A coupled model for multiphase fluid flow and sedimentation deformation in oil reservoir and its numerical simulation

A mathematical model for coupled multiphase fluid flow and sedimentation deformation is developed based on fluid-solid interaction mechanism. A finite difference-finite element numerical approach is presented. The results of an example show that the fluid-solid coupled effect has great influence on multiphase fluid flow and reservoir recovery performances, and the coupled model has practical significance for oilfield development.

Simulating a typhoon storm surge in the East Sea of China using a coupled model

A coupled numerical model with a 2' x 2' resolution grid has been developed and used to simulate five typical typhoon storm surges (5612, 7413, 7910, 8114, and 9711) in the East Sea of China. Three main driving forces have been considered in this coupled model: wave radiation stress, combined wave-current bottom shear stress and wave-state-dependent surface wind stress. This model has then been compared with in situ measurements of the storm set-up. The effect of different driving force components on the total storm surge has also been investigated. This study has found that the coupled model with high resolution is capable of simulating the five typical typhoons better than the uncoupled models, and that the wave-dependent surface wind stress plays an important role in typhoon storm surge-wave coupling in this area and can increase the storm set-up by 1 m. The study of the five typhoon cases has shown that the general coupling effects could increase storm set-up by 20-32%. Thus, it is suggested that to predict typhoon storm surges in the East Sea of China, a storm surge-wave coupled model be adopted. (C) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

A model study on carbon cycle and phytoplankton dynamical processes in the Bohai Sea

The carbon cycle of lower trophic level in the Bohai Sea is studied with a three-dimension-al biological and physical coupled model. The influences of the processes (including horizontal advection,river nutrient load, active transport etc. ) on the phytoplankton biomass and its evolution are estimated.The Bohai Sea is a weak sink of the CO2 in the atmosphere. During the cycle, 13.7% of the gross pro-duction of the phytoplankton enter the higher trophic level and 76.8 % of it are consumed by the respira-tion itself. The nutrient reproduction comes mainly from the internal biogeochemical loop and the rem-ineralization is an important mechanism of the nutrient transfer from organic form to inorganic. Horizon-tal advection decreases the total biomass and the eutrophication in some sea areas. Change in the nutrientload of a river can only adjust the local system near its estuary. Controlling the input of the nutrient,which limits the alga growth, can be very useful in lessening the phytoplankton biomass.

Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model

With the intermediate-complexity Zebiak-Cane model, we investigate the 'spring predictability barrier' (SPB) problem for El Nino events by tracing the evolution of conditional nonlinear optimal perturbation (CNOP), where CNOP is superimposed on the El Nino events and acts as the initial error with the biggest negative effect on the El Nino prediction. We show that the evolution of CNOP-type errors has obvious seasonal dependence and yields a significant SPB, with the most severe occurring in predictions made before the boreal spring in the growth phase of El Nino. The CNOP-type errors can be classified into two types: one possessing a sea-surface-temperature anomaly pattern with negative anomalies in the equatorial central-western Pacific, positive anomalies in the equatorial eastern Pacific, and a thermocline depth anomaly pattern with positive anomalies along the Equator, and another with patterns almost opposite to those of the former type. In predictions through the spring in the growth phase of El Nino, the initial error with the worst effect on the prediction tends to be the latter type of CNOP error, whereas in predictions through the spring in the decaying phase, the initial error with the biggest negative effect on the prediction is inclined to be the former type of CNOP error. Although the linear singular vector (LSV)-type errors also have patterns similar to the CNOP-type errors, they cover a more localized area than the CNOP-type errors and cause a much smaller prediction error, yielding a less significant SPB. Random errors in the initial conditions are also superimposed on El Nino events to investigate the SPB. We find that, whenever the predictions start, the random errors neither exhibit an obvious season-dependent evolution nor yield a large prediction error, and thus may not be responsible for the SPB phenomenon for El Nino events. These results suggest that the occurrence of the SPB is closely related to particular initial error patterns. The two kinds of CNOP-type error are most likely to cause a significant SPB. They have opposite signs and, consequently, opposite growth behaviours, a result which may demonstrate two dynamical mechanisms of error growth related to SPB: in one case, the errors grow in a manner similar to El Nino; in the other, the errors develop with a tendency opposite to El Nino. The two types of CNOP error may be most likely to provide the information regarding the 'sensitive area' of El Nino-Southern Oscillation (ENSO) predictions. If these types of initial error exist in realistic ENSO predictions and if a target method or a data assimilation approach can filter them, the ENSO forecast skill may be improved. Copyright (C) 2009 Royal Meteorological Society

