4D binning is an important processing step to improve the repeatability of time-lapse (4D) data. Binning is a strategy for selecting those traces which are most similar between the timelapse vintages. With two vintages of 4D seismic data the trace similarity is easily obtained, for example, as the difference of the source and the receiver position of the corresponding traces. With more than two vintages, a "cascaded" approach has generally been used, whereby the vintages are binned pair-wise as in the two-vintage case, with each new vintage being binned relative to the previous ones. This does not necessarily yield an optimum solution for multi-vintage datasets and leaves open the debate about which vintage to pick as the reference. In this paper we introduce a simultaneous multi-vintage (SMV) 4D binning algorithm which obtains the best possible repeatability across all vintages and in each bin. We compare SMV 4D binning to cascaded 4D binning on a multi-vintage North Sea survey.