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DOE OSTI2015

Factors Affecting Seismic Velocity in Alluvium

Yucca Flat at the Nevada National Security Site has been selected as the Source Physics Experiment (SPE) Dry Alluvium Geology Phase II site. The alluvium in this part of Yucca Flat is typical of desert basin fill, with discontinuous beds that are highly variable in clast size and provenance. Detailed understanding of the subsurface geology will be needed for interpretation of the SPE seismic data. A 3D seismic velocity model, created for Yucca Flat using interval seismic velocity data, shows variations in velocity within alluvium near the SPE Phase II site beyond the usual gradual increase of density with depth due to compaction. In this study we examined borehole lithologic logs, geophysical logs, downhole videos, and laboratory analyses of sidewall core samples to understand which characteristics of the alluvium are related to these variations in seismic velocity. Seismic velocity of alluvium is generally related to its density, which can be affected by sediment provenance, clast size, gravel percentage, and matrix properties, in addition to compaction. This study presents a preliminary subdivision of the alluvial strata in the SPE Phase II area into mappable units expected to be significant to seismic modeling. Further refinements of the alluvial units may be possible when seismic data are obtained from SPE Phase II tests.

58 GEOSCIENCES↗

DOE OSTI2016

Fault structure, stress, or pressure control of the seismicity in shale? Insights from a controlled experiment of fluid-induced fault reactivation

It is clear that clay formations are present in reservoirs and earthquake faults, but questions remain on their mechanical behavior, as they can vary from ductile (aseismic) to brittle (seismic). An experiment, at a scale of 10 m, aims to reactivate a natural fault by fluid pressure in shale materials. The injection area was surrounded by a dense monitoring network comprising pressure, deformation, and seismicity sensors, in a well-characterized geological setting. Thirty-two microseismic events were recorded during several injection phases in five different locations within the fault zone. Their computed magnitude ranged between -4.3 and -3.7. Their spatiotemporal distribution, compared with the measured displacement at the injection points, shows that most of the deformation induced by the injection is aseismic. Whether the seismicity is controlled by the fault architecture, mineralogy of fracture filling, fluid, and/or stress state is then discussed. The fault damage zone architecture and mineralogy are of crucial importance, as seismic slip mainly localizes on the sealed-with-calcite fractures which predominate in the fault damage zone. As no seismicity is observed in the close vicinity of the injection areas, the presence of fluid seems to prevent seismic slips. The fault core acts as an impermeable hydraulic barrier that favors fluid confinement and pressurization. Therefore, the seismic behavior seems to be strongly sensitive to the structural heterogeneity (including permeability) of the fault zone, which leads to a heterogeneous stress response to the pressurized volume.

58 GEOSCIENCES↗

DOE OSTI2025

Toward more-robust, AI-enabled subsurface seismic imaging for geotechnical applications

Non-invasive seismic imaging has the potential to cost-effectively evaluate large volumes of subsurface material to inform geotechnical site investigation. However, seismic imaging using full waveform inversion (FWI) requires significant computational time and is dependent on an initial starting model. As a result, FWI has not yet been widely adopted into geotechnical practice. Previous efforts, on relatively simple two-layered models, indicate that data-driven artificial intelligence (AI) models may be as effective as FWI at predicting 2D images of shear wave velocity (V s ). Furthermore, the AI model predictions can be made almost instantaneously after data acquisition and do not require an initial starting model. We examine the generality of these findings by developing a new AI model for subsurface seismic imaging, whereby we make several notable contributions. First, we architect a multimodal AI model that combines time- and frequency-domain representations of the seismic wavefield to predict a 50 m by 20 m subsurface image of V s . Second, we developed a new diverse dataset of 100,000 images with their corresponding seismic wavefields to train the AI model. Third, we propose four physics-informed data augmentations for data-driven seismic imaging. Fourth, we develop two prediction consistency tests to evaluate the model’s performance when the true subsurface is unknown. Our final model, which has been made publicly available, is capable of predicting a subsurface V s image from a single seismic wavefield with an average, mean absolute percent error (MAPE) of 24 %. The predictive model is applied to a field dataset and shown to be consistent with local geology and shear-wave refraction measurements from the same location.

