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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Macroscopic and microscopic behaviors of Mn(II) (ad)sorption to goethite with the effects of dissolved carbonates under anoxic conditions

Manganese and its compounds have been extensively researched because of their far-reaching roles in a wide range of biogeochemical processes in natural systems. The (ad)sorption behavior of Mn(II), however, is poorly understood despite its important role as the primary reaction step for surface-catalyzed Mn(II) oxidation that is the principal abiotic process forming various Mn (oxyhydr)oxides in nature. Here, we systematically examined Mn(II) (ad)sorption to one of the most common natural sorbents, goethite, in oxygen- and carbonate-free systems. Traditional sorption edge and isotherm experiments were conducted by varying sorbate-to-sorbent ratio (0.027–15 μmol∙m -2 ) and solution pH (pH 5.0–9.0). The effects of dissolved carbonates on Mn(II) sorption were also assessed in a range of naturally prevalent concentrations (0.5–10 mM NaHCO 3 ). The Mn(II) uptake on goethite followed a typical Langmuir isotherm in the absence of dissolved carbonates, with increasing maximum adsorption capacities (Γ max ) from 0.19 at pH 6.5 to 3.4 μmol∙m -2 at pH 9.0. The presence of dissolved carbonates raised the extent of Mn(II) adsorption, which appeared to be directly correspondent to that of the adsorption of dissolved carbonates. Extended X-ray absorption fine structure (EXAFS) analysis indicated that Mn(II) predominantly formed inner-sphere binuclear bidentate surface complexes. Mn(II) uptake became deviated from the Langmuir model and showed a clear indication of surface precipitation when the Mn(II) sorption density (Γ) exceeded a threshold value in a given solution composition. This secondary Mn(II) phase was identified as rhodochrosite using X-ray diffraction (XRD) and transmission electron microscope (TEM). Furthermore, it would be plausible that a minor fraction of adsorbed Mn(II) coexisted with the secondary rhodochrosite according to a linear combination fitting (LCF) of the X-ray absorption near edge structure (XANES) spectra of Mn reference and samples. These systematic investigations of the macroscopic and microscopic behaviors of Mn(II) (ad)sorption to goethite provide a critical avenue for disentangling surface-catalytic Mn(II) oxidation processes, which ultimately lead to the formation of diverse Mn (oxyhydr)oxides in the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Advancing uncertainty characterization for understanding projected water scarcity in multi-sector, multi-actor river basins across scales.

Invited Talk at AGU Fall Meeting 2023 Modeling how human institutions and infrastructure interact with the water cycle is essential to better understand the vulnerability, and resilience of water resources systems from the local to the global scale. This is especially true when investigating multi-sector, multi-actor responses to the effects of long-term changes and short-term shocks. It is also well recognized that uncertainty present throughout the modeling cycle (e.g., in data, functional relations, and model coupling approaches) limits our ability to trace the interactive dynamics of human-water systems, as well as to quantify their implications for management and planning. Systems with large numbers of diverse stakeholders further compound this challenge, as uncertain drivers and complex dynamics might have very disparate effects on water users. The work presented is conducted through the Integrated Multisector Multiscale Modeling (IM3) Science Focus Area, which explores how human and natural systems co-evolve in response to change. Through this multi-year effort, we have developed exploratory modeling methods to better characterize how the uncertain human and natural drivers of water scarcity yield consequential vulnerabilities in institutionally complex, multi-sectoral systems. This talk will specifically present on a series of uncertainty characterization experiments performed in the Upper Colorado River Basin, a sub-basin of the Colorado with thousands of water users. These complementary and systematic experiments are aimed at understanding: How are various uncertain stressors (e.g., climate change, demand growth) affecting the diverse water users of this basin in terms of water shortage? What are the key drivers of this shortage for each user? Methods and results from this work are used to address additional questions on the ability of adaptation to modulate the effects of these uncertain drivers, and on their compounding effects across spatial scales and through sectoral interactions.

