Stable dispersions of magnetic nanoparticles that are already in use in biomedicine as image-enhancing agents, also have potential use in subsurface applications. Surface-coated nanoparticles are capable of flowing through micron-size pores across long distances in a reservoir with modest retention in rock. Tracing these contrast agents using the current electromagnetic tomography technology could potentially help track the flood-front in waterflood and EOR processes and characterize the reservoir. The electromagnetic (EM) tomography used in the petroleum industry today is based on the difference between the electrical conductivity of reservoir fluids as well as other subsurface entities. The magnetic nanoparticles that are considered in this study, however, change the magnetic permeability of the flooded region, which is a novel application of the existing EM tomography technology. As the first fundamental step, the magnetic permeability change in rock due to injecting magnetic nanoparticles is quantified as a function of particle and reservoir properties. Subsequently, a new formulation is devised to compute the sensitivity of magnetic measurements to magnetic permeability perturbations. The results are then compared with the sensitivity to conductivity perturbations to identify the application space of magnetic contrast agents. Using numerical simulations, the progress of magnetic nanoparticle bank is monitored in the reservoir through time-lapse magnetic tomography measurements that are expected. Initially, simple models for displacement of injection banks are assumed and the level of complexity is gradually increased to incorporate the realities of fluid flow in the reservoir. The fluid-flow behavior of the nanoparticles is dynamically integrated with time-lapse magnetic response. Since the nanoparticles could help illuminate the flow paths, they could be used to indirectly measure reservoir heterogeneities. Therefore, numerous case studies are demonstrated where reservoir heterogeneity could potentially be inferred. Finally, fundamental pore-scale models are developed as a first step towards the multiple fluid phases extension of the EM tomography application. Using magnetic nanoparticles to improve electromagnetic tomography provides several strategic advantages. One key advantage is that the magnetic nanoparticles provide high resolution measurements at very low frequencies where the conductivity contrast is hardly detectable and casing effect is manageable. In addition, the sensitivity of magnetic measurements at the early stages of the flood is significantly improved with magnetic nanoparticles. Moreover, the vertical resolution of magnetic measurements is significantly enhanced with magnetic nanoparticles present in the vicinity of source or receiver. The fact that the progress of the magnetic slug can be detected at very early stages of the flood, that the traveling slug’s vertical boundaries can be identified at low frequencies, that the reservoir heterogeneities could potentially be characterized, and that the magnetic nanoparticles can be sensed much before the actual arrival of the slug at the observer well, provides significant value of using magnetic contrast agents for reservoir illumination. / text

Recent terrorist attacks and the subsequently perceived threats to national security have meant that the demands of security networks are greater than ever before. The walkthrough metal detector (WTMD) is on the frontline of the personal security screening network and is used to check individuals for metallic threat objects such as knives or guns. In many operational conditions each positive identification of a metallic object is first considered to be a threat, however in many instances the source of the trigger does not necessarily constitute the detection of a threat object as many innocuous metallic items are allowed in certain secured zones, e.g. a mobile phone in an airport. Operators are often required to perform physical searches to confirm that the trigger was not due to a threat object. Often little or no positional information is provided, and as a result the time taken to conduct a physical search is often significant and causes delays to people waiting to be screened. A tomographic magnetic imaging system was designed and built with the intention of recovering detailed information about magnetic and/or conductive objects within the detector space, in addition to identifying the position of the detected object to a greater degree of accuracy than is possible with the current generation of WTMDs. The object-specific information that is recovered by the system is in the form of the magnetic polarisability dyadic tensor, which is considered to completely describe the behaviour of an object when it interacts with a magnetic field. The prototype system that has been produced is capable of inverting object tensors with a typical error of < 20%, and determines three-dimensional object location with an error of ±2 to ±3 cm. Given that both the inversion of an object tensor, and object location to this degree of accuracy have not been observed in the academic or commercial literature it is claimed that both of these factors represent original work. In order to achieve this level of performance a special 8-transmit, 8-receive coil array has been produced which is capable of minimising mutual coupling between all channels during background operation. This allows for greater detection of changes occurring as a result of the presence of the object, rather than from the excitation source. A procedure for modelling the response of this prototype coil array to a specified magnetic polarisability dyadic tensor is derived and tested by examining the response of the system to a ferrite sphere. This testing indicates that the measurements from the WTMD and simulated object response differ by less than 10% in almost all cases. Testing of the inversion algorithm has been conducted with six known objects, and the system has been shown to perform consistently, and to an acceptable degree of accuracy. The procedure for the inversion of an object tensor is based upon the response of the model, and consequently this error contains a portion of the error contained from the model. The detector system was tested in an airport environment where sensitivity was shown to be beyond the levels required for typical operation.

