Relevant bibliographies by topics / Multiple reservoir systems

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Multiple reservoir systems'

Author: Grafiati
Published: 19 February 2023

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Journal articles on the topic "Multiple reservoir systems"

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Chu, Jinggang, Yu Li, Yong Peng, and Wei Ding. "Developing a joint operation framework for complex multiple reservoir systems." Water Supply 16, no. 1 (July 21, 2015): 9–16. http://dx.doi.org/10.2166/ws.2015.105.

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This study aims to present a joint operation framework for complex multiple reservoir systems to balance water supply between subsystems and between different stakeholders, and support decisions about water releases from the entire system and individual reservoirs effectively. The framework includes three steps: (1) aggregated virtual reservoirs and various subsystems are established to determine the water releases from the entire system; (2) the common water-supply strategy is identified to determine the water releases from individual reservoirs; and (3) the joint operation problem is solved with a multi-objective optimization algorithm and the results are analyzed using a Many-Objective Visual Analytics Tool (MOVAT). A case study of the DaHuoFang-GuanYinGe-ShenWo multi-reservoir system in northeastern China is used to demonstrate the framework. Results show that the establishment of aggregated virtual reservoirs and identification of a common water-supply strategy could make use of the temporal and spatial differences of runoff, exert the effects of underlying hydrological compensation between river basins, and reduce the complexity of the joint operation model for multiple reservoir systems effectively. The MOVAT provides an effective means of solving many-objective problems, which are generally of particular concern to the decision-maker in practice.
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Karamouz, Mohammad, Mark H. Houck, and Jacque W. Delleur. "Optimization and Simulation of Multiple Reservoir Systems." Journal of Water Resources Planning and Management 118, no. 1 (January 1992): 71–81. http://dx.doi.org/10.1061/(asce)0733-9496(1992)118:1(71).

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Alsukni, Emad, Omar Suleiman Arabeyyat, Mohammed A. Awadallah, Laaly Alsamarraie, Iyad Abu-Doush, and Mohammed Azmi Al-Betar. "Multiple-Reservoir Scheduling Using β-Hill Climbing Algorithm." Journal of Intelligent Systems 28, no. 4 (September 25, 2019): 559–70. http://dx.doi.org/10.1515/jisys-2017-0159.

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Abstract The multi-reservoir systems optimization problem requires defining a set of rules to recognize the water amount stored and released in accordance with the system constraints. Traditional methods are not suitable for complex multi-reservoir systems with high dimensionality. Recently, metaheuristic-based algorithms such as evolutionary algorithms and local search-based algorithms are successfully used to solve the multi-reservoir systems. β-hill climbing is a recent metaheuristic local search-based algorithm. In this paper, the multi-reservoir systems optimization problem is tackled using β-hill climbing. In order to validate the proposed method, four-reservoir systems used in the literature to evaluate the algorithm are utilized. A comparative evaluation is conducted to evaluate the proposed method against other methods found in the literature. The obtained results show the competitiveness of the proposed algorithm.
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Duncan, R. A., G. E. Seymore, D. L. Streiffert, and D. J. Engberg. "Optimal Hydrothermal Coordination for Multiple Reservoir River Systems." IEEE Power Engineering Review PER-5, no. 5 (May 1985): 43. http://dx.doi.org/10.1109/mper.1985.5526581.

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Kim, Sang Hyun. "Impedance Method for Multiple Reservoir Pipeline Valve Systems." Journal of Hydraulic Engineering 145, no. 6 (June 2019): 04019023. http://dx.doi.org/10.1061/(asce)hy.1943-7900.0001610.

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Duncan, R. A., G. E. Seymore, D. L. Streiffert, and D. J. Engberg. "Optimal Hydrothermal Coordination for Multiple Reservoir River Systems." IEEE Transactions on Power Apparatus and Systems PAS-104, no. 5 (May 1985): 1154–59. http://dx.doi.org/10.1109/tpas.1985.323467.

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Nawaz, N. R., A. J. Adeloye, and M. Montaseri. "The Impact of Climate Change on Storage-Yield Curves for Multi-Reservoir Systems." Hydrology Research 30, no. 2 (April 1, 1999): 129–46. http://dx.doi.org/10.2166/nh.1999.0007.

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In this paper, we report on the results of an investigation into the impacts of climate change on the storage-yield relationships for two multiple-reservoir systems, one in England and the other in Iran. The impact study uses established protocol and obtains perturbed monthly inflow series using a simple runoff coefficient approach which accounts for non-evaporative losses in the catchment, and a number of recently published GCM-based scenarios. The multi-reservoir analysis is based on the sequent-peak algorithm which has been modified to analyse multiple reservoirs and to accommodate explicitly performance norms and reservoir surface fluxes, i.e. evaporation and rainfall. As a consequence, it was also possible to assess the effect of including reservoir surface fluxes on the storage-yield functions. The results showed that, under baseline conditions, consideration of net evaporation will require lower storages for the English system and higher storages for the Iranian system. However, with perturbed hydroclimatology different impacts were obtained depending on the systems' yield and reliability. Possible explanations are offered for the observed behaviours.
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Qiu, Hongya, Jianzhong Zhou, Lu Chen, and Yuxin Zhu. "Multiple Strategies Based Salp Swarm Algorithm for Optimal Operation of Multiple Hydropower Reservoirs." Water 13, no. 19 (October 4, 2021): 2753. http://dx.doi.org/10.3390/w13192753.

