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[[file:interpreting-seismic-data_fig12-4.png|thumb|{{figure number|1}}Illustration of the bin concept. Copyright: Liner,<ref name=Liner>Liner, C., 1999, Elements of 3-D Seimology: Tulsa, PennWell</ref> courtesy PennWell.]]

[[file:interpreting-seismic-data_fig12-4.png|thumb|{{figure number|1}}Illustration of the bin concept. Copyright: Liner,<ref name=Liner>Liner, C., 1999, Elements of 3-D Seimology: Tulsa, PennWell</ref> courtesy PennWell.]]

For 2-D seismic, the prestack traces are sorted into groups associated with one midpoint on the earth's surface. The 3-D seismic data are sorted into discrete areas called bins. All actual midpoints that fall into the bin area belong to that bin. In effect, a grid is laid over the actual midpoints. Each bin has an in-line and cross-line dimension. The fold of each bin is the number of traces captured by that bin. Through the stacking process, all traces within a bin are summed to create a single stack trace, greatly improving signal quality.

For 2-D seismic data, the [[prestack trace]]s are sorted into groups associated with one midpoint on the earth's surface. The 3-D seismic data are sorted into discrete areas called bins. All actual midpoints that fall into the bin area belong to that bin. In effect, a grid is laid over the actual midpoints. Each bin has an in-line and cross-line dimension. The [[fold]] of each bin is the number of traces captured by that bin. Through the stacking process, all traces within a bin are summed to create a single stack trace, greatly improving signal quality.

[[:file:interpreting-seismic-data_fig12-4.png|Figure 1]] illustrates the bin concept. The actual midpoints for a well-designed and executed survey will show natural clustering (A). On this cloud of midpoints we impose a grid of bins, each bin capturing all traces whose midpoints lie in it (B). After processing (stacking, migration, etc.), there is one trace at the center of each bin (C). These are the poststack data traces we interpret.

[[:file:interpreting-seismic-data_fig12-4.png|Figure 1]] illustrates the bin concept. The actual midpoints for a well-designed and executed survey will show natural clustering (A). On this cloud of midpoints we impose a grid of bins, each bin capturing all traces whose midpoints lie in it (B). After processing (stacking, migration, etc.), there is one trace at the center of each bin (C). These are the poststack data traces we interpret.