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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mitigating Injection‐Induced Seismicity Along Basement Faults by Extraction: Application to 2016–2018 Pohang Earthquakes

Abstract The risk of induced earthquake is considered as the major obstacle for sustainable subsurface energy activities. As a mitigation approach, mechanistic risk assessment can be essential to minimize the potential of seismic hazard. Coupled hydro‐mechanical modeling approach is integrated with geomechanical analysis to better assess the occurrence of seismicity induced by injection and/or extraction, which will provide a basis to update operational conditions (e.g., number and location of mitigating wells, rate and duration of operations) for mitigating earthquake nucleation. The Coulomb stability analysis and seismicity rate estimates from this generic study indicate that simultaneous extraction can relieve injection‐induced pore‐pressure buildup, but also transfer and accumulate elastic energy along the faults. Field‐scale simulation with variation in well design for the Pohang EGS site, South Korea, show that multiple wells aligned across a preexisting fault form gradients of pressure and stress fields normal to the fault, which can enhance the direct impact of diffusion process and poroelastic stressing on the fault stability perturbation. Our mechanistic study suggests multiphysics‐oriented mitigation strategies that consider (1) possible mechanical deformation, caused by hydro‐mechanical coupling effects, and (2) proper configuration of well operations based on site‐specific geological characteristics.

Chang, K. W.↗
DOE OSTI2020

More Than 40 yr of Potentially Induced Seismicity Close to the San Andreas Fault in San Ardo, Central California

Evidence for fluid–injection–induced seismicity is rare in California hydrocarbon basins, despite widespread injection close to seismically active faults. We investigate a potential case of injection–induced earthquakes associated with San Ardo oilfield operations that began in the early 1950s. The largest potentially induced events occurred in 1955 (M L 5.2) and 1985 (M w 4.5) within ~6 km from the oilfield. We analyze Synthetic Aperture Radar interferometric images acquired by Sentinel–1A/B satellites between 2016 and 2020 and find surface deformation of up to 1.5 cm/yr, indicating pressure–imbalance in parts of the oilfield. Fluid injection in San Ardo is concentrated within highly permeable rocks directly above the granitic basement at a depth of ~800 m. Seismicity predominantly occurs along basement faults at 6–13 km depths. Seismicity and wastewater disposal wells are spatially correlated to the north of the oilfield. Temporal correlations are observed over more than 40 yr with correlation coefficients of up to 0.71 for seismicity within a 24 km distance from the oilfield. Such large distances have not previously been observed in California but are similar to the large spatial footprint of injection in Oklahoma. Furthermore, the San Ardo seismicity shows anomalous clustering with earthquakes consistently occurring at close spatial proximity but long interevent times. Similar clustering has previously been reported in California geothermal fields and may be indicative of seismicity driven by long–term, spatially persistent external forcing.

58 GEOSCIENCES↗
DOE OSTI2021

Machine Learning Predicts the Timing and Shear Stress Evolution of Lab Earthquakes Using Active Seismic Monitoring of Fault Zone Processes

Abstract Machine learning (ML) techniques have become increasingly important in seismology and earthquake science. Lab‐based studies have used acoustic emission data to predict time‐to‐failure and stress state, and in a few cases, the same approach has been used for field data. However, the underlying physical mechanisms that allow lab earthquake prediction and seismic forecasting remain poorly resolved. Here, we address this knowledge gap by coupling active‐source seismic data, which probe asperity‐scale processes, with ML methods. We show that elastic waves passing through the lab fault zone contain information that can predict the full spectrum of labquakes from slow slip instabilities to highly aperiodic events. The ML methods utilize systematic changes in P‐wave amplitude and velocity to accurately predict the timing and shear stress during labquakes. The ML predictions improve in accuracy closer to fault failure, demonstrating that the predictive power of the ultrasonic signals improves as the fault approaches failure. Our results demonstrate that the relationship between the ultrasonic parameters and fault slip rate, and in turn, the systematically evolving real area of contact and asperity stiffness allow the gradient boosting algorithm to “learn” about the state of the fault and its proximity to failure. Broadly, our results demonstrate the utility of physics‐informed ML in forecasting the imminence of fault slip at the laboratory scale, which may have important implications for earthquake mechanics in nature.

58 GEOSCIENCES↗
DOE OSTI2026

Fault Slip and Fluid Flow: Seismic Source Analysis to Assess Role of Multiple Slip Patches in Fault Permeability

The relationship between fault reactivation, microearthquakes (MEQs), and permeability evolution during fluid injection plays a critical role in energy harvesting and waste disposal. Recent studies have demonstrated the possibility of predicting fault permeability using cumulative seismic moments of MEQs quantitatively. To understand the underlying physical processes, we conduct fault reactivation experiments using Utah FORGE granitoid and analyze acoustic emission (AE) signals generated during stepwise increases in fluid injection pressure. Frequency analysis of thousands of calibrated AE signals reveals that fault reactivation produces multiple AE source patches with millimeter-scale radii—smaller than the sample fault radius. The cumulative area of the reactivated patches covers the fault multiple times over (∼10x–50x area) for each pressure step. These findings provide mechanistic insight that measured permeability enhancement is not driven by a single large slip event, but by the sequential and interacting activation of multiple slip patches that create a continuous flow pathway.

