Flattening with geological constraints
Jesse Lomask, Antoine Guitton · 2006
In areas with faults and poor signal/noise ratio, where reflectors can be discontinuous from place to place, a dip-based flattening technique might not be able to appropriately track sedimentary layers. To aid the flattening algorithms, one or a few reflectors can be picked. This information can be then incorporated in our algorithms as geological constraints. In a first method, we add a model mask to a time domain solution using a Gauss-Newton approach that incorporates an initial solution. In a second method, we set the lower and upper bounds of a constrained optimization algorithm called limited memory BFGS with bounds (L-BFGS-B). Having incorporated the geological information, the flattening algorithms can accurately pick reflectors in 3D for a noisy field data example. This method is also able to pick across faults requiring a minimal amount of interpretation. Preliminary performance tests indicate that the Gauss-Newton method converges faster than the L-BFGS-B method.