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At least 307 records · Page 17

An Integrated Feasibility Study of Reservoir Thermal Energy Storage (RTES) in Portland, OR, USA

In regions with long cold overcast winters and sunny summers, Deep Direct-Use (DDU) can be coupled with Reservoir Thermal Energy Storage (RTES) technology to take advantage of pre-existing subsurface permeability to save summer heat for later use during cold seasons. Many aquifers worldwide are underlain by permeable regions (reservoirs) containing brackish or saline groundwater that has limited beneficial use due to poor water quality. We investigate the utility of these relatively deep, slow flowing reservoirs for RTES by conducting an integrated feasibility study in the Portland Basin, Oregon, USA, developing methods and obtaining results that can be widely applied to RTES systems elsewhere. As a case study, we have conducted an economic and social cost-benefit analysis for the Oregon Health and Science University (OHSU), a teaching hospital that is recognized as critical infrastructure in the Portland Metropolitan Area. Our investigation covers key factors that influence feasibility including 1) the geologic framework, 2) heat and fluid flow modeling, 3) capital and maintenance costs, 4) the regulatory framework, and 5) operational risks. By pairing a model of building seasonal heat demand with an integrated model of RTES resource supply, we determine that the most important factors that influence RTES efficacy in the study area are operational schedule, well spacing, the amount of summer heat stored (in our model, a function of solar array size), and longevity of the system. Generally, heat recovery efficiency increases as the reservoir and surrounding rocks warm, making RTES more economical with time. Selecting a base-case scenario, we estimate a levelized cost of heat (LCOH) to compare with other sources of heating available to OHSU and find that it is comparable to unsubsidized solar and nuclear, but more expensive than natural gas. Additional benefits of RTES include energy resiliency in the event that conventional energy supplies are disrupted (e.g., natural disaster) and a reduction in fossil fuel consumption resulting in a smaller carbon footprint. Key risks include reservoir heterogeneity and a possible reduction in permeability through time due to scaling (mineral precipitation). Lastly, a map of thermal energy storage capacity for the Portland Basin yields a total of 43,400 GWh, suggesting tremendous potential for RTES in the Portland Metropolitan Area.

14 SOLAR ENERGY↗

Stepwise Dynamic Calibration of a Hydromechanical Simulation Using Time-Lapse Vertical Seismic Profile

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse Vertical Seismic Profiling (VSP) integration. The selected study site is the 13-10A injector well within the ongoing CO2-EOR operation of the Farnsworth Field Unit. The Time-lapse VSP dataset carries the combined effects of fluid substitution and mean effective stress changes, thereby providing a dataset amenable for the calibration of production and injection-induced stress changes. The concept is similar to calibrating a reservoir simulation model in that the process honor real field data to set up an inverse problem. The solution optimizes the independent and impactful geomechanical parameters that replicate the observed time-lapse seismic velocity changes. This stress calibration is enabled by 4D geomechanical modeling and the VSP Integration workflow. This calibration benefits from extensive geological, geophysical and geomechanical characterization through 3D seismic data, geophysical well logs, and core assessed as part of the 1D MEM conducted on the 13-10A subject well. These data are used to develop a site-specific rock physics model. The Biot Gassmann workflow combines rock physics and reservoir simulation outputs to determine the fluid substitution contribution to seismic velocity change. Additionally, modeled seismic velocity attributed to mean effective stress are determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from the ultrasonic seismic velocity measurements on the extracted Morrow B core. A penalty function is then formed between the modeled seismic velocities and the observed time-lapse VSP dataset. Four independent and impactful geomechanical parameters have been determined. These are the bulk modulus and shear modulus for zero porosity and the shear and compressional seismic velocity to mean effective stress derivatives. The dataset of numerous coupled hydromechanical- geomechanical simulation realizations is built by combining variations of the four stated geomechanical parameters. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer are used to converge on the optimal geomechanical parameters. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling.

