Thesis (Ph. D.)--University of Washington, 1998. / Vita. Includes bibliographical references (leaves [99]-105).

Thesis (Ph.D.)--McMaster University (Canada), 1995. / Source: Dissertation Abstracts International, Volume: 57-03, Section: B, page: 2118. Adviser: G. F. Round.

Zur Kühlung von Prozessströmen kommen aufgrund hoher Leistungsdichten häufig Verdunstungskühltürme zum Einsatz. Um die Übertragungsfläche für Wärme und Stoff zu vergrößern, werden in diesen Kühltürmen Struktureinbauten integriert. Die Weiterentwicklung von Kühlturmeinbauten und die Untersuchung der den Kühlprozess beeinflussenden Faktoren erfolgt empirisch, was eine Vielzahl von Versuchen notwendig macht. Eine numerische Simulation des Kühlprozesses kann diese Messungen unterstützen und so helfen eine Vielzahl an Versuchen einzusparen. Des Weiteren können bei versuchsbegleitender Simulation mit einem geeigneten Modell weitere Untersuchungen durchgeführt und Erkenntnisse gewonnen werden, die bei Messungen am Versuchskühlturm verborgen bleiben. In dieser Arbeit werden zwei Ansätze der numerischen Simulation eines Verdunstungskühlturms betrachtet. Es werden eine CFD-Simulation und ein vereinfachtes Modellkonzept hinsichtlich der Anwendbarkeit auf diese Problemstellung untersucht. Schwerpunkt der vorliegenden Arbeit ist die methodische Entwicklung eines solchen vereinfachten mathematischen Modells. Dieses beruht auf der physikalisch deterministischen Beschreibung der im Kühlturm ablaufenden Prozesse der Wärme- und Stoffübertragung unter Berücksichtigung des Stoffverhaltens. Aufgrund der Nichtlinearität des Stoffverhaltens und der erforderlichen Inkrementierung des Berechnungsgebiets ist ein methodisches Vorgehen erforderlich, um die Erstellung der Modellgleichungen und deren Lösung überhaupt realisieren zu können. Hierfür wird auf allgemeine Methoden der gleichungsorientierten Simulation technischer Systeme zurückgegriffen. Das entwickelte Modellkonzept wird für die Modellierung und Simulation eines Versuchskühlturms angewandt. Mit den so ermittelten Messdaten wird das Modell kalibriert und validiert. Es zeigt sich, dass mit dem erstellten Modell quantitativ und qualitativ valide Ergebnisse erzielt werden können. / Due to the high power density, the cooling of process streams is often done bei evaporative cooling towers. To enlarge the exchange area for the heat and mass transfer, these cooling towers contain integrated structural fills. The future development of cooling tower fills and the research regarding the cooling process and its influencing parameters will be carried out empirically, resulting in a large number of required experiments. A numeric simulation of the cooling process can support theses measurements and reduce the vast number of needed experiments. Furthermore, with the use of test-related simulations and adapted models, it will be possible to gain knowledge and do research in areas which are omitted during regular measurements on cooling towers. In this study it is looked to two different approaches of numeric simulation of a evaporative cooling tower. There will be an examination of a CFD-Simulation and a simplified model concept regarding their respective applicability for this problem. This work is focussed on the systematic developement of such simplified mathematical models, based on the physical deterministic description of the occurring processes of heat and mass transfer in cooling towers considering the stock behaviour. Due to the non-linearity of the stock behaviour and the required incrementation of the calculation area, a systematic approach is needed to model equations and their respective solutions. For this purpose it is necessary to access general techniques of equation-based simulations of technological systems. The developed model concept will be applied for the modelation and simulation of an experimental cooling tower. The model will be calibrated and validated with data from this experimental tower. It shows, that the results from this model are qualitatively and quantitatevily valid.

