Kring-based Geophysical Data Mesh Of Three-Dimensional Space

Geostatistics is an emerging disciplines which is in the field of mathematicalgeology, it is developing quickly, and has a widely applied prospects. Geostatistics isbased on the theory of regionalized variable, the variogram theory is the basic tool,which is used to study the randomness and structural phenomena that spread in space.Its core is Kriging interpolation, is a reserve estimates which is unbiased and hasminimum variance.With the continuous improvement of geostatistical theory and application, it hasapplied in all aspects of human society. Lots of geophysical methods for datapre-processing often need the three-dimensional data interpolation, to make data grid.Because many algorithms always suit for distribution data, because of theincompleted data or missing data will cause the algorithm can not run or the resultsare unpredictable. Missing data does not just mean loss of some information, but moreimportantly, it will generate a lot of unnecessary noises in a variety of processing, thathave an impact on the resolution and signal to noise ratio.The thesis achieved the Kriging interpolation method on the three-dimensionalgeophysical data grid, strike the variogram, as well as automatic fitting the variogramfunction model of straight line and the spherical. For the model test, first we takeencryption grid processing on uniformly distributed data, which we select the seismicvelocity, uniform pumping dilute eighth of the original data, and then interpolation,the estimation variance is0.6×10-3, the error rate is about1.4%. Second we takeexperience on irregular data, we assume that the theory of potential field model ΔTand superposition of two oblique magnetized sphere, ramdomized simplified secondof the original data, The average value of-0.558485before, after interpolation, theaverage value is-0.560489, the estimated variance is1.7×10-3and the error rate is6.3%. For actual data processing, the thesis selected North China crustal S-waveseismic tomography data, we made up the missing layer and random missing data grid,it has made an underground structure model for the follow-up work.Comparison of multiple examples and practice, we knew that the ordinary kriging is not required for the form of the distribution of known data, and has a highinterpolation accuracy, so it is suitable for geophysical irregularly distributed datagrid.