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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Utah FORGE 9-3664: Development of Tagged Proppant for Conductivity Enhancement and Reservoir Characterization - 2024 Annual Workshop Presentation

This is a presentation on the Development and Testing of Tagged Proppant for Fracture Conductivity Enhancement and Reservoir Characterization in EGS by The University of Oklahoma, presented by Ahmad Ghassemi. This slide presentation video discusses the development and testing of new proppants that can be used in geothermal conditions of at least 250 degrees C and at differential pressures of 35-70 MPa. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 13-15, 2024.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Elucidating the Link Between Alkali Metal Ions and Reaction-Transport Mechanisms in Cathode Electrodes for Alkali-ion Batteries

Our long-term goal is to improve the reliability of electrode materials and their ability to transport and store various metal ions for electrochemical energy storage applications. The main objective of this work was to investigate the intrinsic relationship between the role of alkali metal ions and electrochemically driven mechanical stability and kinetic properties of battery materials. The overall question was “What is the role of alkali metal ions on the electrochemical and mechanical behavior of cathode electrodes? Our guiding hypothesis was that intercalation of larger alkali metal ions (Na and K) inevitably alters the coupled transport-reaction processes during battery operation in organic electrolytes, leading to more intensive chemo-mechanical instabilities in cathode electrodes, resulting in rapid capacity fade. To validate the hypothesis, we experimentally characterized the reaction-transport processes and governing forces driving the instability of electrode materials in different alkali metal-ion environments. The project had three main tasks. The first one was to investigate intercalation-induced strains and associated stress generation, and their impact on structural deformations in composite cathode electrodes. The second task focused on identifying potential-dependent dynamic changes in the electrode-electrolyte interface in alkali metal ion batteries. The last task was focused on determining how larger alkali metal ions with slower diffusivity affect the transport-mechanics coupling at faster scan rates, compared to smaller ions with faster diffusivity in electrodes. We shortly provided the outcome of each task in the accomplishment section. This project produced 10 peer-reviewed publications (9 research papers and one review manuscript) and supported two Ph.D. students, who graduated from Oklahoma State University.

25 ENERGY STORAGE↗
DOE OSTI2025

Carbon Storage in Fold‐and‐Thrust Belts: An Overlooked Gigatonne Storage Opportunity

This study presents numerical investigations of the trapping characteristics of fold-and-thrust belt structures, defining three carbon capture and storage (CCS) play types that could be used to store commercial volumes (millions of tonnes) of CO 2 . Specifically, we present simulations of CO 2 storage in three fold-and-thrust belt models comprising a thrust-ramp, duplex, and thrust-fold geometry. To constrain these play types in realistic geology, each model is based on a study site, including a novel investigation of a greenfield saline reservoir in Virginia, USA, being considered for commercial carbon storage and two well-characterized petroleum fields: the Wilburton field in Oklahoma, USA, and the Incahuasi field in Bolivia. Our results provide insight into several key parameters, such as the long-term security of injected CO 2 in these geologies and injection strategies for maximizing storage efficiency while reducing pressure-related risk. These results improve the understanding of CCS in fold-and-thrust belt storage sites globally by describing general storage parameters that may be applied to site-specific projects. We find that thrust-ramp geometries may securely trap CO 2 through solubility and hydrodynamic trapping under suitable reservoir conditions, duplex structures may store some quantities of CO 2 but are pressure-constrained, and that thrust-ramp structures may store large quantities of CO 2 by maximizing fetch volume, which simultaneously lowers geomechanical risk by reducing pressure buildup along zones of weakness.

