bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental and Numerical Study of Steam Flooding in Fractured Porous Media
Authors: Ashrafi Mohammad , Souraki Yaser , Karimaie Hassan , Torsaeter Ole
Published: May 2011

Extra heavy oil and bitumen reservoirs constitute a huge proportion of total world oil reserves. Thermal recovery and steam based methods are the most widely used recovery methods in these kinds of reservoirs. Steam injection into fractured heavy oil reservoirs to recover matrix oil has been considered as an efficient EOR method. However, mechanism of steam injection is more complex in fractured reservoirs than in conventional reservoirs. Evaluation of steam injection in fractured porous media requires good understanding of the physical processes between rock and fluids in matrix and fracture. In fact recovery could be a combination of several mechanisms such as viscous forces, capillary imbibition, thermal expansion and gravity drainage.

This paper presents experimental and simulation study of steam flooding in fractured porous media that contains Athabasca heavy oil. Some PVT properties of Athabasca crude oil have been measured experimentally and simulation study was accomplished using a numerical thermal reservoir simulator. A single horizontal fracture and two surrounding matrix blocks have been defined to verify the performance of steam injection in a 20 cm long sandstone core with a permeability of 640 mD saturated with Athabasca heavy crude. Considering a fractured system, sensitivity analyses were focused on the effect of injection rate, fracture permeability and steam quality.

The most important conclusion is that there is an optimum steam temperature and quality for most efficient steam injection. The permeability of the fracture should be low considering both oil production and steam oil ratio (SOR), which is a measure of economy. Matrix permeability of 640 mD in sandstone core provides satisfactory recovery and SOR. Higher matrix permeability can cause very high SOR and affect the economy of the process. Results also clearly show that higher injection rate improve the oil recovery. However, SOR should also be considered at the same time. There is a trade-off between recovery and SOR. It is also clear that lower fracture width shows better recovery while causing high injection pressure at the inlet.
Applying Fractional Flow Theory to Determine CO2 Storage Capacity of a Deep Saline Aquifer
Authors: Ghanbarnezhad Rouzbeh , Lake Larry W.
Published: May 2011

In this paper, we introduce a novel technique to determine the storage capacity of a saline aquifer for CO2 trapped because of the capillary snap-off and dissolution. The capillary snap-off trapping and dissolution into the aqueous phase are two principal mechanisms of the CO2 sequestration in an intermediate time-scale. The CO2 storage capacity of aquifers provides a criterion to determine the best candidates.

However, conducting numerical simulations to assess the CO2 storage capacity of an aquifer is complex and time-consuming because of various trapping mechanisms acting simultaneously with various rates on different time scales. Further, these simulations require detailed inputs and hence are limited to site-specific study.

We adopt the notion of the optimal solvent-water-slug size and use the graphical solution of multiple geochemical front propagation and fractional flow theory to determine the largest (optimal) slug of injected CO2 trapped because of the capillary trapping and the dissolution. The optimal slug size is the CO2 storage capacity of the aquifer because injecting more than the optimum leads to production of injected CO2 and injecting below the optimum leaves the aquifer unfilled. The two cases represent overcapacity and under-capacity storage, respectively. We use numerical simulation to validate the accuracy of the predicted optimal slug size. Simulation results confirm the accuracy of the predicted values.

In practice, the proposed method provides an efficient screening method to assess the CO2 storage capacity of aquifers and significantly reduces the simulation costs.
Mechanics of Heavy Oil and Bitumen Recovery by Hot Solvent Injection
Authors: Pathak V. , Babadagli T. , Edmunds N. R.
Published: May 2011

In our earlier works (Pathak et al., 2010; 2011), we presented the initial results for heavy oil and bitumen recovery using heated solvent vapours. The heavy oil and bitumen saturated sand pack samples of different heights were exposed to heated vapours of butane or propane at a constant temperature and pressure for an extended duration of time. The produced oil was analyzed for recovery, asphaltene content, viscosity, composition and refractive index. Recovery was found to be very sensitive to temperature and pressure.

The current work was undertaken to better understand the physics of the process and to explain the observations of the earlier experiments using additional experiments on tighter samples of different sizes, numerical simulation and visualization experiments. The effects of temperature and pressure on the recovery were studied using a commercial reservoir simulator. Propane and butane were used as solvents. Asphaltene precipitation was also modeled. A qualitative history match with the experiments on different porous media types was achieved by mainly considering the permeability reduction due to asphaltene precipitation, pore plugging, the extent of interaction between solvent and oil phase, and the parameters like model height, vertical permeability and gravity.

To investigate the phenomenon further, visualization experiments were performed. 2-D Hele-Shaw models were constructed by joining two plexiglass sheets from three sides, leaving some space in between to accommodate oil. The models were saturated with heavy-oil and left open from one side and were exposed to different types of solvents from this side. The setup was continuously monitored to observe fluid fronts and asphaltene precipitation.

