928 resultados para Flood forecasting.
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IEECAS SKLLQG
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This article reports on the performance of a bismuth-coated carbon microdisk electrode (BiFμE) for the determination of trace heavy metals by anodic stripping voltammetry (ASV). The BiFμE was prepared by electrodeposition of a metallic bismuth film onto the microdisk, by applying an in-situ electroplating procedure. To test the performance of the BiFμE, ASV measurements were performed on synthetic solutions containing Cd2+, Pb2+, and Cu2+ as target ions. The results indicated that cadmium and lead gave well-defined ASV peaks with no interference, and their quantitative determination could be carried out straightforwardly. In particular, linear calibration curves over the range 5.0 x 10-8-1.0 x 10-6M for both ions, and detection limits of 7.8 and 2.9 nM, for cadmium and lead, respectively, after applying a 60 sec preconcentration step, were obtained. The reproducibility was also satisfactory, the relative standard deviation (RSD) being within 2.5% for both ions. Copper, instead, gave an ASV response that. in most experimental conditions, overlapped with that of bismuth. This circumstance made the determination of copper at the BiFμE difficult. Since the latter element could be detected reliably at the uncoated carbon microdisk electrode (CμE), both BiFμE and CμE were employed, respectively, for the determination of lead and copper ions in drinking water, wine, and tomato sauce.
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The grey system theory studies the uncertainty of small sample size problems. This paper using grey system theory in the deformation monitoring field, based on analysis of present grey forecast models, developed the spatial multi-point model. By using residual modification, the spatial multi-point residual model eras developed in further study. Then, combined with the sedimentation data of Xiaolangdi Multipurpose Dam, the results are compared and analyzed, the conclusion has been made and the advantages of the residual spatial multi-point model has been proved.
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3DMove software, based on the three-dimension structural model of geologic interpretation, can forecast reservoir cracks from the point of view of formation of the structural geology, and analyze the characteristics of the cracks. 3DMove software dominates in forecasting cracks. We forecast the developments and directions of the cracks in Chengbei buried hill with the application of forecasting technique in 3DMove software, and obtain the chart about strain distributing on top in buried hill and the chart about relative density and orientation and the chart about the analysis of crack unsealing. In Chengbei 30 buried hill zone, north-west and north-east and approximately east-west cracks in Cenozoic are very rich and the main directions in every fault block are different. Forecasting results that are also verified by those of drilling approximately accord with the data from well logging, the case of which shows that the technique has the better ability in forecasting cracks, and takes more effects on exploration and exploitation of crack reservoir beds in ancient buried hill reservoirs.
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In order to developing reservoir of Upper of Ng at high-speed and high-efficient in Chengdao oilfield which is located in the bally shallow sea, the paper builds up a series of theory and means predicting and descripting reservoir in earlier period of oilfield development. There are some conclusions as follows. 1. It is the first time to form a series of technique of fine geological modeling of the channel-sandy reservoir by means of mainly seismic methods. These technique include the logging restriction seismic inversion, the whole three dimension seismic interpretation, seismic properties analysis and so on which are used to the 3-dimension distributing prediction of sandy body, structure and properties of the channel reservoir by a lot of the seismic information and a small quantity of the drilling and the logging information in the earlier stage of the oil-field development. It is the first time that these methods applied to production and the high-speed development of the shallow sea oilfield. The prediction sandy body was modified by the data of new drilling, the new reservoir prediction thinking of traced inversion is built. The applied effect of the technique was very well, according to approximately 200 wells belonging to 30 well groups in Chengdao oilfield, the drilling succeeded rate of the predicting sandy body reached 100%, the error total thickness only was 8%. 