SEARCH · Engineering Papers

Results for “EXPLORATION”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Analysis of Selected Publicly Available Geothermal Exploration Data Gaps

As part of a United States Department of Energy (DOE) supported retrospective analysis of DOE's Play Fairway Analysis (PFA) projects, the National Renewable Energy Laboratory (NREL) compiled and analyzed publicly available geothermal exploration datasets to identify and highlight data gaps in areas prospective for hosting geothermal resources. The analysis was intended to understand the existing geographic coverage of selected datasets commonly utilized both by the PFA projects and geothermal developers during resource assessments including geologic mapping, temperature gradient drilling, and aeromagnetic, gravimetric, and lidar surveys. Results indicate that broad areas of the western United States estimated to have geothermal potential lack sufficient geologic and geophysical coverage necessary for even regional resource exploration. The study directly informed the recent Geoscience Data Acquisition for Western Nevada, or GeoDAWN - which united DOE's Geothermal Technologies Office (GTO) with the U.S. Geological Survey (USGS) of the U.S. Department of the Interior to assist U.S. needs for energy and critical minerals. The study also has the potential to inform public investment in further data acquisition for characterization of the Earth both for geothermal and other natural resource assessments.

data↗

DOE OSTI2021

Exploring Transport Behavior in Hybrid Perovskites Solar Cells via Machine Learning Analysis of Environmental-Dependent Impedance Spectroscopy

Hybrid organic–inorganic perovskites are one of the promising candidates for the next-generation semiconductors due to their superlative optoelectronic properties. However, one of the limiting factors for potential applications is their chemical and structural instability in different environments. Herein, the stability of (FAPbI3)0.85(MAPbBr3)0.15 perovskite solar cell is explored in different atmospheres using impedance spectroscopy. An equivalent circuit model and distribution of relaxation times (DRTs) are used to effectively analyze impedance spectra. DRT is further analyzed via machine learning workflow based on the non-negative matrix factorization of reconstructed relaxation time spectra. This exploration provides the interplay of charge transport dynamics and recombination processes under environment stimuli and illumination. The results reveal that in the dark, oxygen atmosphere induces an increased hole concentration with less ionic character while ionic motion is dominant under ambient air. Under 1 Sun illumination, the environment-dependent impedance responses show a more striking effect compared with dark conditions. In this case, the increased transport resistance observed under oxygen atmosphere in equivalent circuit analysis arises due to interruption of photogenerated hole carriers. The results not only shed light on elucidating transport mechanisms of perovskite solar cells in different environments but also offer an effective interpretation of impedance responses.

36 MATERIALS SCIENCE↗

DOE OSTI2023

High-Throughput Automated Exploration of Phase Growth Behaviors in Quasi-2D Formamidinium Metal Halide Perovskites

Quasi-2D metal halide perovskites (MHPs) are an emerging material platform for sustainable functional optoelectronics, but the uncontrollable, broad phase distribution remains a critical challenge for applications. Nevertheless, the basic principles for controlling phases in quasi-2D MHPs remain poorly understood, due to the rapid crystallization kinetics during the conventional thin-film fabrication process. In this work, a high-throughput automated synthesis-characterization-analysis workflow is implemented to accelerate material exploration in formamidinium (FA)-based quasi-2D MHP compositional space, revealing the early-stage phase growth behaviors fundamentally determining the phase distributions. Upon comprehensive exploration with varying synthesis conditions including 2D:3D composition ratios, antisolvent injection rates, and temperatures in an automated synthesis-characterization platform, it is observed that the prominent n = 2 2D phase restricts the growth kinetics of 3D-like phases—α-FAPbI 3 MHPs with spacer-coordinated surface—across the MHP compositions. Thermal annealing is a critical step for proper phase growth, although it can lead to the emergence of unwanted local PbI 2 crystallites. Additionally, fundamental insights into the precursor chemistry associated with spacer-solvent interaction determining the quasi-2D MHP morphologies and microstructures are demonstrated. The high-throughput study provides comprehensive insights into the fundamental principles in quasi-2D MHP phase control, enabling new control of the functionalities in complex materials systems for sustainable device applications.

