Soil liquefaction takes place during and/or after the occurrence of an earthquake and is a major contributor to urban seismic risk. Geologists use a technique called the cone penetration test (CPT) to determine the properties of soils, including liquefaction levels, which yields large amounts of soil data. The analysis of such massive amounts of data requires high-performance computing resources. In this paper, we present GQO (Grid Query Optimizer), a distributed algorithm that enables the analysis of large CPT data sets efficiently on a grid cyberinfrastructure.