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
Numerical simulation is an essential technique for CO_(2)geological storage operations.However,highresolution geological models typically consist of a large number of grid blocks,making numerical simulations computati...Numerical simulation is an essential technique for CO_(2)geological storage operations.However,highresolution geological models typically consist of a large number of grid blocks,making numerical simulations computationally expensive and time-consuming.Upscaling methods are commonly used to coarsen the fine-scale geological model,with global flow-based upscaling methods generally demonstrating the highest accuracy.However,since these methods require solving flow equations over the global domain,which is still time-consuming,their applications are typically limited to cases where the coarse model is reused repeatedly(e.g.,history matching or optimization).To overcome these limitations,this study develops a novel deep learning(DL)-based upscaling framework for the simulation of CO_(2)injection into saline aquifers.The framework incorporates convolutional neural networks(CNNs),Transformer encoders,and Fourier neural operators(FNOs)to construct surrogate models for upscaled well index,permeability,relative permeability,and capillary pressure.A preprocessing procedure is first applied to address the issue of inaccurate upscaled parameters,which are typically caused by weak flow conditions in traditional upscaling computations.Then the surrogate models are trained using relevant local information,and the trained surrogate models are used to replace traditional numerical upscaling computations,enabling instantaneous and parallel predictions of upscaled parameters.Two representative flow patterns(left-to-right and bottom-to-top)are considered to evaluate the framework's performance.The results demonstrate that the DL-based framework significantly improves computational efficiency,achieving a speedup factor of approximately 1133 times compared to traditional upscaling methods.Additionally,it maintains or even enhances simulation accuracy,as the surrogate models correct inaccurate upscaled parameters.展开更多
Knowledge of the mechanical behavior of planetary rocks is indispensable for space explorations.The scarcity of pristine samples and the irregular shapes of planetary meteorites make it difficult to obtain representat...Knowledge of the mechanical behavior of planetary rocks is indispensable for space explorations.The scarcity of pristine samples and the irregular shapes of planetary meteorites make it difficult to obtain representative samples for conventional macroscale rock mechanics experiments(macro-RMEs).This critical review discusses recent advances in microscale RMEs(micro-RMEs)techniques and the upscaling methods for extracting mechanical parameters.Methods of mineralogical and microstructural analyses,along with non-destructive mechanical techniques,have provided new opportunities for studying planetary rocks with unprecedented precision and capabilities.First,we summarize several mainstream methods for obtaining the mineralogy and microstructure of planetary rocks.Then,nondestructive micromechanical testing methods,nanoindentation and atomic force microscopy(AFM),are detailed reviewed,illustrating the principles,advantages,influencing factors,and available testing results from literature.Subsequently,several feasible upscaling methods that bridge the micro-measurements of meteorite pieces to the strength of the intact body are introduced.Finally,the potential applications of planetary rock mechanics research to guiding the design and execution of space missions are environed,ranging from sample return missions and planetary defense to extraterrestrial construction.These discussions are expected to broaden the understanding of the microscale mechanical properties of planetary rocks and their significant role in deep space exploration.展开更多
Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments.However,a robust and e...Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments.However,a robust and efficient geomechanical upscaling technique for heterogeneous geological reservoirs is lacking to advance the applications of three-dimensional(3D)reservoir-scale geomechanical simulation considering detailed geological heterogeneities.Here,we develop convolutional neural network(CNN)proxies that reproduce the anisotropic nonlinear geomechanical response caused by lithological heterogeneity,and compute upscaled geomechanical properties from CNN proxies.The CNN proxies are trained using a large dataset of randomly generated spatially correlated sand-shale realizations as inputs and simulation results of their macroscopic geomechanical response as outputs.The trained CNN models can provide the upscaled shear strength(R^(2)>0.949),stress-strain behavior(R^(2)>0.925),and volumetric strain changes(R^(2)>0.958)that highly agree with the numerical simulation results while saving over two orders of magnitude of computational time.This is a major advantage in computing the upscaled geomechanical properties directly from geological realizations without the need to perform local numerical simulations to obtain the geomechanical response.The proposed CNN proxybased upscaling technique has the ability to(1)bridge the gap between the fine-scale geocellular models considering geological uncertainties and computationally efficient geomechanical models used to assess the geomechanical risks of large-scale subsurface development,and(2)improve the efficiency of numerical upscaling techniques that rely on local numerical simulations,leading to significantly increased computational time for uncertainty quantification using numerous geological realizations.展开更多
To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions...To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions with different rice variety types, and five to six sites in each region were selected. Then the eight genetic parameters of CERES-Rice, particularly the four parameters related to the yield, were modified and validated using the Trial and Error Method and the local statistical data of rice yield at a county level from 2001 to 2004, combined with the regional experiments of rice varieties in the province as well as the local meteorological and soil data （Method 1）. The simulated results of Method 1 were compared with those of other three traditional methods upscaling the genetic parameters, i.e., using one-site experimental data from a local representative rice variety （Method 2）, using local long-term rice yield data at a county level after deducting the trend yield due to progress of science and technology （Method 3）, and using rice yield data at a super scale, such as provincial, ecological zone, country or continent levels （Method 4）. The results showed that the best fitness was obtained by using the Method 1. The coefficients of correlation between the simulated yield and the statistical yield in the Method 1 were significant at 0.05 or 0.01 levels and the root mean squared error （RMSE） values were less than 9% for all the four rice regions. The method for upscaling the genetic parameters of CERES-Rice presented is not only valuable for the impact studies of climate change, but also favorable to provide a methodology for reference in crop model applications to the other regional studies.展开更多
