Abstract: A computer implemented method and system for simulating a hydrocarbon reservoir. The method includes determining a computational reservoir model, comprising formation data and fluid pressure data for each of a plurality of reservoir cells, and forming a tridiagonal matrix system for each of M strongly connected lines and arranging arrays of the M tridiagonal matrix systems in a level-based data layout to be stored in a memory of a graphical processing unit (GPU). The method further includes to determining, with the GPU, an unknown potential array for each of the tridiagonal matrix systems by solving the tridiagonal matrix systems simultaneously using a Thomas method configured to operate with the level-based data layout.

Abstract: A data processing system systems with parallel processors performing simulations by numerical solution of partial differential equations or similar numerical simulations. The data processing system extends the scaling limit of parallel solvers in those numerical simulations by overcoming the frequent network latencies encountered during a simulation. Fewer, yet larger batches of data are exchanged between computing nodes.

Abstract: A data processing system systems with parallel processors performing simulations by numerical solution of partial differential equations or similar numerical simulations. The data processing system extends the scaling limit of parallel solvers in those numerical simulations by overcoming the frequent network latencies encountered during a simulation. Fewer, yet larger batches of data are exchanged between computing nodes.

Abstract: A reservoir simulator forms by parallel processing in a multimode computer system estimates of behavior of a subsurface reservoir organized into a matrix grid of three-dimensional cells. The simulator is provided with a module which acts on input data regarding actual reservoir performance and parameters of interest. A grammar is provided which has a sequence of tokens and actions to be taken by the computer system on the input data. Based on the grammar, the input data are arranged into data structures for processing. The module translates the data structures into a set of arithmetic and logical actions to be applied to the original input data provided to the simulator.

Abstract: Systems, computer implemented methods, and program products to determine approximate static well pressures for one or more arbitrary shaped wells by estimating the drainage volume of the one or more wells, are provided. The drainage volume of the one or more wells, for example, can be estimated from the one or more computed fluid flow flux vectors, and the approximate static well pressures for the one or more wells can be subsequently calculated by taking the pore volume average of the dynamic grid block pressures within the drainage volume of the one or more wells. The one or more fluid flow flux vectors can be calculated at each iteration in a numerical reservoir simulator as a part of standard simulator computations, negating a need for additional, extraneous computations to calculate effective drainage volume of the one or more wells.

Abstract: A reservoir simulator forms by parallel processing in a multimode computer system estimates of behavior of a subsurface reservoir organized into a matrix grid of three-dimensional cells. The simulator is provided with a module which acts on input data regarding actual reservoir performance and parameters of interest. A grammar is provided which has a sequence of tokens and actions to be taken by the computer system on the input data. Based on the grammar, the input data are arranged into data structures for processing. The module translates the data structures into a set of arithmetic and logical actions to be applied to the original input data provided to the simulator.

Abstract: Systems, computer implemented methods, and program products to determine approximate static well pressures for one or more arbitrary shaped wells by estimating the drainage volume of the one or more wells, are provided. The drainage volume of the one or more wells, for example, can be estimated from the one or more computed fluid flow flux vectors, and the approximate static well pressures for the one or more wells can be subsequently calculated by taking the pore volume average of the dynamic grid block pressures within the drainage volume of the one or more wells. The one or more fluid flow flux vectors can be calculated at each iteration in a numerical reservoir simulator as a part of standard simulator computations, negating a need for additional, extraneous computations to calculate effective drainage volume of the one or more wells.

Abstract: A computer-implemented process simulates production of oil and gas from hydrocarbon reservoirs. The process is used to help forecast the optimal future oil and gas recovery from large hydrocarbon reservoirs. At the same, this process is flexible to allow for further addition of new options; robust and reliable; and easy to use. The process is also comprehensive in that it allows a forecast of future performance of a wide range of reservoirs and future operation scenarios. By using the high-resolution models provided, a reservoir can be described much more accurately.

Abstract: A method for enhancing allocation of fluid flow rates among a plurality of wellbores coupled to surface facilities is disclosed. The method includes modeling fluid flow characteristics of the wellbores and reservoirs penetrated by the wellbores. The method includes modeling fluid flow characteristics of the surface facilities. An optimizer adapted to determine an enhanced value of an objective function corresponding to the modeled fluid flow characteristics of the wellbores and the surface facilities is then operated. The objective function relates to at least one production system performance parameter. Fluid flow rates are then allocated according to the optimization.

Abstract: A method for enhancing allocation of fluid flow rates among a plurality of wellbores coupled to surface facilities is disclosed. The method includes modeling fluid flow characteristics of the wellbores and reservoirs penetrated by the wellbores. The method includes modeling fluid flow characteristics of the surface facilities. An optimizer adapted to determine an enhanced value of an objective function corresponding to the modeled fluid flow characteristics of the wellbores and the surface facilities is then operated. The objective function relates to at least one production system performance parameter. Fluid flow rates are then allocated according to the optimization.

Abstract: A method for enhancing allocation of fluid flow rates among a plurality of wellbores coupled to surface facilities is disclosed. The method includes modeling fluid flow characteristics of the wellbores and reservoirs penetrated by the wellbores. The method includes modeling fluid flow characteristics of the surface facilities. An optimizer adapted to determine an enhanced value of an objective function corresponding to the modeled fluid flow characteristics of the wellbores and the surface facilities is then operated. The objective function relates to at least one production system performance parameter. Fluid flow rates are then allocated according to the optimization.

Abstract: A computer-implemented process simulates production of oil and gas from hydrocarbon reservoirs. The process is used to help forecast the optimal future oil and gas recovery from large hydrocarbon reservoirs. At the same, this process is flexible to allow for further addition of new options; robust and reliable; and easy to use. The process is also comprehensive in that it allows a forecast of future performance of a wide range of reservoirs and future operation scenarios. By using the high-resolution models provided, a reservoir can be described much more accurately.

Abstract: A method for enhancing allocation of fluid flow rates among a plurality of wellbores coupled to surface facilities is disclosed. The method includes modeling fluid flow characteristics of the wellbores and reservoirs penetrated by the wellbores. The method includes modeling fluid flow characteristics of the surface facilities. An optimizer adapted to determine an enhanced value of an objective function corresponding to the modeled fluid flow characteristics of the wellbores and the surface facilities is then operated. The objective function relates to at least one production system performance parameter. Fluid flow rates are then allocated according to the optimization.