Using this analysis, the mechanics of the process was clarified from the effect of solvent type on the recovery process. The optimum operating temperature for the hot solvent process and the dominant mechanisms were identified.
Field Scale Modeling of Tracer Injection in Naturally Fractured Reservoirs using the Random-Walk Simulation
Authors: Stalgorova E. , Babadagli T.
Published: May 2011

Modeling complex transport processes in naturally fractured reservoirs (NFRs) using classical continuum models may not be practically possible, because using classical algorithms for the detailed structure of fracture-matrix system requires unreasonable computational time. Also, fractured reservoirs are highly heterogeneous, and finite-difference calculations for such models often cause convergence problems. In addition to these, an exact representation of a complex fracture network in classical continuum modeling algorithms is highly difficult. An alternative is to use a non-classical technique known as the Random Walk Particle Tracking (RWPT) algorithm.

We showed earlier (Stalgorova and Babadagli, 2009) that the random walk (RW) technique can be adapted to model miscible flooding in a fractured porous medium at the lab scale. The unknown parameters used to match the model results were only diffusion coefficients for oil and solvent, as the diffusive/dispersive transport (effective if fracture and matrix) was coupled with viscous (effective in fracture) and gravity (effective in fracture and matrix) displacement. Advantages of this method over classical simulation are: (1) shorter computational time, which allows avoidance of simplifications, and (2) the ability to model the matrix-fracture diffusion process without any transfer function.

In the present paper, we modified this lab scale RW model for field scale applications. For validation, a series of tracer test results from the Midale field in Canada was used. Fracture network model was constructed based on geological data, and then we used the RWPT model to calibrate the fracture network against tracer test results.

We performed a sensitivity analysis to identify the importance of different parameters for the simulation results. The new model and observations can be used to validate and calibrate stochastically generated fracture network models and to estimate the EOR performance of NFRs.
Experimental Investigation and Numerical Simulation of Steam Flooding in Heavy Oil Fractured Reservoir
Authors: Souraki Yaser , Ashrafi Mohammad , Karimaie Hassan , Torsæter Ole
Published: May 2011

Nowadays, the most promising methods for recovery of heavy oil and bitumen are thermal recovery processes and among these processes, steam flooding is one of the most important methods. Naturally fractured reservoirs hold over 20 billion barrels of heavy oil which necessitates improvement in understanding of the physical processes that takes place between matrix and fracture during steam injection.

This paper addresses experimental and numerical simulation of steam injection in fractured rock. The purpose of the work was to investigate the efficiency and feasibility of steam injection in a core sample which is surrounded by fracture. Athabasca heavy crude oil was used in this study and some PVT properties of the oil was measured experimentally at different temperatures up to 200°C prior to simulation studies. Simulation studies were then conducted on a 20cm long cylindrical sandstone core with a permeability of 640mD. The core was saturated with Athabasca heavy crude oil and is radialy surrounded by a fracture.

The results show that steam injection process has great performance and efficiency in fractured systems. However, steam processes are not recommended in very high permeable fractured reservoirs due to high steam oil ratio (SOR).

Sensitivity analyses were performed on permeability of the fracture and injection rate. High fracture permeability is effective when the steam injection rate is low but it may have negative effect at earlier times for high injection rates. The effect of different injection rates on recovery performance of the system was investigated using the numerical model. Faster oil recovery and higher SOR was observed with increasing injection rates, eventhough the same ultimate recovery was obtained.
Experimental Study of Hot Fluid Injection into Athabasca Oil Sand Reservoir
Authors: Hashemi R. , Pereira P.
Published: May 2011

With more than 170 billion barrels of estimated oil sands, Canada has the second largest oil reserve in the world. 80 percent of these reserves are deep underground and can not be accessed by surface mining. Many In-Situ methods have been developed to extract heavy oil and bitumen from deep reservoirs. Once produced, bitumen is transferred to upgraders converting low quality oil to synthetic crude oil. Transportation of bitumen to a location for upgrading is a challenging aspect of bitumen production. In addition to processing costs, the level of contaminants in bitumen (sulphur, metal and nitrogen) requires special equipments, and has also environmental repercussions.

The "Underground Refinery" using nano-size Ultra-Dispersed (UD) catalyst is one of the alternatives to surface upgrading that may become the "next generation" of oil sands industry improvement. In order to perform a successful downhole upgrading process several steps should be implemented: catalyst placement (or presence) in an appropriate zone; reactants and co-reactant interaction, including heavy oil, catalyst and hydrogen; and creation of necessary reaction condition to obtain higher quality products, such as pressure and temperature.