A significant amount of Viscous Oil (e.g., heavy oil, extra heavy oil, and bitumen) is trapped in Naturally Fractured Carbonate Reservoirs also known as NFCRs. The word VO endowment in NFCRs is estimated at ~ 2 Trillion barrels mostly reported in Canada, the USA, Russia, and the Middle East. To date, contributions to the world daily oil production from this immense energy resource remains negligible mainly due to the lack of appropriate production technologies. Implementation of a VO production technology such as steam injection is expensive (high capital investment), time-consuming, and people-intensive. Hence, before selecting a production technology for detailed economic analysis, use of cursory or broad screening tools or guides is a convenient means of gaining a quick overview of the technical feasibility of the various possible production technologies applied to a particular reservoir. Technical screening tools are only available for the purpose of evaluation of the reservoir performance parameters in oil sands for various thermal VO exploitation technologies such as Steam Assisted Gravity Drainage (SAGD), Cyclic Steam Stimulation (CSS), Horizontal well Cyclic steam Stimulation (HCS), and so on. Nevertheless, such tools are not applicable for VO NFCRs assessment without considerable modifications due to the different nature of these two reservoir types (e.g., presence and effects of fracture network on reservoir behavior, wettability, lithology, fabric, pore structure, and so on) and also different mechanisms of energy and mass transport. Considering the lack of robust and rapid technical reservoir screening tools for the purpose of quick assessment and performance prediction for VO NFCRs under thermal stimulation (e.g., steamflooding), developing such fast and precise tools seems inevitable and desirable. In this dissertation, an attempt was made to develop new screening tools for the purpose of reservoir performance prediction in VO NFCRs using all the field and laboratory available data on a particular thermal technology (vertical well steamflooding). Considering the complex and heterogeneous nature of the NFCRs, there is great uncertainty associated with the geological nature of the NFCRs such as fracture and porosity distribution in the reservoir which will affect any modeling tasks aiming at modeling of processes involved in thermal VO production from these types of technically difficult and economically unattractive reservoirs. Therefore, several modeling and analyses technqiues were used in order to understand the main parameters controlling the steamflooding process in NFCRs and also cope with the uncertainties associated with the nature of geologic, reservoir and fluid properties data. Thermal geomechanics effects are well-known in VO production from oil sands using thermal technologies such as SAGD and cyclic steam processes. Hence, possible impacts of thermal processes on VO NFCRs performance was studied despite the lack of adequate field data. This dissertation makes the following contributions to the literature and the oil industry: Two new statistical correlations were developed, introduced, and examined which can be utilized for the purpose of estimation of Cumulative Steam to Oil Ratio (CSOR) and Recovery Factor (RF) as measures of process performance and technical viability during vertical well steamflooding in VO Naturally Fractured Carbonate Reservoirs (NFCRs). The proposed correlations include vital parameters such as in situ fluid and reservoir properties. The data used are taken from experimental studies and also field trials of vertical well steamflooding pilots in viscous oil NFCRs reported in the literature. The error percentage for the proposed correlations is < 10% for the worst case and contains fewer empirical constants compared with existing correlations for oil sands. The interactions between the parameters were also considered. The initial oil saturation and oil viscosity are the most important predictive factors. The proposed correlations successfully predicted steam/oil ratios and recovery factors in two heavy oil NFCRs. These correlations are reported for the first time in the literature for this type of VO reservoirs. A 3-D mathematical model was developed, presented, and examined in this research work, investigating various parameters and mechanisms affecting VO recovery from NFCRs using vertical well steamflooding. The governing equations are written for the matrix and fractured medium, separately. Uncertainties associated with the shape factor for the communication between the matrix and fracture is eliminated through setting a continuity boundary condition at the interface. Using this boundary condition, the solution method employed differs from the most of the modeling simulations reported in the literature. A Newton-Raphson approach was also used for solving mass and energy balance equations. RF and CSOR were obtained as a function of steam injection rate and temperature and characteristics of the fractured media such as matrix size and permeability. The numerical solution clearly shows that fractures play an important role in better conduction of heat into the matrix part. It was also concluded that the matrix block size and total permeability are the most important parameters affecting the dependent variables involved in steamflooding. A hybrid Artificial Neural Network model optimized by co-implementation of a Particle Swarm Optimization method (ANN-PSO) was developed, presented, and tested in this research work for the purpose of estimation of the CSOR and RF during vertical well steamflooding in VO NFCRs. The developed PSO-ANN model, conventional ANN models, and statistical correlations were examined using field data. Comparison of the predictions and field data implies superiority of the proposed PSO-ANN model with an absolute average error percentage < 6.5% , a determination coefficient (R2) > 0.98, and Mean Squared Error (MSE) < 0.06, a substantial improvement in comparison with conventional ANN model and empirical correlations for prediction of RF and CSOR. This indicates excellent potential for application of hybrid PSO-ANN models to screen VO NFCRs for steamflooding. This is the first time that the ANN technique has been applied for the purpose of performance prediction of steamflooding in VO NFCRs and also reported in the literature. The predictive PSO-ANN model and statistical correlations have strong potentials to be merged with heavy oil recovery modeling softwares available for thermal methods. This combination is expected to speed up their performance, reduce their uncertainty, and enhance their prediction and modeling capabilities. An integrated geological-geophysical-geomechanical approach was designed, presented, and applied in the case of a NFCR for the purpose of fracture and in situ stresses characterization in NFCRs. The proposed methodology can be applied for fracture and in situ stresses characterization which is beneficial to various aspects of asset development such as well placement, drilling, production, thermal reservoir modeling incorporating geomechanics effects, technology assessment and so on. A conceptual study was also conducted on geomechanics effects in VO NFCRs during steamflooding which is not yet well understood and still requires further field, laboratory, and theoretical studies. This can be considered as a small step forward in this area identifying positive potential of such knowledge to the design of large scale thermal operations in VO NFCRs.

