In order to deal with the common trend in size increase of volumetric datasets, in the past few years research in isosurface extraction has focused on related aspects such as surface simplification and load-balanced parallel algorithms. We present a parallel, block-wise extension of the tandem algorithm by Attali et al., which simplifies on the fly an isosurface being extracted. Our approach minimizes the overall memory consumption using an adequate block splitting and merging strategy along with the introduction of a component dumping mechanism that drastically reduces the amount of memory needed for particular datasets such as those encountered in geophysics. As soon as detected, surface components are migrated to the disk along with a meta-data index (oriented bounding box, volume, etc.) that permits further improved exploration scenarios (small component removal or particularly oriented component selection for instance). For ease of implementation, we carefully describe a master and worker algorithm architecture that clearly separates the four required basic tasks. We show several results of our parallel algorithm applied on a geophysical dataset of size 7000 × 1600 × 2000.