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1
AlBinHassan, Nasher M. "Reservoir properties prediction in carbonate reservoirs". Thesis, Imperial College London, 2010. http://hdl.handle.net/10044/1/5922.
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Prediction of fluid pressure before drilling, using geophysical methods helps the industry a lot in saving human life, drilling hazards, and equipments.There are several geophysical methods available to predict the fluid pressure before drilling but the most commonly used in the industry are those based on seismic velocities. However, seismic velocities methods are applied on clastic reservoirs with the assumptions that the pressure mechanism is due to mechanical compaction. A major exploration challenge is to successfully predict the presence of high pressure zones in the carbonate reservoirs. Carbonate reservoirs have a more complicated internal structure than clastic reservoirs. The main objective of this study is to predict the carbonate reservoir properties such as porosity and fluid pressure. The new prediction methods that I used in this thesis are called the artificail intelligent algorithms. These algorithms are better than the conventional geophysical methods because of their ability to explore complex relationships between the input seismic attributes and the predicted properties. The algorithms include artificial neural networks and group methods of data handling. Empirical equations from seismic prediction methods were used to transform velocities to fluid pressure. High resolution velocites (wavefrom tomography) proved that better prediction can be achieved when using better input velocity. The velocity methods performed a nice prediction when used with clastic seismic data but proved to give unreliable results when used with the carbonate seismic data. This was because of the difficult internal structure of carbonate reservoirs. The neural network methods proved that they are robust in clustering and segmenting the input carbonate seismic data. The usage of more input seismic attributes made the neural network methods better than the conventional velocity methods. Also, this gave the neural network methods more information about the same physical reservoir property. Among the different seismic attributes used in the experiment, seismic inversion and coherence attributes showed good reaction to high pressure zones. Porosity results from the supervised neural network method were used as a guide to the unsupervised neural network method to predict fluid pressure. The group method of data handling algorithm is performed here for the first time with seismic data to predict the reservoir properties. The new method showed faster and easier prediction than the neural network methods. The automation of the new method yields to better porosity and pore pressure prediction.
2
Whaballa, Ala. "Reservoir simulation and well testing of compartmentalized reservoirs". Thesis, Heriot-Watt University, 1991. http://hdl.handle.net/10399/1493.
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3
Dickey, Richard Jason Bayne David Roberge. "Oligotrophication effects following diversion of waste effluent from an embayment of Lake Martin, Alabama". Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Fall/Theses/DICKEY_RICHARD_7.pdf.
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4
PETER, COSTANZO. "Capturing reservoir production uncertainty for channelized reservoirs using channel amalgamation indexes". Doctoral thesis, Politecnico di Torino, 2016. http://hdl.handle.net/11583/2644036.
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One of the main concerns in reservoir studies is to accurately define the internal architecture and the geological characteristics of the reservoir so as to estimate the amount of hydrocarbons that could be recovered for a given development strategy. This can represent a major challenge especially during the appraisal stage of a reservoir, because the information available is still very limited, or in the presence of geological heterogeneities, which increase the architectural complexity and the uncertainty associated to the internal description, such as in channelized depositional settings. At the appraisal stage of a reservoir study, all the uncertainties affecting the quantity and distribution of hydrocarbons in the reservoir should be captured and accounted for in the evaluation of the final hydrocarbon recovery to properly assess the viability of any development plan.
A typical modeling workflow accounting for geological uncertainties consists in creating a large set of 3-D stochastic geological (static) models from a set of geological input parameters. Subsequently, a few representative reservoir realizations are selected out of this set based on the calculated hydrocarbons originally in place and simulated to estimate future production so as to propagate the uncertainty onto the final recovery factors. However, even in homogeneous reservoirs, the estimation of the hydrocarbon stored in the reservoir can be affected by uncertainties because it is calculated mostly from local petrophysical parameters, which might not be representative of the rock properties at the reservoir scale. This especially applies to channelized reservoirs characterized by depositional elements with high geological heterogeneity, both in the lateral and in the vertical directions. Thus for these depositional settings a more attractive criterion for the model selection is offered by the study of the connectivity layout of the reservoir elements.
In the technical literature, connectivity is defined through numerical indexes that account for geological connectivity between reservoir elements, which might not be indicative of reservoir production performance. In fact, the latter is influenced by the degree of connectivity among sand bodies and only deep merging of the channels guarantees that the reservoir can be efficiently drained by just a few wells. Therefore, in the first place, the present study was aimed at thoroughly investigating the validity of the indexes previously proposed in the technical literature by evaluating the reservoir production uncertainty associated to sets of synthetic equi-probable models of channelized oil reservoirs. Secondly, the goal of the research was to develop new indexes to express the channel connectivity, capable of incorporating information on the quality of the connectivity through the evaluation of channel amalgamation. When applied to the same set of reservoir equi-probable realizations, these indexes proved that a more effective selection of the geological realizations can be made to capture the uncertainty affecting the forecasted reservoir production performance.
5
Duruewuru, Anthony U. "Thermodynamic analysis of transient two-phase flow in oil and gas reservoirs /". Full-text version available from OU Domain via ProQuest Digital Dissertations, 1985.
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6
Raza, Arshad. "Reservoir Characterization for CO2 Injectivity and Flooding in Petroleum Reservoirs, offshore Malaysia". Thesis, Curtin University, 2017. http://hdl.handle.net/20.500.11937/57524.
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Reservoir characterization of the Malaysian gas reservoir for CO2 storage is carried out at preliminary and comprehensive level to provide insight into the storage capacity, injectivity, trapping mechanisms (structural, capillary, dissolution, and mineral), and containment. Screening tools are proposed in this study for the selections of reservoir, injection well, and injection zone along with CO2 residual trapping novel method, experimental assessment of compaction effect and numerical modeling scheme to improve the reservoir characterization.
7
Sagar, Rajiv K. "Reservoir description by integration of well test data and spatial statistics /". Access abstract and link to full text, 1993. http://0-wwwlib.umi.com.library.utulsa.edu/dissertations/fullcit/9416603.
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8
周潤堂 i Yun-tong Chow. "Pokfulam Reservoir Park". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31980557.
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Yeoh, Jin Shaun. "Reservoir sedimentation control". Thesis, University of Bristol, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.412359.
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Siyam, Ahmed Musa. "Reservoir sedimentation control". Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324265.
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11
Chow, Yun-tong. "Pokfulam Reservoir Park". Hong Kong : University of Hong Kong, 1995. http://sunzi.lib.hku.hk/hkuto/record.jsp?B25950538.
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12
Bertoldi, Alessia <1990>. "HIV e reservoir". Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amsdottorato.unibo.it/8875/1/bertoldi_alessia_tesi.pdf.
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Il maggiore ostacolo all’eradicazione di HIV è la presenza del reservoir virale trascrizionalmente silente ma in grado di replicare e difficilmente accessibile alla terapia. Reservoir di piccole dimensioni correlano con una prognosi migliore e una minor probabilità di rebound virologico in caso di semplificazione di terapia. La quantificazione del reservoir risulta pertanto essenziale per valutare la reale efficacia della terapia.
La quantificazione dell’HIV-DNA totale (circolare e integrato) rappresenta una metodica semplice e ampiamente utilizzata per analizzare il reservoir, nonostante ne sovrastimi le reali dimensioni includendo genomi defettivi.
Pertanto, inizialmente abbiamo ottimizzato una metodica per la quantificazione delle forme circolari di HIV-DNA. La forma circolare 2-LTR è stata misurata con successo; ciò non è stato possibile per la forma 1-LTR a causa di omologie di sequenza con il DNA genomico. Come parte di uno studio attualmente in corso, sette pazienti sono stati arruolati alla diagnosi (T0) e seguiti con prelievi a 6(T1), 12(T2), 18(T3) e 24(T4) mesi dopo l’inizio della terapia. Dati preliminari ottenuti nel primo anno (T0,T1,T2) mostrano un andamento dell’HIV-DNA totale stabile nel tempo (P>0,1); analogamente, la forma 2-LTR non mostra aumenti significativi tra T0 e T1 (P>0,5). Tuttavia, a T0 è stata osservata una differenza statisticamente significativa tra l’HIV-DNA totale e la forma 2-LTR (P<0,05).
La seconda parte dello studio si è focalizzata sul saggio TILDA, un metodo in grado di misurare esclusivamente virus competenti la replicazione. Abbiamo adattato questa metodica alle nostre condizioni sperimentali eseguendola su 3 pazienti HIV-positivi.
Infine, considerando il costante aumento dei casi di infezione con sottotipi non-B e che il saggio TILDA è stato sviluppato principalmente per il sottotipo B, il protocollo è stato modificato in modo da rilevare il sottotipo C, il più diffuso a livello mondiale. In particolare, è stato eseguito con successo su 3 pazienti infetti con il sottotipo C.Persistence of transcriptionally silent but replication-competent HIV reservoir in resting CD4+T cells constitutes the major barrier to viral eradication. Small latent reservoirs are associated to a better prognosis and predictive of less likelihood to undergo virological rebound during simplified therapy. Therefore, the amount of HIV-DNA in latently infected cells is critical to evaluate the efficacy of available regimens and avoid the potential “re-seeding” in aviremic patients. Although the quantification of total HIV-DNA (circular and integrated) overestimates reservoir size because it includes not replication-competent genomes, it represents a simple and widely used biomarker reflecting global viral reservoir. Therefore, first we optimized PCR methods for detection of circular forms of HIV-DNA in HIV-positive patients. We successfully measured the 2-LTR form, but not the 1-LTR form due to homologies with genomic DNA sequence. As part of an ongoing project on HIV-DNA, we tested our in house assay on seven PBMCs samples of treatment-naïve patients collected at 0(T0), 6(T1), 12(T2), 18(T3) and 24(T4) months after starting ART. Preliminary data on T0,T1, and T2 time points showed that total HIV-DNA is stable during time (P>0,1); likewise, the amount of 2-LTR forms did not show significant differences between T0 and T1 time points (P>0,5). However, we observed a statistically significant difference between 2-LTR form and total HIV-DNA amounts at T0 (P<0,05). The second part of this study focused on TILDA, a method that detects only transcriptionally-competent proviruses. Hence, we adapted TILDA to our experimental conditions performing the modified assay in three long-term treated patients. Moreover, considering that the frequency of non-B subtype infections is constantly increasing and TILDA has been developed based on subtype B virus sequence, we modified the protocol to detect subtype C virus, the most prevalent subtype worldwide. We successfully perform the new version of TILDA in three patients harboring subtype C viruses.