This paper will present results of hot fluid injection in an elemental experimental model. Sets of experiments in various temperatures have been conducted to investigate effect of hot fluid on recovery enhancement. Results of each experiment compared with base SAGD process. Temperature profile distribution has been performed for each scenario. Results show that mixed hot fluid injection increased original oil recovery of bitumen up to 39% which shows (5–10 percent) recovery enhancement compared to pure hot fluid injection.
Polymer Screening Criteria for EOR Application - A Rheological Characterization Approach
Authors: Veerabhadrappa Santhosh K , Urbissinova Tolkynay S. , Trivedi Japan J , Kuru Ergun
Published: May 2011

Polymer flooding has been the most widely used enhanced oil recovery technique in both sandstone and carbonate reservoirs. Ample polymer flooding projects have been conducted with different level of success ever since the technique was introduced 50 years ago. It is a usual practice to select a polymer based on viscosity range, concentration and molecular weight without getting into rheological characterization and its effect on oil recovery. However, in recent times the application of polymer flood has gained critical mechanistic insight with advancement in understanding the role of elasticity on sweep efficiency. Therefore, selecting the type of polymer and understanding how its fluid rheology affects oil recovery are probably among the most critical factors involved in designing a successful polymer flood job.

To deal with this, a systematic approach for screening a polymer based on rheological characterization was adapted. Three different polymers, partially hydrolyzed polyacrylamide (HPAM) and Polyoxyethylene (PEO) were first used for fluid rheology study using a cone and plate rheometer and then for oil recovery through a special core holder designed to simulate radial flow through a sand pack – saturated with mineral oil.

Effects of various rheological parameters such as; a) Newtonian vs. non-Newtonian rheology (constant shear viscosity vs. shear thinning), b) shear viscosity vs. elasticity, and c) average molecular weight vs. molecular weight distribution (polydispersivity) on oil recovery were investigated. Finally, a parametric characterization study was performed to develop a screening criteria and to correlate oil recovery prediction. The approach could lead to a successful screening process of polymer based on various characteristic parameters such as average molecular weight, polydispersity and Trouton ratio.
Use of Phase Streamlines for Covariance Localization in Ensemble Kalman Filter for Three-Phase History Matching
Authors: Watanabe Shingo , Datta-Gupta Akhil
Published: May 2011

Ensemble Kalman Filter (EnKF) has gained increased popularity for history matching and continuous reservoir model updating. It is a sequential Monte-Carlo approach that works with an ensemble of reservoir models. Specifically, the method utilizes cross-covariance between measurements and model parameters estimated from the ensemble. For practical field applications, the ensemble size needs to be kept small for computational efficiency. However, this leads to poor approximations of the cross-covariance and can cause loss of geologic realism from unrealistic model updates outside the region of the data influence and/or loss of variance leading to ensemble collapse. A common approach to remedy the situation is through covariance localization to limit the influence of the data.

In this paper, we show that for three phase flow conditions, the region of covariance localization strongly depends on the underlying flow dynamics and also, on the particular data type that is being assimilated viz. water-cut or gas-oil ratio. This makes the traditional distance-based localizations sub-optimal and often, ineffective. Instead, we propose the use of water and gas phase streamlines as a means for covariance localization for water-cut and GOR data assimilation. The phase streamlines can be computed based on individual phase velocities which are readily available after flow simulation. Unlike the total streamlines, phase streamlines can be discontinuous. We show that the discontinuities in water phase and gas phase streamlines naturally define the region of influence for water-cut and GOR data and provide a flow-relevant covariance localization during EnKF updating.

We first demonstrate the validity of the proposed localization approach using a waterflood example in a quarter five-spot pattern. Specifically, we compare the phase streamline trajectories with cross-covariance maps computed using ensemble size of 2000 for both water-cut and GOR data. The results show a close correspondence between the time evolution of phase streamlines and the cross-covariance maps of water-cut and GOR data. a small-size industrial reservoir engineering PUNQ-S3 model application shows that our proposed localization outperforms distance-based localization method. The updated models show improved forecasts while preserving geological realism.
A Semi-Analytic Method for History Matching Fractured Shale Gas Reservoirs
Authors: Samandarli Orkhan , Al-Ahmadi Hasan A. , Wattenbarger Robert A.
Published: May 2011

This paper presents a semi-analytic method to estimate reservoir parameters by history matching the production data of hydraulically fractured shale gas wells. The method is based on the analytical solutions to dual-porosity reservoir models.

Algebraic equations developed by Bello and Wattenbarger (2010) for transient flow regimes which can occur in linear dual porosity model were used in this analysis. As far as practical values of reservoir parameters are involved, only two of the transient flow regimes would be seen in the field – bilinear and late linear. If matrix permeability is known, effective fracture permeability is estimated by doing regression on bilinear flow. Once bilinear flow is matched, linear flow part is also matched by regressing on fracture half length. Semi-analytic solutions are checked with actual data by making correction for gas properties change and desorption of gas at low pressures. When a satisfactory match of field data is obtained, reservoir parameters such as effective fracture and matrix permeability and OGIP can be estimated. Moreover, a future production of gas can be forecasted with estimated reservoir parameters for given economic constraints.

