Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains xii, 136 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 75-76).

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 248-254). Available also in a digital version from Dissertation Abstracts.

Increased world-wide interest in reducing the carbon-footprint of human activities has driven the coal-fueled energy industry to transition to a natural gas fueled future. Coupled with the continually increasing energy demand, the interest in alternate sources of natural gas has gained momentum. Microbially enhanced coalbed methane (MECBM), which aims at microbially converting in situ coal to methane provides one such alternate source of natural gas. Feasibility of MECBM as a viable technology is two-pronged, focusing on associated microbiology, and flow-governing reservoir response. The general advance of research in this area has thus far been from a microbial perspective, where coal-to-methane bioconversion has been successfully reported for several coal types worldwide. However, insights into reservoir properties governing flow and transport of fluids in a MECBM reservoir is missing. Given that coal is both the source and reservoir rock of the produced biogenic methane, a sound knowledge of the effect of bioconversion on flow governing properties of coal is decisive from a production perspective. Evaluating the flow governing reservoir response of a MECBM reservoir is the focus of the work presented in this dissertation. In order to investigate the effect of bioconversion on the Darcian flow regime existing in the natural fractures in coal, two experimental studies were undertaken. First, variation in coal’s flow governing micro- and macro- porosity was investigated using high-resolution scanning electron microscopy. The observed changes were quantified and the expected change in permeability of coal post-bioconversion was estimated. In the second set of experiments, the sorption-induced-strain response of coal pre- and post-bioconversion was studies. Finally, the experimental data was used to model and predict the geomechanical-coupled flow behavior of a MECBM reservoir during bioconversion and production of the produced biogenic methane. Experimental results from the imaging study revealed that bioconversion results in swelling of the coal matrix. This reduces the cleat (macroporous fracture) aperture post-bioconversion, reducing the permeability of the coal significantly. This validated the recently reported results, where measured permeability of coal packs and coal cores dropped by ~70% post-bioconversion. Bioconversion, however, resulted in increase in the cleat width of fractures greater than 5 microns wide, which constituted <5% of the fractures imaged. This is indicative of the possibility of enhanced reservoir performance in artificially fractured coal formations or, ones with wide-aperture fractures, like depleted coalbed methane (CBM) reservoirs and abandoned mines. Investigation into the sorption-induced-strain response of coal revealed suppression of the strain response post-bioconversion. Results from helium and methane flooding revealed that bioconversion softens the coal matrix, reducing the Langmuir pressure and strain constants post-bioconversion. The modeling exercise revealed that the depletion induced the permeability increase commonly associated with producing CBM will be suppressed post-bioconversion. Detailed analysis of the behavioral variation in multiple reservoir parameters was used to define the ideal condition, beyond which the reservoir flow during biogenic methane production improved. Additionally, a rating system is proposed, which can be used to rank coal deposits to rate their suitability for bioconversion from a flow perspective.

One of the most promising mitigation strategies for greenhouse gas accumulation in the atmosphere is carbon capture and storage (CCS). Deep saline aquifers are seen as the most efficient carbon dioxide (CO2) storage sites, mainly because of their vast size and worldwide distribution. Injecting CO2 into brine filled media will cause a physical and chemical disequilibrium in the formation. This PhD thesis documents the investigation of some of the resulting effects which occur at the beginning of the injection, during the injection period and millions of years after injection. When CO2 is injected into a brine filled reservoir, large amounts of in situ brine will be displaced away from the injection well. This causes a pressure increase in the vicinity of the well which may compromise the injection process. The simulation of this pressure increase was performed with the black-oil simulator Eclipse10 (Schlumberger) while using a number of recent formulas to predict the mutual dissolution and the fluid properties of CO2 and brine. The results show that the pressure increase can exceed the maximum sustainable pore pressure and will cause fracturing of the reservoir formation. The pore pressure increase is dependent on parameters such as temperature and salinity because they change the fluid properties of the CO2 and brine, but also the capability of the fluids to dissolve mutually. The mutual dissolution has generally a pressure reducing effect although its impact is regarded to be overestimated. This is mainly because reservoir engineering software cannot simulate the shock front realistically. Undulations, which appear on the injection pressure profile are not a result of model instabilities but can either be related to enhanced mutual dissolution due to grid effects, or to the software which may overestimate or underestimate the pressure and dissolution. A detailed investigation of those undulations is vital for the interpretation of the injection pressure. High fluid pressure can be an important parameter for the estimation of the CO2 storage capacity of saline aquifers such as the offshore Bunter Sandstone Formation, in the UK southern North Sea. Based on fluid pressure, the 1 storage capacity was calculated using the ECLIPSE compositional simulation package and a simple analytical equation. The estimated storage capacity is 6.55 to 7.17 Gt of CO2 calculated with the analytical and the numerical approach respectively. By comparing the results, the differences are relatively moderate and therefore the application of the numerical simulator is not regarded as necessary. This is mainly due to the effective pressure flow which prevents pressure accumulations underneath the cap rock. Although the CO2 storage capacity of the Bunter Sandstone Formation remains high, a previous survey, which was not based on fluid pressure, calculated a storage capacity approximately twice as high as the results presented here. In theory, due to the increase in CO2 concentration, CO2 bearing carbonate minerals could precipitate when CO2 is injected into an aquifer such as the Rotliegend aquifer in the southern North Sea. Geochemical models often predict a relatively rapid growth of carbonate minerals as the most secure form of long term engineered CO2 storage. But validation of model-results remains difficult due to the long periods of time involved. Natural analogue studies can bridge the gap between experiments and real-world storage. The Fizzy field, a southern North Sea (UK) gas accumulation with a high natural CO2 content (c. 50%) provides an ideal opportunity to study the long term effect of CO2 related mineral reaction. However all such reservoirs contain ‘normal’ diagenetic dolomite, so that distinguishing sequestration related dolomite is a challenge. CO2 was stepwise extracted from dolomite from both the Fizzy field and the Orwell Rotliegend sandstone in order to reveal any zonation of the crystals which could be related to enhanced dolomite precipitation due to the high CO2 concentration. According to the method between 0 and 22 % of the dolomite in the Fizzy field precipitated due to the high CO2 concentration. Therefore, between 0 and 19 % of the CO2, which is related to the relatively recent high CO2 concentration, is ‘trapped’ in the ‘sequestration dolomite’. The wide range of this estimate is mainly related to rock heterogeneity.