Hadjimichael, Antonia↗
DOE OSTI2022

Protoplast fusion in Bacillus species produces frequent, unbiased, genome-wide homologous recombination

Abstract In eukaryotes, fine-scale maps of meiotic recombination events have greatly advanced our understanding of the factors that affect genomic variation patterns and evolution of traits. However, in bacteria that lack natural systems for sexual reproduction, unbiased characterization of recombination landscapes has remained challenging due to variable rates of genetic exchange and influence of natural selection. Here, to overcome these limitations and to gain a genome-wide view on recombination, we crossed Bacillus strains with different genetic distances using protoplast fusion. The offspring displayed complex inheritance patterns with one of the parents consistently contributing the major part of the chromosome backbone and multiple unselected fragments originating from the second parent. Our results demonstrate that this bias was in part due to the action of restriction–modification systems, whereas genome features like GC content and local nucleotide identity did not affect distribution of recombination events around the chromosome. Furthermore, we found that recombination occurred uniformly across the genome without concentration into hotspots. Notably, our results show that species-level genetic distance did not affect genome-wide recombination. This study provides a new insight into the dynamics of recombination in bacteria and a platform for studying recombination patterns in diverse bacterial species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Interface learning of multiphysics and multiscale systems

Complex natural or engineered systems comprise multiple characteristic scales, multiple spatiotemporal domains, and even multiple physical closure laws. To address such challenges, we introduce an interface learning paradigm and put forth a data-driven closure approach based on memory embedding to provide physically correct boundary conditions at the interface. To enable the interface learning for hyperbolic systems by considering the domain of influence and wave structures into account, we put forth the concept of upwind learning toward a physics-informed domain decomposition. The promise of the proposed approach is shown for a set of canonical illustrative problems. Here, we highlight that high-performance computing environments can benefit from this methodology to reduce communication costs among processing units in emerging machine-learning-ready heterogeneous platforms toward exascale era.

42 ENGINEERING↗
DOE OSTI2026

Mapping Critical Vulnerabilities in Natural Gas Pipeline Systems through Network Centrality and GIS Analytics

Natural gas plays a central role in the US energy landscape, providing 43% of electricity generation in 2023. Its exclusive recovery ability on pipelines for transmission underscores the importance of understanding the disruption recovery ability of this infrastructure. This study employs a network-based analytical framework integrating geographic information systems (GIS) with multiple centrality measures—betweenness, closeness, degree, and eigenvector—to pinpoint key segments and evaluate the structural robustness of the national pipeline network. Pipelines are grouped by System ID and Operator ID to capture variations across organizational and physical structures. The analysis reveals uneven patterns of network influence, where certain pipelines function as critical connectors or dominant hubs. Spatial mapping highlights geographic dependencies and potential chokepoints, offering a clear view of where targeted risk prevention measures would be most effective. The findings provide practical guidance for prioritizing maintenance, enhancing system robustness, and mitigating risks to ensure a stable and secure energy supply. Future research will expand the framework to incorporate dynamic operational data and real-time network behavior.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
DOE OSTI2022

Counterfactuals to Assess Effects to Species and Systems from Renewable Energy Development

Renewable energy production, mostly via wind, solar, and biofuels, is central to goals worldwide to reduce carbon emissions and mitigate anthropogenic climate change (IPCC, 2014; Portner et al., 2021). Nevertheless, adverse impacts to natural systems, especially fatalities of wildlife and alteration of habitat, are key challenges for renewable energy production (Allison et al., 2019; Katzner et al., 2019).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Applying a Multisector Scenario Framework to Evaluate Past and Future Public Surface Water Supply Infrastructure Strategies in Texas