13
Serrat-Capdevila, Aleix. "An Alternative Approach to the Operation of Multinational Reservoir Systems: Application to the Amistad & Falcon Reservoir System (Lower Rio Grande/Rio Bravo)". Thesis, The University of Arizona, 2004. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu_etd_hy0249_sip1_w.pdf&type=application/pdf.
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14
Seth, Siddhartha. "Increase in surface energy by drainage of sandstone and carbonate". Laramie, Wyo. : University of Wyoming, 2006. http://proquest.umi.com/pqdweb?did=1221730011&sid=4&Fmt=2&clientId=18949&RQT=309&VName=PQD.
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15
Kleopa, Xenia A. "Optimal reservoir operation for drought management". Ohio : Ohio University, 1990. http://www.ohiolink.edu/etd/view.cgi?ohiou1183650664.
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16
Helfer, Fernanda. "Influence of Air-Bubble Plumes and Effects of Climate Change on Reservoir Evaporation". Thesis, Griffith University, 2012. http://hdl.handle.net/10072/365996.
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It is estimated that open water reservoirs in Australia lose around 40% of their total water storage capacity per year to evaporation. This can be attributed to the country’s dry climate, with high temperatures and strong winds. To further exacerbate this issue, temperature increases have been recorded during the past decades, and this is predicted to continue over the coming years in Australia. This has been directing even greater concern to how much water will be lost from Australian reservoirs in the future through the evaporation process.
For several decades, Australia has been investigating mechanisms to minimize evaporation from reservoirs. These include the use of physical and chemical covers, windbreaks and even modifying the reservoir shape in order to reduce its surface area. Most of these techniques however, have been shown to be ineffective, as in the example of windbreaks; to be excessively expensive, as in the example of physical covers and modifying the reservoir shape; or to impose potential risks to the water quality, as in the use of chemical covers. Destratification by air-bubble plumes, which involves pumping compressed air into the interior of a reservoir, thereby allowing the resultant bubbles to rise and carry cold bottom water to the surface, is one technique that deserves further investigation. Air-bubble plumes have been suggested in literature as a potential mechanism for reducing evaporation from reservoirs due to their potential effects on water temperature change.
The primary aim of destratification by air-bubble plumes is to maintain or improve the quality of the reservoir water, specifically by increasing dissolved oxygen in the water. The potential of these systems to reduce evaporative losses is related to the change in water temperature attributable to mixing. The intuitive principle is that cold hypolimnetic water is lifted by the air bubbles, and once at the surface, this water mixes with the lighter epilimnetic water, reducing its temperature and consequently, evaporation rates.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Engineering
Full Text
17
Stoddart, Daniel P. "Petroleum and nitrogen compound reservoir geochemistry of the Eldfisk chalk reservoir". Thesis, University of Newcastle Upon Tyne, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262654.
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18
Gomes, Jorge S. "Reservoir description of the Arab-C Dukhan carbonate reservoir for improved reservoir management and use as a subsurface analogue". Thesis, Heriot-Watt University, 2001. http://hdl.handle.net/10399/1141.
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19
Seetha, Ram Katakam V. "Conjunctive And Multipurpose Operation Of Reservoirs Using Genetic Algorithms". Thesis, Indian Institute of Science, 2000. https://etd.iisc.ac.in/handle/2005/222.
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Optimal operation of reservoir systems is necessary for better utilizing the limited water resources and to justify the high capital investments associated with reservoir projects. However, finding optimal policies for real-life problems of reservoir systems operation (RSO) is a challenging task as the available analytical methods can not handle the arbitrary functions of the problem and almost all methods employed are numerical or iterative type that are computer dependent. Since the computer resources in terms of memory and CPU time are limited, a limit exists for the size of the problem, in terms of arithmetic and memory involved, that can be handled. This limit is approached quickly as the dimension and the nonlinearity of the problem increases.
In encountering the complex aspects of the problem all the traditionally employed methods have their own drawbacks. Linear programming (LP), though very efficient in dealing with linear functions, can not handle nonlinear functions which is the case mostly in real-life problems. Attempting to approximate nonlinear functions to linear ones results in the problem size growing enormously. Dynamic programming (DP), though suitable for most of the RSO problems, requires exponentially increasing computer resources as the dimension of the problem increases and at present many high dimensional real-life problems can not be solved using DP. Nonlinear programming (NLP) methods are not known to be efficient in RSO problems due to slow rate of convergence and inability to handle stochastic problems. Simulation methods can, practically, explore only a small portion of the search region. Many simplifications in formulations and adoption of approximate methods in literature still fall short in addressing the most critical aspects, namely multidimensionality, stochasticity, and additional complexity in conjunctive operation, of the problem. As the problem complexity increases and the possibility of arriving at the solution recedes, a near optimal solution with the best use of computational resources can be very valuable. In this context, genetic algorithms (GA) can be a promising technique which is believed to have an advantage in terms of efficient use of computer resources.
GA is a random search method which find, in general, near optimal solutions using evolutionary mechanism of natural selection and natural genetics. When a pool of feasible solutions, represented in a coded form, are given fitness according to a objective function and explored by genetic operators for obtaining new pools of solutions, then the ensuing trajectories of solutions come closer and closer to the optimal solution which has the greatest fitness associated with it. GA can be applied to arbitrary functions and is not excessively sensitive to the dimension of the problem. Though in general GA finds only the near optimal solutions trapping in local optima is not a serious problem due to global look and random search.
Since GA is not fully explored for RSO problems two such problems are selected here to study the usefulness and efficiency of GA in obtaining near optimal solutions. One problem is conjunctive operation of a system consisting of a surface reservoir and an aquifer, taken from the literature for which deterministic and stochastic models are solved. Another problem is real-time operation of a multipurpose reservoir, operated for irrigation (primary purpose) and hydropower production, which is in the form of a case study.
The conjunctive operation problem consists of determining optimal policy for a combined system of a surface reservoir and an aquifer. The surface reservoir releases water to an exclusive area for irrigation and to a recharge facility from which it reaches the aquifer in the following period. Another exclusive area is irrigated by water pumped from the aquifer. The objective is to maximize the total benefit from the two irrigated areas. The inflow to the surface reservoir is treated as constant in deterministic model and taken at 6 different classes in stochastic model. The hydrological interactions between aquifer and reservoir are described using a lumped parameter model in which the average aquifer water table is arrived at based on the quantity of water in the aquifer, and local drawdown in pumping well is neglected. In order to evaluate the GA solution both deterministic and stochastic models are solved using DP and stochastic DP (SDP) techniques respectively. In the deterministic model, steady state (SS) cyclic (repetitive) solution is identified in DP as well as in GA. It is shown that the benefit from GA solution converges to as near as 95% of the benefit from exact DP solution at a highly discounted CPU time.
In the stochastic model, the steady state solution obtained with SDP consists of converged first stage decisions, which took a 8-stage horizon, for any combination of components of the system state. The GA solution is obtained after simplifying the model to reduce the number of decision variables. Unlike SDP policy which gives decisions considering the state of the system in terms of storages, at reservoir, aquifer, and recharge facility, and previous inflow at the beginning of that period, GA gives decisions for each period of the horizon considering only the past inflow state of the period. In arriving at these decisions the effect of neglected state information is approximately reflected in the decisions by the process of refinement of the decisions, to conform to feasibility of storages in reservoir and aquifer, carried out in a simplified simulation process. Moreover, the validity of the solution is confirmed by simulating the operation with all possible inflow sequences for which the 8-stages benefit converged up to 90 % of the optimum. However, since 8 stages are required for convergence to SS, a 16-stage process is required for GA method in which the first 8 stages policy is valid. Results show that GA convergence to the optimum is satisfactory, justifying the approximations, with significant savings in CPU time.
For real-time operation of a multipurpose reservoir, a rule curve (RC) based monthly operation is formulated and applied on a real-life problem involving releases for irrigation as well as power production. The RC operation is based on the target storages that have to be maintained, at each season of the year, in the reservoir during normal hydrological conditions. Exceptions to target storages are allowed when the demands have to be met or for conserving water during the periods of high inflows. The reservoir in the case study supplies water to irrigation fields through two canals where a set of turbines each at the canal heads generate hydropower. A third set of turbines operate on the river bed with the water let out downstream from the dam. The problem consists of determining the the RC target storages that facilitate maximum power production while meeting the irrigation demands up to a given reliability level. The RC target storages are considered at three different levels, corresponding to dry, normal, and wet conditions, according to the system state in terms of actual (beginning of period) storage of the reservoir. That is, if the actual beginning storage of the reservoir is less than some coefficient, dry-coe, times the normal target storage the target for the end of the period storage is taken at the dry storage target (of the three sets of storages). Similarly the wet level is taken for the end of the period target if the actual beginning storage is greater than some coefficient, wet-coe, times the normal storage. For other conditions the target is the normal storage level.