We present a general homogenization method a periodic heterogeneous material with piecewise constants for diffusion, heat conduction, and wave propagation in The method is relevant to the frequently encountered upsca...We present a general homogenization method a periodic heterogeneous material with piecewise constants for diffusion, heat conduction, and wave propagation in The method is relevant to the frequently encountered upscaling issues for heterogeneous materials. The dispersion relation for each problem is first expressed in the general form where the frequency co （or wavenumber k） is expanded in terms of the wavenumber k （or frequency ω）. A general homogenization model can be directly obtained with any given dispersion relation. Next step we study the unit cell of the heterogeneous material and derive the exact dispersion relation. The final homogenized equations include both leading order terms （effective properties） and high order contributions that represent the effect of the microscopic heterogeneity on the macroscopic behavior. That effect can be lumped into a single dimensionless heterogeneity parameter β, which is bounded between -1/12≤β≤ 0 and has a universal expression for all three problems. Numerical examples validate the proposed method and demonstrate a significant computational saving.展开更多
We present a workflow for upscaling of rock properties using microtomography and percolation theory. In this paper we focus on a pilot study for assessing the plastic strength of rocks from a digital rock image. First...We present a workflow for upscaling of rock properties using microtomography and percolation theory. In this paper we focus on a pilot study for assessing the plastic strength of rocks from a digital rock image. Firstly, we determine the size of mechanical representative volume ele- ment （RVE） by using upper/lower bound dissipation computations in accordance with thermody- namics. Then the mechanical RVE is used to simulate the rock failure at micro-scale using FEM. Two cases of different pressures of linear Drucker-Prager plasticity of rocks are computed to compute the macroscopic cohesion and the angle of internal friction of the rock. We also detect the critical exponents of yield stress for sealing laws from a series of derivative models that are created by a shrinking/expanding algorithm. We use microtomographic data sets of two carbonate samples and compare the results with previous results. The results show that natural rock samples with irregular structures may have the critical exponent of yield stress different from random models. This unexpected result could have significant ramifications for assessing the stability of solid materials with internal structure. Therefore our pilot study needs to be extended to investigate the scaling laws of strength of many more natural rocks with irregular microstructure.展开更多
The main purpose of upscaling in reservoir simulation is to capture the dynamic behavior of fine scale models at the coarse scale. Traditional static or dynamic methods use assumptions about the boundary conditions to...The main purpose of upscaling in reservoir simulation is to capture the dynamic behavior of fine scale models at the coarse scale. Traditional static or dynamic methods use assumptions about the boundary conditions to determine the upscaled properties, in this paper, we show that the upscaled properties are strongly dependent on the flow process observed at the fine scale. We use a simple no- crossflow depletion drive process and demonstrate that an upscaled property is not a constant value. Instead, if the goal is to match the performance of the fine scale model, the upscaled permeability changes with time. We provide an analytical solution to determine the upscaled permeability and present the value of upscaled permeability under limiting conditions. Our equation suggests that it is possible that upscaled value can fall outside the range of fine scale values under certain conditions. We show that for pseudo steady state flow, using common averaging methods like arithmetic or even geometric averaging methods can lead to optimistic results. We also show that the no-crossflow solution is significantly different than crossflow solution at late times. We validate our method by comparing the results of the method with flow simulation results in two and multi-layered models.展开更多
We provide the capillary pressure curves p_(c)(s)as a function of the effective saturation s based on the theoretical framework of upscaling unsaturated flows in vertically heterogeneous porous layers proposed recentl...We provide the capillary pressure curves p_(c)(s)as a function of the effective saturation s based on the theoretical framework of upscaling unsaturated flows in vertically heterogeneous porous layers proposed recently(Z.Zheng,Journal of Fluid Mechanics,950,A17,2022).Based on the assumption of vertical gravitational-capillary equilibrium,the saturation distribution and profile shape of the invading fluid can be obtained by solving a nonlinear integral-differential equation.The capillary pressure curves p_(c)(s)can then be constructed by systematically varying the injection rate.Together with the relative permeability curves k_(rn)(s)that are already obtained.One can now provide quick estimates on the overall behaviours of interfacial and unsaturated flows in vertically-heterogeneous porous layers.展开更多
Describing the orientation state of the particles is often critical in fibre suspension applications.Macroscopic descriptors,the so-called second-order orientation tensor(or moment)leading the way,are often preferred ...Describing the orientation state of the particles is often critical in fibre suspension applications.Macroscopic descriptors,the so-called second-order orientation tensor(or moment)leading the way,are often preferred due to their low computational cost.Closure problems however arise when evolution equations for the moments are derived from the orientation distribution functions and the impact of the chosen closure is often unpredictable.In this work,our aim is to provide macroscopic simulations of orientation that are cheap,accurate and closure-free.To this end,we propose an innovative data-based approach to the upscaling of orientation kinematics in the context of fibre suspensions.Since the physics at the microscopic scale can be modelled reasonably enough,the idea is to conduct accurate offline direct numerical simulations at that scale and to extract the corresponding macroscopic descriptors in order to build a database of scenarios.During the online stage,the macroscopic descriptors can then be updated quickly by combining adequately the items from the database instead of relying on an imprecise macroscopic model.This methodology is presented in the well-known case of dilute fibre suspensions(where it can be compared against closure-based macroscopic models)and in the case of suspensions of confined or electrically-charged fibres,for which state-of-the-art closures proved to be inadequate or simply do not exist.展开更多