A significant amount of Viscous Oil (e.g., heavy oil, extra heavy oil, and bitumen) is trapped in Naturally Fractured Carbonate Reservoirs also known as NFCRs. The word VO endowment in NFCRs is estimated at ~ 2 Trillion barrels mostly reported in Canada, the USA, Russia, and the Middle East. To date, contributions to the world daily oil production from this immense energy resource remains negligible mainly due to the lack of appropriate production technologies. Implementation of a VO production technology such as steam injection is expensive (high capital investment), time-consuming, and people-intensive. Hence, before selecting a production technology for detailed economic analysis, use of cursory or broad screening tools or guides is a convenient means of gaining a quick overview of the technical feasibility of the various possible production technologies applied to a particular reservoir. Technical screening tools are only available for the purpose of evaluation of the reservoir performance parameters in oil sands for various thermal VO exploitation technologies such as Steam Assisted Gravity Drainage (SAGD), Cyclic Steam Stimulation (CSS), Horizontal well Cyclic steam Stimulation (HCS), and so on. Nevertheless, such tools are not applicable for VO NFCRs assessment without considerable modifications due to the different nature of these two reservoir types (e.g., presence and effects of fracture network on reservoir behavior, wettability, lithology, fabric, pore structure, and so on) and also different mechanisms of energy and mass transport. Considering the lack of robust and rapid technical reservoir screening tools for the purpose of quick assessment and performance prediction for VO NFCRs under thermal stimulation (e.g., steamflooding), developing such fast and precise tools seems inevitable and desirable. In this dissertation, an attempt was made to develop new screening tools for the purpose of reservoir performance prediction in VO NFCRs using all the field and laboratory available data on a particular thermal technology (vertical well steamflooding). Considering the complex and heterogeneous nature of the NFCRs, there is great uncertainty associated with the geological nature of the NFCRs such as fracture and porosity distribution in the reservoir which will affect any modeling tasks aiming at modeling of processes involved in thermal VO production from these types of technically difficult and economically unattractive reservoirs. Therefore, several modeling and analyses technqiues were used in order to understand the main parameters controlling the steamflooding process in NFCRs and also cope with the uncertainties associated with the nature of geologic, reservoir and fluid properties data. Thermal geomechanics effects are well-known in VO production from oil sands using thermal technologies such as SAGD and cyclic steam processes. Hence, possible impacts of thermal processes on VO NFCRs performance was studied despite the lack of adequate field data. This dissertation makes the following contributions to the literature and the oil industry: Two new statistical correlations were developed, introduced, and examined which can be utilized for the purpose of estimation of Cumulative Steam to Oil Ratio (CSOR) and Recovery Factor (RF) as measures of process performance and technical viability during vertical well steamflooding in VO Naturally Fractured Carbonate Reservoirs (NFCRs). The proposed correlations include vital parameters such as in situ fluid and reservoir properties. The data used are taken from experimental studies and also field trials of vertical well steamflooding pilots in viscous oil NFCRs reported in the literature. The error percentage for the proposed correlations is < 10% for the worst case and contains fewer empirical constants compared with existing correlations for oil sands. The interactions between the parameters were also considered. The initial oil saturation and oil viscosity are the most important predictive factors. The proposed correlations successfully predicted steam/oil ratios and recovery factors in two heavy oil NFCRs. These correlations are reported for the first time in the literature for this type of VO reservoirs. A 3-D mathematical model was developed, presented, and examined in this research work, investigating various parameters and mechanisms affecting VO recovery from NFCRs using vertical well steamflooding. The governing equations are written for the matrix and fractured medium, separately. Uncertainties associated with the shape factor for the communication between the matrix and fracture is eliminated through setting a continuity boundary condition at the interface. Using this boundary condition, the solution method employed differs from the most of the modeling simulations reported in the literature. A Newton-Raphson approach was also used for solving mass and energy balance equations. RF and CSOR were obtained as a function of steam injection rate and temperature and characteristics of the fractured media such as matrix size and permeability. The numerical solution clearly shows that fractures play an important role in better conduction of heat into the matrix part. It was also concluded that the matrix block size and total permeability are the most important parameters affecting the dependent variables involved in steamflooding. A hybrid Artificial Neural Network model optimized by co-implementation of a Particle Swarm Optimization method (ANN-PSO) was developed, presented, and tested in this research work for the purpose of estimation of the CSOR and RF during vertical well steamflooding in VO NFCRs. The developed PSO-ANN model, conventional ANN models, and statistical correlations were examined using field data. Comparison of the predictions and field data implies superiority of the proposed PSO-ANN model with an absolute average error percentage < 6.5% , a determination coefficient (R2) > 0.98, and Mean Squared Error (MSE) < 0.06, a substantial improvement in comparison with conventional ANN model and empirical correlations for prediction of RF and CSOR. This indicates excellent potential for application of hybrid PSO-ANN models to screen VO NFCRs for steamflooding. This is the first time that the ANN technique has been applied for the purpose of performance prediction of steamflooding in VO NFCRs and also reported in the literature. The predictive PSO-ANN model and statistical correlations have strong potentials to be merged with heavy oil recovery modeling softwares available for thermal methods. This combination is expected to speed up their performance, reduce their uncertainty, and enhance their prediction and modeling capabilities. An integrated geological-geophysical-geomechanical approach was designed, presented, and applied in the case of a NFCR for the purpose of fracture and in situ stresses characterization in NFCRs. The proposed methodology can be applied for fracture and in situ stresses characterization which is beneficial to various aspects of asset development such as well placement, drilling, production, thermal reservoir modeling incorporating geomechanics effects, technology assessment and so on. A conceptual study was also conducted on geomechanics effects in VO NFCRs during steamflooding which is not yet well understood and still requires further field, laboratory, and theoretical studies. This can be considered as a small step forward in this area identifying positive potential of such knowledge to the design of large scale thermal operations in VO NFCRs.