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Reasonable optimal operation policy for complex multiple reservoir systems is very important for the safe and efficient utilization of water resources. The operation policy of multiple hydropower reservoirs should be optimized to maximize total hydropower generation, while ensuring flood control safety by effective and efficient storage and release policy of multiple reservoirs. To achieve this goal, a new meta-heuristic algorithm, salp swarm algorithm (SSA), is used to optimize the joint operation of multiple hydropower reservoirs for the first time. SSA is a competitive bio-inspired optimizer, which has received substantial attention from researchers in a wide variety of applications in finance, engineering, and science because of its little controlling parameters and adaptive exploratory behavior. However, it still faces few drawbacks such as lack of exploitation and local optima stagnation, leading to a slow convergence rate. In order to tackle these problems, multiple strategies combining sine cosine operator, opposition-based learning mechanism, and elitism strategy are applied to the original SSA. The sine cosine operator is applied to balance the exploration and exploitation over the course of iteration; the opposition-based learning mechanism is used to enhance the diversity of the swarm; and the elitism strategy is adopted to find global optima. Then, the improved SSA (ISSA) is compared with six well-known meta-heuristic algorithms on 23 classical benchmark functions. The results obtained demonstrate that ISSA outperforms most of the well-known algorithms. Then, ISSA is applied to optimal operation of multiple hydropower reservoirs in the real world. A multiple reservoir system, namely Xiluodu Reservoir and Xiangjiaba Rservoir, in the upper Yangtze River of China are selected as a case study. The results obtained show that the ISSA is able to solve a real-world optimization problem with complex constraints. In addition, for the typical flood with a 100 return period in 1954, the maximum hydropower generation of multiple hydropower reservoirs is about 6671 GWh in the case of completing the flood control task, increasing by 1.18% and 1.77% than SSA and Particle Swarm Optimization (PSO), respectively. Thus, ISSA can be used as an alternative effective and efficient tool for the complex optimization of multiple hydropower reservoirs. The water resources in the river basin can be further utilized by the proposed method to cope with the increasingly serious climate change.
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Yan, Haijun, Ailin Jia, Fankun Meng, Qinyu Xia, Wei Xu, Qingfu Feng, Wenjun Luo, Xinyu Li, Xun Zhu, and Yicheng Liu. "Comparative Study on the Reservoir Characteristics and Development Technologies of Two Typical Karst Weathering-Crust Carbonate Gas Reservoirs in China." Geofluids 2021 (June 9, 2021): 1–19. http://dx.doi.org/10.1155/2021/6631006.

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Carbonate reservoirs are the main reservoir types in China, which occupy the large ratio of reserves and production at present. The high-efficiency development of carbonate reservoirs is of great significance to assure the stability of national energy supply. The Lower Paleozoic reservoir in Jingbian gas field and the Sinian reservoir in Anyue gas field are two typical carbonate gas reservoirs, and their successful development experiences can provide significant references for other similar carbonate gas reservoirs. For Jingbian gas field, it is a lithological-stratigraphic reservoir developed in a westward monocline and multiple rows of nose-fold structures, and is a stable craton basin with simple palaeognomy distribution and stable connectivity, which has complex gas-water distribution. However, for Anyue gas field, it is a lithological-structural reservoir with multiple tectonic high points and multiple fault systems, and is biological dune beach facies under extensional setting with highly differentiated inside of the block in palaeognomy characteristics, which has limited connectivity and tectonic side water is in a local area. The difference of gas reservoir characteristics leads to the diverse development strategies. For these two gas reservoirs, although there are some similar aspects, such as the screen of enrichment areas, the application of irregular well pattern and reservoir stimulation techniques, the criteria of enrichment areas, the well types, and the means of reservoir stimulation are absolutely different. In addition, due to the differences of control reserves and production capacity for these two kinds of reservoirs, the mode of stable production is also different. The effective development of Jingbian gas field can give some references to the future exploitation on the Sinian gas reservoir. Firstly, the sedimentary characteristics should be studied comprehensively. Secondly, the distribution pattern and distribution characteristics of the palaeognomy should be found and determined. Thirdly, the distribution of fracture system in the reservoir should be depicted finely. Finally, dynamic monitoring on the production performance should be strengthened, and the management for this gas field should be improved further. The findings of this study can help for better understanding of the Karst weathering-crust carbonate gas reservoir formation characteristics and the optimal development technologies that should be taken in practice.
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Wang, Dashun, Di Niu, and Huazhou Andy Li. "Predicting Waterflooding Performance in Low-Permeability Reservoirs With Linear Dynamical Systems." SPE Journal 22, no. 05 (May 16, 2017): 1596–608. http://dx.doi.org/10.2118/185960-pa.

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Summary Several interwell connectivity models such as multiple linear regression (MLR) and the capacitance model (CM) have been proposed to model waterflooding performance in high-permeability reservoirs on the basis of observed production data. However, the existing methods are not effective at characterizing the behavior of transient flows that are prevalent in low-permeability reservoirs. This paper presents a novel dynamic waterflooding model that is based on linear dynamical systems (LDSs) to characterize the injection/production relationships in an oil field during both stationary and nonstationary production phases. We leverage a state-space model (SSM), in which the changing rates of control volumes between injector/producer pairs in the reservoir of interest serve as time-varying hidden states, depending on the reservoir condition. Thus, the model can better characterize the transient dynamics in low-permeability reservoirs. We propose a self-learning procedure for the model to train its parameters as well as the evolution of the hidden states only on the basis of past observations of injection and production rates. We tested the LDS method in comparison with the state-of-the-art CM method in a wide range of synthetic reservoir models including both high-permeability and low-permeability reservoirs, as well as various dynamic scenarios involving varying bottomhole pressure (BHP) of producers, injector shut-ins, and reservoirs of larger scales. We also tested LDS on the real production data collected from Changqing oil field containing low-permeability formations. Testing results demonstrate that an LDS significantly outperforms CM in terms of modeling and predicting waterflooding performance in low-permeability reservoirs and various dynamic scenarios.
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Dissertations / Theses on the topic "Multiple reservoir systems"

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Crawley, P. D. "Optimum operating policies for multiple reservoir systems /." Title page, contents and synopsis only, 1990. http://web4.library.adelaide.edu.au/theses/09EN/09enc911.pdf.

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Crawley, P. D. "Risk and reliability assessment of multiple reservoir water supply headworks systems /." Title page, contents and synopsis only, 1995. http://web4.library.adelaide.edu.au/theses/09PH/09phc911.pdf.

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Montaseri, Majid. "Stochastic investigation of the planning characteristics of within-year and over-year reservoir systems." Thesis, Heriot-Watt University, 1999. http://hdl.handle.net/10399/586.

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Ticlavilca, Andres M. "Multivariate Bayesian Machine Learning Regression for Operation and Management of Multiple Reservoir, Irrigation Canal, and River Systems." DigitalCommons@USU, 2010. https://digitalcommons.usu.edu/etd/600.

