Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing researc...Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing research suggests that the effectiveness of a surrogate model can vary depending on the complexity of the design problem.A surrogate model that has demonstrated success in one scenario may not perform as well in others.In the absence of prior knowledge,finding a promising surrogate model that performs well for an unknown reservoir is challenging.Moreover,the optimization process often relies on a single evolutionary algorithm,which can yield varying results across different cases.To address these limitations,this paper introduces a novel approach called the multi-surrogate framework with an adaptive selection mechanism(MSFASM)to tackle production optimization problems.MSFASM consists of two stages.In the first stage,a reduced-dimensional broad learning system(BLS)is used to adaptively select the evolutionary algorithm with the best performance during the current optimization period.In the second stage,the multi-objective algorithm,non-dominated sorting genetic algorithm II(NSGA-II),is used as an optimizer to find a set of Pareto solutions with good performance on multiple surrogate models.A novel optimal point criterion is utilized in this stage to select the Pareto solutions,thereby obtaining the desired development schemes without increasing the computational load of the numerical simulator.The two stages are combined using sequential transfer learning.From the two most important perspectives of an evolutionary algorithm and a surrogate model,the proposed method improves adaptability to optimization problems of various reservoir types.To verify the effectiveness of the proposed method,four 100-dimensional benchmark functions and two reservoir models are tested,and the results are compared with those obtained by six other surrogate-model-based methods.The results demonstrate that our approach can obtain the maximum net present value(NPV)of the target production optimization problems.展开更多
The phase behavior of gas condensate in reservoir formations differs from that in pressure-volume-temperature(PVT)cells because it is influenced by porous media in the reservoir formations.Sandstone was used as a samp...The phase behavior of gas condensate in reservoir formations differs from that in pressure-volume-temperature(PVT)cells because it is influenced by porous media in the reservoir formations.Sandstone was used as a sample to investigate the influence of porous media on the phase behavior of the gas condensate.The pore structure was first analyzed using computed tomography(CT)scanning,digital core technology,and a pore network model.The sandstone core sample was then saturated with gas condensate for the pressure depletion experiment.After each pressure-depletion state was stable,realtime CT scanning was performed on the sample.The scanning results of the sample were reconstructed into three-dimensional grayscale images,and the gas condensate and condensate liquid were segmented based on gray value discrepancy to dynamically characterize the phase behavior of the gas condensate in porous media.Pore network models of the condensate liquid ganglia under different pressures were built to calculate the characteristic parameters,including the average radius,coordination number,and tortuosity,and to analyze the changing mechanism caused by the phase behavior change of the gas condensate.Four types of condensate liquid(clustered,branched,membranous,and droplet ganglia)were then classified by shape factor and Euler number to investigate their morphological changes dynamically and elaborately.The results show that the dew point pressure of the gas condensate in porous media is 12.7 MPa,which is 0.7 MPa higher than 12.0 MPa in PVT cells.The average radius,volume,and coordination number of the condensate liquid ganglia increased when the system pressure was between the dew point pressure(12.7 MPa)and the pressure for the maximum liquid dropout,Pmax(10.0 MPa),and decreased when it was below Pmax.The volume proportion of clustered ganglia was the highest,followed by branched,membranous,and droplet ganglia.This study provides crucial experimental evidence for the phase behavior changing process of gas condensate in porous media during the depletion production of gas condensate reservoirs.展开更多
