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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Reservoir Engineering for Unconventional Gas Reservoirs: What Do We Have to Consider?

The reservoir engineer involved in the development of unconventional gas reservoirs (UGRs) is required to integrate a vast amount of data from disparate sources, and to be familiar with the data collection and assessment. There has been a rapid evolution of technology used to characterize UGR reservoir and hydraulic fracture properties, and there currently are few standardized procedures to be used as guidance. Therefore, more than ever, the reservoir engineer is required to question data sources and have an intimate knowledge of evaluation procedures. We propose a workflow for the optimization of UGR field development to guide discussion of the reservoir engineer's role in the process. Critical issues related to reservoir sample and log analysis, rate-transient and production data analysis, hydraulic and reservoir modeling and economic analysis are raised. Further, we have provided illustrations of each step of the workflow using tight gas examples. Our intent is to provide some guidance for best practices. In addition to reviewing existing methods for reservoir characterization, we introduce new methods for measuring pore size distribution (small-angle neutron scattering), evaluating core-scale heterogeneity, log-core calibration, evaluating core/log data trends to assist with scale-up of core data, and modeling flow-back of reservoir fluids immediately after well stimulation. Our focus in this manuscript is on tight and shale gas reservoirs; reservoir characterization methods for coalbed methane reservoirs have recently been discussed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Quantum simulation of charge and exciton transfer in multi-mode models using engineered reservoirs

Quantum simulation enables studies of open-system dynamics in non-perturbative regimes by programming electronic, vibrational, and environmental interactions on comparable energy scales. Trapped ions offer this capability, combining spins, phonons, and tunable dissipation on one platform. We demonstrate an open-system quantum simulation of charge and exciton transfer in a multi-mode linear vibronic coupling model. Using tailored spin-phonon interactions with reservoir engineering, we emulate a system with two dissipative vibrational modes coupled to donor and acceptor sites and track its non-equilibrium dynamics. We continuously tune the system from the charge transfer regime to the vibrationally assisted exciton transfer regime and find that degenerate modes enhance transfer rates at large energy gaps, while non-degenerate modes activate pathways that reduce the energy-gap dependence. Thus, the presence of one additional vibration introduces interfering pathways and reshapes non-perturbative excitation transfer. Our results establish a scalable, hardware-efficient route to simulate vibronic processes with engineered environments.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1974

Geothermal reservoir engineering research

The Stanford University research program on the study of stimulation and reservoir engineering of geothermal resources commenced as an interdisciplinary program in September, 1972. The broad objectives of this program have been: (1) the development of experimental and computational data to evaluate the optimum performance of fracture-stimulated geothermal reservoirs; (2) the development of a geothermal reservoir model to evaluate important thermophysical, hydrodynamic, and chemical parameters based on fluid-energy-volume balances as part of standard reservoir engineering practice; and (3) the construction of a laboratory model of an explosion-produced chimney to obtain experimental data on the processes of in-place boiling, moving flash fronts, and two-phase flow in porous and fractured hydrothermal reservoirs.

Ramey, H. J., Jr.↗
DOE OSTI2011

Nanosensors as Reservoir Engineering Tools to Map Insitu Temperature Distributions in Geothermal Reservoirs

The feasibility of using nanosensors to measure temperature distribution and predict thermal breakthrough in geothermal reservoirs is addressed in this report. Four candidate sensors were identified: melting tin-bismuth alloy nanoparticles, silica nanoparticles with covalently-attached dye, hollow silica nanoparticles with encapsulated dye and impermeable melting shells, and dye-polymer composite time-temperature indicators. Four main challenges associated with the successful implementation of temperature nanosensors were identified: nanoparticle mobility in porous and fractured media, the collection and detection of nanoparticles at the production well, engineering temperature sensing mechanisms that are both detectable and irreversible, and inferring the spatial geolocation of temperature measurements in order to map temperature distribution. Initial experiments were carried out to investigate each of these challenges. It was demonstrated in a slim-tube injection experiment that it is possible to transport silica nanoparticles over large distances through porous media. The feasibility of magnetic collection of nanoparticles from produced fluid was evaluated experimentally, and it was estimated that 3% of the injected nanoparticles were recovered in a prototype magnetic collection device. An analysis technique was tailored to nanosensors with a dye-release mechanism to estimate temperature measurement geolocation by analyzing the return curve of the released dye. This technique was used in a hypothetical example problem, and good estimates of geolocation were achieved. Tin-bismuth alloy nanoparticles were synthesized using a sonochemical method, and a bench heating experiment was performed using these nanoparticles. Particle growth due to melting was observed, indicating that tin-bismuth nanoparticles have potential as temperature nanosensors

