Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Shale”

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.

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

At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Prediction and demonstration of periodic tensile cracking in rate-dependent porous cement

Periodic dilation bands are shown to occur when cylinder-shaped saturated cement specimens are subjected to rapid decompression, with the spacing between the bands scaling as a power law of the decompression time. This behavior is predicted by theory, which is specified to this scenario based on prior work that was more general and applied to compaction. Specifically, the formation of the bands is shown to coincide with periodicity that naturally arises in the effective stress when the material follows a Terzaghi-type consolidation law, although in reverse for dilation and with material deformation described by a rate-dependent viscoplastic law. When strain rate is proportional to effective stress to a power that is greater than one, periodic regions of tensile effective stress arise through the poromechanical fluid-solid coupling. The theoretically-predicted exponent of the resulting power-law relationship between dilation band spacing and unloading time successfully brackets the experimental results, for which it is observed that the exponent is slightly stronger than a square-root relationship (0.28 to 0.67) at testing temperatures of 20 °C and 90 °C. Further, these results demonstrate that rapid-depressurization leads to periodic fracturing that could, on the one hand, be detrimental to the isolation provided by cement used to seal wellbores in the petroleum industry. On the other hand, the dilation bands could also be favorable to production if generated in low-permeability reservoir rocks such as shales that are targeted for petroleum production or granites that are targeted for geothermal energy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of the economic implications of varied pressure drawdown strategies generated using a real-time, rapid predictive, multi-fidelity model for unconventional oil and gas wells

Experience has suggested that pressure maintenance in hydraulically fractured reservoirs via lower, more sustained production drawdowns may offer improved cumulative recovery and overall resource extraction efficiency compared to more rapid drawdown approaches aimed at generating high initial production. However, given the inherent variability of oil and natural gas markets, operators pursue production strategies that maximize profitability over resource extraction efficiency. This study focuses on evaluating the implications of contrasting pressure drawdown strategies on the long-term production and resulting economics for a real, producing unconventional gas well in the Marcellus Shale of the Appalachian Basin using a techno-economic analysis approach. Our research combines elements of well-specific horizontal well design, production forecasting, equipment sizing and capital cost estimation, operating cost estimation, and revenue and tax calculations. Gas production forecast outlook scenarios were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning workflow and 2) traditional reservoir simulation. A discounted cash flow model was used to evaluate the resulting economic implications for each drawdown scenario—generating output for exploring the coupled effect of factors like the timing and volume of gas production, prevailing economic and market conditions for natural gas, and overall estimated ultimate recovery on profitability metrics such as internal rate of return and net present value. Results show that there is potential to maximize the cumulative gas produced in the specific case study well by employing a lower pressure drawdown. Conversely, the greatest profitability is achieved using rapid drawdown as signified by a small, specific subset of our outlook scenarios. On an averaging basis, we find that the combinations of highest cumulative producing and most profitable scenarios occur under lower drawdowns with long (>40 years) producing timeframes, but require higher relative gas price and lower discounting considerations. Further, the machine learning predictive outlooking capability proved effective for enabling rapid generation of a multitude of scenario forecasts. As a result, a variety of prominent example cases could be generated to strike the balance of greater productivity and economic return given their associated producing features and economic conditions when compared to similar producing scenarios—critical insight that offers improved decision support for unconventional oil and gas operations.

42 ENGINEERING↗
DOE OSTI2025

A review on advances in oxidative coupling of methane (OCM) for industrial use and prospects of CO 2 –H 2 O splitting integration

