Accuracy of simulated permeability can be improved using soft data during the process of simulation. Integrating soft data with hard data, a method based on COSISIM （sequential indicator cosimulation） was proposed t...Accuracy of simulated permeability can be improved using soft data during the process of simulation. Integrating soft data with hard data, a method based on COSISIM （sequential indicator cosimulation） was proposed to reconstruct permeability. The algorithm COSISIM extends the SISIM （sequential indicator simulation） algorithm to handle secondary data. At the difference of SISIM, data must already be an indicator-coded prior to using COSISIM. The soft data were integrated with hard data using the Markov-Bayes algorithm and must be coded into indicators before they are used. This method was tested on a regional simulation of permeability. The simulated results and the original distribution of permeability were compared. The experimental results demonstrate that this method is practical.展开更多
基金Supported by the National Natural Science Foundation of China（50874005）
文摘Accuracy of simulated permeability can be improved using soft data during the process of simulation. Integrating soft data with hard data, a method based on COSISIM （sequential indicator cosimulation） was proposed to reconstruct permeability. The algorithm COSISIM extends the SISIM （sequential indicator simulation） algorithm to handle secondary data. At the difference of SISIM, data must already be an indicator-coded prior to using COSISIM. The soft data were integrated with hard data using the Markov-Bayes algorithm and must be coded into indicators before they are used. This method was tested on a regional simulation of permeability. The simulated results and the original distribution of permeability were compared. The experimental results demonstrate that this method is practical.
