Continental shale oil reservoirs,characterized by numerous bedding planes and micro-nano scale pores,feature significantly higher stress sensitivity compared to other types of reservoirs.However,research on suitable s...Continental shale oil reservoirs,characterized by numerous bedding planes and micro-nano scale pores,feature significantly higher stress sensitivity compared to other types of reservoirs.However,research on suitable stress sensitivity characterization models is still limited.In this study,three commonly used stress sensitivity models for shale oil reservoirs were considered,and experiments on representative core samples were conducted.By fitting and comparing the data,the“exponential model”was identified as a characterization model that accurately represents stress sensitivity in continental shale oil reservoirs.To validate the accuracy of the model,a two-phase seepage mathematical model for shale oil reservoirs coupled with the exponential model was introduced.The model was discretely solved using the finite volume method,and its accuracy was verified through the commercial simulator CMG.The study evaluated the productivity of a typical horizontal well under different engineering,geological,and fracture conditions.The results indicate that considering stress sensitivity leads to a 13.57%reduction in production for the same matrix permeability.Additionally,as the fracture half-length and the number of fractures increase,and the bottomhole flowing pressure decreases,the reservoir stress sensitivity becomes higher.展开更多
The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics,engineering quality,and well conditions.These relationships,nonlinea...The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics,engineering quality,and well conditions.These relationships,nonlinear in nature,pose challenges for accurate description through physical models.While field data provides insights into real-world effects,its limited volume and quality restrict its utility.Complementing this,numerical simulation models offer effective support.To harness the strengths of both data-driven and model-driven approaches,this study established a shale oil production capacity prediction model based on a machine learning combination model.Leveraging fracturing development data from 236 wells in the field,a data-driven method employing the random forest algorithm is implemented to identify the main controlling factors for different types of shale oil reservoirs.Through the combination model integrating support vector machine(SVM)algorithm and back propagation neural network(BPNN),a model-driven shale oil production capacity prediction model is developed,capable of swiftly responding to shale oil development performance under varying geological,fluid,and well conditions.The results of numerical experiments show that the proposed method demonstrates a notable enhancement in R2 by 22.5%and 5.8%compared to singular machine learning models like SVM and BPNN,showcasing its superior precision in predicting shale oil production capacity across diverse datasets.展开更多
After steam discharge in heavy oil reservoirs,the distribution of temperature,pressure,and permeability in different wells becomes irregular.Flow channels can easily be produced,which affect the sweep efficiency of th...After steam discharge in heavy oil reservoirs,the distribution of temperature,pressure,and permeability in different wells becomes irregular.Flow channels can easily be produced,which affect the sweep efficiency of the oil displacement.Previous studies have shown that the salting-out plugging method can effectively block these channels in high-temperature reservoirs,improve the suction profile,and increase oil production.In the present study,the optimal dosage of the plugging agent is determined taking into account connection transmissibility and inter-well volumes.Together with the connectivity model,a water flooding simulation model is introduced.Moreover,a non-gradient stochastic disturbance algorithm is used to obtain the optimal plugging agent dosage,which provides the basis for the high-temperature salting-out plugging agent adjustment in the field.展开更多
A mathematical model for the gas-water two-phase flow in tight gas reservoirs is elaborated.The model can account for the gas slip effect,stress sensitivity,and high-speed non-Darcy factors.The related equations are s...A mathematical model for the gas-water two-phase flow in tight gas reservoirs is elaborated.The model can account for the gas slip effect,stress sensitivity,and high-speed non-Darcy factors.The related equations are solved in the framework of a finite element method.The results are validated against those obtained by using the commercial software CMG(Computer Modeling Group software for advanced recovery process simulation).It is shown that the proposed method is reliable.It can capture the fracture rejection characteristics of tight gas reservoirs better than the CMG.A sensitivity analysis of various control factors(initial water saturation,reservoir parameters,and fracturing parameters)affecting the production in tight gas wells is conducted accordingly.Finally,a series of theoretical arguments are provided for a rational and effective development/exploitation of tight sandstone gas reservoirs.展开更多
The response of an adjustable critical-flow Venturi nozzle is investigated through a set indoor experiments aimed to determine the related critical flow rate,critical pressure ratio,and discharge coefficient.The effec...The response of an adjustable critical-flow Venturi nozzle is investigated through a set indoor experiments aimed to determine the related critical flow rate,critical pressure ratio,and discharge coefficient.The effect of a variation in the cone displacement and liquid content on the critical flow characteristics is examined in detail and it is shown that the former can be used to effectively adjust the critical flow rate.The critical pressure ratio of the considered nozzle is above 0.85,and the critical flow control deviation of the gas flow is within±3%.Liquid flow can reduce the gas critical mass flow rate accordingly,especially for the cases with larger liquid volume and lower inlet pressure.The set of results and conclusions provided are intended to support the optimization of steam injection techniques in the context of heavy oil recovery processes.展开更多