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The principal objective of this dissertation is to develop Bayesian machine learning models for multiple reservoir, irrigation canal, and river system operation and management. These types of models are derived from the emerging area of machine learning theory; they are characterized by their ability to capture the underlying physics of the system simply by examination of the measured system inputs and outputs. They can be used to provide probabilistic predictions of system behavior using only historical data. The models were developed in the form of a multivariate relevance vector machine (MVRVM) that is based on a sparse Bayesian learning machine approach for regression. Using this Bayesian approach, a predictive confidence interval is obtained from the model that captures the uncertainty of both the model and the data. The models were applied to the multiple reservoir, canal and river system located in the regulated Lower Sevier River Basin in Utah. The models were developed to perform predictions of multi-time-ahead releases of multiple reservoirs, diversions of multiple canals, and streamflow and water loss/gain in a river system. This research represents the first attempt to use a multivariate Bayesian learning regression approach to develop simultaneous multi-step-ahead predictions with predictive confidence intervals for multiple outputs in a regulated river basin system. These predictions will be of potential value to reservoir and canal operators in identifying the best decisions for operation and management of irrigation water supply systems.
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Crawley, P. D. "Optimum operating policies for multiple reservoir systems." Thesis, 1990. http://hdl.handle.net/2440/115778.

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Crawley, P. D. (Philip David). "Risk and reliability assessment of multiple reservoir water supply headworks systems." 1995. http://web4.library.adelaide.edu.au/theses/09PH/09phc911.pdf.

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(7637330), Khalid Karim. "An improved approach to the development of operating policies for multiple reservoir systems." Thesis, 1997. https://figshare.com/articles/thesis/An_improved_approach_to_the_development_of_operating_policies_for_multiple_reservoir_systems/21708203.

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The diminishing potential for development of further reservoirs, coupled with environmental awareness about the negative environmental impacts of reservoir construction and operation, has not only necessitated the need for improved operation of reservoirs through better planning, but has also created an additional demand on reservoirs in the form of instream flow requirements to preserve the ecological integrity of the rivers. The combination of these factors has lead to a considerable interest in both private and government water resources engineering practice in the use of mathematical models for optimisation of reservoir operations.

The optimisation approaches which have been most commonly used for planning the operation of reservoirs are dynamic programming (DP), linear programming (LP) and non-linear programming. While all of these techniques are reasonably effective for optimisation of operation of single reservoirs, dynamic programs are by far the most frequently used partly because of the ease with which they can handle stochasticity of inflow regimes. However, while all the techniques, including dynamic programming techniques, are relatively easily applied to optimisation of single reservoirs, serious theoretical and computational issues arise when they are applied to the optimisation of the operations of multiple reservoir systems, particularly when stochastic issues related to inflow regimes or variation in demands are considered. For this reason, none of the above techniques have been able to be applied directly to the simultaneous optimisation of the operation of multiple reservoir systems. Instead, the optimisation processes have relied upon approximations such as decomposition of a system or joint simulation-optimisation approaches.

The research reported in this thesis proposes a new approach to optimisation of the operation of reservoir systems, particularly multiple reservoir systems. This approach enables improved levels of consideration of the stochasticity of the inflow process while also significantly reducing the computational requirement and permits a more detailed and accurate representation of the system within the optimisation process. The approach is based on consideration of the stochasticity of inflows through the concept of Limiting State Probabilities. These Limiting State Probabilities rely on an assumption of stationarity of monthly transition probability matrices, an assumption which is also commonly used in stochastic reservoir operation models and define a probability distribution of inflows which, for each time period, are independent of the flows in the previous month, but which implicitly incorporate the time period to time period correlations normally captured by Markov processes. The Limiting State Probability vectors for each time period are obtained by a process of multiplication of the transition probability matrices associated with the inflows in that time period and the time period immediately preceding it. These Limiting State Probability vectors are the same as the marginal probabilities of inflows derived from steady state solutions in stochastic dynamic programs. The ability of Limiting State Probability vectors to remove the explicit temporal correlations is derived from the close relationship of Limiting State Probabilities to the long term steady state conditions of optimal reservoir operation. The elimination of temporal correlation also enables the spatial correlation between the inflows to reservoirs at different locations to be considered implicitly rather than explicitly. The spatial correlation is able to be eliminated from explicit consideration in the inflows to the model because the removal of the time period to time period correlation means that the results of a deterministic optimisation of reservoir using an inflow sequence generated by and conforming to the Limiting State Probability are independent of the actual order of inflows in that inflow series. This non-dependence of the results of the optimisation on the order of inflows enables the Limiting State Probability generated inflow sequences to be used as input to each reservoir in a multiple reservoir system with a diminished need to consider spatial correlation of inflows explicitly. The approach is validated first by application to the optimisation of the operation of a single reservoir wherein it is shown that the same results, i.e., optimal operating policies, are obtained when Limiting State Probabilities rather than traditional transition probability matrices are used in the recursive equations of the stochastic dynamic program. Optimal operation of the same single reservoir was then performed by the deterministic modelling technique network linear programming using inflow sequences generated by Limiting State Probabilities. The results obtained from the optimisation technique were similar to those obtained by stochastic dynamic programming with some of the differences being due to use of discrete variables in stochastic dynamic programming and continuous variables in the network linear program. Use of the Limiting State Probability concept was then extended to simultaneous optimisation, using network linear programming, of a multiple reservoir system comprising six reservoirs and seventeen demand centres, plus instream flow requirements. The deterministic inflow inputs, i.e., inflow sequences to each reservoir required by network linear programming were generated on the basis of Limiting State Probabilities relevant to each reservoir. The results of the application of the NLP technique using the inflows generated by Limiting State Probabilities showed the approach to be a computationally tractable and effective means to improved level of consideration of stochasticity of inflows in the optimisation of the operation of multiple reservoir systems.

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Crawley, P. D. (Philip David). "Risk and reliability assessment of multiple reservoir water supply headworks systems / by Philip David Crawley." Thesis, 1995. http://hdl.handle.net/2440/18555.

