Abstract: Systems and methods include a geological structure modeling tool for generating a geological facies model for a target well with decision tree-based models. The decision tree-based models use geographic facie class as a target variable and receives an input data set including well log data, core data, and geological facie class labels (e.g., generated by a subject matter expert (SME)). A predictive analytics model using the decision tree-based models generates, based on an input of target well data, the geological facies model to represent underlying geological structures at a candidate location (e.g., for drilling a well) or a section of a subsurface reservoir (e.g., for resource characterization). Vertical context data can be provided to the decision tree-based models and the input data set can be artificially boosted based on geological facies class label occurrences. A well development action is selected for the candidate location based on the geological facies model.

Abstract: An improved method for eliminating reflections from artificial model boundaries encountered in finite-difference acoustic wave propagation computations is based on applying two different boundary conditions at the artificial boundary. In this method one boundary condition generates reflections having the same polarity as the incident acoustic wave, and the other boundary condition generates reflections with opposite polarity. To apply the improved method simply compute both boundary conditions on a small narrow region adjacent the artificial boundary on a separate set of grids and average the two solutions.