Title :
An Improved Spatial Clustering for the Optimization of Infill Well Placement in High-Water-Cut Oilfield
Author :
Fan Haijun ; Yao Jun
Author_Institution :
China Pet. Univ., Qingdao, China
Abstract :
A method of infill well placement optimization based on improved k-means spatial clustering is presented, in which the remaining oil distribution from reservoir simulation is studied and converted to cluster data. In addition to the spatial positioin of remaining oil, the water saturation and the faults are also been taken into account in the clustering process so as to determine practical infill well locations. Three new definitions, potential grid, invisible grid, saturation distance are given in the improved clustering. The feasibility of this method is demonstrated in the last through an oilfield example.
Keywords :
hydrocarbon reservoirs; optimisation; pattern clustering; production engineering computing; data clustering; high-water-cut oilfield; improved k-means spatial clustering; infill well locations; infill well placement optimization method; invisible grid; oil distribution; potential grid; reservoir simulation; saturation distance; water saturation; Clustering algorithms; Clustering methods; Economics; Optimization; Permeability; Reservoirs; Spatial databases; K-means; Oil distribution; Spatial Clustering; well placement;
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-1-4577-2120-5
DOI :
10.1109/ISdea.2012.502