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Lai, Ru-Hui, and 賴如慧. "Spatial Priority Assessment For Reservoir Watershed Management-Multiple Criteria Decision Making Integrate With Geographic Information Systems." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/04095976079855224066.

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碩士
逢甲大學
土地管理學系
87
Reservoir watershed area provides important water conservation function and preserves essential soil and water conservation region because reservoir watershed are management is highly related to water quality, resources conservation and even life and property security of river basis residence. To satisfy the growing demand for land resources, and to induce the water quantity and quality, while concern the environmental impact from development and watershed damage from natural or manual behavior, reservoir watershed management has became one of the important issue in national land sustainable management. To cope with such sophisticated problem, there is a need to consider all aspects and find optimum alternatives to reduce the conflict for watershed management and the solution can provide decision making reference for policy makers. This study bases on the view of reservoir watershed soil and water resources sustainability for Te-Chi upper watershed area, applies Multiple Criteria Decision Making (MCSM) method to identify spatial priority for watershed management area. This study also applies Geographic Information Systems (GIS) and Remote Sensing (RS) technique as tools to enhance the watershed management planning. The results concluded by various MCDM and weighting strategies analysis are as followings: 1. The average sand prevention completeness ratio was estimated as 13.68%, which integrated the GIS information and RS image classification and universal soil loss equation for land slides volume and sand prevention volume calculation. The results was then served as one of the evaluation parameters for MCDM analysis together with water conservation capacity, total phosphorus in water quality and land use restraints. 2. Sub-watershed number 20 was evaluated as the first priority by ELECTRE method while sub-watershed number 7 was evaluated as the first priority by PROMTHEE method 3. Due to the different mathematical algorithm and requirement of calculation process, the two alternatives results showed a significant different. 4. To understand the influence by weighting changes, this study applied PROMETHEE method to discuss the impact, and concluded that there were no absolute influence but an interference. 5. When the preference function of sand prevention completeness ratio changed from V-shape to usual criterion with no other condition changed, the output changed not only its dominate but also its sequence. 6. The output spatial priority area from MCDM analysis located mostly in Nan-Hu river basin area with lower sand prevention completeness ration and higher slope degree.
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Cheng, Chang Chin, and 張志誠. "Derivation of joint operation policies for a multiple reservoir system in parallel." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/17484134300581892209.

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碩士
國立中央大學
土木工程研究所
87
This study emphasizes on the joint policy for a multiple reservoir system in parallel. The fist part of this research focuses on streamflow generation, the second part on the application of the stochastic dynamic programming to obtain balancing curves. Most of the streamflow generation models were developed by taking only a specific streamflow data into consideration. However, with the trend of overall water resource systems management, it becomes unacceptable to treat each stream in the system independently. This is because the variation of hydrological factors, such as terrain, climate, and soil types, are limited in a nearly area. That is, there must be a certain correlation between the streamflows. With this in mind, a multisite streamflow generation model is developed in this study. Also, in the process of streamflow generation, this research develops an analytic model with meteorological characteristics instead of a harmonic synthetic model. In this way, we can generate streamflow carrying physical meaning. The streamflow generated from the multisite streamflow model is summerized into a streamflow transition probability matrix for later use. A stochastic dynamic programming aims to obtain balancing curves in a ten-day period. The release from each reservoir to the joint demand is defined as a function of the individual storage and the time of the year together with balancing curves indicating the ideal distribution of storage levels among the reservoirs. Two types of joint operation, a full joint operation and a partial one are studied. Moreover, different operation methods are simulated. The balancing curves are compared with the equal proportion storage curves. The simulation of partial joint operation and that of full joint operation are then conducted. A partial joint operation means only certain demands can be made from each reservoir. The Tanshuei River Watershed, consisting of Peishih River, Nanshih River, and Tahan River, is chosen as a case study. Using the demand in year 2000 as the target, the case study, which discarding the current rule curve, is analyzed based on one hundred ten-year runs. The result indicates that compared with the partial joint one, the full joint operation can reduce the amount of demand shortage by 90 percent or so.
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Books on the topic "Multiple reservoir systems"

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Archibald, T. W. An aggregate stochastic dynamic programming model of multiple reservoir systems. Edinburgh: Department of Business Studies, University of Edinburgh, 1995.

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Archibald, T. W. Application of principal component analysis to an aggregate stochastic dynamic programming model of multiple reservoir systems. Edinburgh: University of Edinburgh, Management School, 1995.

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Renwick, Mary E. Valuing water in irrigated agriculture and reservoir fisheries: A multiple-use irrigation system in Sri Lanka. Colombo: International Water Management Institute, 2001.

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Chappell, Dave. Waterflooding: Facilities and Operations. Society of Petroleum EngineersRichardson, Texas, USA, 2020. http://dx.doi.org/10.2118/9781613998106.

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Used successfully for more than a century, waterflooding remains the most widely performed process relying on an external energy source to maximize reservoir recovery. Multiple factors across a wide range of disciplines contribute to the delivery of a fully optimized project, but not all of these critical success factors have been well-documented. A focus on further optimizing all the varying parts of the process has emerged over time to deliver project success. Waterflooding: Facilities and Operations looks at the design of injection and production systems and how they influence success in waterflooding.
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Schmandt, Jurgen, Aysegül Kibaroglu, Regina Buono, and Sephra Thomas, eds. Sustainability of Engineered Rivers In Arid Lands. Cambridge University Press, 2021. http://dx.doi.org/10.1017/9781108261142.

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This interdisciplinary volume examines how nine arid or semi-arid river basins with thriving irrigated agriculture are doing now and how they may change between now and mid-century. The rivers studied are the Colorado, Euphrates-Tigris, Jucar, Limarí, Murray-Darling, Nile, Rio Grande, São Francisco, and Yellow. Engineered dams and distribution networks brought large benefits to farmers and cities, but now the water systems face multiple challenges, above all climate change, reservoir siltation, and decreased water flows. Unchecked, they will see reduced food production and endanger the economic livelihood of basin populations. The authors suggest how to respond to these challenges without loss of food production, drinking water, or environmental health. The analysis of the political, hydrological, and environmental conditions within each basin gives policymakers, engineers, and researchers interested in the water/sustainability nexus a better understanding of engineered rivers in arid lands.
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Reem Fikri Mohamed Osman Digna. Optimizing the Operation of a Multiple Reservoir System in the Eastern Nile Basin Considering Water and Sediment Fluxes. Taylor & Francis Group, 2020.

