Computing Structural Difference between GeoChron Models

@inproceedings{TERTOIS_RM2021,
 abstract = { Uncertainty on geological structures is notoriously difficult to assess and model. In the GeoChron framework, it is possible to evaluate each source of uncertainty independently and generate geologically valid and equiprobable realisations of the structure by modelling and integrating the effects of each uncertain component. Statistics can then be gathered on realisations, typically by measuring volumes of geological units of particular interest. Still, it is difficult to assess how much each model deviates from the base case, or from another equiprobable model, and where. Assigning a degree of uncertainty on one particular component in the model may impact the volume of given geological units, but how does considering uncertainty on this component affect the structure as a whole, from one realisation to the next? Even more challenging, when multiple sources of uncertainty are combined in a single set of realisations, what region of the model shows the most variability? Evaluating volumes of geological units is one way to compare structural realisations, but it lacks the spatial definition which would help refine the uncertainty analysis. In this paper, we propose a simple method based on the GeoChron framework to quantify and visualise differences between equiprobable realisations of a structural model. At each point in the geological space, we associate a displacement vector which shows by how much this point differs from the base case, or from another realisation. Given a number of structural realisations, the structural difference vectors highlight which regions of the model differ the most, or remain broadly the same. In an iterative process, this makes it possible to assess the spatial impact of uncertain parameters on structural simulation results, and then to focus the uncertainty analysis on the most meaningful components. Furthermore, considering the spatial distribution of structural difference magnitude relatively to computed geological unit volumes can show which regions in the model have the most impact on final volumes. Ranking realisations according to this magnitude provides an alternative to volumes alone when selecting the most representative structural models to take forward in the reservoir characterisation workflow. Finally, the structural difference vectors can be used as input to time preserving tomography to update the velocity model associated to the base case structure and make it consistent with the structural realisation. },
 author = { Tertois, Anne-Laure },
 booktitle = { 2021 RING Meeting },
 publisher = { ASGA },
 title = { Computing Structural Difference between GeoChron Models },
 year = { 2021 }
}