Upscaling of primary geological models with huge cells, especially in porous media, is the first step in fluid flow simulation. Numerical methods are often used to solve the models. The upscaling method must preserve ...Upscaling of primary geological models with huge cells, especially in porous media, is the first step in fluid flow simulation. Numerical methods are often used to solve the models. The upscaling method must preserve the important properties of the spatial distribution of the reservoir properties. An grid upscaling method based on adaptive bandwidth in kernel function is proposed according to the spatial distribution of property. This type of upscaling reduces the number of cells, while preserves the main heterogeneity features of the original fine model. The key point of the paper is upscaling two reservoir properties simultaneously. For each reservoir feature, the amount of bandwidth or optimal threshold is calculated and the results of the upscaling are obtained. Then two approaches are used to upscaling two properties simultaneously based on maximum bandwidth and minimum bandwidth. In fact, we now have a finalized upscaled model for both reservoir properties for each approach in which not only the number of their cells, but also the locations of the cells are equal. The upscaling error of the minimum bandwidth approach is less than that of the maximum bandwidth approach.展开更多
Based on the abundant core data of oil sands in the Mackay river in Canada,the termination frequency of muddy interlayers was counted to predict the extension range of interlayers using a queuing theory model,and then...Based on the abundant core data of oil sands in the Mackay river in Canada,the termination frequency of muddy interlayers was counted to predict the extension range of interlayers using a queuing theory model,and then the quantitative relationship between the thickness and extension length of muddy interlayer was established.An equivalent upscaling method of geologic model based on tortuous paths under the effects of muddy interlayer has been proposed.Single muddy interlayers in each coarse grid are tracked and identified,and the average length,width and proportion of muddy interlayer in each coarse grid are determined by using the geological connectivity tracing algorithm.The average fluid flow length of tortuous path under the influence of muddy interlayer is calculated.Based on the Darcy formula,the formula calculating average permeability in the coarsened grid is deduced to work out the permeability of equivalent coarsened grid.The comparison of coarsening results of the oil sand reservoir of Mackay River with actual development indexes shows that the equivalent upscaling method of muddy interlayer by tortuous path calculation can reflect the blocking effect of muddy interlayer very well,and better reflect the effects of geological condition on production.展开更多
Simulation of reservoir flow processes at the finest scale is computationally expensive and in some cases impractical.Consequently,upscaling of several fine-scale grid blocks into fewer coarse-scale grids has become a...Simulation of reservoir flow processes at the finest scale is computationally expensive and in some cases impractical.Consequently,upscaling of several fine-scale grid blocks into fewer coarse-scale grids has become an integral part of reservoir simulation for most reservoirs.This is because as the number of grid blocks increases,the number of flow equations increases and this increases,in large proportion,the time required for solving flow problems.Although we can adopt parallel computation to share the load,a large number of grid blocks still pose significant computational challenges.Thus,upscaling acts as a bridge between the reservoir scale and the simulation scale.However as the upscaling ratio is increased,the accuracy of the numerical simulation is reduced;hence,there is a need to keep a balance between the two.In this work,we present a sensitivity-based upscaling technique that is applicable during history matching.This method involves partial homogenization of the reservoir model based on the model reduction pattern obtained from analysis of the sensitivity matrix.The technique is based on wavelet transformation and reduction of the data and model spaces as presented in the 2Dwp-wk approach.In the 2Dwp-wk approach,a set of wavelets of measured data is first selected and then a reduced model space composed of important wavelets is gradually built during the first few iterations of nonlinear regression.The building of the reduced model space is done by thresholding the full wavelet sensitivity matrix.The pattern of permeability distribution in the reservoir resulting from the thresholding of the full wavelet sensitivity matrix is used to determine the neighboring grids that are upscaled.In essence,neighboring grid blocks having the same permeability values due to model space reduction are combined into a single grid block in the simulation model,thus integrating upscaling with wavelet multiscale inverse modeling.We apply the method to estimate the parameters of two synthetic reservoirs.The history matching results obtained using this sensitivity-based upscaling are in very close agreement with the match provided by fine-scale inverse analysis.The reliability of the technique is evaluated using various scenarios and almost all the cases considered have shown very good results.The technique speeds up the history matching process without seriously compromising the accuracy of the estimates.展开更多
Lab-scale perovskite solar cells have shown ever-increasing power conversion efficiency in recent years.However,practical deployment is hindered by inferior device performance when upscaling from lab-scale cells to la...Lab-scale perovskite solar cells have shown ever-increasing power conversion efficiency in recent years.However,practical deployment is hindered by inferior device performance when upscaling from lab-scale cells to large-area modules.One such limitation originates from the poor thin-film quality of large-area modules.As a result,it is imperative to address the difficulties in fabricating high-quality perovskite absorbers.Herein,we analyze the fundamental challenges existing in large-area perovskite film fabrication,covering everything from crystal nucleation to thin-film growth and passivation.We then discuss a feasible roadmap to enhancing large-area modules through precursor chemistry strategies.These strategies encompass precursor design(solvent selection and additive engineering),drying process modulation(uniform drying,wide processing window,and high throughput),and annealing optimization(moderate annealing and thermal management).In addition,we examine the strengths and weaknesses of scalable deposition methods used in the present upscaling devices.This work provides strategic insights and practical guidelines for minimizing efficiency loss and accelerating the commercialization of perovskite photovoltaics.展开更多
