Box counting enhanced modeling

Abstract

A method can include providing spatial data for a base case of a subsurface geologic formation; providing spatial data for a simulation case of the subsurface geologic formation; performing box counting for the spatial data for the base case; performing box counting for the spatial data for the simulation case; based on the box counting for the spatial data for the base case, determining a fractal dimension for the base case; based on the box counting for the spatial data for the simulation case, determining a fractal dimension for the simulation case; comparing the simulation case to the base case based at least in part on the fractal dimensions; and, based on the comparing, adjusting one or more simulation parameters to generate spatial data for an additional simulation case of the subsurface geologic formation. Various other apparatuses, systems, methods, etc., are also disclosed.

1 - 12 . (canceled) 
     
     
         13 . One or more non-transitory computer-readable media comprising processor-executable instructions to instruct a computing system to:
 receive a parameter value for a base case;   perform box counting on generated test cases to determine a parameter value for each of the test cases;   select an optimal test case from the generated test cases based on a comparison of the parameter values of the test cases and the parameter value of the base case;   decide whether a difference between the parameter value of the selected optimal test case and the parameter value of the base case exceeds an error limit;   adjust one or more generation parameters if the difference exceeds the error limit; and   generate additional test cases based on one or more adjusted generation parameters.   
     
     
         14 . The one or more computer-readable media of  claim 13  wherein the test cases comprise synthetic seismograms. 
     
     
         15 . The one or more computer-readable media of  claim 13  wherein the parameter value comprises a fractal dimension. 
     
     
         16 . One or more non-transitory computer-readable media comprising processor-executable instructions to instruct a computing system to:
 receive a data set;   perform a feature extraction process on the provided data set to generate test cases;   perform box counting on the generated test cases to determine a parameter value for each of the test cases; and   select an optimal test case from the test cases based on a comparison of the parameter values of the test cases.   
     
     
         17 . The one or more computer-readable media of  claim 16  further comprising instructions to instruct a computing system to provide a parameter value for an optimal case to aid in selection of an optimal test case. 
     
     
         18 . The one or more computer-readable media of  claim 16  wherein the feature extraction process comprises ant tracking. 
     
     
         19 . The one or more computer-readable media of  claim 16  wherein the feature extraction process comprises data enhancement prior to feature extraction. 
     
     
         20 . The one or more computer-readable media of  claim 16  further comprising instructions to instruct a computing system to determine another parameter value for each of the test cases and to render a two-dimensional plot of the two parameters to a display. 
     
     
         21 . A method comprising:
 receiving a parameter value for a base case;   performing, using a processor, box counting on generated test cases to determine a parameter value for each of the test cases;   selecting an optimal test case from the generated test cases based on a comparison of the parameter values of the test cases and the parameter value of the base case;   determining whether a difference between the parameter value of the selected optimal test case and the parameter value of the base case exceeds an error limit;   adjusting one or more generation parameters when the difference exceeds the error limit; and   generating additional test cases based on one or more adjusted generation parameters.   
     
     
         22 . The method of  claim 21  wherein the test cases comprise synthetic seismograms. 
     
     
         23 . The method of  claim 21  wherein the parameter value comprises a fractal dimension. 
     
     
         24 . A method, comprising:
 receiving a data set;   performing a feature extraction process on the provided data set to generate test cases;   performing box counting on the generated test cases to determine a parameter value for each of the test cases; and   selecting, using a processor, an optimal test case from the test cases based on a comparison of the parameter values of the test cases.   
     
     
         25 . The method of  claim 24  further comprising determining a parameter value for an optimal case to aid in selection of an optimal test case. 
     
     
         26 . The method of  claim 24  wherein the feature extraction process comprises ant tracking. 
     
     
         27 . The method of  claim 24  wherein the feature extraction process comprises data enhancement prior to feature extraction. 
     
     
         28 . The method of  claim 24  further comprising determining another parameter value for each of the test cases and to render a two-dimensional plot of the two parameters to a display.