The discovery of shale gas reserves has encouraged the development of direct methods for methane conversion into valuable chemicals, offering an alternative to indirect approaches that involve an energy-intensive and intermittent syngas production step, leading to high CO 2 emissions. Amongst the direct methods, the oxidative coupling of methane (OCM) is a potential pathway to reduce CO 2 emissions and can produce commodity chemicals such as ethylene, a chemical regarded as central to the petrochemical industry. Even though OCM has been studied for over four decades, the technology still has not found commercial application. Amongst the challenges regarding industrial deployment of OCM, the most significant one is the requirement of a high ethylene yield of 30 % which is currently reported to be around 20 %. Moreover, the highly exothermic nature of the process and controlling the carbon selectivity over oxides of carbon (COx) is the heart of the problem. Numerous researchers have presented promising results in terms of catalysts, reactor designs and feeding strategies for OCM. However, due to lack of inclusiveness in the results, none of the combination of catalysts, reactors and system optimizations has been able to bring about its industrial viability. The current paper presents an extensive review of the noteworthy attempts to achieve industrial targets for OCM. Moreover, a comprehensive criteria is presented which highlights the desired end state for the industrial deployment of OCM technology. Furthermore, the criteria is based on literature survey and a comparison with industrially deployed ethylene production plants i.e., naphtha or ethane steam cracker plants. Finally, a novel integration technology is presented which includes a combination of OCM and CO 2 -H 2 O splitting in a chemical looping reactor design to enable efficient energy utilization and minimal heat losses to the environment.

CO2 Splitting↗
DOE OSTI2026

Coupling geophysical, geological, geochemical and mineralogical assessments to examine preferential contaminant transport pathways in interbedded fractured bedrock

This study shows that a multi-faceted approach, combining borehole geophysical logging and surface seismic P-wave first-arrival tomography with confirmatory coring, well installation, and chemical and mineralogical analysis, is effective for identifying difficult-to-locate preferential contaminant transport pathways in deeper fractured bedrock. Seismic tomography detected porous 10–20 m wide elongated fractured conduits that allow acidic groundwater contaminated with uranium (U) and nitrate (NO 3 - ) to migrate within interbedded shale-limestone bedrock over 1000 m from a former disposal facility (S-3 Ponds site) located at the DOE Y-12 National Security Complex in Tennessee (USA). Conventional drilling techniques would easily miss these conduits because they are oriented parallel with fractured bedding planes. Synchrotron analysis of aquifer solids revealed that > 95 % of the U is hexavalent (U VI ). This uranyl (UO 2 2+ ) species is coordinated with carbonate, iron oxide, silicate and phosphate minerals within cemented white to yellow precipitates, which contain U concentrations as high as ∼21.6 % by weight fraction. Identifying the presence of these mineral phases, enables a further understanding of the potential effectiveness of remediation actions. The combination of methodologies presented here can also be applied to other explorations, such as the detection of water supply.

Fate and transport↗
DOE OSTI2020

Towards real-time forecasting of natural gas production by harnessing graph theory for stochastic discrete fracture networks

In this work, we compare hydrocarbon production curves obtained from a graph-based reduced-order model with the high-fidelity Discrete Fracture Network (DFN) predictions for a fracture network created using data from a real shale site. We observe that the bounds for the high fidelity DFN model lie within the bounds for the reduced order model, implying that the reduced-order model provides a conservative estimate. Moreover, we found that except for first-passage times and late arriving mass, the production curves from the reduced-order model predict transport accurately. However, it is to be noted that the results are inspite of trading a three-dimensional geometry for a reduced system in the form of a graph, one that is 500–1000 times faster in terms of computational efficiency (for this particular application). In addition, we also compare the production curves for large drawdown and small drawdown using our graph approach. The reduced-order model is successful in showing that the long term productivity is higher in case of small drawdown although the initial productivity is higher for large drawdown. Thus, this reduced-order model offers great potential in uncertainty quantification for production, as well as in providing operators with information to make real-time decisions for optimal production.

