Navegando por Assunto "Porosity"

Agora exibindo 1 - 3 de 3

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)
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.