Abstract:
A computer-based method of conditioning reservoir model data includes performing a modeling process within a 3D stratigraphic grid to generate an initial model including one or more facies objects within the model volume, the modeling process including parametric distributions, initial and boundary conditions as well as depositional and erosional events to define the facies objects within the model volume. The mismatch between this initial model and the conditioning well data and potential input trend model is applied to compute a locally variable constraint model. The method further includes executing a multiple point statistics simulation with this constraint model that varies between completely constrained by the initial model at locations where the initial model is consistent with known well data and potential input trend models, and unconstrained by the initial model at locations where the initial model does not match known well data or potential input trend models to allow conformance to the known data.
Abstract:
Methods and systems for trend modeling of subsurface properties are disclosed. One method includes defining a stratigraphic grid of a subsurface volume, the stratigraphic grid including a plurality of columns and a plurality of layers. The method further includes determining, for each layer or column, an initial average property value based at least in part on well data in the subsurface volume and a confidence interval around that initial average property value defining a range of likely values for a target average property value. The method also includes receiving one or more user-defined edits to the initial average property value in one or more of the layers or columns, the one or more edits resulting in the modeled target average property value, and determining whether the modeled target average property value falls within the confidence interval.