02 PETROLEUM↗

The Influence of Shallow Subsurface Properties on Particle Motion in Acoustic-Seismic Coupling

Atmospheric acoustic waves transmit energy into the solid Earth through air-to-ground coupling. These waves are recorded by seismic sensors and provide insight into both atmospheric phenomena and subsurface properties. Interpreting these signals is often challenging because they are modulated by subsurface structure and the incidence angle of the acoustic wave. This study examines acoustic--seismic coupling generated by the 2012 Camp Minden Explosion, which was recorded by hundreds of seismoacoustic stations. We apply a novel technique to quantify the seismic particle motion, model coupled waves with a propagator matrix approach, and apply a Bayesian inversion to infer properties of the shallow subsurface. Our analysis reveals that prograde motion is widespread and focused in low shear-wave velocity regions, such as the Mississippi Embayment, and retrograde motion is more common in higher shear-velocity areas. Inversion results at some stations produce plausible subsurface models with strong waveform fits, while inversions at other sites are less successful. These results indicate prograde particle motion in air-to-ground coupled waves is more prevalent than previously recognized and may serve as a diagnostic for shallow velocity structure. Our comprehensive modeling and inversion framework provides a potential method to extract layered near-surface properties from acoustic-seismic coupling observations.

58 GEOSCIENCES↗

Identifying geologic characteristics and operational decisions to meet global carbon sequestration goals

Geologic carbon sequestration is the process of injecting and storing CO 2 in subsurface reservoirs and is an essential technology for global environmental security (e.g., climate change mitigation) and economic security (e.g., CO 2 tax credits). To meet energy, economic, and environmental goals, society will have to identify vast volumes of high-capacity, low-cost, and viable storage reservoirs for sequestering CO 2 . In turn, this requires understanding how major geologic characteristics (such as reservoir depth, thickness, permeability, porosity, and temperature) and design and operational decisions (such as injection well spacing) impact CO 2 injection rates, storage capacity, and economics. Although many numerical simulation tools exist, they cannot repeat the required thousands or millions of simulations to identify ideal reservoir properties and the sensitivity and interaction between geologic parameters and operational decisions. Here, we use SCO 2 T—a fast-running, reduced-order modeling framework—to explore the sensitivity of major geologic parameters and operational decisions to engineering (CO 2 injection rates, plume dimensions, and storage capacities and effectiveness) and costs. Our results show, for the first time, benefits and impacts such as allowing CO 2 plumes to overlap, how different well spacing patterns affect CO 2 sequestration, the effects on costs of including brine treatment and disposal, and the effect of restricting injection rates to 1 MtCO 2 per y based on well limitations. We reveal multiple novel and unintuitive findings including: (i) deeper reservoirs have reduced carbon sequestration costs until injection rates reach 1 MtCO 2 per y, at which point deeper reservoirs become more expensive, (ii) thicker formations allow for increased injection rates and storage capacity, but thickness barely impacts plume areas, (iii) higher geothermal gradients result in reduced sequestration costs, unless brine treatment/disposal costs are included, at which point reservoirs having lower geothermal gradients are more economical because they produce less brine for each unit of injected CO 2 , and (iv) allowing plumes to overlap has a significantly positive impact of increasing storage capacities but has only a small influence on reducing sequestration costs. Altogether, our results illustrate new scientific conclusions to help identify suitable sites to inject and store CO 2 , to help understand the complex interaction between geology and resulting costs, and to help support the pursuit of meeting global sequestration targets.

58 GEOSCIENCES↗

Subsurface microbial communities as a tool for characterizing regional-scale groundwater flow

Subsurface microbial community distribution patterns are influenced by biogeochemical and groundwater fluxes and may inform hydraulic connections along groundwater-flow paths. This study examined the regional-scale microbial community of the Death Valley Regional Flow System and evaluated whether subsurface communities can be used to identify groundwater-flow paths between recharge and discharge areas. Samples were collected from 36 sites in three groundwater basins: Pahute Mesa–Oasis Valley (PMOV), Ash Meadows (AM), and Alkali Flat–Furnace Creek Ranch (AFFCR). Microbial diversity within and between communities varied by location, and communities were separated into two overall groups that affiliated with the AM and PMOV/AFFCR basins. Network analysis revealed patterns between clusters of common microbes that represented groundwaters with similar geochemical conditions and largely corroborated hydraulic connections between recharge and discharge areas. Null model analyses identified deterministic and stochastic ecological processes contributing to microbial community assemblages. Most communities were more different than expected and governed by dispersal limitation, geochemical differences, or undominating processes. However, certain communities from sites located within or near the Nevada National Security Site were more similar than expected and dominated by homogeneous dispersal or selection. Overall, the (dis)similarities between the microbial communities of DVRFS recharge and discharge areas supported previously documented hydraulic connections between: (1) Spring Mountains and Ash Meadows; (2) Frenchman and Yucca Flat and Amargosa Desert; and (3) Amargosa Desert and Death Valley. However, only a portion of the flow path between Pahute Mesa and Oasis Valley could be supported by microbial community analyses, likely due to well-associated artifacts in samples from the two Oasis Valley sites. This study demonstrates the utility of combining microbial data with hydrologic, geologic, and water-chemistry information to comprehensively characterize groundwater systems, highlighting both strengths and limitations of this approach.

