Jiali Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Jiali Wang has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Long Chen
Oil and Gas Technology Research Institute, PetroChina Southwest Oil & Gasfield Company, Chengdu 610017, China
2 shared publications - Yunhai Zhao
Oil and Gas Technology Research Institute, PetroChina Southwest Oil & Gasfield Company, Chengdu 610017, China
2 shared publications - Chi Zhao
National Engineering Research Center for Oil & Gas Drilling and Completion Technology, Yangtze University, Wuhan 430100, China
1 shared publication - Hui Mao
College of Energy (College of Modern Shale Gas Industry), Chengdu University of Technology, Chengdu 610059, China
1 shared publication - Jian Yang
Oil and Gas Technology Research Institute, PetroChina Southwest Oil & Gasfield Company, Chengdu 610017, China
1 shared publication - Jiayin Zhang
PetroChina Southwest Oil and Gas Field Oil and Gas Process Research Institute, Chengdu 610017, China
1 shared publication
Latest Publications
- Open Access
Cross-Geometry Flow-Field Prediction in Irregular Wellbores Using Parameterized Physics-Informed Neural Networks
Irregular borehole enlargement alters annular flow structures and can create low-velocity regions that impair hole cleaning. However, conventional computational fluid dynamics (CFD) requires repeated geometric reconstruction and numerical simulations for each wellbore configuration, while existing physics-informed models have limited capability for cross-geometry extrapolation. This study develops transfer-learning-based parameterized physics-informed neural networks (TLP-PINNs) for the rapid three-dimensional prediction of Herschel–Bulkley drilling-fluid flow in locally enlarged irregular wellbores. A Gaussian enlargement ratio is introduced as an explicit geometric input, while mass and momentum conservation equations, boundary conditions, adaptive loss weighting, extrapolation-distance-driven physics-point allocation, and partial-layer transfer learning are integrated into a unified framework. The source model generally maintains good in-range interpolation accuracy for the velocity field within the 10–50% enlargement range, although the pressure error shows greater case-to-case variability for unseen intermediate geometries. For the unseen 80% enlargement case, transfer learning reduces the relative RMSEs of axial velocity, velocity magnitude, and pressure from 14.0%, 13.5%, and 3.5% to 9.42%, 9.50%, and 1.34%, respectively, with corresponding of 0.9668, 0.9663, and 0.9992. The transferred model also accurately captures the low-velocity zone within the enlarged section and the associated redistribution of the local pressure gradient, while reducing neural-network training time by 51.2% relative to full-domain retraining. These results demonstrate a practical cross-geometry framework for the rapid hydraulic assessment of irregular wellbores and provide detailed flow-field information for subsequent analyses of hole cleaning and particle transport.Open AccessCross-Geometry Flow-Field Prediction in Irregular Wellbores Using Parameterized Physics-Informed Neural Networks
Irregular borehole enlargement alters annular flow structures and can create low-velocity regions that impair hole cleaning. However, conventional computational fluid dynamics (CFD) requires repeated geometric reconstruction and numerical simulations for each wellbore configuration, while existing physics-informed models have limited capability for cross-geometry extrapolation. This study develops transfer-learning-based parameterized physics-informed neural networks (TLP-PINNs) for the rapid three-dimensional prediction of Herschel–Bulkley drilling-fluid flow in locally enlarged irregular wellbores. A Gaussian enlargement ratio is introduced as an explicit geometric input, while mass and momentum conservation equations, boundary conditions, adaptive loss weighting, extrapolation-distance-driven physics-point allocation, and partial-layer transfer learning are integrated into a unified framework. The source model generally maintains good in-range interpolation accuracy for the velocity field within the 10–50% enlargement range, although the pressure error shows greater case-to-case variability for unseen intermediate geometries. For the unseen 80% enlargement case, transfer learning reduces the relative RMSEs of axial velocity, velocity magnitude, and pressure from 14.0%, 13.5%, and 3.5% to 9.42%, 9.50%, and 1.34%, respectively, with corresponding of 0.9668, 0.9663, and 0.9992. The transferred model also accurately captures the low-velocity zone within the enlarged section and the associated redistribution of the local pressure gradient, while reducing neural-network training time by 51.2% relative to full-domain retraining. These results demonstrate a practical cross-geometry framework for the rapid hydraulic assessment of irregular wellbores and provide detailed flow-field information for subsequent analyses of hole cleaning and particle transport. - Open Access
Development and Application of Nano-Micro Sealant for Water-Based Drilling Fluids in Deep Shale Gas Formations of the Sichuan-Chongqing Region
To address wellbore instability and the technical challenges associated with high-density water-based drilling fluid loss control in deep shale gas formations of the Sichuan-Chongqing region in China, a novel nano-micro sealant designated CLG-Seal was synthesized via molecular structural optimization. The molecular structure of newly developed CLG-Seal exhibits distinct core–shell structural characteristics. The inorganic nano-silica constitutes the rigid core of CLG-Seal, which guarantees its plugging performance. The hydrophobically associating polymer which is coated on the surface of nano-silica constructs the flexible shell of CLG-Seal, endowing the CLG-Seal with excellent gel-forming capacity, adhesion film-forming capacity, deformability and perfect dispersibility. Transmission electron microscopy and scanning electron microscopy were employed to characterize the morphology of the CLG-Seal nanomicron-scale plugging agent. The sealing performance and underlying mechanisms