Evapotranspiration(ET)plays a crucial role in the global water and energy cycle.Upscaling instantaneous ET(ET_(i))to daily ET(ET_(d))is vital for thermal-based ET estimation.Conventional methods-such as the constant e...Evapotranspiration(ET)plays a crucial role in the global water and energy cycle.Upscaling instantaneous ET(ET_(i))to daily ET(ET_(d))is vital for thermal-based ET estimation.Conventional methods-such as the constant evaporative fraction method(ConEF),radiation-based method,and evaporative ratio method-often overlook environmental factors,leading to biased estimates of ET_(d)from ET_(i).To resolve this issue,this study aimed to assess four machine learning(ML)algorithms-XGBoost,LightGBM,AdaBoost,and Random Forest-to integrate meteorological and remote sensing data for upscaling ETi across 88 global flux sites.Each ML model was tested with eight different variable combinations.Results indicated that XGBoost exhibited the best performance,with a root mean square error(RMSE)generally below 13 W m^(-2)in estimating ET_(d)from ET_(i).The best variable combination simultaneously considers evaporative fraction,available energy,meteorology factors,remote sensing albedo,normalized vegetation index,and leaf area index.Using this combination,the XGBoost model achieved an R^(2)=0.88 and an RMSE=12.33 W m^(-2),outperforming the ConEF method(R^(2)=0.71 and RMSE=18.86 Wm^(-2))and its expansions.These findings support the application of ML models in ET upscaling,enabling ET estimation across large spatiotemporal scales.展开更多
Flash Joule heating(FJH),as a high-efficiency and low-energy consumption technology for advanced materials synthesis,has shown significant potential in the synthesis of graphene and other functional carbon materials.B...Flash Joule heating(FJH),as a high-efficiency and low-energy consumption technology for advanced materials synthesis,has shown significant potential in the synthesis of graphene and other functional carbon materials.Based on the Joule effect,the solid carbon sources can be rapidly heated to ultra-high temperatures(>3000 K)through instantaneous high-energy current pulses during FJH,thus driving the rapid rearrangement and graphitization of carbon atoms.This technology demonstrates numerous advantages,such as solvent-and catalyst-free features,high energy conversion efficiency,and a short process cycle.In this review,we have systematically summarized the technology principle and equipment design for FJH,as well as its raw materials selection and pretreatment strategies.The research progress in the FJH synthesis of flash graphene,carbon nanotubes,graphene fibers,and anode hard carbon,as well as its by-products,is also presented.FJH can precisely optimize the microstructures of carbon materials(e.g.,interlayer spacing of turbostratic graphene,defect concentration,and heteroatom doping)by regulating its operation parameters like flash voltage and flash time,thereby enhancing their performances in various applications,such as composite reinforcement,metal-ion battery electrodes,supercapacitors,and electrocatalysts.However,this technology is still challenged by low process yield,macroscopic material uniformity,and green power supply system construction.More research efforts are also required to promote the transition of FJH from laboratory to industrial-scale applications,thus providing innovative solutions for advanced carbon materials manufacturing and waste management toward carbon neutrality.展开更多
One of the essential steps for satellite albedo validation is upscaling in situ measurements to corresponding pixel scale over relatively heterogeneous land surfaces.Although the multi-scale validation strategy is app...One of the essential steps for satellite albedo validation is upscaling in situ measurements to corresponding pixel scale over relatively heterogeneous land surfaces.Although the multi-scale validation strategy is applicable for heterogeneous surfaces,the calibration of the high-resolution imagery during upscaling process is never perfect,and thus the upscaling results suffer from errors.The regression-kriging(RK)technique can compensate the calibration part by applying kriging to upscale residuals and produce more accurate upscaling results.In this paper,in situ measurements and high spatial resolution albedo imagery combined with RK technique was proposed.This method is illustrated by upscaling surface albedo from in situ measurements scale to the coarse pixel scale in the core experimental area of HiWATER,where 17 WSN nodes were deployed at heterogeneous area.The upscaling results of this method were compared with the upscaling results from multi-scale strategy.The results show that the upscaling method based on in situ measurements and high-resolution imagery combined with RK technique can capture the spatial characteristics of surface albedo better.Further,an attempt was made to expand this method in time series.Finally,a preliminary validation of the Moderate Resolution Imaging Spectroradiometer albedo product was performed as the tentative application.展开更多
We review some of our recent efforts in developing upscaling methods for simulating the flow transport through heterogeneous porous media. In particular, the steady flow transport through highly heterogeneous porous m...We review some of our recent efforts in developing upscaling methods for simulating the flow transport through heterogeneous porous media. In particular, the steady flow transport through highly heterogeneous porous media driven by extraction wells and the flow transport through unsaturated porous media will be considered.展开更多
Upscaling ground albedo is challenged by the serious discrepancy between the heterogeneity of land surfaces and the small number of ground-based measurements.Conventional ground-based measurements cannot provide suffi...Upscaling ground albedo is challenged by the serious discrepancy between the heterogeneity of land surfaces and the small number of ground-based measurements.Conventional ground-based measurements cannot provide sufficient information on the characteristics of surface albedo at the scale of coarse pixels over heterogeneous land surfaces.One method of overcoming this problem is to introduce high-resolution albedo imagery as ancillary information for upscaling.However,due to the low frequency of updating of high-resolution albedo maps,upscaling time series of ground-based albedo measurements is difficult.This paper proposes a method that is based on the idea of conceptual universal scaling methodology for establishing a spatiotemporal trend surface using very few high-resolution images and time series of ground-based measurements for spatial-temporal upscaling of albedo.The construction of the spatiotemporal trend surface incorporates the spatial information provided by auxiliary remote sensing images and the temporal information provided by long time series of ground observations.This approach was illustrated by upscaling ground-based fine-scale albedo measurements to a coarse scale over the core study area in HiWATER.The results indicate that this method can characterize the spatiotemporal variations in surface albedo well,and the overall correlation coefficient was 0.702 during the study period.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partially supported by the National Natural Science Foundation of China(Nos.52334001,U24B200085)the Science Foundation of China University of Petroleum,Beijing(No.2462025XKBH012)。