A geração e proteção de estados quânticos é fundamental para a mecânica quântica. Usualmente, utilizam-se protocolos de engenharia de estados baseados na aplicação sucessiva de transformações unitárias, cuja performance se torna menos efetiva conforme aumenta-se o número de componentes envolvidos nas transformações (já que transformações unitárias dependem de um elevado número de operações ou transformações com alto grau de fidelidade), além de tornarem-se mais vulneráveis a efeitos de flutuações de parâmetros experimentais, efeitos de desordem, decoerência e ruído. Dentre as possíveis estratégias para gerar estados quânticos, existe a chamada engenharia de interações quânticas, na qual pode-se tanto estudar como alterar a maneira a partir da qual sistemas interagem entre si para produzir um determinado estado estacionário desejado, quanto para investigar propriedades dos estados gerados ao se alterar alguma característica de tal interação. Neste trabalho apresentaremos duas propostas para gerar estados não-clássicos via engenharia de reservatórios (engenharia dissipativa) em dois tipos de sistemas distintos. No primeiro, utilizaremos um sistema optomecânico no qual efetua-se engenharia de dissipação a fim de obter hamiltonianos seletivos com os quais é possível preparar-se estados de Fock sob efeitos dissipativos, no qual mostramos o caráter não clássico dos estados obtidos nos regimes de cavidade altos e baixos fatores de qualidade. No segundo, utilizaremos um sistema de spins na qual podemos obter estados não-clássicos (emaranhados) para um sistema com o número de partículas (N) entre 2 e 12 via engenharia de interações quânticas com caráter coletivo, para obter diversos estados, considerando efeitos dissipativos como dissipações térmicas e defasagem, além de considerar a robustez com relação a flutuações em alguns parâmetros experimentais do modelo. / The generation and protection of quantum states is fundamental to quantum mechanics. Usually, state engineering protocols are used based on the successive application of unitary transformations, whose performance becomes less effective as the number of components involved in the transformations increases (as that depends on a large number of high-fidelity operations), in addition to becoming more vulnerable to the effects of fluctuations of experimental parameters , effects of disorder, decoherence and noise. Among the possible strategies to yield quantum states, there is the so-called quantum interaction engineering, in which one can either study how to change the way in which systems interact with each other to produce a desired steady state, or to investigate properties of the engineered states by changing some characteristic of such interaction. In this work we present a proposal to engineer non-classical states through reservoir engineering (dissipative engineering) in two types of systems. In the first one, we will use an optomechanical system in which dissipative engineering is carried out in order to obtain selective Hamiltonians with whom it is possible to prepare Fock states under dissipative effects, in which we show the non-classical character of the states obtained in the good and bad cavity regimes.. In the second, we will use a spin chain system in which we can obtain non-classical (entangled) states for a system with the number of particles (N) between 2 and 12 via quantum interaction engineering with collective character, to obtain several states, taking into account dissipative effects such as thermal dissipation and dephasing, and showing the robustness in relation to fluctuations in some experimental parameters of the model.

We consider the structural and physical properties of complex model morphologies and microstructures obtained by Xray-CT imaging. The Minkowski functionals, a family of statistical measures based on the Euler-Poincar&eacute characteristic of n-dimensional space, are shown to be sensitive measures of the morphology of disordered structures. Analytic results for the Boolean model are given and used to devise a reconstruction scheme, which allows one to accurately reconstruct a complex Boolean structure given at any phase fraction for all other phase fractions. The percolation thresholds of either phase are obtained with good accuracy. From the reconstructions one can subsequently predict property curves for the material across all phase fractions from a single 3D image. We illustrate this for transport and mechanical properties of complex Boolean systems and for experimental sandstone samples. By extending the Minkowski functionals to parallel surfaces using operations from mathematical morphology, a powerful discrimination of structure is obtained. Further the sensitivity of the Minkowski functionals under experimental conditions is analysed. Accurate calculations of conductive and elastic properties directly from tomographic images are achieved by estimating and minimising several sources of numerical error. Simulations of electrical conductivity and linear elastic properties on microtomographic images of Fontainebleau sandstone are in excellent agreement with experimental measurements over a wide range of porosity. The results show the feasibility of combining digitised images with transport and elasticity calculations to accurately predict physical properties of individual material morphologies. We show that measurements of properties based on microtomographic images are more accurate than those based on conventional theories for disordered materials. We study the elastic behaviour of model clean and cemented sandstones. Results are in excellent agreement with available experimental data, and are compared to conventional theoretical and empirical laws. A new predictive empirical method is given for predicting the elastic moduli of sandstone morphologies. The method gives an excellent match to numerical and experimental data.

