Jianli Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Jianli Liu has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Dong Yang
The School of Petroleum Engineering Yangtze University 430100 Wuhan Hubei China
2 shared publications - Hu Han
Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering, Yangtze University, Wuhan 430100, China
2 shared publications - Qiao Deng
School of Petroleum Engineering, Yangtze University, Wuhan 430100, China
2 shared publications - Daicheng Peng
Key Laboratory of Exploration Technologies for Oil and Gas Resource, Ministry of Education, Yangtze University, Wuhan, China
1 shared publication - Fangqing Wen
Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering, China Three Gorges University, Yichang, China
1 shared publication - Hao Geng
Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering, Yangtze University, Wuhan 430100, China
1 shared publication
Latest Publications
- Open Access
Research on Hole-Cleaning Technology Coupled with Prevention and Removal of Cuttings Bed
To address the critical challenges of severe fragmentation in cuttings, persistent cuttings bed accumulation, and abrupt friction torque increases during horizontal well drilling of Jurassic continental shale oil formations in J Block, Sichuan Basin—rooted in the unique high clay content that induces colloidal stability of fine cuttings and resistance to conventional cleaning—this study innovatively proposes a coupled prevention–removal hole-cleaning technology. The core methodology integrates three synergistic components: (1) orthogonal numerical simulations to optimize drilling parameters, reducing the cuttings input rate by 43.48% through “hydraulic carrying + mechanical agitation” synergy; (2) a modified Moore model with horizontal section correction factors to quantify slip velocity of cuttings, lowering the prediction error from ±20% to ±5%; and (3) a helical groove cutting removal sub with 60 m optimal spacing, enhancing local turbulence intensity by 42% to disrupt residual cuttings bed. Field validation in Well J110-8-1H demonstrated remarkable improvements: a 50% reduction in sliding friction, a 25% decrease in rotational torque, and 40% shortening of the drilling cycle. This integrated technology fills the gap in addressing the “fragmentation–colloidal stability” dilemma in shale with high clay contents, providing a quantifiable solution for safe and efficient drilling in similar continental formations.
Open AccessResearch on Hole-Cleaning Technology Coupled with Prevention and Removal of Cuttings Bed
To address the critical challenges of severe fragmentation in cuttings, persistent cuttings bed accumulation, and abrupt friction torque increases during horizontal well drilling of Jurassic continental shale oil formations in J Block, Sichuan Basin—rooted in the unique high clay content that induces colloidal stability of fine cuttings and resistance to conventional cleaning—this study innovatively proposes a coupled prevention–removal hole-cleaning technology. The core methodology integrates three synergistic components: (1) orthogonal numerical simulations to optimize drilling parameters, reducing the cuttings input rate by 43.48% through “hydraulic carrying + mechanical agitation” synergy; (2) a modified Moore model with horizontal section correction factors to quantify slip velocity of cuttings, lowering the prediction error from ±20% to ±5%; and (3) a helical groove cutting removal sub with 60 m optimal spacing, enhancing local turbulence intensity by 42% to disrupt residual cuttings bed. Field validation in Well J110-8-1H demonstrated remarkable improvements: a 50% reduction in sliding friction, a 25% decrease in rotational torque, and 40% shortening of the drilling cycle. This integrated technology fills the gap in addressing the “fragmentation–colloidal stability” dilemma in shale with high clay contents, providing a quantifiable solution for safe and efficient drilling in similar continental formations.
- Open Access
Temperature Prediction Model for Horizontal Shale Gas Wells Considering Stress Sensitivity
In the production process of horizontal wells, wellbore temperature data play a critical role in predicting shale gas production. This study proposes a coupled thermo-hydro-mechanical (THM) mathematical model that accounts for the influence of the stress field when determining the distribution of wellbore temperature. The model integrates the effects of heat transfer in the temperature field, gas transport in the seepage field, and the mechanical deformation of shale induced by the stress field. The coupled model is solved using the finite difference method. The model was validated against field data from shale gas production, and sensitivity analyses were conducted on seven key parameters related to the stress field. The findings indicate that the stress field exerts an influence on both the wellbore temperature distribution and the total gas production. Neglecting the stress field effects may lead to an overestimation of shale gas production by up to 12.9%. Further analysis reveals that reservoir porosity and Langmuir volume are positively correlated with wellbore temperature, while permeability, Young’s modulus, Langmuir pressure, the coefficient of thermal expansion, and adsorption strain are negatively correlated with wellbore temperature.
Open AccessTemperature Prediction Model for Horizontal Shale Gas Wells Considering Stress Sensitivity
In the production process of horizontal wells, wellbore temperature data play a critical role in predicting shale gas production. This study proposes a coupled thermo-hydro-mechanical (THM) mathematical model that accounts for the influence of the stress field when determining the distribution of wellbore temperature. The model integrates the effects of heat transfer in the temperature field, gas transport in the seepage field, and the mechanical deformation of shale induced by the stress field. The coupled model is solved using the finite difference method. The model was validated against field data from shale gas production, and sensitivity analyses were conducted on seven key parameters related to the stress field. The findings indicate that the stress field exerts an influence on both the wellbore temperature distribution and the total gas production. Neglecting the stress field effects may lead to an overestimation of shale gas production by up to 12.9%. Further analysis reveals that reservoir porosity and Langmuir volume are positively correlated with wellbore temperature, while permeability, Young’s modulus, Langmuir pressure, the coefficient of thermal expansion, and adsorption strain are negatively correlated with wellbore temperature.