Abstract: Computer-implemented systems and methods for modeling behavior of at least one fluid in a reservoir are disclosed. The techniques can include obtaining measurements of physical parameters, including pressure, at locations within the reservoir, and discretizing, based on a three-dimensional fine grid, a system of partial differential mass balance equations that model, based on the measurements, at least the physical parameters at the locations within the reservoir, such that a system of nonlinear equations is produced. The techniques can include iterating from a current time step to a next time step, such that a solution to the system of nonlinear equations for a time interval that includes the current time step and the next time step is produced. The iterating can include an adaptive multi-fidelity multiscale technique that employs multiple restriction operators, prolongation operators, and coarse grids, to model various computationally challenging reservoir features, behaviors, or both.

Abstract: Computer-implemented systems and methods for modeling behavior of at least one fluid in a reservoir are disclosed. The techniques can include obtaining measurements of physical parameters, including pressure, at locations within the reservoir, and discretizing, based on a three-dimensional fine grid, a system of partial differential mass balance equations that model, based on the measurements, at least the physical parameters at the locations within the reservoir, such that a system of nonlinear equations is produced. The techniques can include iterating from a current time step to a next time step, such that a solution to the system of nonlinear equations for a time interval that includes the current time step and the next time step is produced. The iterating can include an adaptive multi-fidelity multiscale technique that employs multiple restriction operators, prolongation operators, and coarse grids, to model various computationally challenging reservoir features, behaviors, or both.

Abstract: The invention describes a method to convert geological response data to graphical raw data by using at least one stream processor for this purpose. The geological response data is pre-processed by a CPU and the preprocessed geological response data is fed into one or more stream processors. The stream processor then does the calculation intensive work on the preprocessed geological response data and returns the processing results back to the CPU which does some post-processing on the results coming from the stream processor Stream processors comprise single or multiple programmable GPUs, clusters/networks of nodes with one or several GPU's; cell processors (or processors derived from it) or a cluster of cell processor nodes, game computers (in the spirit of Sony's PlayStation, Nintendo's GameCube, etc.) or clusters of game computers.