54 ENVIRONMENTAL SCIENCES↗

Iodine effective diffusion coefficients through volcanic rock: Influence of iodine speciation and rock geochemistry

Accurate prediction of the subsurface transport of iodine species is important for the assessment of long-term nuclear waste repository performance, as well as monitoring compliance with the Comprehensive Nuclear-Test-Ban Treaty, given that radioiodine decays into radioxenon. However, the transport of iodine through intact geologic media is not well understood, compromising our ability to assess risk associated with radioiodine migration. The current study's goal is to quantify the matrix diffusion of iodine species through saturated volcanic rock, with particular attention paid to the redox environment and potential speciation changes. Here, diffusion experiments were run for iodide through lithophysae-rich lava, lithophysae-poor lava, and welded tuff, whereas iodate diffusion was studied through welded tuff. Iodine transport was compared with a conservative tracer, HDO, and effective diffusion coefficients were calculated. Likely due to a combination of size and anion exclusion effects, iodine species diffused more slowly than the conservative tracer through all rock types tested. Furthermore, oxidation of iodide to iodate was observed in the lithophysae-poor lava, affecting transport. Results provide much needed data for subsurface transport models that predict radioiodine migration from underground sources, and indicate the pressing need for geochemical and redox interactions to be incorporated into these models.

58 GEOSCIENCES↗

NNSA-IAEC Science Area V Environmental ISR: Waste Management and Subsurface Science (Final Report FY18-FY20)

In August 2017, the U.S. National Nuclear Security Administration (NNSA) and the Israel Atomic Energy Commission (IAEC) launched a joint waste management program to evaluate the feasibility of siting a radioactive waste repository at intermediate depths in Israel. The bilateral collaboration involves three National Laboratories (LLNL, LANL, and Sandia), and the Nuclear Research Center, Negev, Geological Survey of Israel, and Ben Gurion University in Israel. This research is designed to assist with the evaluation of locations for an intermediate nuclear waste repository in Israel. This final report is a high-level summary of the results from the past three years by the team that worked on the WM-2: Radionuclide colloid-facilitated transport in fractured carbonate rock project for Science Area V, Environmental ISR: Subsurface Science and Waste Management. We have completed all of our tasks and met all of our milestones. MW-2 had three integrated tasks. Task 1 was laboratory experiments investigating colloid transport of radionuclides in natural fractured carbonate rocks from the Avdat formation, Israel. Task 2 was field experiments injecting radionuclide analogues pre-sorbed to clay colloids into fractured carbonate rock, and task 3 was numerical modeling of laboratory and field experimental results to assess the importance of colloids in the migration of relevant radionuclides. This task was incorporated into tasks 1 and 2. A 4 th task was initiated in FY20, to investigate the role of organics in facilitating radionuclide transport under the same conditions explored in task 1 due to the high organic content of the rocks being investigated for the immediate borehole locations. Preliminary results will be summarized here and the work will continue in FY21-23. The overall objective of this research is to evaluate the role of colloids (naturally occurring < 1 micron particles) in facilitating the transport of long-lived radionuclides from a nuclear waste repository situated in fractured carbonate rocks. Currently little data exists on radionuclide transport in carbonate rocks, but this is the main rock type available for siting a repository in Israel. Laboratory experiments were carried out in both Israel and the U.S., field experiments have taken place in Israel, and reactive transport modeling involved LLNL, LANL and Israel partner institutions. LLNL hosted a graduate student, Emily Tran, from Ben Gurion University in FY18 and FY19 and much of the work presented here was part of her PhD research.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Magmatic Intrusions and a Hydrothermal Origin for Fluvial Valleys on Mars