Este trabalho apresenta um estudo prospectivo referente ao desenvolvimento de um medidor eletromagnético inteligente de vazão, cuja finalidade é determinar a vazão de escoamento a partir da reconstrução do perfil de velocidade utilizando técnicas tomográficas. Em conseqüência disso, o medidor de vazão será capaz de corrigir a vazão dada, através da integração do perfil de velocidade correto reconstruído por tomografia. A técnica de reconstrução tomográfica utilizada é baseada na construção de um funcional de erro, gerado a partir da diferença entre voltagens simuladas numericamente para uma condição experimental, conhecidos os parâmetros determinantes da velocidade no interior da tubulação, e voltagens aproximadas simuladas numericamente para aproximações destes parâmetros. Neste trabalho, o modelo físico do medidor eletromagnético de vazão é baseado em um número de eletrodos colocados sobre as paredes do tubo sob uma estratégia de excitação específica, sem injeção de corrente, considerando o campo magnético uniforme. A partir da expansão do funcional de erro, sobre um conjunto de funções conhecidas, uma superfície de erro é gerada. As características da patologia desta superfície requerem outros tipos de técnicas de otimização. Técnicas tradicionais de otimização não são viáveis, pois o processo de busca pára no primeiro mínimo local encontrado. Essa convergência para mínimos locais é justificada devido à presença de regiões planas e vales apresentando vários mínimos locais circundando o ponto de mínimo global (ou ponto referente aos parâmetros ótimos da velocidade). Em vista da ocorrência deste fato, técnicas baseadas em algoritmos evolucionários são testadas e apresentadas para uma série de casos demonstrando a praticidade de nossa pesquisa. / This work presents a prospective study on the development of an intelligent electromagnetic flow meter intended to determine output based on the reconstruction of velocity profile using tomographic techniques. As a result, the flow meter will be able to correct the output measure through the integration of the right velocity profile produced by tomography. The tomographic reconstruction technique utilized is based on the definition of an error functional generated from the difference between voltages simulated numerically for a experimental condition, being known the parameters which define the velocity within the pipe and approximate voltages simulated numerically for approaches of these parameters. In this work the physical model of the electromagnetic flow meter is based on a number of electrodes flush mounted on pipe walls and under a specific strategy of excitement, without electrical current input and considering the magnetic field uniform. From the expansion of the error functional over a set of known functions an error surface is generated. The characteristics of the pathology of this surface require other types of optimization techniques. Traditional optimization techniques are not viable since the search stops at the first local minimum. This convergence to local minimums is justified due to the presence of flat regions and valleys presenting several local minimums around the global minimum point (or point relative to the optimum parameters of velocity). Due to this fact techniques based on evolutionary algorithms are tested and presented for a series of cases demonstrating the usefulness of our research.