Datasets supporting the index model and scenario analysis used in evaluating surface water supply strategies across different water system types in Texas. These data underpin the scenario development and application of five key indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets are organized by system type—stream reaches (flowlines), waterbodies, and reservoirs—and include both raw and standardized index values. The integrated datasets also provide scenario classifications (original and adjusted) based on infrastructure and planning priorities, enabling comparison across Shared Socioeconomic Pathways (SSPs). Additional strategy-level data are included to support evaluation of state-level new reservoir projects in relation to cost and availability tradeoffs. Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions Folder: Index_model_database.zip Subfolder: Stream_reach.zip Fl_wf.csv, Fl_wq.csv, Fl_er.csv, Fl_wf_wtcUV.csv, Fl_wf_wtcnoUV.csv, Fl_allfac_wic1.csv, Fl_allfac_wic2.csvDatasets for computing WAI, WQI, ERI, WTC, and WIC for surface water systems classified as stream reaches (flowlines). Subfolder: Waterbody.zip Wb_wf.csv, Wb_wq.csv, Wb_er.csv, Wb_wf_wtcUV.csv, Wb_wf_wtcnoUV.csv, Wb_allfac_wic1.csv, Wb_allfac_wic2.csvEquivalent index model datasets for waterbodies, reflecting hydrologic and infrastructure attributes specific to impounded natural systems. Subfolder: Reservoir.zip Rs_wf.csv, Rs_wq.csv, Rs_er.csv, Rs_wf_wtcUV.csv, Rs_wf_wtcnoUV.csv, Rs_allfac_wic1.csv, Rs_allfac_wic2.csvIndex model datasets specific to regulated reservoir systems, incorporating both resource indicators and cost parameters. Folder: Integrated data.zip combined_merged_data.csv, combined_merged_data_scenario.csvDatasets integrating index model indicators (both raw and scaled) with scenario classifications, including adjustments reflecting SSP-aligned transitions and planning shifts. Folder: Additional data.zip wai_supplystrat_wic_merged.csvCurated dataset capturing proposed major reservoir-based municipal water supply strategies in Texas. Integrates site-level planning data with estimated capital infrastructure costs and water availability scores for comparative assessment.

geospatial↗
DOE OSTI2020

The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support

Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of researchers and practitioners revisit the current status of SA, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems. Six areas are discussed that warrant further attention, including (1) structuring and standardizing SA as a discipline, (2) realizing the untapped potential of SA for systems modeling, (3) addressing the computational burden of SA, (4) progressing SA in the context of machine learning, (5) clarifying the relationship and role of SA to uncertainty quantification, and (6) evolving the use of SA in support of decision making. An outlook for the future of SA is provided that underlines how SA must underpin a wide variety of activities to better serve science and society.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

In Situ Chemical Monitoring and Imaging of Contents within Microfluidic Devices Having a Porous Membrane Wall Using Liquid Microjunction Surface Sampling Probe Mass Spectrometry

The ability to observe dynamic chemical processes (e.g., signaling, transport, etc.) in vivo or in situ using nondestructive chemical imaging opens a new door to understanding the complex dynamics of developing biological systems. With the advent of “biology-on-a-chip” devices has come the ability to monitor dynamic chemical processes in a controlled environment, using these engineered habitats to capture key features of natural systems while allowing visual observation of system development. Having the capability to spatially and temporally map the chemical signals within these devices may yield new insights into the forces that drive biosystem development. Here, a porous membrane sealed microfluidic device was designed to allow normal microfluidic operation while enabling continuous, location specific sampling and chemical characterization by liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP MS). LMJ-SSP was used to extract fluids with nL-to-μL/min flow rates directly from selected areas of the microfluidic device without negatively impacting the device function. These extracts were subsequently characterized using MS. This technique was used to acquire MS images of the entirety of several multi-input microfluidic devices having different degrees of fluid mixing. LMJ-SSP MS imaging visualized the spatial distribution of chemical components within the microfluidic channels and could visualize chemical reactions occurring in the device. These microfluidic devices with a porous membrane wall are wholly compatible with the construction of biology-on-a-chip devices. This ultimately would enable correlation of biosystem physical structure with an evolving chemical environment

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Siderophore-Mediated Mobilization of Manganese Limits Iron Solubility in Mixed Mineral Systems

