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A dissertation by Chidera O Iloejesi submitted to the Graduate Faculty of Auburn University In partial fulfillment of the requirements for the Degree of Doctor of Philosophy
Small-scale heterogeneities can significantly affect the fate of the CO 2 plume and trapping during CO 2 migration. We conducted geologic carbon storage field-scale simulations to investigate the impact of small-scale heterogeneities on plume dynamics and trapping performance. Small-scale heterogeneities have been shown to increase the amount of trapped CO 2 during buoyancy-driven flow. The trapped CO 2 saturation is validated by previous sandbox experimental work during buoyancy-driven flow in realistic heterogeneous domains and is implemented through the critical CO 2 saturation parameter (i.e., the first non-zero value in the drainage CO 2 relative permeability curve). Depending on the type and degree of heterogeneity, various critical CO 2 saturation values are exhibited. Furthermore, we investigated the effect of small-scale heterogeneities when multiple capillary pressure models are employed. This study demonstrates that an increase in critical CO 2 saturation reduces the CO 2 plume size and lateral extent, accompanying an increase in residual trapping and a decrease in solubility trapping. Lastly, we show that independent of the capillary pressure model used, an increase in critical saturation leads to similar CO 2 plume dynamics distribution and trapping performance. These results emphasize the importance of quantifying the effect of small-scale heterogeneity as they affect the large-scale behavior of the CO 2 plume.
Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.
Storage of water within soil pores of the root zone introduce memory effects in the dynamics of soil moisture that are considerably longer than the integral timescale of many atmospheric processes. Thus, hydro-climatic states can be “sustained” through land-surface heat and water vapor fluxes primarily because they can “feed off” on this long-term soil moisture memory. Root-zone soil moisture memory is only but one feature characterizing the spectrum of soil moisture dynamics, which is analyzed here using a combination of long-term measurements and models. In particular, the spectrum of root-zone soil moisture content in a Mediterranean ecosystem is examined using 14-years of half-hourly measurements. A distinguishing hydro-climatic feature in such ecosystems is that sources (mainly rainfall) and sinks (mainly evapotranspiration) of soil moisture are roughly out of phase with each other. For over 4 decades of time scales and 7 decades of energy, the canonical shape of the measured soil moisture spectrum is shown to be approximately Lorentzian determined by the soil moisture variance and its memory but with two exceptions: the occurrences of a peak at diurnal-to-daily time scales and a weaker peak at near annual time scales. Model calculations and spectral analysis demonstrate that diurnal and seasonal variations in hydroclimate forcing responsible for variability in evapotranspiration had minor impact on the normalized shape of the soil moisture spectrum. However, their impact was captured by adjustments in the temporal variance. These findings indicate that precipitation and not evapotranspiration variability dominates the multi-scaling properties of soil moisture variability consistent with prior climate model simulations. Furthermore, the soil moisture memory inferred by the annual peak of soil moisture (340 d) is consistent with climate model simulations, while the memory evaluated from the loss function of a linearized mass balance approach leads to a smaller value (50 d), highlighting the effect of weak non-stationarity on soil moisture variability.
The Basin-Scale Structural Features database provides spatial datasets of faults, fractures, folds, and earthquakes compiled from public, authoritative sources (e.g., U.S. Geological Survey and State Geological Surveys) and aggregated into derivative forms to support subsurface assessments. Recognizing that characterizing basin-scale structural features requires interpreting data that are often ambiguous or lack key information, the source data were evaluated using a knowledge-data framework and geospatial fuzzy logic method (Justman et al., 2020) to represent both measured (observed) and predicted (inferred or potential) structural features as derivative datasets. This workflow employs conceptual models for known structural features and predicted structural features, incorporating geospatial data to estimate potential, even with limited data. The aim is to aid and support an understanding of basin-scale features and identify potential gaps in data and knowledge. As of 4/30/2025, the database includes resources for nine sedimentary basins: Appalachian, Denver, U.S. Gulf Coast, Illinois, Michigan, Permian, Sacramento, San Joquin and Williston. The database is organized by basin and then data category: 1) Faults, fractures, folds, 2) Earthquakes, 3) Topographic, 4) Structural contours and isopachs, 5) Geophysical, and 6) Structural feature density assessment maps.
