Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented...Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented in oil shale exploitation.However,accurately capturing the intricate flow dynamics of ICP requires a large number of fine-scale grid-blocks,which renders ICP simulations computationally expensive.Apart from that,plenty of oil shale reservoirs contain natural fractures or require hydraulic fracturing to enhance fluid mobility,creating further challenges in modeling pyrolysis reactions in both rock matrices and fractures.Targeted at the above issues,this work proposes a novel dual-model dualgrid upscaling(DDU)method specifically designed for solid-based thermal-reactive-compositional flow simulations in fractured porous media.Unlike existing upscaling techniques,the DDU method incorporates the upscaling of fracture grids using the embedded discrete fracture modeling(EDFM)approach and introduces a new concept of simplified models to approximate fine-scale results,which are used to correct reaction rates in coarse-scale grids.This method uniquely achieves efficient upscaling for both matrix and fracture grids,supports both open-source and commercial simulation platforms without modifying source codes,and is validated through 3D ICP models with natural fractures.The results indicate that the application of the DDU method can provide a close match with the fine-scale simulation results.Moreover,the DDU method has drastically improved the computational efficiency and speeded up the fine-scale simulation by 396-963 times.Therefore,the proposed DDU method has achieved marked computational savings while maintaining high simulation accuracy,which is significant for the development efficiency and production forecasting of oil shale reservoirs.展开更多
The sandy conglomerate reservoir is tight and exhibits strong heterogeneity,rendering conventional water flooding and gas drive methods inefficient and challenging for the effective development.CO_(2) water alternatin...The sandy conglomerate reservoir is tight and exhibits strong heterogeneity,rendering conventional water flooding and gas drive methods inefficient and challenging for the effective development.CO_(2) water alternating gas(CO_(2)-WAG)injection as an effective enhanced oil recovery(EOR)method has been applied in heterogeneous reservoirs.Simultaneously,it facilitates carbon sequestration,contributing to the green and low-carbon transformation of energy.However,the EOR mechanisms and influencing factors are still unclear for the development of heterogeneous sandy conglomerate reservoirs.In this paper,we conducted core flooding experiments combined nuclear magnetic resonance(NMR)technology to investigate EOR mechanisms of the CO_(2)-WAG injection on the multiscale(reservoir,layer,and pore).The study compared multiscale oil recovery in sandy conglomerate reservoirs under both miscible and immiscible conditions,while also analyzing the effects of water-gas ratio and injection rate.In the immiscible state,the CO_(2)-WAG displacement achieves an oil recovery of approximately 22.95%,representing a 7.82%increase compared to CO_(2) flooding.This method effectively inhibits CO_(2) breakthrough in high-permeability layers while enhancing the oil recovery in medium-and low-permeability layers.Furthermore,CO_(2)-WAG displacement improves the microscopic oil displacement efficiency within mesopores and micropores.As the water-gas ratio increases,the total oil recovery rises,with enhanced oil recovery in low-permeability layers and micropores.Moreover,a gradual increase in injection rate leads to a decrease in total oil recovery,but it leads to an increase in oil recovery from low-permeability sandy conglomerate layers and micropores.In the miscible state,the displacement efficiency of CO_(2)-WAG is significantly enhanced,the total oil recovery three times higher than that in the immiscible state.In particular,the oil recovery from low permeability layers and micropores has further improved.Additionally,experimental results indicate that parameters such as water-gas ratio and injection rate do not significantly affect the oil recovery of CO_(2)-WAG miscible displacement.Therefore,maintaining the reservoir pressure above the minimum miscible pressure is the key to maximizing ultimate recovery factor in these reservoirs.展开更多
