Universal Cokriging of Non stationary Spatial Stochastic Process with an Application to Wells Data in Wana District North of Iraq

This paper is concerned with the prediction ofnonstationaryspatial stochastic process by the multivariate approach which is known as universal cokriging.This approach is a generalization of kriging because universal cokriging depends on the underlying variable as well as other variables named as the secondary variables. These variables have a considerable effect on the process of prediction.In this work we obtained the final formulas of the prediction equations system through the derivation of universal cokriging equations in the form of matrices. The obtained universal cokriging equations are quiet similar to the known equations system, and summarise clearly the spatial weights and prediction error variance. The obtained equations system is applied to a real data which represent two variables which areelevation of water(primary variable) and depth of well(secondary variable)in Wana district in Ninavah governorate in north of Iraq.The results obtained are very encouraging, very near to the real values, and with minimum cokriging variance. We compute eight spatial predictions together with error variance of prediction. All algorithms are programmed by Matlab_7.12 package.