Abstract. The width of the Inter-Tropical Convergence Zone (ITCZ) affects tropical rainfall, Earth's albedo, large-scale circulation, and climate sensitivity. To better understand the ITCZ width and its effects on global climate, we present a protocol to force changes in ITCZ width in climate models. Starting from an aquaplanet configuration with a slab ocean, adding surface heat fluxes in the deep tropics forces the ITCZ to narrow, and subtracting them causes it to widen. The protocol successfully generates changes in ITCZ width in all four climate models used in this study. ITCZ width in each model responds linearly to forcing magnitude and sign. Comparing across the four climate models, a response to varying ITCZ width that is remarkably consistent among models is the ITCZ strength, which is greater the narrower the ITCZ. On the other hand, the effect of varying ITCZ width on climate sensitivity is divergent among our four models, varying even in sign. Results from this pilot study highlight the connections between surface fluxes, ITCZ width, and the wider climate. A comprehensive model intercomparison project (MIP) has the potential to advance understanding of both the physical processes shaping ITCZ width and its influence on remote atmospheric circulations and global climate.
Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local (<5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source (<5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications.
Abstract Background Total DNA (intracellular, iDNA and extracellular, eDNA) from ancient permafrost records the mixed genetic repository of the past and present microbial populations through geological time. Given the exceptional preservation of eDNA under perennial frozen conditions, typical metagenomic sequencing of total DNA precludes the discrimination between fossil and living microorganisms in ancient cryogenic environments. DNA repair protocols were combined with high throughput sequencing (HTS) of separate iDNA and eDNA fraction to reconstruct metagenome-assembled genomes (MAGs) from ancient microbial DNA entrapped in Siberian coastal permafrost. Results Despite the severe DNA damage in ancient permafrost, the coupling of DNA repair and HTS resulted in a total of 52 MAGs from sediments across a chronosequence (26–120 kyr). These MAGs were compared with those derived from the same samples but without utilizing DNA repair protocols. The MAGs from the youngest stratum showed minimal DNA damage and thus likely originated from viable, active microbial species. Many MAGs from the older and deeper sediment appear related to past aerobic microbial populations that had died upon freezing. MAGs from anaerobic lineages, including Asgard archaea, however exhibited minimal DNA damage and likely represent extant living microorganisms that have become adapted to the cryogenic and anoxic environments. The integration of aspartic acid racemization modeling and metaproteomics further constrained the metabolic status of the living microbial populations. Collectively, combining DNA repair protocols with HTS unveiled the adaptive strategies of microbes to long-term survivability in ancient permafrost. Conclusions Our results indicated that coupling of DNA repair protocols with simultaneous sequencing of iDNA and eDNA fractions enabled the assembly of MAGs from past and living microorganisms in ancient permafrost. The genomic reconstruction from the past and extant microbial populations expanded our understanding about the microbial successions and biogeochemical alterations from the past paleoenvironment to the present-day frozen state. Furthermore, we provided genomic insights into long-term survival mechanisms of microorganisms under cryogenic conditions through geological time. The combined strategies in this study can be extrapolated to examine other ancient non-permafrost environments and constrain the search for past and extant extraterrestrial life in permafrost and ice deposits on Mars.
Mass transport within porous structures is a ubiquitous process in biological, geological, and technological systems. Despite the importance of these phenomena, there is no comprehensive theory that describes the complex and diverse transport behavior within porous environments. While the porous matrix itself is generally considered a static and passive participant, many porous environments are in fact dynamic, with fluctuating walls, pores that open and close, and dynamically changing cross-links. While diffusion has been measured in fluctuating structures, notably in model biological systems, it is rarely possible to isolate the effect of fluctuations because of the absence of control experiments involving an identical static counterpart, and it is generally impossible to observe the dynamics of the structure. In this paper, we present a direct comparison of the diffusion of nanoparticles of various sizes within a trackable, fluctuating porous matrix and a geometrically equivalent static matrix, in conditions spanning a range of regimes from obstructed to highly confined. The experimental system comprised a close-packed layer of colloidal spheres that were either immobilized to a planar surface or allowed to fluctuate locally, within the space defined by their nearest neighbors. Interestingly, the effective long-time diffusion coefficient was approximately 35–65% greater in the fluctuating porous matrix than in the static one (depending on the size of the nanoparticle probes), regardless of the geometric regime. This was explained by considering the enhancing effects of matrix fluctuations on the short-time diffusion coefficient and cooperative “gate-opening” motions of matrix particles and nanoparticle probes.