2D perovskites↗

DOE OSTI2026

Exploration of Nirmatrelvir Derivatives as Optimized SARS‐CoV‐2 Antivirals

Nirmatrelvir (NMV) is a SARS‐CoV‐2 antiviral component of the approved COVID‐19 therapeutic Paxlovid. It is a reversible covalent inhibitor of SARS‐CoV‐2 main protease (M Pro ) that is effluxed from human cells by P‐glycoprotein (P‐gp). To identify NMV analogs with improved potency and reduced P‐gp efflux, a structure–activity relationship campaign was conducted. Warheads alternative to nitrile for engaging the active site cysteine were tested showing aldehyde and dichloroacetamide with better enzyme inhibition potency. Crystal structure of MPI‐136−M Pro shows its aldehyde warhead forming a thiohemiacetal with active Cys145 of M Pro . Several S4 binders were explored revealing that an O‐to‐S shift at the N ‐terminal amide leads to better enzyme inhibition. By exploring different combinations of S2, S3, and S4 binders, two inhibitors with better enzyme inhibition potency than NMV were found. Crystal structure of MPI‐148, with ( S )‐2‐azaspiro[4,5]decane‐3‐carboxylate as an alternative S2 binder, shows extensive hydrogen‐bond networks for locking the inhibitor in active site, explaining high affinity of NMV analogs. Further characterization of cellular M Pro engagement and antiviral potency against SARS‐CoV‐2 revealed four inhibitors with greater potency than NMV in P‐gp‐expressing cells. Studies with the P‐gp inhibitor CP‐100356 showed that these compounds were less sensitive to P‐gp inhibition than NMV, consistent with reduced P‐gp‐mediated efflux.

Alugubelli, Yugendar R. [Texas A&M Drug Discovery ↗

DOE OSTI2013

Investigating the experiences of New Zealand MRI technologists: Exploring intra-orbital metallic foreign body safety practices

Qualitative research is lacking regarding the experiences of magnetic resonance imaging (MRI) technologists and their involvement in workplace safety practices. This article provides a gateway to explore, describe and document experiences of MRI technologists in New Zealand (NZ) pertaining to intra-orbital metallic foreign body (IMFB) safety practices. This phenomenological study describes the experiences of seven MRI technologists all with a minimum of 5 years' NZ work experience in MRI. The MRI technologists were interviewed face-to-face regarding their professional IMFB workplace experiences in order to explore historical, current and potential issues. Findings demonstrated that aspects of organization and administration are fundamentally important to MRI technologists. Varying levels of education and knowledge, as well as experience and skills gained, have significantly impacted on MRI technologists’ level of confidence and control in IMFB practices. Participants’ descriptions of their experiences in practice regarding decision-making capabilities further highlight the complexity of these themes. A model was developed to demonstrate the interrelated nature of the themes and the complexity of the situation in totality. Findings of this study have provided insight into the experiences of MRI technologists pertaining to IMFB safety practices and highlighted inconsistencies. It is hoped that these findings will contribute to and improve the level of understanding of MRI technologists and the practices and protocols involved in IMFB safety screening. The scarcity of available literature regarding IMFB safety practices highlights that more research is required to investigate additional aspects that could improve MRI technologists’ experiences.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Automated reaction kinetics and network exploration (Arkane): A statistical mechanics, thermodynamics, transition state theory, and master equation software

The open-source statistical mechanics software described here, Arkane–Automated Reaction Kinetics and Network Exploration–facilitates computations of thermodynamic properties of chemical species, high-pressure limit reaction rate coefficients, and pressure-dependent rate coefficient over multi-well molecular potential energy surfaces (PES) including the effects of collisional energy transfer on phenomenological kinetics. Arkane can use estimates to fill in information for molecules or reactions where quantum chemistry information is missing. The software solves the internal energy master equation for complex unimolecular reaction systems. Inputs to the software include converged electronic structure computations performed by the user using a variety of supported software packages (Gaussian, Molpro, Orca, TeraChem, Q-Chem, Psi4). The software outputs high-pressure limit rate coefficients and pressure-dependent phenomenological rate coefficients, as well as computed thermodynamic properties (enthalpy, entropy, and constant pressure heat capacity) with added energy corrections. Some of the key features of Arkane include treatment of 1D, 2D or ND hindered internal rotation modes, treatment of free internal rotation modes, quantum tunneling effect consideration, transition state theory (TST) and Rice-Ramsperger-Kassel-Marcus (RRKM) rate coefficient computations, master equation solution with four implemented methods, inverse-Laplace transform of high-pressure limit rate coefficients into the energy domain, energy corrections based on bond-additivity or isodesmic reactions, automated and efficient PES exploration, and PES sensitivity analysis. The present work describes the design of Arkane, how it should be used, and refers to the theory that it employs. Arkane is distributed via the RMG-Py software suite (https://github.com/ReactionMechanismGenerator/RMG-Py).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

