Algorithm Development

The use of ion coding at the input to the mass sector to break the trade-off between throughput and resolution, requires accurate mathematical reconstruction to estimate the mass spectrum from the spatial pattern produced at the detector.

An Explicit Forward Model

Thus we have derived a mathematical forward model for our custom built 90-degree magnetic sector system (hereafter referred to as a 90-degree MS) for both 1-D and 2-D coded apertures. Based on some initial known compound measurements, we have calibrated our system forward models such that they correspond to the 90-degree MS. Based on this explicit forward model, we formulate an algorithm to reconstruct mass spectra from ion intensity vs. detector position data measured in our 90-degree MS.

We have measured this ion intensity for a range of concentrations of argon, ethanol, and acetone using spatially coded apertures of varying complexity, and compare the reconstructed spectra with measurements made using a single slit. We have shown that the use of 1-D coded apertures can produce more than an order-of-magnitude increase in throughput and an accompanying increase in SBR with no decrease in instrument resolution.

Algorithms for leak localization will also be developed for this program.

When a potential leak is detected from a central point or “home base," locations at which to sample will be calculated by our algorithms in order to effectively reduce the potential area of the leak location using the algorithms and the data from wind sensors.

Continuous Measurement

The operations protocol is that the CAMMS-ES will routinely survey the well pad, continually acquiring mass spectra. Those measurements will be combined with wind measurements and fed to an inference algorithm that is continually attempting to determine if the measurements are consistent with the presence of leaks.

Once the presence of a leak has been ascertained to within a desired confidence level, the CAMMS-ES will transition to a directed localization mode. In this mode, the inference algorithm will guide the CAMMS-ES to locations on the well pad that are well suited for making measurements that will reduce the leak localization and rate uncertainty. Updated measurements will be employed by the inference algorithm to update the leak model, and the autonomous platform will be redirected to the next most helpful location on the pad.

The goal of the inference algorithm is two-fold:

  • To estimate jointly the locations and flow rates of the leaks described and the background methane profile that together are most consistent with the collected measurements, and
  • Given wind estimates based on the near-term wind history, to predict locations on the well pad that will be well-suited to reducing the uncertainty.