Artificial intelligence↗

DOE OSTI2015

Induced seismicity in geothermal reservoirs: A review of forecasting approaches

In order to reach Europe's 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced seismicity is often perceived as an unsolicited and uncontrollable side effect of geothermal development. In the last decade, significant advances were made in the development of models to forecast induced seismicity, which are either based on catalogues of induced seismicity, on the underlying physical processes, or on a hybrid philosophy. In this paper, we provide a comprehensive overview of the existing approaches applied to geothermal contexts. This overview will outline the advantages and drawbacks of the different approaches, identify the gaps in our understanding, and describe the needs for geothermal observations. Most of the forecasting approaches focus on the stimulation phase of enhanced geothermal systems which are most prone to generate seismic events. Besides the statistical models suited for real-time applications during reservoir stimulation, the physics-based models have the advantage of considering sub-surface characteristics and estimating the impact of fluid circulation on the reservoir. Thus, to mitigate induced seismicity during major hydraulic stimulations, application of hybrid methods in a decision support system seems the best available solution. So far, however, little attention has been paid to geochemical effects on the failure process and to production periods. Quantitative modelling of induced seismicity still is a challenging and complex matter. Appropriate resources remain to be invested for the scientific community to continue its research and development efforts to successfully forecast induced seismicity in geothermal fields. This is a prerequisite for making this renewable energy resource sustainable and accessible worldwide.

58 GEOSCIENCES↗

DOE OSTI2018

Seismicity induced by simultaneous abrupt changes of injection rate and well pressure in Hutubi Gas Field

Hutubi gas field, the largest gas storage field in China, has been operated on annual injection/extraction cycles since 9 June 2013. Here, we study the seismicity near the gas field from 9 June 2013 to 22 October 2015, a time span that the gas field has experienced three injection periods and two extraction periods, and explore its physical mechanism based on the relationship between seismicity and field operation. We identify 273 events (ML >1) in the region within 10 km of the gas field, with 97% of those occurring in the first two injection periods, 0.4% in the third injection period and 1% in the two extraction periods. Seismicity in the first two injection periods occurs mostly as shallow clusters (focal depth < 2 km) at two locations: with one along the fault that marks the southern boundary of the gas field and the other about 2 km south to the southeastern tip of the gas field with the seismicity distributed along north-south direction. The seismicity does not correlate with total gas injection volume, injection rate or well pressure. It instead occurs 11–17 hours after simultaneous abrupt increases/decreases of gas injection rate and well pressure in the field operation in the first two injection periods when some accumulative injection has reached. Such relationship is consistent with a physical mechanism that the seismicity near Hutubi gas field is induced on pore-pressured faults with a rate- and state-dependent friction law through an abrupt change of stress in elastic and undrained poroelastic responses to simultaneous abrupt changes of injection rate and well pressure. Our study also points to the possibility that induced seismicity may be controllable in some practical field operations.

58 GEOSCIENCES↗

DOE OSTI2020

A New Crater Near InSight: Implications for Seismic Impact Detectability on Mars

A new 1.5 m diameter impact crater was discovered on Mars only ~40 km from the InSight lander. Context camera images constrained its formation between 21 February and 6 April 2019; follow-up High Resolution Imaging Science Experiment images resolved the crater. During this time period, three seismic events were identified in InSight data. In this paper, we derive expected seismic signal characteristics and use them to evaluate each of the seismic events. However, none of them can definitively be associated with this source. Atmospheric perturbations are generally expected to be generated during impacts; however, in this case, no signal could be identified as related to the known impact. Using scaling relationships based on the terrestrial and lunar analogs and numerical modeling, we predict the amplitude, peak frequency, and duration of the seismic signal that would have emanated from this impact. The predicted amplitude falls near the lowest levels of the measured seismometer noise for the predicted frequency. Hence, it is not surprising this impact event was not positively identified in the seismic data. Finding this crater was a lucky event as its formation this close to InSight has a probability of only ~0.2, and the odds of capturing it in before and after images are extremely low. We revisit impact-seismic discriminators in light of real experience with a seismometer on the Martian surface. Using measured noise of the instrument, we revise our previous prediction of seismic impact detections downward, from ~a few to tens, to just ~2 per Earth year, still with an order of magnitude uncertainty.