文摘Numerical simulation is an essential technique for CO_(2)geological storage operations.However,highresolution geological models typically consist of a large number of grid blocks,making numerical simulations computationally expensive and time-consuming.Upscaling methods are commonly used to coarsen the fine-scale geological model,with global flow-based upscaling methods generally demonstrating the highest accuracy.However,since these methods require solving flow equations over the global domain,which is still time-consuming,their applications are typically limited to cases where the coarse model is reused repeatedly(e.g.,history matching or optimization).To overcome these limitations,this study develops a novel deep learning(DL)-based upscaling framework for the simulation of CO_(2)injection into saline aquifers.The framework incorporates convolutional neural networks(CNNs),Transformer encoders,and Fourier neural operators(FNOs)to construct surrogate models for upscaled well index,permeability,relative permeability,and capillary pressure.A preprocessing procedure is first applied to address the issue of inaccurate upscaled parameters,which are typically caused by weak flow conditions in traditional upscaling computations.Then the surrogate models are trained using relevant local information,and the trained surrogate models are used to replace traditional numerical upscaling computations,enabling instantaneous and parallel predictions of upscaled parameters.Two representative flow patterns(left-to-right and bottom-to-top)are considered to evaluate the framework's performance.The results demonstrate that the DL-based framework significantly improves computational efficiency,achieving a speedup factor of approximately 1133 times compared to traditional upscaling methods.Additionally,it maintains or even enhances simulation accuracy,as the surrogate models correct inaccurate upscaled parameters.
基金supported by China Postdoctoral Science Foundation(No.2023TQ0247)Shenzhen Science and Technology Program(No.JCYJ20220530140602005)+2 种基金the Fundamental Research Funds for the Central Universities(No.2042023kfyq03)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515111071)the Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(No.GZB20230544).
文摘Knowledge of the mechanical behavior of planetary rocks is indispensable for space explorations.The scarcity of pristine samples and the irregular shapes of planetary meteorites make it difficult to obtain representative samples for conventional macroscale rock mechanics experiments(macro-RMEs).This critical review discusses recent advances in microscale RMEs(micro-RMEs)techniques and the upscaling methods for extracting mechanical parameters.Methods of mineralogical and microstructural analyses,along with non-destructive mechanical techniques,have provided new opportunities for studying planetary rocks with unprecedented precision and capabilities.First,we summarize several mainstream methods for obtaining the mineralogy and microstructure of planetary rocks.Then,nondestructive micromechanical testing methods,nanoindentation and atomic force microscopy(AFM),are detailed reviewed,illustrating the principles,advantages,influencing factors,and available testing results from literature.Subsequently,several feasible upscaling methods that bridge the micro-measurements of meteorite pieces to the strength of the intact body are introduced.Finally,the potential applications of planetary rock mechanics research to guiding the design and execution of space missions are environed,ranging from sample return missions and planetary defense to extraterrestrial construction.These discussions are expected to broaden the understanding of the microscale mechanical properties of planetary rocks and their significant role in deep space exploration.
基金financial support provided by the Future Energy System at University of Alberta and NSERC Discovery Grant RGPIN-2023-04084。
文摘Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments.However,a robust and efficient geomechanical upscaling technique for heterogeneous geological reservoirs is lacking to advance the applications of three-dimensional(3D)reservoir-scale geomechanical simulation considering detailed geological heterogeneities.Here,we develop convolutional neural network(CNN)proxies that reproduce the anisotropic nonlinear geomechanical response caused by lithological heterogeneity,and compute upscaled geomechanical properties from CNN proxies.The CNN proxies are trained using a large dataset of randomly generated spatially correlated sand-shale realizations as inputs and simulation results of their macroscopic geomechanical response as outputs.The trained CNN models can provide the upscaled shear strength(R^(2)>0.949),stress-strain behavior(R^(2)>0.925),and volumetric strain changes(R^(2)>0.958)that highly agree with the numerical simulation results while saving over two orders of magnitude of computational time.This is a major advantage in computing the upscaled geomechanical properties directly from geological realizations without the need to perform local numerical simulations to obtain the geomechanical response.The proposed CNN proxybased upscaling technique has the ability to(1)bridge the gap between the fine-scale geocellular models considering geological uncertainties and computationally efficient geomechanical models used to assess the geomechanical risks of large-scale subsurface development,and(2)improve the efficiency of numerical upscaling techniques that rely on local numerical simulations,leading to significantly increased computational time for uncertainty quantification using numerous geological realizations.
基金supported by the National Natural Science Foundation of China (Grant Nos. 30370815 and 30470332)
文摘To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions with different rice variety types, and five to six sites in each region were selected. Then the eight genetic parameters of CERES-Rice, particularly the four parameters related to the yield, were modified and validated using the Trial and Error Method and the local statistical data of rice yield at a county level from 2001 to 2004, combined with the regional experiments of rice varieties in the province as well as the local meteorological and soil data （Method 1）. The simulated results of Method 1 were compared with those of other three traditional methods upscaling the genetic parameters, i.e., using one-site experimental data from a local representative rice variety （Method 2）, using local long-term rice yield data at a county level after deducting the trend yield due to progress of science and technology （Method 3）, and using rice yield data at a super scale, such as provincial, ecological zone, country or continent levels （Method 4）. The results showed that the best fitness was obtained by using the Method 1. The coefficients of correlation between the simulated yield and the statistical yield in the Method 1 were significant at 0.05 or 0.01 levels and the root mean squared error （RMSE） values were less than 9% for all the four rice regions. The method for upscaling the genetic parameters of CERES-Rice presented is not only valuable for the impact studies of climate change, but also favorable to provide a methodology for reference in crop model applications to the other regional studies.