In December 2018, a partnership between the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL), the Japan Oil, Gas and Metals National Corporation (JOGMEC), and the U.S. Geological Survey (USGS) successfully drilled and logged the Hydrate-01 Stratigraphic Test Well (STW) in the greater Prudhoe Bay oil field on Alaska North Slope. The logging-while-drilling (LWD) data confirmed the presence of gas hydrate-bearing reservoirs within two sand reservoirs (Unit B and Unit D) that are suitable targets for future testing. The interpreted log data and core sample measurements were used to create reservoir models for the Prudhoe Bay Unit (PBU) Kuparuk 7-11-12 Site. The models combine both gas hydrate-bearing sections in Unit B and Unit D together with the intermediate Unit C and over- and underburden sands and shales. The vertical heterogeneity in porosity, gas hydrate saturation, and permeability distributions for reservoir and non-reservoir units was implemented using fine mesh discretization. The depressurization method was applied to Unit B to induce gas hydrate destabilization at constant bottom hole pressure (BHP) values. The results of the numerical simulations support the development of production scenarios, well design, surface facilities, and field test procedures with the main goal to perform efficient and safe scientific production testing. Project results contribute to the knowledge base of permafrost-associated gas hydrate accumulations as a future energy source.
Although magmatic- and metamorphic- derived fluids are widely recognized mineralizing agents, the role of crustal architecture in defining source and sink zones within the middle to lower crust and upper mantle of ancient orogens remains enigmatic. The globally largest and best-preserved Archean greenstone belts lie in the Superior Province, Canada. They provide an ideal location to investigate the influence of igneous construction and subsequent syn-deformational plutonism and metamorphism on the localization of metal-rich melts and fluids throughout the crustal column. Integration of three-dimensional magnetotelluric modelling and seismic reflection sections across the Abitibi subprovince reveals details of a 'whole-of-crust' magmatic and hydrothermal system. East-west low resistivity structures broadly underlie the surface traces of the major deformation zones that are host to significant gold endowment (>200 Moz), while mid-crustal cross trends suggest mineralized fluids flowed along 'pipes' within fault planes. Most low resistivity structures are inferred to represent domains containing interconnected zones of graphite and/or sulfide. Furthermore, these delineate relict mantle source/transit domains and crustal pathways enriched by the flow of magmas or metamorphic fluids genetically related to a late-stage pulse of ore-bearing magmatism, possibly as a result of slab break-off or delamination. Using the combined MT and seismic data, we develop a 3-D crustal-scale model which highlights how evolving orogenic architecture-controlled mass transfer and metallogenic processes developed.
Supercritical (sc) CO 2 in geologic carbon sequestration (GCS) can chemically and mechanically deteriorate wellbore cement, raising concerns for long-term operations. In contrast to the conventional view of “sulfate attack” on cement, we found that adding 0.15 M sulfate to the acidic brine can significantly reduce the impact of scCO 2 attack on Portland cement, resulting in stronger cement than that found in a sulfate-free system. Scanning electron microscopy revealed a decreased total attack depth in reacted cement in the presence of sulfate. With a newly defined minimum porosity term in reactive transport modeling, our model suggests that sulfate caused CaCO 3 to fill more nanopore spaces in the cement. Small angle X-ray scattering experiments also showed that sulfate can decrease the pore sizes of the carbonate layer. The results suggest that the interactions between sulfate and cement can generate a less porous CaCO 3 layer, which better resists acidic brine. Using this mechanism as a proof-of-concept, we tested the incorporation of sodium sulfate into Portland cement and synthesized new cement composites that show stronger resistance against scCO 2 attacks. Finally, these newly discovered interfacial interactions between CaCO 3 and sulfate provide new insights into engineering mechanically strong and green materials for safer GCS.