Numerical Simulation of the Flow Field and Concentration Distribution in the Bulk Growth of Silicon Carbide Crystals

The physical vapor transport (PVT) method is being widely used to grow large-size single SiC crystals. The growth process is associated with heat and mass transport in the growth chamber, chemical reactions among multiple species as well as phase change at the crystal/gas interface. The current paper aims at studying and verifying the transport mechanism and growth kinetics model by demonstrating the flow field and species concentration distribution in the growth system. We have developed a coupled model, which takes into account the mass transport and growth kinetics. Numerical simulation is carried out by employing an in-house developed software based on finite volume method. The results calculated are in good agreement with the experimental observation.

Numerical Simulation of the Flow Field and Concentration Distribution in the Bulk Growth of Silicon Carbide Crystals

The physical vapor transport (PVT) method is being widely used to grow large-size single SiC crystals. The growth process is associated with heat and mass transport in the growth chamber, chemical reactions among multiple species as well as phase change at the crystal/gas interface. The current paper aims at studying and verifying the transport mechanism and growth kinetics model by demonstrating the flow field and species concentration distribution in the growth system. We have developed a coupled model, which takes into account the mass transport and growth kinetics. Numerical simulation is carried out by employing an in-house developed software based on finite volume method. The results calculated are in good agreement with the experimental observation.

Tidally induced upwelling off Yangtze River estuary and in Zhejiang coastal waters in summer

MASNUM wave-tide-circulation coupled numerical model (MASNUM coupled model, hereinafter) is developed based on the Princeton Ocean Model (POM). Both POM and MASNUM coupled model are applied in the numerical simulation of the upwelling off Yangtze River estuary and in Zhejiang coastal waters in summer. The upwelling mechanisms are analyzed from the viewpoint of tide, and a new mechanism is proposed. The study suggests that the tidally inducing mechanism of the upwelling includes two dynamic aspects: the barotropic and the baroclinic process. On the one hand, the residual currents induced by barotropic tides converge near the seabed, and upwelling is generated to maintain mass conservation. The climbing of the residual currents along the sea bottom slope also contributes to the upwelling. On the other hand, tidal mixing plays a very important role in inducing the upwelling in the baroclinic sea circumstances. Strong tidal mixing leads to conspicuous front in the coastal waters. The considerable horizontal density gradient across the front elicits a secondary circulation clinging to the tidal front, and the upwelling branch appears near the frontal zone. Numerical experiments are designed to determine the importance of tide in inducing the upwelling. The results indicate that tide is a key and dominant inducement of the upwelling. Experiments also show that coupling calculation of the four main tidal constituents(M-2, S-2, K-1, and O-1), rather than dealing with the single M-2 constituent, improves the modeling precision of the barotropic tide-induced upwelling.

