Terrain-based automated detection of well pads and their surroundings

1. A computer-implemented method comprising:

detecting, by a processor and using a first machine learning model, a first well pad at a first location based at least in part on a first set of data comprising spectral data describing a gas emission from the first location;

detecting, by the processor, an environmental event within a threshold distance of the well pad;

determining, by the processor, a probability of damage to the first well pad from the environmental event; and

predicting a suitable location for a second well pad at a second location without a well pad based at least in part on a similarity of a terrain of the second location and the first location and a probability of damage due to the environmental event at the second location.

2. The computer-implemented method of claim 1 , wherein the environmental event is a fire, landslide or flooding.

3. The computer-implemented method of claim 1 further comprising extracting, using a second machine learning model, features from the first set of data to determine the terrain of the location.

4. The computer-implemented method of claim 1 further comprising encoding the data to delineate a boundary of a potential well pad, based at least in part on the terrain.

5. The computer-implemented method of claim 4 , wherein the first machine learning model determines whether the bounded potential well pad is a source of the gas emission.

6. The computer-implemented method of claim 1 further comprising determining an identity, composition and volume of the gas emission and compare emissions with regulatory requirements.

7. A system comprising:

a memory having computer readable instructions; and

one or more processors for executing the computer readable instructions, the computer readable instructions controlling the one or more processors to perform operations comprising:

detecting, using a first machine learning model, a first well pad at a first location based at least in part on a first set of data comprising spectral data describing a gas emission from the first location;

detecting an environmental event within a threshold distance of the well pad;

determining a probability of damage to the first well pad from the environmental event; and

predicting a suitable location for a second well pad at a second location without a well pad based at least in part on a similarity of a terrain of the second location and the first location and a probability of damage due to the environmental event at the second location.

8. The system of claim 7 , wherein the environmental event is a fire, landslide or flooding.

9. The system of claim 7 , the operations further comprising extracting, using a second machine learning model, features from the first set of data to determine the terrain of the location.

10. The system of claim 7 , the operations further comprising encoding the data to delineate a boundary of a potential well pad, based at least in part on the terrain.

11. The system of claim 10 , wherein the first machine learning model determines whether the bounded potential well pad is a source of the gas emission.

12. The system of claim 7 , the operations further comprising determining an identity, composition and volume of the gas emission and compare emissions with regulatory requirements.

13. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations comprising:

detecting, using a first machine learning model, a first well pad at a first location based at least in part on a first set of data comprising spectral data describing a gas emission from the first location;

detecting an environmental event within a threshold distance of the well pad;

determining a probability of damage to the first well pad from the environmental event; and

predicting a suitable location for a second well pad at a second location without a well pad based at least in part on a similarity of a terrain of the second location and the first location and a probability of damage due to the environmental event at the second location.

14. The computer program product of claim 13 , wherein the environmental event is a fire or flooding.

15. The computer program product of claim 13 , the operations further comprising extracting, using a second machine learning model, features from the first set of data to determine the terrain of the location.

16. The computer program product of claim 13 , the operations further comprising encoding the data to delineate a boundary of a potential well pad, based at least in part on the terrain.

17. The computer program product of claim 16 , wherein the first machine learning model determines whether the bounded potential well pad is a source of the gas emission.