900 research outputs found
Seasonal temperature effect compensation in ERT monitoring without ground thermal measurements
No full textThe seasonal temperature effect on electrical resistivity data is often overlooked in ERT monitoring surveys and modelling efforts.
This oversight can lead to anomalies in the models that are orders of magnitude greater than the target anomalies being monitored,
potentially resulting in unusable or misleading results. When not overlooked, temperature correction involves costly and logistically
complex measurements of ground temperature alongside resistivity data collection.
In this study, we propose a novel Time-Lapse inversion scheme, named ARES, to address the seasonal temperature effect without
the need of subsoil measurements. The ARES correction directly incorporates temperature into the modeling, estimating subsoil
temperature by solving the heat diffusion equation for each time-step and introducing the thermal diffusivity of the medium as an
inversion parameter. We present synthetic modelling to test the effectiveness of the ARES correction and develop guidelines for
implementing ERT monitoring with the ARES correction. Subsequently, the application of ARES scheme to a 20-month ERT
monitoring project over a Municipal Solid Waste landfill is presented, where a 3D acquisition layout is employed to observe waste
evolution and identify area of high biogas productivity. Our results demonstrate that without the ARES correction, temperature effects
overshadowed target anomalies, hindering interpretations. However, with the ARES correction, we successfully compensated for
temperature effects in the inversion models. In the real case study, this correction enabled the detection of anomalies associated with
different physical phenomena, allowing for quantitative interpretations
Modelling temperature effect in time lapse DC monitoring experiments through inversion of thermal diffusivity
No full textIn the recent years, time-lapse surveys have been performed widely to monitor, for instance, hydrogeological tracer experiments (Cassiani et al., 2006), groundwater watershed characterization (Miller et al., 2008; Deiana et al., 2018), seasonal variations (Hiblich et al., 2011; Musgrave and Binley 2011), landslide behaviour and evolution (Cassiani et al., 2009, Wilkinson et al., 2010), and so on. One of the main concerns, when resistivity surveys are performed, is to be sure to impute the variations to the right phenomena, distinguishing the electrical changes of interest from all the others, which are assumable as noise. Temperature variations might represent the main noise source in the time-lapse conductivity surveys since temperature has a strong impact on the resistivity parameters, hence on the inversion results. For example, seasonal temperature trends could mask the conductivity variations, and thus leading to misleading interpretations, up to the depths from the surface that can be reached by external fluctuations. Haley et al. (2007; 2009; 2010) have pointed out the importance of considering the temperature variations in time-lapse geoelectrical surveys, including in the inversion procedure a correction for this effect. In this study we intend to disentangle the temperature effect from resistivity variations inverting for the thermal diffusivity of the medium in a simultaneous time-lapse inversion that does not require direct temperature measurements below ground, both on a synthetic dataset and on-field experiments
4D Airborne EM with Independent Hydrogeological Validation (IHV) – Evolution Study of a Saltwater Aquifer
No full textIn this study, a multitemporal Airborne EM survey (2015, 2022, 2024) was conducted to monitor the
groundwater changes in the shallow aquifer of the Bookpurnong floodplain, South Australia. Over 200 km of
AEM lines were acquired during each survey in this naturally high-salinity aquifer region, with the aim of
tracking freshwater recharge induced by the River Murray's discharge. The river and its flood events are the
sole freshwater source sustaining the shallow hydrogeological system, which is crucial for native vegetation
survival and for the agricultural activities in the floodplain surrounding (Munday et al., 1997).
