Jerry P. Fairley

Rapid transport pathways for geothermal fluids in an active Great Basin fault zone

We present an analysis of fault hydraulic architecture, based on >700 spatially distributed ground and geothermal spring temperature measurements taken in an active fault zone. Geostatistical simulations were used to extrapolate the measured data over an 800 × 100 m area and develop a high-resolution image of temperatures in the fault. On the basis of the modeled temperatures, a simple analytical model of convective heat transport was used to infer a probability distribution function for hydraulic conductivities in a two-dimensional plane parallel to the land surface, and the partitioning of flow between flow paths of different conductivities was calculated as a fraction of the total flux. The analysis demonstrates the existence of spatially discrete, high-permeability flow paths within the predominantly lower-permeability fault materials. Although the existence of fast-flow paths in faults has been hypothesized for >10 yr, their prevalence and contribution to the total flow of fluid in a fault zone are debated. On the basis of our findings, we conclude that the flux transmitted by an individual fast-flow path is significantly greater than that of an average flow path, but the total flux transported in fast-flow paths is a negligible fraction of the total flux transmitted by the fault.

Estimating surface roughness of terrestrial laser scan data using orthogonal distance regression

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.

Experimental evaluation of terrestrial LiDAR-based surface roughness estimates

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.

Challenges for numerical modeling of enhanced geothermal systems.

A recent guest editorial by Wood (2009) pointed out the potential of enhanced geothermal systems (EGS) as a future source of “green” energy and suggested that EGS offers research opportunities for hydrogeologists seeking to become involved in the world’s energy future. Although EGS may have a bright future as a sustainable, low-carbon emission energy source, significant technical challenges must be overcome before this promising energy resource can be commercially viable. Because pilot EGS projects in the United States face very different economic constraints than current European projects, there is a real need to make technological advances to improve the return on capital investment. In this article, we amplify on Wood’s excellent editorial by describing some of the challenges that exist for the simulation of EGS.

Unsaturated Flow Through a Small Fracture -- Matrix Network: Part 2. Uncertainty in Modeling Flow Processes

Simulations of flow and transport in variably saturated fractured rock generally assume equilibrium conditions between the fractures and the porous matrix, leading to predictions that are dominated by a diffusive process. Contrary to these predictions, an increasing body of evidence suggests that fracture-dominated flow, under nonequilibrium conditions between the fractures and porous matrix, occurs frequently in field and laboratory settings. Flow processes, such as fluid cascades and flow path switching, are often observed in laboratory experiments, but are generally not captured by diffusion-based conceptual and numerical models. Many of these processes are assumed to be averaged out at some representative elemental volume scale; however, anecdotal evidence from field experiments conducted at various scales of investigation suggest that this may not be the case. Comparison of experimental observations with numerical simulations illustrates at least two potential problems with standard equivalent continuum and discrete fracture conceptual models of unsaturated fractured and porous media flow. First, such models tend to overestimate the strength of interaction between the fracture and matrix domains. Second, model calibration may allow diffusion-based models to accurately reproduce experimental observations without providing a complete description of the physics governing the system. Failure to incorporate convective transport, reduced fracture–matrix interaction, and other sub-grid-scale processes in models of flow in fractured porous media may result in erroneous descriptions of system behavior.

Physical constraints on geologic CO2 sequestration in low-volume basalt formations

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.

Unsaturated Flow through a Small Fracture–Matrix Network

Simulations of flow and transport in variably saturated fractured rock generally assume equilibrium conditions between the fractures and the porous matrix, leading to predictions that are dominated by a diffusive process. Contrary to these predictions, an increasing body of evidence suggests that fracture-dominated flow, under nonequilibrium conditions between the fractures and porous matrix, occurs frequently in field and laboratory settings. Flow processes, such as fluid cascades and flow path switching, are often observed in laboratory experiments, but are generally not captured by diffusion-based conceptual and numerical models. Many of these processes are assumed to be averaged out at some representative elemental volume scale; however, anecdotal evidence from field experiments conducted at various scales of investigation suggest that this may not be the case. Comparison of experimental observations with numerical simulations illustrates at least two potential problems with standard equivalent continuum and discrete fracture conceptual models of unsaturated fractured and porous media flow. First, such models tend to overestimate the strength of interaction between the fracture and matrix domains. Second, model calibration may allow diffusion-based models to accurately reproduce experimental observations without providing a complete description of the physics governing the system. Failure to incorporate convective transport, reduced fracture–matrix interaction, and other sub-grid-scale processes in models of flow in fractured porous media may result in erroneous descriptions of system behavior.

