Yishan Lou
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Yishan Lou has a total of 26 co-authors. Here are the top co-authors by number of shared publications:
- Biao Yin
Sinopec Petroleum Engineering Technology Research Institute Co., Ltd., Beijing 102206, China
2 shared publications - Shanyong Liu
Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering, Yangtze University, Wuhan, China
2 shared publications - Xiaopeng Zhai
Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering, Yangtze University, Wuhan 430100, China
2 shared publications - Aoxiang Ke
School of Petroleum Engineering, Yangtze University, National Engineering Research Center for Oil & Gas Drilling and Completion Technology, Wuhan 430100, China
1 shared publication - Bailie Wu
CNOOC Research Institute Co., Ltd., Beijing 100028, China
1 shared publication - Biao Yin
School of Petroleum Engineering, Yangtze University, Wuhan, 430100, China
1 shared publication
Latest Publications
- Open Access
- 7 September 2024
- Published by MDPI AG in Journal of Marine Science and Engineering
- Vol. 12 (9) , 1582
Mechanisms of Proppant Transport in Rough Fractures of Offshore Unconventional Reservoirs: Shale and Tight Sandstone
After hydraulic fracturing, unconventional reservoirs frequently encounter challenges related to limited effective proppant support distance and suboptimal proppant placement. Due to the strong heterogeneity of offshore reservoirs, which causes varying fracture roughnesses depending on different lithologies, a systematic study of the relationship between roughness and proppant transport could optimize operational parameters. This study incorporates the box dimension method for fractal dimension analysis to quantify roughness in auto-correlated Gaussian distributed surfaces created by true triaxial tests. Combined with the numerical analysis of (computational fluid dynamics) CFD-DEM (discrete element method) for bidirectional coupling, the laws of proppant deposition and transport processes within fractures with different roughnesses are obtained through comparative verification simulations. The results show that for rougher fractures of shale, the proppants are transported farther, but at JRC_52, (joint roughness coefficient), where there may be plugging in curved areas, there is a risk of near-well blockages. Compared to the smooth model, fluctuations in JRC_28 (tight sandstone) drastically increase turbulent kinetic energy within the fracture, altering particle transport dynamics. Moreover, smaller proppants (d/w ≤ 0.3) exhibit better transport capacity due to gravity, but the conductivity of the proppant is limited when the particles are too small. A d/w of 0.4 is recommended to guarantee transport capacity and proppant efficiency near the well. Additionally, proppants injected sequentially from small to large in shale fractures offer optimal propping effects, and can take advantage of the better transport capacity of smaller proppants in rough fractures. The large proppant (d/w = 0.8) is primarily deposited by gravity and forms a sloping sand bed, which subsequently ensures the aperture of the fractures. This research provides a fresh perspective on the influence of fracture roughness on proppant transport in offshore unconventional reservoirs and offers valuable considerations for the order of proppant injection.
- 7 September 2024
- Published by MDPI AG in Journal of Marine Science and Engineering
- Vol. 12 (9) , 1582
Open AccessMechanisms of Proppant Transport in Rough Fractures of Offshore Unconventional Reservoirs: Shale and Tight Sandstone
After hydraulic fracturing, unconventional reservoirs frequently encounter challenges related to limited effective proppant support distance and suboptimal proppant placement. Due to the strong heterogeneity of offshore reservoirs, which causes varying fracture roughnesses depending on different lithologies, a systematic study of the relationship between roughness and proppant transport could optimize operational parameters. This study incorporates the box dimension method for fractal dimension analysis to quantify roughness in auto-correlated Gaussian distributed surfaces created by true triaxial tests. Combined with the numerical analysis of (computational fluid dynamics) CFD-DEM (discrete element method) for bidirectional coupling, the laws of proppant deposition and transport processes within fractures with different roughnesses are obtained through comparative verification simulations. The results show that for rougher fractures of shale, the proppants are transported farther, but at JRC_52, (joint roughness coefficient), where there may be plugging in curved areas, there is a risk of near-well blockages. Compared to the smooth model, fluctuations in JRC_28 (tight sandstone) drastically increase turbulent kinetic energy within the fracture, altering particle transport dynamics. Moreover, smaller proppants (d/w ≤ 0.3) exhibit better transport capacity due to gravity, but the conductivity of the proppant is limited when the particles are too small. A d/w of 0.4 is recommended to guarantee transport capacity and proppant efficiency near the well. Additionally, proppants injected sequentially from small to large in shale fractures offer optimal propping effects, and can take advantage of the better transport capacity of smaller proppants in rough fractures. The large proppant (d/w = 0.8) is primarily deposited by gravity and forms a sloping sand bed, which subsequently ensures the aperture of the fractures. This research provides a fresh perspective on the influence of fracture roughness on proppant transport in offshore unconventional reservoirs and offers valuable considerations for the order of proppant injection.