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Reem Fikri Mohamed Osman Digna. Optimizing the Operation of a Multiple Reservoir System in the Eastern Nile Basin Considering Water and Sediment Fluxes. Taylor & Francis Group, 2020.

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Reem Fikri Mohamed Osman Digna. Optimizing the Operation of a Multiple Reservoir System in the Eastern Nile Basin Considering Water and Sediment Fluxes. Taylor & Francis Group, 2020.

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Optimizing the Operation of a Multiple Reservoir System in the Eastern Nile Basin Considering Water and Sediment Fluxes. Taylor & Francis Group, 2020.

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Reem Fikri Mohamed Osman Digna. Optimizing the Operation of a Multiple Reservoir System in the Eastern Nile Basin Considering Water and Sediment Fluxes. Taylor & Francis Group, 2020.

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Book chapters on the topic "Multiple reservoir systems"

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Kiczko, Adam, and Tatiana Ermolieva. "Multiple-Criteria Decision Support System for Siemianówka Reservoir under Uncertainties." In Lecture Notes in Economics and Mathematical Systems, 187–201. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22884-1_9.

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Bertoni, Federica. "Advancing Joint Design and Operation of Water Resources Systems Under Uncertainty." In Special Topics in Information Technology, 119–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62476-7_11.

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AbstractGlobally, many countries are actively seeking to maximize the hydropower potential of major river basins, yielding proposals for constructing approximately 3,700 major dams in the near future. The planning of new water reservoir systems raises several major challenges that must be conjunctively accounted for within the system design phase, in order to design efficient yet sustainable infrastructures able to satisfy multiple water needs and perform well under a wide range of external future changes. This contribution aims at advancing the current planning and operation of water reservoir systems, focusing on the coupling of dam sizing and operation design in order to thoroughly capture their interdependencies also with respect to uncertainty in the main external drivers.
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Kheriji, Walid, Yalchin Efendiev, Victor Manuel Calo, and Eduardo Gildin. "Model Reduction for Coupled Near-Well and Reservoir Models Using Multiple Space-Time Discretizations." In Model Reduction of Parametrized Systems, 471–90. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58786-8_29.

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Tangi, Marco. "Dynamic Sediment Connectivity Modelling for Strategic River Basin Planning." In Special Topics in Information Technology, 27–37. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15374-7_3.

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AbstractSediment connectivity is a distributed property of river systems that emerges from the connected transfer of sediment between multiple sources and sinks. Its disruption, brought by anthropic disturbances, can have severe and unforeseen consequences on both fluvial ecosystems and human livelihood. Modeling network-scale sediment connectivity provides a foundational understanding of river processes and their response to new pressures and can be used to forecast future system evolutions. In this chapter, we present the basin-scale, dynamic sediment connectivity model D-CASCADE (Dynamic CAtchment Sediment Connectivity And DElivery), which quantifies spatiotemporal patterns of sediment delivery in river networks. D-CASCADE considers multiple factors affecting transport, including heterogeneities in hydrology and sediment supply, different grain sizes, channel morphological evolution, and reservoir presence and management. The model is designed to be flexible, data parsimonious, and computationally efficient. We also present two applications of D-CASCADE in real-world case studies for historic geomorphic evolution reconstruction and future dam impacts forecasting. D-CASCADE is intended for integrated, basin-scale water management efforts, to perform multiple screening of various decision portfolios for hydromorphological impact assessments.
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Wang, Chi-Yuen, and Michael Manga. "Mud Volcanoes." In Lecture Notes in Earth System Sciences, 323–42. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64308-9_12.

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AbstractThe eruption of mud and magma can be influenced by earthquakes and reports date back more than 2000 years. Dozens of examples of eruptions have now been documented in response to both static and dynamic stresses from earthquakes. Already erupting systems are most sensitive to earthquakes compared to initiating new eruptions. Multiple plausible mechanisms have been proposed for triggering eruptions including disrupting particle-rich materials, mobilizing bubbles, or changing permeability—changes may occur both within and outside the reservoir hosting the materials that ultimately erupt. Using historical examples of triggered mud eruptions, we explain why it is unlikely that the Sidoarjo mud flow (sometimes nicknamed “Lusi”) was initiated by an earthquake. As multiparameter monitoring of volcanoes expands, it may eventually be possible to identify triggering mechanisms and how seismic waves influence magma and mud mobility in field settings.
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Qiu, Hongya, Jianzhong Zhou, Lu Chen, and Yuxin Zhu. "Optimal Allocation of Flood Control Capacity of Multiple Reservoir System." In Environment and Sustainable Development, 200–209. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1704-2_19.

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Fadlelmula, Mohamed M., Serhat Akin, and Sebnem Duzgun. "Parameterization of Channelized Training Images: A Novel Approach for Multiple-Point Simulations of Fluvial Reservoirs." In Lecture Notes in Earth System Sciences, 557–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32408-6_122.

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"Balancing Fisheries Management and Water Uses for Impounded River Systems." In Balancing Fisheries Management and Water Uses for Impounded River Systems, edited by Christopher J. Goudreau, Richard W. Christie, and D. Hugh Barwick. American Fisheries Society, 2008. http://dx.doi.org/10.47886/9781934874066.ch5.