The dry-coe and wet-coe parameters are obtained by trial and error analysis working on a small sequence of inflows. The three sets of targets are obtained from optimization over a 1000 year generated inflow sequence. With deterministic DP solutions, for small sequences of inflows, the optimization capability of GA-RC approach, in terms of objective function convergence, and generalization or robustness capability of GA-RC approach, for which the GA-RC benefit is obtained by simulating the reservoir operation using the previously obtained GA-RC solution, are evaluated. In both the cases GA-RC approach proves to be promising. Finally a 15 year real-time simulation of the reservoir is carried out using historical inflows and demands and the comparison with the historical operation shows significant improvement in benefit, i.e. power produced, without compromising irrigation demands throughout the simulation period.
20
Seetha, Ram Katakam V. "Conjunctive And Multipurpose Operation Of Reservoirs Using Genetic Algorithms". Thesis, Indian Institute of Science, 2000. http://hdl.handle.net/2005/222.
Pełny tekst źródłaStreszczenie:
Optimal operation of reservoir systems is necessary for better utilizing the limited water resources and to justify the high capital investments associated with reservoir projects. However, finding optimal policies for real-life problems of reservoir systems operation (RSO) is a challenging task as the available analytical methods can not handle the arbitrary functions of the problem and almost all methods employed are numerical or iterative type that are computer dependent. Since the computer resources in terms of memory and CPU time are limited, a limit exists for the size of the problem, in terms of arithmetic and memory involved, that can be handled. This limit is approached quickly as the dimension and the nonlinearity of the problem increases.
In encountering the complex aspects of the problem all the traditionally employed methods have their own drawbacks. Linear programming (LP), though very efficient in dealing with linear functions, can not handle nonlinear functions which is the case mostly in real-life problems. Attempting to approximate nonlinear functions to linear ones results in the problem size growing enormously. Dynamic programming (DP), though suitable for most of the RSO problems, requires exponentially increasing computer resources as the dimension of the problem increases and at present many high dimensional real-life problems can not be solved using DP. Nonlinear programming (NLP) methods are not known to be efficient in RSO problems due to slow rate of convergence and inability to handle stochastic problems. Simulation methods can, practically, explore only a small portion of the search region. Many simplifications in formulations and adoption of approximate methods in literature still fall short in addressing the most critical aspects, namely multidimensionality, stochasticity, and additional complexity in conjunctive operation, of the problem. As the problem complexity increases and the possibility of arriving at the solution recedes, a near optimal solution with the best use of computational resources can be very valuable. In this context, genetic algorithms (GA) can be a promising technique which is believed to have an advantage in terms of efficient use of computer resources.
GA is a random search method which find, in general, near optimal solutions using evolutionary mechanism of natural selection and natural genetics. When a pool of feasible solutions, represented in a coded form, are given fitness according to a objective function and explored by genetic operators for obtaining new pools of solutions, then the ensuing trajectories of solutions come closer and closer to the optimal solution which has the greatest fitness associated with it. GA can be applied to arbitrary functions and is not excessively sensitive to the dimension of the problem. Though in general GA finds only the near optimal solutions trapping in local optima is not a serious problem due to global look and random search.
Since GA is not fully explored for RSO problems two such problems are selected here to study the usefulness and efficiency of GA in obtaining near optimal solutions. One problem is conjunctive operation of a system consisting of a surface reservoir and an aquifer, taken from the literature for which deterministic and stochastic models are solved. Another problem is real-time operation of a multipurpose reservoir, operated for irrigation (primary purpose) and hydropower production, which is in the form of a case study.
The conjunctive operation problem consists of determining optimal policy for a combined system of a surface reservoir and an aquifer. The surface reservoir releases water to an exclusive area for irrigation and to a recharge facility from which it reaches the aquifer in the following period. Another exclusive area is irrigated by water pumped from the aquifer. The objective is to maximize the total benefit from the two irrigated areas. The inflow to the surface reservoir is treated as constant in deterministic model and taken at 6 different classes in stochastic model. The hydrological interactions between aquifer and reservoir are described using a lumped parameter model in which the average aquifer water table is arrived at based on the quantity of water in the aquifer, and local drawdown in pumping well is neglected. In order to evaluate the GA solution both deterministic and stochastic models are solved using DP and stochastic DP (SDP) techniques respectively. In the deterministic model, steady state (SS) cyclic (repetitive) solution is identified in DP as well as in GA. It is shown that the benefit from GA solution converges to as near as 95% of the benefit from exact DP solution at a highly discounted CPU time.
In the stochastic model, the steady state solution obtained with SDP consists of converged first stage decisions, which took a 8-stage horizon, for any combination of components of the system state. The GA solution is obtained after simplifying the model to reduce the number of decision variables. Unlike SDP policy which gives decisions considering the state of the system in terms of storages, at reservoir, aquifer, and recharge facility, and previous inflow at the beginning of that period, GA gives decisions for each period of the horizon considering only the past inflow state of the period. In arriving at these decisions the effect of neglected state information is approximately reflected in the decisions by the process of refinement of the decisions, to conform to feasibility of storages in reservoir and aquifer, carried out in a simplified simulation process. Moreover, the validity of the solution is confirmed by simulating the operation with all possible inflow sequences for which the 8-stages benefit converged up to 90 % of the optimum. However, since 8 stages are required for convergence to SS, a 16-stage process is required for GA method in which the first 8 stages policy is valid. Results show that GA convergence to the optimum is satisfactory, justifying the approximations, with significant savings in CPU time.
For real-time operation of a multipurpose reservoir, a rule curve (RC) based monthly operation is formulated and applied on a real-life problem involving releases for irrigation as well as power production. The RC operation is based on the target storages that have to be maintained, at each season of the year, in the reservoir during normal hydrological conditions. Exceptions to target storages are allowed when the demands have to be met or for conserving water during the periods of high inflows. The reservoir in the case study supplies water to irrigation fields through two canals where a set of turbines each at the canal heads generate hydropower. A third set of turbines operate on the river bed with the water let out downstream from the dam. The problem consists of determining the the RC target storages that facilitate maximum power production while meeting the irrigation demands up to a given reliability level. The RC target storages are considered at three different levels, corresponding to dry, normal, and wet conditions, according to the system state in terms of actual (beginning of period) storage of the reservoir. That is, if the actual beginning storage of the reservoir is less than some coefficient, dry-coe, times the normal target storage the target for the end of the period storage is taken at the dry storage target (of the three sets of storages). Similarly the wet level is taken for the end of the period target if the actual beginning storage is greater than some coefficient, wet-coe, times the normal storage. For other conditions the target is the normal storage level.
The dry-coe and wet-coe parameters are obtained by trial and error analysis working on a small sequence of inflows. The three sets of targets are obtained from optimization over a 1000 year generated inflow sequence. With deterministic DP solutions, for small sequences of inflows, the optimization capability of GA-RC approach, in terms of objective function convergence, and generalization or robustness capability of GA-RC approach, for which the GA-RC benefit is obtained by simulating the reservoir operation using the previously obtained GA-RC solution, are evaluated. In both the cases GA-RC approach proves to be promising. Finally a 15 year real-time simulation of the reservoir is carried out using historical inflows and demands and the comparison with the historical operation shows significant improvement in benefit, i.e. power produced, without compromising irrigation demands throughout the simulation period.
21
Fok, Chun-wing, i 霍雋穎. "Un-reserving reservoir: multi-layered water infrastructure in lower Shing Mun reservoir". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47542342.
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22
Ngo, Long Le. "Optimising reservoir operation a case study of the Hoa Binh reservoir, Vietnam /". Kgs. Lyngby : Institute of Environment & Resources, Technical University of Denmark, 2006. http://www.er.dtu.dk/publications/fulltext/2006/MR2006-148.pdf.
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Merrick, Chester John. "Phytoplankton-zooplankton interactions in Mt. Bold Reservoir, South Australia /". Title page, contents and summary only, 1990. http://web4.library.adelaide.edu.au/theses/09PH/09phm568.pdf.
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Ahmed, Elfeel Mohamed. "Improved upscaling and reservoir simulation of enhanced oil recovery processes in naturally fractured reservoirs". Thesis, Heriot-Watt University, 2014. http://hdl.handle.net/10399/2755.
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Naturally fractured reservoirs (NFR) contain a significant amount of remaining petroleum reserves and are now considered for Enhanced Oil Recovery (EOR) schemes that involve three-phase flow such as water-alternating-gas (WAG) injection. Accurate numerical simulation of flow in NFR is essential for sound reservoir management decisions to maximise oil recovery and minimise the cost of field development. In this thesis, two important issues related to flow simulation in NFR are investigated. First, a step-wise upscaling approach is developed to evaluate the accuracy of dual porosity models in estimating matrix-fracture transfer duringWAG injection. It was found that the classical dual porosity models generally overestimate recovery from matrix blocks. Hence, a double block model was developed and extended to a multi-rate dual porosity (MRDP). The multi-rate double block model showed significant improvements in matching detailed fine grid simulations of three-phase matrix-fracture transfer. Second, the accuracy of upscaling discrete fracture networks (DFN) is assessed and its impact on history matching was investigated on a real fractured reservoir. A new method to upscale the shape factors needed for MRDP models from DFN is presented. This method is a notable step towards more accurate but still efficient reservoir simulation in NFR.
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Dominick, Nehemiah Eliezer. "Reservoir heterogeneity of the sandstone reservoirs within the Pletmos basin, block11a, offshore South Africa". Thesis, University of the Western Cape, 2014. http://hdl.handle.net/11394/3901.