The method was applied on hydraulically fractured shale gas wells from Barnett play. It gives good results in history matching and estimation of reservoir parameters. Considering the recent interests in development of unconventional reservoirs, this method is future promising technique in better understanding those types of reservoirs.
Experimental Study of Co-Injection of Potential Solvents with Steam to Enhance SAGD Process
Authors: Ardali M. , Mamora D. D. , Barrufet M.
Published: May 2011

Steam-Assisted Gravity Drainage (SAGD) is the preferred in-situ technology to recover heavy oil and bitumen from Canadian reservoirs. It is commercially proven, delivers high oil rates and high ultimate recoveries. Given the large energy requirement and the volume of emitted greenhouse gases from SAGD process, there is a strong motivation to develop enhanced oil recovery processes with lower energy and emission intensities. Addition of potential alkane solvents to steam in processes such as ES-SAGD can reduce the high use of energy and green-house emissions in SAGD. Potential hydrocarbon additives provide an additional means to raise oil phase mobility beyond that achieved by heat.

Numerous simulation studies are published on the effect of hydrocarbon additives on SAGD process but few experimental results exist in public domain. Often, Conflicting results exist both in simulation studies and even field tests. In addition, numerical simulations are unable to fully capture the mechanism of hybrid steam solvent processes.

This paper summarizes experimental results of addition of potential solvents to steam in SAGD process. N-hexane was selected as the preferred additive to be co-injected with the steam and the experimental result are compared with pure steam injection process. Experiments were conducted using a scaled two dimensional cylindrical model. Peace River Bitumen samples were used to conduct the experiments at 80 psia.

Experimental results were analyzed to determine the key parameters involved in solvent assisted SAGD processes. Experimental results confirmed the effectiveness of hydrocarbon additives to enhance SAGD process. Co-injection of potential solvents led to accelerated oil production rate, higher oil recovery and lower energy to oil ratio.
A Combined Experimental and Simulation Workflow to Improve Predictability of In Situ Combustion
Authors: Bazargan M. , Chen B. , Cinar M. , Glatz G. , Lapene A. , Zhu Z. , Castanier L. , Gerritsen M. , Kovscek A. R.
Published: May 2011

In-situ Combustion (ISC) is widely accepted as an enhanced oil recovery method that is applicable to various oil-reservoir types. Prediction of the likelihood of a successful ISC project from first principles, however, is still unclear. Conventionally, combustion tube tests of a crude-oil and rock are used to infer whether one expects that ISC works at reservoir scale and the oxygen requirements. Combustion tube test results may lead to field-scale simulation on a coarse grid with Arrhenius reaction kinetics. If ISC is unsuccessful at field scale whereas tube tests are positive, the reservoir geological heterogeneity or operational problems are generally blamed. As an alternative, this paper suggests a comprehensive workflow to predict the likelihood of a successful combustion at the reservoir scale, based on both experimental laboratory data and simulation models at all scales. In our workflow, a sample of crushed reservoir rock or an equivalent synthetic sample is mixed with water/brine and the crude-oil sample. The mixture is placed in a kinetics cell reactor and oxidized at different heating rates. An isoconversional method is used to obtain an estimate of kinetic parameters versus temperature and combustion characteristics of the sample. Results from the isoconversional interpretation also provide a first screen of the likelihood that a combustion front can be propagated successfully. Then, a full-physics simulation model of the kinetics cell experiment is used to simulate the flue gas production. The model combines a detailed PVT of the multiphase system and a multistep reaction model. A genetic algorithm is used to estimate reaction parameters and thereby match oxygen consumption and gas production. A mixture identical to that tested in the kinetics cell is also burned in a combustion tube experiment. Temperature profiles along the tube and also the flue gas compositions are measured during the experiment. A high-resolution simulation model of the combustion tube test is developed and validated. This simulation uses the reaction model we have obtained from the genetic algorithm and/or isoconversional analysis. Finally, the high-resolution model is used as a basis for upscaling the reaction model to field dimensions employing nonArrhenius kinetics.
Application of Potential Theory to Modeling of ECBM Recovery
Authors: Shojaei Hasan , Jessen Kristian
Published: May 2011

In recent years, coalbed methane has become an important source of energy in the United States. Since primary production techniques typically recover less than half of the methane in a coalbed, enhanced coalbed methane (ECBM) recovery processes are needed in which N2 and/or CO2 are injected into the coalbed to recover more CH4. CO2 injection into coalbeds also provides additional benefit of sequestering carbon in the subsurface.

One of the main mechanisms that govern the dynamics of ECBM recovery processes is the sorption of gases onto the coal surfaces. Despite the well-documented complexity of multicomponent sorption phenomena, adsorption and desorption of CH4/CO2/N2 mixtures in the porous coal is commonly modeled with the extended Langmuir model. The extended Langmuir model has been proven unable to accurately describe the multicomponent sorption that is central to ECBM recovery processes and, therefore, more sophisticated sorption models are needed.

In this paper we apply potential theory to describe the multicomponent sorption of relevance to ECBM processes. In this approach for modeling multicomponent sorption, each component is assumed to be affected by a characteristic potential field emitted by the coal surface. We discuss the implementation of potential theory with emphasis on the simulation of ECBM processes where computational efficiency and accuracy must be balanced. The model must be solved by an iterative scheme, and is hence more computationally expensive than the extended Langmuir approach. The results and analysis presented in this paper demonstrate that the application of potential theory of sorption to modeling of ECBM recovery processes can improve the accuracy of calculations. However, the additional complexity of the model and the associated increase in the computational efforts may not balance the gain in accuracy sufficiently to warrant application in general purpose reservoir simulation.

