Stochastic seismic interpretation of salt bodies: detection, sampling and impact on seismic imaging

@phdthesis{clausolles:tel-03284830,
 abstract = {Building a numerical 3D model of the subsurface requires to integrate sparse and ambiguous data. Due to salt tectonics specificities, salt bodies have complex shapes and may present topological singularities. Modeling their geometries is, therefore, difficult, but important as they introduce large physical property contrasts in the subsurface. Seismic imaging is commonly used to map salt and get information about its geometry. Nevertheless, building a seismic image is a long and iterative process, which requires numerous interpretation phases. These interpretations are prone to uncertainties, stemming from the limits of data acquisition and resolution and the assumptions underlying their processing. These uncertainties propagate through the imaging process and impact our understanding and models of the subsurface. Taking them into account is, therefore, crucial during seismic interpretation and requires to be done automatically given the iterative nature of seismic imaging. In this thesis, I am interested in the assessment of structural uncertainties related to the interpretation of ambiguous seismic images of salt tectonics environments. The main contribution of this thesis is a numerical method for stochastically modeling variable shapes of salt bodies and their connectivity. The modeling is based on an a priori definition of the uncertainties, represented as a buffer zone encompassing the salt boundary. The boundary is defined as the combination of a reference scalar field, computed from the buffer zone, and a spatially correlated random field that is used as a perturbation. This implicit formulation allows for the simulation of both varying salt geometries and topologies while ensuring the validity of the simulated boundaries. When the simulated diapir is a bulb detached from its pedestal, a weld is simulated to connect them. The position of the weld is determined from the scalar field representing the salt boundary, to ensure its consistency with the simulated salt bodies. The method is automatic and proposes to integrate punctual information (e.g., well data or manual seismic picks) and, to some extent, prior geological knowledge. The second contribution of this thesis is an application of this method to the characterization of structural uncertainties underlying seismic imaging on a 2D synthetic data set. Starting from a rough buffer zone, I simulate a set of possible interpretations of the salt boundary. I use these interpretations to define a set of equiprobable migration velocity models, that are used in turn to generate as many seismic images. The statistical analysis of this image set, both directly and from derived seismic attributes, permits to highlight the image parts which are most sensitive to migration velocity variations, and provides insights on the nature of the imaged salt bodies. These contributions open new perspectives for uncertainty quantification in an automatic velocity model updating framework in seismic imaging.},
 author = {Clausolles, Nicolas},
 hal_id = {tel-03284830},
 hal_version = {v1},
 keywords = {3D geomodeling ; Uncertainty quantification ; Seismic interpretation ; Salt tectonics ; G{\'e}omod{\'e}lisation 3D ; Quantification des incertitudes ; Interpr{\'e}tation sismique ; Tectonique salif{\`e}re},
 month = {March},
 number = {2020LORR0280},
 pdf = {https://hal.univ-lorraine.fr/tel-03284830v1/file/DDOC_T_2020_0280_CLAUSOLLES.pdf},
 school = {{Universit{\'e} de Lorraine}},
 title = {{Stochastic seismic interpretation of salt bodies: detection, sampling and impact on seismic imaging}},
 type = {Theses},
 url = {https://hal.univ-lorraine.fr/tel-03284830},
 year = {2020}
}