The University of Queensland

Using machine learning to improve drilling of unconventional resources

Zhong, Ruizhi (2022). Using machine learning to improve drilling of unconventional resources. Machine learning applications in subsurface energy resource management. (pp. 91-110) edited by Srikanta Mishra. Boca Raton, FL USA: CRC Press. doi: 10.1201/9781003207009-9

Wellbore strengthening

Zhong, Ruizhi (2022). Wellbore strengthening. Drilling Mechanics: Advanced Applications and Technology. (pp. 324-348) edited by Stefan Z. Miska, Robert F. Mitchell and Evren M. Ozbayoglu. New York, NY United States: McGraw-Hill.

Automatic coal mine roof rating calculation using machine learning

Li, Jimmy Xuekai, Tsang, Matt, Zhong, Ruizhi, Esterle, Joan, Pirona, Claire, Rajabi, Mojtaba and Chen, Zhongwei (2023). Automatic coal mine roof rating calculation using machine learning. International Journal of Coal Geology, 274 104292, 1-14. doi: 10.1016/j.coal.2023.104292

Machine learning for drilling applications: a review

Zhong, Ruizhi, Salehi, Cyrus and Johnson, Ray (2022). Machine learning for drilling applications: a review. Journal of Natural Gas Science and Engineering, 108 104807, 1-17. doi: 10.1016/j.jngse.2022.104807

Experimental investigation of the flow properties of layered coal-rock analogues

Santiago, Vanessa, Zabala, Francy Guerrero, Sanchez-Barra, Angel J., Deisman, Nathan, Chalaturnyk, Richard J., Zhong, Ruizhi and Hurter, Suzanne (2022). Experimental investigation of the flow properties of layered coal-rock analogues. Chemical Engineering Research and Design, 186, 685-700. doi: 10.1016/j.cherd.2022.08.046

Efficient implicit methods for wellbore shear failure analysis during drilling and production in coalbeds

Zhong, Ruizhi, Mitchell, Travis, Johnson Jr., Raymond and Leonardi, Christopher (2022). Efficient implicit methods for wellbore shear failure analysis during drilling and production in coalbeds. International Journal of Rock Mechanics and Mining Sciences, 155 105129, 105129. doi: 10.1016/j.ijrmms.2022.105129

Time-dependent coal permeability: impact of gas transport from coal cleats to matrices

Wang, Chunguang, Zhang, Jidong, Zang, Yuxiao, Zhong, Ruizhi, Wang, Jianguo, Wu, Yu, Jiang, Yujing and Chen, Zhongwei (2021). Time-dependent coal permeability: impact of gas transport from coal cleats to matrices. Journal of Natural Gas Science and Engineering, 88 103806, 103806. doi: 10.1016/j.jngse.2021.103806

Understanding competing effect between sorption swelling and mechanical compression on coal matrix deformation and its permeability

Wang, Chunguang, Zhang, Jidong, Chen, Junguo, Zhong, Ruizhi, Cui, Guanglei, Jiang, Yujing, Liu, Weitao and Chen, Zhongwei (2021). Understanding competing effect between sorption swelling and mechanical compression on coal matrix deformation and its permeability. International Journal of Rock Mechanics and Mining Sciences, 138 104639, 104639. doi: 10.1016/j.ijrmms.2021.104639

Prediction of methane adsorption in shale: classical models and machine learning based models

Meng, Meng, Zhong, Ruizhi and Wei, Zhili (2020). Prediction of methane adsorption in shale: classical models and machine learning based models. Fuel, 278 118358, 118358. doi: 10.1016/j.fuel.2020.118358

Generating pseudo density log from drilling and logging-while-drilling data using extreme gradient boosting (XGBoost)

Zhong, Ruizhi, Johnson Jr, Raymond and Chen, Zhongwei (2020). Generating pseudo density log from drilling and logging-while-drilling data using extreme gradient boosting (XGBoost). International Journal of Coal Geology, 220 103416, 1-13. doi: 10.1016/j.coal.2020.103416