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<em>Abstract</em>.—The Catawba-Wateree river basin is a highly regulated system in North Carolina and South Carolina that includes 11 main-stem reservoirs and four regulated riverine reaches. The reservoirs support typical southeastern U.S. warmwater fisheries, while the riverine reaches support a variety of species, including trout and several diadromous fishs. The reservoirs and regulated river reaches provide multiple uses, including hydroelectric generation, drinking water, cooling water for electric power plants, recreation, and residential development. As part of the relicensing process for the hydroelectric developments, many stakeholders were convened to study and negotiate a comprehensive relicensing agreement. A computer model was used to assess the combined effects of various operating regimes, water-use amounts, and hydrologic conditions on reservoir levels, river flows, and hydroelectric generation. The model used projections of the effects of increased population growth, water use, and reservoir sedimentation for a period 50 years into the future. Model outputs were postprocessed to further understand the impacts to aquatic habitat, recreation, aesthetics, hydropower generation, and water supply. Although future demand for water resources exceeded the available supply under some conditions, an acceptable balance was reached after extensive negotiation. The objectives of this paper are to describe how the relicensing process was used to arrive at a balanced management plan for water and other resources in a large basin, describe some of the tools used to assist the decision-making process, and to list some important lessons that can assist others in designing a framework for other water allocation efforts.
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Azad, Abdus Samad, Pandian Vasant, Junzo Watada, and Rajalingam Al Sokkalingam. "Meta-Heuristic Approaches for the Optimization of Hydropower Energy." In Handbook of Research on Smart Technology Models for Business and Industry, 351–75. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-3645-2.ch015.

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The concept of a multireservoir systems in hydropower introduces the function of multiple units simultaneously to reach the peak requirements. The reservoir optimized operation is a complex, extremely nonlinear, high dimensional, and multimodal task. The options that can be evaluated manually are generally limited in numbers, which made it difficult to identify the most appropriate option and should be taken into account while making decisions. Presently, for solving the optimization problems in multireservoir system, many modern heuristic stochastic search algorithms were established. That is possible because of the aspects of artificial and computational intelligence technologies. By connecting metaheuristic algorithms, the decision options can be identified to make the most suitable utilization of the scarce resources, best natural results for a given allotment can be attained, and the best trade-offs between contending goals can be established. In this chapter, the authors review the latest meta-heuristic optimization technique and their applications to maximize the economic factors.
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Digna, Reem Fikri Mohamed Osman. "Development of the Eastern Nile reservoirs system sedimentation model." In Optimizing the Operation of a Multiple Reservoir System in the Eastern Nile Basin Considering Water and Sediment Fluxes, 83–108. CRC Press, 2021. http://dx.doi.org/10.1201/9781003097792-6.

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Conference papers on the topic "Multiple reservoir systems"

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Nicklow, John W., and Larry W. Mays. "Operation of Multiple Reservoir Systems to Control Sedimentation in Rivers and Reservoirs." In 29th Annual Water Resources Planning and Management Conference. Reston, VA: American Society of Civil Engineers, 1999. http://dx.doi.org/10.1061/40430(1999)105.

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Eskandari, K., and S. Srinivasan. "Reservoir Modelling of Complex Geological Systems - A Multiple Point Perspective." In Canadian International Petroleum Conference. Petroleum Society of Canada, 2008. http://dx.doi.org/10.2118/2008-176.

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Guo, Zhenyu, Wenyue Sun, and Sathish Sankaran. "Efficient Reservoir Management with a Reservoir Graph Network Model." In SPE Western Regional Meeting. SPE, 2022. http://dx.doi.org/10.2118/209337-ms.

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Abstract Efficient reservoir models are more desirable for fast-paced reservoir management. Moreover, due to the complexity of flow underground, it is also essential to capture the most fundamental physics for model reliability. Though running fast, pure data-driven models often suffer from the issues associated with interpretability, physical consistency, and ability to forecast. On the other hand, we have used full-physics simulation models to mimic and investigate hydrocarbon systems for over several decades. However, considering its infrequent model updates related to high model complexity, it is a big challenge to manage reservoirs using full-physics models in short cycles. The objective here is to propose an approach that blends reservoir physics with data-driven models to fit in the framework of dynamic reservoir management. We propose to use a reservoir graph network (RGNet) modeling approach based on diffusive time-offlight (DTOF) concept to simulate reservoir behaviors. By assimilating field observation data (such as pressure and rates), an RGNet model can be used for future predictions, scenario studies and well-control optimizations. By discretizing DTOF of a three-dimensional system with multiple wells, RGNet simplifies the system into a graph network represented by a set of one-dimensional grid blocks that significantly reduces the system complexity and run time. RGNet can also handle multiple flow problems with various types of physics. In this work, we investigate multiple grid connectivity methods to develop reliable and parsimonious models for large scale systems. In addition, we propose a more robust method to assimilate static pressure data, when available. We applied the proposed approach to a synthetic example. Two different history matching algorithms, the ensemble smoother with multiple data assimilation (ES-MDA) and an adjoint-based method, are compared. While ES-MDA provides the capability for uncertainty analysis, an adjoint-based method generally requires fewer simulation runs to generate a posterior model. With the proposed gridding methods, RGNet model calibration can be achieved without system redundancy and spurious longdistance well-connectivity. Also, by using a more stable pressure matching technique, we show that pressure data are better matched and reservoir volume is accurately characterized. RGNet provides a novel hybrid physics and data-driven reservoir modeling method to fit in closed-loop reservoir management. As RGNet models are combined with fundamental flowing physics, the calibrated model parameters are easy to interpret and understand. An RGNet model runs with far less computational cost than required by a full-physics model, which allows it to be a more practical solution to history match, predict and optimize real assets.
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Reichhardt, David, and B. Todd Hoffman. "A Numerical Model Study of Scale-Dependent Fluid Flow and Storage Systems in Unconventional Reservoirs." In SPE Western Regional Meeting. SPE, 2022. http://dx.doi.org/10.2118/209298-ms.