03 NATURAL GAS↗
DOE OSTI2021

Characterizing mineralization on low carbon steel exposed to aerated and degassed synthetic hydraulic fracture fluids

This study investigates the mineralization occurring at the interface between injected hydraulic fracturing fluids and steel production casing during the shut-in period of unconventional shale wells. Mild steel coupons were reacted with synthetic hydraulic fracturing fluids with varying base fluid and dissolved gas concentrations. Experiments were carried out in an autoclave system set at 50 °C and 2000 PSI for 2 and 14 days. Physical and mineralogical changes to the steel coupons’ surface were characterized using an FEI Quanta 600 field emission gun (FEG) scanning electron microscope (SEM) and a PANalytical XPert Pro diffractometer. Barite precipitation occurred ubiquitously during the first 48 hours in all experimental scenarios. Sulfate radicals created from degradation and reduction of ammonium persulfate breakers facilitate barite formation. Concomitant barite and corrosion related precipitates on the sample surfaces suggest iron hydroxy salts act as nucleation sites for mineral scale growth. These results suggest hydraulic fracturing fluids may have deleterious effects on the wellbore before production of the well begins.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Critical mineral source potential from oil & gas produced waters in the United States

The volume of produced water, a by-product of oil & gas operations and other energy processes, has been growing across the United States (U.S.) along with the need to manage or recycle this wastewater. Produced water contains many naturally occurring elements of varying concentrations, including critical minerals which are essential to the clean energy transition. However, the current understanding of critical mineral concentrations in produced water and the associated volumes across the U.S. is limited. This study has assessed available databases and literature to gain insight into the presence and concentration of five high priority critical minerals, namely cobalt, lithium, magnesium, manganese, and nickel. The U.S. Geological Survey's National Produced Waters Geochemical Database was the main data source used for determining average critical mineral concentrations in produced water from the major oil and gas reservoirs in the U.S. The volumes of produced water for these major reservoirs were coupled with these concentrations to provide insights into where critical minerals are likely to have high abundance and therefore more recovery options. The analysis indicated the highest recovery potential for lithium and magnesium from produced water in the Permian basin and the Marcellus shale region. However, these assessments should be considered conservative due to the limited availability of reliable concentration data. Finally, it is expected more critical mineral recovery options could emerge with comprehensive characterization data from more recent and representative sources of produced water.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Comparison of direct and CO 2 -oxidative dehydrogenation of propane

Propane dehydrogenation to propylene has received increasing attention due to the fast growth in propylene demand and the exploration of shale gas containing propane. Direct dehydrogenation of propane (DDHP) offers high propylene selectivity but is limited by quick deactivation due to coke formation. CO 2 -assisted oxidative dehydrogenation of propane (CO 2 -ODHP) can consume CO 2 and meanwhile reduce coke deposition via the reverse Boudouard reaction. Here in the current review, direct and CO 2 -assisted dehydrogenation of propane has been compared from three aspects: reaction mechanisms, catalyst compositions, and CO 2 footprint analysis. As the average CO 2 emissions from electricity generation decrease due to the utilization of renewable energy, CO 2 -ODHP potentially leads to a net-negative CO 2 footprint while DDHP cannot.

58 GEOSCIENCES↗
DOE OSTI2025

Autocorrelation and Multifractal Detrended Fluctuation Analyses Reveal Superdiffusive Mass Transport in Solvent-Filled Nanoporous Media

Fluorescence fluctuation spectroscopy experiments were conducted to better understand the complex mass transport dynamics of organic molecules in liquid-filled nanoporous media. Anodic aluminum oxide (AAO) membranes incorporating 10 and 20 nm diameter cylindrical pores were employed as model materials. Nile red (NR) dye was used as a fluorescent tracer. The dye was dissolved separately in ethanol and toluene at a concentration of 20 nM and used to fill the membrane nanopores. Confocal fluorescence microscopy was employed to capture photon intensity time series data reflecting apparent diffusion of the dye within the pores. Autocorrelation of these data revealed that NR diffusion within the membranes occurred over a broad range of time scales. The autocorrelation decays were fit to a model for one-dimensional diffusion incorporating both fast and slow components having apparent diffusion coefficients, D f and D s , differing by a factor of ∼100. The fast mechanism was attributed to hindered bulk-like diffusion in the central pore cavity, while slow diffusion likely involved absorption of the dye to the pore surfaces. Unfortunately, important evidence of diffusion anomalies is lost in the broad autocorrelation decays obtained. The method of multifractal detrended fluctuation analysis (MF-DFA) was applied to the same data as a means to overcome this limitation. MF-DFA revealed that time series acquired from within the nanopores were multifractal and exhibited evidence of anomalous superdiffusion, likely resulting from the participation of a desorption-mediated diffusion mechanism. Monte Carlo simulations of time series modeling desorption-mediated diffusion in cylindrical nanopores provided support for this assignment. Here, the new knowledge gained affords an improved understanding of hydrocarbon dynamics within nanoporous oil and gas shales.