58 GEOSCIENCES↗

DOE OSTI2020

Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning

The continuously growing amount of seismic data collected worldwide is outpacing our abilities for analysis, since to date, such datasets have been analyzed in a human-expert intensive, supervised fashion. Moreover, analyses that are conducted can be strongly biased by the standard models employed by seismologists. In response to both of these challenges, we develop a new unsupervised machine learning framework for detecting and clustering seismic signals in continuous seismic records. Our approach combines a deep scattering network and a Gaussian mixture model to cluster seismic signal segments and detect novel structures. To illustrate the power of the framework, we analyze seismic data acquired during the June 2017 Nuugaatsiaq, Greenland landslide. We demonstrate the blind detection and recovery of the repeating precursory seismicity that was recorded before the main landslide rupture, which suggests that our approach could lead to more informative forecasting of the seismic activity in seismogenic areas.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Seismic data are rich in information about subsurface formations and fluids

Seismic attributes are defined as any measured or computed information derived from seismic data. Throughout the last decades extensive work has been done in developing variety of mathematical approaches to extract maximum information from seismic data. Nevertheless, geoscientists found that seismic is still mature and rich in information. In this paper a new seismic attribute is introduced. Instantaneous energy seismic attribute is an amplitude based attribute that has the potential to emphasize anomalous amplitude associated with hydrocarbons. Promising results have been obtained from applying the attribute on seismic section traversing hydrocarbon filled sand from Alberta, Canada.

58 GEOSCIENCES↗

DOE OSTI2021

Profiling the Quito basin (Ecuador) using seismic ambient noise

SUMMARY Quito, the capital of Ecuador, with more than 2.5 M inhabitants, is exposed to a high seismic hazard due to its proximity to the Pacific subduction zone and active crustal faults, both capable of generating significant earthquakes. Furthermore, the city is located in an intermontane piggy-back basin prone to seismic wave amplification. To understand the basin’s seismic response and characterize its geological structure, 20 broad and medium frequency band seismic stations were deployed in Quito’s urban area between May 2016 and July 2018 that continuously recorded ambient seismic noise. We first compute horizontal-to-vertical spectral ratios to determine the resonant frequency distribution in the entire basin. Secondly, we cross-correlate seismic stations operating simultaneously to retrieve interstations surface-wave Green’s functions in the frequency range of 0.1–2 Hz. We find that Love waves travelling in the basin’s longitudinal direction (NNE–SSW) show much clearer correlograms than those from Rayleigh waves. We then compute Love wave phase-velocity dispersion curves and invert them in conjunction with the HVSR curves to obtain shear-wave velocity profiles throughout the city. The inversions highlight a clear difference in the basin’s structure between its northern and southern parts. In the centre and northern areas, the estimated basin depth and mean shear-wave velocity are about 200 m and 1800 ms−1, respectively, showing resonance frequency values between 0.6 and 0.7 Hz. On the contrary, the basement’s depth and shear-wave velocity in the southern part are about 900 m and 2500 ms−1, having a low resonance frequency value of around 0.3 Hz. This difference in structure between the centre-north and the south of the basin explains the spatial distribution of low-frequency seismic amplifications observed during the Mw 7.8 Pedernales earthquake in April 2016 in Quito.

Pacheco, D. (ORCID:0000000282355096)↗

DOE OSTI2015

Discovering new events beyond the catalogue—application of empirical matched field processing to Salton Sea geothermal field seismicity