- Open Access
Development and Characterization of Thermoresponsive Smart Self-Adaptive Chitosan-Based Polymer for Wellbore Plugging
To meet the escalating demand for oil and gas exploration in microporous reservoirs, it has become increasingly crucial to develop high-performance plugging materials. Through free radical grafting polymerization technology, a carboxymethyl chitosan grafted poly (oligoethylene glycol) methyl ether methyl methacrylate acrylic acid copolymer (CCMMA) was successfully synthesized. The resulting CCMMA exhibited thermoresponsive self-assembling behavior. When the temperature was above its lower critical solution temperature (LCST), the nanomicelles began to aggregate, forming mesoporous aggregated structures. Additionally, the electrostatic repulsion of AA chains increased the value of LCST. By precisely adjusting the content of AA, the LCST of CCMMA could be raised from 84.7 to 122.9 °C. The rheology and filtration experiments revealed that when the temperature surpassed the switching point, CCMMA exhibited a noteworthy plugging effect on low-permeability cores. Furthermore, it could be partially released as the temperature decreased, exhibiting temperature-switchable and self-adaptive plugging properties. Meanwhile, CCMMA aggregates retained their reversibility, along with thermal thickening behavior in the pores. However, more detailed experiments and analysis are needed to validate these claims, such as a comprehensive study of the CCMMA copolymer’s physical properties, its interaction with the reservoir environment, and its performance under various conditions. Additionally, further studies are required to optimize its synthesis process and improve its efficiency as a plugging material for oil and gas recovery in microporous reservoirs.
Open AccessDevelopment and Characterization of Thermoresponsive Smart Self-Adaptive Chitosan-Based Polymer for Wellbore Plugging
To meet the escalating demand for oil and gas exploration in microporous reservoirs, it has become increasingly crucial to develop high-performance plugging materials. Through free radical grafting polymerization technology, a carboxymethyl chitosan grafted poly (oligoethylene glycol) methyl ether methyl methacrylate acrylic acid copolymer (CCMMA) was successfully synthesized. The resulting CCMMA exhibited thermoresponsive self-assembling behavior. When the temperature was above its lower critical solution temperature (LCST), the nanomicelles began to aggregate, forming mesoporous aggregated structures. Additionally, the electrostatic repulsion of AA chains increased the value of LCST. By precisely adjusting the content of AA, the LCST of CCMMA could be raised from 84.7 to 122.9 °C. The rheology and filtration experiments revealed that when the temperature surpassed the switching point, CCMMA exhibited a noteworthy plugging effect on low-permeability cores. Furthermore, it could be partially released as the temperature decreased, exhibiting temperature-switchable and self-adaptive plugging properties. Meanwhile, CCMMA aggregates retained their reversibility, along with thermal thickening behavior in the pores. However, more detailed experiments and analysis are needed to validate these claims, such as a comprehensive study of the CCMMA copolymer’s physical properties, its interaction with the reservoir environment, and its performance under various conditions. Additionally, further studies are required to optimize its synthesis process and improve its efficiency as a plugging material for oil and gas recovery in microporous reservoirs.
