Systems and methods for likelihood-based mapping of areas surveyed for gas leaks using mobile survey equipment
In some embodiments, vehicle-based natural gas leak detection methods are used to generate 2-D spatial distributions (heat maps) of gas emission source probabilities and surveyed area locations using measured gas concentrations and associated geospatial (e.g. GPS) locations, wind direction and wind speed, and atmospheric condition data. Bayesian updates are used to incorporate the results of one or more measurement runs into computed spatial distributions. Operating in gas-emission plume space rather than raw concentration data space allows reducing the computational complexity of updating gas emission source probability heat maps. Gas pipeline location data and other external data may be used to determine the heat map data.
1. A non-transitory computer-readable medium encoding instructions which, when executed by a computer system comprising at least one processor, cause the at least one processor to:
identify a prior 2-D surveyed area according to a first set of gas emission survey data resulting from a first mobile measurement run performed by a mobile measurement device along a first measurement path, the first set of gas emission survey data comprising a trajectory of the first measurement path and a first set of associated atmospheric condition data characterizing the first mobile measurement run, wherein the prior 2-D surveyed area comprises a plurality of indicators of whether corresponding locations within the prior 2-D surveyed area have been surveyed following the first mobile measurement run; and
perform a Bayesian update of the prior 2-D surveyed area to generate a posterior 2-D surveyed area according to a second set of gas emission survey data resulting from a second mobile measurement run, the second set of gas emission survey data comprising a second set of associated atmospheric condition data characterizing the second mobile measurement run, wherein the posterior 2-D surveyed area comprises a plurality of indicators of whether corresponding locations within the posterior 2-D surveyed area have been surveyed following the first mobile measurement run and the second measurement run.
2. The computer-readable medium of claim 1 , wherein the instructions further cause the at least one processor to identify the posterior 2-D surveyed area according to an atmospheric transport model employing the second set of associated atmospheric condition data.
3. The computer-readable medium of claim 1 , wherein the instructions further cause the at least one processor to generate display data for displaying a map of the posterior 2-D surveyed area to a user.
4. The computer-readable medium of claim 3 , wherein the map is a heat map.
5. The computer-readable medium of claim 1 , wherein the first set of associated atmospheric condition data comprises a plurality of wind speed and wind direction values acquired along the first measurement path.
6. The computer-readable medium of claim 1 , wherein the second measurement run is performed along a second measurement path different from the first measurement path.
7. A computer system comprising at least one processor configured to:
identify a prior 2-D surveyed area according to a first set of gas emission survey data resulting from a first mobile measurement run performed by a mobile measurement device along a first measurement path, the first set of gas emission survey data comprising a trajectory of the first measurement path and a first set of associated atmospheric condition data characterizing the first mobile measurement run, wherein the prior 2-D surveyed area comprises a plurality of indicators of whether corresponding locations within the prior 2-D surveyed area have been surveyed following the first mobile measurement run; and
perform a Bayesian update of the prior 2-D surveyed area to generate a posterior 2-D surveyed area according to a second set of gas emission survey data resulting from a second mobile measurement run, the second set of gas emission survey data comprising a second set of associated atmospheric condition data characterizing the second mobile measurement run, wherein the posterior 2-D surveyed area comprises a plurality of indicators of whether corresponding locations within the posterior 2-D surveyed area have been surveyed following the first mobile measurement run and the second measurement run.
8. The system of claim 7 , wherein the at least one processor is further configured to identify the posterior 2-D surveyed area according to an atmospheric transport model employing the second set of associated atmospheric condition data.
9. The system of claim 7 , wherein the at least one processor is further configured to generate display data for displaying a map of the posterior 2-D surveyed area to a user.
10. The system of claim 9 , wherein the map is a heat map.
11. The system of claim 7 , wherein the first set of associated atmospheric condition data comprises a plurality of wind speed and wind direction values acquired along the first measurement path.
12. The system of claim 7 , wherein the second measurement run is performed along a second measurement path different from the first measurement path.
13. A method comprising:
collecting a first set of gas emission survey data by conducting a first mobile measurement run using a mobile measurement device traveling along a first measurement path, the first set of gas emission survey data comprising a trajectory of the first measurement path and a first set of associated atmospheric condition data characterizing the first mobile measurement run;
identifying a prior 2-D surveyed area according to the first set of gas emission survey data, wherein the prior 2-D surveyed area comprises a plurality of indicators of whether corresponding locations within the prior 2-D surveyed area have been surveyed following the first mobile measurement run;
collecting a second set of gas emission survey data by conducting a second mobile measurement run, the second set of gas emission survey data comprising a second set of associated atmospheric condition data characterizing the second mobile measurement run; and
performing a Bayesian update of the prior 2-D surveyed area to generate a posterior 2-D surveyed area according to the second set of gas emission survey data, wherein the posterior 2-D surveyed area comprises a plurality of indicators of whether corresponding locations within the posterior 2-D surveyed area have been surveyed following the first mobile measurement run and the second measurement run.
14. The method of claim 13 , further comprising identifying the posterior 2-D surveyed area according to an atmospheric transport model employing the second set of associated atmospheric condition data.
15. The method of claim 13 , further comprising generating display data for displaying a map of the posterior 2-D surveyed area to a user.
16. The method of claim 15 , wherein the map is a heat map.
17. The method of claim 13 , wherein the first set of associated atmospheric condition data comprises a plurality of wind speed and wind direction values acquired along the first measurement path.
18. The method of claim 13 , wherein the second measurement run is performed along a second measurement path different from the first measurement path.