Abstract Cornell University intends to use a deep direct-use geothermal system to heat its Ithaca, New York, campus. In preparation for this project, the Cornell Seismic Network has been monitoring the background seismicity in this intraplate region since 2019. From January 2020 to June 2023, 95 events were detected within 20 km of the proposed geothermal well site, with local magnitudes ranging from −1.02 to 0.56. None of these events appear in regional or national catalogs. Events locate in a narrow geographic band, with one-fourth exhibiting multimodal hypocentral probability peaks both near the surface and at 1–4 km depth. We relocate events with a joint hypocenter and 1D velocity model inversion, in addition to a fully nonlinear method, and then compare observations with synthetic waveforms. Together, these approaches provide strong evidence for >95% of events locating at the surface or within the 3-km-thick sedimentary sequence. We explore how anthropogenic activity and regional topographic stress may contribute to frequent surficial events. This information is critical for characterizing the background microseismicity for comparison during future geothermal operations. Ithaca’s geology of Paleozoic sediments overlying Precambrian crystalline basement is typical of many continental interiors, so these results also provide insight into intraplate microseismicity patterns.
Summary There has been substantial controversy concerning the role of geological carbon storage (GCS) in sequestering anthropogenic carbon emissions to mitigate climate change and global warming. Arguments center on the inability to monitor a geological storage site precisely and continuously, especially highlighting the associated costs and spatiotemporal trade-offs when using conventional subsurface monitoring techniques (well logs, core samples, chemical tracers, and 4D seismics). Active surveillance of GCS sites is essential for managing and mitigating potential leaks but is also required by regulation. With the goal of enhancing the monitoring capability at GCS sites, we present a rock physics-based joint data assimilation model to study a popular GCS site at Cranfield, Mississippi, USA. Synthetic continuous active-source seismic monitoring (CASSM) data (in the form of Vp and Qp measurements) and wellbore pressure monitoring data are assimilated with an ensemble of reservoir realizations to monitor gas saturation and reservoir pressure changes over a period of 100 years. Synthetic seismic attributes are generated using rock physics models (RPMs) and wellbore pressure monitoring data are extracted from the ground truth. Two assimilation methods, ensemble Kalman filter (EnKF) and ensemble Kalman smoother (EnKS), are tested in an observation system simulation experiment (OSSE) environment to assess the prediction accuracy of the individual and composite observation systems. The joint monitoring system achieves more accurate estimates of gas saturation and pressure, across the time span from start of injection to end of forecast, as compared to a single type of monitoring tool and irrespective of data assimilation algorithm choice. These results indicate that jointly assimilated data from two types of sensors (in this case, crosswell seismic and downhole pressure) may lead to a more risk-reducing monitoring design. One would expect that more data, vis-à-vis inclusion of a new sensor type, will improve the accuracy of any GCS monitoring system. However, from a practical standpoint, one important question is whether such a gain in accuracy is worth the additional cost associated with the new sensor. This paper focuses on quantifying the gain in accuracy, such that a practitioner can answer this question.
Abstract Land surface models (LSMs) play a crucial role in elucidating water and carbon cycles by simulating processes such as plant transpiration and evaporation from bare soil, yet calibration often relies on comparing LSM outputs of landscape total evapotranspiration ( ET ) and discharge with measured bulk fluxes. Discrepancies in partitioning into component fluxes predicted by various LSMs have been noted, prompting the need for improved evaluation methods. Stable water isotopes serve as effective tracers of component hydrologic fluxes, but data and model integration challenges have hindered their widespread application. Leveraging National Ecological Observation Network measurements of water isotope ratios at 16 US sites over 3 years combined with LSM‐modeled fluxes, we employed an isotope‐enabled mass balance framework to simulate ET isotope values ( δET ) within three operational LSMs (Mosaic, Noah, and VIC) to evaluate their partitioning. Models simulating δET values consistent with observations were deemed more reflective of water cycling in these ecosystems. Mosaic exhibited the best overall performance (Kling‐Gupta Efficiency of 0.28). For both Mosaic and Noah there were robust correlations between bare soil evaporation fraction and error (negative) as well as transpiration fraction and error (positive). We found the point at which errors are smallest ( x ‐intercept of the multi‐site regression) is at a higher transpiration fraction than is currently specified in the models. Which means that transpiration fraction is underestimated on average. Stable isotope tracers offer an additional tool for model evaluation and identifying areas for improvement, potentially enhancing LSM simulations and our understanding of land‐surface hydrologic processes.