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Abstract Unconventional reservoirs hold vast amounts of untapped hydrocarbon resources; however, given current production capabilities and our understanding of unconventional reservoir production mechanisms only 5% to 10% of these hydrocarbons are typically recovered. The ability to recover additional hydrocarbons from unconventional reservoirs is dependent on an improved understanding of the production mechanisms which are a function of the complex lithology and reservoir fluid systems, and the interactions between these systems. The lithology and fluid systems present in most unconventional reservoirs result in production from several scale-dependent fluid flow and storage systems, or depletion systems, that combine to contribute to the total production. These depletion systems can include matrix level features defined by pore size, natural fracture systems within the matrix, and hydraulic fractures in addition to the traditional depletion systems defined by stacked pay. The fluid phase behavior within these systems also has a scale dependence that must be taken into consideration. As a result, the individual systems tend to deplete at different rates. The purpose of this work is to describe the production mechanisms in terms of the lithology and reservoir fluid interactions. By using numerical simulation to systematically isolate production from individual depletion systems, the role and significance of each system is quantified. A numerical model was developed to simulate the contributions to total hydrocarbon production from multiple depletion systems. Fluid tracers were placed within each depletion system to isolate the individual system production. The results show the stage of production when each depletion system is active and the associated hydrocarbon volumes. For example, the hydraulic fracture system provides most of the initial production, but contribution from the matrix and natural fractures quickly overtakes it. Composite production curves were developed by combining the simulated production contributions from each depletion system, highlighting the influence the different systems have on the total production. This paper provides insights into the production contributions from multiple depletion systems found in many unconventional reservoirs. Understanding the roles that the different depletion systems play on production will lead to better well spacing, reserve estimates, and improved reservoir production practices including enhanced oil recovery methods that may be optimized to target the most promising aspects of the reservoir.
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Mohd Razak, Syamil, Atefeh Jahandideh, Ulugbek Djuraev, and Behnam Jafarpour. "Deep Learning for Latent Space Data Assimilation LSDA in Subsurface Flow Systems." In SPE Reservoir Simulation Conference. SPE, 2021. http://dx.doi.org/10.2118/203997-ms.

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Abstract We present a deep learning architecture for efficient reduced-order implementation of ensemble data assimilation. Specifically, deep learning is used to improve two important aspects of data assimilation workflows: (i) low-rank representation of complex reservoir property distributions for geologically consistent feature-based model updating, and (ii) efficient prediction of the statistical information that are required for model updating. The proposed method uses deep convolutional autoencoders to nonlinearly map the original complex and high-dimensional parameters onto a low-dimensional parameter latent space that compactly represents the original parameters. In addition, a low-dimensional data latent space is constructed to predict the observable response of each model parameter realization, which can be used to compute the statistical information needed for the data assimilation step. The two mappings are developed as a joint deep learning architecture with two autoencoders that are connected and trained together. The training uses an ensemble of model parameters and their corresponding production response predictions as needed in implementing the standard ensemble-based data assimilation frameworks. Simultaneous training of the two mappings leads to a joint data-parameter manifold that captures the most salient information in the two spaces for a more effective data assimilation, where only relevant data and parameter features are included. Moreover, the parameter-to-data mapping provides a fast forecast model that can be used to increase the ensemble size for a more accurate data assimilation, without a major computational overhead. We implement the developed approach to a series of numerical experiments, including a 3D example based on the Volve field in the North Sea. For data assimilation methods that involve iterative schemes, such as ensemble smoothers with multiple data assimilation or iterative forms of ensemble Kalman filter, the proposed approach offers a computationally competitive alternative. Our results show that a fully low-dimensional implementation of ensemble data assimilation using deep learning architectures offers several advantages compared to standard algorithms, including joint data-parameter reduction that respects the salient features in each space, geologically consistent feature-based updates, increased ensemble sizes to improve the accuracy and computational efficiency of the calculated statistics for the update step.
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Tang, Meng, Yimin Liu, and Louis J. Durlofsky. "History Matching Complex 3D Systems Using Deep-Learning-Based Surrogate Flow Modeling and CNN-PCA Geological Parameterization." In SPE Reservoir Simulation Conference. SPE, 2021. http://dx.doi.org/10.2118/203924-ms.

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Abstract The use of deep-learning-based procedures for geological parameterization and fast surrogate flow modeling may enable the application of rigorous history matching algorithms that were previously considered impractical. In this study we incorporate such methods – specifically a geological parameterization that entails principal component analysis combined with a convolutional neural network (CNN-PCA) and a flow surrogate that uses a recurrent residual-U-Net procedure – into three different history matching procedures. The history matching algorithms considered are rejection sampling (RS), randomized maximum likelihood with mesh adaptive direct search optimization (MADS-RML), and ensemble smoother with multiple data assimilation (ES-MDA). RS is a rigorous sampler used here to provide reference results (though it can become intractable in cases with large amounts of observed data). History matching is performed for a channelized geomodel defined on a grid containing 128,000 cells. The CNN-PCA representation of geological realizations involves 400 parameters, and these are the variables determined through history matching. All flow evaluations (after training) are performed using the recurrent residual-U-Net surrogate model. Two cases, involving different amounts of historical data, are considered. We show that both MADS-RML and ES-MDA provide history matching results in general agreement with those from RS. MADS-RML is more accurate, however, and ES-MDA can display significant error in some quantities. ES-MDA requires many fewer function evaluations than MADS-RML, however, so there is a tradeoff between computational demand and accuracy. The framework developed here could be used to evaluate and tune a range of history matching procedures beyond those considered in this work.
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Gross, Herve, and Antoine Mazuyer. "GEOSX: A Multiphysics, Multilevel Simulator Designed for Exascale Computing." In SPE Reservoir Simulation Conference. SPE, 2021. http://dx.doi.org/10.2118/203932-ms.

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Abstract Evaluating large basin-scale formations for CO2 sequestration is one of the most important challenges for our industry. The technical complexity and the quantification of risks associated with these operations call for new reservoir engineering and reservoir simulation tools. The impact of multiple coupled physical phenomena, the century timescale, and basin-sized models in these operations force us to completely take apart and revisit the numerical backbone of existing simulation tools. We need a reservoir simulation tool designed for scalability and portability on high-performance computing architectures. To achieve this, we are proposing a new, open-source, multiphysics, and multilevel physics simulation tool called GEOSX. This tool is jointly created by Lawrence Livermore National Laboratory, Stanford University, and Total. It is designed for scalability on multiple CPUs and multiple GPUs and offers a suite of physical solvers that can be extended easily while achieving a balance between performance and portability. GEOSX is initially targeting multiphysics simulations with coupled geomechanics, flow, and transport mechanics but with its open architecture, it allows access to high-performance physical solvers as building blocks of other multiphysics problems and provides users with a suite of tools for numerical optimization across platforms. In this paper, we introduce GEOSX, expose its fundamental architecture principles, and show an example of geological sequestration of CO2 modeling on real data. We demonstrate our ability to simulate fluid and rock poromechanical interactions over long periods and basin-scale dimensions. GEOSX demonstrates its usefulness for such complex and large problems and proves to be scalable and portable across multiple high-performance systems.
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Abd, Abdul Salam, Ahmad Abushaikha, and Denis Voskov. "Coupling of Rigorous Multiphase Flash with Advanced Linearization Schemes for Accurate Compositional Simulation." In SPE Reservoir Simulation Conference. SPE, 2021. http://dx.doi.org/10.2118/203956-ms.

