T012-0001
Satellite-based monitoring of fluid fluxes within the Earth: The importance of regularization and source constraints
Satellite-based monitoring of fluid fluxes within the Earth: The importance of regularization and source constraints
Tuesday, 8 December 2020
Poster
Abstract:
Geodetic data, such as observations of InSAR range change, suffer from a significant loss of resolution with depth.
One approach to mitigate this issue is to adopt simplified source models with very few parameters.
However, this approach is likely to introduce biases that are not based upon prior knowledge of the source
of the deformation. We describe an alternative approach, the introduction of regularization penalty functions or constraints
based upon the expected properties of the source. We illustrate this approach with a few examples.
In one example range change data, obtained from Synthetic Aperture Radar satellites,
forms the basis for estimates of aquifer volume change in California's Central Valley.
The estimation algorithm incorporates a function penalizing changes far from known well locations,
linking the aquifer volume changes to agricultural, industrial, and municipal pumping within the Tulare basin.
We show that the range changes are compatible with the hypothesis that the source of aquifer volume changes
are variations in effective pressure around documented wells.
Specifically, inclusion of the well distance penalty does not degrade the fit to the observations,
inversions both with it and without it give variance reductions of 99.6%.
The patterns of aquifer volume change vary significantly from the drought year, between October
2015 and October 2016, to a wet year in 2017, and into 2018, a year with near average rainfall.
In another example, an inequality constraint improves the imaging of fluid volume changes
associated with a leaking well. The distribution of volume change suggests propagation
along one or more fractures surrounding the well. In the final example, we describe an approach for estimating stress changes above a
producing reservoir using InSAR range change data whereby we constrain the source model
using information on production and injection.
One approach to mitigate this issue is to adopt simplified source models with very few parameters.
However, this approach is likely to introduce biases that are not based upon prior knowledge of the source
of the deformation. We describe an alternative approach, the introduction of regularization penalty functions or constraints
based upon the expected properties of the source. We illustrate this approach with a few examples.
In one example range change data, obtained from Synthetic Aperture Radar satellites,
forms the basis for estimates of aquifer volume change in California's Central Valley.
The estimation algorithm incorporates a function penalizing changes far from known well locations,
linking the aquifer volume changes to agricultural, industrial, and municipal pumping within the Tulare basin.
We show that the range changes are compatible with the hypothesis that the source of aquifer volume changes
are variations in effective pressure around documented wells.
Specifically, inclusion of the well distance penalty does not degrade the fit to the observations,
inversions both with it and without it give variance reductions of 99.6%.
The patterns of aquifer volume change vary significantly from the drought year, between October
2015 and October 2016, to a wet year in 2017, and into 2018, a year with near average rainfall.
In another example, an inequality constraint improves the imaging of fluid volume changes
associated with a leaking well. The distribution of volume change suggests propagation
along one or more fractures surrounding the well. In the final example, we describe an approach for estimating stress changes above a
producing reservoir using InSAR range change data whereby we constrain the source model
using information on production and injection.