Using machine learning methods to identify coal pay zones from drilling and Logging-While-Drilling (LWD) data

Zhong, Ruizhi, Johnson, Raymond L. and Chen, Zhongwei (2020). Using machine learning methods to identify coal pay zones from drilling and Logging-While-Drilling (LWD) data. SPE Journal, 25 (03), 1241-1258. doi: 10.2118/198288-pa

Adsorption characteristics of supercritical CO2/CH4 on different types of coal and a machine learning approach

Meng, Meng, Qiu, Zhengsong, Zhong, Ruizhi, Liu, Zhenguang, Liu, Yunfeng and Chen, Pengju (2019). Adsorption characteristics of supercritical CO2/CH4 on different types of coal and a machine learning approach. Chemical Engineering Journal, 368, 847-864. doi: 10.1016/j.cej.2019.03.008

Experimental investigation of fracture-based wellbore strengthening using a large-scale true triaxial cell

Zhong, Ruizhi, Miska, Stefan, Yu, Mengjiao, Meng, Meng, Ozbayoglu, Evren and Takach, Nicholas (2019). Experimental investigation of fracture-based wellbore strengthening using a large-scale true triaxial cell. Journal of Petroleum Science and Engineering, 178, 691-699. doi: 10.1016/j.petrol.2019.03.081

Results of hydraulic fracturing design improvements and changes in execution strategies for unconventional tight gas targets in the Cooper Basin, Australia

Johnson Jr, Raymond, Zhong, Ruizhi and Nguyen, Lan (2019). Results of hydraulic fracturing design improvements and changes in execution strategies for unconventional tight gas targets in the Cooper Basin, Australia. APPEA Journal, 59 (1), 244-259. doi: 10.1071/aj18185

Coal identification using neural networks with real-time coalbed methane drilling data

Zhong, Ruizhi, Johnson Jr, Raymond, Chen, Zhongwei and Chand, Nathaniel (2019). Coal identification using neural networks with real-time coalbed methane drilling data. The APPEA Journal, 59 (1), 319-327. doi: 10.1071/aj18091

An integrated fluid flow and fracture mechanics model for wellbore strengthening

Zhong, Ruizhi, Miska, Stefan, Yu, Mengjiao, Ozbayoglu, Evren and Takach, Nicholas (2018). An integrated fluid flow and fracture mechanics model for wellbore strengthening. Journal of Petroleum Science and Engineering, 167, 702-715. doi: 10.1016/j.petrol.2018.04.052

Parametric study of controllable parameters in fracture-based wellbore strengthening

Zhong, Ruizhi, Miska, Stefan and Yu, Mengjiao (2017). Parametric study of controllable parameters in fracture-based wellbore strengthening. Journal of Natural Gas Science and Engineering, 43, 13-21. doi: 10.1016/j.jngse.2017.03.018

Modeling of near-wellbore fracturing for wellbore strengthening

Zhong, Ruizhi, Miska, Stefan and Yu, Mengjiao (2017). Modeling of near-wellbore fracturing for wellbore strengthening. Journal of Natural Gas Science and Engineering, 38, 475-484. doi: 10.1016/j.jngse.2017.01.009

Estimation of rock permeability scores using machine learning methods

Qalandari, Roohullah, Zhong, Ruizhi, Salehi, Cyrus, Chand, Nathaniel, Johnson, Raymond Leslie, Vazquez, Gonzalo, Mclean-Hodgson, Jack and Zimmerman, Joel (2022). Estimation of rock permeability scores using machine learning methods. SPE Asia Pacific Oil & Gas Conference and Exhibition, Adelaide, SA Australia, 17-19 October 2022. Dallas, TX USA: Society of Petroleum Engineers. doi: 10.2118/210711-ms

Real time, automatic injecting of foaming agent for gas deliquification in CQQK Gas Field, China: a case study