The presented algorithms and modeling results are directly applicable in the development and utilization of coalbed methane resources.
Combined bulk and wall reactions in turbulent pipe flow: decay coefficients and concentration profiles
Authors: Lari Kaveh Sookhak , van Reeuwijk Maarten , Maksimović Čedo , Sharifan Suzan
Published: May 2011

This study discusses the effect of combined first-order, bulk and wall reactions on the overall intensity of mass withdrawal in smooth pipes. A one-dimensional model for the transport of high Schmidt number compounds (where the Schmidt number is the ratio of the fluid viscosity to the solute diffusivity) is extended with the effect of a first-order bulk reaction. Profiles of velocity and eddy diffusivity are obtained with a standard high Reynolds number k–∊ closure in combination with a modified Van Driest wall function. By comparing the results of the 1D model to an analytical asymptotic high Sc approximation, it is shown that the interaction between bulk and wall reactions is very weak. In terms of the decay coefficient, a maximum deviation of 4% is observed for very high bulk demand due to the attenuation of the streamwise solute mass flux. The parameter range for which the concentration profiles can be safely assumed to be uniform, both in the viscous sublayer and in the bulk, is established.
Analysis of the impact of intermittent distribution by modelling the network-filling process
Authors: De Marchis M. , Fontanazza C. M. , Freni G. , Loggia G. La , Napoli E. , Notaro V.
Published: May 2011

In many countries, users acquire private tanks to reduce their vulnerability to water scarcity. In such conditions, water managers often apply intermittent distribution in order to reduce the water volumes supplied to the users. This practice modifies the hydraulic behaviour of the network and determines competition among users that need to collect enough water resource for their uses. Intermittent distribution is thus responsible for the inequality that can occur among users: those located in advantaged positions of the network are able to obtain water resources soon after the service period begins, while others have to wait much longer, after the network is full. This paper analyses the inequalities that take part when intermittent distribution is applied in water scarcity scenarios. Considering the complexity of the process, the analysis was performed by means of an unsteady numerical model. The model was applied to a real case study which provided interesting insights into the network filling process, helping to highlight the advantaged and disadvantaged areas of the network in different water scarcity scenarios.
Application of classification trees to determine biological and chemical indicators for river assessment: case study in the Chaguana watershed (Ecuador)
Authors: Dominguez-Granda L. , Lock K. , Goethals P. L. M.
Published: May 2011

Benthic macroinvertebrates were sampled in the Chaguana river basin in SW Ecuador in March (wet season) and September (dry season) of 2005 and 2006. Aquatic insects dominated the macrobenthos, with Trichoptera, Diptera, Ephemeroptera, Hemiptera and Odonata being the orders with the highest diversity and Ephemeroptera and Diptera being most abundant. No systematic differences in richness and abundance were observed between dry and wet seasons, which is in agreement with the literature. It is concluded that, in the neotropics, macroinvertebrates can probably be sampled for water quality assessments during the whole year: however, sampling soon after spates should be avoided. Using multivariate analysis, stations could be clustered into three groups based on their macroinvertebrate community composition: sites with low, intermediate and high human impact. Classification trees indicated that stations with low human impact had low conductivities, while stations with high conductivities were characterised as highly impacted if the dissolved oxygen concentration was low and intermediately impacted if the dissolved oxygen concentration was high. Classification trees also indicated that Leptophlebiidae (Ephemeroptera) were characteristic for sites with low impact; in sites with intermediate impact, this family was absent but Hydropsychidae (Trichoptera) were present; when both families were absent, impact was high.
Some explicit formulations of Colebrook–White friction factor considering accuracy vs. computational speed
Authors: Giustolisi O. , Berardi L. , Walski T. M.
Published: May 2011

The Colebrook–White formulation of the friction factor is implicit and requires some iterations to be solved given a correct initial search value and a target accuracy. Some new explicit formulations to efficiently calculate the Colebrook–White friction factor are presented herein. The aim of this investigation is twofold: (i) to preserve the accuracy of estimates while (ii) reducing the computational burden (i.e. speed). On the one hand, the computational effectiveness is important when the intensive calculation of the friction factor (e.g. large-size water distribution networks (WDN) in optimization problems, flooding software, etc.) is required together with its derivative. On the other hand, the accuracy of the developing formula should be realistically chosen considering the remaining uncertainties surrounding the model where the friction factor is used. In the following, three strategies for friction factor mapping are proposed which were achieved by using the Evolutionary Polynomial Regression (EPR). The result is the encapsulation of some pieces of the friction factor implicit formulae within pseudo-polynomial structures.
Combined particle swarm optimization and fuzzy inference system model for estimation of current-induced scour beneath marine pipelines
Authors: Zanganeh M. , Yeganeh-Bakhtiary A. , Bakhtyar R.
Published: May 2011