Neuronal apoptosis is mediated by intrinsic and extrinsic signaling pathways such as the membrane-mediated,mitochondrial,and endoplasmic reticulum stress pathways.Few studies have examined the endoplasmic reticulum-me...Neuronal apoptosis is mediated by intrinsic and extrinsic signaling pathways such as the membrane-mediated,mitochondrial,and endoplasmic reticulum stress pathways.Few studies have examined the endoplasmic reticulum-mediated apoptosis pathway in the penumbra after traumatic brain injury,and it remains unclear whether endoplasmic reticulum stress can activate the caspase-12-dependent apoptotic pathway in the traumatic penumbra.Here,we established rat models of fluid percussion-induced traumatic brain injury and found that protein expression of caspase-12,caspase-3 and the endoplasmic reticulum stress marker 78 k Da glucose-regulated protein increased in the traumatic penumbra 6 hours after injury and peaked at 24 hours.Furthermore,numbers of terminal deoxynucleotidyl transferase-mediated d UTP nick end labeling-positive cells in the traumatic penumbra also reached peak levels 24 hours after injury.These findings suggest that caspase-12-mediated endoplasmic reticulum-related apoptosis is activated in the traumatic penumbra,and may play an important role in the pathophysiology of secondary brain injury.展开更多
For reservoirs with complex non-Gaussian geological characteristics,such as carbonate reservoirs or reservoirs with sedimentary facies distribution,it is difficult to implement history matching directly,especially for...For reservoirs with complex non-Gaussian geological characteristics,such as carbonate reservoirs or reservoirs with sedimentary facies distribution,it is difficult to implement history matching directly,especially for the ensemble-based data assimilation methods.In this paper,we propose a multi-source information fused generative adversarial network(MSIGAN)model,which is used for parameterization of the complex geologies.In MSIGAN,various information such as facies distribution,microseismic,and inter-well connectivity,can be integrated to learn the geological features.And two major generative models in deep learning,variational autoencoder(VAE)and generative adversarial network(GAN)are combined in our model.Then the proposed MSIGAN model is integrated into the ensemble smoother with multiple data assimilation(ESMDA)method to conduct history matching.We tested the proposed method on two reservoir models with fluvial facies.The experimental results show that the proposed MSIGAN model can effectively learn the complex geological features,which can promote the accuracy of history matching.展开更多
The calculation sequence of collision, propagation and macroscopic variables is not very clear in lattice Boltzmann method (LBM) code implementation. According to the definition, three steps should be computed on all ...The calculation sequence of collision, propagation and macroscopic variables is not very clear in lattice Boltzmann method (LBM) code implementation. According to the definition, three steps should be computed on all nodes respectively, which mean three loops are needed. While the “pull” scheme makes the only one loop possible for coding, this is called semi-implicit scheme in this study. The accuracy and efficiency of semi-implicit scheme are discussed in detail through the simulation of lid-driven cavity flow. Non-equilibrium extrapolation scheme is adopted on the boundary of simulation area. The results are compared with two classic articles, which show that semi-implicit scheme has good agreement with the classic scheme. When Re is less than 3000, the iterations steps of semi-scheme can be decreased by about 30% though comparing the semi-implicit scheme with standard scheme containing three loops. As the Re increases into more than 3400, the standard scheme is not converged. On the contrary, the iterations of semi-implicit scheme are approximately linear to Re.展开更多