- Open Access
Study on Fracturing Parameters Optimization of Horizontal Wells in Low-Permeability Reservoirs in South China Sea
The oil and gas resources in the deep Paleogene system of the South China Sea are abundant. However, due to its poor reservoir physical properties and strong heterogeneity, the deep Paleogene system needs to be commercially exploited by hydraulic fracturing technology. In view of the challenges of offshore low-permeability reservoirs, large-scale fracturing is not allowed because of the limited operation sites and complex string structure. Taking the H oilfield in the South China Sea as the target, based on the concept of the integration of geologic and engineering techniques, parameters such as the number of fracturing stages and the fracture length were optimized by a numerical simulation, and a study on the slurry rate and fracturing scale was carried out based on the type of fracturing and the pipe string structure. The results show that multistage fracturing technology is available in low-permeability offshore oil fields. It is suggested to adopt networking fracturing technology with a “slick water + high slurry rate” framework. A higher rate is recommended, and the fracturing scale of each stage should be 50 m3 of the sands and 700 m3 of the fluids. This research provides a new model for offshore low-permeability oilfield development.
Open AccessStudy on Fracturing Parameters Optimization of Horizontal Wells in Low-Permeability Reservoirs in South China Sea
The oil and gas resources in the deep Paleogene system of the South China Sea are abundant. However, due to its poor reservoir physical properties and strong heterogeneity, the deep Paleogene system needs to be commercially exploited by hydraulic fracturing technology. In view of the challenges of offshore low-permeability reservoirs, large-scale fracturing is not allowed because of the limited operation sites and complex string structure. Taking the H oilfield in the South China Sea as the target, based on the concept of the integration of geologic and engineering techniques, parameters such as the number of fracturing stages and the fracture length were optimized by a numerical simulation, and a study on the slurry rate and fracturing scale was carried out based on the type of fracturing and the pipe string structure. The results show that multistage fracturing technology is available in low-permeability offshore oil fields. It is suggested to adopt networking fracturing technology with a “slick water + high slurry rate” framework. A higher rate is recommended, and the fracturing scale of each stage should be 50 m3 of the sands and 700 m3 of the fluids. This research provides a new model for offshore low-permeability oilfield development.
- Open Access
- 25 July 2023
- Published by Springer Nature in Journal of Petroleum Exploration and Production Technology
- Vol. 13 (11) , 2303-2314
Study of accelerated erosion of elbow-shaped connections with corrosion defects
- 25 July 2023
- Published by Springer Nature in Journal of Petroleum Exploration and Production Technology
- Vol. 13 (11) , 2303-2314
Open AccessStudy of accelerated erosion of elbow-shaped connections with corrosion defects
- Open Access
Prediction of Leakage Pressure in Fractured Carbonate Reservoirs Based on PSO-LSTM Neural Network
Shunbei Oilfield is a fractured carbonate reservoir with complex geological structures that are influenced by fault movements and prone to collapse and leak incidents. Precisely predicting leakage pressure is crucial for conducting fracturing operations in the later stages of production. However, current fracture-related leakage pressure prediction models mostly rely on statistical and mechanical methods, which require the consideration of factors such as fracture aperture and parameter selection, thereby leading to limitations in prediction efficiency and accuracy. To enhance the accuracy of reservoir leakage pressure prediction, this study leverages the advantages of artificial intelligence methods in dealing with complex nonlinear problems and proposes an optimized Long Short-Term Memory (LSTM) neural network prediction approach using the Particle Swarm Optimization (PSO) algorithm. Firstly, the Spearman correlation coefficient is used to evaluate the correlation between nine parameter features and leakage pressure. Subsequently, an LSTM network framework is constructed, and the PSO algorithm is applied to optimize its hyper-parameters, establishing an optimal model for leakage pressure prediction. Finally, the model’s performance is evaluated using the Coefficient of Determination (), Root Mean Squared Error (), and Mean Absolute Percentage Error (). The evaluation results demonstrate