An initial exploration of Bayesian model calibration for estimating the composition of rocks and soils on Mars

The Mars Curiosity rover carries an instrument, ChemCam, designed to measure the composition of surface rocks and soil using laser-induced breakdown spectroscopy (LIBS). The measured spectra from this instrument must be analyzed to identify the component elements in the target sample, as well as their relative proportions. This process, which we call disaggregation, is complicated by so-called matrix effects, which describe nonlinear changes in the relative heights of emission lines as an unknown function of composition due to atomic interactions within the LIBS plasma. In this work, we explore the use of the plasma physics code ATOMIC, developed at Los Alamos National Laboratory, for the disaggregation task. ATOMIC has recently been used to model LIBS spectra and can robustly reproduce matrix effects from first principles. The ability of ATOMIC to predict LIBS spectra presents an exciting opportunity to perform disaggregation in a manner not yet tried in the LIBS community, namely via Bayesian model calibration. However, using it directly to solve our inverse problem is computationally intractable due to the large parameter space and the computation time required to produce a single output. Therefore, we also explore the use of emulators as a fast solution for this analysis. We discuss a proof of concept Gaussian process emulator for disaggregating two-element compounds of sodium and copper. The training and test datasets were simulated with ATOMIC using a Latin hypercube design. After testing the performance of the emulator, we successfully recover the composition of 25 test spectra with Bayesian model calibration.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Combinatorial Growth of Vertically Aligned Nanocomposite Thin Films for Accelerated Exploration in Composition Variation

Combinatorial growth is capable of creating a compositional gradient for thin film materials and thus has been adopted to explore composition variation mostly for metallic alloy thin films and some dopant concentrations for ceramic thin films. This study uses a combinatorial pulsed laser deposition method to successfully fabricate two‐phase oxide–oxide vertically aligned nanocomposite (VAN) thin films of La 0.7 Sr 0.3 MnO 3 (LSMO)‐NiO with variable composition across the film area. The LSMO‐NiO compositional gradient across the film alters the two‐phase morphology of the VAN through varying nanopillar size and density. Additionally, the magnetic anisotropy and magnetoresistance properties of the nanocomposite thin films increase with increasing NiO composition. This demonstration of a combinatorial method for VAN growth can increase the efficiency of nanocomposite thin film research by allowing all possible compositions of thin film materials to be explored in a single deposition.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Exploring extended scalar sectors with di-Higgs signals: A Higgs EFT perspective

We consider extended scalar sectors of the Standard Model as ultraviolet complete motivations for studying the effective Higgs self-interaction operators of the Standard Model effective field theory. We investigate all motivated heavy scalar models which generate the dimension-six effective operator, |H| 6 , at tree level and proceed to identify the full set of tree-level dimension-six operators by integrating out the heavy scalars. Of seven models which generate |H| 6 at tree level only two, quadruplets of hypercharge Y = 3 Y H and Y = Y H , generate only this operator. Next we perform global fits to constrain relevant Wilson coefficients from the LHC single Higgs measurements as well as the electroweak oblique parameters S and T. We find that the T parameter puts very strong constraints on the Wilson coefficient of the |H| 6 operator in the triplet and quadruplet models, while the singlet and doublet models could still have Higgs self-couplings which deviate significantly from the standard model prediction. To determine the extent to which the |H| 6 operator could be constrained, we study the di-Higgs signatures at the future 100 TeV collider and explore future sensitivity of this operator. As a result, projected onto the Higgs potential parameters of the extended scalar sectors, with 30 ab -1 luminosity data we will be able to explore the Higgs potential parameters in all seven models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Numerical exploration of three relativistic particles in a finite volume including two-particle resonances and bound states

