Speaker(s): Guillaume Caumon

Date: Thursday 12th of November 2020, 1:20 pm


Speaker(s): Lionel Bertrand & Martin Stanek

Date: Thursday 22nd of October 2020, 1:00 pm.


La caractérisation du réseaux de failles et des fractures associées est un élément clé pour la compréhension des circulations de fluides dans de nombreux objets géologiques. C’est particulièrement le cas pour les réservoirs fracturés où les failles sont une des cible des prospections pétrolières ou géothermiques. Pour une analyse optimale des circulations de fluides associées aux failles, il est nécessaire d’étudier les objets à toutes les échelles : à l’échelle régionale (bassin, orogène,…) pour comprendre le batî structural et l’organisation du réseaux de failles pouvant servir de drains, à l’échelle du réservoir pour caractériser et modéliser les circulations de fluides dans les coeurs de failles et les zones endommagées, à l’échelle microscopique où la microfissuration a une influence sur les interactions fluides-roches qui modifient les propriétés matricielles du réservoir. Dans ce séminaire, il s’agit de présenter les data utilisées et disponibles dans l’équipe RC de GeoRessources pour la réalisation de ces études, les résultats qui sont espérés et problématiques associées à chaque type de data.

Speaker(s): Paul Baville

Date: Thursday 15th of October 2020, 1:00 pm.


Assisted well correlation aims at complementing sedimentological expertise with computational rigor to increase automation, improve reproducibility and assess uncertainties during stratigraphic correlation. We propose a computer-assisted method which automatically generates possible well correlations based on facies interpretation, dipmeter data and knowledge about depositional environments.

This method uses facies interpretations and progading or backstepping trends deduced from the vertical stacking of depositional environments. These data are translated into a paleo-geographic variable inferred from depositional environments, e.g. the position along a proximal-to-distal transect. Assuming that wells have a global distality due to their position with respect to the overall basin geometry within the considered stratigraphic interval, we can interpolate a three-dimensional surface constrained by well-markers and dipmeter data acquired along wells. These surfaces represent chronostratigraphic surfaces. In a first approximation, the depositional dip direction is assumed to parallel sediment transport direction and the depositional strike direction being at a right angle to the former.

Well correlations are computed using correlation costs between all possible marker combinations aggregated by the Dynamic Time Warping algorithm. These correlation costs are based on the shape of the relative paleo-topography. Additionally, proximal facies interpreted in a distal well cannot be associated with distal facies interpreted in a proximal well, and conversely distal facies interpreted in a distal well may be likely associated with a proximal facies interpreted in a proximal well. Along the depositional strike, the method tries to associate identical or close facies with respect to distality.

Speaker(s): Zoé Renat

Date: Thursday 01st of October 2020 - 01:00 pm.


Time reversal allows us to locate earthquakes by back-propagating seismic waveforms recorded at a set of receivers in depth. Doing so, the seismic energy focuses, pointing out the actual seismic source. Interestingly, this method can handle noisy recordings and complex geological settings.

From a theoretical point of view, it requires the receivers to form a closed surface at depth, known as time-reversal mirror. Obviously, this condition cannot be satisfied in practice, but this is not our purpose to discuss the limitation here. Placing ourselves in the ideal framework, we implement a perfect time-reversal mirror to study the effect of the two force terms which generate the backpropagated field. One force-term is the traction at the mirror; the other is a dipole derived from the displacement at the mirror. The implementation of these two terms is performed in SpecFEM2d.

We show that the two force-terms are not necessary to generate the wavefield. With only one, the wavefield still focuses but also moves apart outside the closed surface. This result is encouraging because the traction is difficult to measure in practice.

Speaker(s): Pauline Collon

Date: Thursday 24th of September  2020 - 01:00 pm.


Il y a quelques années nous proposions d'étudier les réseaux kartsiques en les considérant comme des graphes (Collon et al., 2017, dans Geomorphology). Cette approche nous permettait d'étendre les classiques analyses géométriques à des analyses topologiques des réseaux en s'appuyant sur des indicateurs bien connus issus de la théorie des graphes. En effectuant ces calculs sur une 30aine de réseaux réels, nous fournissions ainsi des valeurs de référence et identifions les métriques les plus pertinentes.

Afin de permettre au plus grand nombre d'utiliser ces travaux et d'étendre les gammes de valeurs réalistes, nous avons depuis développé Karstnet : utilisant la bibliothèque NetworkX, ce petit programme python permet en quelques clics d'obtenir une analyse complète d'un réseau karstique tel que nous la proposions dans l'article.
Il est disponible sur Github en open-source avec sa batterie de tests unitaires et ses notebooks.

==> Ce séminaire est donc l'occasion de revenir sur cette recherche en vous (re)présentant les concepts, l'outil, et tout ce qui s'ouvre désormais au développement collaboratif grâce à ce projet.

Speaker(s): Francois Bonneau

Date: Thursday 20th of August, 2:00 pm.


Fracture networks (FN) are systems of complex mechanical discontinuities, which dramatically impact the physical behavior of rocks. Their statistical characterization is an important first step of stochastic modeling. It is, however, a big challenge because field data are sparse and incomplete and present several biases due to sampling (censoring, truncation, orientation).

The present paper concentrates on the statistical analysis of outcrops, which often may be considered as planar sections through three-dimensional FN. For the corresponding planar FN there exist well elaborated statistical methods, which yield first-order characteristics such as fracture density or fracture length distributions. Using ideas from stochastic geometry, in particular the theory of fiber processes and marked point processes, we develop second-order characteristics such as pair correlation function and mark correlation functions, which describe the variability of planar FN and their inner spatial correlations. Surprisingly, one of these characteristics is closely related to characteristics used in statistics of fractals applied to FN.

We demonstrate the application of our ideas by field outcrops already published in the literature.

Speaker(s): Corentin Gouache

Date: Thursday 09th July 2020 - 02:00 pm


Most of the seismic active regions are localised along plate boundaries, thus spatial distribution of earthquakes is also clustered along these boundaries. Moreover with high accumulation rates (>1cm/y) one can expect the area of the next large earthquakes. These findings aren't true for Stable Continental Region (SCR) like French mainland. In these territories, seismic events seem to be uniformly distributed in space. Furthermore, some observations express a dependency behaviour between SCR earthquakes, as in seismic sequences but over hundreds of years. These findings are taken in account into the Generator of Earthquakes for Barely seismic areas.

Speaker(s): Paul Baville & Capucine Legentil

Date: Wednesday 01st July 2020 - 11:00 am


We will briefly present how Bezier interpolator works and its utility to generate chronostratigraphic lines (2D) or surfaces (3D) from well markers (dip and strike data). Once these lines generated, it is possible to extrapolate them using a signed distance function within a 2D meshed model (3D is the next step).

Speaker(s): Guillaume Caumon

Date: Thursday 18th June 2020 – 11:00 am


In this talk, I briefly review some key machine learning principles and report on some recent work using convolutional networks for the structural interpretation of seismic images.