Abstract: A computer-implemented method may include receiving test data representing a cutter/rock interaction for a cutter/rock pair; calibrating an analytical model to represent the cutter/rock interaction mechanism for a cutter/rock pair; applying the calibrated analytical model to expand the test data to form one of a plurality of expanded test datasets; generating a first neural network model, of a plurality of first neural network models, representing cutter/rock interaction between a plurality of cutters of different cutter sizes and a particular rock type, wherein the first neural network is generated using the plurality of expanded test datasets as training input; generating a second neural network model using the plurality of first neural network models as training input, wherein the second neural network model represents non-tested cutter/rock interactions between a plurality of cutters of different cutter sizes and a plurality of rock types.

Abstract: A method for designing a drill bit includes simulating a cutting element cutting a digitized rock sample, storing outputs from the simulating in a digital rock interaction file, modeling the drill bit to have at least one of the cutting element, and using data in the digital rock interaction file to simulate the drill bit in a drilling operation

Abstract: A computer-implemented method may include receiving test data representing a cutter/rock interaction for a cutter/rock pair; calibrating an analytical model to represent the cutter/rock interaction mechanism for a cutter/rock pair; applying the calibrated analytical model to expand the test data to form one of a plurality of expanded test datasets; generating a first neural network model, of a plurality of first neural network models, representing cutter/rock interaction between a plurality of cutters of different cutter sizes and a particular rock type, wherein the first neural network is generated using the plurality of expanded test datasets as training input; generating a second neural network model using the plurality of first neural network models as training input, wherein the second neural network model represents non-tested cutter/rock interactions between a plurality of cutters of different cutter sizes and a plurality of rock types.

Abstract: A method, system and computer program product for inverting boundary conditions for rock mass field in-situ stress computation for a geologic structure are disclosed. According to an embodiment, the current invention includes a method for inverting boundary conditions for rock mass field in-situ stress computation for a geologic structure, the method comprising: considering physical constraint of the geological structure; deriving and solving normal equations of penalized weighted least squares, said normal equations of penalized weighted least squares partially representing said physical constraint of the geological structure; and outputting boundary conditions and reproducing the rock mass field in-situ stress based on the result of said solved normal equations of penalized weighted least squares.

Abstract: A method, system and computer program product for inverting boundary conditions for rock mass field in-situ stress computation for a geologic structure are disclosed. According to an embodiment, the current invention includes a method for inverting boundary conditions for rock mass field in-situ stress computation for a geologic structure, the method comprising: considering physical constraint of the geological structure; deriving and solving normal equations of penalized weighted least squares, said normal equations of penalized weighted least squares partially representing said physical constraint of the geological structure; and outputting boundary conditions and reproducing the rock mass field in-situ stress based on the result of said solved normal equations of penalized weighted least squares.