Cao, Guangqiang, Li, Nan, Wang, Haoyu, Zhong, Ruizhi and Shi, Tao (2022). Real time, automatic injecting of foaming agent for gas deliquification in CQQK Gas Field, China: a case study. SPE Asia Pacific Oil & Gas Conference and Exhibition, Adelaide, SA Australia, 17-19 October 2022. Dallas, TX USA: Society of Petroleum Engineers. doi: 10.2118/210756-ms

Study on the labyrinth screw pump for heavy oil production

Wang, Zhuoyu, Zhu, Jianjun, Cao, Guangqiang, Zhu, Hongwu, Zhong, Ruizhi and Zhu, Haiwen (2022). Study on the labyrinth screw pump for heavy oil production. SPE Asia Pacific Oil & Gas Conference and Exhibition, Adelaide, SA Australia, 17-19 October 2022. Dallas, TX USA: Society of Petroleum Engineers. doi: 10.2118/210687-ms

UCS prediction by group-based machine learning method

Li, Jimmy Xuekai, Tsang, Matt, Giese, Stephen, Zhong, Ruizhi, Esterle, Joan, Pirona, Claire, Rajabi, Mojtaba and Chen, Zhongwei (2022). UCS prediction by group-based machine learning method. Resource Operators Conference, Virtual, 10-11 February 2022. Wollongong, NSW, Australia: University of Wollongong and University of Southern Queensland.

Case Study and Sensitivity Analysis of Borehole Breakout in the Cooper Basin, Australia

Zhong, Ruizhi, Azman, Aideel, Johnson, Ray, You, Zhenjiang and Nguyen, Lan (2021). Case Study and Sensitivity Analysis of Borehole Breakout in the Cooper Basin, Australia. SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, Online, 16-18 November 2021. Tulsa, OK United States: Unconventional Resources Technology Conference. doi: 10.15530/ap-urtec-2021-208373

Analytical and numerical assessment of the influence of bulk coal strength on drilling operations in unconventional coal seam gas wells

Leonardi, C. R., Zhong, R., Mitchell, T. R., Chen, Z., Johnson, R. L., O'Hagan, D. and Flottmann, T. (2021). Analytical and numerical assessment of the influence of bulk coal strength on drilling operations in unconventional coal seam gas wells. 55th US Rock Mechanics/Geomechanics Symposium, Houston, TX USA, 20-23 June 2021. Alexandria, VA USA: American Rock Mechanics Association.

Improving estimation of rock mechanical properties using machine learning

Zhong, Ruizhi, Tsang, Matt, Makusha, Gift, Yang, Ben and Chen, Zhongwei (2021). Improving estimation of rock mechanical properties using machine learning. Resource Operators Conference, Virtual, 11-12 February 2021. Wollongong, Australia: University of Wollongong/University of Southern Queensland.

Numerical evaluation of bulk geomechanical properties of fractured coal with changing net effective stress conditions

Mitchell, Travis R., Zhong, Ruizhi, Johnson, Ray and Leonardi, Christopher R. (2021). Numerical evaluation of bulk geomechanical properties of fractured coal with changing net effective stress conditions. SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, Virtual, 16-18 November 2021. Tulsa, OK, United States: Unconventional Resources Technology Conference. doi: 10.15530/ap-urtec-2021-208346

Using machine learning for geosteering during in-seam drilling

Zhong, Ruizhi, Johnson Jr, Ray L. and Chen, Zhongwei (2021). Using machine learning for geosteering during in-seam drilling. SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, Virtual, 16–18 November, 2021. Tulsa, OK, United States: Unconventional Resources Technology Conference. doi: 10.15530/ap-urtec-2021-208298

Wellbore stability analysis of horizontal drilling in Bowen and Surat coal seam gas wells

Zhong, Ruizhi, Leonardi, Christopher R., Mitchell, Travis R. and Johnson, Ray L. (2021). Wellbore stability analysis of horizontal drilling in Bowen and Surat coal seam gas wells. SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, Virtual, 16-18 November 2021. Tulsa, OK, United States: Unconventional Resources Technology Conference. doi: 10.15530/ap-urtec-2021-208399

