THE CONCEPT OF 3D DATA

SAC has facilities for handling a basic type of three-dimensional (3D) data, which are function values evaluated on a regular grid of (X,Y) positions. This type of data can be viewed as evenly sampled in space and fits naturally into SAC file types. The file consists of the string of samples at each grid point, and file header information that flags it as 3D gives the X and Y dimensions of the grid. SAC calls data of this type XYZ.

The simplest visualization of 3D data is map elevation data. Imagine a section of land whose elevation is specified on a grid every 100 m eastwards and 100 m northwards. Over a plot of land 1 km by 1 km, the elevation could be described by a string of 121 values, the first 11 values along the westernmost traverse and the final 11 along the easternmost traverse.

Another type of data that can be represented in 3D is a spectrum as a function of time. If equal lengths of time are cut from a seismogram, the number of points in their FFTs will be the same. If the interval between spectral samples is constant, these values will also form agrid.

A final type of data inherently 3D is a misfit function evaluated over a two-dimensional (2D) grid of points. The misfit minimum within the sampled parameter space yields the optimum combination of parameters that best fit some observations, and the shape of the minimum provides a measure of the joint uncertainty of the parameter estimates.