of CLG-Seal were subsequently evaluated via particle plugging apparatus tests, displacement experiments, and etched glass micromodel simulations. Field trials conducted in the third section of Well WY3-2-3HF validated the application effectiveness of this agent in drilling fluid systems. The results indicate that the nano-micro sealant CLG-Seal exhibits a median particle size of D50 is 146 nm, which can be modulated by adjusting the synthesis conditions. The nano-micro sealant CLG-Seal significantly mitigates fluid loss in low-permeability microfractures and fissures. Notably, a concentration of merely 3% is sufficient to achieve optimal nano-micro plugging performance. The results of the mechanism study indicate that while the CLG-Seal particles are close to each other, the polymer chains with flexible long chain structure which are coated on the surface of nano-silica constructs tend to be intertwined, forming a cross-linked network structure of gel film, thereby increasing the interaction between nano-micron particles and forming an impermeable plugging film. In addition, due to the nanoscale effect, the CLG-Seal has a strong tendency to adsorb onto the surface of shale rock through hydrogen bonding with the shale matrix. The hydrophobically associating polymer with high elastic modulus and excellent mechanical properties can enhance the pressure-bearing capacity of the filter cake through elastic deformation. Therefore, these nano-micron particles can form a strong sealing film on the filter cake and at the micropores of shale rock, thereby creating a dense mud cake on the outside of the shale formation. Field trial results demonstrate that the incorporation of the nano-micro sealant CLG-Seal into the drilling fluid for the third section of Well WY3-2-3HF reduced the PPA fluid loss to 4.6 mL. This value represents a substantial reduction compared to adjacent wells and signifies a remarkable improvement over the drilling fluids previously employed in the Longmaxi Formation of this block. Furthermore, the treated drilling fluid exhibited a superior filtration control pressure capacity of 10.5 MPa. The operation was completed successfully without any lost circulation or wellbore instability, and achieved a drilling footage of 42 h with an average penetration rate of 7.81 m/h. The mud weight was reduced by approximately 0.08–0.10 g/cm3 compared to offset wells. These results confirm the excellent application efficiency of the newly developed CLG-Seal in field operations.
Open AccessDevelopment and Application of Nano-Micro Sealant for Water-Based Drilling Fluids in Deep Shale Gas Formations of the Sichuan-Chongqing Region
To address wellbore instability and the technical challenges associated with high-density water-based drilling fluid loss control in deep shale gas formations of the Sichuan-Chongqing region in China, a novel nano-micro sealant designated CLG-Seal was synthesized via molecular structural optimization. The molecular structure of newly developed CLG-Seal exhibits distinct core–shell structural characteristics. The inorganic nano-silica constitutes the rigid core of CLG-Seal, which guarantees its plugging performance. The hydrophobically associating polymer which is coated on the surface of nano-silica constructs the flexible shell of CLG-Seal, endowing the CLG-Seal with excellent gel-forming capacity, adhesion film-forming capacity, deformability and perfect dispersibility. Transmission electron microscopy and scanning electron microscopy were employed to characterize the morphology of the CLG-Seal nanomicron-scale plugging agent. The sealing performance and underlying mechanisms of CLG-Seal were subsequently evaluated via particle plugging apparatus tests, displacement experiments, and etched glass micromodel simulations. Field trials conducted in the third section of Well WY3-2-3HF validated the application effectiveness of this agent in drilling fluid systems. The results indicate that the nano-micro sealant CLG-Seal exhibits a median particle size of D50 is 146 nm, which can be modulated by adjusting the synthesis conditions. The nano-micro sealant CLG-Seal significantly mitigates fluid loss in low-permeability microfractures and fissures. Notably, a concentration of merely 3% is sufficient to achieve optimal nano-micro plugging performance. The results of the mechanism study indicate that while the CLG-Seal particles are close to each other, the polymer chains with flexible long chain structure which are coated on the surface of nano-silica constructs tend to be intertwined, forming a cross-linked network structure of gel film, thereby increasing the interaction between nano-micron particles and forming an impermeable plugging film. In addition, due to the nanoscale effect, the CLG-Seal has a strong tendency to adsorb onto the surface of shale rock through hydrogen bonding with the shale matrix. The hydrophobically associating polymer with high elastic modulus and excellent mechanical properties can enhance the pressure-bearing capacity of the filter cake through elastic deformation. Therefore, these nano-micron particles can form a strong sealing film on the filter cake and at the micropores of shale rock, thereby creating a dense mud cake on the outside of the shale formation. Field trial results demonstrate that the incorporation of the nano-micro sealant CLG-Seal into the drilling fluid for the third section of Well WY3-2-3HF reduced the PPA fluid loss to 4.6 mL. This value represents a substantial reduction compared to adjacent wells and signifies a remarkable improvement over the drilling fluids previously employed in the Longmaxi Formation of this block. Furthermore, the treated drilling fluid exhibited a superior filtration control pressure capacity of 10.5 MPa. The operation was completed successfully without any lost circulation or wellbore instability, and achieved a drilling footage of 42 h with an average penetration rate of 7.81 m/h. The mud weight was reduced by approximately 0.08–0.10 g/cm3 compared to offset wells. These results confirm the excellent application efficiency of the newly developed CLG-Seal in field operations.