A5032889367- Geological Modeling and Analysis
- Reservoir Engineering and Simulation Methods
- Seismic Imaging and Inversion Techniques
- Geological formations and processes
- Geochemistry and Geologic Mapping
- Hydrocarbon exploration and reservoir analysis
- Computational Geometry and Mesh Generation
- 3D Modeling in Geospatial Applications
- Computer Graphics and Visualization Techniques
- Drilling and Well Engineering
- Hydraulic Fracturing and Reservoir Analysis
- 3D Surveying and Cultural Heritage
- Soil Geostatistics and Mapping
- Image Processing and 3D Reconstruction
- Methane Hydrates and Related Phenomena
- Enhanced Oil Recovery Techniques
- Groundwater flow and contamination studies
- 3D Shape Modeling and Analysis
- Time Series Analysis and Forecasting
- CO2 Sequestration and Geologic Interactions
- Geophysical and Geoelectrical Methods
- Geographic Information Systems Studies
- Landslides and related hazards
- Advanced Numerical Methods in Computational Mathematics
- Geology and Paleoclimatology Research
Centre National de la Recherche Scientifique
2014-2024
Université de Lorraine
2015-2024
École Nationale Supérieure des Mines de Nancy
2015-2024
Institut Universitaire de France
2024
GeoRessources
2018-2024
Monash University
2024
Colorado School of Mines
2016
Institut National Polytechnique de Lorraine
2009-2015
Centre National pour la Recherche Scientifique et Technique (CNRST)
2010-2015
Institut National Polytechnique de Toulouse
2009-2015
Seismic structural interpretation involves highlighting and extracting faults horizons that are apparent as geometric features in a seismic image. Although image processing methods have been proposed to automate fault horizon interpretation, each of which today still requires significant human effort. We improve automatic images by using convolutional neural networks (CNNs) recently shown excellent performances detecting useful objects. The main limitation applying CNNs is the preparation...
Remote sensing data provide significant information to constrain the geometry of geological structures at depth. However, use intraformational geomorphologic features such as flatirons and incised valleys often calls for tedious user interaction during 3-D model building. We propose a new method generate models stratigraphic formations, based primarily on remote images digital elevation models. This is interpretations main relief markers interpolation property tetahedral mesh covering domain...
A wide class of numerical methods needs to solve a linear system, where the matrix pattern non-zero coefficients can be arbitrary. These problems greatly benefit from highly multithreaded computational power and large memory bandwidth available on graphics processor units (GPUs), especially since dedicated general purpose APIs such as close-to-metal (CTM) (AMD–ATI) compute unified device architecture (CUDA) (NVIDIA) have appeared. CUDA even provides BLAS implementation, but only for dense...
Abstract. We propose and evaluate methods for the integration of automatic implicit geological modelling into geophysical (potential field) inversion process. The objective is to enforce structural realism consider observations in a level set inversion, which inverts location boundaries between rock units. two approaches. In first approach, correction term applied at each iteration reduce inconsistencies. This achieved by integrating an scheme within second we use derive dynamic prior model...
This paper introduces a stochastic structural modelling method that honours interpretations of both faults and stratigraphic horizons on maps cross-sections in conjunction with prior information, such as fault orientation statistical size–displacement relationships. The generated models sample not only geometric uncertainty but also topological about the network. Faults are simulated sequentially; at each step, traces randomly chosen to constrain surface order obtain consistent geometry...