A Time-Lapse inversion scheme (Fiandaca et al., 2015) is employed to model the data, transitioning from the
classic independent inversion approach to minimize model artifacts entering the evolution study. The
temporal analysis revealed clear trends in electrical resistivity changes, highlighting a differential behaviour
between the shallow and deeper aquifers. A comprehensive validation of the results is performed by first
comparing the models with available log-EM data for the floodplain. This is followed by an Independent
Hydrogeological Validation (IHV), where hydrogeological indices, calculated following Vonk (2024), are
matched with the geophysical results. The comparison demonstrated strong coherence between the AEM
models and the hydrogeological indices, thereby validating the spatial information provided by the 3D
geophysical models and the quantitative subsurface evolution they reveal
Time-Lapse Airborne EM for monitoring the evolution of a saltwater aquifer
No full textIn this study, a multitemporal Airborne EM survey (2015, 2022, 2024) is conducted to monitor the ground-water changes in the shallow aquifer of the Bookpurnong floodplain, South Australia. Over 200 km of AEM lines were acquired during each survey in this naturally high-salinity aquifer region, with the aim of track-ing the freshwater recharge induced by the River Murray's discharge. A comprehensive comparison be-tween the benefits achieved by applying Time-Lapse modelling to Airborne EM data is provided, show-casing also a synthetic experiment before the real case study. In both instances, enforcing temporal con-straints, characterised by the Asymmetric Minimum Support Norm (AGSM, Fiandaca et al., 2015, doi: 10.1093/gji/ggv350), proves crucial in reducing noise-induced model anomalies that could mislead inter-pretations. Specifically, a Spatial Constrained Inversion approach (Viezzoli et al., 2008, doi: 10.1190/1.2895521), which enables quasi-3D solutions by spatially linking neighbouring EM soundings, is integrated into the unified Time-Lapse framework, where all the dataset are inverted simultaneously using a cascade-style approach. In the latter, the multitemporal models are connected to a reference model, obtained from an initial dataset. Moreover, specific processing procedures are implemented to suppress noise induced anomaly propagation. The Time-Lapse results reveal a clear evolution of the floodplain within the geophysical models, unveiling a different hydrogeological behaviour from the shal-low parts of the models, of primary interest for the groundwater management in the area, to the deep portions (~-120m). A full validation of the results is carried out first employing the available log-EM data for the floodplain and then performing an Independent Hydrogeological Validation (IHV), where hydro-geological indices, calculated following Vonk (2024, doi: https://doi.org/10.5281/zenodo.10816741), are compared to the geophysical outcomes
Time-Lapse Airborne EM for monitoring the evolution a saltwater aquifer
No full textThis work presents the Time-Lapse modelling of an Airborne EM (AEM) monitoring datasets
acquired over the Bookpurnong area (Southern Australia) to study the evolution and interactions
between the Murray River freshwater discharge and the highly saline floodplain aquifers.
First, the effectiveness of AEM Time-Lapse modelling is underscored via synthetic experiment,
which enhanced data-driven solutions and minimized artifacts compared to the independent
approach.
Then the same modelling framework is applied on Bookpurnong floodplain data where, SkyTEM
datasets were acquired in 2015, 2022, and 2024, each consisting of 200 km of overlapping lines
spaced 100 meters apart.
Regarding the AEM data processing, a new simultaneous approach was deemed necessary to
address and eliminate all noise couplings in the temporal datasets.
A comparison between Time-Lapse and Independent inversion models from the field data is then
presented, confirming the synthetic test results, with the Time-Lapse modelling producing more
compact, conservative, and likely more data-driven results.
The interpretation of the Time-Lapse models initially focused on the shallow variations, main
interest for this study, which are first validated through the comparison with log-EM measurements
that revealed strong agreement with AEM models.
Then, a novel Independent Hydrogeological Validation further assessed the Time-Lapse results. This
analysis allowed an unbiased evaluation of the hydrological response of the floodplain over time
and revealed a solid correlation between this index and the shallow evolution depicted by the AEM
models.
