First EAGE Workshop on Unmanned Aerial Vehicles

One of the most real factors of geological exploration optimization is low-altitude Earth remote sensing that includes geophysical prospecting methods. This article describes a case of the efficient application of complex low-altitude UAV-based aerogeophysical surveying during greenfield prospecting for gold in greenfield localized in the Western Sayan mountains (Russia). 90 sq. km site characterized by extremely complicated landscape and terrain conditions as well as controversial views on its geological conditions. Surveys from a multirotor UAV (unmanned aircraft vehicle) were made with terrain flowing and included a simultaneous magnetic and gamma-ray radiometric surveying as well as gamma-ray spectrometry by the ‘static hovering’ method and multispectral photogrammetry. The articles sets forth main principles of the method applied as well as demonstrates the advantages of unmanned aircraft technologies vs. traditional geophysical prospecting methods, i.e. high performance and low costs even in those conditions when ground and aerial surveys are economically impractical or entirely impossible. Application of low-altitude UAV-surveys allowed for a large-scale geological and geophysical mapping involving low costs, for clearing up a controversial point of the site geological conditions and for planning further prospecting, while avoiding erroneous solutions prompted by wrong priori assumptions about a geological structure of the site.

UAV magnetic surveys often consist of a multitude of sorties due the short flight time of battery powered UAVs and the necessity to maintain visual contact with the UAV all times. Processing the data into a final map product is often laborious and time consuming. The UAV Extension for Oasis Montaj improves the effectiveness of flight operations through pre-survey planning and reduces the time required to process the data to a final map product by a set of automation tools.

We present a method and preliminary results from a UAV-based vector magnetic survey system. The key element is an accurate inertial measurement unit (IMU) that measures the orientation of the UAV platform. Equivalent layer modelling and numerical optimization is then used to find out the angular (roll, pitch, yaw) difference between the coordinate systems of the IMU and the fluxgate (FG) magnetometer installed rigidly into the tail boom of a fixed-wing UAV. Once the true orientation of the FG sensor is known, the components of the measured magnetic field are rotated to the geographical coordinate system. The vector magnetic field, i.e., the XYZ components of the magnetic field provide useful information for magnetic data interpretation. We present an example illustrating how the direction of the magnetization can obtained from 3-component magnetic data by numerical inversion. Based on the example, 3D inversion of vector magnetic data helps identifying remnant magnetization, for example.

The investigation of outcrop analogues using Unmanned Aerial Vehicle (UAV) has become increasingly popular to improve the understanding of subsurface heterogeneity. Although seismic data offer an invaluable method to characterize the stratigraphic architecture of deep-water systems and therefore help unlock their reservoir potential, the scale of observations cannot capture detailed vertical extent of the sediment distribution and the related processes responsible for the deposits.

This work uses a combination of photographic data acquired from a UAV using Ground Control Points, and traditional fieldwork data to better characterize the gravity-driven systems of the Hikurangi subduction wedge (North Island, New Zealand). Their best onshore expressions are found along the coastline: a challenging working environment which evolves every day leading to multiple acquisitions (tides will affect wind variation and wave action, impacting sand coverage; sun and clouds will impact light exposure).

It is therefore essential to adapt the way we acquire and model data to ensure that all the information are gathered into one single comprehensive model. Our study proposes to expand on the traditional Structure from Motion workflow to account for such settings and help create more accurate models. We will present this approach applied to three different coastal outcrops.

A new workflow covering from data acquisition of outcrops with Unmanned Aerial Vehicles (UAV) to subsurface seismic data interpretation and characterization as an integrated solution is presented here. This novel workflow aims at reducing the time spent on interpretation and integration of surface analogues into reservoir characterization studies while increasing quality, productivity and saving cost. The adoption of such workflow will open new exploration and development opportunities through geological modeling, integrating outcrops and modern analogues data along with conventional geophysical measurements of the subsurface. Furthermore, this workflow provides a step towards geological expert systems-based interpretation processes that can be applied into a live data ecosystem.

Using affordable drones and photogrammetric software it is possible to generate spectacular 3D models of geological outcrops nowadays.

Unfortunately, when it comes to sharing the model with other coworkers, the most obvious solution is to take a screen capture of the model and share it as a 2D image. This simple solution does not allow to share the unique value of a 3D model, that is to be able to see it in three dimensions and from different points of view.

The present work describes a workflow that allows to complement the 3D model of a geological outcrop with other graphic elements, like geological surfaces and a graphic scale. The model is made available on the internet to a larger audience, with the possibility to manipulate it (rotate, zoom) and interact with it by hiding/showing certain graphic elements.

The workflow achieves this result by combining the use of three software: Move (specific for geological modeling), Blender and Sketchfab (specific for 3D graphics editing and online sharing).

This paper aims to introduce a novel approach to improve the detection efficacy of human hidden by debris with the help of new technologies such as unmanned aerial vehicles, augmented reality, and thermal photography. A thermal camera mounted upon a drone is used to gather images of the damaged area quickly. After heat signature detection of a buried body, the detected suspicious location sends out to the real-time virtual reality system and help the rescue team to locate the victims and their position quickly. It is also proved that thermography is a non-invasive method that can provide valuable information about body health, especially pain and inflammation. The increased warm in the thermogram may indicate that some health issues exist, such as inflammation, injury, bone fracture, etc. The results show that this new approach enhances the efficacy of rescue in terms of time and human locating, and semi- precise location of injured body organisim.