thomas laverne

I have a background in mathematical modeling for fluid and solid mechanic. I've spent the last 18 years in the Oil and Gas industry, developping innovative software solutions (C++) for structural modeling in complex environements: - Mechanical FEM engine for Dynel2D/Dynel3D (Augmented Lagrangian, SQP solver, non-linear finite large deformations, sliding contacts ang geological constraints) - Fault modeling engine for Petrel Structural Geology (fault parameterization, mesh generation, conformable distorsion minimizing regularization, fault truncations, fault QC,...) -Embedded discontinuies cartesian mesh for efficient simulation in a complex, fractured environment. - HPC Solvers (Two Levels Domain Decomposition Additive Schwartz method) for various subsurface applications linked to Petrel Structural geology plugins (SR2D, VBM) - DepoSpace engine (creating a virtual depostional space using non-linear elasticity, used for the generation of Reservoir Simulation Grid: DepoGrid) - Computing implicit representation of subsurface structures for SR2D (least-square sparse solvers, biharmonic equations) - Efficient solvers for sparse least-square systems based on a sparse QR decomposition - QC manager algorithms to inspect the validity of the fault model - Machine Learning approaches to build suggestion algorithm for faults relationships I have created and improved algorithms for building subsurface structural models and structural restoration, in an exceptional team in charge of the structural modeling workflow for Petrel, the leading Exploration and Production software from Schlumberger. The purpose of my job is to generate a representation of the underground structures, based on the different data available (seismic surveys, well logs, geoscientists interpretations...). The subsurface structure can be very complex, and data are sometime not very good (sparse, noisy, inconsistent), therefore it can be very challenging, and requires complex machine-human interactions. Beside my day to day work, I have a strong interest in many fields such as hypersonic and non-equilibrium flows simulation, graph-based preconditioning, machine learning and quantum computing.