The mechanically choked orifice plate (MCOP) is a new type of device for flow control by which choking conditionsfor incompressible fluids can be obtained with relatively small pressure losses. Given the lack of relev...The mechanically choked orifice plate (MCOP) is a new type of device for flow control by which choking conditionsfor incompressible fluids can be obtained with relatively small pressure losses. Given the lack of relevant results anddata in the literature, in the present study, we concentrate on the experimental determination of the flow coefficientfor the annular orifice, the pressure distribution in the MCOP, and the characteristics of the choked flow itself. Asconfirmed by the experimental results, the Reynolds number, the orifice plate thickness, the plug taper, and theeccentricity have an obvious influence on the aforementioned flow coefficient. The pressure drop in the MCOPis mainly generated near the orifice plate, and the pressure upstream of the orifice plate is slightly reduced in theflow direction, while the pressure downstream of the orifice plate displays a recovery trend. The choked flow rateof the MCOP can be adjusted by replacing the spring with a maximum flow control deviation of 4.91%.展开更多
A Smooth Particle Hydrodynamics(SPH)method is employed to simulate the two-phase flow of oil and water in a reservoir.It is shown that,in comparison to the classical finite difference approach,this method is more stab...A Smooth Particle Hydrodynamics(SPH)method is employed to simulate the two-phase flow of oil and water in a reservoir.It is shown that,in comparison to the classical finite difference approach,this method is more stable and effective at capturing the complex evolution of this category of two-phase flows.The influence of several smooth functions is explored and it is concluded that the Gaussian function is the best one.After 200 days,the block water cutoff for the Gaussian function is 0.3,whereas the other functions have a block water cutoff of 0.8.The effect of various injection ratios on real reservoir production is explored.When 14 and 8 m^(3)/day is employed,the water breakthrough time is 130 and 170 days,respectively,and the block produces 9246 m^(3) and 6338 m^(3) of oil cumulatively over 400 days.展开更多
Due to the difficulties associated with preprocessing activities and poor grid convergence when simulating shale reservoirs in the context of traditional grid methods,in this study an innovative two-phase oil-water se...Due to the difficulties associated with preprocessing activities and poor grid convergence when simulating shale reservoirs in the context of traditional grid methods,in this study an innovative two-phase oil-water seepage model is elaborated.The modes is based on the radial basis meshless approach and is used to determine the pressure and water saturation in a sample reservoir.Two-dimensional examples demonstrate that,when compared to the finite difference method,the radial basis function method produces less errors and is more accurate in predicting daily oil production.The radial basis function and finite difference methods provide errors of 5.78 percent and 7.5 percent,respectively,when estimating the daily oil production data for a sample well.A sensitivity analysis of the key parameters that affect the radial basis function’s computation outcomes is also presented.展开更多
The Chinese Loess Plateau has long been plagued by severe soil erosion and water scarcity.In this study,we proposed a technique involving the combined use of polymer SH and ryegrass and evaluated its effectiveness in ...The Chinese Loess Plateau has long been plagued by severe soil erosion and water scarcity.In this study,we proposed a technique involving the combined use of polymer SH and ryegrass and evaluated its effectiveness in modifying the water-holding characteristics of loess on the Chinese Loess Plateau(Chinese loess).We analysed the volumetric water content and water potential of untreated loess,treated loess with single polymer SH,treated loess with single ryegrass,and treated loess with both polymer SH and ryegrass using the loess samples collected from the Chinese Loess Plateau in July 2023.Moreover,fractal theory was used to analyse the fractal characteristics of the soil structure,and wet disintegration tests were conducted to assess the structural stability of both untreated and treated loess samples.The results showed that the loess samples treated with both polymer SH and ryegrass presented much higher volumetric water content and water potential than the untreated loess samples and those treated only with ryegrass or polymer SH.Moreover,the planting density of ryegrass affected the combined technique,since a relatively low planting density(20 g/m2)was conducive to enhancing the water-holding capacity of Chinese loess.The fractal dimension was directly correlated with both volumetric water content and water potential of Chinese loess.Specifically,since loess treated with both polymer SH and ryegrass was more saturated with moisture,its water potential increased,thus improving its water-holding capacity and fractal dimension.The combined technique better resisted disintegration than ryegrass alone but had slightly less resistance than polymer SH alone.This study provides insight into soil reinforcement and soil water management using polymetric materials and vegetation on the Chinese Loess Plateau.展开更多
基金supported by the China Postdoctoral Science Foundation(2021M702304)Natural Science Foundation of Shandong Province(ZR2021QE260).