In this work, we use an extension of the quantization condition, given in ref. [1], to numerically explore the finite-volume spectrum of three relativistic particles, in the case that two-particle subsets are either resonant or bound. The original form of the relativistic three-particle quantization condition was derived under a technical assumption on the two- particle K matrix that required the absence of two-particle bound states or narrow two- particle resonances. Here we describe how this restriction can be lifted in a simple way using the freedom in the definition of the K-matrix-like quantity that enters the quantization condition. With this in hand, we extend previous numerical studies of the quantization condition to explore the finite-volume signature for a variety of two- and three-particle interactions. We determine the spectrum for parameters such that the system contains both dimers (two-particle bound states) and one or more trimers (in which all three particles are bound), and also for cases where the two-particle subchannel is resonant. We also show how the quantization condition provides a tool for determining infinite-volume dimer- particle scattering amplitudes for energies below the dimer breakup. We illustrate this for a series of examples, including one that parallels physical deuteron-nucleon scattering. All calculations presented here are restricted to the case of three identical scalar particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Exploring the strong-coupling region of SU( N ) Seiberg-Witten theory

We consider the Seiberg-Witten solution of pure N = 2 gauge theory in four dimensions, with gauge group SU(N). A simple exact series expansion for the dependence of the 2(N – 1) Seiberg-Witten periods a I (u), a DI (u) on the N – 1 Coulomb-branch moduli un is obtained around the Z 2N -symmetric point of the Coulomb branch, where all u n vanish. This generalizes earlier results for N = 2 in terms of hypergeometric functions, and for N = 3 in terms of Appell functions. Using these and other analytical results, combined with numerical computations, we explore the global structure of the Kähler potential K = 1/2Σ I Im(a¯ I a DI ), which is single valued on the Coulomb branch. Evidence is presented that K is a convex function, with a unique minimum at the Z 2N -symmetric point. Finally, we explore candidate walls of marginal stability in the vicinity of this point, and their relation to the surface of vanishing Kähler potential.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Interactive Exploration of High-Dimensional Phase Diagrams

High-dimensional thermodynamic phase stability databases are becoming increasingly common due to the convergence of three recent trends: (i) the widespread interest in so-called “high-entropy” alloys, (ii) the availability of high-throughput computational assessments of phase stability in broad composition spaces and (iii) the ongoing development of ever-increasingly broad, multicomponent, multiphase CALPHAD databases. Although automated computational tools can readily process such high-dimensional data, scientists are often unable to visualize the relevant phase relations, an ability that is crucial to gaining an intuitive understanding of the stability constraints governing materials design. The present work addresses this need by providing algorithms that enable the interactive exploration of phase equilibria in high-dimensional spaces. These algorithms concentrate the complex nonlinear nonsmooth optimization needed into a preprocessing step that generates a large number of high-dimensional yet elementary graphical primitives. Furthermore, these primitives can then be cross-sectioned to yield 3-dimensional views in a computationally efficient manner that enables an interactive exploration of high-dimensional spaces. All of these operations are highly parallelizable, thus facilitating scaling of this method to large data sets.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Exploring microscopic driving volatility in naturalistic driving environment prior to involvement in safety critical events—Concept of event-based driving volatility

The sequence of instantaneous driving decisions and its variations, known as driving volatility, prior to involvement in safety critical events can be a leading indicator of safety. Here, this study focuses on the component of “driving volatility matrix” related to specific normal and safety-critical events, named “event-based volatility.” The research issue is characterizing volatility in instantaneous driving decisions in the longitudinal and lateral directions, and how it varies across drivers involved in normal driving, crash, and/or near-crash events. To explore the issue, a rigorous quasi-experimental study design is adopted to help compare driving behaviors in normal vs unsafe outcomes. Using a unique real-world naturalistic driving database from the 2nd Strategic Highway Research Program (SHRP), a test set of 9593 driving events featuring 2.2 million temporal samples of real-world driving are analyzed. This study features a plethora of kinematic sensors, video, and radar spatiotemporal data about vehicle movement and therefore offers the opportunity to initiate such exploration. By using information related to longitudinal and lateral accelerations and vehicular jerk, 24 different aggregate and segmented measures of driving volatility are proposed that captures variations in extreme instantaneous driving decisions. In doing so, careful attention is given to the issue of intentional vs. unintentional volatility. The volatility indices, as leading indicators of near-crash and crash events, are then linked with safety critical events, crash propensity, and other event specific explanatory variables. Owing to the presence of unobserved heterogeneity and omitted variable bias, fixed- and random-parameter discrete choice models are developed that relate crash propensity to unintentional driving volatility and other factors. Statistically significant evidence is found that driver volatilities in near-crash and crash events are significantly greater than volatility in normal driving events. After controlling for traffic, roadway, and unobserved factors, the results suggest that greater intentional volatility increases the likelihood of both crash and near-crash events. A one-unit increase in intentional volatility is associated with positive vehicular jerk in longitudinal direction increases the chance of crash and near-crash outcome by 15.79 and 12.52 percentage points, respectively. Importantly, intentional volatility in positive vehicular jerk in lateral direction has more negative consequences than intentional volatility in positive vehicular jerk in longitudinal direction. Compared to acceleration/deceleration, vehicular jerk can better characterize the volatility in microscopic instantaneous driving decisions prior to involvement in safety critical events. Finally, the magnitudes of correlations exhibit significant heterogeneity, and that accounting for the heterogeneous effects in the modeling framework can provide more reliable and accurate results. The study demonstrates the value of quasi-experimental study design and big data analytics for understanding extreme driving behaviors in safe vs. unsafe driving outcomes.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Photometric redshifts probability density estimation from recurrent neural networks in the DECam local volume exploration survey data release 2