Numerical models of Martian hydrothermal systems demonstrate that systems associated with magmatic intrusions greater than several hundred cubic kilometers can provide sufficient groundwater outflow to form the observed fluvial valleys, if subsurface permeability exceeds about 1.0 darcy. Groundwater outflow increases with increasing intrusion volume and subsurface permeability and is relatively insensitive to intrusion depth and subsurface porosity within the range considered here. Hydrothermally-derived fluids can melt through 1 to 2 km thick ice-rich permafrost layers in several thousand years. Hydrothermal systems thus provide a viable alternative to rainfall for providing surface water for valley formation. This mechanism can form fluvial valleys not only during the postulated early warm, wet climatic epoch, but also during more recent epochs when atmospheric conditions did not favor atmospheric cycling of water. The clustered distribution of the valley networks on a given geologic surface or terrain unit of Mars may also be more compatible with localized, hydrothermally-driven groundwater outflow than regional rainfall. Hydrothermal centers on Mars may have provided appropriate environments for the initiation of life or final oases for the long-term persistence of life.

Gulick, Virginia C↗

Salt Distribution from Freezing Intrusions in Ice Shells on Ocean Worlds: Application to Europa

Several icy moons and dwarf planets appear to have hosted subsurface liquid water. Liquid water intruding upwards into the icy outer shells of these worlds freezes, forming ice and (from ocean solutes) non-ice solids. Here, we model concentrated aqueous solutions below 273 K to simulate the compositional evolution of freezing spherical intrusions. Starting solutions are based on five previously reported compositional end members for Europa's ocean. For moderate-pH end members dominated by chloride, sulfate, and/or carbonate, the solids formed include Ca-, Mg-, and Na-sulfates and -carbonates, as well as Na- and K-chlorides. For silica-rich, high-pH end members, abundant amorphous silica forms with, potentially, similarly abundant NaOH and KOH. We further develop a new numerical model to compute the spatial distribution of the formed solids and residual brine as freezing progresses. If non-ice solids settle to the bottom, their deposits tend to have stacked hourglass shapes, widening each time the crystallization temperature of a new solid is reached. We discuss the applicability of this model to vertical fractures and global freezing of a subsurface ocean. These results inform (i) how compositional heterogeneities may affect the thermophysical properties of ice shells, which in turn influence convective and cryovolcanic transport, (ii) the compatibility of brine pockets with physicochemical conditions suitable for microbial life, and (iii) possible measurements of compositional heterogeneities within ice shells by spacecraft such as NASA's Europa Clipper and ESA's JUICE missions. The methodology developed here is applicable to other ice-covered ocean worlds.

Planetary structure↗

Technoeconomic Analysis of Infrastructure Buildout Scenarios

The success of CCUS deployment in the southeast will depend on the optimized pipeline network from CO 2 point sources to geologic sinks for CO 2 storage. An optimal pipeline framework will reduce both environmental impacts and pipeline building cost. However, finding an optimal pipeline/transport infrastructure design is a non-trivial task and requires simultaneous usage of large volumes of data, computational resources, and a state-of-the-art simulator. Such a transport infrastructure model must consider point sources for CO 2 capture and associated volumes, sinks for CO 2 storage, and transportation from source to sink via pipeline networks. These considerations must be addressed simultaneously and systemically in an optimization process, in which a defined objective function (i.e., capital, variable CO 2 capture, transport, and storage cost function) is required to be minimized with the consideration of practical constraints (e.g., CO 2 flow through pipelines is less than the maximum capacity). Although optimization has been widely used in subsurface resources production and CO 2 storage, its application in large scale CCUS infrastructure design is rarely reported in the literature. SimCCS, developed by Los Alamos National Laboratory, is an open-source CCUS pipeline infrastructure design toolset that facilitates the optimization of pipeline infrastructure networks.

99 GENERAL AND MISCELLANEOUS↗

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES↗

Differential Muon Tomography to Continuously Monitor Changes in the Composition of Subsurface Fluids