Nurshal, M. E. M. [Pennsylvania State University, ↗
DOE OSTI2021

Three-dimensional paganica fault morphology obtained from hypocenter clustering (L'Aquila 2009 seismic sequence, Central Italy)

In seismic modelling, fault planes are normally assumed to be flat due to the lack of data which can constrain fault morphology. However, incorporating 3D fault morphology is important for modelling several phenomena, for example calculating mainshock induced stress changes. Here we utilize a data-analytical method to unveil the 3D rupture morphology of faults using unsupervised clustering techniques applied to earthquake hypocenters in seismic sequences. We apply this method to the 2009 L'Aquila seismic sequence which involved a M W 6.1 mainshock on April 6th. We use a dataset of about 50,000 relocated events, mostly microearthquakes, reaching magnitude of completeness equal to 0.7. Clustering distinguishes the earthquakes as occurring in three main clusters along with other minor fault segments. We then represent the morphology of the main Paganica fault system (responsible for the largest mainshock) using splines. This method shows promise as a step toward robustly and quickly obtaining 3D rupture morphologies where earthquake sequences have been monitored. The 3D model is presented interactively online, and the processing is presented in an interactive Jupyter Notebook (https://bit.ly/2MnCFdj).

58 GEOSCIENCES↗
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗
DOE OSTI2020

Analysis of Fault Zone Resonance Modes Recorded by a Dense Seismic Array Across the San Jacinto Fault Zone at Blackburn Saddle

We present observations and modeling of spatial eigen-functions of resonating waves within fault zone waveguide, using data recorded on a dense seismic array across the San Jacinto Fault Zone (SJFZ) in southern California. The array consists of 5-Hz geophones that cross the SJFZ with ~10-30 m spacing at the Blackburn Saddle near the Hemet Stepover. Wavefield snapshots after the S wave arrival are consistent for more than 50 near-fault events, suggesting that this pattern is controlled by the fault zone structure rather than source properties. Data from example event with high signal to noise ratio shows three main frequency peaks at ~1.3 Hz, ~2.0 Hz, and ~2.8 Hz in the amplitude spectra of resonance waves averaged over stations near the fault. The data are modeled with analytical expressions for eigen-functions of resonance waves in a low-velocity layer (fault zone) between two quarter-spaces. Using a grid search-based method, we investigate the possible width of the waveguide, location within the array, and shear wave velocities of the media that fit well the resonance signal at ~1.3 Hz. The results indicate a ~300 m wide damaged fault zone layer with ~65% S wave velocity reduction compared to the host rock. The SW edge of the low-velocity zone is near the mapped fault surface trace, indicating that the damage zone is asymmetrically located at the regionally faster NE crustal block. The imaging resolution of the fault zone structure can be improved by modeling fault zone resonance modes and trapped waves together.

58 GEOSCIENCES↗
DOE OSTI2023

Identification of Faults Susceptible to Induced Seismicity (Final Report)

Central to the work documented in this report is the capability of geocellular models to represent the geologic conceptual model updated with fault identification from machine learning and joint inversion modeling of microseismic data measured and recorded as a consequence of CO 2 injection at a field demonstration site: the Illinois Basin - Decatur Project (IBDP). This work required seven unique geocellular models with 100s of simulated variations to gain a very high degree of confidence in the identification of geologic features present that contributed to induced microseismicity at IBDP. All forward modeling: pressure modeling, stress modeling, and seismic modeling used the same geologic conceptual model and representations of that model at different scales. The pressure modeling and poroelastic modeling created “snapshots” of pore pressure and stress field changes at different times during CO 2 injection, in which microseismic events were clustered (in time). These pressure and stress snapshots, within the framework and architecture of the geologic conceptual model via the geocellular model, informed the single fault and fault network models to ascertain the likelihood of fault movement (seismic or aseismic). The outcomes of the pressure, stress, and fault/fault network (seismic) modeling confirmed that the faults in the geologic conceptual model in Task 2 were likely the source of microseismic events measured at IBDP and acted as conduits for pressure to be transmitted from the injection interval into the Precambrian crystalline basement rock. This closely coordinated and integrated unique modeling approach was conducted to prove the viability of our proposed workflow 1) to better resolve crystalline basement faults, 2) detect subseismic faults that could be activated by injection, 3) increase the certainty in fault detection and their susceptibility to release seismic energy, and 4) understand transmission of pressure vertically from the well to the underlying fractured crystalline basement. The proposed methodology was effective in guiding an iterative process of calibrating forward modeling results based on similar geocellular models while honoring the geologic conceptual model (i.e., characterization data and knowledge of regional geology); this led to higher level of certainty in the identification of fault/faults zones to control seismicity and transmission of pressure to the regions of recorded and located injection induced seismicity.

