Interprétation des images sismiques : Approche par fusion coopérative

L'interprétation des images sismiques dans le cadre de la prospection pétrolière, est une opération complexe qui nécessite de la part des experts, une connaissance importante. Afin de les aider, une méthode semi-automatique basée sur la fusion d'informations est proposée. Elle permet de traiter un nombre important de données sismiques. La théorie des sous-ensembles flous a été retenue pour modéliser les connaissances exprimées de manière symbolique par les interprètes et les coupler avec les valeurs numériques des attributs issus de l'image. L'interface logicielle réalisée dans la cadre de cette étude permet, de plus, une coopérativité entre l'utilisateur et la machine grâce à cet aspect symbolique. Cette méthode permet ainsi de reproduire rapidement des segmentations de régions complexes

DETECTION ET REHAUSSEMENT DES FAILLES DANS LES BLOCS SISMIQUES PAR PROCESSUS OBJET

Nous proposons une nouvelle approche pour extraire le réseau de faille dans un bloc sismique 3D. Notre approche est fondée sur un processus ponctuel marqué en considérant un modèle a priori dans lequel les failles sont des segments fins connectés entre eux. L'attache aux données utilisée peut être inspirée d'attributs de détection de faille classiques leur conférant ainsi un caractère multi-échelle. De plus, l'utilisation conjointe de plusieurs attributs peut nous permettre de définir notre processus comme un processus de fusion de décision. Enfin, en considérant le réseau obtenu comme le résultat d'un processus de segmentation, nous proposons d'itérer la réalisation de l'ensemble du processus de points dans le but d'en faire une méthode de rehaussement de la détection par un attribut faille

Seismic Fault Preserving Diffusion

This paper focuses on the denoising and enhancing of 3-D reflection seismic data. We propose a pre-processing step based on a non linear diffusion filtering leading to a better detection of seismic faults. The non linear diffusion approaches are based on the definition of a partial differential equation that allows us to simplify the images without blurring relevant details or discontinuities. Computing the structure tensor which provides information on the local orientation of the geological layers, we propose to drive the diffusion along these layers using a new approach called SFPD (Seismic Fault Preserving Diffusion). In SFPD, the eigenvalues of the tensor are fixed according to a confidence measure that takes into account the regularity of the local seismic structure. Results on both synthesized and real 3-D blocks show the efficiency of the proposed approach.Comment: 10 page

A fuzzy rule-based interactive fusion system for seismic data analysis

International audienceThe study presented in this paper concerns an interactive fusion system that uses the fuzzy set theory to detect regions in three-dimensional seismic images. To achieve detection of regions in 3D seismic images, attributes extracted from images are fused using geophysicist interpreter knowledge by means of a fuzzy rule-based classifier. The original contribution of this work lies in the means proposed to the end-user for tuning the fuzzy membership functions in a two-dimensional universe for particular 2D reference image sections. The proposed graphic user interface allows to obtain a better region detection compared with the detection obtained without fusion. Moreover, a confidence index, based on information theory concepts, is introduced. This index is based on a coefficient of attribute influence and provides some elucidation on how the fusion results have been obtained

Seismic Image Segmentation by Fuzzy Fusion of Attributes

International audienceNowadays, petroleum companies want to nd some deposits to be explored in future years. To know the subsoil organization, Geophysicists try to interpret seismic images acquired by sending acoustic waves in the soil. This paper presents a method for the segmentation of these images in geological regions in order to help interpreters in their study. Information fusion of image attributes allows to solve part of this complex problem. To realize aggregation, the fuzzy subset theory is an appropriate tool to code interpreter knowledge by a set of rules. The results obtained are promising and show the necessity to evaluate their quality more thoroughly

A fuzzy linguistic-based software tool for seismic image interpretation

International audienceThe contribution of this paper concerns the well-known problem of fuzzy system parameter tuning. At this aim, a software tool based on a fuzzy linguistic approach and applied to an attribute fusion system devoted to three-dimensional (3D) seismic image analysis is proposed. The fusion is based on interpreters' knowledge and a graphic user interface has been developed in order to have a cooperative behavior between the experts and the system. It provides an original way to adjust, on a two-dimensional part of the block, some of the fusion parameters which are understandable and close to the interpreters' language. Then, in order to control the detection propagation to the whole 3D seismic block, an automatic parameter adjustment is realized based on a quantitative performance evaluation of the detection. The results obtained for the detection as well as for the handling of the system by interpreters' show the interest of the proposed method