La thèse se présente comme un bilan de plus de 25 ans de fréquentation de la craie, dans divers domaines, principalement dans le domaine pétrolier. La phénoménologie du comportement de ce matériau atypique craie est présentée dans ses divers contextes, dans une optique pluridisciplinaire. Le mémoire comprend quatre parties principales : -la première partie concerne la craie en elle-même: sa constitution, sa répartition stratigraphique et géographique, sa structure, ses propriétés physiques et pétrophysiques générales; -la deuxième partie pose les problèmes des réservoirs pétroliers de Mer du Nord; -la troisième partie, la plus volumineuse, aborde le comportement mécanique de la craie comme roche réservoir; -la quatrième partie expose certains développements en cours et considère les perspectives de développements futurs.

With the recent development of smart-well technology, the reservoir community now faces the challenge of developing robust and efficient techniques for reservoir characterization by means of data inversion. Unfortunately, classical history-matching methodologies do not possess computational efficiency and robustness needed to assimilate data measured almost in real time. Therefore, the reservoir community has started to explore techniques previously applied in other disciplines. Such is the case of the representer method, a variational data assimilation technique that was first applied in physical oceanography. The representer method is an efficient technique for solving linear inverse problems when a finite number of measurements are available. To the best of our knowledge, a general representer-based methodology for nonlinear inverse problems has not been fully developed. We fill this gap by presenting a novel implementation of the representer method applied to the nonlinear inverse problem of identifying petrophysical properties in reservoir models. Given production data from wells and prior knowledge of the petrophysical properties, the goal of our formulation is to find improved parameters so that the reservoir model prediction fits the data within some error given a priori. We first define an abstract framework for parameter identification in nonlinear reservoir models. Then, we propose an iterative representer-based scheme (IRBS) to find a solution of the inverse problem. Sufficient conditions for convergence of the proposed algorithm are established. We apply the IRBS to the estimation of absolute permeability in single-phase Darcy flow through porous media. Additionally, we study an extension of the IRBS with Karhunen-Loeve (IRBS-KL) expansions to address the identification of petrophysical properties subject to linear geological constraints. The IRBS-KL approach is compared with a standard variational technique for history matching. Furthermore, we apply the IRBS-KL to the identification of porosity, absolute and relative permeabilities given production data from an oil-water reservoir. The general derivation of the IRBS-KL is provided for a reservoir whose dynamics are modeled by slightly compressible immiscible displacement of two-phase flow through porous media. Finally, we present an ad-hoc sequential implementation of the IRBS-KL and compare its performance with the ensemble Kalman filter. / text

The data assimilation process of adjusting variables in a reservoir simulation model to honor observations of field data is known as history matching and has been extensively studied for few decades. However, limited success has been achieved due to the high complexity of the problem and the large computational effort required by the practical applications. An automatic history matching module based on the ensemble Kalman filter is developed and validated in this dissertation. The ensemble Kalman filter has three steps: initial sampling, forecasting through a reservoir simulator, and assimilation. The initial random sampling is improved by the singular value decomposition, which properly selects the ensemble members with less dependence. In this way, the same level of accuracy is achieved through a smaller ensemble size. Four different schemes for the assimilation step are investigated and direct inverse and square root approaches are recommended. A modified ensemble Kalman filter algorithm, which addresses the preference to the ensemble members through a nonequally weighting factor, is proposed. This weighted ensemble Kalman filter generates better production matches and recovery forecasting than those from the conventional ensemble Kalman filter. The proposed method also has faster convergence at the early time period of history matching. Another variant, the singular evolutive interpolated Kalman filter, is also applied. The resampling step in this method appears to improve the filter stability and help the filter to deliver rapid convergence both in model and data domains. This method and the ensemble Kalman filter are effective for history matching and forecasting uncertainty quantification. The independence of the ensemble members during the forecasting step allows the benefit of high-performance computing for the ensemble Kalman filter implementation during automatic history matching. Two-level computation is adopted; distributing ensemble members simultaneously while simulating each member in a parallel style. Such computation yields a significant speedup. The developed module is integrated with reservoir simulators UTCHEM, GEM and ECLIPSE, and has been implemented in the framework Integrated Reservoir Simulation Platform (IRSP). The successful applications to two and three-dimensional cases using blackoil and compositional reservoir cases demonstrate the efficiency of the developed automatic history matching module.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.