15 GEOTHERMAL ENERGY↗
DOE OSTI2013

Reservoir Engineering Optimization Strategies for Subsurface CO 2 Storage

The purpose of this report is to outline a methodology for calculating the optimum number of injection wells for geologic CCS. The methodology is intended primarily for reservoir pressure management, and factors in cost as well. Efficiency may come in many forms depending on project goals; therefore, various results are presented simultaneously. The developed methodology is illustrated via application in a case study of the Rocky Mountain Carbon Capture and Storage (RMCCS) project, including a CCS candidate site near Craig, Colorado, USA. The forecasting method provided reasonable estimates of cost and injection volume when compared to simulated results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Enhancing Entanglement: Non-Markovian and Floquet Reservoir Engineering in Many-Qubit Superconducting Quantum Circuits

This is an experimental and theoretical project to leverage dissipation engineering under non-Markovian settings in order to aid in the preparation and stabilization of large, non-trivial, entangled quantum states. This project is a collaborative effort between the Painter group at Caltech and the Clerk group at the University of Chicago. By utilization of superconducting qubits coupled to the metamaterial waveguide described in the proposal, we tackle this goal via two parallel thrusts: (i) non-Markovian dynamics of a superconducting qubit strongly coupled to a slow-light waveguide reservoir and generation of 2D cluster states and (ii) many-qubit waveguide circuit QED for studying quantum many-body physics. In addition to device development and testing, we are also developing theoretical methods for understanding physics in the deep non-Markovian regime and driven-dissipative protocols for preparing and stabilizing the quantum many-body states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Quantum simulation of dissipative processes without reservoir engineering

We present a quantum algorithm to simulate general finite dimensional Lindblad master equations without the requirement of engineering the system-environment interactions. The proposed method is able to simulate both Markovian and non-Markovian quantum dynamics. It consists in the quantum computation of the dissipative corrections to the unitary evolution of the system of interest, via the reconstruction of the response functions associated with the Lindblad operators. Our approach is equally applicable to dynamics generated by effectively non-Hermitian Hamiltonians. We confirm the quality of our method providing specific error bounds that quantify its accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1977

Applications of aerospace technology to petroleum extraction and reservoir engineering

Through contacts with the petroleum industry, the petroleum service industry, universities and government agencies, important petroleum extraction problems were identified. For each problem, areas of aerospace technology that might aid in its solution were also identified, where possible. Some of the problems were selected for further consideration. Work on these problems led to the formulation of specific concepts as candidate for development. Each concept is addressed to the solution of specific extraction problems and makes use of specific areas of aerospace technology.

Jaffe, L. D.↗
DOE OSTI2022

Coupling subsurface and above-surface models for optimizing the design of borefields and district heating and cooling systems in the presence of varying water-table depth. In: Proceedings, 46th Workshop on Geothermal Reservoir Engineering

Dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes, without flow of groundwater. On the other hand, detailed simulation tools for subsurface heat and mass transfer exist, but these fall short in simulating above-surface energy systems. To support the design and operation of such systems, we have developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the ground. For the first, we use the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, we use the TOUGH simulator. TOUGH can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. In previous work, we described the coupling of these software packages, including how time-dependent boundary conditions for the borehole walls are synchronized for use in Modelica and TOUGH. We verified that the coupled Modelica/TOUGH code produced consistent results with the original Modelica code for an idealized problem in which heat transfer was purely by conduction in a uniform geologic medium. Here, we examine less idealized problems for which TOUGH’s advanced capabilities for modeling fluid flow are required. The first problem has a shallow vadose zone, and the second problem has a thicker vadose zone with a water-table depth that varies in time, which requires a fine vertical grid discretization for the TOUGH model.

Doughtry, Christine↗
DOE OSTI2024

SMART Deliverable 6.1.2a: Application of the ORION tool to the IBDP Carbon Storage Site

Forecasting and managing potential induced seismic activity is one of the challenges facing commercialscale geologic carbon sequestration (GCS), as well as other geologic energy extraction and byproduct disposal technologies. Historically, the process to develop robust, science-based forecasts of induced seismicity has required an integrated effort from experts in seismology, geomechanics, and reservoir engineering to manage data, develop and evaluate models of subsurface processes, and to calibrate and interpret the results from a range of models to understand site behavior relative to prescribed standards and in the context of uncertainty in geologic characterization data, forecasting models, and operational scenario uncertainty. The Operational Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by two U.S. DOE-funded initiatives: the National Risk Assessment Partnership (NRAP) and the Scienceinformed Machine Learning for Accelerating Real Time Decisions in Subsurface Applications (SMART) Initiative. ORION is designed to provide functionality to support decision making about seismic hazard analysis and risk management for GCS stakeholders ranging from the public to site operators to expert seismologists. The tool, which is written as open-source code in the Python programming language, is composed of a desktop graphical user interface (GUI) and an underlying forecasting engine. The forecasting engine uses available reservoir properties, well and fluid injection scenario details, and observed seismic catalog data as inputs to produce a set of temporal and spatio-temporal seismic forecasts.

