelligence (AI)-based workflow is deployed to develop and test procedures for
estimating shale barrier configurations from SAGD production profiles. The data employed in …

Method and practice of deep favorable shale reservoirs prediction based on machine learning

B Cheng, XU Tianji, LUO Shiyi, C Tianjie… - Petroleum Exploration …, 2022 - Elsevier
A set of methods for predicting the favorable reservoir of deep shale gas based on machine
learning is proposed through research of parameter correlation feature analysis principle …

[HTML][HTML] Smart shale gas production performance analysis using machine learning applications

FI Syed, S Alnaqbi, T Muther, AK Dahaghi… - Petroleum …, 2022 - Elsevier
With the advancement of technology and innovation in the oil and gas industry, the
production of liquid and gaseous hydrocarbon from conventional and unconventional …

Integration of artificial intelligence and production data analysis for shale heterogeneity characterization in steam-assisted gravity-drainage reservoirs

Z Ma, JY Leung, S Zanon - Journal of Petroleum Science and Engineering, 2018 - Elsevier
Abstract Steam-Assisted Gravity Drainage (SAGD) recovery is strongly impacted by
distributions of heterogeneous shale barriers, which impede the vertical growth and lateral …

[HTML][HTML] Intelligent prediction and integral analysis of shale oil and gas sweet spots

KR Qian, ZL He, XW Liu, YQ Chen - Petroleum Science, 2018 - Springer
Shale reservoirs are characterized by low porosity and strong anisotropy. Conventional
geophysical methods are far from perfect when it comes to the prediction of shale sweet spot …

Machine learning-based production forecast for shale gas in unconventional reservoirs via integration of geological and operational factors

G Hui, S Chen, Y He, H Wang, F Gu - Journal of Natural Gas Science and …, 2021 - Elsevier
Hundreds of horizontal wells have been performed fracturing operations to exploit the
unconventional shale gas resources in the Duvernay Formation of Fox Creek, Alberta …

[HTML][HTML] Shale gas production evaluation framework based on data-driven models

YW He, ZY He, Y Tang, YJ Xu, JC Long… - Petroleum Science, 2023 - Elsevier
Increasing the production and utilization of shale gas is of great significance for building a
clean and low-carbon energy system. Sharp decline of gas production has been widely …