This experiment was conducted on Chardonnay dry white wines from five districts of China. In order to discriminate the different wines in terms of geographical origins, a visualization method was proposed to mining the chemical information of aromatic data. Solid-phase micro-extraction (SPME) followed by GC-MS technique was used to qualify and quantify volatile compounds in sample wines, and odor active values (OAV) of analytes were calculated and redefined. By the algorithm of gray-scale maps, the standardized data matrices were translated into visual aroma fingerprints of sample wines. The results showed that the gray scale maps corresponding to redefined OAV were better to distinguish Chardonnay dry white wines from different regions visually and easily.