Muon tomography has been used to seek hidden chambers in Egyptian pyramids and image subsurface features in volcanoes. It seemed likely that it could be used to image injected, supercritical carbon dioxide as it is emplaced in porous geological structures being used for carbon sequestration, and also to check on subsequent leakage. It should work equally well in any other application where there are two fluids of different densities, such as water and oil, or carbon dioxide and heavy oil in oil reservoirs. Continuous monitoring of movement of oil and/or flood fluid during enhanced oil recovery activities for managing injection is important for economic reasons. Checking on leakage for geological carbon storage is essential both for safety and for economic purposes. Current technology (for example, repeat 3D seismic surveys) is expensive and episodic. Muons are generated by high- energy cosmic rays resulting from supernova explosions, and interact with gas molecules in the atmosphere. This innovation has produced a theoretical model of muon attenuation in the thickness of rock above and within a typical sandstone reservoir at a depth of between 1.00 and 1.25 km. Because this first simulation was focused on carbon sequestration, the innovators chose depths sufficient for the pressure there to ensure that the carbon dioxide would be supercritical. This innovation demonstrates for the first time the feasibility of using the natural cosmic-ray muon flux to generate continuous tomographic images of carbon dioxide in a storage site. The muon flux is attenuated to an extent dependent on, amongst other things, the density of the materials through which it passes. The density of supercritical carbon dioxide is only three quarters that of the brine in the reservoir that it displaces. The first realistic simulations indicate that changes as small as 0.4% in the storage site bulk density could be detected (equivalent to 7% of the porosity, in this specific case). The initial muon flux is effectively constant at the surface of the Earth. Sensitivity of the method would be decreased with increasing depth. However, sensitivity can be improved by emplacing a greater array of particle detectors at the base of the reservoir.

Coleman, Max↗

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗

Risk Considerations of Transitioning CO2-EOR Field to CO2 storage Field: Case Study

In the United States (U.S.), carbon dioxide (CO2) injection wells at EOR sites are currently regulated as Class II wells under the U.S. Environmental Protection Agency’s (EPA) Underground Injection Control (UIC) program while dedicated geological CO2 storage (GCS) wells are considered Class VI wells. A CO2-EOR facility considering a transitioning from tertiary oil recovery to injecting CO2 for the primary purpose of long-term storage is required to obtain a Class VI permit where this transition poses an increased risk to underground sources of drinking water. This study considers how transitioning operations from CO2-EOR to storage can impact reservoir plume and pressure transient in the storage envelope, and how these changes could impact area of review and potential unwanted fluid migration. We developed a case study to assess subsurface response and leakage risks associated with a representative, hypothetical operation in a carbonate reservoir. This reservoir transitions from tertiary hydrocarbon recovery to dedicated GCS. Reservoir simulations were run for a set of credible CO2-EOR scenarios to estimate distributions of fluids phases and pressures throughout the model domain after CO2 flooding as well as forecasting the behavior of the reservoir after the transition to a dedicated storage phase. The evolutions from all simulated scenarios were used as the basis for leakage risk quantification using the National Risk Assessment Partnership’s Open-Source Integrated Assessment Model (NRAP-Open-IAM) with a novel reduced-order model to estimate time-dependent leakage of CO2, brine, and hydrocarbon fluids through potentially leaky wells. Results include a description of reservoir response, an estimate of the areal extent that could potentially be impacted by leakage to underground sources of drinking water, and estimates of the magnitude of potential leakage. Considerations for dedicated storage injection well selection, injectivity, and injection scheme performance and potential leakage risk are presented, with implications for risk assessment of well transition discussed. This study presents a risk-based workflow for the Class II to Class VI well transition. Integrating credible numerical simulation of viable CO2-EOR to dedicated CO2 storage with quantitative risk assessment tools, such as the NRAP-Open-IAM, will provide a valuable means to devise operational scenarios and inform decision-making related to storage benefit, leakage risk, and liability. Presented at the SPE/AAPG/SEG Carbon Capture Utilization and Storage Conference in Houston, TX, March 11-13, 2024.

Liu, Guoxiang↗

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

CO2 geologic storage↗

Three‐Dimensional Permeability Inversion Using Convolutional Neural Networks and Positron Emission Tomography

