For the engineer with limited experience in using models, these case histories can be helpful. They show that difficulties can arise with cross-section models and with improper relative permeability data and that it's easy to get carried away with your own faked-in input data. But they also show that, properly used, models can be a godsend.
The multicell reservoir simulation models have reached that stage of development at which they are being passed from the hands of the scientists and mathematicians who originated them into the hands of the reservoir engineer for his everyday use. Whereas numerous papers have been published describing the theoretical aspect and mathematical approaches developed for these model, the paper is intended as a look at multicell models from the engineers rather than the scientist's point of view.
Engineers are quickly realizing that these models are the best tool developed in recent years for under standing oil and gas reservoirs and predicting their performance. Modeling a reservoir by dividing it performance. Modeling a reservoir by dividing it into cells provides a flexibility to the engineer that he never had before. High-speed computers permit multiple runs of a reservoir model to test different methods of field operations or to check the sensitivity of reservoir behavior to unknown rock or fluid properties. properties. The multicell models have many valid applications, but they can also be misused because the model is only providing answers that the input data are forcing it to provide. Therefore, a careful analysis and selection of input data is imperative. The engineer can usually obtain representative data on reservoir rock and fluid properties. The greater difficulty lies in properly selecting such items as relative permeability, properly selecting such items as relative permeability, vertical permeability, and cell size.
Stated simply, a multicell model simulates fluid flow in an oil or gas reservoir. Models cannot describe flow exactly as it occurs, but they do give valid approximations. The mathematics of these models requires that the reservoir be treated as if it were composed of many individual segments. These segments are usually called cells, but are also referred to as grids, nodes, mesh points, or a network. Models are made to represent reservoir fluid flow from cell to cell in one, two, or three dimensions and accordingly are termed one-dimensional, two-dimensional, or three-dimensional models. These are illustrated in Figs. 1 through 3.
Each cell is assigned its specific reservoir properties of size, porosity, permeability, elevation, properties of size, porosity, permeability, elevation, pressure, and fluid saturations. In addition to cell pressure, and fluid saturations. In addition to cell properties, well data must also be provided. These properties, well data must also be provided. These include location, productivity index, desired producing or injection rates, and limiting conditions such as economic limit, maximum water cut and GOR, and minimum bottom-hole flowing pressure. General fluid and rock data must also be provided for the entire field or section of field being studied. These usually include PVT data for the oil, gas, and water; rock compressibility; PVT data for the oil, gas, and water; rock compressibility; and relative permeability for each flowing phase. Models using PVT data for oil, gas, and water are frequently referred to as "black-oil models."
JPT
P. 1428