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>Magister Scientiae - MScThis study is aimed at illustrating the reservoir heterogeneity in the BCII - BCI interval of the Ga-field, offshore South Africa. This was achieved by generating a conceptual static model as a predictive tool for the BCII - BCI interval. The reservoir zones between BCII - BCI were sub divided into two major zones, viz: zone A and zone B. Petrophysical analysis was conducted on the three wells Ga-A3, Ga-Q1 and Ga-Q2. The application of the sequential gaussian algorithm ensured that all of the available data was honoured to the highest extent in generating the realisations to display the heterogeneity of the BCII – BCI sandstone reservoir. Sampling values from the well logs were extrapolated into the 3D grid. Each reservoir contained a percentage of shale or clay of about 45% -50%. Small scaled reservoir heterogeneity has been construed to the influence of the sedimentary structures. Large scaled reservoir heterogeneity has been identified, due to the lateral extent of the claystones which is widely distributed throughout the study area
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Grema, Alhaji Shehu. "Optimization of Reservoir Waterflooding". Thesis, Cranfield University, 2014. http://dspace.lib.cranfield.ac.uk/handle/1826/9263.
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Waterflooding is a common type of oil recovery techniques where water is
pumped into the reservoir for increased productivity. Reservoir states change
with time, as such, different injection and production settings will be required to
lead the process to optimal operation which is actually a dynamic optimization
problem. This could be solved through optimal control techniques which
traditionally can only provide an open-loop solution. However, this solution is
not appropriate for reservoir production due to numerous uncertain properties
involved. Models that are updated through the current industrial practice of
‘history matching’ may fail to predict reality correctly and therefore, solutions
based on history-matched models may be suboptimal or non-optimal at all.
Due to its ability in counteracting the effects uncertainties, direct feedback
control has been proposed recently for optimal waterflooding operations. In this
work, two feedback approaches were developed for waterflooding process
optimization. The first approach is based on the principle of receding horizon
control (RHC) while the second is a new dynamic optimization method
developed from the technique of self-optimizing control (SOC). For the SOC
methodology, appropriate controlled variables (CVs) as combinations of
measurement histories and manipulated variables are first derived through
regression based on simulation data obtained from a nominal model. Then the
optimal feedback control law was represented as a linear function of
measurement histories from the CVs obtained.
Based on simulation studies, the RHC approach was found to be very sensitive
to uncertainties when the nominal model differed significantly from the
conceived real reservoir. The SOC methodology on the other hand, was shown
to achieve an operational profit with only 2% worse than the true optimal
control, but 30% better than the open-loop optimal control under the same
uncertainties. The simplicity of the developed SOC approach coupled with its
robustness to handle uncertainties proved its potentials to real industrial
applications.
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Dale, Matthew. "Reservoir Computing in materio". Thesis, University of York, 2018. http://etheses.whiterose.ac.uk/22306/.
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Reservoir Computing first emerged as an efficient mechanism for training recurrent neural networks and later evolved into a general theoretical model for dynamical systems. By applying only a simple training mechanism many physical systems have become exploitable unconventional computers. However, at present, many of these systems require careful selection and tuning by hand to produce usable or optimal reservoir computers. In this thesis we show the first steps to applying the reservoir model as a simple computational layer to extract exploitable information from complex material substrates. We argue that many physical substrates, even systems that in their natural state might not form usable or "good" reservoirs, can be configured into working reservoirs given some stimulation. To achieve this we apply techniques from evolution in materio whereby configuration is through evolved input-output signal mappings and targeted stimuli. In preliminary experiments the combined model and configuration method is applied to carbon nanotube/polymer composites. The results show substrates can be configured and trained as reservoir computers of varying quality. It is shown that applying the reservoir model adds greater functionality and programmability to physical substrates, without sacrificing performance. Next, the weaknesses of the technique are addressed, with the creation of new high input-output hardware system and an alternative multi-substrate framework. Lastly, a substantial effort is put into characterising the quality of a substrate for reservoir computing, i.e its ability to realise many reservoirs. From this, a methodological framework is devised. Using the framework, radically different computing substrates are compared and assessed, something previously not possible. As a result, a new understanding of the relationships between substrate, tasks and properties is possible, outlining the way for future exploration and optimisation of new computing substrates.
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Kulkarni, Manjari S. "Memristor-based Reservoir Computing". PDXScholar, 2012. https://pdxscholar.library.pdx.edu/open_access_etds/899.
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In today's nanoscale era, scaling down to even smaller feature sizes poses a significant challenge in the device fabrication, the circuit, and the system design and integration. On the other hand, nanoscale technology has also led to novel materials and devices with unique properties. The memristor is one such emergent nanoscale device that exhibits non-linear current-voltage characteristics and has an inherent memory property, i.e., its current state depends on the past. Both the non-linear and the memory property of memristors have the potential to enable solving spatial and temporal pattern recognition tasks in radically different ways from traditional binary transistor-based technology. The goal of this thesis is to explore the use of memristors in a novel computing paradigm called "Reservoir Computing" (RC). RC is a new paradigm that belongs to the class of artificial recurrent neural networks (RNN). However, it architecturally differs from the traditional RNN techniques in that the pre-processor (i.e., the reservoir) is made up of random recurrently connected non-linear elements. Learning is only implemented at the readout (i.e., the output) layer, which reduces the learning complexity significantly. To the best of our knowledge, memristors have never been used as reservoir components. We use pattern recognition and classification tasks as benchmark problems. Real world applications associated with these tasks include process control, speech recognition, and signal processing. We have built a software framework, RCspice (Reservoir Computing Simulation Program with Integrated Circuit Emphasis), for this purpose. The framework allows to create random memristor networks, to simulate and evaluate them in Ngspice, and to train the readout layer by means of Genetic Algorithms (GA). We have explored reservoir-related parameters, such as the network connectivity and the reservoir size along with the GA parameters. Our results show that we are able to efficiently and robustly classify time-series patterns using memristor-based dynamical reservoirs. This presents an important step towards computing with memristor-based nanoscale systems.
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Tran, Dat Tien. "Memcapacitive Reservoir Computing Architectures". PDXScholar, 2019. https://pdxscholar.library.pdx.edu/open_access_etds/5001.
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In this thesis, I propose novel brain-inspired and energy-efficient computing systems. Designing such systems has been the forefront goal of neuromorphic scientists over the last few decades. The results from my research show that it is possible to design such systems with emerging nanoscale memcapacitive devices.
Technological development has advanced greatly over the years with the conventional von Neumann architecture. The current architectures and materials, however, will inevitably reach their physical limitations. While conventional computing systems have achieved great performances in general tasks, they are often not power-efficient in performing tasks with large input data, such as natural image recognition and tracking objects in streaming video. Moreover, in the von Neumann architecture, all computations take place in the Central Processing Unit (CPU) and the results are saved in the memory. As a result, information is shuffled back and forth between the memory and the CPU for processing, which creates a bottleneck due to the limited bandwidth of data paths. Adding cache memory and using general-purpose Graphic Processing Units (GPUs) do not completely resolve this bottleneck.
Neuromorphic architectures offer an alternative to the conventional architecture by mimicking the functionality of a biological neural network. In a biological neural network, neurons communicate with each other through a large number of dendrites and synapses. Each neuron (a processing unit) locally processes the information that is stored in its input synapses (memory units). Distributing information to neurons and localizing computation at the synapse level alleviate the bottleneck problem and allow for the processing of a large amount of data in parallel. Furthermore, biological neural networks are highly adaptable to complex environments, tolerant of system noise and variations, and capable of processing complex information with extremely low power.
Over the past five decades, researchers have proposed various brain-inspired architectures to perform neuromorphic tasks. IBM's TrueNorth is considered as the state-of-the-art brain-inspired architecture. It has 106 CMOS neurons with 256 x 256 programmable synapses and consumes about 60nW/neuron. Even though TrueNorth is power-efficient, its number of neurons and synapses is nothing compared to a human brain that has 1011 neurons and each neuron has, on average, 7,000 synaptic connections to other neurons. The human brain only consumes 2.3nW/neuron.
The memristor brought neuromorphic computing one step closer to the human brain target. A memristor is a passive nano-device that has a memory. Its resistance changes with applied voltages. The resistive change with an applied voltage is similar to the function of a synapse. Memristors have been the prominent option for designing low power systems with high-area density. In fact, Truong and Min reported that an improved memristor-based crossbar performed a neuromorphic task with 50% reduction in area and 48% of power savings compared to CMOS arrays. However, memristive devices, by their nature, are still resistors, and the power consumption is bounded by their resistance. Here, a memcapacitor offers a promising alternative. My initial work indicated that memcapacitive networks performed complex tasks with equivalent performance, compared to memristive networks, but with much higher energy efficiency.
A memcapacitor is also a two-terminal nano-device and its capacitance varies with applied voltages. Similar to a memristor, the capacitance of the memcapacitor changes with an applied voltage, similar to the function of a synapse. The memcapacitor is a storage device and does not consume static energy. Its switching energy is also small due to its small capacitance (nF to pF range). As a result, networks of memcapacitors have the potential to perform complex tasks with much higher power efficiency.
Several memcapacitive synaptic models have been proposed as artificial synapses. Pershin and Di Ventra illustrated that a memcapacitor with two diodes has the functionality of a synapse. Flak suggested that a memcapacitor behaves as a synapse when it is connected with three CMOS switches in a Cellular Nanoscale Network (CNN). Li et al. demonstrated that when four identical memcapacitors are connected in a bridge network, they characterize the function of a synapse as well.
