Subsurface models are essential to build knowledge and support decisions about natural resource and hazard management, but they can be affected by large uncertainties due to the lack and incompleteness of subsurface data. We perform Research for Integrative Numerical Geology to better account for geological concepts in interpretation of geoscientific data and to sample and reduce the associated uncertainties. Our ultimate objective is to effectively describe geological objects with evolving and adaptative numerical models, integrating geometry and physics at various space and time scales, with real-time updates. This translates into novel technologies to efficiently represent, build, update and ask questions to deterministic and stochastic subsurface models.

Our research primarily focuses on the geometry, topology and properties of geological objects. It is declined into four main research areas:

  • Stochastic structural and stratigraphic modeling: The goal is to capture the main uncertainties in the interpretation of tectonic and stratigraphic structures by combining data and ancillary conceptual and regional knowledge. We see this research as an essential component of geomodels because fractures, faults and folds exert a tremendous control on subsurface heterogeneities.
  • Stochastic sedimentary and diagenetic objects description: The goal is to describe or simulate geological objects created by depositional and diagenetic processes consistently with observations and genetic or pseudo-genetic concepts. Such realistic descriptions are important to capture the spatial structures of hydrodynamic and mechanical heterogeneities.
  • Adaptive gridding and scale management: The goal is to establish simple links between geological models and the physical processes involved in several indirect subsurface measurements (e.g., reservoir production, deformations, waveforms, gravity anomalies, etc). Controlling the level of detail and consistently simplifying the geomodel is essential to ensure efficient and accurate physical computations such as flow simulation.
  • Physical processes: We investigate the relations between geological structures and the physical processes in the subsurface (mechanical evolution, wave propagation, flow). This research concerns the past and current geometry and physical state of the subsurface, and has implications for optimizing natural resource management and reducting geological uncertainties by solving inverse problems.