4 resultados para critical path methods
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
In the present study we elaborated algorithms by using concepts from percolation theory which analyze the connectivity conditions in geological models of petroleum reservoirs. From the petrophysical parameters such as permeability, porosity, transmittivity and others, which may be generated by any statistical process, it is possible to determine the portion of the model with more connected cells, what the interconnected wells are, and the critical path between injector and source wells. This allows to classify the reservoir according to the modeled petrophysical parameters. This also make it possible to determine the percentage of the reservoir to which each well is connected. Generally, the connected regions and the respective minima and/or maxima in the occurrence of the petrophysical parameters studied constitute a good manner to characterize a reservoir volumetrically. Therefore, the algorithms allow to optimize the positioning of wells, offering a preview of the general conditions of the given model s connectivity. The intent is not to evaluate geological models, but to show how to interpret the deposits, how their petrophysical characteristics are spatially distributed, and how the connections between the several parts of the system are resolved, showing their critical paths and backbones. The execution of these algorithms allows us to know the properties of the model s connectivity before the work on reservoir flux simulation is started
Resumo:
In the present study we elaborated algorithms by using concepts from percolation theory which analyze the connectivity conditions in geological models of petroleum reservoirs. From the petrophysical parameters such as permeability, porosity, transmittivity and others, which may be generated by any statistical process, it is possible to determine the portion of the model with more connected cells, what the interconnected wells are, and the critical path between injector and source wells. This allows to classify the reservoir according to the modeled petrophysical parameters. This also make it possible to determine the percentage of the reservoir to which each well is connected. Generally, the connected regions and the respective minima and/or maxima in the occurrence of the petrophysical parameters studied constitute a good manner to characterize a reservoir volumetrically. Therefore, the algorithms allow to optimize the positioning of wells, offering a preview of the general conditions of the given model s connectivity. The intent is not to evaluate geological models, but to show how to interpret the deposits, how their petrophysical characteristics are spatially distributed, and how the connections between the several parts of the system are resolved, showing their critical paths and backbones. The execution of these algorithms allows us to know the properties of the model s connectivity before the work on reservoir flux simulation is started
Resumo:
The complex behavior of a wide variety of phenomena that are of interest to physicists, chemists, and engineers has been quantitatively characterized by using the ideas of fractal and multifractal distributions, which correspond in a unique way to the geometrical shape and dynamical properties of the systems under study. In this thesis we present the Space of Fractals and the methods of Hausdorff-Besicovitch, box-counting and Scaling to calculate the fractal dimension of a set. In this Thesis we investigate also percolation phenomena in multifractal objects that are built in a simple way. The central object of our analysis is a multifractal object that we call Qmf . In these objects the multifractality comes directly from the geometric tiling. We identify some differences between percolation in the proposed multifractals and in a regular lattice. There are basically two sources of these differences. The first is related to the coordination number, c, which changes along the multifractal. The second comes from the way the weight of each cell in the multifractal affects the percolation cluster. We use many samples of finite size lattices and draw the histogram of percolating lattices against site occupation probability p. Depending on a parameter, ρ, characterizing the multifractal and the lattice size, L, the histogram can have two peaks. We observe that the probability of occupation at the percolation threshold, pc, for the multifractal is lower than that for the square lattice. We compute the fractal dimension of the percolating cluster and the critical exponent β. Despite the topological differences, we find that the percolation in a multifractal support is in the same universality class as standard percolation. The area and the number of neighbors of the blocks of Qmf show a non-trivial behavior. A general view of the object Qmf shows an anisotropy. The value of pc is a function of ρ which is related to its anisotropy. We investigate the relation between pc and the average number of neighbors of the blocks as well as the anisotropy of Qmf. In this Thesis we study likewise the distribution of shortest paths in percolation systems at the percolation threshold in two dimensions (2D). We study paths from one given point to multiple other points. In oil recovery terminology, the given single point can be mapped to an injection well (injector) and the multiple other points to production wells (producers). In the previously standard case of one injection well and one production well separated by Euclidean distance r, the distribution of shortest paths l, P(l|r), shows a power-law behavior with exponent gl = 2.14 in 2D. Here we analyze the situation of one injector and an array A of producers. Symmetric arrays of producers lead to one peak in the distribution P(l|A), the probability that the shortest path between the injector and any of the producers is l, while the asymmetric configurations lead to several peaks in the distribution. We analyze configurations in which the injector is outside and inside the set of producers. The peak in P(l|A) for the symmetric arrays decays faster than for the standard case. For very long paths all the studied arrays exhibit a power-law behavior with exponent g ∼= gl.
Resumo:
The present essay shows strategies of improvement in a well succeded evolutionary metaheuristic to solve the Asymmetric Traveling Salesman Problem. Such steps consist in a Memetic Algorithm projected mainly to this problem. Basically this improvement applied optimizing techniques known as Path-Relinking and Vocabulary Building. Furthermore, this last one has being used in two different ways, in order to evaluate the effects of the improvement on the evolutionary metaheuristic. These methods were implemented in C++ code and the experiments were done under instances at TSPLIB library, being possible to observe that the procedures purposed reached success on the tests done