Using empirical matched field processing (MFP), we compare 4 yr of continuous seismic data to a set of 195 master templates from within an active geothermal field and identify over 140 per cent more events than were identified using traditional detection and location techniques alone. In managed underground reservoirs, a substantial fraction of seismic events can be excluded from the official catalogue due to an inability to clearly identify seismic-phase onsets. Empirical MFP can improve the effectiveness of current seismic detection and location methodologies by using conventionally located events with higher signal-to-noise ratios as master events to define wavefield templates that could then be used to map normally discarded indistinct seismicity. Since MFP does not require picking, it can be carried out automatically and rapidly once suitable templates are defined. In this application, we extend MFP by constructing local-distance empirical master templates using Southern California Earthquake Data Center archived waveform data of events originating within the Salton Sea Geothermal Field. We compare the empirical templates to continuous seismic data collected between 1 January 2008 and 31 December 2011. The empirical MFP method successfully identifies 6249 additional events, while the original catalogue reported 4352 events. The majority of these new events are lower-magnitude events with magnitudes between M0.2–M0.8. Here, the increased spatial-temporal resolution of the microseismicity map within the geothermal field illustrates how empirical MFP, when combined with conventional methods, can significantly improve seismic network detection capabilities, which can aid in long-term sustainability and monitoring of managed underground reservoirs.

15 GEOTHERMAL ENERGY↗

DOE OSTI2016

Case History : Using time-lapse vertical seismic profiling data to constrain velocity-saturation relations: the Frio brine pilot CO 2 injection: Time-lapse VSP to constrain VSRs

CO 2 sequestration projects benefit from quantitative assessment of saturation distribution and plume extent for field development and leakage prevention. In this work, we carry out quantitative analysis of time-lapse seismic by using rock physics and seismic modelling tools. We investigate the suitability of Gassmann's equation for a CO 2 sequestration project with 1600 tons of CO 2 injected into high-porosity, brine-saturated sandstone. We analyze the observed time delays and amplitude changes in a time-lapse vertical seismic profile dataset. Both reflected and transmitted waves are analyzed qualitatively and quantitatively. To interpret the changes obtained from the vertical seismic profile, we perform a 2.5D elastic, finite-difference modelling study. The results show a P-wave velocity reduction of 750 m/s in the proximity of the injection well evident by the first arrivals (travel-time delays and amplitude change) and reflected wave amplitude changes. These results do not match with our rock physics model using Gassmann's equation predictions even when taking uncertainty in CO 2 saturation and grain properties into account. We find that time-lapse vertical seismic profile data integrated with other information (e.g., core and well log) can be used to constrain the velocity–saturation relation and verify the applicability of theoretical models such as Gassmann's equation with considerable certainty. The study shows that possible nonelastic factors are in play after CO 2 injection (e.g., CO 2 –brine–rock interaction and pressure effect) as Gassmann's equation underestimated the velocity reduction in comparison with field data for all three sets of time-lapse vertical seismic profile attributes. Here, our work shows the importance of data integration to validate the applicability of theoretical models such as Gassmann's equation for quantitative analysis of time-lapse seismic data.

58 GEOSCIENCES↗

DOE OSTI2020

Code for Calculating Regional Seismic Travel Time

The RSTT software computes predictions of the travel time of seismic energy traveling from a source to a receiver through 2.5D models of the seismic velocity distribution within the Earth. The two primary applications for the RSTT library are tomographic inversion studies and seismic event location calculations. In tomographic inversions studies, a seismologist begins with number of source-receiver travel time observations and an initial starting model of the velocity distribution within the Earth. A forward travel time calculator, such as the RSTT library, is used to compute predictions of each observed travel time and all of the residuals (observed minus predicted travel time) are calculated. The Earth model is then modified in some systematic way with the goal of minimizing the residuals. The Earth model obtained in this way is assumed to be a better model than the starting model if it has lower residuals. The other major application for the RSTT library is seismic event location. Given an Earth model, an initial estimate of the location of a seismic event, and some number of observations of seismic travel time thought to have originated from that event, location codes systematically modify the estimate of the location of the event with the goal of minimizing the difference between the observed and predicted travel times. The second application, seismic event location, is routinely implemented by the military as part of its effort to monitor the Earth for nuclear tests conducted by foreign countries.