Photometric wide-field surveys are imaging the sky in unprecedented detail. These surveys face a significant challenge in efficiently estimating galactic photometric redshifts while accurately quantifying associated uncertainties. In this work, we address this challenge by exploring the estimation of Probability Density Functions (PDFs) for the photometric redshifts of galaxies across a vast area of 17,000 square degrees, encompassing objects with a median 5 σ point-source depth of g = 24.3, r = 23 . 9 , i = 23.5, and z = 22.8 mag. Our approach uses deep learning, specifically integrating a Recurrent Neural Network architecture with a Mixture Density Network, to leverage magnitudes and colors as input features for constructing photometric redshift PDFs across the whole DECam Local Volume Exploration (DELVE) survey sky footprint. Subsequently, we rigorously evaluate the reliability and robustness of our estimation methodology, gauging its performance against other well-established machine learning methods to ensure the quality of our redshift estimations. Our best results constrain photometric redshifts with the bias of − 0 . 0013 , a scatter of 0.0293, and an outlier fraction of 5.1%. These point estimates are accompanied by well-calibrated PDFs evaluated using diagnostic tools such as Probability Integral Transform and Odds distribution. We also address the problem of the accessibility of PDFs in terms of disk space storage and the time demand required to generate their corresponding parameters.We present a novel Autoencoder model that reduces the size of PDF parameter arrays to one-sixth of their original length, significantly decreasing the time required for PDF generation to one-eighth of the time needed when generating PDFs directly from the magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Exploring the decision-space for renewable energy generation to enhance spatial efficiency

Decentralized power generation can play a significant role in contributing to renewable energy (RE) supply. Accordingly, regions can be important players in the transformation of the energy system. However, only scarce spatial capacities are available for a sustainable RE generation. Knowledge gaps exist concerning data and methods for integrating RE assessment and environmental planning methods. This paper presents a methodology for the integrated assessment of different RE potentials and their land requirements. The potential is contrasted with the actual availability of land for RE-generation considering environmental restrictions. An application in the Hanover region demonstrates that using energy capacity maps supports using the most efficient mixture in RE generation. Generally, a combination of wind and solar energies produces the highest energy yield per ha. Furthermore, relying primarily on generalized environmental restrictions for defining exclusion areas can be only a first step: On the one hand the assessment is probably underrating the potential for environmentally sound RE generation due to the undifferentiated exclusion of large areas of a certain protective status. On the other hand, some energy sources, in particular energy crops for bioenergy generation, are malpositioned due to missing spatially explicit information about ecosystem sensitivities and a lack of regulative possibilities. Further research is needed to explore synergistic combinations of energy potentials and their environmentally sound spatial allocation in more detail. - Highlights: • We combine models of RE potentials with technical and environmental restrictions. • We explore the resulting “decision-spaces” for regional RE development. • “Decision-spaces” are small and need to be developed carefully to avoid trade-offs. • Planning needs more differentiated analyses to test RE allocation-scenarios. • We recommend detailed analyses on (cumulative) impacts of (multifunctional) RE use.

