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
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
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
One-class classification problem has become a popular problem in many fields, with a wide range of applications in anomaly detection, fault diagnosis, and face recognition. We investigate the one-class classification ...One-class classification problem has become a popular problem in many fields, with a wide range of applications in anomaly detection, fault diagnosis, and face recognition. We investigate the one-class classification problem for second-order tensor data. Traditional vector-based one-class classification methods such as one-class support vector machine (OCSVM) and least squares one-class support vector machine (LSOCSVM) have limitations when tensor is used as input data, so we propose a new tensor one-class classification method, LSOCSTM, which directly uses tensor as input data. On one hand, using tensor as input data not only enables to classify tensor data, but also for vector data, classifying it after high dimensionalizing it into tensor still improves the classification accuracy and overcomes the over-fitting problem. On the other hand, different from one-class support tensor machine (OCSTM), we use squared loss instead of the original loss function so that we solve a series of linear equations instead of quadratic programming problems. Therefore, we use the distance to the hyperplane as a metric for classification, and the proposed method is more accurate and faster compared to existing methods. The experimental results show the high efficiency of the proposed method compared with several state-of-the-art methods.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
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
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
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 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One-class classification problem has become a popular problem in many fields, with a wide range of applications in anomaly detection, fault diagnosis, and face recognition. We investigate the one-class classification problem for second-order tensor data. Traditional vector-based one-class classification methods such as one-class support vector machine (OCSVM) and least squares one-class support vector machine (LSOCSVM) have limitations when tensor is used as input data, so we propose a new tensor one-class classification method, LSOCSTM, which directly uses tensor as input data. On one hand, using tensor as input data not only enables to classify tensor data, but also for vector data, classifying it after high dimensionalizing it into tensor still improves the classification accuracy and overcomes the over-fitting problem. On the other hand, different from one-class support tensor machine (OCSTM), we use squared loss instead of the original loss function so that we solve a series of linear equations instead of quadratic programming problems. Therefore, we use the distance to the hyperplane as a metric for classification, and the proposed method is more accurate and faster compared to existing methods. The experimental results show the high efficiency of the proposed method compared with several state-of-the-art methods.
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.
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.
