Interferometric Synthetic Aperture Radar (InSAR) techniques can measure surface deformation associated with fluid injection and withdrawal associated with oil and gas production. We derived basin-wide deformation maps using Sentinel-1 C-band SAR images between 2015-2022 over three oil producing basins in Texas: Delaware, Midland, and Eagle Ford. In the Delaware Basin, we observed areas of up to 13 cm of subsidence and areas of up to 12 cm of uplift, due to production and injection respectively. In the Midland basin, we observed up to 8 cm of cumulative line of sight (LOS) subsidence that increased with production from 2015-2022. In the Eagle Ford basin, we observed a ~900 km2region of up to 13 cm of cumulative LOS subsidence. We validated the InSAR results using independent GPS data at all 30 available stations and achieved mm-level accuracy. We used additional production and injection data and earthquakes records and found a correlation between deformation and production in all three basins. Specifically, in the Delaware Basin, the magnitude of subsidence is linearly related to production. Rates of subsidence increased from mid 2018-2021. Uplift features, surrounded by subsidence, also increased in 2020-2021. In the Midland Basin, local deformation patterns correlate with production and injection wells. In the Eagle Ford, the observed large subsidence features align with drilling locations and confined aquifer pumping.

In this study, we derive time series histories over the southern Central Valley and the Carrizo-Wilcox aquifer using spaceborne Interferometric Synthetic Aperture Radar (InSAR) techniques. The observed subsidence signals are associated with withdrawal of fluids from the subsurface, either from confined aquifer pumping or oil and gas production. We processed 122 C-Band Sentinel-1 SAR images over the Central Valley and 123 images over a ~100 x 200 km region near San Antonio, TX from 2017-2021. These InSAR datasets suffer from severe decorrelation artifacts due to the presence of dense vegetation. To overcome this limitation, we use a recently developed Persistent Scatterer (PS) algorithm to reconstruct spatially coherent phase patterns in decorrelated interferograms. We derived SBAS solutions using varying temporal baselines using original, uncorrected data and PS-interpolated interferograms. In the Central Valley, computing all interferograms and selecting those with minimal unwrapping artifacts result in the smallest linear rate misfit when compared to independent GPS data. Using this strategy over the San Antonio site, we observe a region over 100 km long of up to 10 cm of cumulative line of sight (LOS) subsidence overlaying the Eagle Ford shale. Subsidence mapping over the large-scale, complex, vegetated aquifers will help transform our understanding of groundwater resources and their sustainable management.

Interferometric Synthetic Aperture Radar (InSAR) surface deformation estimates often suffer from tropospheric noise errors, and many study sites do not have GPS or in-situ measurements for validating InSAR surface deformation solutions. Here we present a method for characterizing both surface deformation and tropospheric noise from interferogram subsets. Choosing different subsets of interferograms that use a common-reference SAR scene allows us to quantify tropospheric noise and deformation signals. We demonstrate this method using 95 C-Band Sentinel-1 SAR scenes acquired over the Oman Ophiolite and 133 scenes over the Island of Hawaii. For the Oman case, our method suggests that there is no detectable deformation signal. In this scenario, the average of any subset of interferograms with a common-reference SAR scene estimates the tropospheric noise contribution on that reference SAR date. Achieving ~0.5 cm of uncertainty requires a subset size of 40 common-reference interferograms. The observed tropospheric noise is non-Gaussian, and follows a seasonal pattern. Propagation of tropospheric noise leads to up to ~5 cm of false deformation signal when deriving either a stacking or SBAS time series solution. For the Hawaii case, our method shows that the observed InSAR phase on the south flank of Kilauea is due to a secular deformation signal, while the phase over Mauna Loa is mostly associated with tropospheric noise. Our results are validated with independent GPS tropospheric zenith delay and surface deformation time series with sub-cm RMS errors.

Interferometric Synthetic Aperture Radar (InSAR) surface deformation estimates often suffer from tropospheric noise errors. Here we present a method for co-characterizing surface deformation and tropospheric noise from interferogram subsets. Choosing different subsets of all available interferograms allow identification of linear secular deformation, little apparent deformation, transient events, or higher order nonlinear rates. We demonstrate this method using 95 C-Band Sentinel-1 SAR scenes acquired over the Oman Ophiolite and 133 scenes over the Island of Hawaii. In Oman, our method suggests that there is no detectable deformation signal. In this scenario, we averaged subsets of randomly selected interferograms that share a common reference SAR scene. As the subset size increases, at$\sim 50$, the results converge to accurate estimates of tropospheric noise on the reference date. In Hawaii, our method shows that the observed InSAR phase on the south flank of Kilauea is due to a secular deformation signal, while the phase over Mauna Loa is mostly associated with tropospheric noise. Our approach provides a new way to derive InSAR uncertainty analyses without requiring additional in situ validation or prior knowledge of deformation models.

The Samail Ophiolite comprises ultramafic rocks, which undergo chemical processes known as serpentinization and carbonation when exposed to air and water. As a byproduct, this permanently binds atmospheric CO2to stable carbonate minerals and stores it underground. The intensive fracturing in the peridotites during carbon mineralization can lead to a net volume increase and observable surface uplift. Here we use 89 Sentinel-1 SAR images to measure surface displacement from January 2017 through December 2019. InSAR time series analysis shows uplift of several centimeters in mid-2017, following a significant 72 mm rainfall event in March 2016. We developed an approach to evaluate the magnitude of tropospheric noise in InSAR time series over regions with limited ground truth measurements. Our analysis shows that the observed surface deformation signals are likely well above the tropospheric noise level. Due to the absence of other localized deformation sources (e.g. hydrologic or tectonic forcings), these InSAR deformation signatures could correspond to carbon mineralization. Our results contribute to the ongoing research related to accelerating this process as a means to help reduce our carbon footprint.

Interferometric Synthetic Aperture Radar (InSAR) measurements reveal ground deformation following a rainfall event in the Samail Ophiolite in Oman. Due to the absence of usual tectonic and hydrologic forcings, we hypothesize that deformation is a result of chemical reactions and associated fracturing in the subsurface. When the ultramafic rocks in the ophiolite are exposed to air and water, they undergo carbonation which increases the rock volume and fractures the rock, resulting in observable ground surface uplift. A pilot study using 41 Sentinel-1 SAR images between 2016/11/15 and 2018/03/22 shows up to 4 cm of uplift in the several weeks following a major rainfall event, suggesting that carbonation is limited by rainfall. The uplift signal eventually recedes back to the noise level thus a longer time series with more rainfall events will better confirm this hypothesis. An eventual InSAR time series from 2015-present and an associated groundwater table model may improve the current estimates of CO2captured by the carbonation, and its rate, in ultramafic rocks.