In order to investigate the influence on shale gas well productivity caused by gas transport in nanometer- size pores, a mathematical model of multi-stage fractured horizontal wells in shale gas reservoirs is built, w...In order to investigate the influence on shale gas well productivity caused by gas transport in nanometer- size pores, a mathematical model of multi-stage fractured horizontal wells in shale gas reservoirs is built, which considers the influence of viscous flow, Knudsen diffusion, surface diffusion, and adsorption layer thickness. A dis- crete-fracture model is used to simplify the fracture mod- cling, and a finite element method is applied to solve the model. The numerical simulation results indicate that with a decrease in the intrinsic matrix permeability, Knudsen diffusion and surface diffusion contributions to production become large and cannot be ignored. The existence of an adsorption layer on the nanopore surfaces reduces the effective pore radius and the effective porosity, resulting in low production from fractured horizontal wells. With a decrease in the pore radius, considering the adsorption layer, the production reduction rate increases. When the pore radius is less than 10 nm, because of the combined impacts of Knudsen diffusion, surface diffusion, and adsorption layers, the production of multi-stage fractured horizontal wells increases with a decrease in the pore pressure. When the pore pressure is lower than 30 MPa, the rate of production increase becomes larger with a decrease in pore pressure.展开更多
As a promising enhanced gas recovery technique,CO_(2)huff-n-puff has attracted great attention recently.However,hydraulic fracture deformation hysteresis is rarely considered,and its effect on CO_(2)huff-n-puff perfor...As a promising enhanced gas recovery technique,CO_(2)huff-n-puff has attracted great attention recently.However,hydraulic fracture deformation hysteresis is rarely considered,and its effect on CO_(2)huff-n-puff performance is not well understood.In this study,we present a fully coupled multi-component flow and geomechanics model for simulating CO_(2)huff-n-puff in shale gas reservoirs considering hydraulic fracture deformation hysteresis.Specifically,a shale gas reservoir after hydraulic fracturing is modeled using an efficient hybrid model incorporating an embedded discrete fracture model(EDFM),multiple porosity model,and single porosity model.In flow equations,Fick’s law,extended Langmuir isotherms,and the Peng-Robinson equation of state are used to describe the molecular diffusion,multi-component adsorption,and gas properties,respectively.In relation to geomechanics,a path-dependent constitutive law is applied for the hydraulic fracture deformation hysteresis.The finite volume method(FVM)and the stabilized extended finite element method(XFEM)are applied to discretize the flow and geomechanics equations,respectively.We then solve the coupled model using the fixed-stress split iterative method.Finally,we verify the presented method using several numerical examples,and apply it to investigate the effect of hydraulic fracture deformation hysteresis on CO_(2)huff-n-puff performance in a 3D shale gas reservoir.Numerical results show that hydraulic fracture deformation hysteresis has some negative effects on CO_(2)huff-n-puff performance.The effects are sensitive to the initial conductivity of hydraulic fracture,production pressure,starting time of huff-n-puff,injection pressure,and huff-n-puff cycle number.展开更多
Herein, cisplatin-loaded poly（L-glutamic acid）-g-methoxy poly（ethylene glycol） nanoparticles were evaluated as a potential chemotherapeutic agent against osteosarcoma by using alone or with an i RGD（internalizing...Herein, cisplatin-loaded poly（L-glutamic acid）-g-methoxy poly（ethylene glycol） nanoparticles were evaluated as a potential chemotherapeutic agent against osteosarcoma by using alone or with an i RGD（internalizing RGD, CRGDKDPDC）. The release rate of platinum from the cisplatin-loaded nanoparticles CDDP/PLG160-g-m PEG2K（CDDP-NPs） accelerated with the increase of the acidity of the environment. In vitro test demonstrated that CDDP-NPs could inhibit the proliferation of MNNG/Hos osteosarcoma cells with IC50（72 h） of 12.2 μg·mL^-1. In vivo test for MNNG/Hos osteosarcoma tumor bearing mice exhibited that CDDP-NPs had comparable or slightly higher efficacy but significantly lower side effects in comparison with free CDDP. The coadministration of i RGD could further enhance the anticancer efficacy of CDDP-NPs against MNNG/Hos osteosarcoma without bringing obvious side effects. Therefore, CDDP-NPs using alone or with iRGD have great potential for the treatment of osteosarcoma.展开更多
基金This work is supported by the National Natural Science Foundation of China under Grant 52274057,52074340 and 51874335the Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-008+2 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSNthe Science and Technology Support Plan for Youth Innovation of University in Shandong Province under Grant 2019KJH002111 Project under Grant B08028.