文摘Continental shale oil reservoirs,characterized by numerous bedding planes and micro-nano scale pores,feature significantly higher stress sensitivity compared to other types of reservoirs.However,research on suitable stress sensitivity characterization models is still limited.In this study,three commonly used stress sensitivity models for shale oil reservoirs were considered,and experiments on representative core samples were conducted.By fitting and comparing the data,the“exponential model”was identified as a characterization model that accurately represents stress sensitivity in continental shale oil reservoirs.To validate the accuracy of the model,a two-phase seepage mathematical model for shale oil reservoirs coupled with the exponential model was introduced.The model was discretely solved using the finite volume method,and its accuracy was verified through the commercial simulator CMG.The study evaluated the productivity of a typical horizontal well under different engineering,geological,and fracture conditions.The results indicate that considering stress sensitivity leads to a 13.57%reduction in production for the same matrix permeability.Additionally,as the fracture half-length and the number of fractures increase,and the bottomhole flowing pressure decreases,the reservoir stress sensitivity becomes higher.
基金supported by the China Postdoctoral Science Foundation(2021M702304)Natural Science Foundation of Shandong Province(ZR20210E260).
文摘The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics,engineering quality,and well conditions.These relationships,nonlinear in nature,pose challenges for accurate description through physical models.While field data provides insights into real-world effects,its limited volume and quality restrict its utility.Complementing this,numerical simulation models offer effective support.To harness the strengths of both data-driven and model-driven approaches,this study established a shale oil production capacity prediction model based on a machine learning combination model.Leveraging fracturing development data from 236 wells in the field,a data-driven method employing the random forest algorithm is implemented to identify the main controlling factors for different types of shale oil reservoirs.Through the combination model integrating support vector machine(SVM)algorithm and back propagation neural network(BPNN),a model-driven shale oil production capacity prediction model is developed,capable of swiftly responding to shale oil development performance under varying geological,fluid,and well conditions.The results of numerical experiments show that the proposed method demonstrates a notable enhancement in R2 by 22.5%and 5.8%compared to singular machine learning models like SVM and BPNN,showcasing its superior precision in predicting shale oil production capacity across diverse datasets.
基金supported by China Postdoctoral Science Foundation(No.2021M702304)Shandong Provincial Natural Science Foundation Youth Fund(No.ZR2021QE260).
文摘After steam discharge in heavy oil reservoirs,the distribution of temperature,pressure,and permeability in different wells becomes irregular.Flow channels can easily be produced,which affect the sweep efficiency of the oil displacement.Previous studies have shown that the salting-out plugging method can effectively block these channels in high-temperature reservoirs,improve the suction profile,and increase oil production.In the present study,the optimal dosage of the plugging agent is determined taking into account connection transmissibility and inter-well volumes.Together with the connectivity model,a water flooding simulation model is introduced.Moreover,a non-gradient stochastic disturbance algorithm is used to obtain the optimal plugging agent dosage,which provides the basis for the high-temperature salting-out plugging agent adjustment in the field.
基金supported by the China Postdoctoral Science Foundation(2021M702304)and Natural Science Foundation of Shandong Province(ZR2021QE260).
文摘A mathematical model for the gas-water two-phase flow in tight gas reservoirs is elaborated.The model can account for the gas slip effect,stress sensitivity,and high-speed non-Darcy factors.The related equations are solved in the framework of a finite element method.The results are validated against those obtained by using the commercial software CMG(Computer Modeling Group software for advanced recovery process simulation).It is shown that the proposed method is reliable.It can capture the fracture rejection characteristics of tight gas reservoirs better than the CMG.A sensitivity analysis of various control factors(initial water saturation,reservoir parameters,and fracturing parameters)affecting the production in tight gas wells is conducted accordingly.Finally,a series of theoretical arguments are provided for a rational and effective development/exploitation of tight sandstone gas reservoirs.
基金The authors would like to acknowledge the support provided by the National Natural Science Foundation of China(No.62173049)the open fund of the Key Laboratory of Exploration Technologies for Oil and Gas Resources(Yangtze University),Ministry of Education(Grant K2021-17).