Geological CO 2 sequestration in deep saline aquifers has been extendedly investigated to reach the goal of carbon neutral as large amount of CO 2 can be reduced in a short time. Here, this study investigates the feasibility of water-alternating-gas (WAG) injection and brine extraction on enhancing CO 2 storage in a target deep saline aquifer, Minnelusa Sandstone in the Powder River Basin (PRB) of Wyoming. An integrated numerical model is developed to account for four scenarios: (1) CO 2 continuous injection (CI) through one injection well, (2) WAG injection through one injection well, (3) CO 2 CI through one injection well and brine extraction through one producer, (4) WAG injection through one injection well and brine extraction through one producer. Simulation results suggest that WAG injection and brine extraction corporately make it possible to enhance CO 2 injectivity while securing CO 2 storage safety. For instance, WAG injection considerably reduces structural trapping contribution while enhances dissolved and residual trapping contributions. As for brine extraction, it can decrease the maximum averaged reservoir pressure by 37% and 22% for CI and WAG injection, respectively. Besides, sensitive analyses of the operational parameters for the fourth scenarios are performed. Results reveal that, when the amount of total CO 2 injection has been predetermined, CO 2 injection time and rate within each period of WAG should be small whereas it is preferable to have large water injection time and rate. This is to secure desirable dissolved and residual trapping contributions (store CO 2 with safety). Sensitive degree results confirm that CO 2 injection rate, water injection time, and CO 2 injection time of WAG injection exhibit significant effects on CO 2 storage whereas the impacts of producer bottom-hole pressure (BHP), water injection rate, and CO 2 -water injection time are relatively weaker. This study not only sheds light on achieving double-win goal: enhance CO 2 injectivity and store CO 2 with safety, but also can be a critical reference for other CO 2 storage in deep saline aquifers.
The operational dynamic subseasonal to seasonal (S2S) models for Madden-Julian oscillation (MJO) forecasting mostly still suffer from systematic errors in capturing the MJO's key dynamic features, such as its growth rate and propagation speed. By deriving the linear dynamic operators using the linear inverse modeling (LIM) approach, we propose a method to partly correct the errors in MJO linear dynamic operators to improve the MJO predictions of three operational dynamic S2S models. Correcting the deficiencies of the too-fast decay rates and the unrealistic propagating phase speeds lead to MJO prediction skills being extended by approximately 2–4 days. The improvements are more significant for the models with larger biases in MJO amplitude and propagation. This approach in principle may be extendable to predictions of other types of climate variability such as ENSO on one hand, and possible inclusions of nonlinear dynamics effects on the other hand.
Abstract The formation of new mineral phases in confined environments, especially in porous media, is crucial for various geological processes like mineralization and diagenesis. The nucleation and precipitation of minerals are initiated at the microscale through fluid‐rock interaction, where dissolution of primary phases leads to supersaturated conditions and nucleation and growth of secondary ones. Previous research has focused primarily on either precipitation or nucleation, without fully exploring their combined impact. Our study introduces a computational framework that integrates classical nucleation theory with the micro‐continuum method. We validated our model by comparing with experiments, and discovered that different surface nucleation rate changes the mode of precipitation from a preferential to uniform precipitate textures. Furthermore, our study uncovered that the conventional deterministic precipitation method tends to underestimate the permeability of the porous matrix. In contrast, the new framework significantly improves model accuracy by incorporating preferential precipitation and heterogeneous nucleation.