42 ENGINEERING↗
DOE OSTI2024

Calculating a minimum overlap period for successful intercalibration of soil moisture sensors

Abstract Long‐term in situ soil moisture monitoring inevitably requires sensors to be replaced. Ensuing discontinuities in the data record can be mitigated by intercalibration, however it is unclear how long the existing sensor needs to remain alongside the newly installed before there is enough overlapping data to generate a robust intercalibration. We used 154 pairs of established and newly installed sensors within the Marena, Oklahoma, In Situ Sensor Testbed to determine if there is a minimum overlap time that should be considered when planning upcoming replacements. Hourly observations of the existing sensor were linearly calibrated to those of the newly installed sensor with coefficients determined from overlap periods incremented by 30 days until a reference period of 2 years was reached. The resulting bias, root‐mean‐square error, and correlation coefficient for sensor pairs indicate that a minimum of 6 to 9 months of overlapping data are required to generate a successful intercalibration. Extending that to a full year before decommissioning the old sensor results in a stable intercalibration with higher confidence.

Agriculture↗
DOE OSTI2022

A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part III: Boundary-Layer Parametrizations

Numerical weather prediction is often used to supply the mean wind and turbulence fields for atmospheric transport and dispersion plume models as they provide dense geographic coverage in comparison to typically sparse monitoring networks. Here, the Weather Research and Forecasting (WRF) model 4.0 was run over the month-long period of the Joint Urban 2003 field campaign conducted in Oklahoma City. We compare three different simulations in their ability to reproduce the observations, each using a different boundary-layer parametrization. Specifically, we examine the Mellor–Yamada–Janjic (MYJ), Yonsei University (YSU), and Mellor–Yamada–Nakanishi–Niino (MYNN) boundary-layer parametrizations. All three predict the wind speed well during the day but overpredict it at night. The MYNN parametrization is better than MYJ at predicting the daytime turbulence in the surface layer, but both underpredict the nocturnal turbulence. Additionally, the MYJ parametrization is best at predicting the reciprocal Obukhov length, while MYNN and YSU both significantly overpredict thermal stability. Reconstructing the reciprocal Obukhov length from other simulated parameters produces more accurate values for both parametrizations. All three models overpredict the boundary-layer height, particularly under convective conditions. The MYJ parametrization overestimates boundary-layer height the most, while YSU and MYNN have comparable performance with MYNN having an advantage in predicting the stable boundary-layer height. Several days were found where the WRF simulations predict significant deviations from the prevailing diurnal pattern in wind direction, which are not found in the observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Using ground-based lidar data to investigate the water–vapor budget in the daytime atmospheric boundary layer

The moisture advection term in the water–vapor budget equation is investigated with a combination of a vertically-staring water–vapor lidar and Doppler lidar systems. These instruments make it possible to get the mean profile of moisture tendency and the latent heat flux (LHF) divergence. We use data of the Land–Atmosphere Feedback Experiment (LAFE) at the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site, Oklahoma, USA, collected on 30 August 2017 between 15 and 24 UTC, which corresponds to 09 to 18 LT. The lidars provide turbulence resolving profiles of moisture and vertical wind fluctuations. The LHF profile is derived from the covariance of these moisture and vertical wind fluctuations. The mean boundary layer height z i is determined from the peak of the moisture variance. The results demonstrate that the combination of two remote sensing instruments can be applied for determining the dominant water–vapor budget terms, namely moisture tendency, latent heat flux divergence and moisture advection.

Advection↗
DOE OSTI2021

Plentiful electricity turns wholesale prices negative

In 2020, average wholesale electricity prices in the United States fell to $21/MWh, their lowest level since the beginning of the 21st century. Low natural gas prices and the proliferation of low marginal cost resources like wind and solar had already established a trend toward lower wholesale prices, and this trend was exacerbated by declining electricity demand due to the Covid-19 pandemic in 2020. Negative real-time hourly wholesale prices occurred in about 4% of all hours and wholesale market nodes across the United States, but these were not distributed evenly. Regional clusters emerged, for example, in the Permian Basin in western Texas, and in Kansas and western Oklahoma in the Southwest Power Pool (SPP), negative prices accounted for more than 25% of all hours. Negative electricity prices result either from local congestion of the transmission system leading supply to exceed demand locally or due to system-wide oversupply. Looking at the latter condition in SPP, we find that all major generator types contribute to this excess supply, because of limited ramping flexibility or self-scheduled out-of-market unit commitments. Additional monetary production incentives such as renewable energy credits or tax credits also enable negative bids; indeed, negative prices predominantly occur when demand levels are low and wind production levels are high. Frequent negative prices can inform the value of additional renewable energy investments at specific locations, the need for transmission and storage development, and opportunities load growth or adaptation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Intensification differentially affects the delivery of multiple ecosystem services in subtropical and temperate grasslands