In this paper the capability of Particle Swarm Optimization (PSO) is employed to deal with an Adaptive Network based Fuzzy Inference System (ANFIS) model's inherent shortcomings to extract optimum fuzzy if–then rules in noisy areas arising from the application of nondimensional variables to estimate scour depth. In the model, a PSO algorithm is employed to optimize the clustering parameters controlling fuzzy if–then rules in subtractive clustering while another PSO algorithm is employed to tune the fuzzy rule parameters associated with the fuzzy if–then rules. The PSO model's objective function is the Root Mean Square (RMSE), by which the model attempts to minimize the error in scour depth estimation with respect to its generalization capability. To evaluate the model's performance, the experimental datasets are used as training, checking and testing datasets. Two-dimensional and nondimensional models are developed such that in the dimensional model the mean current velocity, mean grain size, water depth, pipe diameter and shear boundary velocity are used as input variables while in the nondimensional model the pipe, boundary Reynolds numbers, Froude number and normalized depth of water are set as input variables. The results show that the model provides an alternative approach to the conventional empirical formulae. It is evident that the developed PSO–FIS–PSO is superior to the ANFIS model in the noisy area in which the input and output variables are slightly related to each other.
The search for orthogonal hydrological modelling metrics: a case study of 20 monitoring stations in Colombia
Authors: Domínguez E. , Dawson C. W. , Ramírez A. , Abrahart R. J.
Published: May 2011

This paper presents a Colombian-based study on hydrological modelling metrics, arguing that redundancies and overlap in statistical assessment can be resolved using principal component analysis. Numerous statistical scores for optimal operator water level models developed at 20 hydrological monitoring stations, producing daily, weekly and ten-day forecasts, are first reduced to a set of five composite orthogonal metrics that are not interdependent. Each orthogonal component is next replaced by a single surrogate measure, selected from a set of several original metrics that are strongly related to it, and that in overall terms delivered limited losses with regard to ‘explained variance’. The surrogates are thereafter amalgamated to construct a single measure of assessment based on Ideal Point Error. Depending on the forecast period, the use of three or four traditional metrics to deliver a combined evaluation vector, is the minimum recommended set of scores that is needed for analysis to establish the operational performance at a particular station in the gauging network under test.
Swarm intelligence for groundwater management optimization
Authors: Sedki A. , Ouazar D.
Published: May 2011

This paper presents some simulation–optimization models for groundwater resources management. These models couple two of the most successful global optimization techniques inspired by swarm intelligence, namely particle swarm optimization (PSO) and ant colony optimization (ACO), with one of the most commonly used groundwater flow simulation code, MODFLOW. The coupled simulation–optimization models are formulated and applied to three different groundwater management problems: (i) maximization of total pumping problem, (ii) minimization of total pumping to contain contaminated water within a capture zone and (iii) minimization of the pumping cost to satisfy the given demand for multiple management periods. The results of PSO- and ACO-based models are compared with those produced by other methods previously presented in the literature for the three case studies considered. It is found that PSO and ACO are promising methods for solving groundwater management problems, as is their ability to find optimal or near-optimal solutions.
Improving real-time reservoir operation based on combining demand hedging and simple storage management rules
Authors: Ilich Nesa
Published: May 2011

A number of deterministic reservoir optimization models are capable of finding optimal basin allocation over multiple time steps simultaneously. This is commonly referred to as Multiple Time Step Optimization (MTO). However, such solutions are predicated on perfect foreknowledge of incoming runoff over the entire simulated period (typically one year), which is not available to reservoir operators in real time, thus creating a gap between the results of MTO-based modeling and their practical use. There is no universally accepted methodology on how the results of MTO should be used to develop practical and easy-to-understand operating rules. This paper offers a simple approach to bridge this gap and suggests additional avenues for further research in this direction.
A framework for accurate geospatial modeling using image ranking and machine learning
Authors: Bajcsy Peter , Lin Yu-Feng , Yahja Alex , Kim Chulyun
Published: May 2011

There is a large class of modeling problems where the complexity of the underlying phenomena is overwhelming and hence the accuracy of mathematical models is limited. Our approach to this class of problems is to design frameworks that bring together physically based and data-driven models, and incorporate the tacit knowledge of experts by providing visual exploration and feedback capabilities. This paper presents such a novel computer-assisted framework for accurate geospatial modeling applied to improve groundwater recharge and discharge (R/D) patterns. The novelty of our work is in designing a methodology for ranking and extracting relationships, as well as in developing a general framework for building accurate geospatial models. The framework combines variables derived using physically based inverse modeling with auxiliary geospatial variables directly sensed, ranks variables and extracts variable relationships using data-driven (“machine learning”) techniques, and supports partially expert-driven trial-and-error experimentation and more rigorous optimization, as well as visual explorations, to derive more accurate models for R/D pattern estimation. When the framework was tested by experts, it led to a high level of consistency between the machine-learning-based knowledge and the experts' knowledge about R/D distribution. The prototype solution of the framework is available for downloading at http://isda.ncsa.uiuc.edu/Sp2Learn/.
Transient tests for locating and sizing illegal branches in pipe systems
Authors: Meniconi S. , Brunone B. , Ferrante M. , Massari C.
Published: May 2011