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Abstract The properties of fluids flowing in a petroleum reservoir are quantified by understanding the thermodynamic behavior of each flowing phase in the system. This work describes proper techniques to formulate and execute a thermodynamic model for accurately predicting the equilibrium behavior of oil-gas-brine systems within the practical range of pressure and temperature. The three-phase flash algorithm is validated against published data from the available literature. The multiphase flash procedure is implemented to generate linearized physical properties by using an Operator Based Linearization (OBL) modelling technique allowing for a combination of multiple complex physics in the nonlinear solution of governing equations. This is the first implementation of three-phase flash calculations for hydrocarbons and brines based on fugacity-activity models coupled with an advanced highly efficient linearization scheme. Our approach increases the efficiency and flexibility of the modelling process of physical phenomena such as fluid flow in porous subsurface reservoirs.
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Mohamed, Ahmed, Mandefro B. Woldeamanuel, Mohamed Gouda, and Hesham Rashad. "Water Based Mud High-Resolution Resistivity Images, Innovated Operational Practices to Enhance Log Quality in Lateral Boreholes Drilled with Multiple Fluid Systems." In SPE Reservoir Characterisation and Simulation Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212660-ms.

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Abstract Understanding how natural fractures are behaving is providing a growing knowledge about reservoir's structures and stresses, hence it becomes important to deploy high-resolution resistivity imaging service, especially in case of severe drilling fluid losses. In lateral boreholes, deployment of such service comes with its known additional operational challenges. In certain cases, drilling of these laterals starts with oil-based mud (OBM) to achieve certain objectives, then displacement with water-based mud (WBM) takes place when mud losses encountered at certain depth while drilling. Recording these sensitive measurements in such environment requires special planning for the string configuration and logging parameters optimization, and this article is explaining innovative operational practices followed to acquire high-quality image logs, and it will go through different scenarios while highlighting the potential constraints and limitations. Firstly, it is important to identify how long the borehole interval is drilled with OBM before displacement operations, as this controls the borehole conditioning process after TD and before pull-out-of-hole (POOH) for pipe-conveyed logging (PCL). It depends, so the situation is being assessed and discussed to decide the feasibility of logging operations. Afterwards, decision comes to either cancel the service request if it is confirmed that quality of data is expected to be highly degraded, or to proceed with logging operations if log quality is anticipated to be acceptable and meeting the deployment objective(s). With the latter option, clear plan of borehole conditioning procedures will be prepared, while considering an optimized tool's acquisition parameters in such mixed and challenging borehole environment. Different scenarios of complex mud environments were tested, including one case with variable WBM salinities across the logged MD interval without having any interference from any OBM during the drilling process. General conclusion is that less interval drilled with OBM pours into the benefit of obtaining higher data quality from WBM resistivity imager after less borehole conditioning time. In certain cases when longer interval was drilled with OBM, different treatment and conditioning processes resulted in accepted WBM resistivity imagers data quality. These practices of real tested cases are not granting accepted images quality all the way because of different variables like mixed fluids additives and salinities as well as borehole wall exposure time to such conditions, but they are providing sufficient awareness about how and when to expect an accepted image quality. To illustrate this conclusion, this article will also present a case where performed treatments and borehole conditioning processes were insufficient and had never produced any accepted image quality at all, which gives an insight that anticipated images quality in such scenario is considerably poor, and where to set valid cutoffs for the whole service request depending on how mixed borehole environmental conditions are. Instead of completely omitting resistivity imaging service in mixed borehole environments, these practices can beat the challenges, reduce the service limitations, and experimentally deliver accepted high-resolution resistivity images quality with clearly mapped natural fractures.
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Salewicz, Kazimierz A., Maiko Sakamoto, and Mikiyasu Nakayama. "Multiple criteria optimization in analysis of conflict associated with Al-Tharthar reservoir operation." In 2014 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2014. http://dx.doi.org/10.1109/smc.2014.6974372.

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Reports on the topic "Multiple reservoir systems"

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Wurbs, Ralph A. Optimization of Multiple-Purpose Reservoir Systems Operations: A Review of Modeling and Analysis Approaches. Fort Belvoir, VA: Defense Technical Information Center, January 1991. http://dx.doi.org/10.21236/ada236080.

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Sartain, Bradley, Kurt Getsinger, Damian Walter, John Madsen, and Shayne Levoy. Flowering rush control in hydrodynamic systems : part 1 : water exchange processes. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45425.

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In 2018, field trials evaluated water-exchange processes using rhodamine WT dye to provide guidance on the effective management of flowering rush (Butomus umbellatus L.) at McNary Dam and Reservoir (Wallula Lake, 15,700 ha). Additional evaluations determined the effectiveness of BubbleTubing (hereafter referred to as bubble curtain) at reducing water exchange within potential flowering rush treatment areas. Dye readings were collected from multiple sampling points at specific time intervals until a dye half-life could be determined. Whole-plot dye half-lives at sites without bubble curtain ranged 0.56–6.7 h. In slower water-exchange sites (≥2.6 h dye half-life), the herbicide diquat should have a sufficient contact time to significantly reduce flowering rush aboveground biomass. Other sites demonstrated very rapid water exchange (<1.5 h dye half-life), likely too rapid to effectively control flowering rush using chemical treatments without the use of a barrier or curtain to slow water exchange. At one site, the use of the bubble curtain increased the dye half-life from 3.8 h with no curtain to 7.6 and 7.1 h with a bubble curtain. The bubble curtain’s ability to slow water exchange will provide improved chemical control and in-crease the potential for other chemical products to be effectively used.
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