文摘We present a general homogenization method a periodic heterogeneous material with piecewise constants for diffusion, heat conduction, and wave propagation in The method is relevant to the frequently encountered upscaling issues for heterogeneous materials. The dispersion relation for each problem is first expressed in the general form where the frequency co （or wavenumber k） is expanded in terms of the wavenumber k （or frequency ω）. A general homogenization model can be directly obtained with any given dispersion relation. Next step we study the unit cell of the heterogeneous material and derive the exact dispersion relation. The final homogenized equations include both leading order terms （effective properties） and high order contributions that represent the effect of the microscopic heterogeneity on the macroscopic behavior. That effect can be lumped into a single dimensionless heterogeneity parameter β, which is bounded between -1/12≤β≤ 0 and has a universal expression for all three problems. Numerical examples validate the proposed method and demonstrate a significant computational saving.
基金Petrobras’ financial support of this research and the permission of this publication
文摘We present a workflow for upscaling of rock properties using microtomography and percolation theory. In this paper we focus on a pilot study for assessing the plastic strength of rocks from a digital rock image. Firstly, we determine the size of mechanical representative volume ele- ment （RVE） by using upper/lower bound dissipation computations in accordance with thermody- namics. Then the mechanical RVE is used to simulate the rock failure at micro-scale using FEM. Two cases of different pressures of linear Drucker-Prager plasticity of rocks are computed to compute the macroscopic cohesion and the angle of internal friction of the rock. We also detect the critical exponents of yield stress for sealing laws from a series of derivative models that are created by a shrinking/expanding algorithm. We use microtomographic data sets of two carbonate samples and compare the results with previous results. The results show that natural rock samples with irregular structures may have the critical exponent of yield stress different from random models. This unexpected result could have significant ramifications for assessing the stability of solid materials with internal structure. Therefore our pilot study needs to be extended to investigate the scaling laws of strength of many more natural rocks with irregular microstructure.
文摘The main purpose of upscaling in reservoir simulation is to capture the dynamic behavior of fine scale models at the coarse scale. Traditional static or dynamic methods use assumptions about the boundary conditions to determine the upscaled properties, in this paper, we show that the upscaled properties are strongly dependent on the flow process observed at the fine scale. We use a simple no- crossflow depletion drive process and demonstrate that an upscaled property is not a constant value. Instead, if the goal is to match the performance of the fine scale model, the upscaled permeability changes with time. We provide an analytical solution to determine the upscaled permeability and present the value of upscaled permeability under limiting conditions. Our equation suggests that it is possible that upscaled value can fall outside the range of fine scale values under certain conditions. We show that for pseudo steady state flow, using common averaging methods like arithmetic or even geometric averaging methods can lead to optimistic results. We also show that the no-crossflow solution is significantly different than crossflow solution at late times. We validate our method by comparing the results of the method with flow simulation results in two and multi-layered models.
基金by the Program for Professor of Special Appointment(Eastern Scholar,No.TP2020009)at Shanghai Institutions of Higher Learning。
文摘We provide the capillary pressure curves p_(c)(s)as a function of the effective saturation s based on the theoretical framework of upscaling unsaturated flows in vertically heterogeneous porous layers proposed recently(Z.Zheng,Journal of Fluid Mechanics,950,A17,2022).Based on the assumption of vertical gravitational-capillary equilibrium,the saturation distribution and profile shape of the invading fluid can be obtained by solving a nonlinear integral-differential equation.The capillary pressure curves p_(c)(s)can then be constructed by systematically varying the injection rate.Together with the relative permeability curves k_(rn)(s)that are already obtained.One can now provide quick estimates on the overall behaviours of interfacial and unsaturated flows in vertically-heterogeneous porous layers.
文摘Describing the orientation state of the particles is often critical in fibre suspension applications.Macroscopic descriptors,the so-called second-order orientation tensor(or moment)leading the way,are often preferred due to their low computational cost.Closure problems however arise when evolution equations for the moments are derived from the orientation distribution functions and the impact of the chosen closure is often unpredictable.In this work,our aim is to provide macroscopic simulations of orientation that are cheap,accurate and closure-free.To this end,we propose an innovative data-based approach to the upscaling of orientation kinematics in the context of fibre suspensions.Since the physics at the microscopic scale can be modelled reasonably enough,the idea is to conduct accurate offline direct numerical simulations at that scale and to extract the corresponding macroscopic descriptors in order to build a database of scenarios.During the online stage,the macroscopic descriptors can then be updated quickly by combining adequately the items from the database instead of relying on an imprecise macroscopic model.This methodology is presented in the well-known case of dilute fibre suspensions(where it can be compared against closure-based macroscopic models)and in the case of suspensions of confined or electrically-charged fibres,for which state-of-the-art closures proved to be inadequate or simply do not exist.