The remarkable agreement between geophysical and hydrogeological analyses underscored the
suitability of AEM surveys to monitor groundwater processes when modelled within a Time-Lapse
framework
Temperature Correction for Long-Time DC Monitoring Experiments
No full textTime-lapse DC monitoring is widely performed to study electrical conductivity (EC) variations over long periods that might derive from subsoil changed conditions, potentially interesting for hydrogeological, geotechnical, or for general environmental purposes. The inversion of time-lapse models differs from the classic inversion techniques mainly due to the implementation of techniques to reduce systematic measurement errors and obtain compact changes in subsequent inversions. For time-lapse surveys which last across seasonality, the temperature variations will affect the subsoil EC conditions, representing therefore a source of noise that might hide the electrical changes of interest. To avoid such an effect, in this study the model vector contains the resistivity at a reference temperature and the temperature as parameters. The effective EC is then computed cell-by-cell before running the forward response. A synthetic experiment is performed simulating two different ground temperature models associated to two different resistivity models, to show the comparison of classic inversion, without temperature modelling, and time lapse inversion with temperature modelling. A real case scenario is also proposed to confirm first the temperature effect on the shallowest subsoil EC, then to present the results of the temperature modeling on the conductivity final model
Time-Lapse Airborne EM for monitoring the evolution of a saltwater aquifer
No full textThis work presents a novel time-lapse modelling scheme for Airborne Electromagnetics (AEM)
monitoring datasets, applied to study the hydro-related evolution of the Bookpurnong
floodplain in South Australia. Additionally, it introduces a new wide-ranging approach for this
type of study, incorporating new processing, validation, and interpretation tools.
Time-Lapse studies are widespread in the literature but are not commonly applied to model EM
data, particularly AEM data. This is likely due to the challenges of performing overlapping
acquisitions with inductive systems. The key features of the new time-lapse scheme, which
address these issues, include the definition of independent forward and model meshes.
Additionally, a novel dedicated processing workflow for AEM monitoring is presented.
The results of the time-lapse geophysical models are evaluated with an Independent
Hydrogeological Validation (IHV), designed to support the geophysical results validation and
interpretation phases with hydrogeological assessment of the system.
At Bookpurnong, along a sector of the Murray River floodplain, multitemporal AEM survey were
collected in 2015, 2022 and 2024, to study the groundwater system evolution over time. The
time-lapse models show very small variations compared to the independent ones, while
revealing sharply bounded variation zones over the floodplain. This demonstrates the
effectiveness of the new time-lapse scheme, especially considering the discrepancies in data
location and acquisition height among datasets.
The AEM models are first validated through comparison with resistivity borehole
measurements. The models are ultimately validated and interpreted using the IHV approach,
which revealed a direct correlation between the hydrological stress of the Murray River and the
response of the shallow aquifers.
We believe that the time-lapse methodology developed in this work can be applied to AEM
multitemporal studies for monitoring different processes, surpassing the results of single-time
AEM investigations and providing a new dimension for studying large-scale processes with
greater accuracy
Joint Inversion of Electrical and Electromagnetic data including IP: a Methodological Breakthrough
No full textThis study focuses on the joint inversion of Electrical and Electromagnetic (EEM) data, specifically galvanic and inductive
measurements, within a unified inversion framework. The proposed joint inversion includes both galvanic and inductive datasets in
the data space, with the modelling accounting for induced polarization (IP) effects.
This joint inversion procedure is first assessed using synthetic models and then applied to a field case study involving AEM and
high-density geophysical coverage. The results consistently show that joint inversion yields models with enhanced resolution,
capturing both high and low electrical conductivity features more precisely compared to independent models.
The joint model is validated using borehole data, including EM geophysical logging and lithological descriptions, confirming the
methodology's effectiveness. This study highlights the potential of joint inversion techniques to provide comprehensive and reliable
subsurface models, crucial for geophysical applications especially in complex geological settings
Joint Inversion of Electrical and Electromagnetic data including IP: a Methodological Breakthrough
No full textThis study focuses on the joint inversion of Electrical and Electromagnetic (EEM) data, specifically galvanic and inductive measurements, within a unified inversion framework. The proposed joint inversion includes both galvanic and inductive datasets in the data space, with the modelling accounting for induced polarization (IP) effects. This joint inversion procedure is first assessed using synthetic models and then applied to a field case study involving AEM and high-density geophysical coverage. The results consistently show that joint inversion yields models with enhanced resolution, capturing both high and low electrical conductivity features more precisely compared to independent models. The joint model is validated using borehole data, including EM geophysical logging and lithological descriptions, confirming the methodology's effectiveness. This study highlights the potential of joint inversion techniques to provide comprehensive and reliable subsurface models, crucial for geophysical applications especially in complex geological settings
Joint Inversion of Electrical and Electromagnetic data including IP: a Methodological Breakthrough
No full textJoint Inversion of E&EM dat
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