文摘The response of an adjustable critical-flow Venturi nozzle is investigated through a set indoor experiments aimed to determine the related critical flow rate,critical pressure ratio,and discharge coefficient.The effect of a variation in the cone displacement and liquid content on the critical flow characteristics is examined in detail and it is shown that the former can be used to effectively adjust the critical flow rate.The critical pressure ratio of the considered nozzle is above 0.85,and the critical flow control deviation of the gas flow is within±3%.Liquid flow can reduce the gas critical mass flow rate accordingly,especially for the cases with larger liquid volume and lower inlet pressure.The set of results and conclusions provided are intended to support the optimization of steam injection techniques in the context of heavy oil recovery processes.
基金the Foundation of the Educational Commission of Hubei Province of China[Grant No.Q20191310]。
文摘The mechanically choked orifice plate (MCOP) is a new type of device for flow control by which choking conditionsfor incompressible fluids can be obtained with relatively small pressure losses. Given the lack of relevant results anddata in the literature, in the present study, we concentrate on the experimental determination of the flow coefficientfor the annular orifice, the pressure distribution in the MCOP, and the characteristics of the choked flow itself. Asconfirmed by the experimental results, the Reynolds number, the orifice plate thickness, the plug taper, and theeccentricity have an obvious influence on the aforementioned flow coefficient. The pressure drop in the MCOPis mainly generated near the orifice plate, and the pressure upstream of the orifice plate is slightly reduced in theflow direction, while the pressure downstream of the orifice plate displays a recovery trend. The choked flow rateof the MCOP can be adjusted by replacing the spring with a maximum flow control deviation of 4.91%.
基金This work was supported by The China Postdoctoral Science Foundation(2021M702304)Natural Science Foundation of Shandong Province(ZR2021QE260).
文摘A Smooth Particle Hydrodynamics(SPH)method is employed to simulate the two-phase flow of oil and water in a reservoir.It is shown that,in comparison to the classical finite difference approach,this method is more stable and effective at capturing the complex evolution of this category of two-phase flows.The influence of several smooth functions is explored and it is concluded that the Gaussian function is the best one.After 200 days,the block water cutoff for the Gaussian function is 0.3,whereas the other functions have a block water cutoff of 0.8.The effect of various injection ratios on real reservoir production is explored.When 14 and 8 m^(3)/day is employed,the water breakthrough time is 130 and 170 days,respectively,and the block produces 9246 m^(3) and 6338 m^(3) of oil cumulatively over 400 days.
基金supported by The China Postdoctoral Science Foundation(2021M702304)Natural Science Foundation of Shandong Province(ZR2021QE260).
文摘Due to the difficulties associated with preprocessing activities and poor grid convergence when simulating shale reservoirs in the context of traditional grid methods,in this study an innovative two-phase oil-water seepage model is elaborated.The modes is based on the radial basis meshless approach and is used to determine the pressure and water saturation in a sample reservoir.Two-dimensional examples demonstrate that,when compared to the finite difference method,the radial basis function method produces less errors and is more accurate in predicting daily oil production.The radial basis function and finite difference methods provide errors of 5.78 percent and 7.5 percent,respectively,when estimating the daily oil production data for a sample well.A sensitivity analysis of the key parameters that affect the radial basis function’s computation outcomes is also presented.
基金supported by the Natural Science Foundation of Qinghai Province(2024-ZJ-987)the Natural Science Foundation of Qinghai University(2023-QGY-9).
文摘The Chinese Loess Plateau has long been plagued by severe soil erosion and water scarcity.In this study,we proposed a technique involving the combined use of polymer SH and ryegrass and evaluated its effectiveness in modifying the water-holding characteristics of loess on the Chinese Loess Plateau(Chinese loess).We analysed the volumetric water content and water potential of untreated loess,treated loess with single polymer SH,treated loess with single ryegrass,and treated loess with both polymer SH and ryegrass using the loess samples collected from the Chinese Loess Plateau in July 2023.Moreover,fractal theory was used to analyse the fractal characteristics of the soil structure,and wet disintegration tests were conducted to assess the structural stability of both untreated and treated loess samples.The results showed that the loess samples treated with both polymer SH and ryegrass presented much higher volumetric water content and water potential than the untreated loess samples and those treated only with ryegrass or polymer SH.Moreover,the planting density of ryegrass affected the combined technique,since a relatively low planting density(20 g/m2)was conducive to enhancing the water-holding capacity of Chinese loess.The fractal dimension was directly correlated with both volumetric water content and water potential of Chinese loess.Specifically,since loess treated with both polymer SH and ryegrass was more saturated with moisture,its water potential increased,thus improving its water-holding capacity and fractal dimension.The combined technique better resisted disintegration than ryegrass alone but had slightly less resistance than polymer SH alone.This study provides insight into soil reinforcement and soil water management using polymetric materials and vegetation on the Chinese Loess Plateau.