Reservoir Computing (RC) has been used to explain higher-order cognitive functions and the interaction of short-term memory with other cognitive processes. Rigotti et al. observed that a dynamic system with short-term memory is essential in defining the internal brain states of a test agent. Although both traditional Recurrent Neural Networks (RNNs) and RC are dynamical systems, RC has a great benefit over RNNs due to the fact that the learning process of RC is simple and based on the training of the output layer. RC harnesses the computing nature of a random network of nonlinear devices, such as memcapacitors.
Appeltant et al. showed that RC with a simplified reservoir structure is sufficient to perform speech recognition. Fewer nonlinear units connecting in a delay feedback loop provide enough dynamic responses for RC. Fewer units in reservoirs mean fewer connections and inputs, and therefore lower power consumption.
As Goudarzi and Teuscher indicated, RC architectures still have inherent challenges that need to be addressed. First, theoretical studies have shown that both regular and random reservoirs achieve similar performances for particular tasks. A random reservoir, however, is more appropriate for unstructured networks of nanoscale devices. What is the role of network structure in RC for solving a task (Q1)?
Secondly, the nonlinear characteristics of nanoscale devices contribute directly to the dynamics of a physical network, which influences the overall performance of an RC system. To what degree is a mixture of nonlinear devices able to improve the performances of reservoirs (Q2)?
Thirdly, modularity, such as CMOS circuits in a digital building, is an essential key in building a complex system from fundamental blocks. Is hierarchical RCs able to solve complex tasks? What network topologies/hierarchies will lead to optimal performance? What is the learning complexity of such a system (Q3)?
My research goal is to address the above RC challenges by exploring memcapacitive reservoir architectures. The analysis of memcapacitive monolithic reservoirs addresses both questions Q1 and Q2 above by showing that Small-World Power-Law (SWPL) structure is an optimal topological structure for RCs to perform time series prediction (NARMA-10), temporal recognition (Isolate Spoken Digits), and spatial task (MNIST) with minimal power consumption. On average, the SWPL reservoirs reduce significantly the power consumption by a factor of 1.21x, 31x, and 31.2x compared to the regular, the random, and the small-world reservoirs, respectively. Further analysis of SWPL structures underlines that high locality α and low randomness β decrease the cost to the systems in terms of wiring and nanowire dissipated power but do not guarantee the optimal performance of reservoirs. With a genetic algorithm to refine network structure, SWPL reservoirs with optimal network parameters are able to achieve comparable performance with less power. Compared to the regular reservoirs, the SWPL reservoirs consume less power, by a factor of 1.3x, 1.4x, and 1.5x. Similarly, compared to the random topology, the SWPL reservoirs save power consumption by a factor of 4.8x, 1.6x, and 2.1x, respectively. The simulation results of mixed-device reservoirs (memristive and memcapacitive reservoirs) provide evidence that the combination of memristive and memcapacitive devices potentially enhances the nonlinear dynamics of reservoirs in three tasks: NARMA-10, Isolated Spoken Digits, and MNIST.
In addressing the third question (Q3), the kernel quality measurements show that hierarchical reservoirs have better dynamic responses than monolithic reservoirs. The improvement of dynamic responses allows hierarchical reservoirs to achieve comparable performance for Isolated Spoken Digit tasks but with less power consumption by a factor of 1.4x, 8.8x, 9.5, and 6.3x for delay-line, delay-line feedback, simple cycle, and random structures, respectively. Similarly, for the CIFAR-10 image tasks, hierarchical reservoirs gain higher performance with less power, by a factor of 5.6x, 4.2x, 4.8x, and 1.9x. The results suggest that hierarchical reservoirs have better dynamics than the monolithic reservoirs to solve sufficiently complex tasks.
Although the performance of deep mem-device reservoirs is low compared to the state-of-the-art deep Echo State Networks, the initial results demonstrate that deep mem-device reservoirs are able to solve a high-dimensional and complex task such as polyphonic music task. The performance of deep mem-device reservoirs can be further improved with better settings of network parameters and architectures.
My research illustrates the potentials of novel memcapacitive systems with SWPL structures that are brained-inspired and energy-efficient in performing tasks. My research offers novel memcapacitive systems that are applicable to low-power applications, such as mobile devices and the Internet of Things (IoT), and provides an initial design step to incorporate nano memcapacitive devices into future applications of nanotechnology.
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Aniekwena, Anthony Udegbunam. "Integrated reservoir study of the 8 reservoir of the Green Canyon 18 field". Texas A&M University, 2003. http://hdl.handle.net/1969.1/1196.
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The move into deeper waters in the Gulf of Mexico has produced new opportunities for petroleum production, but it also has produced new challenges as different reservoir problems are encountered. This integrated reservoir characterization effort has provided useful information about the behavior and characteristics of a typical unconsolidated, overpressured, fine-grained, turbidite reservoir, which constitutes the majority of the reservoirs present in the Outer Continental Shelf of the Gulf of Mexico.
Reservoirs in the Green Canyon 18 (GC 18) field constitute part of a turbidite package with reservoir quality typically increasing with depth. Characterization of the relatively shallow 8 reservoir had hitherto been hindered by the difficulty in resolving its complex architecture and stratigraphy. Furthermore, the combination of its unconsolidated rock matrix and abnormal pore pressure has resulted in severe production-induced compaction.
The reservoir's complex geology had previously obfuscated the delineation of its hydrocarbon accumulation and determination of its different resource volumes. Geological and architectural alterations caused by post-accumulation salt tectonic activities had previously undermined the determination of the reservoir's active drive mechanisms and their chronology.
Seismic interpretation has provided the reservoir geometry and topography. The reservoir stratigraphy has been defined using log, core and seismic data. With well data as pilot points, the spatial distribution of the reservoir properties has been defined using geostatistics. The resulting geological model was used to construct a dynamic flow model that matched historical production and pressure data..
The reservoir's pressure and production behavior indicates a dominant compaction drive mechanism. The results of this work show that the reservoir performance is influenced not only by the available drive energy, but also by the spatial distribution of the different facies relative to well locations. The study has delineated the hydrocarbon bearing reservoir, quantified the different resource categories as STOIIP/GIIP = 19.8/26.2 mmstb/Bscf, ultimate recovery = 9.92/16.01 mmstb/Bscf, and reserves (as of 9/2001) = 1.74/5.99 mmstb/Bscf of oil and gas, respectively. There does not appear to be significant benefit to infill drilling or enhanced recovery operations.
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Xie, Ming 1973. "Prediction of daily net inflows for management of reservoir systems". Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=33043.
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Operational planning of water resource systems like reservoirs and hydropower plants calls for real-time forecasting of reservoir inflow. Reservoir daily inflow forecasts provide a warning of impending floods or drought conditions and help to optimize operating policies for reservoir management based on a fine time scale. The aim of this study was to determine the best model for daily reservoir inflow prediction through linear regression, exponential smoothing and artificial neural network (ANN) techniques. The Hedi reservoir, the third largest reservoir in south China with a 1.144 x 109 m 3, was selected as the study site. The performance of these forecasting models, in terms of forecasting accuracy, efficiency of model development and adaptability for future prediction, were compared to one another. All models performed well during the dry season (inflow with low variability), while the non-linear ANNs were superior to other models in frontal rainy season and typhoon season (inflow with high variability). The performance of ANN models were hardly affected by the high degree of uncertainty and variability inherent to the rainy season. Stepwise selection was very helpful in identifying significant variables for regression models and ANNs. This procedure reduced ANN's size and greatly improved forecasting accuracy for ANN models. The impact of training data series, model architecture and network internal parameters on ANNs performances were also addressed in this study. The overall evaluation indicates that ANNs are an effective and robust tool for input-output mapping under more extreme and variable conditions. ANNs provide an alternative forecasting approach to conventional time series forecasting models for daily reservoir inflow prediction.
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Sebastià, Miravet Pau. "Insights on the interaction of Ralstonia solanacearum with Solanum dulcamara and Solanum tuberosum". Doctoral thesis, Universitat Autònoma de Barcelona, 2020. http://hdl.handle.net/10803/672037.