Intensification, the process of intensifying land management to enhance agricultural goods, results in “intensive” pastures that are planted with productive grasses and fertilized. These intensive pastures provide essential ecosystem services, including forage production for livestock. Understanding the synergies and tradeoffs of pasture intensification on the delivery of services across climatic regions is crucial to shape policies and incentives for better management of natural resources. Here, we investigated how grassland intensification affects key components of provisioning (forage productivity and quality), supporting (plant diversity) and regulating services (CO 2 and CH 4 fluxes) by comparing these services between intensive versus extensive pastures in subtropical and temperate pastures in the USDA Long-term Agroecosystem Research (LTAR) Network sites in Florida and Oklahoma, USA over multiple years. Our results suggest that grassland intensification led to a decrease in measured supporting and regulating services, but increased forage productivity in temperate pastures and forage digestibility in subtropical pastures. Intensification decreased the net CO 2 sink of subtropical pastures while it did not affect the sink capacity of temperate pastures; and it also increased environmental CH 4 emissions from subtropical pastures and reduced CH 4 uptake in temperate pastures. Intensification enhanced the global warming potential associated with C fluxes of pastures in both ecoregions. Our study demonstrates that comparisons of agroecosystems in contrasting ecoregions can reveal important drivers of ecosystem services and general or region-specific opportunities and solutions to maintaining agricultural production and reducing environmental footprints. Further LTAR network-scale comparisons of multiple ecosystem services across croplands and grazinglands intensively vs extensively managed are warranted to inform the sustainable intensification of agriculture within US and beyond. Our results highlight that achieving both food security and environmental stewardship will involve the conservation of less intensively managed pastures while adopting sustainable strategies in intensively managed pastures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Nth-plant scenario for blended pellets of Miscanthus, Switchgrass, and Corn Stover using multi-modal transportation: Biorefineries and depots in the contiguous U.S.

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Here, this study addresses the logistic challenge of mobilizing national cellulosic feedstock supplies for a sustainable bioenergy industry. A Mixed Integer Linear Programming (MILP) model was developed and updated to deliver on-spec biomass that considers both a desired quantity and quality at the biorefinery. Our supply chain analysis includes multi-modal transport (truck and rail), varying depot and biorefinery sizes, and feedstock blends of corn stover (harvested by either a two- or three-pass method), switchgrass, and miscanthus. The following US states: Illinois, Kansas, Missouri, North Carolina, Oklahoma, Georgia, and Texas were identified as key locations for producing accessible miscanthus. Based on our most optimistic scenario, using trucks as the only transportation mode in 2040 with a cost target of $\$$79/dt, corn stover, switchgrass, and miscanthus could help meet 48% of the EPA target, 173 million dry tons that translate into 7.8 billion GGE. The addition of rail transportation for biomass delivery to biorefineries could help meet 79% of the EPA target, 283 million dry tons that translate into 12.7 billion GGE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Kinetic and equilibrium reactions on natural and laboratory generation of thermogenic gases from Type II marine shale

