An extensive airborne electromagnetic (AEM) survey was carried out in Norway with the primary purpose to obtain information of depth to bedrock in areas with little or no prior geotechnical knowledge. We present different approaches to extract a bedrock model from the high-resolution time-domain AEM data, including both automated and manual procedures. It was found that in the area of investigation a user-driven approach of manual bedrock picking was the most suitable, taking into account the strongest vertical resistivity gradient and geological information as additional information. A semi-automatic, statistical method, called Localized Smart Interpretation (LSI), is also presented and discussed. This method, while not included in the original bedrock model for the entire area, showed promising results while using less time compared to the fully manual approach. It is recommended that LSI be considered in future projects of similar scope.
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?
AbstractWe investigate an active rock slide in Western Norway with ground- and airborne resistivity mapping to ultimately find weakness zones & sliding planes embedded in crystalline bedrock. The study area comprises phyllite, a low grade metamorphic rock type that tends to be reworked to clay in disturbed zones. Mapping these electrically conductive clay zones was the aim of the survey. GPS measurements over the last 5 years indicate that precipitation drives rock slide movements. The role of ground water is thus a crucial factor to investigate for risk assessment in the area.Based on a successful airborne electromagnetic (AEM) demonstration survey, we conducted a total of 1.600 profile meters of ground resistivity (ERT) measurements to confirm AEM anomalies, to gain precise 2D geometries and to link conductivity anomalies with geology.All resistivity results confirm AEM anomalies and refine their lateral extent. In the East we find consistency between a strong conductor, dipping sub horizontal SW with an outcropping thrust fault, separating phyllite and gneiss. In the West a conductor dipping steeply NNW seems to be fed by surface water and may represent a formerly unknown sliding plane. While ERT and AEM anomaly shapes generally agree within their mutual resolution limitations, the resistivity values significantly deviate. It remains unclear whether anisotropy or strong 3D artefacts cause this disagreement.KeywordsAEMERTgeohazards3D AcknowledgmentsWe want to acknowledge Bjørn Sture Rosenvold (Aurland municipality) for initiating this investigation and partial funding. We further thank Max Halkjær & Rasmus Teilman (SkyTEM ApS) for excellent work during AEM data acquisition and Espen Auken & Nikolaj Foged (University of Århus) for supplying SCI results. AAP and EG received funding from the Norwegian Research Foundation through KMB project 182728. The project has been supported by the International Centre for Geohazards and EU project SafeLand.
The polar oceans’ sea ice cover is a challenging geophysical target to map. Current state of practice helicopter-electromagnetic (HEM) ice thickness mapping is limited to 1D interpretation due to common procedures and systems that are mainly sensitive to layered structures. We present a new generation Multi-sensor, Airborne Sea Ice Explorer (MAiSIE) to overcome these limitations. As the actual sea ice structure is 3D and in parts heterogeneous, errors up to 50% are observed due to the common 1D approximation. With MAiSIE we present a new EM concept based on one multi frequency transmitter loop and a three component receiver coil triplet without bucking The small weight frees additional payload to include a line scanner (lidar) and high accuracy INS/dGPS. The 3D surface topography from the scanner with the EM data at from 500 Hz to 8 kHz, in x, y, and z direction, will increase the accuracy of HEM derived pressure ridge geometry significantly. Experience from two field campaigns shows the proof-of-concept with acceptable sensor drift and receiver sensitivity. The preliminary 20 ppm noise level @ 4.1 kHz is sufficient to map level ice thickness with 10 cm precision for sensor altitudes below 13 m.
A new road segment is being planned northeast of Norway's capital city, Oslo. In this context, knowledge of sediment thickness is vital, as is information about occurrence and extent of highly sensitive marine clay (so-called quick clay). Airborne EM measurements were conducted to provide information of depth to bedrock/sediment thickness between drilling sites and guide the further drilling program. AEM data indicate a variable bedrock depth with a general trend towards shallower bedrock in the northeastern part of the investigation area. Quick clay is not easily identified in the AEM data, but some possible occurrences agree well with the results from drillings. Two methods for estimating depth to bedrock were compared: (1) Depth to a survey-wide resistivity threshold, guided by interpolating depth between boreholes, and (2) by kriging AEM data and contouring an appropriate resistivity value as a function of position. Though both exhibit the same general trends, predictions for some locations differed significantly. A contouring algorithm was developed to incorporate both borehole and AEM data and hence account for variations in resistivity at the sediment-bedrock boundary. Work is ongoing to evaluate the algorithm's results, to test more computationally efficient interpolation methods aside from kriging, and to compute the uncertainty in predicted depths. Based on the AEM results recommendations for further drillings were given, thus reducing the overall costs of the project.
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