that the PSO-optimized LSTM model achieved an of 0.828, of 0.049, and of 3.2, all of which outperformed the original model. The optimized LSTM model showed an average accuracy approximately 12.8% higher than that of the single LSTM model, indicating its higher prediction accuracy. The verification results from multiple development wells in this block further confirmed that the deep learning model established in this study surpassed traditional methods in prediction accuracy. Consequently, this approach is beneficial for drilling engineers and decision-makers to plan drilling operations more effectively and achieve accurate risk avoidance during the drilling process.Open AccessPrediction of Leakage Pressure in Fractured Carbonate Reservoirs Based on PSO-LSTM Neural Network
Shunbei Oilfield is a fractured carbonate reservoir with complex geological structures that are influenced by fault movements and prone to collapse and leak incidents. Precisely predicting leakage pressure is crucial for conducting fracturing operations in the later stages of production. However, current fracture-related leakage pressure prediction models mostly rely on statistical and mechanical methods, which require the consideration of factors such as fracture aperture and parameter selection, thereby leading to limitations in prediction efficiency and accuracy. To enhance the accuracy of reservoir leakage pressure prediction, this study leverages the advantages of artificial intelligence methods in dealing with complex nonlinear problems and proposes an optimized Long Short-Term Memory (LSTM) neural network prediction approach using the Particle Swarm Optimization (PSO) algorithm. Firstly, the Spearman correlation coefficient is used to evaluate the correlation between nine parameter features and leakage pressure. Subsequently, an LSTM network framework is constructed, and the PSO algorithm is applied to optimize its hyper-parameters, establishing an optimal model for leakage pressure prediction. Finally, the model’s performance is evaluated using the Coefficient of Determination (), Root Mean Squared Error (), and Mean Absolute Percentage Error (). The evaluation results demonstrate that the PSO-optimized LSTM model achieved an of 0.828, of 0.049, and of 3.2, all of which outperformed the original model. The optimized LSTM model showed an average accuracy approximately 12.8% higher than that of the single LSTM model, indicating its higher prediction accuracy. The verification results from multiple development wells in this block further confirmed that the deep learning model established in this study surpassed traditional methods in prediction accuracy. Consequently, this approach is beneficial for drilling engineers and decision-makers to plan drilling operations more effectively and achieve accurate risk avoidance during the drilling process. - Open Access
- 25 August 2020
- Published by Hindawi Limited in Geofluids
- Vol. 2020, 1-10
Laboratory Investigation on Optimum Selection of a Sand Control Method for an Interbedded Sandstone and Mudstone Reservoir
It is critical to select an optimized sand control method for an interbedded sandstone and mudstone reservoir (ISMR) due to its serious sand production hazards. However, currently, most general sand control methods cannot meet the requirements of sand control in interbedded sandstone and mudstone reservoirs (e.g., Bohai Bay oil and gas fields from China). Ensuring efficiency of sand control and increasing the oil and gas production rate in this interbedded sandstone and mudstone become more and more important. In this paper, a multilayer rotatable sand control experimental device for the interbedded sandstone and mudstone reservoir was developed. A series of sand control experimental studies were conducted by using the proposed device. The net-to-gross ratio (NTG) and well inclinations are two major factors considered in the experimental analysis. In addition, a sensitivity analysis regarding formation particle size distribution (PSD), clay content, and mineral compositions is performed in the experiment under a moderate sand control mode. With systematic experimental test results in this work, combined with numerous existing sand control models, a set of optimum sand control design and the associated optimization template for ISMR were developed, which have been successfully applied in Bohai Bay. Field application results show that NTG and well inclination are two critical parameters in the design of sand control in ISMR. The optimal indexes of a sand control mode are determined as NTG of 0.4 and well inclination of 45. The introduction of these two key factors in sand control design broadens the application range of moderate sand production.