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Ralstonia solanacearum és un dels patògens de plantes bacterians més destructius arreu del món. Provoca el marciment bacterià en més de 200 espècies vegetals, entre elles cultius d’alta importància econòmica. Grans esforços s’han dut a terme durant les últimes dècades per tal d’identificar els factors de virulència més rellevants d’aquest patogen, però una comprensió més detallada i dinàmica sobre els perfils d’expressió gènica dels determinants de virulència al llarg del procés d’infecció faltava. Així també, diferents grups de recerca han identificat hostes salvatges de R. solanacearum, la qual cosa ha ajudat a ampliar el coneixement de com aquest bacteri completa el seu cicle de vida complex. No obstant això, la informació relacionada amb la interacció entre R. solanacearum i els seus hostes reservori era molt escassa. En aquesta tesi, hem abordat el primer repte mitjançant l’establiment de tres estadis diferents d’infecció de la soca UY031 de R. solanacearum en patatera: l’apoplast, xilema inicial i xilema tardà. El transcriptoma bacterià al llarg de la infecció i els seu posterior anàlisi van revelar com R. solanacearum activa o reprimeix gens de virulència específics per tal de manipular les defenses de la planta així com l’ús de vies metabòliques bacterianes per facilitar la colonització dels diferents teixits vegetals durant la infecció. Destaquem el fet que R. solanacearum indueix l’expressió de la majoria dels efectors de tipus III durant la fase del xilema. A més a més, diferents tipus de motilitat bacteriana estan regulades i associades a diferents ambients d’infecció de la planta i per últim, que R. solanacearum depèn de l’activació de diferents gens del metabolisme del nitrogen per adaptar-se a ambients d’hipòxia al xilema. El segon gran repte d’aquesta tesi ha sigut comprendre com R. solanacearum interacciona amb el seu hoste reservori Solanum dulcamara. Després d’analitzar el procés d’infecció utilitzant diferents mètodes d’inoculació, vam concloure que S. dulcamara no és només un hoste reservori però també un hoste tolerant de R. solanacearum, perquè quantitats similars de bacteri es troben comparat amb altres hostes susceptibles, però els símptomes de marciment bacterià són més baixos. Hem aprés que S. dulcamara presenta una estructura lignificada al xilema molt estable que no disminueix després de la infecció, la qual cosa explica parcialment el fenotip tolerant observat. Per últim, hem esbrinat que la tolerància de S. dulcamara contra R. solanacearum és més marcada a temperatures més fresques, destacant la importància de l’ambient quan s’investiguen interaccions entre plantes i patògens. En resum, aquest treball proporciona tant un terreny sòlid per estudis de caracterització de diferents factors de virulència de R. solanacearum in planta, com també una aproximació del comportament del bacteri dins del seu hoste reservori tolerant S. dulcamara.Ralstonia solanacearum es uno de los patógenos de plantas bacterianos más destructivos en todo el mundo. Provoca el marchitamiento bacteriano en más de 200 especies vegetales, entre ellas cultivos de alta importancia económica. Grandes esfuerzos se han llevado a cabo en las últimas décadas con tal de identificar los factores de virulencia más relevantes de este patógeno, pero faltaba una comprensión más detallada y dinámica sobre los perfiles de expresión génica de los determinantes de virulencia durante el proceso de infección. Así mismo, diferentes grupos de investigación han identificado huéspedes salvajes de R. solanacearum, lo cual ha ayudado a ampliar el conocimiento de cómo esta bacteria completa su ciclo de vida complejo. No obstante, la información relacionada con la interacción entre R. solanacearum y sus huéspedes reservorio era muy escasa. En esta tesis, hemos abordado el primer reto mediante el establecimiento de tres estadíos diferentes de infección de la cepa UY031 de R. solanacearum en patata: apoplasto, xilema inicial y xilema tardío. El transcriptoma bacteriano a lo largo de la infección y su posterior análisis revelaron cómo R. solanacearum activa o reprime genes de virulencia específicos con tal de manipular las defensas de la planta, así como el uso de vías metabólicas bacterianas para facilitar la colonización de diferentes tejidos vegetales durante la infección. Destacamos el hecho que R. solanacearum induce la expresión de la mayoría de los efectores de tipo III durante la fase del xilema. Además, diferentes tipos de motilidad bacteriana están reguladas y asociadas a diferentes ambientes de infección de la planta y por último, R. solanacearum depende de la activación de diferentes genes del metabolismo del nitrógeno para adaptar-se a ambientes de hipoxia en el xilema. El segundo gran reto de esta tesis ha sido entender cómo R. solanacearum interacciona con su huésped reservorio Solanum dulcamara. Después de analizar el proceso de infección utilizando diferentes métodos de inoculación, concluimos que S. dulcamara no es sólo un huésped reservorio, pero también un huésped tolerante de R. solanacearum, porque cantidades similares de bacteria se encuentran comparado con otros huéspedes susceptibles, pero los síntomas de marchitamiento bacteriano son más bajos. Hemos aprendido que S. dulcamara presenta una estructura lignificada al xilema muy estable que no disminuye después de la infección, lo cual explica parcialmente el fenotipo tolerante observado. Por último, hemos averiguado que la tolerancia de S. dulcamara contra R. solanacearum es más marcada a temperaturas más frescas, destacando la importancia del ambiente cuando se investigan interacciones entre plantas y patógenos. En resumen, este trabajo proporciona tanto un terreno sólido para el estudio de caracterización de diferentes factores de virulencia de R. solanacearum in planta, como también una aproximación del comportamiento de la bacteria dentro de su huésped reservorio tolerante S. dulcamara.
Ralstonia solanacearum is one of the most destructive bacterial plant pathogens worldwide. It causes bacterial wilt on more than 200 plant species, among them economically important crops. A big effort has been done during the last decades in order to identify the most relevant virulence factors of this pathogen, but a comprehensive and dynamic understanding of the gene expression profile of these virulence determinants along the infection process was lacking. Also, different groups have identified wild reservoir hosts of R. solanacearum, which has helped in broadening the knowledge of how this bacterium completes its complex life cycle. However, the information regarding the interaction between R. solanacearum and its reservoir hosts was very scarce. In this thesis, we have tackled the first challenge by establishing three different infection stages of R. solanacearum UY031 strain in potato: apoplast, early xylem and late xylem. The bacterial transcriptome along the infection process and its analysis revealed how R. solanacearum activates or represses specific virulence genes to hijack plant defences as well as the use of bacterial metabolic pathways to facilitate the colonization of different plant tissues during the infection. We underscore the fact that R. solanacearum induces the expression of most of its type III effectors during the xylem phase. In addition to that, different types of motility are regulated and associated to different plant environments and last but not least, that R. solanacearum largely depends on the activation of different nitrogen metabolism genes to adapt to the hypoxic xylem vessels. The second big challenge of this thesis has been to understand how R. solanacearum interacts with its reservoir host Solanum dulcamara. After analysing the infection process using different inoculation methods, we concluded that S. dulcamara it is not only a reservoir host but also a tolerant host of R. solanacearum, since similar bacterial loads are found compared to other susceptible hosts, but the bacterial wilt symptoms are much lower. We learned that S. dulcamara presents a very stable xylem lignification, which is not impaired upon bacterial infection, partly explaining this tolerant phenotype. Lastly, we found out that S. dulcamara tolerance against R. solanacearum is even more clear at cooler temperatures, underscoring the importance of the environment when investigating plant pathogen interactions. In summary, this work provides both a solid ground for in planta R. solanacearum functional and characterization studies of different virulence factors, as well as an insight of how the bacterium behaves inside its reservoir tolerant host S. dulcamara.
Universitat Autònoma de Barcelona. Programa de Doctorat en Biologia i Biotecnologia Vegetal
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Seers, Thomas Daniel. "Image based characterisation of structural heterogeneity within clastic reservoir analogues". Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/image-based-characterisation-of-structural-heterogeneity-within-clastic-reservoir-analogues(30de0147-57d2-428f-8a10-1b48476476a3).html.
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The presence of subseismic scale faulting within high porosity sandstone reservoirs and aquifers represents a significant source of uncertainty for activities such as hydrocarbon production and the geologic sequestration of carbon dioxide. The inability to resolve geometrical properties of these smaller scale faults, such as size, connectivity and intensity, using conventional subsurface datasets (i.e. seismic reflection tomography, wireline log and core), leads to ambiguous representations within reservoir models and simulators. In addition, more fundamental questions still remain over the role of cataclastic faults in the trapping and transfer of mobile geofluids within the subsurface, particularly when two or more immiscible fluid phases are present, as is the case during hydrocarbon accumulation, waterflood operations and CO2 injection. By harnessing recent developments in 3D digital surface and volume imaging, this study addresses uncertainties pertaining to the geometrical and petrophysical properties of subseismic scale faults within porous sandstone reservoirs. A novel structural feature extraction and modelling framework is developed, which facilitates the restoration of fault and fracture architecture from digital rock surface models. This framework has been used to derive volumetric fault abundance and connectivity from a normal sense array of cataclastic shear bands developed within high porosity sandstones of the Vale of Eden Basin, UK. These spatially resolved measures of discontinuity abundance provide the basis for the geostatistical extrapolation of fracture/fault intensity into reservoir modelling grids, which promises the introduction of a much higher degree of geological realism into discrete fracture network models than can currently be achieved through purely stochastic methods. Moreover, by establishing spatial correspondences between volumetric faulting intensity and larger scale features of deformation observed at the study area (cataclastic shear zones), the work demonstrates the potential to relate reservoir equivalent measures of fault or fracture abundance obtained from outcrop to seismically resolvable structures within the subsurface, aiding the prediction of reservoir structure from oilfield datasets. In addition to the derivation of continuum scale properties of sub-seismic scale fault networks, a further investigation into the pore-scale controls which govern the transfer of fluids within cataclised sandstones has been conducted. Through X-ray tomographic imaging of experimental core flood (scCO2-brine primary drainage) through a cataclastic shear band bearing sandstone, insights into the influence that variations in fault structure exert over the intra-fault drainage pathway of an invading non-wetting fluid have been gained. Drainage across the fault occurs as a highly non-uniform and non-linear process, which calls into question the practice of using continuum methods to model cross fault flow. This work has also provided an improved understanding of the role that high capillary entry pressure cataclised regions play in modifying pore-fluid displacement processes within the surrounding matrix continuum. In particular, the high sweep efficiency and enhanced non-wetting phase pore-wall contact relating to elevated phase pressure observed during drainage points towards favourable conditions for wettability alteration within cataclised sandstones. This is likely to negatively impact upon the effectiveness of oil recovery and CO2 sequestration operations within equivalent reservoir and aquifer settings.
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Chang, Yan. "Impacts of Climate Changeson Reservoirs in Northern Sweden : case study of Akkajaure reservoir by modelling". Thesis, Linköpings universitet, Tema vatten i natur och samhälle, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68419.