Forecast of Natural Aquifer Discharge Using a Data-Driven, Statistical Approach

In the Western United States, demand for water is often out of balance with limited water supplies. This has led to extensive water rights conflict and litigation. A tool that can reliably forecast natural aquifer discharge months ahead of peak water demand could help water practitioners and managers by providing advanced knowledge of potential water-right mitigation requirements. The timing and magnitude of natural aquifer discharge from the Eastern Snake Plain Aquifer (ESPA) in southern Idaho is accurately forecast 4 months ahead of the peak water demand, which occurs annually in July. An ARIMA time-series model with exogenous predictors (ARIMAX model) was used to develop the forecast. The ARIMAX model fit to a set of training data was assessed using Akaikes information criterion to select the optimal model that forecasts aquifer discharge, given the previous years discharge and values of the predictor variables. Model performance was assessed by application of the model to a validation subset of data. The Nash-Sutcliffe efficiency for model predictions made on the validation set was 0.57. The predictor variables used in our forecast represent the major recharge and discharge components of the ESPA water budget, including variables that reflect overall water supply and important aspects of water administration and management. Coefficients of variation on the regression coefficients for streamflow and irrigation diversions were all much less than 0.5, indicating that these variables are strong predictors. The model with the highest AIC weight included streamflow, two irrigation diversion variables, and storage.

A field sampling strategy for semivariogram inference of fractures in rock outcrops

The stochastic continuum (SC) representation is one common approach for simulating the effects of fracture heterogeneity in groundwater flow and transport models. These SC reservoir models are generally developed using geostatistical methods (e.g., kriging or sequential simulation) that rely on the model semivariogram to describe the spatial variability of each continuum. Although a number of strategies for sampling spatial distributions have been published in the literature, little attention has been paid to the optimization of sampling in resource- or access-limited environments. Here we present a strategy for estimating the minimum sample spacing needed to define the spatial distribution of fractures on a vertical outcrop of basalt, located in the Box Canyon, east Snake River Plain, Idaho. We used fracture maps of similar basalts from the published literature to test experimentally the effects of different sample spacings on the resulting semivariogram model. Our final field sampling strategy was based on the lowest sample density that reproduced the semivariogram of the exhaustively sampled fracture map. Application of the derived sampling strategy to an outcrop in our field area gave excellent results, and illustrates the utility of this type of sample optimization. The method will work for developing a sampling plan for any intensive property, provided prior information for a similar domain is available; for example, fracture maps or ortho-rectified photographs from analogous rock types could be used to plan for sampling of a fractured rock outcrop.

Evidence for Composite Hydraulic Architecture in an Active Fault System Based on 3D Seismic Reflection, Time-Domain Electromagnetics and Temperature Data

Fault hydrology is a topic of scientific and practical importance but considerable uncertainty exists regarding the nature of structural controls on fluid flow. Here we use seismic reflection and time-domain electromagnetic data to develop a three-dimensional model of hydraulic architecture in a predominantly dip-slip normal fault system and we predict the architectural elements based on subsurface fluid flow patterns inferred from near-surface temperature measurements. Our observations indicate the presence of high-permeability flow paths parallel to fault planes in poorly-lithified sediments. These results are best explained using a combination of elements from commonly accepted conceptual models of fault architecture, a finding that exhibits the heterogeneous nature of the geologic materials comprising the site. These insights may be useful as a guide to future studies of active fault systems, where multiple-mode investigations (geophysical, hydrologic, thermal, geochemical) will be required to better understand subsurface fluid/fault interactions.