Este trabalho apresenta um estudo prospectivo referente ao desenvolvimento de um medidor eletromagnético inteligente de vazão, cuja finalidade é determinar a vazão de escoamento a partir da reconstrução do perfil de velocidade utilizando técnicas tomográficas. Em conseqüência disso, o medidor de vazão será capaz de corrigir a vazão dada, através da integração do perfil de velocidade correto reconstruído por tomografia. A técnica de reconstrução tomográfica utilizada é baseada na construção de um funcional de erro, gerado a partir da diferença entre voltagens simuladas numericamente para uma condição experimental, conhecidos os parâmetros determinantes da velocidade no interior da tubulação, e voltagens aproximadas simuladas numericamente para aproximações destes parâmetros. Neste trabalho, o modelo físico do medidor eletromagnético de vazão é baseado em um número de eletrodos colocados sobre as paredes do tubo sob uma estratégia de excitação específica, sem injeção de corrente, considerando o campo magnético uniforme. A partir da expansão do funcional de erro, sobre um conjunto de funções conhecidas, uma superfície de erro é gerada. As características da patologia desta superfície requerem outros tipos de técnicas de otimização. Técnicas tradicionais de otimização não são viáveis, pois o processo de busca pára no primeiro mínimo local encontrado. Essa convergência para mínimos locais é justificada devido à presença de regiões planas e vales apresentando vários mínimos locais circundando o ponto de mínimo global (ou ponto referente aos parâmetros ótimos da velocidade). Em vista da ocorrência deste fato, técnicas baseadas em algoritmos evolucionários são testadas e apresentadas para uma série de casos demonstrando a praticidade de nossa pesquisa. / This work presents a prospective study on the development of an intelligent electromagnetic flow meter intended to determine output based on the reconstruction of velocity profile using tomographic techniques. As a result, the flow meter will be able to correct the output measure through the integration of the right velocity profile produced by tomography. The tomographic reconstruction technique utilized is based on the definition of an error functional generated from the difference between voltages simulated numerically for a experimental condition, being known the parameters which define the velocity within the pipe and approximate voltages simulated numerically for approaches of these parameters. In this work the physical model of the electromagnetic flow meter is based on a number of electrodes flush mounted on pipe walls and under a specific strategy of excitement, without electrical current input and considering the magnetic field uniform. From the expansion of the error functional over a set of known functions an error surface is generated. The characteristics of the pathology of this surface require other types of optimization techniques. Traditional optimization techniques are not viable since the search stops at the first local minimum. This convergence to local minimums is justified due to the presence of flat regions and valleys presenting several local minimums around the global minimum point (or point relative to the optimum parameters of velocity). Due to this fact techniques based on evolutionary algorithms are tested and presented for a series of cases demonstrating the usefulness of our research.

One of the most challenging tasks of our visual systems is to structure and integrate the enormous amount of incoming information into distinct coherent objects. It is an ongoing debate whether or not the formation of visual objects requires attention. Implicit behavioral measures suggest that object formation can occur for task-irrelevant and unattended visual stimuli. The present study investigated pre-attentive visual object formation by combining implicit behavioral measures and an electrophysiological indicator of pre-attentive visual irregularity detection, the visual mismatch negativity (vMMN) of the event-related potential. Our displays consisted of two symmetrically arranged, task-irrelevant ellipses, the objects. In addition, there were two discs of either high or low luminance presented on the objects, which served as targets. Participants had to indicate whether the targets were of the same or different luminance. In separate conditions, the targets either usually were enclosed in the same object or in two different objects (standards). Occasionally, the regular target-to-object assignment was changed (deviants). That is, standards and deviants were exclusively defined on the basis of the task-irrelevant target-to-object assignment but not on the basis of some feature regularity. Although participants did not notice the regularity nor the occurrence of the deviation in the sequences, task-irrelevant deviations resulted in increased reaction times. Moreover, compared with physically identical standard displays deviating target-to-object assignments elicited a negative potential in the 246–280 ms time window over posterio-temporal electrode positions which was identified as vMMN. With variable resolution electromagnetic tomography (VARETA) object-related vMMN was localized to the inferior temporal gyrus. Our results support the notion that the visual system automatically structures even task-irrelevant aspects of the incoming information into objects.