ALBERT

Description: With the increasing accessibility of terrestrial light detection and ranging scanners (LiDAR), generating tools to elicit meaningful information from high-density point cloud data has become of paramount importance. Surface roughness is one metric that has gained popularity, largely due to the accuracy and density of LiDAR-derived point cloud data. Surface roughness is typically defined as a spread of point distances from a reference datum, the standard deviation of point distances from a model surface being a commonly employed model. Unfortunately, a recent literature review has found that existing surface roughness models are far from standardized and may be prone to error resulting from underlying surface topography. In the research presented here, we develop a surface roughness model that is robust to underlying topographic variability by segmenting the point cloud with a three-dimensional regular grid, establishing local (grid cell) reference planes by orthogonal distance regression, and estimating the surface roughness of each grid cell as the standard deviation of orthogonal point-to-plane distances. This surface roughness model is employed to identify fracture and rubble zone distributions within a terrestrial LiDAR scan from a basalt outcrop in southeast Idaho, and the results are compared to a more common model based on ordinary least-squares plane fitting. Results indicate that the orthogonal regression model is robust to outcrop orientation and that the ordinary least-squares model systematically overestimates surface roughness by contaminating estimates with spatially correlated errors that increase with decreasing grid size.

Description: The rapid proliferation of portable, ground-based light detection and ranging (LiDAR) instruments suggests the need for additional quantitative tools complementary to the commonly invoked digital terrain model (DTM). One such metric is surface roughness, which is a measure of local-scale topographic variability and has been shown to be effective for mapping discrete morphometric features, i.e., fractures in outcrop, landslide scarps, and alluvial fan deposits, to name a few. Several surface roughness models have been proposed, the most common of which is based on the standard deviation of point distances from a reference datum, e.g., DTM panels or best-fit planes. In the present work, we evaluate the accuracy of these types of surface roughness models experimentally by constructing a surface of known roughness, acquiring terrestrial LiDAR scans of the surface at 25 dual-axis rotations, and comparing surface roughness estimates for each rotation calculated by three surface roughness models. Results indicate that a recently proposed surface roughness model based on orthogonal distance regression (ODR) planes and orthogonal point-to-plane distance measurements is generally preferred on the basis of minimum error surface roughness estimates. In addition, the effects of terrestrial LiDAR sampling errors are discussed with respect to this ODR-based surface roughness model, and several practical suggestions are made for minimizing these effects. These include (1) positioning the laser scanner at the largest reasonable distance from the scanned surface, (2) maintaining half-angles for individual scans at less than 22.5°, and (3) minimizing occlusion (shadowing) errors by using multiple, merged scans with the least possible overlap.

Description: Radon anomalies are widely reported in the vicinity of active faults, where they are often inferred to result from upward migration of fluids along fault zones. We examine the up-fault flow hypothesis by measuring radon ( 220 Rn and 222 Rn) in soil gas above two active normal fault zones within the central Taupo rift, New Zealand. In agreement with previous investigations, we find that the average concentrations of both radon isotopes are generally higher near mapped faults, although in some cases we find that the difference with background populations is not significant. Soil samples recovered from 1 m depth indicate that some of the radon anomalies along faults may reflect local changes in soil types. The 220 Rn isotope emanation measured from extracted soil samples shows a linear correlation with the field concentration measurements (R 2 = 0.90, p value = 3 x 10 –6 ), whereas 222 Rn emanation shows no linear correlation (R 2 = 0.17, p value = 0.17). The soil gas isotopes measured show a significant linear correlation of 220 Rn and 222 Rn concentrations (R 2 = 0.44–0.55, p value 〈10 –5 ) near faults. This correlation suggests a constant radon isotopic ratio is emitted from the soils tested, and this finding is supported by emission data measured on extracted soil samples. The distribution of 222 Rn concentration compared to 220 Rn can be explained by small-scale diffusion for 〉90% of the soil gas measurements, showing that a majority of radon anomalies along faults are not necessarily caused by advection of gases along fault planes and can be explained by an increase in radon soil emanation. However, diffusion cannot account for all of the observed patterns in the data, and in some specific locations along faults, 222 Rn concentrations are most likely produced by advective flow of subsurface gases, suggesting channelized gas flow in portions of some faults.

Description: Deep basalt formations within large igneous provinces have been proposed as target reservoirs for carbon capture and sequestration on the basis of favorable CO 2 -water-rock reaction kinetics that suggest carbonate mineralization rates on the order of 10 2 –10 3 d. Although these results are encouraging, there exists much uncertainty surrounding the influence of fracture-controlled reservoir heterogeneity on commercial-scale CO 2 injections in basalt formations. This work investigates the physical response of a low-volume basalt reservoir to commercial-scale CO 2 injections using a Monte Carlo numerical modeling experiment such that model variability is solely a function of spatially distributed reservoir heterogeneity. Fifty equally probable reservoirs are simulated using properties inferred from the deep eastern Snake River Plain aquifer in southeast Idaho, and CO 2 injections are modeled within each reservoir for 20 yr at a constant mass rate of 21.6 kg s –1 . Results from this work suggest that (1) formation injectivity is generally favorable, although injection pressures in excess of the fracture gradient were observed in 4% of the simulations; (2) for an extensional stress regime (as exists within the eastern Snake River Plain), shear failure is theoretically possible for optimally oriented fractures if S h ≤ 0.70S V ; and (3) low-volume basalt reservoirs exhibit sufficient CO 2 confinement potential over a 20 yr injection program to accommodate mineral trapping rates suggested in the literature.