- 25 August 2020
- Published by Hindawi Limited in Geofluids
- Vol. 2020, 1-10
Open AccessLaboratory Investigation on Optimum Selection of a Sand Control Method for an Interbedded Sandstone and Mudstone Reservoir
It is critical to select an optimized sand control method for an interbedded sandstone and mudstone reservoir (ISMR) due to its serious sand production hazards. However, currently, most general sand control methods cannot meet the requirements of sand control in interbedded sandstone and mudstone reservoirs (e.g., Bohai Bay oil and gas fields from China). Ensuring efficiency of sand control and increasing the oil and gas production rate in this interbedded sandstone and mudstone become more and more important. In this paper, a multilayer rotatable sand control experimental device for the interbedded sandstone and mudstone reservoir was developed. A series of sand control experimental studies were conducted by using the proposed device. The net-to-gross ratio (NTG) and well inclinations are two major factors considered in the experimental analysis. In addition, a sensitivity analysis regarding formation particle size distribution (PSD), clay content, and mineral compositions is performed in the experiment under a moderate sand control mode. With systematic experimental test results in this work, combined with numerous existing sand control models, a set of optimum sand control design and the associated optimization template for ISMR were developed, which have been successfully applied in Bohai Bay. Field application results show that NTG and well inclination are two critical parameters in the design of sand control in ISMR. The optimal indexes of a sand control mode are determined as NTG of 0.4 and well inclination of 45. The introduction of these two key factors in sand control design broadens the application range of moderate sand production.
- 13 November 2012
- Published by American Society of Civil Engineers (ASCE)
- p. 920-926
The Influence of Drilling Parameters on Casing Wear in Ultra-Deep Directional Well
During the drilling of horizontal wells, extended reach directional wells and ultra-deep directional wells, there is always a long drilling period after the cementing of intermediate casing. The rotation, tripping, flexing by bit weight and transverse vibration of the drilling pipes causes casing wear during this period which lowers the internal pressure strength and the collapsing strength of casing. At a certain casing grade, the drilling parameters that affect casing wear mainly includes rotary speed, rate of penetration (ROP), mud density, mud type, and bottom hole assembly. Until now, quantitative influences of each important factor on casing wear have not been studied. The authors addressed this need by studying the XG-X well, and the results indicate that rotary speed and ROP affect e wear the most. The wear of the well's casing at different rotary speeds and different rates of penetration was computed and the relationship of ROP to rotary speed to wear shows that the parameters are controllable within a certain scope. The two drilling parameters can be rationally selected to reduce the wearing during the actual drilling process so as to lengthen casing life and oil well service life.
- 13 November 2012
- Published by American Society of Civil Engineers (ASCE)
- p. 920-926
The Influence of Drilling Parameters on Casing Wear in Ultra-Deep Directional Well
During the drilling of horizontal wells, extended reach directional wells and ultra-deep directional wells, there is always a long drilling period after the cementing of intermediate casing. The rotation, tripping, flexing by bit weight and transverse vibration of the drilling pipes causes casing wear during this period which lowers the internal pressure strength and the collapsing strength of casing. At a certain casing grade, the drilling parameters that affect casing wear mainly includes rotary speed, rate of penetration (ROP), mud density, mud type, and bottom hole assembly. Until now, quantitative influences of each important factor on casing wear have not been studied. The authors addressed this need by studying the XG-X well, and the results indicate that rotary speed and ROP affect e wear the most. The wear of the well's casing at different rotary speeds and different rates of penetration was computed and the relationship of ROP to rotary speed to wear shows that the parameters are controllable within a certain scope. The two drilling parameters can be rationally selected to reduce the wearing during the actual drilling process so as to lengthen casing life and oil well service life.