The following input data are the unknown, to be determined model parameters which should be optimized using the inverse modelling:
Permeabilities:
In a 3D model the horizontal (KWER) and vertical (KWEV) K-values can be optimized simultaneously. It is possible to optimize the horizontal K-values and simultaneously hold the vertical K-values constant or the other way round.
In these cases, there is no way to influence the anisotropy factor between horizontal and vertical K-values. However, it is possible to optimize the horizontal K-values and hold the ratio between horizontal and vertical K-values constant by entering KFVH (Attributes 
Special Features Adjust factor vertical/horizontal K-value (KFVH) …, default: global KFVH = 0.1).
Special Features Adjust factor vertical/horizontal K-value (KFVH) …, default: global KFVH = 0.1).Storage coefficients:
The storage coefficient (attribute KSPE) in a horizontal model or the porosity (PORO) for calculating the storage coefficient in 3D or vertical models can be optimized (see explanations to the storage coefficient in chapter: “Transient calculation“).
Leakage coefficients:
The leakage coefficients for polylines (attribute LERA, per m) can be optimized.
About these parameters p, there is usually prior knowledge, for example in the form of laboratory tests, or interpretations of field tests or subjective preliminary estimations. The starting values for the iteration of the inverse problem are based on this previous knowledge.
They must be defined for an optimization in a separate file. This file is mentioned in the following as “parameter file”. The structure of the parameter file is described in chapter: "Realization in SPRING".
Observation data and measured data