Earth & Environmental Sciences

This study presents the results from in-well hydraulic fracture monitoring within a horizontal well in an unconventional reservoir utilizing Distributed Fiber Optic Sensing (DFOS). An in-house-developed Brillouin-based Distributed Strain Sensing (DSS) interrogator was deployed to obtain strain measurements, complemented by a commercial Raman-based Distributed Temperature Sensing (DTS) interrogator for temperature measurements and a commercial Rayleigh-based Low-Frequency Distributed Acoustic Sensing (LF-DAS) interrogator for strain-rate measurements. Examined over a ten-day period, the spatio-temporal distribution of temperature-compensated strain obtained from DSS and DTS revealed distinct signatures of the multi-stage hydraulic fracturing process. These signatures were analyzed with respect to fracture width growth and closure, residual strain effects, and fracture conductivity near the wellbore. Fracture widths within the fracture zone were estimated for individual stages. The findings were assessed with LF-DAS measurements for further evaluation. This work integrates DFOS-measured strain, temperature, and strain-rate data for monitoring in-well hydraulic fracturing, with the goal of supporting future studies in interpreting DFOS measurements for improved understanding of hydraulic fracturing in unconventional reservoirs.

Executive Summary Scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) have teamed up with the University of Hawai‘i at Manoa (UH Manoa) through the U.S. Department of Energy’s Energy Technology Innovation Partnership Project to evaluate the technological and market feasibility of shallow geothermal heat exchanger (GHE) technology. UH requested this analysis to evaluate opportunities in building cooling, energy efficiency, and emissions reduction applications in Hawai‘i. UH has an abundance of geologic and geothermal data and is looking to the national labs’ expertise to execute this analysis. UH is also interested in investigating policy, regulatory, and business conditions advantageous for implementation of a pilot project and more broad deployment of this technology in Hawai‘i. In many locations around the world, the demands for heating and cooling are roughly balanced over the course of the year, so GHEs do not cause significant long-term changes in subsurface temperature. This is not the case in Hawai’i, where the demand for heating is very small, meaning that, over time, GHEs will add heat to the subsurface. If temperatures increase significantly, GHE systems will not work as designed. Regional groundwater flow has the potential to sweep heated water away from boreholes, thereby maintaining the functionality of the GHE system. Significant regional groundwater flow requires two things: a sufficiently large driving hydraulic head gradient (usually closely related to surface topography), and sufficient porosity and permeability to enable groundwater to flow in large enough quantities to enable near-borehole temperatures to be maintained at ambient values. Hawai‘i’s volcanic terrain offers ample surface topographic variation. The lava itself shows an extremely large range of porosity and permeability, so sites with large enough values of these properties must be selected. Numerical modeling of coupled groundwater and heat flow can be used to determine how large is large enough. Primarily, closed-loop systems have been investigated. Other options considered are open-loop systems and using cool seawater as the chilling source. Project work investigated the feasibility of GHE technology at two scales. At the island scale, GIS layers of various attributes relevant for GHE were combined to develop an overall favorability map for employing GHE in Hawai‘i. At the local scale, a hydrogeologic model for the subsurface component of a closed-loop system was developed for the Stan Sheriff Center at the UH Manoa campus. This site is considered promising because the rock below and immediately downgradient of the borefield is highly permeable, consisting of a subsurface karst system (limestone containing high-permeability open channels), which is underlain by a thick, high-permeability fractured basalt. Moreover, the site is near the base of the Ko‘olau Range, providing a large hydraulic head gradient. Thus, groundwater flow through the site is expected to be large, enabling efficient removal of heated groundwater. A full-GHE-system model of the site was also developed, with a simplified representation of the subsurface, in which groundwater flow is not considered and heat transfer is purely by conduction. Using the building cooling load data provided by UH, simulation results show that with groundwater flow present, a GHE can operate successfully for at least 10 years, but with no groundwater flow, the subsurface begins to heat up after only one year of operation, making the GHE unviable within 2-6 years. The team also developed a techno-economic model for this site to compare the cost of cooling using a GHE system with the costs of operating the current air-conditioning system. The GHE system is advantageous economically if favorable tax incentives and interest rates can be obtained.