文摘Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing research suggests that the effectiveness of a surrogate model can vary depending on the complexity of the design problem.A surrogate model that has demonstrated success in one scenario may not perform as well in others.In the absence of prior knowledge,finding a promising surrogate model that performs well for an unknown reservoir is challenging.Moreover,the optimization process often relies on a single evolutionary algorithm,which can yield varying results across different cases.To address these limitations,this paper introduces a novel approach called the multi-surrogate framework with an adaptive selection mechanism(MSFASM)to tackle production optimization problems.MSFASM consists of two stages.In the first stage,a reduced-dimensional broad learning system(BLS)is used to adaptively select the evolutionary algorithm with the best performance during the current optimization period.In the second stage,the multi-objective algorithm,non-dominated sorting genetic algorithm II(NSGA-II),is used as an optimizer to find a set of Pareto solutions with good performance on multiple surrogate models.A novel optimal point criterion is utilized in this stage to select the Pareto solutions,thereby obtaining the desired development schemes without increasing the computational load of the numerical simulator.The two stages are combined using sequential transfer learning.From the two most important perspectives of an evolutionary algorithm and a surrogate model,the proposed method improves adaptability to optimization problems of various reservoir types.To verify the effectiveness of the proposed method,four 100-dimensional benchmark functions and two reservoir models are tested,and the results are compared with those obtained by six other surrogate-model-based methods.The results demonstrate that our approach can obtain the maximum net present value(NPV)of the target production optimization problems.
基金the National Natural Science Foundation of China(Nos.52122402,12172334,52034010,52174051)Shandong Provincial Natural Science Foundation(Nos.ZR2021ME029,ZR2022JQ23)Fundamental Research Funds for the Central Universities(No.22CX01001A-4)。
文摘The phase behavior of gas condensate in reservoir formations differs from that in pressure-volume-temperature(PVT)cells because it is influenced by porous media in the reservoir formations.Sandstone was used as a sample to investigate the influence of porous media on the phase behavior of the gas condensate.The pore structure was first analyzed using computed tomography(CT)scanning,digital core technology,and a pore network model.The sandstone core sample was then saturated with gas condensate for the pressure depletion experiment.After each pressure-depletion state was stable,realtime CT scanning was performed on the sample.The scanning results of the sample were reconstructed into three-dimensional grayscale images,and the gas condensate and condensate liquid were segmented based on gray value discrepancy to dynamically characterize the phase behavior of the gas condensate in porous media.Pore network models of the condensate liquid ganglia under different pressures were built to calculate the characteristic parameters,including the average radius,coordination number,and tortuosity,and to analyze the changing mechanism caused by the phase behavior change of the gas condensate.Four types of condensate liquid(clustered,branched,membranous,and droplet ganglia)were then classified by shape factor and Euler number to investigate their morphological changes dynamically and elaborately.The results show that the dew point pressure of the gas condensate in porous media is 12.7 MPa,which is 0.7 MPa higher than 12.0 MPa in PVT cells.The average radius,volume,and coordination number of the condensate liquid ganglia increased when the system pressure was between the dew point pressure(12.7 MPa)and the pressure for the maximum liquid dropout,Pmax(10.0 MPa),and decreased when it was below Pmax.The volume proportion of clustered ganglia was the highest,followed by branched,membranous,and droplet ganglia.This study provides crucial experimental evidence for the phase behavior changing process of gas condensate in porous media during the depletion production of gas condensate reservoirs.
基金supported by the Natural Science Foundation of Hebei Province of China,No.H2014206383Foundation for High-Level Personnel Projects in Hebei Province of China,No.A201401041
文摘Neuronal apoptosis is mediated by intrinsic and extrinsic signaling pathways such as the membrane-mediated,mitochondrial,and endoplasmic reticulum stress pathways.Few studies have examined the endoplasmic reticulum-mediated apoptosis pathway in the penumbra after traumatic brain injury,and it remains unclear whether endoplasmic reticulum stress can activate the caspase-12-dependent apoptotic pathway in the traumatic penumbra.Here,we established rat models of fluid percussion-induced traumatic brain injury and found that protein expression of caspase-12,caspase-3 and the endoplasmic reticulum stress marker 78 k Da glucose-regulated protein increased in the traumatic penumbra 6 hours after injury and peaked at 24 hours.Furthermore,numbers of terminal deoxynucleotidyl transferase-mediated d UTP nick end labeling-positive cells in the traumatic penumbra also reached peak levels 24 hours after injury.These findings suggest that caspase-12-mediated endoplasmic reticulum-related apoptosis is activated in the traumatic penumbra,and may play an important role in the pathophysiology of secondary brain injury.