In pipe systems illegal branches can take away remarkable water resources with negative effects from both the economic and technical points of view. Difficulties in pointing out illegal branches by means of steady-state pressure and discharge measurements are mainly due to the fact that, of course, such systems are not active according to a regular time schedule. In this paper the possibility of using Transient Test-Based Techniques (TTBT) for the location and sizing of branches is shown. Specifically, tests carried out in different branched pipe systems at the Water Engineering Laboratory of the University of Perugia, Italy, show that TTBT allow us to detect branches irrespective of whether they are active or not. To improve the precision of the localization, arrival times of pressure waves are detected by means of wavelet analysis. Finally, a simple relation based on the water hammer theory is proposed to size the branch reliably.
Water quality comprehensive evaluation method for large water distribution network based on clustering analysis
Authors: Chang Kui , Gao Jin Liang , Wu Wen Yan , Yuan Yi Xing
Published: May 2011

In order to evaluate water quality for a large water distribution network comprehensively, a two-stage classification method was used and the clustering methods, self-organizing map (SOM), K-means method and fuzzy c-mean (FCM), were represented. With these clustering methods, the pipes of a large real water distribution network were divided into some groups considering one or more water quality indicators synchronously. The water quality indicators of residual chlorine, water age, THMs, TAAs, TOC and BDOC are used in this paper. Residual chlorine and water age are two main water quality indicators. THMs and TAAs can represents the disinfection byproducts information. And TOC and BDOC are used to represents biological stability. According to the clustering results, the status of water quality of the water network was analysed. The results showed that the classification of SOM could express the comprehensive water quality in a water distribution network (WDN) directly and vividly by high-dimension water quality indicator projection to a low dimensional topology grid and that two-stage classification method has higher efficiency in comparison to the traditional clustering method. Water quality comprehensive evaluation was of significance for locating water quality monitoring, water network rehabilitation and expansion.
Improved real-time data anomaly detection using context classification
Authors: Branisavljević Nemanja , Kapelan Zoran , Prodanović Dušan
Published: May 2011

The number of automated measuring and reporting systems used in water distribution and sewer systems is dramatically increasing and, as a consequence, so is the volume of data acquired. Since real-time data is likely to contain a certain amount of anomalous values and data acquisition equipment is not perfect, it is essential to equip the SCADA (Supervisory Control and Data Acquisition) system with automatic procedures that can detect the related problems and assist the user in monitoring and managing the incoming data. A number of different anomaly detection techniques and methods exist and can be used with varying success. To improve the performance, these methods must be fine tuned according to crucial aspects of the process monitored and the contexts in which the data are classified. The aim of this paper is to explore if the data context classification and pre-processing techniques can be used to improve the anomaly detection methods, especially in fully automated systems. The methodology developed is tested on sets of real-life data, using different standard and experimental anomaly detection procedures including statistical, model-based and data-mining approaches. The results obtained clearly demonstrate the effectiveness of the suggested anomaly detection methodology.
An artificial intelligence approach for optimizing pumping in sewer systems
Authors: Ostojin S. , Mounce S. R. , Boxall J. B.
Published: May 2011

This paper presents details of a fuzzy logic system developed for the control of sewer pumping stations for energy costs savings. This is part of an ongoing collaborative project between Anglian Water and the University of Sheffield. The model rules and operation are developed for one representative pumping station in order to enable the identification of potential benefits and inhibitors to Anglian Water. Results are included that demonstrate the potential for energy cost-savings by application to a single pumping station for dry weather flow conditions and through comparison to current on/off switching rules. The fuzzy system is shown to be robust to changes in flow pattern (using both modelled inflow data and real data from a flow survey), but sensitive to changes in price structures. Application of a genetic algorithm (GA) search technique was used to adjust the parameters that define the membership functions in the fuzzy rules, in order to provide automated minimization of the energy costs towards an optimal solution. The GA system is shown to be transferable to another pumping station with different pump sizes, wet well capacity and inflow pattern. The GA solution outperformed the base case in terms of energy costs and switching totals.
Clinical Efficacy and Cost-Effectiveness of Lanthanum Carbonate as Second-Line Therapy in Hemodialysis Patients in Japan
Authors: Goto Shunsuke , Komaba Hirotaka , Moriwaki Kensuke , Fujimori Akira , Shibuya Koji , Nishioka Masato , Kim Jong-Il , Yoshiya Kunihiko , Shin Jeongsoo , Hasegawa Hirohito , Taniguchi Masatomo , Fujii Hideki , Nishi Shinichi , Kamae Isao , Fukagawa Masafumi
Published: May 2011

Background and objectives

Lanthanum carbonate (LC) is a nonaluminum, noncalcium phosphate binder that is effective for hyperphosphatemia in dialysis patients. However, its efficacy and cost-effectiveness as second-line therapy have not been fully examined.