The phenomenon that laboratory pyrolysis experiments produce much wetter gases than those in natural reservoirs is a long-recognized and debated problem in the investigation of natural gases in sedimentary basins. In this study, we explore the discrepancy by pyrolyzing a type II kerogen from the Woodford Shale in Oklahoma, compared with the previous results on the produced natural gases from the Arkoma Basin generated from the same source rock (Liu et al., 2019) with the discussion of gas and isotopic compositions at bulk and position-specific (PS) levels. An improved GC-pyrolysis-GC IRMS method is applied for the determination of PS δ 13 C of propane produced in the pyrolysis of the Woodford Shale at Easy %R o from 0.76 to 3.27. Kinetic and thermodynamic considerations of the chemical and isotopic compositions of the natural and laboratory pyrolysis gases suggest that the generation of light hydrocarbons involves uni-directional cracking reactions, exchange reactions with water, and likely reversible reactions among light hydrocarbons and other H-containing volatiles. After the gas generation in the unconventional Woodford Shale reservoirs, the C 1 -C 4 gases might have approached close to chemical equilibrium of C 1 -C 3 and isotope equilibrium of C 2 -C 1 and C 3 -C 1 pairs at their peak temperatures. The capping H for the generation of C 1 -C 4 in the Woodford Shale gases appears to have experienced at least partial exchange with the water, while that in the pyrolysis gases is only originated from organic-bound compounds with large kinetic isotope effects (KIE). Our findings indicate that elevated compound-specific and PS δ 13 C values of propane in the wet-gas cracking stage are significantly influenced by the breakdown of the thermally stable compounds (e.g., remaining kerogen, residues). A first synthesis of PS δ 13 C and δ 2 H isotopic compositions of propane from this study and the literature data suggests relatively similar isotopic structures of propane precursors in kerogens. Finally, this study demonstrates that PS isotope analysis of propane can contribute to identifying various geological (e.g., maturation, wet-gas cracking, H exchange, diffusion) and biodegradation processes.

58 GEOSCIENCES↗
DOE OSTI2023

Proxy-based Bayesian inversion of strain tensor data measured during well tests

Recent instrument developments have made it possible to measure the strain tensor caused by injecting or pumping fluid from aquifers or reservoirs, but the full value of these data is limited because the long runtimes of poroelastic forward models makes it impractical to use many inversion schemes. This limits the interpretation of strain data for managing the recovery of resources or storage of wastes in the subsurface. This paper describes a method of inverting deformation data using a poroelastic numerical simulator so the results can be used to manage reservoirs or aquifers. We developed a workflow designed to reduce the number of simulations sufficiently to make it feasible to use DREAMzs, an advanced Bayesian inversion method that translates the uncertainties from different sources into unbiased posterior parameter distributions and uncertainty envelopes around the field data. Using a KNN proxy model for the poroelastic simulator is key to reducing the overall computations, and the workflow includes a strategy for ensuring the proxy model results converge on the results from the simulator. The workflow is tested using an idealized example that verifies the ability to correctly identify parameters and characterize noise used to perturb the data. Field data from an injection test at an oil reservoir near Tulsa, Oklahoma, are also used to evaluate the efficacy of the workflow with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), where the results were used to characterize posterior parameter distribution and evaluate the prediction uncertainty. Furthermore, this workflow is significant because it enables strain tensor, or other geomechanical measurements to be interpreted to guide decision-making during energy and environmental processes in the subsurface.

42 ENGINEERING↗
DOE OSTI2020

Centroidal Voronoi tessellation based methods for optimal rain gauge location prediction

With more satellite and model precipitation data becoming available, new analytical methods are needed that can take advantage of emerging data patterns to make well informed predictions in many hydrological applications. Herein we propose a new strategy where we extract precipitation variability patterns and use correlation map to build the resulting density map that serves as an input to centroidal Voronoi tessellation construction that optimizes placement of precipitation gauges. We provide results of numerical experiments based on the data from the Alto-Adige region in Northern Italy and Oklahoma and compare them against actual gauge locations. This method provides an automated way for choosing new gauge locations and can be generalized to include physical constraints and to tackle other types of resource allocation problems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ - θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. Further, this study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Detrital U-Pb zircon and 40 Ar/ 39 Ar muscovite geochronology from Middle Pennsylvanian strata in the Anadarko Basin, Texas Panhandle, USA

