Uncertainty assessment of 3D geological models based on spatial diffusion and merging model

Abstract The geological model plays an important role in geophysics and engineering geology. data source of modeling comes from interpretation data, borehole outcrop data. Due to economic technical limitations, it is impossible obtain highly accurate high-density sources. sparsity inaccuracy sources lead the uncertainty models. Unlike problem probability, there not enough samples for a model. Spatial diffusion merging are introduced, which more satisfied with cognition than existing methods. And then, using conditional information entropy, quantification method uncertainty, proposed. Compared approaches this took full account constraints laws. Based on models framework assessment established. It necessary our create multiple models, time-consuming laborious task. application Hashan survey located at north China shows that study reasonable effective.