Recent laboratory and field studies show the need to consider the formation of aqueous Mn(III)-siderophore complexes in manganese (Mn) and iron (Fe) geochemical cycling, a shift from the historical view that aqueous Mn(III) species are unstable and thus unimportant. In this study, we quantified Mn and Fe mobilization by desferrioxamine B (DFOB), a terrestrial bacterial siderophore, in single (Mn or Fe) and mixed (Mn and Fe) mineral systems. We selected manganite (γ-MnOOH), δ-MnO 2 , lepidocrocite (γ-FeOOH), and 2-line ferrihydrite (Fe 2 O 3 ·0.5H 2 O) as relevant mineral phases. We found that DFOB mobilized Mn(III) as Mn(III)-DFOB complexes to varying extents from both Mn(III,IV) oxyhydroxides but reduction of Mn(IV) to Mn(III) was required for the mobilization of Mn(III) from δ-MnO 2 . The initial rates of Mn(III)-DFOB mobilization from manganite and δ-MnO 2 were not affected by the presence of lepidocrocite but decreased by a factor of 5 and 10 for manganite and δ-MnO 2 , respectively, in the presence of 2-line ferrihydrite. Additionally, the decomposition of Mn(III)-DFOB complexes through Mn-for-Fe ligand exchange and/or ligand oxidation led to Mn(II) mobilization and Mn(III) precipitation in the mixed-mineral systems (~10% (mol Mn/mol Fe)). As a result, the concentration of Fe(III) mobilized as Fe(III)-DFOB decreased by up to 50% and 80% in the presence of manganite and δ-MnO 2 , respectively, compared to the single mineral systems. Our results demonstrate that siderophores, through their complexation of Mn(III), reduction of Mn(III,IV), and mobilization of Mn(II), can redistribute Mn to other soil minerals and limit the bioavailability of Fe in natural systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Unraveling the Effects of Hierarchical Bimodal Microscale Porosity on Thick Electrodes

The thick electrode design is preferential in high-energy lithium-ion batteries (LIBs) systems. However, the sluggish ionic transport in homogeneous porous thick electrodes severely limits the areal capacity at high charging/discharging rates. The hierarchical porous design is a promising approach to mitigate kinetic limitations because it can distribute mass effectively in natural systems. In this study, the effects of bimodal microscale pores are fully investigated in thick electrodes from both architectural and electrochemical perspectives. Notably, by introduction of the bimodal microscale porous structure, the rate capability improves remarkably in thick electrodes with a low porosity (39%). Herein, by combining experimental results with simulations, this work presents a rational design guideline for preparing thick electrodes with a porosity at the commercial level, as well as simultaneous high energy and power densities, which brings new insights into the advanced electrode architecture design in scalable high-energy and high-power energy storage systems for practical applications.

25 ENERGY STORAGE↗
DOE OSTI2022

A Typology for Characterizing Human Action in MultiSector Dynamics Models

The role of individual and collective human agency is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short-term (hourly to daily) to long-term (annually to centennial) timescales, and from the local to the global, pushing systems towards either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human-natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system-of-systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services towards some human end. We trace the salient features of modeled representations of human systems by organizing the typology around three key questions: 1) Who are the modeled actors in MSD systems? 2) What are their modeled actions? 3) How and for what purpose are these actors and actions operationalized in a computational model? The typology is used to critically examine existing models and chart the frontier of future human systems modeling for MSD research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Self‐Limiting Polymerization‐Induced Crystallization‐Driven Self‐Assembly (SL‐PI‐CDSA) Enables Templated Synthesis of Chiral Plasmonic, Hybrid 2D Hexagonal Assemblies

Examples of self-regulating synthetic self-assembly are relatively few, with most known chemical systems relying on kinetic rather than thermodynamic control. Herein, we demonstrate the rapid generation (t ≤ 5 min) of size-tunable ultralow dispersity (Ð ≤ 1.01) 2D hexagonal nanosheets governed by self-limiting self-assembly (SLSA). Self-assembly in natural systems occurs with exquisite control of structure, function, and dimension. We demonstrate that key aspects of biological assembly can be rationally applied toward the development of bottom-up approaches for the construction of chiral nanomaterials. To this end, self-limiting polymerization-induced crystallization-driven self-assembly (SL-PI-CDSA) of modular and templating aryl isocyanide (AIC) monomers yields functional 2D assemblies permitting post-polymerization/assembly modifications. Detailed study of the internal and external structure of the hexagonal nanosheets reveals topological defects which offer mechanistic insights into both their assembly and subsequent utilization. Specifically, these features enable fabrication of chiral hybrid organic–inorganic nanomaterials incorporating chiral plasmonic metal nanoparticles (MNPs). Our results suggest that the synergistic interplay of template-driven confinement and hierarchical chirality induce symmetry breaking of in situ-generated gold MNPs. We anticipate that the platform presented will facilitate fabrication of new hybrid, chiral organic–inorganic nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evaluation of Methods for Causal Discovery in Hydrometeorological Systems