Diffusion↗
DOE OSTI2022

Autothermal Chemical Looping Oxidative Dehydrogenation of Ethane: Redox Catalyst Performance, Longevity, and Process Analysis

Energy-efficient upgrading of stranded ethane from shale gas to olefins holds the promise of increasing the supply of useful chemical feedstocks while reducing flaring-based CO 2 emissions. Previously, we reported a modular ethane-to-liquids (M-ETL) system based on a chemical looping oxidative dehydrogenation (CL-ODH) scheme. In this article, we present long-term (>1200 h) results of Li 2 CO 3 -promoted La 0.8 Sr 0.2 FeO 3 corresponding to ~4125 CL-ODH cycles in a large laboratory-scale packed bed reactor. Temperature monitoring along the bed length confirmed the exothermicity of both the oxidative dehydrogenation and regeneration steps, enabling an autothermal operation. Product gas analysis indicated that the redox catalyst maintains a high C 2+ selectivity (~90%) and ethane conversion (~67%) at 735 °C after continuous cycling of >1000 h. As a result, product distributions and heats of reactions were used to update our M-ETL process model for revised techno-economic analysis, demonstrating that the current system is economically viable with relatively low required selling prices across a wide range of operating scenarios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Hierarchical Galloaluminosilicate MFI Catalysts for Ethane Nonoxidative Dehydroaromatization

This study presented an approach to overcome diffusion limitation and imbalance between Brønsted and Lewis acidities that affect conversion and aromatic yield in alkane nonoxidative dehydroaromatization (DHA) conversion. Three different Ga-promoted ZSM-5 catalysts were synthesized for the ethane DHA reaction. The hierarchical galloaluminosilicate Meso-GaZSM-5 was prepared by the solid-state crystallization technique wherein Ga was introduced through the in situ synthesis process. The microporous galloaluminosilicate Micro-GaZSM-5 was synthesized by the hydrothermal technique wherein Ga was introduced in situ during zeolite formation. The hierarchically structured Ga-Meso-ZSM-5 was synthesized by the solid-state crystallization method, but the Ga was introduced by the incipient wetness method. Additional Pt was incorporated by the incipient wetness technique for all three catalysts to enhance the DHA activity. The solid-state crystallization technique created the hierarchical structure without using a template. With the in situ technique, Ga species replaced the Al framework, reducing the strong Brønsted acidity. Meanwhile, they created the extraframework GaO + , introducing the strong Lewis acid sites into catalysts. Due to better synergistic interaction between the oxidation state of metals, acidic properties, and catalyst porosity, Pt-Meso-GaZSM-5 showed higher C 2 H 6 conversion and aromatic selectivity. The improvement on diffusivity not only reduces the effect of channel blockage but also improves the utilization of active sites. As a result, this work sheds light on the direct, nonoxidative conversion of shale gas without going through the syngas route.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multiscale Modeling of a Direct Nonoxidative Methane Dehydroaromatization Reactor with a Validated Model for Catalyst Deactivation