Estimating Coal Permeability Using Machine Learning Methods

Salehi, Cyrus, Zhong, Ruizhi, Ganpule, Sameer, Dewar, Steven, Johnson, Raymond and Chen, Zhongwei (2020). Estimating Coal Permeability Using Machine Learning Methods. SPE Asia Pacific Oil & Gas Conference and Exhibition, Online, 17-19 November 2020. Richardson, TX United States: Society of Petroleum Engineers. doi: 10.2118/202271-ms

Parametric study of in-situ stresses in depleted reservoirs

Li, Zhonghui, Zhong, Ruizhi, Lou, Yishan, Lu, Jun and Ni, Yafei (2019). Parametric study of in-situ stresses in depleted reservoirs. International Conference and Exhibition on Computational Biology and Bioinformatics , Taipei, Taiwan, 1-2 December 2019. Chichester, West Sussex, United Kingdom: Wiley-Blackwell.

Using machine learning methods to identify coals from drilling and logging-while-drilling LWD data

Zhong, Ruizhi, Johnson Jr., Raymond L. and Chen, Zhongwei (2019). Using machine learning methods to identify coals from drilling and logging-while-drilling LWD data. SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, Brisbane, QLD, Australia, 18-19 November 2019. Tulsa, OK, United States: Unconventional Resources Technology Conference. doi: 10.15530/ap-urtec-2019-198288

Investigation of fracture reopening pressure in wellbore strengthening

Zhong, Ruizhi, Miska, Stefan, Yu, Mengjiao, Ozbayoglu, Evren and Takach, Nicholas (2018). Investigation of fracture reopening pressure in wellbore strengthening. IADC/SPE Drilling Conference and Exhibition, Fort Worth, TX United States, 6-8 March 2018. Richardson, TX United States: Society of Petroleum Engineers. doi: 10.2118/189575-ms

Well trajectory, completion and fracture design changes improve execution for deep unconventional tight gas targets in the cooper basin, Australia

Johnson, Raymond L., Zhong, Ruizhi and Nguyen, Lan (2018). Well trajectory, completion and fracture design changes improve execution for deep unconventional tight gas targets in the cooper basin, Australia. SPE Hydraulic Fracturing Technology Conference and Exhibition 2019, HFTC 2019, The Woodlands, TX United States, 5 - 7 February 2019. Society of Petroleum Engineers. doi: 10.2118/194366-MS

A leak-off model for critical permeability in wellbore strengthening applications

Zhong, Ruizhi, Miska, Stefan, Yu, Mengjiao, Ozbayoglu, Evren, Zhang, Jianguo and Majidi, Reza (2017). A leak-off model for critical permeability in wellbore strengthening applications. AADE National Technical Conference and Exhibition, Houston, TX, United States, 11-12 April 2017.

Numerical modeling of land subsidence resulting from oil production

Zhang, S., Zhong, R. and Liu, Y. (2016). Numerical modeling of land subsidence resulting from oil production. 50th US Rock Mechanics / Geomechanics Symposium 2016, Houston, TX, United States, June 26-June 29 2016. American Rock Mechanics Association (ARMA).

Fully coupled finite element model to study fault reactivation during multiple hydraulic fracturing in heterogeneous tight formations

Zhong, Ruizhi, Bao, Jinqing and Fathi, Ebrahim (2014). Fully coupled finite element model to study fault reactivation during multiple hydraulic fracturing in heterogeneous tight formations. SPE Eastern Regional Meeting, SPE Eastern Regional Meeting, SPE Eastern Regional Meeting. Richardson, TX, USA: Society of Petroleum Engineers (SPE). doi: 10.2118/171035-ms

Microfluidic human blood plasma separation for lab on chip based heavy metal detections

Zhong, Ruizhi, Wu, Nianqiang and Liu, Yuxin (2012). Microfluidic human blood plasma separation for lab on chip based heavy metal detections. Sensors Based on Fluorescence, SERS, SPR, and Photoelectrochemistry, Boston MA, USA, 9-14 October 2011. doi: 10.1149/1.3697855