Groundwater age distributions provide fundamental insights on coupled water and biogeochemical processes in mountain watersheds. Field-based studies have found mixtures of young and old-aged groundwater in mountain catchments underlain by bedrock; yet, the processes that dictate these groundwater age distributions are poorly understood. In this work, we use the coupled ParFlow-CLM integrated hydrologic and EcoSLIM particle tracking models to simulate groundwater age distributions on a lower montane hillslope in the East River Watershed, Colorado (USA). We develop a convolution-based approach to propagate fracture-matrix diffusion processes to the EcoSLIM advection-dominated age distributions. We compare observed ³H and ⁴He concentrations from two groundwater wells against model predictions that have varying advective transport times and matrix diffusion magnitudes. Based on a Monte Carlo analysis that considers uncertain matrix and fracture parameters, we find that matrix diffusion is needed to jointly predict ³H and ⁴He observations at both wells. The advection-dominated age distributions lack adequate mixing of young and old-aged water to capture the observed co-occurrence of ³H and ⁴He. The model scenario that best matches the ³H, ⁴He, and water level observations when considering both advective flowpath and matrix diffusion mixing processes has a dynamic bedrock groundwater reservoir that is susceptible to considerable storage losses during low-snow periods. This dynamic groundwater system amplifies the need to assimilate deeper bedrock groundwater into watershed hydro-biogeochemical predictions. This work further highlights the importance of considering matrix diffusion when interpreting environmental tracers in bedrock groundwater systems.

Snow thermal insulation is a critical factor influencing ground thermal dynamics and associated biogeochemical processes. We analyzed the spatiotemporal variability of snow accumulation, melting, and thermal insulation dynamics using spatially dense, collocated snow depth and ground interface temperature time series over two consecutive years. We demonstrated that considering late-winter snow depth alone was insufficient to fully capture the complexity in snow and insulation dynamics. The influence of vegetation and topography on snow depth distribution varied over the season, across sites and years. We found that deep snow with a long melting period had a substantial impact on thawing n-factors. To better predict snow insulation effects, we proposed a new weighted snow depth metric that integrates mean daily snow depth and air temperature throughout the cold season. Our results provide insights for developing space-time remote sensing products and evaluating the representation of snow and permafrost processes in Earth system models.

This multi-lab, DOE-funded project addresses the significant energy and water consumption and cost to cool information technology (IT) equipment in data centers by utilizing subsurface thermal energy storage systems, more specifically, reservoir thermal energy storage (RTES). The project was augmented by an industrial advisory group (IAG), including experts from both the data center and subsurface energy storage sectors, to provide feedback. A scenario-based method was applied to perform techno-economic feasibility analysis based on three types of data centers covering a range of sizes and in three geographical locations. The techno-economic analysis (TEA) was performed to compare RTES scenarios with commonly used or most competitive non-RTES cooling scenarios. The main conclusions from the investigation are that all RTES systems studied are technically feasible and sustainable for at least a period of 20 years without major modifications of the RTES and IT cooling systems. Within the context of the assumptions made by this study, the key factor to make RTES for data center cooling economically feasible and attractive in the right location includes: 1) a shallow non-potable water-bearing geological formation with large transmissivity (thick and high permeability formation) to maximize storability and minimize the number and depth of wells needed; and 2) potential to use free (compressorless) or inexpensive cooling. Compressorless cooling can be provided by dry coolers in mild climates (although that is not the only option,) and inexpensive cooling can utilize compressor cooling when power costs are very low or negative (e.g., excessive renewable energy production). Future studies should further consider using chillers for RTES cooling (in addition to dry coolers) when there is a significant grid value to do so (large difference between peak and off-peak power cost). Additionally, system optimization should be performed for a specific site to maximize the benefit of using RTES for cooling when deployed. Additional benefits, such as resiliency during high heat events, are often not captured in traditional TEA studies, and should be considered.