Due to the recent boom in shale gas production, aromatics production using direct nonoxidative methane dehydroaromatization (DHA) is being investigated extensively. However, due to rapid coke formation, catalysts in the nonoxidative methane DHA reactors get deactivated, which is one of the critical issues for the commercial success of the methane DHA process. In this paper, a model for catalyst deactivation is developed. Rate models for other DHA reactions are developed by considering the decrease in the catalyst activity with time. Due to the very fast coke formation rate on the fresh catalyst, there is coke formation immediately upon the introduction of the feed. Therefore, an algorithm is developed for estimation of the initial state of the reactor and the kinetic parameters by coupling an iterative direct substitution approach with an optimization approach. Transient experimental data from an in-house reactor are first reconciled and then used for developing the kinetic model including the coke formation model. Using the rate model, a dynamic, heterogeneous, multiscale reactor model with embedded heating is developed. Here, the model couples the catalyst pellet level model with a reactor level model. Impacts of temperature, L/D ratio, and scheduling of reactors on variability in conversion and yield with time are studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Probing Pore Size and Connectivity in Porous Silicas Using 13C MAS NMR Spectroscopy of Supercritical Methane

Measuring the pore size and pore-size distributions and exploring the fluid-exchange dynamics between different types of pores in porous materials remains a significant experimental challenge but is critical to understanding catalysis, chromatography, nutrient cycling, and a whole range of geochemical phenomena, including shale gas and tight gas extraction. Here, we present the results of 1D 13 C NMR and 2D exchange spectroscopy (EXSY) NMR investigations of a porous silica using supercritical methane (scCH 4 ) as a direct probe of pore size and fluid exchange between pore types. The results show that the 13 C chemical shift of scCH 4 adsorbed in nanometer-scale silica pores becomes more negative with increasing pore diameter, in agreement with trends reported for gas hydrates, zeolites, MOFs, and clays and other microporous (<10 nm pores) geochemical materials. These 13 C chemical shifts follow a natural log–linear trend with pore size in the vacuum-dried porous silicas studied here, allowing one to predict pore size based on the 13 C chemical shift in dry silica nanopores. The EXSY and 1D 13 C NMR results both show that CH 4 exchanges between pore and bulk fluid environments over rate scales from 0.01 to 1 kHz in vacuum-dried samples and that exchange dynamics must be considered when interpreting 13 C NMR of pore-adsorbed CH 4 . Introducing H 2 O to the system causes the 13 C chemical shift to become more negative with increasing H 2 O content as a result of H 2 O preferentially filling small pores, forcing CH 4 to occupy larger pores that are better connected to the bulk environment. Likewise, the 1D 13 C data show a decreased distribution of exchange rates between pore-adsorbed and bulk CH 4 in the presence of H 2 O.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modeling Nanoconfinement Effects Using Active Learning

Predicting the spatial configuration of gas in nanopores of is relevant in applications such as fluid flow forecasting and hydrocarbon reserves estimation. For example, shale reservoirs have suffered from computationally intractable multiscale problems, since fluid properties such as viscosity, density, and adsorption must be calculated by using expensive molecular dynamics (MD) simulations within each nanopore, whereas flow through these connected nanopores must be simulated at the micrometer scale. We utilize machine learning techniques to quickly and accurately model nanoscale confinement effects as an important step toward bridging the nano and micro scales. Our workflow is based on building and training physics-based deep-neural-networks models by learning from a database of MD calculations. The model accounts for the adsorption phenomenon by predicting the statistical distribution of gas inside nanopores. Because large databases of MD calculations are expensive to create, we investigate active learning (AL) as a data set construction strategy. In this workflow, new data are selected based on the model uncertainty via the query-by-committee approach. We show that our workflow obtains accurate models that generalize to real scanning electron microscopy geometries with 1/10th of the number of MD calculations required vs random data set generation. Our method enables the possibility of modeling nanoconfinement effects at the mesoscale, where complex connected sets of nanopores affect flow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Effect of Confinement on the Density and Diffusivity of Organic Molecules in Single-Digit Nanopores Relative to Bulk Fluid Behavior