2. The author advanced the thinking and methods of the forecasting residual-oil prediction at the earlier stage of production. Based on well data and seismic data, correlation of sediment units was correlated by cycle-correlation and classification control methods, and the normalization and finely interpretation of the well logging and sedimentation micro-facies were acquired. On the region of poor well, using the logging restriction inversion technique and regarding finished drilling production well as the new restriction condition, the sand body distributing and its property were predicted again and derived 3-dimension pool geologic model including structure, reservoir, fluid, reservoir engineering parameter and producing dynamic etc. According to the reservoir geologic model, the reservoir engineering design was optimized, the tracking simulation of the reservoir numerical simulation was done by means of the dynamic data (pressure, yield and water content) of development well, the production rule and oil-water distributing rule was traced, the distributing of the remaining oil was predicted and controlled. The dynamic reservoir modeling method in metaphase of development was taken out. Based on the new drilling data, the static reservoir geologic model was momentarily modified, the research of the flow units was brought up including identifying flow units, evaluating flow units capability and establishing the fine flow units model; according to the dynamic data of production and well testing data, the dynamic tracing reservoir description was realized through the constant modification of the reservoir geologic model restricted these dynamic data by the theory of well testing and the reservoir numerical simulation. It was built the dynamic tracing reservoir model, which was used to track survey of the remaining oil on earlier period. The reservoir engineering tracking analysis technique on shallow sea oilfield was founded. After renewing the structure history since tertiary in Chengdao area by the balance section technique and estimating the activity character of the Chengbei fault by the sealing fault analysis technique, the meandering stream sediment pattern of the Upper of Ng was founded in which the meandering border was the uppermost reservoir unit. Based on the specialty of the lower rock component maturity and the structure maturity, the author founded 3 kinds of pore structure pattern in the Guanshang member of Chengdao oil-field in which the storing space mainly was primary (genetic) inter-granular pore, little was secondary solution pore and the inter-crystal pore tiny pore, and the type of throat mainly distributed as the slice shape and the contract neck shape. The positive rhythmic was briefly type included the simple positive rhythm, the complex positive rhythm and the compound rhythm. Interbed mainly is mudstone widely, the physical properties and the calcite interbed distribute localized. 5. The author synthetically analyzed the influence action of the micro-heterogeneity, the macro-heterogeneity and the structure heterogeneity to the oilfield water flood development. The efficiency of water flood is well in tiny structure of convex type or even type at top and bottom in which the water breakthrough of oil well is soon at the high part of structure when inject at the low part of structure, and the efficiency of water flood is poor in tiny structure of concave type at top and bottom. The remaining oil was controlled by sedimentary facies; the water flooding efficiency is well in the border or channel bar and is bad in the floodplain or the levee. The separation and inter layer have a little influence to the non-obvious positive rhythm reservoir, in which the remaining oil commonly locate within the 1-3 meter of the lower part of the separation and inter layer with lower water flooding efficiency.
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Hulun Lake, China’s fifth-largest inland lake, experienced severe declines in water level in the period of 2000-2010. This has prompted concerns whether the lake is drying up gradually. A multi-million US dollar engineering project to construct a water channel to transfer part of the river flow from a nearby river to maintain the water level was completed in August 2010. This study aimed to advance the understanding of the key processes controlling the lake water level variation over the last five decades, as well as investigate the impact of the river transfer engineering project on the water level. A water balance model was developed to investigate the lake water level variations over the last five decades, using hydrological and climatic data as well as satellite-based measurements and results from land surface modelling. The investigation reveals that the severe reduction of river discharge (- 364±64 mm/yr, ~70% of the five-decade average) into the lake was the key factor behind the decline of the lake water level between 2000 and 2010. The decline of river discharge was due to the reduction of total runoff from the lake watershed. This was a result of the reduction of soil moisture due to the decrease of precipitation (-49±45 mm/yr) over this period. The water budget calculation suggests that the groundwater component from the surrounding lake area as well as surface run off from the un-gauged area surrounding the lake contributed ~ net 210 Mm3/yr (equivalent to ~ 100 mm/yr) water inflows into the lake. The results also show that the water diversion project did prevent a further water level decline of over 0.5 m by the end of 2012. Overall, the monthly water balance model gave an excellent prediction of the lake water level fluctuation over the last five decades and can be a useful tool to manage lake water resources in the future.