Understanding causal relations is of utmost importance in hydrology and climate research for systems identification, prediction, and understanding systems behavior in a changing climate. Traditionally, researchers in hydrometeorology attempted to study causal questions by conducting controlled experiments using numerical models. This approach, however, in most cases of interest provides uncertain results because the models are approximate representation of the natural system. An alternative approach that has recently drawn significant attention in several fields is to infer causal relations from purely observational data. It possesses several traits to its utility particularly in hydrometeorology due to the rapid accumulation of in situ and remotely sensed data records. The first objective of this study is to present a brief description of four causal discovery methods (Granger causality, Transfer Entropy, graph-based algorithms, and Convergent Cross Mapping) with special emphasis on the assumptions on which they are built. Second, using synthetic data generated from a hydrological model, we assess their performance in retrieving causal information taking into account sensitivity to sample size and presence of noise. Last, we use causal analysis to examine and formulate hypotheses on causal drivers of evapotranspiration in a shrubland region during summer and winter seasons. An interpretation of the hypotheses based on canopy seasonal dynamics and evapotranspiration processes is presented. It is hoped that the results presented here can be useful in guiding researchers studying hydrometeorological systems as to which causal method is most appropriate to the characteristics of the system under study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Automating Genetic Algorithm Mutations for Molecules Using a Masked Language Model

Inspired by the evolution of biological systems, genetic algorithms have been applied to generate solutions for optimization problems in a variety of scientific and engineering disciplines. For a given problem, a suitable genome representation must be defined along with a mutation operator to generate subsequent generations. Unlike natural systems which display a variety of complex rearrangements (e.g. mobile genetic elements), mutation for genetic algorithms commonly utilizes only random point-wise changes. Furthermore, generalizing beyond point-wise mutations poses a key difficulty as useful genome rearrangements depend on the representation and problem domain. To move beyond the limitations of manually defined point-wise changes, here we propose the use of techniques from masked language models to automatically generate mutations. As a first step, common subsequences within a given population are used to generate a vocabulary. The vocabulary is then used to tokenize each genome. A masked language model is trained on the tokenized data in order to generate possible rearrangements (i.e. mutations). In order to illustrate the proposed strategy, we use string representations of molecules and use a genetic algorithm to optimize for drug-likeness and synthesizability. Finally, our results show that moving beyond random point-wise mutations accelerates genetic algorithm optimization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Symbiotic niche mapping reveals functional specialization by two ectomycorrhizal fungi that expands the host plant niche

Mutualisms are ubiquitous in natural systems, but less is known about how these positive interactions influence species distributions compared with antagonistic interactions, such as competition and predation. The niche concept is one useful approach for thinking about factors that shape species ranges, which we apply here towards understanding how the nature of plant-mycorrhizal symbioses change across large environmental gradients. We used a continuous niche mapping approach to examine how two ectomycorrhizal fungi (Thelephora terrestris, Suillus pungens) impact pine seedling growth across a two-dimensional soil nitrogen (N) and phosphorus (P) gradient. We found that ectomycorrhizal fungi improved plant growth most in nutrient addition treatments with highly imbalanced N:P ratios, demonstrating that mycorrhizal benefits depend on interactions between niche axes. Nevertheless, T. terrestris (highN:lowP) and S. pungens (lowN:highP) benefited plants most at opposite ends of the resource ratio spectrum, consistent with niche partitioning and functional specialization. While ectomycorrhizal fungi are often thought of as being most beneficial for nitrogen uptake, our results suggest that members of the Thelephoraceae may specialize in improving plant P uptake. Ectomycorrhizal colonization by a single fungus increased plant niche volume (calculated as convex hull volumes of plant growth response surfaces across N and P gradients) compared to non-mycorrhizal control plants and shows the overall positive effects of mutualisms on plant niche volume. Despite plant host benefits in S. pungens and T. terrestris single species treatments, the presence of both fungi together decreased plant niche volume. The lack of functional complementarity, despite functional specialization, indicates that in some environments, either fungal competition or the cost of maintaining a suboptimal mycorrhizal partner can limit the benefits of a higher quality partner. The niche mapping approach we present has the potential to answer fundamental questions about the dimensions of functional diversity in ectomycorrhizal fungi and the distributions of mycorrhizal symbioses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Enhancing photonic systems using topology and non-Hermiticity

