| Adsorption characteristics of supercritical CO2/CH4 on different types of coal and a machine learning approach M Meng, Z Qiu, R Zhong, Z Liu, Y Liu, P Chen Chemical Engineering Journal 368, 847-864, 2019 | 114 | 2019 |
| Prediction of methane adsorption in shale: Classical models and machine learning based models M Meng, R Zhong, Z Wei Fuel 278, 118358, 2020 | 80 | 2020 |
| Generating pseudo density log from drilling and logging-while-drilling data using extreme gradient boosting (XGBoost) R Zhong, R Johnson Jr, Z Chen International Journal of Coal Geology 220, 103416, 2020 | 65 | 2020 |
| Using machine learning methods to identify coal pay zones from drilling and logging-while-drilling (LWD) data R Zhong, RL Johnson Jr, Z Chen Spe Journal 25 (03), 1241-1258, 2020 | 46 | 2020 |
| Modeling of near-wellbore fracturing for wellbore strengthening R Zhong, S Miska, M Yu Journal of Natural Gas Science and Engineering 38, 475-484, 2017 | 45 | 2017 |
| Time-dependent coal permeability: Impact of gas transport from coal cleats to matrices C Wang, J Zhang, Y Zang, R Zhong, J Wang, Y Wu, Y Jiang, Z Chen Journal of Natural Gas Science and Engineering 88, 103806, 2021 | 39 | 2021 |
| Machine Learning for Drilling Applications: A Review R Zhong, C Salehi, Johnson Jr R Journal of Natural Gas Science and Engineering, 2022 | 32 | 2022 |
| Understanding competing effect between sorption swelling and mechanical compression on coal matrix deformation and its permeability C Wang, J Zhang, J Chen, R Zhong, G Cui, Y Jiang, W Liu, Z Chen International Journal of Rock Mechanics and Mining Sciences 138, 104639, 2021 | 32 | 2021 |
| An integrated fluid flow and fracture mechanics model for wellbore strengthening R Zhong, S Miska, M Yu, E Ozbayoglu, N Takach Journal of Petroleum Science and Engineering 167, 702-715, 2018 | 30 | 2018 |
| Parametric study of controllable parameters in fracture-based wellbore strengthening R Zhong, S Miska, M Yu Journal of Natural Gas Science and Engineering 43, 13-21, 2017 | 28 | 2017 |
| Numerical modeling of land subsidence resulting from oil production S Zhang, R Zhong, Y Liu ARMA US Rock Mechanics/Geomechanics Symposium, ARMA-2016-382, 2016 | 23 | 2016 |
| Experimental investigation of fracture-based wellbore strengthening using a large-scale true triaxial cell R Zhong, S Miska, M Yu, M Meng, E Ozbayoglu, N Takach Journal of Petroleum Science and Engineering 178, 691-699, 2019 | 21 | 2019 |
| Using machine learning methods to identify coals from drilling and logging-while-drilling LWD data R Zhong, RL Johnson Jr, Z Chen Asia Pacific Unconventional Resources Technology Conference, Brisbane …, 2019 | 17 | 2019 |
| Coal identification using neural networks with real-time coalbed methane drilling data R Zhong, R Johnson, Z Chen, N Chand The APPEA Journal 59 (1), 319-327, 2019 | 13 | 2019 |
| Fully coupled finite element model to study fault reactivation during multiple hydraulic fracturing in heterogeneous tight formations R Zhong, J Bao, E Fathi SPE Eastern Regional Meeting, SPE-171035-MS, 2014 | 13 | 2014 |
| Estimating coal permeability using machine learning methods C Salehi, R Zhong, S Ganpule, S Dewar, R Johnson, Z Chen SPE Asia Pacific Oil and Gas Conference and Exhibition, D023S013R003, 2020 | 11 | 2020 |
| Improving rock mechanical properties estimation using machine learning R Zhong, M Tsang, G Makusha, B Yang, Z Chen University of Wollongong/University of Southern Queensland, 2021 | 8* | 2021 |
| Experimental investigation of the flow properties of layered coal-rock analogues V Santiago, FG Zabala, AJ Sanchez-Barra, N Deisman, RJ Chalaturnyk, ... Chemical Engineering Research and Design 186, 685-700, 2022 | 5 | 2022 |
| Modeling and Experimental Study of Fracture-Based Wellbore Strengthening R Zhong Ph. D. Thesis, 2018 | 5 | 2018 |
| A leak-off model for critical permeability in wellbore strengthening applications R Zhong, S Miska, M Yu, E Ozbayoglu, J Zhang, R Majidi AADE National Technical Conference and Exhibition, Houston, Texas, 11-12, 2017 | 5 | 2017 |
Zhongwei ChenUniversity of Queensland在 uq.edu.au 的电子邮件经过验证
