<p><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Este estudo objetivou estimar a função Intensidade-Duração-Frequência (IDF) de eventos pluviométricos extremos a partir dos dados de precipitação das estações pluviométricas instaladas no estado de Rondônia, de modo que posteriormente tais informações possam ser utilizadas no dimensionamento de obras hidráulicas. Utilizou-se 41 estações pluviométricas com séries históricas acima de 10 anos, disponibilizadas pela Agência Nacional de Águas (ANA). Essas séries passaram inicialmente pelo teste de aderência Kolmogorov-Smirnov (KS), a fim de verificar o ajuste das mesmas as </span><span style="font-size: 12pt; line-height: 115%; font-family: 'Times New Roman', serif;">distribuições: Normal, Log-Normal, Exponencial, Gama, Gumbel, Weibull e Logística</span><span style="font-size: 12pt; line-height: 115%; font-family: 'Times New Roman', serif;">. O trabalho denotou que o teste de aderência </span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Kolmogorov-Smirnov de forma geral forneceu uma expressiva aceitação na maioria das distribuições estatística testadas.</span></p><p> </p><p align="center"><strong><em>Analysis of fitness for extreme rainfall events in western amazon in static models: state Rondônia</em></strong></p><p> </p><p><strong>ABSTRACT: </strong>This study aimed to estimate the Intensity - Duration - Frequency (IDF) function extreme rainfall events from the data of precipitation of rainfall stations located in the State of Rondônia, so that such information can be later used in hydraulic structures. We used 41 rainfall stations with historical series over 10 years, provided by the National Water Agency (ANA). These series originally started by adherence Kolmogorov -Smirnov (KS) in order to check the fit of the same distributions: Normal, Log- Normal, Exponential, Gamma, Gumbel, Weibull and Logistics. Work denoted that the Kolmogorov - Smirnov test of adherence generally provided a significant acceptance in most of the tested statistical distributions.<strong></strong></p><p><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"><br /></span></p>
Considered important analogues of pre-salt reservoirs in hydrocarbon-producing basins throughout eastern Brazilian shore, the coquinas of the Morro do Chaves Formation (Barremian-Aptian of the Sergipe-Alagoas Basin) were studied in this work from a petrophysical standpoint using advanced characterization methods for cores recovered from four wells (2-SMC-01-AL, 2-SMC-02-AL, 2-SMC-03-AL e 2-SMC-01-AL) drilled in the Atoll Quarry, which is located in city of São Miguel dos Campos, Alagoas State, Brazil. To understand the relationships between lithological and diagenetic heterogeneities that control the distribution of permeability-porosity properties of this rock type, the cores underwent Dual-Energy X-ray imaging, which determines bulk density and photoelectric factor data to define seven rock types and generate effective porosity curves for the studied wells. Permeabilities in wells were modeled based on the Flow Zone Index (FZI) concept, and each reservoir interval based on the Global Hydraulic Elements (GHEs) approach. Results were calibrated with laboratory measurements in plugs, and porosity was classified by petrographic analysis by Digital Image Analysis (DIA). All wells were correlated and four internal flooding surfaces identified, with a regressive surface (RS) dividing the Morro do Chaves Formation into an upper section with better reservoir characteristics and a lower one with worse ones.
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