Le transfert radiatif dû aux gaz joue un rôle important dans les applications industrielles comme les chambres de combustion, les sciences atmosphériques, etc. Plusieurs modèles ont été proposées pour estimer les propriétés radiatives des gaz. Le plus précis est l'approche dite Raie Par Raie (RPR). Cependant, cette méthode implique un coût de calcul excessif qui la rend inappropriée pour la plupart des applications. Néanmoins, elle reste la méthode de référence que nous utiliserons pour l'évaluation d’autres modèles approchés. Le modèle de coefficient d’absorption corrélé (Ck) est généralement suffisant pour de nombreuses applications. Cette méthode est réputée précise lorsque petits gradients de température sont rencontrés au sein du gaz. Toutefois, si le milieu gazeux est soumis à d'importants gradients de température, la méthode Ck peut conduire à des erreurs qui peuvent atteindre 50% en termes de flux radiatifs par rapport à des simulations de RPR. Le but de cette thèse est de proposer une version améliorée de la méthode Ck, appelée l'approche de coefficient d’absorption corrélé en multi spectral (MSCk). La principale différence entre les modèles Ck et MSCk est que, dans l'approche Ck les intervalles spectraux sur lesquels les propriétés radiatives des gaz sont moyennées sont choisis contiguës alors que, dans l’approche MSCk, ces intervalles sont construits afin d'assurer que le coefficient d'absorption soit corrélé sur ces intervalles. Par conséquent, l'hypothèse de corrélation dans l’approche MSCk est mieux adaptée que dans l’approche Ck. La construction de ces intervalles spectraux (en utilisant la méthode de classification automatique de données fonctionnelles) est détaillée. Cette approche est évaluée par rapport à la référence RPR dans plusieurs cas test. Ces cas traitent de mélanges de gaz (H2O-N2 et H2O-CO2-N2) dans l’intervalle de température [300-3000K]. Les résultats montrent que la méthode MSCk permet d'obtenir de meilleures précisions que les méthodes Ck tout en restant acceptable en termes de coût de calcul. / Radiative heat transfer of gas plays an important role in industrial applications such as in combustion chambers, atmospheric sciences, etc. Several models [11] have been proposed to estimate the radiative properties of gases. The most accurate one is the Line-By-Line (LBL) approach. However, this technique involves excessive computation cost which makes it inappropriate for most applications. Nevertheless, it remains the reference approach for the assessment of other approximate models. The Correlated k-distribution method (Ck) [11] was shown to be a relevant choice for many applications. This method performs usually well, when only small temperature gradients are involved [21]. However, if the gaseous medium is subject to large temperature gradients, it may lead to errors that can reach 50% in terms of radiative heat fluxes when compared to LBL simulations [21]. The aim of the present paper is to propose an enhanced version of the Ck method, called the Multi-Spectral Correlated k-distribution approach (MSCk). The main difference between Ck and MSCk models is that in the Ck approach spectral intervals over which the radiative properties of the gas are averaged are chosen contiguous whereas, in the MSCk technique, those intervals are built in order to ensure that the absorption coefficient are scaled over them [27]. Accordingly, the usual assumption of correlated spectrum used in k-distribution approaches for the treatment of non uniformities is more acceptable in the MSCk case than in the Ck one. The building of those spectral intervals (using Functional Data Clustering, [52]) is detailed and the approach is assessed against LBL reference data in several test cases. These cases involve H2O-N2 and H2O-CO2-N2 mixtures in the [300-3000K] temperature range. Results show that the MSCk method enables to achieve better accuracies than Ck methods while remaining acceptable in terms of computational cost.