PhD. thesis: Automatic recognition of tectono-saliferous structures from geophysical imagery and geological data

The geological structures resulting from the mechanisms of the salt tectonics, especially at the level of the passive continental margins, are known to be of good reservoir of energy resources. The main difficulty is to recognize structures associated. The seismic imagery allows to recognize these forms / structures by interpretation of the signal. This step always requires an interpretation by a structural geologist expert. This leads to very subjective and highly variable renderings. Recently, computer-based methods of machine learning (in particular "deep learning" branch for image analysis) make it possible to automatically extract the relevant characteristics over large amounts of data. These methods can be applied to geoscientific problems and in particular to the automatic recognition of complex geological structures from relevant descriptive variables: eg. geophysical images and geological informations (rock type, formation type, structural elements, ...).

To do this, we propose 1) to compile and manage all existing data to identify geological structures and more particularly salt tectonics associated; (2) to define a predictive model based on built-up examples and deduce main variables (here type of geological structures); (3) to develop / apply the algorithms of automatic shape recognition methods and this on a case of application on one or more basins affected by salt tectonics mechanisms.

The candidate should have one of these profiles:

  • Master degree in Applied Mathematics or Computer Science with a background in Data Science and a strong interest for geology or observational sciences
  • Master degree in Earth Sciences (tectonics or geophysics) with a background in numerical approaches and geological data processing.

Programming skills are essential to carry out the expected digital developments. Knowledge of geological and geophysical data to characterize geological structures is expected. The taste for field geology / field observation will also be appreciated as well as a good capacity for synthesis and writing. The candidate should be motivated by research work. He/she should be autonomous in his/her work and have a rigorous approach of scientific issues. Fluent English is necessary to publish his/her results in international publications.

Please send your application with curriculum vitae, a one-page statement of research interests, Master academic transcript and rank and names and contact details of potential references before 7th June or applied following this link .

Contacts: Christelle Loiselet (; Vincent Labbé ( ) ; Prof. Jean Paul Callot ( )

published: 07 May 2019     Please mention EARTHWORKS when responding to this advertisement.