Prediction of fluid properties in microporous and mesoporous confinement is non-trivial due to distinct influences from pore surface functionality and shape and fluid molecular characteristics. The vast majority of literature focuses nearly exclusively on a small number of components that are generally low molecular weight gases and vapors. Missing are studies that utilize a relatively large number of compounds that are liquid at ambient conditions to probe the impact of molecular shape and size on confined fluid properties. Such materials are of great interest in the extraction of oil and gas from shale reservoirs or for the design of selective adsorbents for chemical separation. In this work, we reveal non-intuitive relationships that emerge when comparing bulk fluid properties to those when confined in amorphous silica single-digit nanopores (approx. 5 nm SBA-15), specifically the confined density and self-diffusivity. A counterintuitive result was obtained where larger molecules had relatively faster self-diffusivities; however, this behavior was revealed to be caused by these larger compounds exhibiting a relatively low density when confined. As the prediction of confined fluid properties impacts a diversity of disciplines, the results highlight the need for additional investigations where consistent and large-scale experimental procedures are employed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine Learning Self-Diffusion Prediction for Lennard-Jones Fluids in Pores

Predicting the diffusion coefficient of fluids under nanoconfinement is important for many applications including the extraction of shale gas from kerogen and product turnover in porous catalysts. Due to the large number of important variables, including pore shape and size, fluid temperature and density, and the fluid–wall interaction strength, simulating diffusion coefficients using molecular dynamics (MD) in a systematic study could prove to be prohibitively expensive. Here, we use machine learning models trained on a subset of MD data to predict the self-diffusion coefficients of Lennard-Jones fluids in pores. Our MD data set contains 2280 simulations of ideal slit pore, cylindrical pore, and hexagonal pore geometries. We use the forward feature selection method to determine the most useful features (i.e., descriptors) for developing an artificial neutral network (ANN) model with an emphasis on easily acquired features. Our model shows good predictive ability with a coefficient of determination (i.e., R 2 ) of ~0.99 and a mean squared error of ~2.9 × 10 –5 . Finally, we propose an alteration to our feature set that will allow the ANN model to be applied to nonideal pore geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Electrochemically Engineered, Highly Energy-Efficient Conversion of Ethane to Ethylene and Hydrogen below 550 °C in a Protonic Ceramic Electrochemical Cell

Ethylene is one of the largest building blocks in the petrochemical industry, mainly produced by steam cracking of ethane derived from naphtha or shale gas at high temperatures (>800 °C). Despite its technical maturity and economic competitiveness, the thermal steam cracking of ethane is highly energy-intensive. In this work, an electrochemically engineered direct conversion process of ethane to produce hydrogen and ethylene using a planar protonic ceramic membrane reactor with a bi-functional three-dimensional catalytic electrode is reported, with a single-pass ethane conversion of 40% and ethylene yield of 26.7% at 550 °C. Compared with the industrial ethane steam cracking, this method saves process energy input by 45.1% and improves process energy efficiency by 50.6%, based on comprehensive process simulation using Aspen Plus software. Further, steam electrolysis treatment under the solid oxide electrolysis cell mode can regenerate the system’s catalytic performance and significantly alleviate catalytic degradation by 74%, demonstrating high techno-economic viability.

bi-functional electrode↗
DOE OSTI2022

Membrane Bioreactor Pretreatment of High-Salinity O&G Produced Water

Produced water (PW) from oil and gas production contains variable constituents that are difficult to remove with conventional treatment processes. The focus of this study was to explore the long-term performance of a membrane bioreactor (MBR) for the removal of organic constituents from PW and how performance and microbial community composition are affected by progressively increasing salinity and introduction of PW from different shale basins around the United States. Dissolved organic carbon removal from the PW remained consistent throughout the study, averaging 86% from the Denver-Julesburg basin PW and 66% removal from the Permian basin PW. Surfactant removal was less consistent, showing 87% removal of poly(ethylene glycols) (PEGs) at a total dissolved solid (TDS) concentration of 40 g/L but only 58% removal at a TDS concentration of 100 g/L. Diversity in the microbial community decreased during reactor establishment but increased at TDS concentrations above 80 g/L. Finally, the results of this study suggest that MBRs can be effective PW pretreatment processes even at high salinities.

42 ENGINEERING↗