Dissertações em Geofísica (Mestrado) - CPGF/IG
URI Permanente para esta coleçãohttps://repositorio.ufpa.br/handle/2011/4993
O Mestrado Acadêmico pertente a o Programa de Pós-Graduação em Geofísica (CPGF) do Instituto de Geociências (IG) da Universidade Federal do Pará (UFPA).
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Item Acesso aberto (Open Access) Cálculo da porosidade: identificação do argilomineral(Universidade Federal do Pará, 2017-04-20) ALMEIDA, Thales Luiz Pinheiro de; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926In the daily practice of Formation Evaluation it is common the adoption of simplifying hypotheses or premises about the physical properties of the reservoir rock constituent materials to allow the porosity calculation. The knowledge of the physical properties of the clay in the reservoir rock is fundamental for porosity calculation. In this work it is argued that the physical properties of the clay mineral in the reservoir rock are different from the mean physical properties of the nearby shale layers. Geologically, the clay is one of the constituent materials of shale rock and to admit that the physical properties of the shale are equal to the physical properties of the clay in the reservoir rock means to disregard all the other constituents and to assume a sedimentary continuity that due to numerous postpositional processes may not occur. In this work, we apply the angular competitive neural network to the Density- Neutron Plot to show that if a reservoir rock and a shale present in the basin have the same clay, they have the same angular pattern. This methodology is presented with synthetic data and evaluated with actual well logs and core analysis from borehole drilled in the Namorado’s field, in the Campos Basin, Brazil.Item Acesso aberto (Open Access) Cálculo de porosidade com a rede neural competitiva(Universidade Federal do Pará, 2015-10-26) ROSELLÓN GUZMAN, Laura Yesenia; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926Porosity is the petrophysical property that quantifies the fluid volume in the reservoir rock under for subsurface original condition. However, its calculation by the densityneutron method is extremely difficult in non cored borehole by the lack of the knowledge about the matrix physical properties (density and neutron porosity). This work presents a method for enabling the use of density-neutron Method in non cored boreholes, showing a realistic estimate of the matrix physical properties for each reservoir layer, using a angular competitive neural network. For each layer, network training is performed in the density-neutron plot built with the points of this layer and the information about the grain density (matrix density), obtained in the core analysis. This method is presented with synthetic data, which satisfy the petrophysical model and real data from two cored wells in the Namorado field, Campos basin.Item Acesso aberto (Open Access) Estimativa de porosidade em lâminas petrográficas através da morfologia matemática binária(Universidade Federal do Pará, 2013-08-02) CASTELO, Fernando Walleson Louzada; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926Oil exploration in offshore basins needs for drilling boreholes with high angle and horizontal wells, aimed at optimizing the number of exploration targets hit by a single platform. In these cases, it is technically impossible to carry out the coring operations, which prevents core analysis for direct measurement of porosity. In some situations in formation evaluation the geological knowledge of the area may help when there is low confidence in the porosity values. For the semi-submerged basins, the lateral continuity of geologic layers may allow sampling of outcrops in the immersed part of the basin. In the case of offshore basins, may be collected hand samples in outcrops of analogous formations. A relatively common problem in a petrophysical laboratory is the extraction of plugs adapted to the measuring equipment, directly from rock samples collected from outcrops. On the other hand, for this type of rock sample is trivial to obtain thin sections. The objective of this work is to estimate porosity directly on the petrographic images using the image processing method, known as mathematical morphology, which aims to describe quantitatively the geometric structures (forms) in this image.Item Acesso aberto (Open Access) Identificação de fácies em perfis com algoritmo heurístico(Universidade Federal do Pará, 2015-02-27) ALMEIDA, Thelson Luiz Pinheiro de; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926The development of oil well drilling techniques and the optimization exploitation of various hydrocarbon reservoirs on the same time, an issue has drawn attention from researchers from the oil industry: identification of sedimentary facies in wells not core available. Therefore, this paper proposes the use of a heuristic algorithm based on the behavior of insects, which contributes to the interpretation of M-N Graphic on computational way. Using wells logs and plot your data in graphic M-N, we have aimed to sort of well log points in relation to fixed points, using the creation of groups (clusters) of data that have some similarity or symmetry, based on what we call attractiveness. Using the creation of these groups of points of the well log, in the neighborhood of fixed points through which suffered major attraction, we can do the identification of multiple data families which, in this work, will be taken as layers, depending on which mineral fixed point are closer, can have their main mineral composition identified without the help of the core and thus obtain the sedimentary facies knowledge overpassed by the well.Item Acesso aberto (Open Access) Identificação de fácies em perfis com rede neural direta(Universidade Federal do Pará, 2015) GOMES, Kivia do Carmo Palheta; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926The application of coring techniques is usually carried out in a limited number of vertical wells drilled in an oil field, causing the rarefaction of facies descriptions and not allowing a realistic characterization of reservoirs. Increased production of hydrocarbons in an oil field is extremely important for the oil industry and deeply dependent on the knowledge of the reserves in accordance with their petrophysical properties, which vary depending on geological facies. A better description of facies may reflect more realistic estimates of hydrocarbon volumes. This dissertation presents an intelligent algorithm capable of producing the transport of geologic information produced by the facies analysis of cores to the non-cored wells in an oil field, through the design of a direct neural network trained to perform a mapping of geological information in terms of the physical properties