基金Supported by the Fundamental Research Funds for the Central Universities (HEUCFR1109)"111" projects foundation (Grant No.B07019) from State Administration of Foreign Experts Affairs of China and Ministry of Education of China
基金supported by the National Natural Science Foundation of China under Grant 51722406,52074340,and 51874335the Shandong Provincial Natural Science Foundation under Grant JQ201808+5 种基金The Fundamental Research Funds for the Central Universities under Grant 18CX02097Athe Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-008the Science and Technology Support Plan for Youth Innovation of University in Shandong Province under Grant 2019KJH002the National Research Council of Science and Technology Major Project of China under Grant 2016ZX05025001-006111 Project under Grant B08028Sinopec Science and Technology Project under Grant P20050-1
文摘For reservoirs with complex non-Gaussian geological characteristics,such as carbonate reservoirs or reservoirs with sedimentary facies distribution,it is difficult to implement history matching directly,especially for the ensemble-based data assimilation methods.In this paper,we propose a multi-source information fused generative adversarial network(MSIGAN)model,which is used for parameterization of the complex geologies.In MSIGAN,various information such as facies distribution,microseismic,and inter-well connectivity,can be integrated to learn the geological features.And two major generative models in deep learning,variational autoencoder(VAE)and generative adversarial network(GAN)are combined in our model.Then the proposed MSIGAN model is integrated into the ensemble smoother with multiple data assimilation(ESMDA)method to conduct history matching.We tested the proposed method on two reservoir models with fluvial facies.The experimental results show that the proposed MSIGAN model can effectively learn the complex geological features,which can promote the accuracy of history matching.
文摘The calculation sequence of collision, propagation and macroscopic variables is not very clear in lattice Boltzmann method (LBM) code implementation. According to the definition, three steps should be computed on all nodes respectively, which mean three loops are needed. While the “pull” scheme makes the only one loop possible for coding, this is called semi-implicit scheme in this study. The accuracy and efficiency of semi-implicit scheme are discussed in detail through the simulation of lid-driven cavity flow. Non-equilibrium extrapolation scheme is adopted on the boundary of simulation area. The results are compared with two classic articles, which show that semi-implicit scheme has good agreement with the classic scheme. When Re is less than 3000, the iterations steps of semi-scheme can be decreased by about 30% though comparing the semi-implicit scheme with standard scheme containing three loops. As the Re increases into more than 3400, the standard scheme is not converged. On the contrary, the iterations of semi-implicit scheme are approximately linear to Re.
基金supported by the National Natural Science Foundation of China (No. 51234007, No. 51490654, No. 51504276, and No. 51504277)Program for Changjiang Scholars and Innovative Research Team in University (IRT1294)+3 种基金the Natural Science Foundation of Shandong Province (ZR2014EL016, ZR2014EEP018)China Postdoctoral Science Foundation (No. 2014M551989 and No. 2015T80762)the Major Programs of Ministry of Education of China (No. 311009)Introducing Talents of Discipline to Universities (B08028)
文摘In order to investigate the influence on shale gas well productivity caused by gas transport in nanometer- size pores, a mathematical model of multi-stage fractured horizontal wells in shale gas reservoirs is built, which considers the influence of viscous flow, Knudsen diffusion, surface diffusion, and adsorption layer thickness. A dis- crete-fracture model is used to simplify the fracture mod- cling, and a finite element method is applied to solve the model. The numerical simulation results indicate that with a decrease in the intrinsic matrix permeability, Knudsen diffusion and surface diffusion contributions to production become large and cannot be ignored. The existence of an adsorption layer on the nanopore surfaces reduces the effective pore radius and the effective porosity, resulting in low production from fractured horizontal wells. With a decrease in the pore radius, considering the adsorption layer, the production reduction rate increases. When the pore radius is less than 10 nm, because of the combined impacts of Knudsen diffusion, surface diffusion, and adsorption layers, the production of multi-stage fractured horizontal wells increases with a decrease in the pore pressure. When the pore pressure is lower than 30 MPa, the rate of production increase becomes larger with a decrease in pore pressure.
