Download Characterizing Sedimentary Outcrops with Laser Scanning

Abstract
The traditional approach to studying and characterizing exposed, sedimentary rock outcrops has depended
on both the experience of the geologist involved and on the accessibility of the rock surfaces themselves.
Morphological characterization of an outcrop, such as its layered rock orientation and thicknesses, are features that can be measured by hand using a measuring device, a compass and Jacob’s Staff for example, or
with 3D digital instrumentation such as a total station or GNSS. However, these methods can be time consuming when the scale of the outcrop is tens of meters large and outcrop height blocks GNSS signal. While
characterizing outcrops has proved useful for reservoir mapping and exploration, identifying markers can
also provide a point of comparison between various outcrops as the values further our understanding of subsurface processes and the drivers that formed the rocks themselves. Thus, the goal of this study is to first
determine which morphological features of rock outcrops are characteristic, and then, how those features
can be estimated efficiently and without a loss in accuracy to traditional measurements.
When considering efficiency, automation in the measurement and feature estimation processes was prioritized. A terrestrial laser scanner (TLS) is a close-range, data collection device that calculates line-of-sight
distances to create a three dimensional point cloud representation of the target, an outcrop in this case. It
can collect millions of points in just minutes with millimeter accuracy, and automated after scan parameters
are input. This solution appeared to suit the needs of the project and was selected for outcrop data collection. The next challenge was selecting an region with sufficient data, or outcrops, to study. The Drôme
department, primarily composed of the French Alpine foothills, contains numerous outcrops of varying formations, dimensions, and characteristics. The rocks in the region were formed ~100 − 150 million years ago
from sediments in a deep sea that existed at that time. The distinct sedimentary rock layers also encourage
data collection here as the morphological features protruded from the outcrop surfaces providing clear planar features and an opportunity to try out automated feature extraction. The week-long fieldwork survey in
the region concluded with dense (sub-centimeter) TLS data for ten outcrops of varying features. The most
distinct layering was found in an outcrop near the village of La Charce. From this 3D point cloud sample,
quantifiable orientation and thicknesses values need to be estimated.
The characteristic feature estimation process was then developed through a semi-automatic work flow of
efficiently extracting information from the 3D point cloud. The algorithms composing the work flow were
developed in Matlab on a 5 x 5 m sample section of the La Charce outcrop. The local surface normals of
the points in this section were calculated, grouped, and then filtered to extract points only belonging to the
tops of bedding layers. Virtual planes were fit to these grouped ’top’ points and estimated values for the dip
and dip direction (layer orientation) and exposed layer thicknesses were calculated from the planes. Based
on traditional compass measurements taken in the field of these same parameters, the algorithms estimated
values fall within one standard deviation of orientation field measurements. In fact, the estimates may actually be more precise considering an average of the layering over a larger area (than compass measurements)
was used in the algorithm calculations and compass measurements are subject to human (BSc student) error. Thickness estimates of layers within the formation varied greatly (20 − 300cm) from field staff data and
are dependent on the layers that the measurements were taken from (algorithm estimates of layers within the
La Charce sample fall within this range, regardless).
Close-range three dimensional measurement data from terrestrial laser scanning has proven to provide adequate information for estimating morphological features of rock outcrops. In addition, possibilities were explored for using laser intensity and surface roughness to derive rock composition, and this is recommended
for future study. Thus, in addition to traditional field measurements, laser scanning can be used to both validate and gain possibly more accurate insight to the true geometry and characterization of a sedimentary
outcrop. It is a relatively efficient method that ’brings’ the outcrop back into the laboratory for repeatable,
detailed analysis. This developed method, fully functional for the La Charce sample outcrop, demonstrates a
viable road map for extracting morphological features from 3D point clouds of sedimentary rock outcrops.
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