58 GEOSCIENCES↗
DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗
DOE OSTI2019

EGS Collab: 3D Geophysical Model Around the Sanford Underground Research Facility

This package contains data associated with a proceedings paper (linked below) submitted to the 44th Workshop on Geothermal Reservoir Engineering. The Geophysical Model text file contains density, P- and S-wave seismic speeds on a 3D grid. The file has six columns and provides latitude (degree), longitude (degree), depth (km), P-wave speed (km/s), S-wave speed (km/s), and density (g/cm^3) at each grid point. The Interactive Geophysical Model API file is an interactive visualization of the 3D geophysical model. The visualization allows users to view depth slices and vertical profiles of the model side by side. The depth of the slices and the location of the profile can be changed. Reference: Chai, C., Maceira, M., Santos-Villalobos, H. J., and EGS Collab team, 2019, Subsurface Seismic Structure around the Sanford Underground Research Facility, in PROCEEDINGS, 44th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Trade off-free entanglement stabilization in a superconducting qutrit-qubit system

Abstract Quantum reservoir engineering is a powerful framework for autonomous quantum state preparation and error correction. However, traditional approaches to reservoir engineering are hindered by unavoidable coherent leakage out of the target state, which imposes an inherent trade off between achievable steady-state state fidelity and stabilization rate. In this work we demonstrate a protocol that achieves trade off-free Bell state stabilization in a qutrit-qubit system realized on a circuit-QED platform. We accomplish this by creating a purely dissipative channel for population transfer into the target state, mediated by strong parametric interactions coupling the second-excited state of a superconducting transmon and the engineered bath resonator. Our scheme achieves a state preparation fidelity of 84% with a stabilization time constant of 339 ns, leading to a 54 ns error-time product in a solid-state quantum information platform.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Mechanisms of Waterflood Inefficiency: Analysis of Geological, Petrophysical and Reservoir History, a Field Case Study of FWU (East Section)

The petroleum reservoir represents a complex heterogeneous system that requires thorough characterization prior to the implementation of any incremental recovery technique. One of the most commonly utilized and successful secondary recovery techniques is waterflooding. However, a lack of sufficient investigation into the inherent behavior and characteristics of the reservoir formation in situ can result in failure or suboptimal performance of waterflood operations. Therefore, a comprehensive understanding of the geological history, static and dynamic reservoir characteristics, and petrophysical data is essential for analyzing the mechanisms and causes of waterflood inefficiency and failure. In this study, waterflood inefficiency was observed in the Morrow B reservoir located in the Farnsworth Unit, situated in the northwestern shelf of the Anadarko Basin, Texas. To assess the potential mechanisms behind the inefficiency of waterflooding in the east half, geological, petrophysical, and reservoir engineering data, along with historical information, were integrated, reviewed, and analyzed. The integration and analysis of these datasets revealed that several factors contributed to the waterflood inefficiency. Firstly, the presence of abundant dispersed authigenic clays within the reservoir, worsened by low reservoir quality and high heterogeneity, led to unfavorable conditions for waterflood operations. The use of freshwater for flooding exacerbated the adverse effects of sensitive and migratory clays, further hampering the effectiveness of the waterflood. In addition to these factors, several reservoir engineering issues played a significant role in the inefficiency of waterflooding. These issues included inadequate perforation strategies due to the absence of detailed hydraulic flow units (HFUs) and rock typing, random placement of injectors, and uncontrolled injected fresh water. These external controlling parameters further contributed to the overall inefficiencies observed during waterflood operations in the east half of the reservoir. A detailed understanding of the mechanistic factors of inefficient waterflood operation will provide adequate insights into the development of the improved recovery technique for the field.

Morgan, Anthony (ORCID:0000000211519153)↗
DOE OSTI2016

Integrating a reservoir regulation scheme into a spatially distributed hydrological model

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, natural streamflow timing and magnitude have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land use/land cover and climate changes. To understand the fine scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is of desire. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Model (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM model was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficients of determination (R2) and the Nash-Sutcliff Efficiency (NSE) are 0.85 and 0.75, respectively. These results suggest that this reservoir module has promise for use in sub-monthly hydrological simulations. Enabled with the new reservoir component, the DHSVM model provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.

Zhao, Gang↗