Depuis plusieurs années, le LIDAR est utilisé en géologie pour acquérir la géométrie des affleurements sous forme de nuages de points et de surfaces. L'objectif de cette thèse consiste à développer des techniques visant à automatiser le traitement de ces données et notamment l'interprétation de structures géologiques sur affleurements numériques. Ces travaux s'insèrent dans un projet de recherche plus important financé par ENI qui a pour objectif de concevoir des méthodologies pour intégrer des données d'affleurements aux modèles géologiques. La problématique de cette thèse se focalise sur l'extraction d'objets géologiques (ie, traces de fractures ou de limites stratigraphiques) à partir de modèles numériques 3D d'affleurements. L'idée fondamentale consiste à considérer ces entités géologiques comme des lignes de ravins (ie, des lignes de forte concavité). Ce problème fait référence à la détection de lignes caractéristiques en informatique graphique. Dans un premier temps, nous proposons une méthode reposant sur les propriétés différentielles de troisième ordre de la surface (ie, dérivées de courbures). Un traitement est intégré afin de prendre en compte une connaissance a priori pour n'extraire que les objets orientés selon une direction particulière. Du fait du caractère rugueux et erratique des géométries d'affleurements, plusieurs limites apparaissent et mettent en défaut ce genre d'approche. Ainsi, dans un second temps, nous présentons deux algorithmes alternatifs afin de détecter de manière pertinente les objets géologiques ciblés. Ceux-ci prennent le contre-pied des techniques existantes en s'appuyant sur un marquage de sommets, établi depuis des propriétés différentielles de second ordre, suivi d'une opération de squelettisation. Nous validons, dans une dernière partie, l'ensemble des méthodes développées et proposons diverses applications afin de souligner la généricité des approches. / For a few years now, the LIDAR technology has been employed in geology to capture outcrop geometries as point clouds and surfaces. The objective of this thesis is to develop solutions aiming at processing these data automatically and particularly interpreting geological structures on numerical outcrops. This work is funded by ENI-Agip and fits into a larger project which is devoted to creating methodologies to integrate outcrop data into geological models. The problematic of this thesis focuses on the extraction of geological objects (ie, fractures and stratigraphic limit traces) depicted as polylines from numerical outcrop data. The fundamental idea therefore considers these geological entities as ravine lines (ie, lines with high concavity). This problem belongs to the large domain of feature line detection in computer graphics. We propose an approach based on third-order differential properties of the surface (ie, curvature derivatives). An a priori knowledge is integrated to constrain the detection in order to extract the geological structures oriented in a particular direction.The outcrop rugosity and erratic body geometries however raise several limits of this kind of method. We present two alternative algorithms to detect targeted geological objects in a pertinent way. These algorithms rely on a vertex labeling which is executed according to second-order differential properties and followed by a skeletonization process overcoming traditional approaches of feature detection. We finally present a different context of application than the detection of geological structures to validate the proposed approaches and emphasize their genericity.

Made available in DSpace on 2015-02-24T19:48:44Z (GMT). No. of bitstreams: 1 AndersonMS_TESE_inicio_pag69.pdf: 4445825 bytes, checksum: 1053632581a0015bab09d4146df22458 (MD5) Previous issue date: 2013-01-31 / Petr?leo Brasileiro SA - PETROBRAS / The aim of this work was to describe the methodological procedures that were mandatory to develop a 3D digital imaging of the external and internal geometry of the analogue outcrops from reservoirs and to build a Virtual Outcrop Model (VOM). The imaging process of the external geometry was acquired by using the Laser Scanner, the Geodesic GPS and the Total Station procedures. On the other hand, the imaging of the internal geometry was evaluated by GPR (Ground Penetrating Radar).The produced VOMs were adapted with much more detailed data with addition of the geological data and the gamma ray and permeability profiles. As a model for the use of the methodological procedures used on this work, the adapted VOM, two outcrops, located at the east part of the Parnaiba Basin, were selected. On the first one, rocks from the aeolian deposit of the Piaui Formation (Neo-carboniferous) and tidal flat deposits from the Pedra de Fogo Formation (Permian), which arises in a large outcrops located between Floriano and Teresina (Piau?), are present. The second area, located at the National Park of Sete Cidades, also at the Piau?, presents rocks from the Cabe?as Formation deposited in fluvial-deltaic systems during the Late Devonian. From the data of the adapted VOMs it was possible to identify lines, surfaces and 3D geometry, and therefore, quantify the geometry of interest. Among the found parameterization values, a table containing the thickness and width, obtained in canal and lobes deposits at the outcrop Pared?o and Biblioteca were the more relevant ones. In fact, this table can be used as an input for stochastic simulation of reservoirs. An example of the direct use of such table and their predicted radargrams was the identification of the bounding surface at the aeolian sites from the Piau? Formation. In spite of such radargrams supply only bi-dimensional data, the acquired lines followed of a mesh profile were used to add a third dimension to the imaging of the internal geometry. This phenomenon appears to be valid for all studied outcrops. As a conclusion, the tool here presented can became a new methodology in which the advantages of the digital imaging acquired from the Laser Scanner (precision, accuracy and speed of acquisition) were combined with the Total Station procedure (precision) using the classical digital photomosaic technique / Neste trabalho s?o apresentados os procedimentos metodol?gicos necess?rios para realizar o imageamento digital 3D da geometria externa e interna de afloramentos an?logos a reservat?rios, e elaborar seus Modelos Virtuais de Afloramentos (MVA). Para imagear a geometria externa foram utilizados o Laser Scanner, o GPS Geod?sico e a Esta??o Total, enquanto que para imagear a geometria interna foi utilizado o GPR. Nos MVA elaborados foram acrescidas ainda as informa??es geol?gicas e as obtidas nas perfilagens com raios gama e de permeabilidade. Como estudo de caso, para exemplificar os procedimentos metodol?gicos propostos, foram escolhidos dois conjuntos de afloramentos na borda leste da Bacia do Parna?ba. Na primeira ?rea ocorrem rochas de origem e?lica da Forma??o Piau? (Neocarbon?fero) e plan?cie de mar? da Forma??o Pedra de Fogo (Permiano), que afloram em um amplo corte de estrada, situado entre Floriano e Teresina (Piau?). A segunda ?rea, situada no Parque Nacional de Sete Cidades, tamb?m no Piau?, envolve rochas da Forma??o Cabe?as depositadas em sistemas fl?vio-deltaicos, durante o Neodevoniano. Com os MVA elaborados foi poss?vel identificar, linhas, superf?cies e geometrias 3D e, assim, quantificar as geometrias de interesse. Dentre as parametriza??es mais relevantes, ressaltam-se a tabela com valores de espessura e largura, obtidas em dep?sitos de canais e em lobos, nos afloramentos Pared?o e Biblioteca. Esta tabela pode ser utilizada como entrada (input) para simula??o estoc?stica de reservat?rios. Um exemplo da aplica??o direta dos radargramas interpretados foi a identifica??o de superf?cies limitantes, em dep?sitos e?licos, da Forma??o Piau?. Apesar dos radargramas oferecerem apenas dados bidimensionais, a aquisi??o de linhas distribu?das segundo uma malha acrescentou a terceira dimens?o ao imageamento das geometrias internas em todos os afloramentos estudados. ? ainda proposta uma nova metodologia que busca conciliar as vantagens obtidas com o imageamento digital com Laser Scanner (precis?o, acur?cia e velocidade de aquisi??o) e a Esta??o Total (precis?o), com o uso cl?ssico de fotomosaicos digitais