文摘Upscaling of primary geological models with huge cells, especially in porous media, is the first step in fluid flow simulation. Numerical methods are often used to solve the models. The upscaling method must preserve the important properties of the spatial distribution of the reservoir properties. An grid upscaling method based on adaptive bandwidth in kernel function is proposed according to the spatial distribution of property. This type of upscaling reduces the number of cells, while preserves the main heterogeneity features of the original fine model. The key point of the paper is upscaling two reservoir properties simultaneously. For each reservoir feature, the amount of bandwidth or optimal threshold is calculated and the results of the upscaling are obtained. Then two approaches are used to upscaling two properties simultaneously based on maximum bandwidth and minimum bandwidth. In fact, we now have a finalized upscaled model for both reservoir properties for each approach in which not only the number of their cells, but also the locations of the cells are equal. The upscaling error of the minimum bandwidth approach is less than that of the maximum bandwidth approach.
基金Supported by the China National Science and Technology Major Project(2016ZX05031002-001)National Natural Science Foundation of China(41572081)Innovation Group of Hubei Province(2016CFA024)
文摘Based on the abundant core data of oil sands in the Mackay river in Canada,the termination frequency of muddy interlayers was counted to predict the extension range of interlayers using a queuing theory model,and then the quantitative relationship between the thickness and extension length of muddy interlayer was established.An equivalent upscaling method of geologic model based on tortuous paths under the effects of muddy interlayer has been proposed.Single muddy interlayers in each coarse grid are tracked and identified,and the average length,width and proportion of muddy interlayer in each coarse grid are determined by using the geological connectivity tracing algorithm.The average fluid flow length of tortuous path under the influence of muddy interlayer is calculated.Based on the Darcy formula,the formula calculating average permeability in the coarsened grid is deduced to work out the permeability of equivalent coarsened grid.The comparison of coarsening results of the oil sand reservoir of Mackay River with actual development indexes shows that the equivalent upscaling method of muddy interlayer by tortuous path calculation can reflect the blocking effect of muddy interlayer very well,and better reflect the effects of geological condition on production.
基金the support received from King Fahd University of Petroleum & Minerals through the DSR research Grant IN111046
文摘Simulation of reservoir flow processes at the finest scale is computationally expensive and in some cases impractical.Consequently,upscaling of several fine-scale grid blocks into fewer coarse-scale grids has become an integral part of reservoir simulation for most reservoirs.This is because as the number of grid blocks increases,the number of flow equations increases and this increases,in large proportion,the time required for solving flow problems.Although we can adopt parallel computation to share the load,a large number of grid blocks still pose significant computational challenges.Thus,upscaling acts as a bridge between the reservoir scale and the simulation scale.However as the upscaling ratio is increased,the accuracy of the numerical simulation is reduced;hence,there is a need to keep a balance between the two.In this work,we present a sensitivity-based upscaling technique that is applicable during history matching.This method involves partial homogenization of the reservoir model based on the model reduction pattern obtained from analysis of the sensitivity matrix.The technique is based on wavelet transformation and reduction of the data and model spaces as presented in the 2Dwp-wk approach.In the 2Dwp-wk approach,a set of wavelets of measured data is first selected and then a reduced model space composed of important wavelets is gradually built during the first few iterations of nonlinear regression.The building of the reduced model space is done by thresholding the full wavelet sensitivity matrix.The pattern of permeability distribution in the reservoir resulting from the thresholding of the full wavelet sensitivity matrix is used to determine the neighboring grids that are upscaled.In essence,neighboring grid blocks having the same permeability values due to model space reduction are combined into a single grid block in the simulation model,thus integrating upscaling with wavelet multiscale inverse modeling.We apply the method to estimate the parameters of two synthetic reservoirs.The history matching results obtained using this sensitivity-based upscaling are in very close agreement with the match provided by fine-scale inverse analysis.The reliability of the technique is evaluated using various scenarios and almost all the cases considered have shown very good results.The technique speeds up the history matching process without seriously compromising the accuracy of the estimates.
基金National Natural Science Foundation of China,Grant/Award Numbers:52573266,12574467Fundamental Research Funds for the Central Universities,Grant/Award Numbers:501RCQD2025158003,501XYGG2025158009State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,Grant/Award Number:LAPS2500。
文摘Lab-scale perovskite solar cells have shown ever-increasing power conversion efficiency in recent years.However,practical deployment is hindered by inferior device performance when upscaling from lab-scale cells to large-area modules.One such limitation originates from the poor thin-film quality of large-area modules.As a result,it is imperative to address the difficulties in fabricating high-quality perovskite absorbers.Herein,we analyze the fundamental challenges existing in large-area perovskite film fabrication,covering everything from crystal nucleation to thin-film growth and passivation.We then discuss a feasible roadmap to enhancing large-area modules through precursor chemistry strategies.These strategies encompass precursor design(solvent selection and additive engineering),drying process modulation(uniform drying,wide processing window,and high throughput),and annealing optimization(moderate annealing and thermal management).In addition,we examine the strengths and weaknesses of scalable deposition methods used in the present upscaling devices.This work provides strategic insights and practical guidelines for minimizing efficiency loss and accelerating the commercialization of perovskite photovoltaics.
基金supported by the Excellent Young Scholars Fund of Hebei Natural Science Foundation[No.D2023205012]Doctoral(Post-Doctoral)Research Startup Fund of Hebei Normal University[No.L2023B30]+1 种基金the National Natural Science Foundation of China[No.42101382,No.42201407]the Shandong Provincial Natural Science Foundation[No.ZR2020QD016,No.ZR2022QD120].
