Abstract: A method may include obtaining a selection of various user-defined coarsening parameters. The user-defined coarsening parameters may include a predetermined fine-grid region in a geological region of interest and a predetermined cell distance. The method may further include determining an area of interest (AOI) mask for the geological region of interest based on the predetermined fine-grid region. The method may further include determining a geological property mask based on the user-defined coarsening parameters. The geological property mask may correspond to a predetermined geological feature within the predetermined cell distance from the AOI mask. The method may further include generating a coarsened grid model using grid model data and well data for the geological region of interest. The method may further include performing a reservoir simulation of the geological region of interest using the coarsened grid model.

Abstract: A method may include obtaining grid model data regarding a geological region of interest. The method may further include obtaining well data regarding a well in the geological region of interest. The method may further include obtaining a grid model for the geological region of interest based on the grid model data and the well data. The method may further include obtaining a time selection for a look-ahead simulation. The method may further include determining a look-ahead model for the look-ahead simulation based on the grid model data, the well data, and a coarsening function. The method may further include performing the look-ahead simulation using the look-ahead model and the time selection. The method may further include performing a reservoir simulation of the geological region of interest using the grid model and the look-ahead simulation.

Abstract: A method may include obtaining model data for a reservoir region of interest. The model data may include flow property data based on streamlines. The method may further include generating a multilevel coarsening mask describing various coarsening levels that correspond to different flow values among the flow property data. The method may further include generating a coarsened grid model using the model data and the multilevel coarsening mask. The method may further include performing a reservoir simulation of the reservoir region of interest using the coarsened grid model.

Abstract: A method may include generating three-dimensional (3D) reservoir simulation data regarding a subsurface formation. The 3D reservoir simulation data may correspond to a plurality of reservoir properties at a predetermined timestep within a reservoir simulation. The method may include generating a 3D pixel dataset using the 3D reservoir simulation data. Each pixel of the 3D pixel dataset may be determined based on a plurality of reservoir property values. Each pixel of the 3D pixel dataset may include a red value, a green value, and a blue value that corresponds to three different reservoir property values out of the plurality of reservoir property values. The method may include generating a two-dimensional (2D) pixel dataset using the 3D pixel dataset. The 2D pixel dataset may correspond to a single video frame within various video frames.

Abstract: A system and method of simulating fluid flow in a hydrocarbon reservoir is disclosed. The method includes obtaining a coarse grid model of the hydrocarbon reservoir and a trajectory of a wellbore that penetrates the hydrocarbon reservoir, and determining an initial grid geometry surrounding the trajectory. The method further includes constructing a reservoir simulation grid, conformal to the initial grid geometry in a first region in a vicinity of the wellbore and conformal with the coarse grid model in a second region more distant from the wellbore than the first region, and performing a hydrocarbon reservoir simulation, modeling a flow of fluid in the hydrocarbon reservoir based, at least in part, on the reservoir simulation grid.

Abstract: A method may include obtaining a selection of various user-defined coarsening parameters. The user-defined coarsening parameters may include a predetermined fine-grid region in a geological region of interest and a predetermined cell distance. The method may further include determining an area of interest (AOI) mask for the geological region of interest based on the predetermined fine-grid region. The method may further include determining a geological property mask based on the user-defined coarsening parameters. The geological property mask may correspond to a predetermined geological feature within the predetermined cell distance from the AOI mask. The method may further include generating a coarsened grid model using grid model data and well data for the geological region of interest. The method may further include performing a reservoir simulation of the geological region of interest using the coarsened grid model.

Abstract: A method may include obtaining well activity data regarding various wells in a reservoir region of interest. The method may further include determining a predetermined well assignment for various parallel processing stages using a bin-packing problem algorithm and the well activity data. The predetermined well assignment may assign the wells to the parallel processing stages. A respective parallel processing stage among the parallel processing stages may perform a portion of a reservoir simulation using a respective computer processor and a well among the wells. The method may further include simulating the reservoir region of interest based on the wells being simulated according the predetermined well assignment for the parallel processing stages.

Abstract: A method may include obtaining a property mask based on model data for a reservoir region of interest. The method may further include adjusting a grid region within the property mask to produce an expanded grid region. The method may further include performing an edge smoothing operation to the expanded grid region to produce a smoothed grid region. The method may further include generating a coarsened grid model using the model data, a lookup operation, and an adjusted property mask including the smoothed grid region. The method may further include performing a reservoir simulation of the reservoir region of interest using the coarsened grid model.

Abstract: A method may include obtaining model data for a reservoir region of interest. The model data may include flow property data based on streamlines. The method may further include generating a multilevel coarsening mask describing various coarsening levels that correspond to different flow values among the flow property data. The method may further include generating a coarsened grid model using the model data and the multilevel coarsening mask. The method may further include performing a reservoir simulation of the reservoir region of interest using the coarsened grid model.

Abstract: A method may include generating three-dimensional (3D) reservoir simulation data regarding a subsurface formation. The 3D reservoir simulation data may correspond to a plurality of reservoir properties at a predetermined timestep within a reservoir simulation. The method may include generating a 3D pixel dataset using the 3D reservoir simulation data. Each pixel of the 3D pixel dataset may be determined based on a plurality of reservoir property values. Each pixel of the 3D pixel dataset may include a red value, a green value, and a blue value that corresponds to three different reservoir property values out of the plurality of reservoir property values. The method may include generating a two-dimensional (2D) pixel dataset using the 3D pixel dataset. The 2D pixel dataset may correspond to a single video frame within various video frames.

Abstract: A method may include obtaining well activity data regarding various wells in a reservoir region of interest. The method may further include determining a predetermined well assignment for various parallel processing stages using a bin-packing problem algorithm and the well activity data. The predetermined well assignment may assign the wells to the parallel processing stages. A respective parallel processing stage among the parallel processing stages may perform a portion of a reservoir simulation using a respective computer processor and a well among the wells. The method may further include simulating the reservoir region of interest based on the wells being simulated according the predetermined well assignment for the parallel processing stages.

Abstract: Embodiments provide a method for surveying a hydrocarbon reservoir utilizing a reservoir model. The method includes the step of establishing an ensemble of models reflecting attributes of the hydrocarbon reservoir based on the reservoir model in its present state. The method includes the step of updating the reservoir model by utilizing a volumetric density image of the hydrocarbon reservoir. The volumetric density image can be constructed via muon tomography.

Abstract: Embodiments provide a method for surveying a hydrocarbon reservoir utilizing a reservoir model. The method includes the step of establishing an ensemble of models reflecting attributes of the hydrocarbon reservoir based on the reservoir model in its present state. The method includes the step of updating the reservoir model by utilizing a volumetric density image of the hydrocarbon reservoir. The volumetric density image can be constructed via muon tomography.