registered in the well logs. The intelligent algorithm processes the result produced by the neural network through a depth coherence filter to locate the boundaries of the layers along the well trajectory. For all of our cases the intelligent algorithm presented results compatible with the core analysis and independent of the size of the training set.Item Acesso aberto (Open Access) Identificação de fácies em perfis de poço com algoritmo inteligente(Universidade Federal do Pará, 2014-02-17) SANTOS, Renata de Sena; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926Facies identification in an uncored borehole is a classic problem in formation evaluation. In this study, this problem is treated as the extraction of geological information or facies descriptions from a cored borehole in terms of their physical properties registered in well logs and perform their encoding through the parameters L and K calculated from porosity logs, and shaliness calculated using the natural gamma ray log to construct the Vsh-L-K plot. For interpretation is presented an intelligent algorithm based on the competitive generalized angular neural network, built for angular pattern classification or data clustering in ndimensional space that have an approximately ellipsoidal envelope, which are the characteristics of clusters in the Vsh-L-K plot and make your visual interpretation extremely complex. The application of intelligent algorithm is able to identify and classify the layers present in uncored boreholes, in terms of the facies identified in the cored borehole or in terms of its main mineral, when it is absent in the cored borehole. This methodology is presented with synthetic data and well logs from cored boreholes in Namorado oil field, in the Campos Basin, located on the continental shelf of Rio de Janeiro, Brazil.Item Acesso aberto (Open Access) Identificação litológica com affinity propagation(Universidade Federal do Pará, 2013-03-26) CALDAS, Nayara Safira da Silva; GUERRA, Carlos Eduardo; http://lattes.cnpq.br/7633019987920516; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926This work presents a methodology for solving the problem of extracting geological information, such as identification of lithologies at depth, directly from wireline logs. For this propose, the Vsh-M-N plot is used as the formation evaluation technique for identifying the lithologies in the logged borehole, in terms of the physical properties of the main mineral in each lithology. However, the visual interpretation of this graphic is limited by the large spread of the points in the graph. To evaluate a form of computational interpretation of the Vsh-M-N, the affinity propagation algorithm is used in reason of its characteristic transport of information among similar objects, which enables the interpretation of Vsh-M-N plot considering the physical properties and continuity in the depth. This methodology is presented using synthetic data and well logs from one borehole in the Namorado field. Campos basin. Brazil.Item Acesso aberto (Open Access) Reconhecimento de fáceis em perfis geofísicos de poços com rede neural competitiva(Universidade Federal do Pará, 2015-02-27) COSTA, Jéssica Lia Santos da; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926The description of a depositional system based on the recognition of sedimentary facies is critical to the oil industry to characterize the petroleum system. In the absence of these facies description by cores or outcrop, we present a methodology based on intelligent algorithm able to identify facies of interest in wireline logs. This methodology uses a competitive neural network to extract geological information from the physical properties mapped in the M-N plot. The competition among neurons identifies the facies of interest, which have been previously identified in a cored borehole in other non-cored boreholes in the same oil field. The purpose of this methodology is to encode and transmit the geological information gained in cored boreholes to non-cored wells and thus achieve the geological interpretation of the facies of interest in an oil field. This methodology has been evaluated with synthetic data and actual wireline logs from two cored boreholes drilled in the Namorado oil field, Campos Basin, Brazil.Item Acesso aberto (Open Access) Tying seismic to well based on deterministic wavelet estimative and predictive deconvolution: application in the North Sea seismic(Universidade Federal do Pará, 2015-12-04) MACEDO, Isadora Augusta Santana de; FIGUEIREDO, José Jadsom Sampaio de; http://lattes.cnpq.br/1610827269025210; SILVA, Carolina Barros da; http://lattes.cnpq.br/5306784916926352Wavelet estimation as well as well-tie procedure are important tasks in seismic processing and interpretation. In this work we perform comparative study of the well-to-seismic tie. The comparison relies on different approaches to estimate the wavelet: a deterministic estimation, based on both seismic and well log data, and a statistical estimation, based on predictive deconvolution and the classical assumptions concerning the convolutional model. Tests with numerical data show the estimation of seismic wavelet with reasonable accuracy for both cases. The feasibility of this approach is also verified on the real seismic and well data from Viking Graben field, North Sea, Norway. The results also shown the influence of the washout zones on the well log data on the well to seismic tie.Item Acesso aberto (Open Access) Zoneamento de poços através da inferência Fuzzy(Universidade Federal do Pará, 2015-06-26) RUIZ TAPIA, Alberto José; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926Well zoning may be understood as the geological characterization (location and facies description) of each layer crossed by the borehole trajectory. Well zoning is a common activity in conventional core analysis and important for petroleum geology, assisting the construction of stratigraphic column and also for petroleum engineering aiding in the development of the well exploitation plan. This work presents a method for well zoning wells of non cored boreholes, so that the information gained in these wells can contribute to improve the knowledge of sedimentology and oilfield engineering. The method showed here uses the core description for building the knowledge base of a fuzzy inference system, which operates with P parameter (a new combination of density log and sonic log), parameter M (M-N plot) and the natural gamma ray log and the deep resistivity log. Operation of this fuzzy inference system using log data from non cored borehole produces the well zoning of each non cored borehole. This method is presented with synthetic data satisfying the petrophysical model and the Archie Law, and real data of two cored boreholes from the Namorado oilfield, in the Campos Basin.