1. College of Construction Engineering, Jilin University, Changchun 130026, China;2. State Key Laboratory of Superhard Materials, Jilin University, Changchun 130012, China;3. Key Laboratory of Complex Condition Drilling and Mining Technology of Ministry of Land and Resources, Jilin University, Changchun 130026, China;4. College of Applied Technology, Jilin University, Changchun 130022, China
Abstract:Through the collection of various typed drilling data in the City of Changchun and the surrounding areas, the visualization model of three-dimensional stratum structure in Changchun and the surrounding areas is established by using the software of GMS. The model fits with the actual geology (topography) quite well, clear reflecting the stratum structure of Changchun, by means of the software, the profile situation of any stratum locations could be also observed. The neural network is introduced, by using hole coordinates (x, y, z), the depth of the stratum, and the thickness of the stratum as input, the corresponding geological age and the lithology (in Chinese and English) is able to be accurately predicted. Using the 5-13-5 structure of the BP neural network (single hidden layer), the average relative error of prediction is 11.12% (among them, minimum error is 7.50%, maximum error is 15.71%); using the improved 5-11-7-5 structure of the BP neural network (two hidden layers), the average relative prediction error is 4.64% (among them, minimum error is 3.63%, maximum error is 6.59%), the requirement for forecast accuracy is fully met.
温继伟;;陈晨;;陈宝义;徐克里. 基于GMS的地层三维结构可视化模型及神经网络预测[J]. , 2013, 31(15): 44-51.
WEN Jiwei;;CHEN Chen;;CHEN Baoyi;XU Keli. Visualization Model of the Stratum Three-dimensional Structure Based on GMS and the Prediction of the Neural Network. , 2013, 31(15): 44-51.