Navegando por Assunto "Porosidade"

Agora exibindo 1 - 9 de 9

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/8388930487104926
In 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.
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/8388930487104926
Porosity 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.
Acesso aberto (Open Access)
Determinação automática da porosidade e zoneamento de perfis através da rede neural artificial competitiva
(Universidade Federal do Pará, 2000) LIMA, Klédson Tomaso Pereira de; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926
Two of the most important activities of log interpretation, for the evaluation of hydrocarbon reservoirs are the log zonation and the effective porosity calculation of the rocks crossed by the well. The log zonation is the visual log interpretation for the identification, in depth, of the reservoir layers and its vertical limits, that is to say, it is the formal separation in reservoir rocks and non reservoir rocks (shales). The log zonation procedure is accomplished in a manual way, being been worth of the geologic and geophysical knowledge, and of the experience of the log analyst, in the visual evaluation of the curve patterns (log characteristics) corresponding to each specific rock type. The calculation of the effective porosity (porosity of the rock reservoir corrected by clay effects), combines a visual activity so much in the identification of the representative points of a reservoir rock in the log, as well as the adapted choice of the petrophysics equation, that relates the physical properties of the rock to the porosity. Starting from the knowledge of the porosity, the hydrocarbon volume will be established. This activity, essential for the reservoirs qualification, requests a lot of the knowledge and of the experience of the log analyst, for the effective porosity evaluation. An efficient form of automating these procedures and assistant the log analyst, in these activities, that particularly demand a great expenditure of time, is presented in this dissertation, in the form of a new log, derived of the traditional porosity logs, that presents the log zonation, highlighting the top and base depths of the occurrences of reservoir rocks, and non reservoir rocks, scaled in form of effective porosity, called here, as "zoning effective porosity log". The obtaining of the zoning effective porosity log, is based on the project and execution of several architectures of artificial neural feedforward networks, with not supervised training, and contends a layer of artificial competitive neurons. Projected in way to simulate the behavior of the log analyst, when he uses the neutron-density chart, for the situations of applicability of the shale-sandstone model. The applicability and limitations of this methodology will be appraised on real data, originated from of Lago Maracaibo's basin (Venezuela).
Acesso aberto (Open Access)
Estimativa dos perfis de permeabilidade e de porosidade utilizando rede neural artificial
(Universidade Federal do Pará, 2002-11-05) GOMES, Laércio Gouvêa; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926
The permeability and the porosity are the two most important petrophysical properties for qualification of oil and gas reservoirs. The porosity is related to the capacity of fluids storage and the permeability, with the production of these fluids. The estimates of the permeability and porosity are of fundamental importance for reservoir engineers and geophysics, once its values can define the completacion or not of an oil well. Its measures are, usually, accomplished in laboratory, through cores of the rock. The porosity log and its relationship with the density log, is very well-known in the well logging, however, it just exist a few qualitative relationships (Kozeny's relation, for instance) between the porosity and the permeability. This work search the establishment of the permeability log and of the porosity log, starting from information of the density log. For so much, we looked for the relationship among the physical property of the rock (density) and the petrophysical properties: permeability and porosity, using as methodology the technique of artificial neural networks with radial base function. To obtaining the permeability and the porosity, the artificial neural network possessing as input the information of the density that facilitates a smaller cost for the acquisition of those important petrophysical information, giving possibility to the well log analysts, to opt or not for the exploration of a studied unit, in addition, it facilitates a more complete vision of the reservoir. The procedures for the estimate of the permeability and of the porosity are addressed for an only formation, but the log interpreters can apply the guideline presented in the program of artificial neural network with radial base function, using the estimate of those properties for another formations, besides of another oil fields. Therefore, is recommended the use of a large data set of the same well in order to make possible the best interpretation.
Acesso aberto (Open Access)
Imageamento da porosidade através de perfis geofísicos de poço
(Universidade Federal do Pará, 2004-01-27) MIRANDA, Anna Ilcéa Fischetti; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926
Porosity images are graphical representations of the lateral distribution of rock porosity estimated from well log data. We present a methodology to produce this geological image entirely independent of interpreter intervention, with an interpretative algorithm approach, which is based on two types of artificial neural networks. The first is based on neural competitive layer and is constructed to perform an automatic interpretation of the classical Pb - ΦN cross-plot, which produces the log zonation and porosity estimation. The second is a feed-forward neural network with radial basis function designed to perform a spatial data integration, which can be divided in two steps. The first refers to well log correlation and the second produces the estimation of lateral porosity distribution. This methodology should aid the interpreter in defining the reservoir geological model, and, perhaps more importantly, it should help him to efficiently develop strategies for oil or gas field development. The results or porosity images are very similar to conventional geological cross-sections, especially in a depositional setting dominated by clastics, where a color map scaled in porosity units illustrates the porosity distribution and the geometric disposition of geological layers along the section. The methodology is applied over actual well log data from the Lagunillas Formation, in the Lake Maracaibo basin, located in western Venezuela.