BALLARD, SANFORD↗

DOE OSTI2020

Regional Seismic Travel Time v.3.2.0

BALLARD, SANFORD↗

DOE OSTI2022

Neural net detection of seismic features related to gas hydrates and free gas accumulations on the northern U.S. Atlantic margin

Bottom-simulating reflections (BSRs) that sometimes mark the base of the gas hydrate stability zone in marine sediments are often identified based on the reverse polarity reflections that cut across stratigraphic layering in seismic amplitude data. On the northern U.S. Atlantic margin (USAM) between Cape Hatteras and Hudson Canyon, legacy seismic data have revealed pronounced BSRs south of the deepwater extension of Hudson Canyon and more subtle ones from offshore Delaware south to Cape Hatteras, where the reflections sometimes follow stratigraphic layering. Using high-resolution seismic data acquired during the 2018 Mid-Atlantic Resource Imaging Experiment and a supervised neural net, we identify seismic features associated with gas hydrates and/or the top of gas between Hudson Canyon and Cape Hatteras. Using seismic attributes especially sensitive to the presence of gas, we train a neural network algorithm on seismic data from an area with strong BSRs and then apply the model to the rest of the data set. The results indicate that gas hydrate and/or shallow free gas are significantly more widespread on the northern part of the USAM than previously known. Seismic indicators of gas extend landward from the 2000 m isobath to the upper continental slope in sectors with (offshore Virginia) and, to a lesser extent, without (offshore New Jersey) pervasive upper slope methane seeps. Higher sand content and intermediate sediment thickness, factors related to the container size and gas charge in a petroleum systems framework, are associated with more robust gas indicators.

Geochemistry & Geophysics↗

DOE OSTI2023

Locating Operational Events of the Cooling Tower of a Nuclear Reactor with a Very Local Seismic Network

Geolocation of emergent seismic signals is challenging at close distances. Here, we used three-component data from a seismic network and a targeted experiment at a research nuclear reactor to locate seismic sources. Utilizing known events collected during the targeted experiment, we were able to infer source locations with seismic amplitudes and polarization characteristics of the data. Although the resolution of the source location is not perfect, the seismic amplitudes and polarization analysis offer useful constraints. For the known events, the source region inferred with our analysis includes the true source locations. Synthetic tests indicate the resolution is largely due to limited data coverage and measurement uncertainties because the synthetic tests show similar results compared with the field data. We identified the source of the unknown event through spectrum cross correlation between the signals from the known events and an unknown event. Our findings were confirmed by operational staff at the facility. When the propagation medium properties (i.e., seismic velocity and quality factor for attenuation) are known, our analysis can be applied to continuous data from a seismic array to infer both source amplitude and location. If the medium properties are not known, a targeted experiment can be conducted to estimate them.

58 GEOSCIENCES↗

DOE OSTI2016

Induced seismicity and carbon storage: Risk assessment and mitigation strategies

Geologic carbon storage (GCS) is widely recognized as an important strategy to reduce atmospheric carbon dioxide (CO 2 ) emissions. Like all technologies, however, sequestration projects create a number of potential environmental and safety hazards that must be addressed. These include earthquakes—from microseismicity to large, damaging events—that can be triggered by altering pore-pressure conditions in the subsurface. To date, measured seismicity due to CO 2 injection has been limited to a few modest events, but the hazard exists and must be considered. There are important similarities between CO 2 injection and fluid injection from other applications that have induced significant events—e.g. geothermal systems, waste-fluid injection, hydrocarbon extraction, and others. There are also important distinctions among these technologies that should be considered in a discussion of seismic hazard. This report focuses on strategies for assessing and mitigating risk during each phase of a CO 2 storage project. Four key risks related to fault reactivation and induced seismicity were considered. Induced slip on faults could potentially lead to: (1) infrastructure damage, (2) a public nuisance, (3) brine-contaminated drinking water, and (4) CO 2 -contaminated drinking water. These scenarios lead to different types of damage—to property, to drinking water quality, or to the public welfare. Given these four risks, this report focuses on strategies for assessing (and altering) their likelihoods of occurrence and the damage that may result. This report begins with an overview of the basic physical mechanisms behind induced seismicity. This science basis—and its gaps—is crucial because it forms the foundation for risk assessment and mitigation. Available techniques for characterizing and monitoring seismic behavior are also described. Again, this technical basis—and its limitations—must be factored into the risk assessment and mitigation approach. A phased approach to risk management is then introduced. The basic goal of the phased approach is to constantly adapt site operations to current conditions and available characterization data. The remainder of the report then focuses in detail on different components of the monitoring, risk assessment, and mitigation strategies. Issues in current seismic risk assessment methods that must be modified to address induce seismicity are highlighted. The report then concludes with several specific recommendations for operators and regulatory authorities to consider when selecting, permitting, and operating a storage project.