Design, setting, participants, & measurements

We first conducted a multicenter, open-label, 16-week clinical trial to examine the effect of additive LC in 116 hemodialysis patients who had uncontrolled hyperphosphatemia with conventional phosphorus-lowering therapy alone. Based on these clinical data, a state transition model was developed to evaluate the benefits and costs associated with LC as second-line therapy. Reduced risks for cardiovascular morbidity and mortality among patients treated with LC arise through more of the population achieving the target phosphorus levels. Uncertainty was explored through sensitivity analysis.

Results

After 16 weeks of additive LC treatment, mean serum phosphorus levels decreased from 7.30 ± 0.90 to 5.71 ± 1.32 mg/dl, without significant changes in serum calcium or intact parathyroid hormone levels. A subsequent cost-effectiveness analysis showed that compared with conventional treatment, additive LC incurred an average additional lifetime cost of $22,054 per person and conferred an additional 0.632 quality-adjusted life years (QALYs). This resulted in an incremental cost-effectiveness ratio of $34,896 per QALY gained. Applying a cost-effectiveness threshold of $50,000 per QALY, a probabilistic sensitivity analysis showed that additive LC had a 97.4% probability of being cost-effective compared with conventional treatment.

Conclusions

Our results indicate that the use of LC as second-line therapy would be cost-effective among hemodialysis patients with uncontrolled hyperphosphatemia in Japan.
Extended Follow-Up of Unruptured Intracranial Aneurysms Detected by Presymptomatic Screening in Patients with Autosomal Dominant Polycystic Kidney Disease
Authors: Irazabal Maria V. , Huston John , Kubly Vickie , Rossetti Sandro , Sundsbak Jamie L. , Hogan Marie C. , Harris Peter C. , Brown Robert D. , Torres Vicente E.
Published: May 2011

Background and objectives

Autosomal dominant polycystic kidney disease (ADPKD) patients have an increased risk for intracranial aneurysms (IAs). The importance of screening for unruptured IAs (UIAs) depends on their risks for growth and rupture.

Design, setting, participants, & measurements

ADPKD patients with UIAs found by presymptomatic screening with magnetic resonance angiography (MRA) during 1989 to 2009 were followed initially at 6 months and annually, and less frequently after demonstration of stability.

Results

Forty-five saccular aneurysms were detected in 38 patients from 36 families. Most were small (median diameter 3.5 mm) and in the anterior circulation (84%). Median age at diagnosis was 49 years. During cumulative imaging follow-up of 243 years, one de novo UIA was detected and increased in size from 2 to 4.4 mm over 144 months and two UIAs grew from 4.5 to 5.9 mm and 4.7 to 6.2 mm after 69 and 184 months, respectively. Seven patients did not have imaging follow-up. No change was detected in the remaining 28 patients. During cumulative clinical follow-up of 316 years, no aneurysm ruptured. Five patients died from unrelated causes and two were lost to follow-up after 8 and 120 months. Three patients underwent surgical clipping.

Conclusions

Most UIAs detected by presymptomatic screening in ADPKD patients are small and in the anterior circulation. Growth and rupture risks are not higher than those of UIAs in the general population. These data support very selective screening for UIAs in ADPKD patients, and widespread screening is not indicated.
Paradoxical Embolism after Declotting of Hemodialysis Fistulae/Grafts in Patients with Patent Foramen Ovale
Authors: Wu Steven , Ahmad Iftikhar , Qayyum Sohail , Wicky Stephan , Kalva Sanjeeva P.
Published: May 2011

Background and objectives

The safety of percutaneous endovascular declotting procedures for thrombosed hemodialysis fistulae/grafts is well described in the general population; however, its safety in the presence of a patent foramen ovale (PFO) is not known. The objective of this study is to assess the incidence of symptomatic paradoxical embolic events associated with declotting procedure of thrombosed arteriovenous (AV) graft or fistula in patients with documented PFO.

Design, setting, participants, & measurements

This was a retrospective study in a hospital-based, academic practice. It included 23 patients (10 men; mean age, 65) with PFO and thrombosed hemodialysis graft/fistula who underwent a standardized declotting procedure with 2 mg of Alteplase and balloon thrombectomy. Twenty patients (87%) had AV grafts, and three (13%) had AV fistulae. The PFO shunt was right to left in two (9%), left to right in eight (34%), and bidirectional in ten (44%). The shunt direction was not specified in three patients (13%). The technical success of the declotting procedure and the frequency of clinically manifested paradoxical embolic events in this patient population were calculated.

Results

Fifty declotting procedures were performed on 23 patients with a technical success rate of 96% (48 of 50, 96%). No symptomatic paradoxical embolic events were found in any of the 23 patients with PFO.

Conclusions

Symptomatic paradoxical embolic events after percutaneous endovascular declotting procedures of thrombosed AV grafts and fistulae in patients with documented PFO are rare. This procedure appears to be safe in patients with a PFO.