Key Techniques Of Three-dimensional Dynamic Modeling In Geological Space

Geological space is a three-dimensional space which is nonhomogeneous, nonparametic and non-eyeable. The dynamic modeling of the 3D geological solid in this space is becoming one of the focus problems of 3D spatial information technology research fields, and is also one of the difficult problems in these fields. With the analysis of the geological space attributes, some key problems such as the 3D geospatial cognition, 3D geological solid data structure, the system and methods of 3D geological modeling, the interpolation and fitting algorithms of 3D geological model, the 3D geological solid simplification algorithms and the spatial index, are researched in the paper. The main study contents composed of following items:(1)With concluding and summarizing the geological space attributes, the three basic attributes--nonhomogeneous, nonparametic and non-eyeable, and the mix spatial cognition model of the 3D geological space are presented. Based on this cognition, the extended boundary representation integration model (EBRIM)is presented in this paper.(2)The dynamic modeling methods of 3D geological solid based on borehole, section and disperse points, are studies on. The dynamic modeling algorithm based on continuous borehole stratum series matching is presented. This algorithm includes two main steps. The first is generating the continuous standard stratum dictionary automatically by analyzing and judging the stratums in the research area. The second is doing dynamic matching between borehole and dictionary with guiding by some certain rules. It resolves the dynamic modeling problems in the condition of having fault and stratum annihilating.(3)The dynamic modeling algorithm of 3D geological solid based on noncoplanar section topology reasoning is presented. This algorithm imports the topology reasoning into 3D geological dynamic modeling, realizes the topology reasoning, judging and section corresponding automatically for the four cases: having no topology change, stratum annihilating, stratum bifurcating and fault slippage. Furthermore the automatic reconstruction of 3D geological solid for the 4 cases is implemented.(4)The dynamic reconstruction algorithm based on convex hull cutting and restrictive disperse points division has been presented. This algorithm does interpolation of borehole and section data attached with geological information as boundary restrictive conditions at first. Then the disperse points are classified with the geological age, and the minimums convex hull of each classified points are calculated. Then the convex hulls are sorted by geological age and cutted the adjacent convex hull in sequence, and then the results are divided to receive the 3D geological solid based on EBRI model. The topology relationships are built and the model simplifications are done at last. It resolves the problem that the surface model can not support auto-reconstruction and the solid model can do it, but is not practical because of the huge data.(5)The virtual borehole interpolation algorithm based on TIN and NURBS is presented. It imports the NURBS surface reverse interpolation into this algorithm in order to solve the rough surface problem brought on the virtual borehole interpolation algorithm which only bases on TIN. The virtual section interpolation based on section topology reasoning is presented. This algorithm implements the virtual section auto-generation for the four cases: having no topology change, stratum annihilating, and stratum bifurcating and fault slippage.(6)The n-dimensional general mesh (GM)and the GM simplification (GMS)based on the simplex-collapse are brought out, and implement many kinds of grid general simplification algorithm. The GMS is more effective than the simplification algorithm based on edge-collapse.(7)A new index algorithm named clustering sorting record tree (CSR-Tree),which is not same as R-Tree, packed R-Tree, R+-Tree, R*-Tree, is presented and implemented in the paper. This algorithm includes three main steps. The first step is spatial objects center distance clustering. The second step is sorting the clustering results by scanning X, Y, Z axis, and selecting direction which has the minus sum of the adjacent distance between each two spatial objects. The last step is constructing CSR-Tree recursively. This algorithm reduces the probability of the covering of node boundary rectangle by thinking over the spatial objects'distance relativity, and improves the R-Tree searching efficiency.(8)A Grid+CSR-Tree 3D mix index method named mix grid clustering sorting record tree (MGCSR-Tree)is brought out. This algorithm uses two level index mechanisms to manage huge spatial data, which reduces the memory spending and enhances the index operation efficiency.The algorithms above all has been used in many projects, and obtained good practice effects, and proved these algorithms are valid and practicable.