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Since the middle of the 20th century, the average temperature of the atmosphere near Earthsurface has increased. The global warming causes many effects in hydrological systems, suchas changes in thermal structure, water quality, aquatic ecosystems, etc. This thesis studies theimpact of climate change on Akkajaure reservoir, the second largest regulated reservoir inSweden, by simulating a predicted temperature rise based on the climate and hydrologicalconditions of Akkajaure in 1998-2002. The congeal duration, ice thickness and the turbulentkinetic energy (TKE) in the lake were calculated by the catchment hydrological model and thelake model. The movement of phytoplankton and their mean net production (MeanNP) rateare simulated by the dispersion model and the photosynthesis model. By comparing thesimulation results of past situation and three predicted scenarios, it is obtained that theincreases of temperature shorten the congeal duration, which is a lead factor for shortening thetrough period and amplification of peak value of TKE. The comparison of plankton particlesposition illustrates that the particles stay in a deeper position for a longer time because of thechanges of TKE. Though the plankton stays in euphotic zone longer as the temperatureincreases, the comparison of the mean production rate between the real scenario and thepredicted scenarios concludes that the mean production rate grows as the temperatureincreases because the shortened ice cover period makes the duration of absorbed sunlightincreases in lake. The effects of global warming may influence the distribution of microalgaein on high latitude lakes and reservoirs. The phytoplankton will stay in deeper water layers fora longer time.
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Nejedlik, John. "Reservoir characterisation of Golden Beach Group reservoirs along the northern margin of the Gippsland Basin /". Title page, contents and acknowledgments only, 1998. http://web4.library.adelaide.edu.au/theses/09S.B/09s.bn417.pdf.
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Vasilikou, Foteini. "Modeling CO2 Sequestration and Enhanced Gas Recovery in Complex Unconventional Reservoirs". Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64320.
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Geologic sequestration of CO2 into unmineable coal seams is proposed as a way to mitigate the greenhouse gas effect and potentially contribute to economic prosperity through enhanced methane recovery.
In 2009, the Virginia Center for Coal and Energy Research (VCCER) injected 907 tonnes of CO2 into one vertical coalbed methane well for one month in Russell County, Virginia (VA). The main objective of the test was to assess storage potential of coal seams and to investigate the potential of enhanced gas recovery. In 2014, a larger scale test is planned where 20,000 tonnes of CO2 will be injected into three vertical coalbed methane wells over a period of a year in Buchanan County, VA.
During primary coalbed methane production and enhanced production through CO2 injection, a series of complex physical and mechanical phenomena occur. The ability to represent the behavior of a coalbed reservoir as accurately as possible via computer simulations yields insight into the processes taking place and is an indispensable tool for the decision process of future operations. More specifically, the economic viability of projects can be assessed by predicting production: well performance can be maximized, drilling patterns can be optimized and, most importantly, associated risks with operations can be accounted for and possibly avoided.
However, developing representative computer models and successfully simulating reservoir production and injection regimes is challenging. A large number of input parameters are required, many of which are uncertain even if they are determined experimentally or via in-situ measurements. Such parameters include, but are not limited to, seam geometry, formation properties, production constraints, etc.
Modeling of production and injection in multi-seam formations for hydraulically fractured wells is a recent development in coalbed methane/enhanced coalbed methane (CBM/ECBM) reservoir modeling, where models become even more complex and demanding. In such cases model simulation times become important.
The development of accurate simulation models that correctly account for the behavior of coalbeds in primary and enhanced production is a process that requires attention to detail, data validation, and model verification. A number of simplifying assumptions are necessary to run these models, where the user should be able to balance accuracy with computational time.
In this thesis, pre- and post-injection simulations for the site in Russell County, VA, and preliminary reservoir simulations for the Buchanan County, VA, site are performed. The concepts of multi-well, multi-seam, explicitly modeled hydraulic fractures and skin factors are incorporated with field results to provide accurate modeling predictions.Ph. D.
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Jankovic-Karasoulos, Tanja. "A case study of the physical, chemical and biological factors affecting dissolved organic carbon in the Warren Reservoir, South Australia /". Title page, table of contents and abstract only, 2004. http://web4.library.adelaide.edu.au/theses/09PH/09phj339.pdf.
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Bessa, Fadila. "Reservoir characterization and reservoir modeling in the northwestern part of Hassi Messaoud Field, Algeria". [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=973413182.
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Kulkarni, Kanad. "Reservoir quality determination and modelling of unconsolidated Canadian Oil Sands reservoir following analytical techniques". Thesis, University of Portsmouth, 2018. https://researchportal.port.ac.uk/portal/en/theses/reservoir-quality-determination-and-modelling-of-unconsolidated-canadian-oil-sands-reservoir-following-analytical-techniques(efdd2eb4-ba2e-4f2b-9940-e15611faedf3).html.
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Canadian Oil Sands covering an area of 142,000KM2 boasts one of the largest heavy oil proven reserves standing at 166 Bbbl. This volume makes it a promising prospect for the future of the oil and gas industry. Though, having large reserves it is not the easiest to produce from. The oil in this region is categorized as heavy, extra heavy to bituminous which means that it is highly viscous and incapable of flowing without reducing viscosity. Furthermore, the Geology for this reservoir is heterogeneous with bioturbated sections which adds to the complexity. Additionally, lack of cementing matrix within formation makes this reservoir an unconsolidated reservoir. The unconsolidated nature introduces challenges during routine core analysis leading to the inaccurate results and in certain cases questions reliability of the methodology followed to assess this reservoir. The lack of any reliable work flow with methodologies act as a primary research gas for this thesis. Owing to aforementioned reasons, this study aims to establish a new workflow to determine properties from unconsolidated reservoirs, that includes use of Thin section analysis, Scanning Electron Microscopy (SEM), micro-CT techniques followed by image analysis to determine morphological and reservoir properties to simulate the reservoir to test applicability of the said workflow. To achieve set aims this research has made good use of thin sections that were prepared from outcrop samples and has followed further with detailed studies on core samples. Analysis of the thin sections has demonstrated arrangements. SEM and micro CT are able to provide properties more reliably than RCAL analysis. The simulations developed to test applicability of the properties followed has demonstrated variations to the recovery that can be observed by applying variety of porosity and permeability determined following the workflow of this thesis. Furthermore, the effect of bioturbation can also be observed with variation to the production volume observed as part of the simulation results.
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Hani, Lylia. "Caractérisation et rôle des lymphocytes T CD4+ mémoires SAMHD1low au cours de l'infection par le VIH-1". Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC0087/document.
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La mise en évidence du rôle de la molécule SAMHD1 dans l’infection par le VIH-1 en tant que facteur de restriction a ouvert de nouvelles perspectives dans la compréhension de la pathogénicité du virus.En effet, il a été clairement démontré que dans les cellules myéloïdes comme les monocytes/macrophages et les cellules dendritiques ainsi que les lymphocytes T CD4+ quiescents, SAMHD1 jouait un rôle important dans la protection de ces cellules de l’infection. En revanche, le rôle de cette molécule dans l’infection des lymphocytes activés, qui sont souvent la cible préférentielle du virus, n’est pas élucidé.Nos résultats ont révélé l'existence d'une sous-population de lymphocytes T CD4+ mémoires exprimant de faibles niveaux de SAMHD1 (CD4+ CD45RO+ SAMHD1low), tandis que la grande majorité des lymphocytes expriment cette molécule à des niveaux plus élevés (94±0.7%). Nous montrons également que ces cellules sont hautement différenciées, qu’elles expriment en larges proportions le marqueur de cycle cellulaire Ki67 et qu’elles sont enrichies en cellules « T helper 17 » (Th17) dans le sang périphérique.De plus, la fréquence de la population CD4+ CD45RO+ SAMHD1low, est diminuée de manière significative chez les patients infectés par le VIH-1 par rapport aux sujets sains. De manière intéressante, nous montrons que dans les ganglions, les cellules T follicular helper (Tfh) expriment faiblement SAMHD1 et sont plus susceptibles à l’infection par le VIH-1 in vitro.L’ensemble de ces résultats suggère que les cellules SAMHD1 low représentent une cible préférentielle pour le virus et pourraient contribuer au réservoir viral.Les objectifs de ce projet sont:1. Déterminer si les cellules SAMHD1low contiennent plus de virus par comparaison aux cellules mémoires SAMHD1high et comparer les séquences virales isolées des cellules mémoires SAMHD1low et SAMHD1high.2. Caractérisation des cellules SAMHD1low au niveau moléculaire par une analyse transcriptomique qui permettra la mise en évidence de marqueurs membranairesWe have previously reported the presence of memory CD4+ T cells that display low levels of SAMHD1 (SAMHD1low ) enriched in Th17 and Tfh cells. Here we investigated gene expression profile and the size and composition of HIV DNA population in SAMHD1 low cells.A total of 36 individuals on c-ART (median: 7y) with median CD4+ counts and nadir of 549 cells/ul and 210 cells/ul respectively, including 6 elite controllers (EC, CD4+: 900 cells/ul) and 8 healthy donors were studied. Blood memory CD4+ CD45RO+ SAMHD1low, CD45RO+ SAMHD1high and naive CD45RO- SAMHD1high cells were sorted. Cell associated HIV-1 DNA levels were quantified (HIV DNA Cell, Biocentric) and ultra-deep-sequencing (UDS, 454/Roche) of partial env (C2/V3) HIV-1 DNA was performed. Gene expression profile on sorted cells was deternined with RNA-Sequencing (Illumina RNASeq technology). Levels of HIV-1 DNA were significantly higher in memory SAMHD1low cells compared to SAMHD1high cells (4.5 [3.1-6.2] vs 3.8 [2.9-5.7] log/10 6 cells, respectively, p=0.02) among c-ART individuals, while naïve CD45RO- SAMHD1high showed lower levels (3.1 [1.6-4.4]). EC exhibited low HIV-1 DNA level in both SAMHD1low and SAMHD1high (1.6 and 2.3 log/10 6 cells respectively p>0.05). Naïve CD45RO - SAMHD1 high cells from EC showed lower DNA compared to naïve cells from c-ART pts (1.6 and 3.1 log/10 6 cells, respectively, p=0.01). Phylogenetic analyses revealed well-segregated HIV-DNA populations between subsets with significant compartmentalization between SAMHD1low and SAMHD1high cells in all but 2 participants (p<0.001) and limited viral exchange. Moreover SAMHD1low cells exhibited a distinct gene profile as compared to SAMHD1high allowing thus further characterisation of these cells.This pilot study revealed distinct HIV DNA populations in size and composition associated with unique genes profile in memory SAMHD1low cells. We show that memory SAMHD1low cells exhibit distinct genes profile which segregates them from the SAMHD1 high counterpart, and contain the highest level of HIV-1 DNA. We reveal distinct/well-segregated HIV-1 DNA populations in both subsets, suggesting minimal viral exchange
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Moore, David L. "Reservoir management during drought an expert system approach". Ohio : Ohio University, 1993. http://www.ohiolink.edu/etd/view.cgi?ohiou1175718241.