五种红树植物光合产量模型及对环境因子的响应

以木榄（Bruguiera gymnorriza）、白骨壤（Avicennia marina）、桐花树（Aegiceras corniculata）、秋茄（Kandelia candel）和海漆（Excoecaria agallocha）为对象，以光合作用对环境因子的响应为主线，建立了从叶片水平到群体冠层水平上的光合产量模型，探讨了从器官、个体到群体的光合产量对环境因子响应的定量关系。 将Farquhar提出的单叶片光合作用生理生化模型与气孔导度B-B模型相结合，建立了光合作用－气孔导度耦合模型。模型模拟结果与实际测量结果具有较好的一致性。在温度为25.0℃，光合有效辐射为1000μmol•m-2s-1 的条件下，当外部CO2浓度倍增到720μmol•mol-1时，白骨壤、木榄、桐花树、秋茄、海漆的光合速率分别提高22.56%，17.13%，18.43%，18.63%和18.41%。在大气CO2浓度和光合有效辐射通量密度不变的条件下，光合作用速率对温度的响应呈单峰型曲线，即有一个最适温度，5种红树植物的最适温度值均为26.5℃左右。大气CO2浓度和温度固定不变（分别为350μmol•mol-1和25.0 ℃）时，光合作用对光合有效辐射的响应符合Michaelis-Menten反应曲线，模型在PAR<1800μmol•m-2s-1时模拟精度较高（P<0.01）。 在典型晴天条件下，5种红树植物的光合速率日变化都出现两个极大值（分别在11时和15时左右），中午前后光合速率较低，模型模拟光合速率日变化与实测数值日变化趋势一致。本模型能较好地模拟5种红树植物光合产量以及对环境因子的响应，模拟预测精度较高（P<0.01）。 以Ross和Nilson叶倾角分布模型为基础，分别建立了直接辐射和散射辐射在冠层内传输的子模型。冠层内的消光系数均有明显的日变化，且上午8时之前和下午16时之后随时间变化较大。在典型晴天条件下，单位土地面积日合成干物质总量（折合为CH2O）白骨壤为15.840g•m-2d-1，对于木榄、桐花树、秋茄、海漆其相应的值分别为 22.254 g•m-2d-1， 23.610 g•m-2d-1，24.525 g•m-2d-1和25.996 g•m-2d-1 。

岩石中地震波速度和衰减的应力变化响应研究

Stress change is one of key factors in seismic nucleating and triggering; therefore for understanding and forecasting earthquakes, it is necessary to research on stress status and its changes in rocks. Propagating in underground structures, wave velocity and attenuation contain information on stress changes of the Earth’s interior. For a better understanding of relationship between seismic data and stress changes, modeling and ultrasonic test supply significant references. In this article, acoustoelastic theory is introduced to explain nonlinear elastic characteristics of rocks. Based on the acoustoelastic theory, a solid-fluid coupled model is given to calculate velocity under different stress for porous and liquid fulfilled rocks. Except for the stress-velocity relationship, effects of pore pressure induced stress changes on ultrasonic coda attenuation are also studied. Intrinsic attenuation quality factors are calculated for a comparison purpose. Finally, the relationship between elastic constants and stress changes is thoroughly investigated, a mixture model from two phases of Hooke media is introduced to explain the differences between dynamic and static moduli, a relation among wave length, wave velocities and elastic moduli considering dimension of microstructure, dimension and state of surface between phases is presented. The most important aspect of this work is exploring and establishing relationships between the seismic properties of rocks and changes of their stress conditions, which will have its application in earthquake forecast and seismic hazard.

基于盆地地下水模型与山区地表水模型耦合的济源盆地地下水模拟研究

The aim of this study is to increase the precision of groundwater modeling. The way is use the distributed model calculate the mountain basin groundwater lateral discharge and the river runoff. With appropriate technique help, the groundwater model can couple the distributed model results. This paper’s study object is makeing the distributed hydrological model HEC-HMS coupled to the popular groundwater model Visual MODFLOW. The application example is Jiyuan basin which is a typical basin of North China. HEC-HMS can calculate the surface runoff and subsurface runoff at mountain-pass. The subsurface runoff can turn to recharge well straightly. The water level - runoff course and Trial method is used to back analyze the parameters of surface runoff to Visual MODFLOW. So the distributed hydrological model can coupled to the groundwater model. The research proved that base on couple the distributed surface water model the groundwater model’s results are notability improved. The example is Jiyuan basin where use the distributed model coupled to the groundwater model. On the base of the coupled model applied to Jiyuan basin groundwater modeling. The paper estimates the groundwater change in the study area. Then, by use the water resources integrated planning results, the article calculate the basin groundwater can be development and utilization quantity and potential.

地理信息系统支持下的滑坡灾害空间分析预测-以云南小江流域为例

As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.