Abstract Quantification of heterogeneous multiscale permeability in geologic porous media is key for understanding and predicting flow and transport processes in the subsurface. Recent utilization of in situ imaging, specifically positron emission tomography (PET), enables the measurement of three‐dimensional (3‐D) time‐lapse radiotracer solute transport in geologic media. However, accurate and computationally efficient characterization of the permeability distribution that controls the solute transport process remains challenging. Leveraging the relationship between local permeability variation and solute advection behavior, an encoder‐decoder based convolutional neural network (CNN) is implemented as a permeability inversion scheme using a single PET scan of a radiotracer pulse injection experiment as input. The CNN can accurately capture the 3‐D spatial correlation between the permeability and the radiotracer solute arrival time difference maps in geologic cores. We first test the inversion accuracy using synthetic test datasets and then test the accuracy on a suite of experimental PET imaging datasets acquired on four different geologic cores. The network‐predicted permeability maps from the geologic cores are used to parameterize forward numerical models that are directly compared with the experimental PET imaging data. The results indicate that a single trained network can generate robust 3‐D permeability inversion maps in seconds. Numerical models parameterized with these permeability maps closely capture the experimentally observed solute arrival time behavior. This work provides an unprecedented approach for efficiently characterizing multiscale permeability heterogeneity in complex geologic samples.

54 ENVIRONMENTAL SCIENCES↗

Assessing Habitability: Lessons from the Phoenix Mission

The Phoenix mission's key objective was to search for a habitable zone. The Phoenix lander carried a robotic arm with digging scoop to collect soil and icy material for analysis with an instrument payload that included volatile mineral and organic analysis(3) and soil ionic chemistry analysis (4). Results from Phoenix along with theoretical modeling and other previous mission results were used to evaluate the habitability of the landing site by considering four factors that characterize the environments ability to support life as we know it: the presence of liquid water, the presence of an energy source to support metabolism, the presence of nutrients containing the fundamental building blocks of life, and the absence of environmental conditions that are toxic to or preclude life. Phoenix observational evidence for the presence of liquid water (past or present) includes clean segregated ice, chemical etching of soil grains, calcite minerals in the soil and variable concentrations of soluble salts5. The maximum surface temperature measured was 260K so unfrozen water can form only in adsorbed films or saline brines but warmer climates occur cyclically on geologically short time scales due to variations in orbital parameters. During high obliquity periods, temperatures allowing metabolism extend nearly a meter into the subsurface. Phoenix discovered ~1%w/w perchlorate salt in the soil, a chemical energy source utilized by a wide range of microbes. Nutrient sources including C, H, N, O, P and S compounds are supplied by known atmospheric sources or global dust. Environmental conditions are within growth tolerance for terrestrial microbes. Summer daytime temperatures are sufficient for metabolic activity, the pH is 7.8 and is well buffered and the projected water activity of a wet soil will allow growth. In summary, martian permafrost in the north polar region is a viable location for modern life. Stoker et al. presented a formalism for comparing the habitability of various regions visited to date on Mars that involved computing a habitability probability, defined as the product of probabilities for the presence of liquid water (P(sub lw)), energy (P(sub e)), nutrients (P(sub ch)), and a benign environment (P(sub b)). Using this formalism, they argued that the Phoenix site was the most habitable of any site visited to date by landed missions and warranted a follow up mission to search for modern evidence of life. This paper will review that conclusion in view of more recent information from the Mars Exploration Rovers and Mars Science Lander missions.

Stoker, Carol R.↗

2020 Innovation Fair Project: Is Midlatitude Ground Ice on Mars Habitable for Life?

The objective of this project was to perform a modeling study to evaluate whether midlatitude ground ice on Mars that could support life in geologically recent times. Recent studies from Mars orbital imaging, ground penetrating radar data, and infrared thermal data have revealed that large areas of Mars at latitudes higher than 40o N host near surface ground ice. Past climate cycles driven by orbital oscillations are expected to result in the distribution of ground ice changing over geologically recent history. The insolation at any location on Mars varies over time due to quasi-periodic changes in its orbital parameters (obliquity, eccentricity, perihelion longitude). The last 2 MY Mars obliquity varied between 15o and 35o but 5 MY ago varied between 24o and 48o with the average obliquity being 36o. The current low obliquity Mars atmosphere is dryer than average conditions. Recent work (Mellon and Sizemore Icarus (2022) 371;114667) has shown that repeatedly over the last 2 MY ground ice was present even at low Northern latitudes. The ice table depth is controlled by diffusive equilibrium with water vapor in the atmosphere, which also varies with orbital parameters. Determining the surface temperature and water vapor abundance requires a sophisticated climate model that was developed at NASA Ames, and results of high obliquity climate simulations will be used in the study. Work is underway to evaluate the subsurface thermal conditions in ice-rich areas of Mars during high obliquity periods to determine whether, where, and when the subsurface ice becomes warm enough to support metabolic processes or growth of terrestrial organisms.

Carol R Stoker↗