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Rivera, Vega Nestor. "Reservoir characterization using wavelet transforms". Texas A&M University, 2003. http://hdl.handle.net/1969.1/482.
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Automated detection of geological boundaries and determination of cyclic events controlling deposition can facilitate stratigraphic analysis and reservoir characterization. This study applies the wavelet transformation, a recent advance in signal analysis techniques, to interpret cyclicity, determine its controlling factors, and detect zone boundaries. We tested the cyclostratigraphic assessments using well log and core data from a well in a fluvio-eolian sequence in the Ormskirk Sandstone, Irish Sea. The boundary detection technique was tested using log data from 10 wells in the Apiay field, Colombia.
We processed the wavelet coefficients for each zone of the Ormskirk Formation and determined the wavelengths of the strongest cyclicities. Comparing these periodicities with Milankovitch cycles, we found a strong correspondence of the two. This suggests that climate exercised an important control on depositional cyclicity, as had been concluded in previous studies of the Ormskirk Sandstone.
The wavelet coefficients from the log data in the Apiay field were combined to form features. These vectors were used in conjunction with pattern recognition techniques to perform detection in 7 boundaries. For the upper two units, the boundary was detected within 10 feet of their actual depth, in 90% of the wells. The mean detection performance in the Apiay field is 50%.
We compared our method with other traditional techniques which do not focus on selecting optimal features for boundary identification. Those methods resulted in detection performances of 40% for the uppermost boundary, which lag behind the 90% performance of our method.
Automated determination of geologic boundaries will expedite studies, and knowledge of the controlling deposition factors will enhance stratigraphic and reservoir characterization models. We expect that automated boundary detection and cyclicity analysis will prove to be valuable and time-saving methods for establishing correlations and their uncertainties in many types of oil and gas reservoirs, thus facilitating reservoir exploration and management.
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Kjærås, Halvor. "Sediments in Angostura Hydropower Reservoir". Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for vann- og miljøteknikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19298.
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Reservoirs in areas with a high sediment yield will without mitigation sooner or later be filled up with sediments, reducing the volume available for regulation for electric generation. Flushing of sediments is a management strategy used in many reservoirs in the world, with varying degree of success. The Angostura reservoir is a shallow reservoir located on an inundated river, making it extra vulnerable to sedimentation. It is estimated a yearly inflow of 1.5 million tons of sediment. Other reservoirs are located upstream, and the flushing of these leads to large quantities of sediment inflow in a short period of time. In September every year, the water level in Angostura is partially drawn down to route this sediment through the reservoir. In November, the water level is drawn down completely, and a full sediment flushing is performed. The RESCON model is a spreadsheet program designed to find a technically feasible sediment management strategy that maximizes the economical benefits of the project. Flushing is modeled with a simple algebraic model. SSIIM is a three-dimensional computational fluid dynamics program designed for hydraulic engineering. Sediment erosion, transport and sedimentation can be modeled in a complex reservoir geometry using an adaptive grid with a moveable bed. The main objective of this thesis is to test the performance of the RESCON and SSIIM models. The RESCON model was tested on the November flushing to see if it can reproduce the measured volume of flushed sediments. SSIIM was used for simulation of sediment concentration distribution in the reservoir, and to model the September flushing. The results are compared to measured values. The reservoir geometry is based on bathymetry data from September 2011. Inflow series are from logged values at the hydropower plant. Depth-averaged concentration values are used to present the longitudinal concentration distribution, and Hunter Rouse profiles to present the vertical distribution. Using known reservoir values and the recommended coefficients, the RESCON model was not able to get close to the actual volume of flushed sediments. Although the model has given promising results in other cases, the complex reservoir geometry in Angostura sets heavy restrictions on the flushing processes in the reservoir, which an algebraic model of this type cannot reproduce. The steady state simulation was successful in explaining previously unexplained variations in the concentration in the lateral and longitudinal direction of the reservoir. The simulation reproduces the longitudinal and vertical concentration distribution well. A bug in the implementation of the second-order scheme in SSIIM was discovered, which has later been fixed, giving more similar results for the first-order and second-order schemes. The time allocated for the flushing simulation was not enough to get satisfactory results. The erosion in the upstream end is modelled well, but the measured sedimentation in the downstream area is much larger than in the simulations. With more time for this simulation, it would have been possible to increase the quality of the results.
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Kistenmacher, Martin. "Reservoir system management under uncertainty". Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/49012.
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Reservoir systems are subject to several uncertainties that are the result of imperfect knowledge about system behavior and inputs. A major source of uncertainty arises from the inability to predict future inflows. Fortunately, it is often possible to generate probabilistic forecasts of inflow volumes in the form of probability density functions or ensembles. These inflow forecasts can be coupled with stochastic management models to determine reservoir release policies and provide stakeholders with meaningful information of upcoming system responses such as reservoir levels, releases, flood damage risks, hydropower production, water supply withdrawals, water quality conditions, navigation opportunities, and environmental flows, among others. This information on anticipated system responses is also expressed in the form of forecasts that must reliably represent the actual system behavior when it eventually occurs. The first part of this study presents an assessment methodology that can be used to determine the consistency of ensemble forecasts through the use of relative frequency histograms and minimum spanning trees (MST). This methodology is then used to assess a management model's ability to produce reliable ensemble forecasts. It was found that neglecting to account for hydrologic state variables and improperly modeling the finite management horizon decrease ensemble consistency. Several extensions to the existing management model are also developed and evaluated. The second portion of this study involves the management of the uncertainties in reservoir systems. Traditional management models only find management policies that optimize the expected values of system benefits or costs, thereby not allowing operators and stakeholders to explicitly explore issues related to uncertainty and risk management. A technique that can be used to derive management policies that produce desired probabilistic distributions of reservoir system outputs reflecting stakeholder preferences is developed. This technique can be embedded in a user-interactive framework that can be employed to evaluate the trade-offs and build consensus in multi-objective and multi-stakeholder systems. The methods developed in this dissertation are illustrated in case studies of real reservoir systems, including a seven-reservoir, multi-objective system in California's Central Valley.
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Najafiazar, Bahador. "Mathematical Optimization in Reservoir Management". Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for petroleumsteknologi og anvendt geofysikk, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-27058.
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Getting the most out of a hydrocarbon reservoir is not a trivial task. It takes plentyof interwoven decisions to make. There are many forms of tools that support engineersto make correct decisions. The simplest ones would only display measurementsin a suitable way, and appoint the rest of the decision making processto human knowledge and experience. Complex decision support tools may implementmodel-based estimation and optimization. This work targets methods foroptimization-based decision support.The objective of this study is to formulate, implement and test promising methodsof hydrocarbon production optimization through various test cases. To do this, avarious optimizations algorithm were applied to the simulated reservoir modelsusing the Matlab Reservoir Simulation Toolbox (MRST).
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Campos, RogeÌrio. "Three-dimensional reservoir sedimentation model". Thesis, University of Newcastle Upon Tyne, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.421172.
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Tolouie, Esmaiel. "Reservoir sedimentation and de-siltation". Thesis, University of Birmingham, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.551025.
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An attempt has been made to review and summarize available knowledge pertaining to sedimentation and de-siltation of storage reservoirs. Additional data have been collected on Sefid - Rud Reservoir (Iran), during its normal and de-siltation operation periods. Some supplementary measures have been introduced to increase the de-siltation efficiency of flushing operations, based on field observations and experiments made during de- iltation operation of Sefid - Rud Reservoir. These measures seem to be a practical and cheap tools for conservation and rehabilitation of large - capacity reservoirs. It is hoped that the subject of resevoir sedimentation may be advanced as much as its importance warrants.
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Lee, Tai-yong Seinfeld John H. "Estimation of petroleum reservoir properties /". Diss., Pasadena, Calif. : California Institute of Technology, 1987. http://resolver.caltech.edu/CaltechETD:etd-03012008-135126.
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Luca, Gheorghe. "Toward high definition reservoir characterization". Morgantown, W. Va. : [West Virginia University Libraries], 2001. http://etd.wvu.edu/templates/showETD.cfm?recnum=2175.
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Thesis (M.S.)--West Virginia University, 2001.Title from document title page. Document formatted into pages; contains xi, 149 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 118-124).
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Agarwal, Anshul. "Thermal adaptive implicit reservoir simulation /". May be available electronically:, 2009. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
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