基金This work is supported by the National Natural Sci‐ence Foundation of China(Nos.52004321,52034010,and 12131014)the Natural Science Foundation of Shandong Province,China(No.ZR2020QE116)the Fundamental Research Funds for the Central Universities,China(Nos.20CX06025A and 21CX06031A).
文摘As a promising enhanced gas recovery technique,CO_(2)huff-n-puff has attracted great attention recently.However,hydraulic fracture deformation hysteresis is rarely considered,and its effect on CO_(2)huff-n-puff performance is not well understood.In this study,we present a fully coupled multi-component flow and geomechanics model for simulating CO_(2)huff-n-puff in shale gas reservoirs considering hydraulic fracture deformation hysteresis.Specifically,a shale gas reservoir after hydraulic fracturing is modeled using an efficient hybrid model incorporating an embedded discrete fracture model(EDFM),multiple porosity model,and single porosity model.In flow equations,Fick’s law,extended Langmuir isotherms,and the Peng-Robinson equation of state are used to describe the molecular diffusion,multi-component adsorption,and gas properties,respectively.In relation to geomechanics,a path-dependent constitutive law is applied for the hydraulic fracture deformation hysteresis.The finite volume method(FVM)and the stabilized extended finite element method(XFEM)are applied to discretize the flow and geomechanics equations,respectively.We then solve the coupled model using the fixed-stress split iterative method.Finally,we verify the presented method using several numerical examples,and apply it to investigate the effect of hydraulic fracture deformation hysteresis on CO_(2)huff-n-puff performance in a 3D shale gas reservoir.Numerical results show that hydraulic fracture deformation hysteresis has some negative effects on CO_(2)huff-n-puff performance.The effects are sensitive to the initial conductivity of hydraulic fracture,production pressure,starting time of huff-n-puff,injection pressure,and huff-n-puff cycle number.
基金financially supported by the National Natural Science Foundation of China(Nos.51373168,51233004,21104076,51321062 and 51390484)Ministry of Science and Technology of China(International Cooperation and Communication Program 2011DFR51090)the Program of Scientific Development of Jilin Province(Nos.20130206066GX,20130727050YY and 20130521011JH)
文摘Herein, cisplatin-loaded poly（L-glutamic acid）-g-methoxy poly（ethylene glycol） nanoparticles were evaluated as a potential chemotherapeutic agent against osteosarcoma by using alone or with an i RGD（internalizing RGD, CRGDKDPDC）. The release rate of platinum from the cisplatin-loaded nanoparticles CDDP/PLG160-g-m PEG2K（CDDP-NPs） accelerated with the increase of the acidity of the environment. In vitro test demonstrated that CDDP-NPs could inhibit the proliferation of MNNG/Hos osteosarcoma cells with IC50（72 h） of 12.2 μg·mL^-1. In vivo test for MNNG/Hos osteosarcoma tumor bearing mice exhibited that CDDP-NPs had comparable or slightly higher efficacy but significantly lower side effects in comparison with free CDDP. The coadministration of i RGD could further enhance the anticancer efficacy of CDDP-NPs against MNNG/Hos osteosarcoma without bringing obvious side effects. Therefore, CDDP-NPs using alone or with iRGD have great potential for the treatment of osteosarcoma.
