Statistical prediction is often required in reservoir simulation to quantify production uncertainty or assess potential risks.Most existing uncertainty quantification procedures aim to decompose the input random field...Statistical prediction is often required in reservoir simulation to quantify production uncertainty or assess potential risks.Most existing uncertainty quantification procedures aim to decompose the input random field to independent random variables,and may suffer from the curse of dimensionality if the correlation scale is small compared to the domain size.In this work,we develop and test a new approach,K-means clustering assisted empirical modeling,for efficiently estimating waterflooding performance for multiple geological realizations.This method performs single-phase flow simulations in a large number of realizations,and uses K-means clustering to select only a few representatives,on which the two-phase flow simulations are implemented.The empirical models are then adopted to describe the relation between the single-phase solutions and the two-phase solutions using these representatives.Finally,the two-phase solutions in all realizations can be predicted using the empirical models readily.The method is applied to both 2D and 3D synthetic models and is shown to perform well in the P10,P50 and P90 of production rates,as well as the probability distributions as illustrated by cumulative density functions.It is able to capture the ensemble statistics of the Monte Carlo simulation results with a large number of realizations,and the computational cost is significantly reduced.展开更多
Main problem of modern climatology is to assess the present as well as future climate change, For this aim two approaches are used: physic-mathematic modeling on the basis of GCMs and palaeoclimatic analogues. The thi...Main problem of modern climatology is to assess the present as well as future climate change, For this aim two approaches are used: physic-mathematic modeling on the basis of GCMs and palaeoclimatic analogues. The third approach is based on the empirical-statistical methodology and is developed in this paper. This approach allows to decide two main problems: to give a real assessment of climate changes by observed data for climate monitoring and extrapolation of obtained climate tendencies to the nearest future (10-15 years) and give the empirical basis for further development of physic-mathematical models. The basic theory and methodology of empirical-statistic approach have been developed as well as a common model for description of space-time climate variations taking into account the processes of different time scales. The way of decreasing of the present and future uncertainty is suggested as the extraction of long-term climate changes components in the particular time series and spatial generalization of the same climate tendencies in the obtained homogeneous regions. Algorithm and methods for realization of empirical-statistic methodology have been developed along with methods for generalization of intraannual fluctuations, methods for extraction of homogeneous components of different time scales (interannual, decadal, century), methodology and methods for spatial generalization and modeling, methods for extrapolation on the basis of two main kinds of time models: stochastic and deterministic-stochastic. Some applications of developed methodology and methods are given for the longest time series of temperature and precipitation over the world and for spatial generalization over the European area.展开更多
The global sustainability plan for future development relies on solar radiation which is the main source of renewable energy. Thus, this work studies the performance of six models to estimate global solar radiation on...The global sustainability plan for future development relies on solar radiation which is the main source of renewable energy. Thus, this work studies the performance of six models to estimate global solar radiation on a horizontal surface for the Abeche site in Chad. The data used in this work were collected at the General Directorate of National Meteorology of Chad. The reliability and accuracy of different models for estimating global solar radiation were validated by statistical indicators to identify the most accurate model. The results show that among all the models, the Sabbagh model has the best performance in estimating the global solar radiation. The average is 6.354 kWh/m<sup>2</sup> with an average of -3.704%. This model is validated against NASA data which is widely used.展开更多
Many problems in rock engineering are limited by our imperfect knowledge of the material properties and failure mechanics of rock masses. Mining problems are somewhat unique, however, in that plenty of real world expe...Many problems in rock engineering are limited by our imperfect knowledge of the material properties and failure mechanics of rock masses. Mining problems are somewhat unique, however, in that plenty of real world experience is generally available and can be turned into valuable experimental data.Every pillar that is developed, or stope that is mined, represents a full-scale test of a rock mechanics design. By harvesting these data, and then using the appropriate statistical techniques to interpret them,mining engineers have developed powerful design techniques that are widely used around the world.Successful empirical methods are readily accepted because they are simple, transparent, practical, and firmly tethered to reality. The author has been intimately associated with empirical design for his entire career, but his previous publications have described the application of individual techniques to specific problems. The focus of this paper is the process used to develop a successful empirical method. A sixstage process is described: identification of the problem, and of the end users of the final product; development of a conceptual rock mechanics model, and identification of the key parameters in that model;identification of measures for each of the key parameters, and the development of new measures(such as rating scales) where necessary; data sources and data collection; statistical analysis; and packaging of the final product. Each of these stages has its own potential rewards and pitfalls, which will be illustrated by incidents from the author's own experience. The ultimate goal of this paper is to provide a new and deeper appreciation for empirical techniques, as well as some guidelines and opportunities for future developers.展开更多
