A computer-implemented method for modeling a three-dimensional ("3D") geological structure, which method comprises: selecting (102, 104) input data containing structural information of the geological structure including an image of the geological structure; digitizing the image of the geological structure, the digitized image comprising multiple sample points; processing the digitized image using intelligent point densification, which densification only initializes and optimizes a sample point location, the initializing taking place by filling a space spanned by the digitized image with a pseudo-regular lattice of points, where a nominal distance between the sample point and its nearest neighbors varies consistently with the density of structural features in the digitized image, and the optimizing taking place by moving the points within the space to minimize a total potential energy, defined to be a weighted sum of a point potential energy for each sample point and a potential energy for the digitized image; calculating a structure and diffusion tensor field for the digitized image, each tensor for the tensor field being linked with a respective sample point at an optimized sample point location for the respective sample point and each tensor being constructed to have eigenvectors following a local orientation of the digitized image; processing the digitized image to form an enhanced image, which processing uses structure-oriented smoothing along structures apparent in the digitized image, which structures were calculated in the form of the structure and the diffusion tensor field; calculating a fault displacement field for the digitized image using a computer processor, which fault displacement field is merged with the calculated structure and diffusion tensor field and the processed, structure-oriented-smoothed, digitized image; and interpolating the merged calculated fault displacement field, calculated structure and diffusion tensor field and processed, structure-oriented-smoothed, digitized image to produce a 3D geological model. selecting (102, 104) input data containing structural information of the geological structure including an image of the geological structure; digitizing the image of the geological structure, the digitized image comprising multiple sample points; processing the digitized image using intelligent point densification, which densification only initializes and optimizes a sample point location, the initializing taking place by filling a space spanned by the digitized image with a pseudo-regular lattice of points, where a nominal distance between the sample point and its nearest neighbors varies consistently with the density of structural features in the digitized image, and the optimizing taking place by moving the points within the space to minimize a total potential energy, defined to be a weighted sum of a point potential energy for each sample point and a potential energy for the digitized image; calculating a structure and diffusion tensor field for the digitized image, each tensor for the tensor field being linked with a respective sample point at an optimized sample point location for the respective sample point and each tensor being constructed to have eigenvectors following a local orientation of the digitized image; processing the digitized image to form an enhanced image, which processing uses structure-oriented smoothing along structures apparent in the digitized image, which structures were calculated in the form of the structure and the diffusion tensor field; calculating a fault displacement field for the digitized image using a computer processor, which fault displacement field is merged with the calculated structure and diffusion tensor field and the processed, structure-oriented-smoothed, digitized image; and interpolating the merged calculated fault displacement field, calculated structure and diffusion tensor field and processed, structure-oriented-smoothed, digitized image to produce a 3D geological model.