58 GEOSCIENCES↗

DOE OSTI2018

The Effects of Stochastic Velocity Variations on Estimating Time Dependent Seismic Moment Tensors: Applications to the Blue Mountain Well Perforation Data

Resolving the time dependent terms in the seismic moment tensor provides important information that can be used to interpret the source process of an explosion, including the separation of isotropic explosion terms from shear forces and potentially isolated force couples. In this report, we detail our method of inverting three component seismic data for the seismic moment tensor. We review possible seismic source models from the simplest isotropic explosion type source to those incorporating the six independent moment tensor terms. The inversion we describe is formulated in the frequency domain, and results in estimates of time dependent moment tensor components. The inversion relies on an accurate estimate of the Green's functions of the Earth. However, given the complexity of the Earth, we explore the effects of inaccuracies in the presumed Earth model used to estimate the Green's functions needed for the inversion. Specifically, we explore the effects of stochastic variations in the Earth models on the inversion results. These tests are synthetic throughout, and show that adding stochastic density/velocity heterogeneity in the presumed Earth model results in reduced amplitude seismic moment tensor estimates, as well as degrading the data misfit. We suggest two mitigation strategies. First, produce a suite of Green's functions using different realizations of the stochastic field within the Earth Model. Secondly, perform the in- version in the power spectral domain, eliminating all phase information. Finally, we analyze actual seismic data collected in winter 2017/2018. The seismic data was collected at in active geothermal well site outside of Winnimucca, NV, and was produced during well stimulation operations. In general, the inversion results were poor, with a high degree of data misfit. We hypothesize that the poor results are a function of a poorly constrained Earth model as well as noisy, high-frequency data being used in the inversion.

58 GEOSCIENCES↗

DOE OSTI2020

Advanced High-Performance Computational Modeling of the Seismic Response of High-Hazard and/or Nuclear Facilities and Critical Infrastructure at the NNSS

New methods for predicting the amplitude and variability of ground shaking from earthquakes (and explosions) are needed for seismic hazard analysis for buildings, nuclear power plants, and critical infrastructure at the NNSS. We are comparing existing 1-D and new 3-D geophysical methods for estimating the shear-wave velocity structure in the upper 30 meters of the ground surface (Vs30), which plays a major role in ground motion amplification and seismic response of buildings. We evaluate the performance of these methodologies at the U1a Complex at the NNSS and develop simple 1-D and high-resolution 3-D Vs30 models. We then emplace these high-resolution models into a background seismic velocity model. We will collaborate with Lawrence Livermore National Laboratory (LLNL) to conduct numerical modeling of the ground shaking at the NNSS using their high-performance computing technology and state-of-the-art ground motion simulation methodology. The primary work that was completed in FY 2019 was to acquire the seismic systems and familiarize staff at the NNSS with their use. We also worked on developing a collection plan with the Device Assembly Facility (DAF) at the NNSS, but due to time constraints and other ongoing projects at the DAF, we had to use U1a as a backup. We were able to coordinate the seismic survey, and we will complete the collection of seismic data in FY 2020. Additionally, during FY 2019, we completed the geologic framework model (GFM) for the U1a Complex and modeled the Yucca fault. LLNL worked with us through FY 2019 to prepare the data files for their modeling software and tested the software for reliability. In FY 2020 we will develop the end-to-end capability so that any facility could easily be modeled and the expected shaking from a local earthquake understood. The work in FY 2020 will include building fault models from the GFM and finalizing the velocity model analysis. The final simulations will be run for multiple rupture models, and final assessments will demonstrate the seismic hazard at the U1a Complex.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