Combining airborne electromagnetic and geotechnical data for automated depth to bedrock tracking

Christensen, Craig W.; Pfaffhuber, Andreas Aspmo; Anschütz, Helgard; Smaavik, Tone Fallan

doi:10.1016/j.jappgeo.2015.05.008

Cited by 28 publications

(16 citation statements)

References 17 publications

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“…This last measurement device is particularly promising as it can help delineate soil stratigraphy and layers with contrasting hydraulic properties [ Eguchi et al ., ; Masaoka et al ., ]. Examples of indirect bedrock depth measurement methods include the use of gravity survey [ Stewart , ; Bohidar et al ., ], geophysical exploration [ Dahlke et al ., ], seismic refraction [ Zhou and Wu , ], electrical resistivity tomography [ Zhou et al ., ; Lucà et al ., ], and airborne electromagnetic [ Christensen et al ., ]. These latter five measurement methods make it possible to determine noninvasively the physical properties of the subsurface, yet inversion methods are required to interpret these indirect observations of the bedrock depth.…”

Section: Introductionmentioning

confidence: 99%

Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom‐up control hypothesis using high‐resolution topographic data

Gomes

Vrugt

Vargas

2016

Water Resources Research

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Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom-up control hypothesis using high-resolution topographic data Abstract The depth to bedrock controls a myriad of processes by influencing subsurface flow paths, erosion rates, soil moisture, and water uptake by plant roots. As hillslope interiors are very difficult and costly to illuminate and access, the topography of the bedrock surface is largely unknown. This essay is concerned with the prediction of spatial patterns in the depth to bedrock (DTB) using high-resolution topographic data, numerical modeling, and Bayesian analysis. Our DTB model builds on the bottom-up control on freshbedrock topography hypothesis of Rempe and Dietrich (2014) and includes a mass movement and bedrock-valley morphology term to extent the usefulness and general applicability of the model. We reconcile the DTB model with field observations using Bayesian analysis with the DREAM algorithm. We investigate explicitly the benefits of using spatially distributed parameter values to account implicitly, and in a relatively simple way, for rock mass heterogeneities that are very difficult, if not impossible, to characterize adequately in the field. We illustrate our method using an artificial data set of bedrock depth observations and then evaluate our DTB model with real-world data collected at the Papagaio river basin in Rio de Janeiro, Brazil. Our results demonstrate that the DTB model predicts accurately the observed bedrock depth data. The posterior mean DTB simulation is shown to be in good agreement with the measured data. The posterior prediction uncertainty of the DTB model can be propagated forward through hydromechanical models to derive probabilistic estimates of factors of safety.

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Section: Introductionmentioning

confidence: 99%

Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom‐up control hypothesis using high‐resolution topographic data

Gomes

Vrugt

Vargas

2016

Water Resources Research

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“…Bedrock topography is the main target for geotechnical surveys in terms of stability and mass balance as well as for tunnel planning in terms of portal design and expected rock cover. Combined with sparse boreholes, we have previously computed detailed bedrock models based on spatial correlation of the datasets (Christensen et. al.…”

Section: Resultsmentioning

confidence: 99%

The emperor's new clothes - opportunities and limitations applying AEM to geotechnical design work

Pfaffhuber¹,

Anschütz²,

Kåsin³

2016

ASEG Extended Abstracts

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In summer 2015, we acquired close to 6.000 km of Helicopter, time-domain airborne electromagnetic (AEM) data for regional geotechnical mapping for the Norwegian National Rail Administration. This survey and further experience from related Norwegian road planning projects demonstrated the unprecedented accuracy of modern AEM data. The extent of geotechnical site investigations can be drastically reduced, both in terms of time schedule, and costs if AEM derived bedrock models are included when soil investigations are planned. Geotechnical projects demand high resolution (meter scale) and AEM data is to some extent capable of delivering that. Some of our data matched the resolution of corresponding ground geophysics data. Here we present the way in which AEM can be used as bedrock models, sensitive clay delineation and to determine bedrock types. Our discussion leads us to the missing link between high vertical resolution in the first tens of meters for geotechnical work and the focus on simple, sub-vertical structures in exploration AEM. Ultimately, we should strive for the best of both worlds, shouldn't we?

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“…This is done for two main reasons: AEM system selection and AEM system validation. In other regions, such as Norway, comparisons of AEM to borehole logs are often done to pick out geological features of interest such as depth to bedrock (Christensen et al, 2015). The application of combining AEM to borehole logs is enormous.…”

Section: Introductionmentioning

confidence: 99%

Making EM systems and bore logs speak the same language

Davis¹,

Hauser²

2019

ASEG Extended Abstracts

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Combining airborne electromagnetic and geotechnical data for automated depth to bedrock tracking

Cited by 28 publications

References 17 publications

Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom‐up control hypothesis using high‐resolution topographic data

Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom‐up control hypothesis using high‐resolution topographic data

The emperor's new clothes - opportunities and limitations applying AEM to geotechnical design work

Making EM systems and bore logs speak the same language

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