In the realm of subsurface flow simulations,deep-learning-based surrogate models have emerged as a promising alternative to traditional simulation methods,especially in addressing complex optimization problems.However...In the realm of subsurface flow simulations,deep-learning-based surrogate models have emerged as a promising alternative to traditional simulation methods,especially in addressing complex optimization problems.However,a significant challenge lies in the necessity of numerous high-fidelity training simulations to construct these deep-learning models,which limits their application to field-scale problems.To overcome this limitation,we introduce a training procedure that leverages transfer learning with multi-fidelity training data to construct surrogate models efficiently.The procedure begins with the pre-training of the surrogate model using a relatively larger amount of data that can be efficiently generated from upscaled coarse-scale models.Subsequently,the model parameters are finetuned with a much smaller set of high-fidelity simulation data.For the cases considered in this study,this method leads to about a 75%reduction in total computational cost,in comparison with the traditional training approach,without any sacrifice of prediction accuracy.In addition,a dedicated well-control embedding model is introduced to the traditional U-Net architecture to improve the surrogate model's prediction accuracy,which is shown to be particularly effective when dealing with large-scale reservoir models under time-varying well control parameters.Comprehensive results and analyses are presented for the prediction of well rates,pressure and saturation states of a 3D synthetic reservoir system.Finally,the proposed procedure is applied to a field-scale production optimization problem.The trained surrogate model is shown to provide excellent generalization capabilities during the optimization process,in which the final optimized net-present-value is much higher than those from the training data ranges.展开更多
在理论上,超大质量黑洞(supermassive black holes,SMBH)周围的吸积盘在外区具有复杂结构,其中自引力将不可避免地导致恒星形成;在观测上,类星体金属丰度测量和引力波探测显示在活动星系核(active galactic nuclei,AGN)中心区域存在大...在理论上,超大质量黑洞(supermassive black holes,SMBH)周围的吸积盘在外区具有复杂结构,其中自引力将不可避免地导致恒星形成;在观测上,类星体金属丰度测量和引力波探测显示在活动星系核(active galactic nuclei,AGN)中心区域存在大质量恒星形成与演化.AGN盘上的恒星及致密天体通常具有很高的吸积率,以至于这些天体命运发生重大变化,我们统称为“吸积致变恒星”(accretion-modified star,AMS),由此形成了一个理论问题和观测效应十分丰富的崭新领域.研究表明,AGN盘上的AMS星族会通过吸积快速演化,最终以大质量恒星为主导,且在大质量端堆积或截断堆积式分布.AMS死亡后可产生恒星级黑洞,形成围绕SMBH的卫星黑洞群.在标准盘上的恒星级黑洞通常会发生Bondi爆炸,该爆炸的非热辐射峰值在X-射线和伽马射线波段,热辐射光度可以达到~10^(44)erg s^(-1).吸积盘上的黑洞在迁移过程中可形成双黑洞,与周围气体的相互作用可能会加速并合过程,同时为解释大质量黑洞并合事件提供契机.此外,AMS模型可合理解释银河系中心的恒星盘和金属丰度,其中质量为40 M_(⊙)的卫星黑洞可解释红外闪烁周期和耀斑轨迹等现象,这可能是距地球最近的EMRI(extreme mass ratio inspiral)天体.未来,更多的引力波探测与光谱光变观测计划相结合,有望更好地回答AGN盘上恒星及致密天体的演化与并合问题.展开更多
Time-division multiple access (TDMA) and code-division multiple access (CDMA) are two technologies used in digital cellular networks. The authentication protocols of TDMA networks have been proven to be vulnerable to ...Time-division multiple access (TDMA) and code-division multiple access (CDMA) are two technologies used in digital cellular networks. The authentication protocols of TDMA networks have been proven to be vulnerable to side-channel analysis (SCA), giving rise to a series of powerful SCA-based attacks against unprotected subscriber identity module (SIM) cards. CDMA networks have two authentication protocols, cellular authentication and voice encryption (CAVE) based authentication protocol and authentication and key agreement (AKA) based authentication protocol, which are used in different phases of the networks. However, there has been no SCA attack for these two protocols so far. In this paper, in order to figure out if the authentication protocols of CDMA networks are sufficiently secure against SCA, we investigate the two existing protocols and their cryptographic algorithms. We find the side-channel weaknesses of the two protocols when they are implemented on embedded systems. Based on these weaknesses, we propose specific attack strategies to recover their authentication keys for the two protocols, respectively. We verify our strategies on an 8-bit microcontroller and a real-world SIM card, showing that the authentication keys can be fully recovered within a few minutes with a limited number of power measurements. The successful experiments demonstrate the correctness and the effectiveness of our proposed strategies and prove that the unprotected implementations of the authentication protocols of CDMA networks cannot resist SCA.展开更多
Side-channel attacks(SCAs)play an important role in the security evaluation of cryptographic devices.As a form of SCAs,profiled differential power analysis(DPA)is among the most powerful and efficient by taking advant...Side-channel attacks(SCAs)play an important role in the security evaluation of cryptographic devices.As a form of SCAs,profiled differential power analysis(DPA)is among the most powerful and efficient by taking advantage of a profiling phase that learns features from a controlled device.Linear regression(LR)based profiling,a special profiling method proposed by Schindler et al.,could be extended to generic-emulating DPA(differential power analysis)by on-the-fly profiling.The formal extension was proposed by Whitnall et al.named SLR-based method.Later,to improve SLR-based method,Wang et al.introduced a method based on ridge regression.However,the constant format of L-2 penalty still limits the performance of profiling.In this paper,we generalize the ridge-based method and propose a new strategy of using variable regularization.We then analyze from a theoretical point of view why we should not use constant penalty format for all cases.Roughly speaking,our work reveals the underlying mechanism of how different formats affect the profiling process in the context of side channel.Therefore,by selecting a proper regularization,we could push the limits of LR-based profiling.Finally,we conduct simulation-based and practical experiments to confirm our analysis.Specifically,the results of our practical experiments show that the proper formats of regularization are different among real devices.展开更多
