The analytical data of drill holes from the Jiama polymetallic copper deposit exhibit striped distribution. When Cokriging is used for these striped data, the outlying data in the stripe frequently receive higher weights than all other data. This paper first introduced the relevant theory of Cokriging algorithm, then corrected the weight of outlying data in the stripe based on Cokriging algorithm with the purpose of making outlying data receive smaller weights, and finally presented the program of the correction algorithm. With the grade data of Cu in the Jiama ore district obtained in 2012 as an example, the authors calculated Cokriging and Cokriging of weight correction respectively. The results show that the Cokriging of weight correction can achieve the better effect and hence it is important for the modeling of geological properties, reserves estimation and spatial data of the Jiama polymetallic copper deposit in Tibet.