Edge-preserving gaussian grid smoothing of noise components in subsurface grids to generate geological maps

1. A method of generating geological maps of subsurface formations by implementing edge-preservation and filtering of noise components in subsurface grids, the method comprising:

generating a subsurface grid from geophone sensor data indicating properties of the subsurface formations;

generating, by a seismic mapping engine, a weighting grid that is distinct from the subsurface grid, where generating the weighting grid comprises:

receiving seismic data representing the subsurface formations;

identifying, from the seismic data, seismic attributes that are used to preserve geological discontinuities in the subsurface formations; and

determining, by a weighting module of the seismic mapping engine, a reduced weight that is assigned to grid points of the weighting grid,

wherein the grid points correspond to seismic attributes that indicate the presence of a discontinuity in the subsurface formations;

accessing a compact Gaussian filter weighted by values in the weighting grid;

iteratively computing, by the seismic mapping engine, local averages of grid points in the subsurface grid in response to processing the subsurface grid using the compact Gaussian filter that is weighted by values in the weighting grid;

generating a filtered subsurface grid in response to iteratively computing the local averages of grid points in the subsurface grid, the filtered subsurface grid being distinct from the weighting grid; and

generating a geological map of subsurface formations based on the filtered subsurface grid.

2. The method of claim 1 , wherein iteratively computing local averages of grid points in the subsurface grid using the compact Gaussian filter comprises:

decomposing the compact Gaussian filter into multiple individual filters; and

applying each of the multiple individual filters consecutively to grid points in the subsurface grid that correspond to a discontinuity.

3. The method of claim 2 , wherein iteratively computing local averages of grid points in the subsurface grid comprises:

computing each iteration of a local average using a spatially varying weight function.

4. The method of claim 3 , wherein generating the weighting grid comprises:

varying the weight function based on spatial coordinates of a set of grid points in the subsurface grid; and

generating the weighting grid in response to varying the weight function.

5. The method of claim 2 , wherein applying each of the multiple individual filters consecutively to grid points in the subsurface grid comprises:

generating a respective output grid for each application of an individual filter of the multiple individual filters.

6. The method of claim 5 , further comprising:

providing grid points of the respective output grid generated from a first application of a first individual filter as inputs to a second application of a second individual filter.

7. The method of claim 6 , wherein generating the filtered subsurface grid comprises:

generating the filtered subsurface grid based at least on a respective output grid that is generated from the second application of the second individual filter.

8. The method of claim 1 , wherein generating a weighting grid comprises:

generating a weighting grid that indicates each edge or discontinuity of the subsurface grid to be preserved when filtering a plurality of noise components in the subsurface grid.

9. The method of claim 1 , wherein the compact Gaussian filter is decomposed into four individual filters that are applied consecutively to grid points in the subsurface grid or to grid points of an output grid that corresponds to at least one of the four individual filters.

10. A system for generating geological maps of subsurface formations by implementing edge-preservation and filtering of noise components in subsurface grids, the system comprising one or more processing devices and one or more non-transitory machine-readable storage devices storing instructions that are executable by the one or more processing devices to cause performance of operations comprising:

generating a subsurface grid from geophone sensor data indicating properties of the subsurface formations;

generating, by a seismic mapping engine, a weighting grid that is distinct from the subsurface grid, where generating the weighting grid comprises:

receiving seismic data representing the subsurface formations;

identifying, from the seismic data, seismic attributes that are used to preserve geological discontinuities in the subsurface formations; and

determining, by a weighting module of the seismic mapping engine, a reduced weight that is assigned to grid points of the weighting grid,

wherein the grid points correspond to seismic attributes that indicate the presence of a discontinuity in the subsurface formations;

accessing a compact Gaussian filter weighted by values in the weighting grid;

iteratively computing, by the seismic mapping engine, local averages of grid points in the subsurface grid in response to processing the subsurface grid using the compact Gaussian filter that is weighted by values in the weighting grid;

generating a filtered subsurface grid in response to iteratively computing the local averages of grid points in the subsurface grid, the filtered subsurface grid being distinct from the weighting grid; and

generating a geological map of subsurface formations based on the filtered subsurface grid.

11. The system of claim 10 , wherein iteratively computing local averages of grid points in the subsurface grid using the compact Gaussian filter comprises:

decomposing the compact Gaussian filter into multiple individual filters; and

applying each of the multiple individual filters consecutively to grid points in the subsurface grid that correspond to a discontinuity.

12. The system of claim 11 , wherein iteratively computing local averages of grid points in the subsurface grid comprises:

computing each iteration of a local average using a spatially varying weight function.

13. The system of claim 12 , wherein generating the weighting grid comprises:

varying the weight function based on spatial coordinates of a set of grid points in the subsurface grid; and

generating the weighting grid in response to varying the weight function.

14. The system of claim 11 , wherein applying each of the multiple individual filters consecutively to grid points in the subsurface grid comprises:

generating a respective output grid for each application of an individual filter of the multiple individual filters.

15. The system of claim 14 , wherein the operations further comprise:

providing grid points of the respective output grid generated from a first application of a first individual filter as inputs to a second application of a second individual filter.

16. The system of claim 15 , wherein generating the filtered subsurface grid comprises:

generating the filtered subsurface grid based at least on a respective output grid that is generated from the second application of the second individual filter.

17. The system of claim 10 , wherein generating a weighting grid comprises:

generating a weighting grid that indicates each edge or discontinuity of the subsurface grid to be preserved when filtering a plurality of noise components in the subsurface grid.

18. The system of claim 10 , wherein the compact Gaussian filter is decomposed into four individual filters that are applied consecutively to grid points in the subsurface grid or to grid points of an output grid that corresponds to at least one of the four individual filters.

19. A non-transitory machine-readable storage device storing instructions for generating geological maps of subsurface formations by implementing edge-preservation and filtering of noise components in subsurface grids, the instructions being executable by a processing device to cause performance of operations comprising:

generating a subsurface grid from geophone sensor data indicating properties of the subsurface formations;

generating, by a seismic mapping engine, a weighting grid that is distinct from the subsurface grid, where generating the weighting grid comprises:

receiving seismic data representing the subsurface formations;

identifying, from the seismic data, seismic attributes that are used to preserve geological discontinuities in the subsurface formations; and

determining, by a weighting module of the seismic mapping engine, a reduced weight that is assigned to grid points of the weighting grid,

wherein the grid points correspond to seismic attributes that indicate the presence of a discontinuity in the subsurface formations;

accessing a compact Gaussian filter weighted by values in the weighting grid;

iteratively computing, by the seismic mapping engine, local averages of grid points in the subsurface grid in response to processing the subsurface grid using the compact Gaussian filter that is weighted by values in the weighting grid;

generating a filtered subsurface grid in response to iteratively computing the local averages of grid points in the subsurface grid, the filtered subsurface grid being distinct from the weighting grid; and

generating a geological map of subsurface formations based on the filtered subsurface grid.

20. The machine-readable storage device of claim 19 , wherein iteratively computing local averages of grid points in the subsurface grid using the compact Gaussian filter comprises:

decomposing the compact Gaussian filter into multiple individual filters; and

applying each of the multiple individual filters consecutively to grid points in the subsurface grid that correspond to a discontinuity.