基金the financial support from the National Science Foundation of China(No.52374063 and No.52204065)the Natural Science Foundation of Shandong Province,China(No.ZR2023ME049 and No.ZR2021JQ18)the Fundamental Research Funds for the Central Universities,China(24CX06017A)。
文摘Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented in oil shale exploitation.However,accurately capturing the intricate flow dynamics of ICP requires a large number of fine-scale grid-blocks,which renders ICP simulations computationally expensive.Apart from that,plenty of oil shale reservoirs contain natural fractures or require hydraulic fracturing to enhance fluid mobility,creating further challenges in modeling pyrolysis reactions in both rock matrices and fractures.Targeted at the above issues,this work proposes a novel dual-model dualgrid upscaling(DDU)method specifically designed for solid-based thermal-reactive-compositional flow simulations in fractured porous media.Unlike existing upscaling techniques,the DDU method incorporates the upscaling of fracture grids using the embedded discrete fracture modeling(EDFM)approach and introduces a new concept of simplified models to approximate fine-scale results,which are used to correct reaction rates in coarse-scale grids.This method uniquely achieves efficient upscaling for both matrix and fracture grids,supports both open-source and commercial simulation platforms without modifying source codes,and is validated through 3D ICP models with natural fractures.The results indicate that the application of the DDU method can provide a close match with the fine-scale simulation results.Moreover,the DDU method has drastically improved the computational efficiency and speeded up the fine-scale simulation by 396-963 times.Therefore,the proposed DDU method has achieved marked computational savings while maintaining high simulation accuracy,which is significant for the development efficiency and production forecasting of oil shale reservoirs.
基金supported by the National Natural Science Foundation of China(No.52204065,No.52374063)the Independent Innovation Research Project of China University of Petroleum(No.24CX06017A)Shandong Provincial Natural Science Foundation,China(No.ZR2024QE075,No.ZR2023ME049)。
文摘The sandy conglomerate reservoir is tight and exhibits strong heterogeneity,rendering conventional water flooding and gas drive methods inefficient and challenging for the effective development.CO_(2) water alternating gas(CO_(2)-WAG)injection as an effective enhanced oil recovery(EOR)method has been applied in heterogeneous reservoirs.Simultaneously,it facilitates carbon sequestration,contributing to the green and low-carbon transformation of energy.However,the EOR mechanisms and influencing factors are still unclear for the development of heterogeneous sandy conglomerate reservoirs.In this paper,we conducted core flooding experiments combined nuclear magnetic resonance(NMR)technology to investigate EOR mechanisms of the CO_(2)-WAG injection on the multiscale(reservoir,layer,and pore).The study compared multiscale oil recovery in sandy conglomerate reservoirs under both miscible and immiscible conditions,while also analyzing the effects of water-gas ratio and injection rate.In the immiscible state,the CO_(2)-WAG displacement achieves an oil recovery of approximately 22.95%,representing a 7.82%increase compared to CO_(2) flooding.This method effectively inhibits CO_(2) breakthrough in high-permeability layers while enhancing the oil recovery in medium-and low-permeability layers.Furthermore,CO_(2)-WAG displacement improves the microscopic oil displacement efficiency within mesopores and micropores.As the water-gas ratio increases,the total oil recovery rises,with enhanced oil recovery in low-permeability layers and micropores.Moreover,a gradual increase in injection rate leads to a decrease in total oil recovery,but it leads to an increase in oil recovery from low-permeability sandy conglomerate layers and micropores.In the miscible state,the displacement efficiency of CO_(2)-WAG is significantly enhanced,the total oil recovery three times higher than that in the immiscible state.In particular,the oil recovery from low permeability layers and micropores has further improved.Additionally,experimental results indicate that parameters such as water-gas ratio and injection rate do not significantly affect the oil recovery of CO_(2)-WAG miscible displacement.Therefore,maintaining the reservoir pressure above the minimum miscible pressure is the key to maximizing ultimate recovery factor in these reservoirs.