Acesso aberto (Open Access)
Interpretação do gráfico de Hingle através de rede competitiva angular
(Universidade Federal do Pará, 2007) SILVA, Carolina Barros da; ANDRADE, André José Neves; http://lattes.cnpq.br/8388930487104926
Water saturation is an important petrophysical property for formation evaluation, defining the final wellbore destination. The Archie’s equation calculates the water saturation for clean formations in function of rock resistivity, from a deep resistivity log and porosity, from one porosity log. The Archie’s equation, still involves the knowledge of formation water resistivity, which requires local determination and appropriated Archie’s coefficients. Hingle plot is traditional method in well logging for water saturation calculus, specially when the water resistivity is unknown. This method promotes a linearization of Archie’s equation from resistivity and porosity logs as the water line in the Hingle plot. The water resistivity is obtained from water line inclination. Independent of logging tools and digital computers development, the log analyst still handles with visual data interpretation and as all visual data interpretation, the Hingle plots interpretation is subject of sharpness errors. The objective of this dissertation is to simulate the visual interpretation of Hingle plot by a angular competitive neural network to mitigate the occurrence of sharpness errors and produces a real time first approach of water saturation, based on angular pattern identification in the raw well logging data.. The evaluation of this methodology is accomplished on synthetic data that satisfies the Archie’s equation and on actual well logging data.
Acesso aberto (Open Access)
Modelamento da permissividade dielétrica de rochas saturadas de óleo e água e suas aplicações em perfilagem de poço
(Universidade Federal do Pará, 1990-10-12) GOMES, Arnaldo Lopez Pereira; VERMA, Om Prakash; http://lattes.cnpq.br/2723609019309173
The electromagnetic propagation tool (EPT) provides the propagation time (Tpl) and the attenuation (A) of an electromagnetic wave propagating in a lossy medium. These EPT responses depend on the dielectric permittivity of the medium. There are several models and mixing equations concerning the dielectric permittivity of reservoir rocks that can be used in the interpretation of the high frequency tool. However, the mixing equations do not take into account the distribution and the geometry of the pore space, and these parameters are essential to obtaining dielectric responses approximating a true rock. A model based on the parameters described above was selected and this was applied to dielectric data available in the literature. A good agreement was reached between the theoretical curves and experimental data, confirming that the distribution and geometry of the pore space must be considered in the development of a realistic model. Aspect ratio distribution functions of the pores were also obtained, which were used for generating several curves relating the EPT responses to various oil/gas saturations. These curves were applied to the log analysis. The selected model fit the dielectric data available in the literature reasonably well, thus, making it suitable for application to experimental data of rock from Brazilian producing fields for the interpretation of the EPT in these fields.
Acesso aberto (Open Access)
Post-imaging analysis of pressure prediction in productive sedimentary basins for oil and gas exploration
(Universidade Federal do Pará, 2015-05-26) VIEIRA, Wildney Wallacy da Silva; LEITE, Lourenildo Williame Barbosa; http://lattes.cnpq.br/8588738536047617
This thesis has several aspects related to the problem of basin modeling towards oil and gas exploration, and with two general divisions: parameter estimation, and pressure prediction. For the structure of this work, the first topic is related to velocity analysis and effective media, where estimated a distribution for the P wave velocity in time, the transformation to depth, and the use an effective model for the density and for the S wave velocity distributions. The reason for initially focusing on these estimations is because they represent one of the most basic information that one can have from the seismic domain, from where the other seismic parameters can be calculated, and from where the second part of this is totally based. The second topic is related to computing stress, strain and pressure distribution in the subsurface using the information from the P and S wave velocities and the density models, in order to localize areas of high and low pressures that act as natural suction pumps for the mechanics of oil and gas accumulation into productive zones and layers. We have highlighted this second part for the final work presentation, and call attention to the sensitivity of pressure mapping to the velocity and density variations. We also classify the first division as dedicated to the conventional seismic processing and imaging, and have clled the second division as post-imaging stressstrain-pressure prediction. As for the final aim of geophysics is to create images of the subsurface under different properties, the stress calculation only makes total sense for real data, and this makes mandatory the acquired seismic data be three component. As an important conclusion from the numerical experiments, we show that pressure does not have a trivial behavior, since it can decrease with depth and create natural pumps that are responsible for accumulating fluids. The theory of porous media is based on integral geometry, because this mathematical discipline deals with collective geometrical properties for real reservoirs. It was shown that such collective properties are namely for porosity, specific surface, average curvature and Gaussian curvature. For example, cracked media has, as a rule, small porosity, but very large specific surface area that creates anomalous high 𝛾 = 𝑣𝑆/𝑣𝑃 ratio, what means a negative 𝜎 Poisson coefficient. Another conclusion is related to calculating discontinuity in pressure between solid and fluid, what depends on the structure of pore space.
Acesso aberto (Open Access)
Propriedades físicas do solo e sistema radicular do cacaueiro, da pupunheira e do açaizeiro na Amazônia oriental
(Universidade Federal do Pará, 2012-10) MARTINS, Paulo Fernando da Silva; AUGUSTO, Sebastião Geraldo
The knowledge on the relationship between roots of crop plants and soil physical properties is very important. This article evaluates the distribution of the root systems of cocoa, palm peach and açai and their relationships with the soil physical properties. The research was carried out in an alic Yellow Latosol and root and soil samples were obtained from 10 cm to 40 cm depth. The experiment was arranged in a randomized block in the factorial design (four depth soils and three root class), with four replications. The açai root amount is twice of the palm peach and ten times more that of cacao. No difference was verified in the amount of roots of peach between the distances of the plants. The roots were collected in two distances of the plant stem in monolith samples and separated in three diameter class: < 1.0 mm, 1.0-3.0 mm e > 3.0 mm. The roots amount of the three plants was directly correlated with the coarse sand content and inversely correlated with clay content and bulk density. The large pores size was also directly correlated with the amount of cacao and açai roots in the three classes of diameter. The açai showed the most abundant root system and it the greatest number of correlations between the amount of roots and the physical properties of soil involving the three diameter root classes.