1. Field of the Invention
The present invention relates to reservoir simulation by computer processing and more particularly to processing data relating to a subsurface reservoir to compress the reservoir simulation grids, and subsequently to decompress the grids for study and analysis of the simulation results.
2. Description of the Related Art
In the oil and gas industries, massive amounts of data are required to be processed for computerized simulation, modeling, and analysis for exploration and production purposes. For example, the development of underground hydrocarbon reservoirs typically includes development and analysis of computer simulation models of the reservoir. A realistic simulation model of the reservoir, and the presence of its fluids, helps in forecasting the optimal future oil and gas recovery from hydrocarbon reservoirs. Oil and gas companies have come to depend on simulation models as an important tool to enhance the ability to exploit a petroleum reserve.
The underground hydrocarbon reservoirs are typically complex rock formations which contain both a petroleum fluid mixture and water. The reservoir fluid content usually exists in two or more fluid phases. The petroleum mixture in reservoir fluids is produced by wells drilled into and completed in these rock formations. Sometimes, fluids such as water and/or gases are also injected into these rock formations to improve the recovery of the petroleum fluids.
Reservoir simulation belongs to the general domain of flow in porous media simulation. However, reservoir simulation normally involves multiple hydrocarbon components and multiple fluid phases in an underground geological formation which is under high pressure and temperature. The chemical phase behavior of these hydrocarbon fluids and the included groundwater has to be taken into account in these simulators.
The simulation models contain volumetric data which describe the specific geometry of the rock formations and the wells, and also reservoir properties data, such as the fluid and rock properties, as well as production and injection history pertaining to the specific reservoirs of the oil or gas field in question. The simulation models are formed by a simulator (known as a reservoir simulator) which is a suite of computer programs run on a data processing system.
The reservoir simulator which runs these models is a computer implemented numerical methodology, or coded algorithms and data constructs of an underlying mathematical model. The mathematical model which represents the physics of fluid movements in these hydrocarbon reservoirs is a system of nonlinear partial differential equations which describe the transient multiple-phase, multiple-component fluid flow, and material balance behaviors in these reservoirs induced by the production and/or injection of fluids, as well as the pressure-volume-temperature (PVT) relationships of the reservoir fluids.
A reservoir simulator simulates the multiphase multicomponent fluid flow and material balance in subterranean reservoirs and the included surrounding porous rock formations by subdividing the volume into contiguous cells, also known as grid blocks. In simulation models, the reservoir is thus organized into a number of individual cells. A cell or grid block is the basic finite volume where the underlying mathematical model is applied. The number of cells varies depends on the resolution needed for the simulation and the size of the reservoirs in question.
For a large reservoir, such as the type known in the industry as a giant reservoir, which may have multi-billion barrels of original oil-in-place (OOIP), the number of grid cells can be in the hundreds of millions to over a billion. This number of cells is required in order to have adequate resolution to represent flow dynamics, formation rock porosity and permeability heterogeneity, and many other geologic and depositional complexities within the reservoir. Simulation of this size reservoir can be termed giga-cell reservoir simulation.
The challenges in hydrocarbon reservoir simulation require the use of the latest technology to maximize recovery in a cost-effective manner. Reservoir simulators such as GigaPOWERS have been described in the literature. See, for example articles by Dogru, A. H. et al., “A Next-Generation Parallel Reservoir Simulator for Giant Reservoirs,” SPE 119272, proceedings of the 2009 SPE Reservoir Simulation Symposium, The Woodlands, Tex., USA, Feb. 2-4, 2009 and by Dogru, A. H., Fung, L. S., Middya, U., Al-Shaalan, T. M., Byer, T., Hoy, H., Hahn, W. A., Al-Zamel, N., Pita, J., Hemanthkumar, K., Mezghani, M., Al-Mana, A., Tan, J, Dreiman, T., Fugl, A, Al-Baiz, A., “New Frontiers in Large Scale Reservoir Simulation,” SPE 142297, Proceedings of the 2011 SPE Reservoir Simulation Symposium, The Woodlands, Tex., USA, Feb. 21-23, 2011. GigaPOWERS reservoir simulation is capable of fine-scale grid simulation that exceeds a billion-cell barrier for post-processing while utilizing hundreds of GB footprint per scenario.
The total number of simulation runs for a company with a number of hydrocarbon reservoirs and appreciable reserves exceeds multiple tens of thousands per year, and one or more petabytes of high performance storage is required to host these data. For full simulation studies, it is required to maintain and store for subsequent use and analysis all of the simulation visualization data that are represented by the hundreds or thousands gigabytes of reservoir simulations.
Consider the case of a single volumetric grid of 10243 grid points (on the order of a billion cells) that is processed by a solver such as GigaPowers. Storing volumetric data alone requires 3 times 10243 floats (4 bytes each) for space coordinates (x, y, z). State of the art data formats would imply a memory space or capacity of 12.88 GB for volumetric data alone.
This memory space for volumetric data coordinates is required without even considering the many other properties attached to each cell as a result of simulation, such as oil saturation, water saturation, etc. Serious maintenance issues arise due to the vast file size, such as time delays for I/O, file disk size limitations, and required support for increasing or expanding the available memory space capacity as petroleum engineers and reservoir analysts generate more simulation data on a continuing basis.
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