Summary The proposed low cost 4D QI workflow using Machine Learning fills the gap between qualitative interpretation of 4D attribute maps and 4D probabilistic inversion of seismic wiggles, thus enabling the rapid quantification of reservoir property changes. This workflow has been applied in several deepwater fields with multiple 4D acquisitions. The estimated water saturation changes have been used to provide key geophysical input to analyze injection efficiency, support the water flood optimization and infill drilling, especially meeting the deadline of business decision making.