The Late Mississippian-Permian Anadarko Basin formed in Texas and Oklahoma, USA as the result of inversion of Neoproterozic and Cambrian rift structures. Subsidence was driven by flexural loading of the Amarillo-Wichita Uplift, and this uplift may represent the easternmost element of the Ancestral Rocky Mountains system. The northwestern part of this basin has generally been interpreted to have been filled by sediment derived from the Ancestral Front Range Uplift, ~475 km to the northwest during the early stages of basin filling. We test this model using U-Pb detrital zircon and 40 Ar/ 39 Ar detrital muscovite results from three subsurface samples of the Morrow B sandstone in the northwestern part of the Anadarko Basin. We provide a new maximum depositional age of 310.9 ± 4.9 Ma that indicates the age of the Morrow B to be no older than late Atokan to early Desmoinesian Age (Moscovian), ~10 Myr younger than previously interpreted. In contrast to some previous interpretations, we propose that the most likely source for the sediment in the Morrow B is the Amarillo Uplift to the south. Detrital zircon and detrital muscovite data have age peaks at 900–1300 Ma, 1370 Ma and 1600–1800 Ma corresponding to derivation from Grenville, Granite-Rhyolite and Yavapai-Mazatzal basement provinces, respectively. A dominant detrital zircon peak at 1370 Ma suggests that Mesoproterozoic granites in the Amarillo Uplift were exposed by Middle Pennsylvanian time, and detritus eroded from the Amarillo Uplift dominated the lowstand sediment budget of the Texas Panhandle during this time; small volumes of sediment were likely sourced from the Ancestral Front Range. In conclusion, this study presents the first detrital geochronology data from the subsurface Anadarko Basin and the first detrital muscovite data from late Paleozoic southwestern Laurentia. The results presented here highlight the interpretive power of combined detrital zircon and muscovite datasets.

58 GEOSCIENCES↗
DOE OSTI2022

Preparation of illite coated geomaterial microfluidic surfaces: Effect of salinity and heat treatment

Unique characteristics of clay (e.g., high surface area, deficiency in positive charges) make any clay abundant shales a good source of adsorbed gas. However, the presence of clay in porous media can also affect shale rock's producibility. The clay-water interaction can cause significant swelling and fines migration in the formation and impair the overall hydrocarbon recovery from shale. Geomaterial micromodels, developed by functionalizing traditional glass or PDMS surfaces with geomaterials (e.g., calcite, Quartz, clay), can represent the physicochemical properties of the natural porous media and have been used during the last few years to understand and evaluate the solid-fluid physicochemical interactions. Here, this study focuses on developing a clay-coated geomaterial surface and investigates the effect of base fluid's salinity on clay adsorption to the glass surface. Glass capillary tubes and straight channel borosilicate glass micromodels are coated with Illite clay to represent the pore-scale clay chemistry of Caney Shale, a Mississippian unconventional play in Southern Oklahoma, USA. 10 wt% of Illite clay slurries made with brines of four different salinities are used to coat the glass-capillary tubes to understand the effect of salinity in clay adsorption on the glass surface and overall coating quality. To achieve a stable coating and evaluate the impact of heat treatment on coating's stability, straight channel glass flow cells coated with Illite clay are heat-treated at low (25 °C) and high temperature (125 °C), and the results are compared with an untreated coated surface. Flooding tests were carried out with brines of different salinities on the coated surface to evaluate the stability of the coating. The experimental results indicated a strong relationship between the brine's salinity and the adsorption of clay particles on the glass surface. An increase in brine concentration resulted in improved adsorption of clay particles on the glass surface. Experiments involving heat treating the glass surface following the coating demonstrated significant improvement in the stability of the coating.