基金the funding supported by Beijing Natural Science Foundation(Grant No.3222037)the PetroChina Innovation Foundation(Grant No.2020D-5007-0203)by the Science Foundation of China University of Petroleum,Beijing(Nos.2462021YXZZ010,2462018QZDX13,and 2462020YXZZ028)
文摘Statistical prediction is often required in reservoir simulation to quantify production uncertainty or assess potential risks.Most existing uncertainty quantification procedures aim to decompose the input random field to independent random variables,and may suffer from the curse of dimensionality if the correlation scale is small compared to the domain size.In this work,we develop and test a new approach,K-means clustering assisted empirical modeling,for efficiently estimating waterflooding performance for multiple geological realizations.This method performs single-phase flow simulations in a large number of realizations,and uses K-means clustering to select only a few representatives,on which the two-phase flow simulations are implemented.The empirical models are then adopted to describe the relation between the single-phase solutions and the two-phase solutions using these representatives.Finally,the two-phase solutions in all realizations can be predicted using the empirical models readily.The method is applied to both 2D and 3D synthetic models and is shown to perform well in the P10,P50 and P90 of production rates,as well as the probability distributions as illustrated by cumulative density functions.It is able to capture the ensemble statistics of the Monte Carlo simulation results with a large number of realizations,and the computational cost is significantly reduced.
文摘Main problem of modern climatology is to assess the present as well as future climate change, For this aim two approaches are used: physic-mathematic modeling on the basis of GCMs and palaeoclimatic analogues. The third approach is based on the empirical-statistical methodology and is developed in this paper. This approach allows to decide two main problems: to give a real assessment of climate changes by observed data for climate monitoring and extrapolation of obtained climate tendencies to the nearest future (10-15 years) and give the empirical basis for further development of physic-mathematical models. The basic theory and methodology of empirical-statistic approach have been developed as well as a common model for description of space-time climate variations taking into account the processes of different time scales. The way of decreasing of the present and future uncertainty is suggested as the extraction of long-term climate changes components in the particular time series and spatial generalization of the same climate tendencies in the obtained homogeneous regions. Algorithm and methods for realization of empirical-statistic methodology have been developed along with methods for generalization of intraannual fluctuations, methods for extraction of homogeneous components of different time scales (interannual, decadal, century), methodology and methods for spatial generalization and modeling, methods for extrapolation on the basis of two main kinds of time models: stochastic and deterministic-stochastic. Some applications of developed methodology and methods are given for the longest time series of temperature and precipitation over the world and for spatial generalization over the European area.
文摘The global sustainability plan for future development relies on solar radiation which is the main source of renewable energy. Thus, this work studies the performance of six models to estimate global solar radiation on a horizontal surface for the Abeche site in Chad. The data used in this work were collected at the General Directorate of National Meteorology of Chad. The reliability and accuracy of different models for estimating global solar radiation were validated by statistical indicators to identify the most accurate model. The results show that among all the models, the Sabbagh model has the best performance in estimating the global solar radiation. The average is 6.354 kWh/m<sup>2</sup> with an average of -3.704%. This model is validated against NASA data which is widely used.
文摘Many problems in rock engineering are limited by our imperfect knowledge of the material properties and failure mechanics of rock masses. Mining problems are somewhat unique, however, in that plenty of real world experience is generally available and can be turned into valuable experimental data.Every pillar that is developed, or stope that is mined, represents a full-scale test of a rock mechanics design. By harvesting these data, and then using the appropriate statistical techniques to interpret them,mining engineers have developed powerful design techniques that are widely used around the world.Successful empirical methods are readily accepted because they are simple, transparent, practical, and firmly tethered to reality. The author has been intimately associated with empirical design for his entire career, but his previous publications have described the application of individual techniques to specific problems. The focus of this paper is the process used to develop a successful empirical method. A sixstage process is described: identification of the problem, and of the end users of the final product; development of a conceptual rock mechanics model, and identification of the key parameters in that model;identification of measures for each of the key parameters, and the development of new measures(such as rating scales) where necessary; data sources and data collection; statistical analysis; and packaging of the final product. Each of these stages has its own potential rewards and pitfalls, which will be illustrated by incidents from the author's own experience. The ultimate goal of this paper is to provide a new and deeper appreciation for empirical techniques, as well as some guidelines and opportunities for future developers.