文摘Evapotranspiration(ET)plays a crucial role in the global water and energy cycle.Upscaling instantaneous ET(ET_(i))to daily ET(ET_(d))is vital for thermal-based ET estimation.Conventional methods-such as the constant evaporative fraction method(ConEF),radiation-based method,and evaporative ratio method-often overlook environmental factors,leading to biased estimates of ET_(d)from ET_(i).To resolve this issue,this study aimed to assess four machine learning(ML)algorithms-XGBoost,LightGBM,AdaBoost,and Random Forest-to integrate meteorological and remote sensing data for upscaling ETi across 88 global flux sites.Each ML model was tested with eight different variable combinations.Results indicated that XGBoost exhibited the best performance,with a root mean square error(RMSE)generally below 13 W m^(-2)in estimating ET_(d)from ET_(i).The best variable combination simultaneously considers evaporative fraction,available energy,meteorology factors,remote sensing albedo,normalized vegetation index,and leaf area index.Using this combination,the XGBoost model achieved an R^(2)=0.88 and an RMSE=12.33 W m^(-2),outperforming the ConEF method(R^(2)=0.71 and RMSE=18.86 Wm^(-2))and its expansions.These findings support the application of ML models in ET upscaling,enabling ET estimation across large spatiotemporal scales.
基金supported by the National Natural Science Foundation of China(52276196)the Foundation of State Key Laboratory of Coal Combustion(FSKLCCA2508)the High-level Talent Foundation of Anhui Agricultural University(rc412307).
文摘Flash Joule heating(FJH),as a high-efficiency and low-energy consumption technology for advanced materials synthesis,has shown significant potential in the synthesis of graphene and other functional carbon materials.Based on the Joule effect,the solid carbon sources can be rapidly heated to ultra-high temperatures(>3000 K)through instantaneous high-energy current pulses during FJH,thus driving the rapid rearrangement and graphitization of carbon atoms.This technology demonstrates numerous advantages,such as solvent-and catalyst-free features,high energy conversion efficiency,and a short process cycle.In this review,we have systematically summarized the technology principle and equipment design for FJH,as well as its raw materials selection and pretreatment strategies.The research progress in the FJH synthesis of flash graphene,carbon nanotubes,graphene fibers,and anode hard carbon,as well as its by-products,is also presented.FJH can precisely optimize the microstructures of carbon materials(e.g.,interlayer spacing of turbostratic graphene,defect concentration,and heteroatom doping)by regulating its operation parameters like flash voltage and flash time,thereby enhancing their performances in various applications,such as composite reinforcement,metal-ion battery electrodes,supercapacitors,and electrocatalysts.However,this technology is still challenged by low process yield,macroscopic material uniformity,and green power supply system construction.More research efforts are also required to promote the transition of FJH from laboratory to industrial-scale applications,thus providing innovative solutions for advanced carbon materials manufacturing and waste management toward carbon neutrality.
基金This research is jointly supported by the National Basic Research Program of China under Grant 2013CB733401the Natural Science Foundation of China under Grant nos.41671363 and 91125003.
文摘One of the essential steps for satellite albedo validation is upscaling in situ measurements to corresponding pixel scale over relatively heterogeneous land surfaces.Although the multi-scale validation strategy is applicable for heterogeneous surfaces,the calibration of the high-resolution imagery during upscaling process is never perfect,and thus the upscaling results suffer from errors.The regression-kriging(RK)technique can compensate the calibration part by applying kriging to upscale residuals and produce more accurate upscaling results.In this paper,in situ measurements and high spatial resolution albedo imagery combined with RK technique was proposed.This method is illustrated by upscaling surface albedo from in situ measurements scale to the coarse pixel scale in the core experimental area of HiWATER,where 17 WSN nodes were deployed at heterogeneous area.The upscaling results of this method were compared with the upscaling results from multi-scale strategy.The results show that the upscaling method based on in situ measurements and high-resolution imagery combined with RK technique can capture the spatial characteristics of surface albedo better.Further,an attempt was made to expand this method in time series.Finally,a preliminary validation of the Moderate Resolution Imaging Spectroradiometer albedo product was performed as the tentative application.
文摘We review some of our recent efforts in developing upscaling methods for simulating the flow transport through heterogeneous porous media. In particular, the steady flow transport through highly heterogeneous porous media driven by extraction wells and the flow transport through unsaturated porous media will be considered.
基金This research is jointly supported by the National Basic Research Program of China[grant number 2013CB733401]the National Natural Science Foundation of China[grant numbers 41671363 and 91125003].
文摘Upscaling ground albedo is challenged by the serious discrepancy between the heterogeneity of land surfaces and the small number of ground-based measurements.Conventional ground-based measurements cannot provide sufficient information on the characteristics of surface albedo at the scale of coarse pixels over heterogeneous land surfaces.One method of overcoming this problem is to introduce high-resolution albedo imagery as ancillary information for upscaling.However,due to the low frequency of updating of high-resolution albedo maps,upscaling time series of ground-based albedo measurements is difficult.This paper proposes a method that is based on the idea of conceptual universal scaling methodology for establishing a spatiotemporal trend surface using very few high-resolution images and time series of ground-based measurements for spatial-temporal upscaling of albedo.The construction of the spatiotemporal trend surface incorporates the spatial information provided by auxiliary remote sensing images and the temporal information provided by long time series of ground observations.This approach was illustrated by upscaling ground-based fine-scale albedo measurements to a coarse scale over the core study area in HiWATER.The results indicate that this method can characterize the spatiotemporal variations in surface albedo well,and the overall correlation coefficient was 0.702 during the study period.
