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
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
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
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 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
Clarifying the pore structure characteristics of shale reservoirs,which are low porosity,low permeability and high heterogeneity,is an essential prerequisite for the efficient development of shale oil and gas.Fractal ...Clarifying the pore structure characteristics of shale reservoirs,which are low porosity,low permeability and high heterogeneity,is an essential prerequisite for the efficient development of shale oil and gas.Fractal theory is especially suited for characterizing the complex pore structures of shales.This work compares the pore structure characteristics between marine shales from the Longmaxi Formation and continental shales from the Shahejie Formation through low-temperature nitrogen adsorption,nuclear magnetic resonance,and scanning electron microscopy.Different fractal scaling models are adopted to determine the fractal dimensions and lacunarities of shales by low-temperature nitrogen adsorption data and scanning electron microscopy images.In addition,the mineral compositions from X-ray diffraction are analyzed to elucidate the mechanisms by which mineral content influences fractal dimensions.Finally,the correlations between total organic carbon content and microscopic structure are discussed.These results indicate that the pore size of marine shale is smaller than that of continental shale.Additionally,the fractal dimensions of marine shales are greater than that of continental shales,suggesting a more complex pore structure.The more quartz and clay content lead to greater complexity in pore space,resulting in higher fractal dimensions.The illite/smectite mixed layer shows a strong positive correlation with fractal dimensions for marine shales,whereas this correlation is less pronounced for continental shales.The presence of microfractures in organic matter leads to a reduction for the pore surface fractal dimension in continental shales.展开更多
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)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)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 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 the National Natural Science Foundation of China(Grant Nos.42172159,42302143,and 52404048).
文摘Clarifying the pore structure characteristics of shale reservoirs,which are low porosity,low permeability and high heterogeneity,is an essential prerequisite for the efficient development of shale oil and gas.Fractal theory is especially suited for characterizing the complex pore structures of shales.This work compares the pore structure characteristics between marine shales from the Longmaxi Formation and continental shales from the Shahejie Formation through low-temperature nitrogen adsorption,nuclear magnetic resonance,and scanning electron microscopy.Different fractal scaling models are adopted to determine the fractal dimensions and lacunarities of shales by low-temperature nitrogen adsorption data and scanning electron microscopy images.In addition,the mineral compositions from X-ray diffraction are analyzed to elucidate the mechanisms by which mineral content influences fractal dimensions.Finally,the correlations between total organic carbon content and microscopic structure are discussed.These results indicate that the pore size of marine shale is smaller than that of continental shale.Additionally,the fractal dimensions of marine shales are greater than that of continental shales,suggesting a more complex pore structure.The more quartz and clay content lead to greater complexity in pore space,resulting in higher fractal dimensions.The illite/smectite mixed layer shows a strong positive correlation with fractal dimensions for marine shales,whereas this correlation is less pronounced for continental shales.The presence of microfractures in organic matter leads to a reduction for the pore surface fractal dimension in continental shales.