Molecular hydrogen (H2) is found in a variety of settings on and in the Earth from low-temperature sediments to hydrothermal vents, and is actively being considered as an energy resource for the transition to a green energy future. The hydrogen isotopic composition of H2, given as D/H ratios or δD, varies in nature by hundreds of per mil from ∼−800 ‰ in hydrothermal and sedimentary systems to ∼+450 ‰ in the stratosphere. This range reflects a variety of processes, including kinetic isotope effects associated with formation and destruction and equilibration with water, the latter proceeding at fast (order year) timescales at low temperatures (<100 °C). At isotopic equilibrium, the D/H fractionation factor between liquid water and hydrogen (DαH2O(l)-H2(g)) is a function of temperature and can thus be used as a geothermometer for H2 formation or re-equilibration temperatures. Multiple studies have produced theoretical calculations for hydrogen isotopic equilibrium between H2 and water vapor. However, only three published experimental calibrations used in geochemistry exist for the H2O-H2 system: two between 51 and 742 °C for H2O(g)-H2(g) (Suess, 1949; Cerrai et al., 1954), and one in the H2O(l)-H2(g) system for temperatures <100 °C (Rolston et al., 1976). Despite these calibrations existing, there is uncertainty on their accuracy at low temperatures (<100 °C; e.g., Horibe and Craig, 1995). Here we present a new experimental calibration of the equilibrium hydrogen isotopic fractionation factor for liquid water and molecular hydrogen from 3 to 90 °C. Equilibration was achieved using platinum catalysts and verified via experimental bracketing by approaching final values of DαH2O(l)-H2(g) at a given temperature from both higher (top-bracket) and lower (bottom-bracket) initial Dα values. Our calibration yields the following equation: [Formula presented] Where T is in Kelvin. We find that our calibrations differ from prior experimental calibrations by, on average, up to 20 ‰ and prior theoretical results by up to, on average, 25 ‰. Good agreement with theoretical results (<11 ‰ differences) is found for calculations that consider both anharmonic effects and the Diagonal Born-Oppenheimer correction.

Among the subsurface geophysical methods used in the critical zone investigations, induced polarization (IP) shows great vitality thanks to its unique ability to assess porosity via bulk conduction and estimate permeability through surface conduction and/or polarization. However, such an advantageous separation between bulk and surface is mostly implemented by multi-salinity experiments in the laboratory, which is incredibly difficult to realize in the field. One promising approach to address such an obstinate issue is to gauge the surface conductivity (σs) from the quadrature conductivity (σ″) or normalized chargeability (Mn) with the ratios between (l = σ″/σs, lmn = Mn/σs). While these ratios are known not to be universal, the underlying principles are not fully understood and relevant theoretical studies are rare, which makes quantitative IP applications difficult. Here we scrutinize the conduction and polarization mechanisms of geomaterials and pinpoint that the two ratios are inherently functions of salinities and frequencies rather than only determined by the properties of the electrical double layer (EDL), hence representative samples from the investigated field must be calibrated in the laboratory and a characteristic frequency should be chosen for their usage. Besides the macro-scale ratios l and lmn, we define two micro-scale ratios χ and χmn directly from the EDL, such that the new ratios exclude the effect of salinity and frequency and offer the opportunity to characterize and monitor changes of the EDL. Our study demonstrates that the existing macro-scale ratios converge toward the values of novel micro-scale ratios at high water salinity.

In a high-pressure injection fault activation experiment conducted at the Mont Terri underground research laboratory in Switzerland, the transmissivity of the Opalinus Clay fault significantly increased due to opening and shearing. The fluid injection, spanning a few hours, generated a 10 m radius fault activation patch. Subsequent pressure pulse tests conducted bi-weekly for a year revealed the gradual return of fault transmissivity to its initial state. The study utilized fluid pressure decay analysis, optical fiber monitoring, continuous active source seismic measurements and borehole displacement sensors for measuring fault displacements. The fault zone exhibited a dilation of approximately 1.4 mm, associated with both normal and tangential movements during activation, resulting in a sudden transmissivity increase from 1 × 10−12 to 3.2 × 10−7 m2/s. Early post-activation, transient compaction and the subsequent slow compaction were observed, transitioning to an extension regime. The pressure pulse tests demonstrated a rapid transmissivity drop by more than two orders of magnitude within the first 10 days, followed by a gradual and less pronounced decrease. Plastic shear and compaction dominated the transmissivity evolution until 70 days after injection ended, followed by a period where additional factors, such as clay mineral swelling, influenced the behavior. Extrapolation suggested a sealing process taking at least 50 years after the initial activation.

Information about evapotranspiration (ET) and its components, that is, evaporation and transpiration, is crucial for a wide range of water and ecosystem management applications. However, partitioning ET into its two components is often challenging because of their spatiotemporal variabilities and lack of process understanding. This study developed a machine learning (ML) framework to shed light on ET processes and assess the relative importance of different drivers by incorporating hydrometeorology and biomass productivity variables. The Shapley Additive Explanations (SHAP) approach was applied to enhance explainability and rank the importance of ET drivers and their components. A total of 62 variables covering hydrometeorological and biomass productivity dimensions were considered from the Reynolds Creek Critical Zone Observatory (CZO) station in Idaho. The variable importance assessment identified the leading drivers individually for evaporation, transpiration and ET (soil water content for evaporation, vapour pressure deficit for transpiration and soil water content for ET). The results further highlighted the value of combining hydrometeorological and biomass productivity variables to achieve better predictability of ET processes.