The broad goal of this project was to develop new analytical and numerical insights for how important photonic processes can be improved using recently discovered principles in topological and non-Hermitian physics. In particular, there are two recent discoveries that we aimed to harness to achieve this goal. First, it was discovered in condensed matter physics that crystalline symmetries can protect low-dimensional topologically protected states in lattices without the need for breaking time-reversal symmetry. These so-called ‘higher-order’ topological systems represent an important development for photonic systems, where it is very difficult to break time-reversal symmetry, and which had been previously thought necessary to realize topological phenomena. Second, the last decade has seen a significant amount of interest in phenomena which are unique to non-Hermitian systems, i.e., systems which do not conserve energy. For example, spatially patterned gain and loss can be used to realize exceptional points, which are degeneracies in a system’s spectrum where the system becomes defective, while the existence of radiative losses also enables a new route to confinement through bound states in the continuum. For such non-Hermitian phenomena, photonics again represents a critical platform, as photonic systems naturally lose light to their radiative environments, making them generally non-Hermitian, and it is also possible to incorporate additional gain or loss. Based on these broad principles, we pursued a range of projects to harness bound states in the continuum in a variety of different systems and architectures, develop real-space methods for classifying topological systems to yield better photonic design principles, and a novel Brillouin-based fiber laser for sensing strain.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

HFTS-1 Natural Joint Data and Engineering Summary

This report provides an analysis of engineering and geologic data collected from the Hydraulic Fracturing Test Site #1 (HTSF-1) project in the southern Midland Basin, Reagan County, Texas. The site is being studied as part of the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative at the National Energy Technology Laboratory (NETL). The data collected is intended to provide a basis of understanding of the site and to construct simulation models. This report provides a summary analysis of the engineering and geologic data collected from the project to provide a basis of understanding of the site and to construct simulation models. The report examines various possible correlations in engineering properties based on natural fracture data from the program, which consisted of 11 horizontal wells, one vertical well, and one slant well. The horizontal wells are in two horizons: 1) Upper and 2) Middle Wolfcamp formations. Program data include: fracture frequency and fracture orientation data from four core runs in a slant well; fracture spacing and orientation from a vertical pilot well; laboratory triaxial testing and mineralogical determinations; and porosity results from magnetic resonance analyses from various wells, together with observations based on the data collection. In addition, available references were reviewed on the site for additional insights. As the focus of the report is on the natural system, hydraulic fracture data from the site were not examined in detail in this report. Data variability is the chief observation in examination of the database. Fracture frequency in the slant well can range from sections with values as high as five fractures per ft to sections up to 100+ ft in length with no natural observed fractures. Fracture spacing across is typically less than 10 ft, but can range up to hundreds of feet. Apparent fracturing shows the trends in two predominate orientations, E-SW and WNW-ESE, but minor variations exist. The rock units vary across the site from siliceous mudstones to calcareous mudstones, showing a general layering with depth. The laboratory properties such as strength and modulus show no apparent trend with depth, but appear to correlate with rock mineralogy with high strength and modulus values where calcium content is high. In addition, an attempt to examine variability and mineralogy on a larger scale was made using a color-coded system based on gamma ray measurements. A staged colored approach was adopted, presuming that lower gamma ray values indicate higher value of calcium content (blue scale) and that higher gamma ray values indicate higher clay mineral content (orange scale). As provided in report appendices, the system correlated well with visual examination of the slant core and the petrofabric analyses of the vertical pilot well. The results showed large variability in mineral content along the horizontal plane across the site. The change in mineral content was also rapid, on a scale less than that of the average hydraulic fracture stage length of about 180 ft.

42 ENGINEERING↗