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Grattan, J. Pollution and paradigms: Lessons from Icelandic volcanism for continental flood basalt studies. Lithos. 2005. 79 pp 343-353
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Wind energy is the energy source that contributes most to the renewable energy mix of European countries. While there are good wind resources throughout Europe, the intermittency of the wind represents a major problem for the deployment of wind energy into the electricity networks. To ensure grid security a Transmission System Operator needs today for each kilowatt of wind energy either an equal amount of spinning reserve or a forecasting system that can predict the amount of energy that will be produced from wind over a period of 1 to 48 hours. In the range from 5m/s to 15m/s a wind turbine’s production increases with a power of three. For this reason, a Transmission System Operator requires an accuracy for wind speed forecasts of 1m/s in this wind speed range. Forecasting wind energy with a numerical weather prediction model in this context builds the background of this work. The author’s goal was to present a pragmatic solution to this specific problem in the ”real world”. This work therefore has to be seen in a technical context and hence does not provide nor intends to provide a general overview of the benefits and drawbacks of wind energy as a renewable energy source. In the first part of this work the accuracy requirements of the energy sector for wind speed predictions from numerical weather prediction models are described and analysed. A unique set of numerical experiments has been carried out in collaboration with the Danish Meteorological Institute to investigate the forecast quality of an operational numerical weather prediction model for this purpose. The results of this investigation revealed that the accuracy requirements for wind speed and wind power forecasts from today’s numerical weather prediction models can only be met at certain times. This means that the uncertainty of the forecast quality becomes a parameter that is as important as the wind speed and wind power itself. To quantify the uncertainty of a forecast valid for tomorrow requires an ensemble of forecasts. In the second part of this work such an ensemble of forecasts was designed and verified for its ability to quantify the forecast error. This was accomplished by correlating the measured error and the forecasted uncertainty on area integrated wind speed and wind power in Denmark and Ireland. A correlation of 93% was achieved in these areas. This method cannot solve the accuracy requirements of the energy sector. By knowing the uncertainty of the forecasts, the focus can however be put on the accuracy requirements at times when it is possible to accurately predict the weather. Thus, this result presents a major step forward in making wind energy a compatible energy source in the future.
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For at least two millennia and probably much longer, the traditional vehicle for communicating geographical information to end-users has been the map. With the advent of computers, the means of both producing and consuming maps have radically been transformed, while the inherent nature of the information product has also expanded and diversified rapidly. This has given rise in recent years to the new concept of geovisualisation (GVIS), which draws on the skills of the traditional cartographer, but extends them into three spatial dimensions and may also add temporality, photorealistic representations and/or interactivity. Demand for GVIS technologies and their applications has increased significantly in recent years, driven by the need to study complex geographical events and in particular their associated consequences and to communicate the results of these studies to a diversity of audiences and stakeholder groups. GVIS has data integration, multi-dimensional spatial display advanced modelling techniques, dynamic design and development environments and field-specific application needs. To meet with these needs, GVIS tools should be both powerful and inherently usable, in order to facilitate their role in helping interpret and communicate geographic problems. However no framework currently exists for ensuring this usability. The research presented here seeks to fill this gap, by addressing the challenges of incorporating user requirements in GVIS tool design. It starts from the premise that usability in GVIS should be incorporated and implemented throughout the whole design and development process. To facilitate this, Subject Technology Matching (STM) is proposed as a new approach to assessing and interpreting user requirements. Based on STM, a new design framework called Usability Enhanced Coordination Design (UECD) is ten presented with the purpose of leveraging overall usability of the design outputs. UECD places GVIS experts in a new key role in the design process, to form a more coordinated and integrated workflow and a more focused and interactive usability testing. To prove the concept, these theoretical elements of the framework have been implemented in two test projects: one is the creation of a coastal inundation simulation for Whitegate, Cork, Ireland; the other is a flooding mapping tool for Zhushan Town, Jiangsu, China. The two case studies successfully demonstrated the potential merits of the UECD approach when GVIS techniques are applied to geographic problem solving and decision making. The thesis delivers a comprehensive understanding of the development and challenges of GVIS technology, its usability concerns, usability and associated UCD; it explores the possibility of putting UCD framework in GVIS design; it constructs a new theoretical design framework called UECD which aims to make the whole design process usability driven; it develops the key concept of STM into a template set to improve the performance of a GVIS design. These key conceptual and procedural foundations can be built on future research, aimed at further refining and developing UECD as a useful design methodology for GVIS scholars and practitioners.
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Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.
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A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.