14 SOLAR ENERGY↗

DOE OSTI2015

Environmental impact assessment in urban transport planning: Exploring process-related barriers in Spanish practice

The effectiveness of EIA for evaluating transport planning projects is increasingly being questioned by practitioners, institutions and scholars. The academic literature has traditionally focused more on solving content-related problems with EIA (i.e. the measurement of environmental effects) than on process-related issues (i.e. the role of EIA in the planning process and the interaction between key actors). Focusing only on technical improvements is not sufficient for rectifying the effectiveness problems of EIA. In order to address this knowledge gap, the paper explores how EIA is experienced in the Spanish planning context and offers in-depth insight into EIA process-related issues in the field of urban transport planning. From the multitude of involved actors, the research focuses on exploring the perceptions of the two main professional groups: EIA developers and transport planners. Through a web-based survey we assess the importance of process-related barriers to the effective use of EIA in urban transport planning. The analyses revealed process issues based fundamentally on unstructured stakeholders involvement and an inefficient public participation - Highlights: • Qualitative research on perceptions of EIA participants on EIA processes. • Web-based survey with different participants (EIA-developers; transport planners). • It was seen an inefficient participation of stakeholders during the EIA processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Exploring Citizen Infrastructure and Environmental Priorities in Mumbai, India

Many cities worldwide seek to understand local policy priorities among their general populations. This study explores how differences in local conditions and among citizens within and across Mumbai, India shape local infrastructure (e.g. energy, water, transport) and environmental (e.g. managing pollution, climate-related extreme weather events) policy priorities for change that may or may not be aligned with local government action or global environmental sustainability concerns such as low-carbon development. In this rapidly urbanizing city, multiple issues compete for prominence, ranging from improved management of pollution and extreme weather to energy and other infrastructure services. To inform a broader perspective of policy priorities for urban development and risk mitigation, a survey was conducted among over 1200 citizens. The survey explored the state of local conditions, the challenges citizens face, and the ways in which differences in local conditions (socio-institutional, infrastructure, and health-related) demonstrate inequities and influence how citizens perceive risks and rank priorities for the future design and implementation of local planning, policy, and community-based efforts. With growing discussion and tensions surrounding the new urban sustainable development goal, announced by the UN in late September 2015, and a new global urban agenda document to be agreed upon at 'Habitat III', issues on whether sustainable urbanization priorities should be set at the international, national or local level remain controversial. As such, this study aims to first understand determinants of and variations in local priorities across one city, with implications discussed for local-to-global urban sustainability. Findings from survey results indicate the determinants and variation in conditions such as age, assets, levels of participation in residential action groups, the health outcome of chronic asthma, and the infrastructure service of piped water provision to homes are significant in shaping the top infrastructure and environmental policy priorities that include water supply and sanitation, air pollution, waste, and extreme heat.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

A probabilistic application of oil and gas data for exploration stage geothermal reservoir assessment in the Appalachian Basin

Geothermal energy is a renewable, widespread, baseload energy source that has the potential to supply a large portion of the world’s energy needs. High development risk, specifically high drilling costs combined with uncertainty in subsurface flow properties, have hampered growth of geothermal energy development. One option to reduce subsurface risk is to target locations where reservoir data are already available, including sedimentary basins where there has been extensive hydrocarbon production. Sedimentary basins are widespread and often have suitable geothermal gradients. This chapter presents a low-cost methodology that can be used at the pre-drilling exploration phase of a low-temperature geothermal project to predict the location of high-productivity and low-risk reservoirs, applied to a case study of the Appalachian Basin in the eastern United States. Because only averaged reservoir data were available for analysis, the technique uses a Monte Carlo simulation of the Reservoir Flow Capacity (RFC) and Reservoir Productivity Index (RPI) for over 1800 individual reservoirs, using liquid water or supercritical carbon dioxide (sCO 2 ) as the reservoir fluid. RFC is used as an initial screening tool to identify high-priority geologic formations and reservoirs. Here our results indicate that 99% of the reservoirs in the basin are of insufficient quality for geothermal heat production with water as the assumed fluid and without using stimulation technologies associated with Enhanced Geothermal Systems (EGS). RPI is also used as an alternative metric to identify high-productivity reservoirs. When comparing the RPI results to natural gas production volumes from several selected reservoirs, the predicted RPI proves to be a good estimate of flow potential for porous reservoirs, but overestimates flow by a factor of three for fractured or vuggy reservoirs. A greater uncertainty ought to be utilized when applying the RPI equation to non-porous media, therefore we recommend utilizing the RPI metric when higher resolution data are available for analysis. This methodology can be utilized in other basins that have experienced hydrocarbon exploration and production, to highlight low-risk reservoirs or geologic formations for further geothermal development.

15 GEOTHERMAL ENERGY↗