Evolução diagenética e caracterização dos reservatórios da seção devoniana na Bacia do Rio do Peixe-Nordeste do Brasil

The Rio do Peixe Basin represents a main basin of northeastern Brazil and pioneering work positioned the rocks of this basin in the Early Cretaceous. However, a recent study, based on integrated pollen analysis from three wells, found an unprecedented siliciclastic sedimentary section, in the region, of early Devonian age. Therefore, the present study aims a detailed petrographic and petrological analysis of this devonian section, in the Rio do Peixe Basin and proposes a diagenetic evolution, to understand the characteristics of the porous system, identify the main reservoir petrofacies with the main factors impacting on the quality of these rocks as reservoirs and a quick study on the provenance of this section. The petrographic study was based on samples obtained from subsurface and surface. The diagenetic evolution of petrofacies and its identification were based only on subsurface samples and the study of provenance was based on surface samples. The thin sections were prepared from sandstones, pelites and sandstones intercalated with pelites. The original detrital composition for this section is arcosean and the main diagenetic processes that affected these rocks occur in various depths and different conditions, which resulted in extensive diagenetic variety. The following processes were identified: early fracture and healing of grains; albitization of K-feldspar and plagioclase; siderite; precipitation of silica and feldspar; mechanical infiltration of clay and its transformation to illite/esmectite and illite; autigenesis of analcime; dissolution; autigenesis of chlorite; dolomite/ferrous dolomite/anquerite; apatite; calcite; pyrite; titanium minerals and iron oxide-hidroxide. The occurrence of a recently discovered volcanism, in the Rio do Peixe Basin, may have influenced the diagenetic evolution of this section. Three diagenetic stages affected the Devonian section: eo, meso and telodiagenesis. This section is compositionally quite feldspathic, indicating provenance from continental blocks, between transitional continental and uplift of the basement. From this study, we observed a wide heterogeneity in the role of the studied sandstones as reservoirs. Seven petrofacies were identified, taking into account the main diagenetic constituent responsible for the reduction of porosity. It is possible that the loss of original porosity was influenced by intense diagenesis in these rocks, where the main constituent for the loss of porosity are clays minerals, oxides and carbonate cement (calcite and dolomite)

Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR

This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary layers, from a data bank built with information from the Ground Penetrating Radar GPR. The intelligent system was built to model the relation between the porosity (response variable) and the electromagnetic attribute from the GPR (explicative variables). Using it, the porosity was estimated using the artificial neural network (Multilayer Perceptron MLP) and the multiple linear regression. The data from the response variable and from the explicative variables were achieved in laboratory and in GPR surveys outlined in controlled sites, on site and in laboratory. The proposed intelligent system has the capacity of estimating the porosity from any available data bank, which has the same variables used in this Thesis. The architecture of the neural network used can be modified according to the existing necessity, adapting to the available data bank. The use of the multiple linear regression model allowed the identification and quantification of the influence (level of effect) from each explicative variable in the estimation of the porosity. The proposed methodology can revolutionize the use of the GPR, not only for the imaging of the sedimentary geometry and faces, but mainly for the automatically achievement of the porosity one of the most important parameters for the characterization of reservoir rocks (from petroleum or water)