In elastography, we want to image the entire range of stiffnesses of the elastic components found in inhomogeneous tissues. In order to achieve this, the elastographic dynamic range should equal the entire stiffness dynamic range in the target. Various sources of noise limit the dynamic range of elastography. The recently-defined strain filter concept offers an analytical and graphical way of observing these limitations. In this paper, we describe a method that achieves the expansion of the elastographic dynamic range. It involves the application of variable strains in combination with selective storage of strain data that have optimal elastographic signal-to-noise ratios. This expands the current dynamic range of elastography by orders of magnitude when compared to single compression elastography. The process is explained theoretically using the strain filter framework, and 1 D as well as 2D tissue simulations are used to corroborate the theory.