Origin-Destination surveys, which are regularly conducted in many cities (to calibrate transport models), contain indirect information on individual time use that can be recovered through the declared trip purpose. Although this data source is very rich, it has two limitations for the calibration of time use models: the level of disaggregation regarding time use is constrained by the definition of trip purposes, and the information gathered on different time periods is usually obtained from different individuals. In this paper we propose a new method to overcome the second limitation, transforming the original daily observations into individual-weeks. For every working day observation we build Saturday and Sunday ‘‘twins’’ as a convex combination of observed weekend individuals such that the distance between the attributes of the working day individual and the synthetic twin is minimized. We applied this procedure to the Santiago OD survey, and generated a database of weekly observations particularly rich for model calibration and segmentation.