基金funding support from the National Natural Science Foundation of China(No.52204065,No.ZX20230398)supported by a grant from the Human Resources Development Program(No.20216110100070)of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)。
文摘In the realm of subsurface flow simulations,deep-learning-based surrogate models have emerged as a promising alternative to traditional simulation methods,especially in addressing complex optimization problems.However,a significant challenge lies in the necessity of numerous high-fidelity training simulations to construct these deep-learning models,which limits their application to field-scale problems.To overcome this limitation,we introduce a training procedure that leverages transfer learning with multi-fidelity training data to construct surrogate models efficiently.The procedure begins with the pre-training of the surrogate model using a relatively larger amount of data that can be efficiently generated from upscaled coarse-scale models.Subsequently,the model parameters are finetuned with a much smaller set of high-fidelity simulation data.For the cases considered in this study,this method leads to about a 75%reduction in total computational cost,in comparison with the traditional training approach,without any sacrifice of prediction accuracy.In addition,a dedicated well-control embedding model is introduced to the traditional U-Net architecture to improve the surrogate model's prediction accuracy,which is shown to be particularly effective when dealing with large-scale reservoir models under time-varying well control parameters.Comprehensive results and analyses are presented for the prediction of well rates,pressure and saturation states of a 3D synthetic reservoir system.Finally,the proposed procedure is applied to a field-scale production optimization problem.The trained surrogate model is shown to provide excellent generalization capabilities during the optimization process,in which the final optimized net-present-value is much higher than those from the training data ranges.
文摘在理论上,超大质量黑洞(supermassive black holes,SMBH)周围的吸积盘在外区具有复杂结构,其中自引力将不可避免地导致恒星形成;在观测上,类星体金属丰度测量和引力波探测显示在活动星系核(active galactic nuclei,AGN)中心区域存在大质量恒星形成与演化.AGN盘上的恒星及致密天体通常具有很高的吸积率,以至于这些天体命运发生重大变化,我们统称为“吸积致变恒星”(accretion-modified star,AMS),由此形成了一个理论问题和观测效应十分丰富的崭新领域.研究表明,AGN盘上的AMS星族会通过吸积快速演化,最终以大质量恒星为主导,且在大质量端堆积或截断堆积式分布.AMS死亡后可产生恒星级黑洞,形成围绕SMBH的卫星黑洞群.在标准盘上的恒星级黑洞通常会发生Bondi爆炸,该爆炸的非热辐射峰值在X-射线和伽马射线波段,热辐射光度可以达到~10^(44)erg s^(-1).吸积盘上的黑洞在迁移过程中可形成双黑洞,与周围气体的相互作用可能会加速并合过程,同时为解释大质量黑洞并合事件提供契机.此外,AMS模型可合理解释银河系中心的恒星盘和金属丰度,其中质量为40 M_(⊙)的卫星黑洞可解释红外闪烁周期和耀斑轨迹等现象,这可能是距地球最近的EMRI(extreme mass ratio inspiral)天体.未来,更多的引力波探测与光谱光变观测计划相结合,有望更好地回答AGN盘上恒星及致密天体的演化与并合问题.
文摘Time-division multiple access (TDMA) and code-division multiple access (CDMA) are two technologies used in digital cellular networks. The authentication protocols of TDMA networks have been proven to be vulnerable to side-channel analysis (SCA), giving rise to a series of powerful SCA-based attacks against unprotected subscriber identity module (SIM) cards. CDMA networks have two authentication protocols, cellular authentication and voice encryption (CAVE) based authentication protocol and authentication and key agreement (AKA) based authentication protocol, which are used in different phases of the networks. However, there has been no SCA attack for these two protocols so far. In this paper, in order to figure out if the authentication protocols of CDMA networks are sufficiently secure against SCA, we investigate the two existing protocols and their cryptographic algorithms. We find the side-channel weaknesses of the two protocols when they are implemented on embedded systems. Based on these weaknesses, we propose specific attack strategies to recover their authentication keys for the two protocols, respectively. We verify our strategies on an 8-bit microcontroller and a real-world SIM card, showing that the authentication keys can be fully recovered within a few minutes with a limited number of power measurements. The successful experiments demonstrate the correctness and the effectiveness of our proposed strategies and prove that the unprotected implementations of the authentication protocols of CDMA networks cannot resist SCA.
基金supported by the State Grid Science and Technology Project of China under Grant No.546816190003.
文摘Side-channel attacks(SCAs)play an important role in the security evaluation of cryptographic devices.As a form of SCAs,profiled differential power analysis(DPA)is among the most powerful and efficient by taking advantage of a profiling phase that learns features from a controlled device.Linear regression(LR)based profiling,a special profiling method proposed by Schindler et al.,could be extended to generic-emulating DPA(differential power analysis)by on-the-fly profiling.The formal extension was proposed by Whitnall et al.named SLR-based method.Later,to improve SLR-based method,Wang et al.introduced a method based on ridge regression.However,the constant format of L-2 penalty still limits the performance of profiling.In this paper,we generalize the ridge-based method and propose a new strategy of using variable regularization.We then analyze from a theoretical point of view why we should not use constant penalty format for all cases.Roughly speaking,our work reveals the underlying mechanism of how different formats affect the profiling process in the context of side channel.Therefore,by selecting a proper regularization,we could push the limits of LR-based profiling.Finally,we conduct simulation-based and practical experiments to confirm our analysis.Specifically,the results of our practical experiments show that the proper formats of regularization are different among real devices.