02 PETROLEUM↗
DOE OSTI2021

Improving Prediction of Surface Solar Irradiance Variability by Integrating Observed Cloud Characteristics and Machine Learning

A 5-year, 1-minute resolution observational dataset of clouds and solar radiation was produced that includes two metrics of the variability in surface solar irradiance due to cloud type and fractional sky cover. Multiple regression models were trained to fit observations of surface solar irradiance variability from those two cloud property predictors. We found that ensemble tree-based methods, Random Forest and Gradient Boosting Machine, have the least overfitting issues and showed the best performance with an R2 of 0.42. While the observational data trained in this study was only from one site, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, initial comparisons of the seasonality of the statistics suggest that these results are relatively weather regime independent; the generality of such a finding across sites will be tested in future work. The observational data and developed machine learning model are being used to create a numerical weather prediction model parameterization to enable day-ahead solar variability prediction in a computationally efficient way. This is a first step towards creating a new paradigm of predicting day-ahead variability with the potential to provide a new tool to improve grid operation, planning, and resilience.

Riihimaki, Laura↗
DOE OSTI2022

Molecular Characterization of Organosulfate-Dominated Aerosols over Agricultural Fields from the Southern Great Plains by High-Resolution Mass Spectrometry

The molecular composition of organic aerosols, especially for day/nighttime variations of organosulfates above agricultural fields, is not well understood despite profound impacts on regional climate, crop production, air quality, and human health. Here, nanospray desorption electrospray ionization with high-resolution mass spectrometry (nano-DESI-HRMS) is used to interrogate the molecular composition of organic aerosols collected at the Southern Great Plains, located in an agricultural region of Oklahoma. Identified molecular formulae featured carbon, hydrogen, oxygen (CHO), nitrogen (CHNO), and/or sulfur (CHOS, CHNOS), with higher organosulfate proportions during daytime (41%) compared to nighttime (30%). In this work, nighttime aerosols featured increases in CHO, CHNO, and extremely low volatility organic carbon (ELVOC) species. However, due to high relative humidity, the nighttime aerosols phase state was found to be more liquid-like than daytime aerosols using parametrized glass transition temperatures. Aerosol molecular composition from an anthropogenically influenced plume (southerly winds) showed significant increases in CHOS and ELVOC species. By comparison with chamber studies, CHOS species are suspected to be of mixed biogenic and anthropogenic origin, whereas CHNOS species (not identified in the southerly winds) are suggested to predominately be of biogenic origin. Overall, this study provides key insight into organosulfates above agricultural fields, demonstrating dependence upon day/night cycles and episodic anthropogenic emissions.

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

SeismoGen: Seismic Waveform Synthesis Using GAN With Application to Seismic Data Augmentation

Abstract Detecting earthquake arrivals within seismic time series can be a challenging task. Visual, human detection has long been considered the gold standard but requires intensive manual labor that scales poorly to large data sets. In recent years, automatic detection methods based on machine learning have been developed to improve the accuracy and efficiency. However, the accuracy of those methods relies on access to a sufficient amount of high‐quality labeled training data, often tens of thousands of records or more. We aim to resolve this dilemma by answering two questions: (1) provided with a limited amount of reliable labeled data, can we use them to generate additional, realistic synthetic waveform data? and (2) can we use those synthetic data to further enrich the training set through data augmentation, thereby enhancing detection algorithms? To address these questions, we use a generative adversarial network (GAN), a type of machine learning model which has shown supreme capability in generating high‐quality synthetic samples in multiple domains. Once trained, our GAN model is capable of producing realistic seismic waveforms of multiple labels (noise and event classes). Applied to real Earth seismic data sets in Oklahoma, we show that data augmentation from our GAN‐generated synthetic waveforms can be used to improve earthquake detection algorithms in instances when only small amounts of labeled training data are available.

Wang, Tiantong↗