58 GEOSCIENCES↗
DOE OSTI2022

Sequences of seismic and aseismic slip on bimaterial faults show dominant rupture asymmetry and potential for elevated seismic hazard

Here we perform numerical simulations of sequences of earthquake and aseismic slip on planar rate and state faults separating dissimilar material within the 2-D plane strain approximation. We resolve all stages of the earthquake cycle from aseismic slip to fast ruptures while incorporating full inertia effects during seismic event propagation. We show that bimaterial coupling results in favorable nucleation site and subsequent asymmetric rupture propagation. We demonstrate that increasing the material contrast enhances this asymmetry leading to higher slip rates and normal stress drops in the preferred rupture propagation direction. The normal stress drop, induced by the bimaterial effect, leads to strong dynamic weakening of the fault and may destabilize the creeping region on a heterogeneous rate and state fault, resulting in extended rupture propagation. Such rupture penetration into creeping patches may lead to more frequent opening of earthquake gates, causing increased seismic hazard. Furthermore, bimaterial coupling may lead to irregular seismicity pattern in terms of event length, peak slip rates, and hypocenter location, depending on the properties of the creeping patches bordering the seismogenically active part of the fault. Our results highlight robust characteristics of bimaterial interfaces that persist over long sequence of events and suggest the need for further exploration of the role of material contrast in earthquake physics and models of seismic hazard.

58 GEOSCIENCES↗
DOE OSTI2023

Induced microseismicity and tremor signatures illuminate different slip behaviours in a natural shale fault reactivated by a fluid pressure stimulation (Mont Terri)

SUMMARY Fault slip induced by fluid perturbation in shale formations may only lead to a sparse seismicity. However, fault slip may strongly impact the integrity of shale formations that serve as caprocks for geological reservoirs holding buoyant fluids such as CO2, natural gas or hydrogen. A better understanding of the fluid reactivation processes of fault and the seismic triggering process is therefore critical for reservoir monitoring and fault stability. Here we analyse the seismic responses of a shale fault exposed to fluid pressurization during an in situ field-scale injection experiment at ∼340 m depth in the Mont Terri underground research laboratory (Switzerland). Two main types of seismic signals are observed as the fault was activated and started to slowly slip. After an aseismic phase, we observed tremor signatures and an increase in noise amplitude, which were directly associated with the slowly propagating fault slip in response to fluid injection. These signatures were later followed by micro-earthquakes that seem to occur further away from the fluid-pressurized area. We interpret these micro-earthquakes to be triggered by stress perturbations from the main slip growth. These two classes of seismic responses therefore highlight two different processes. Tremors seem to be a more direct observation for the fluid-induced slip propagation than micro-earthquakes. Even hidden in the noise, they precede earthquake failures, thus providing a useful tool for monitoring fluid leakage activated by slow deformation on low permeable shale faults, with applications for sealing integrity of caprocks.

De Barros, Louis (ORCID:0000000255419162)↗
DOE OSTI2024

Probing the evolution of fault properties during the seismic cycle with deep learning

We use seismic waves that pass through the hypocentral region of the 2016 M6.5 Norcia earthquake together with Deep Learning (DL) to distinguish between foreshocks, aftershocks and time-to-failure (TTF). Binary and N-class models defined by TTF correctly identify seismograms in test with > 90% accuracy. We use raw seismic records as input to a 7 layer CNN model to perform the classification. Here we show that DL models successfully distinguish seismic waves pre/post mainshock in accord with lab and theoretical expectations of progressive changes in crack density prior to abrupt change at failure and gradual postseismic recovery. Performance is lower for band-pass filtered seismograms (below 10 Hz) suggesting that DL models learn from the evolution of subtle changes in elastic wave attenuation. Tests to verify that our results indeed provide a proxy for fault properties included DL models trained with the wrong mainshock time and those using seismic waves far from the Norcia mainshock; both show degraded performance. Our results demonstrate that DL models have the potential to track the evolution of fault zone properties during the seismic cycle. If this result is generalizable it could improve earthquake early warning and seismic hazard analysis.

58 GEOSCIENCES↗
DOE OSTI2023

The effect of shear strain and shear localization on fault healing

The seismic cycle of repeated earthquake failure requires that faults regain frictional strength during the interseismic phase, when the fault is locked or undergoing quasi-static creep. Fault healing plays a central role in determining earthquake stress drop, recurrence interval, elastic radiation frequency and other source parameters. In particular, the longer a fault remains quasi-stationary, the stronger it becomes and the larger the potential stress drop can be for the next event. Here, we address the role of shear strain and strain localization on fault healing and healing rate. We performed slide-hold-slide friction experiments on quartz gouge in the double-direct shear configuration for shear strain up to 25 and hold times from 10 to 1000 s. The results show that both healing and healing rate increase nonlinearly with increasing shear strain. Frictional healing scales with volumetric strain within the laboratory fault zone. Using the volumetric strain upon reshear as a proxy for strain localization, we demonstrate that the capacity of a fault to heal is directly proportional to shear bandwidth and degree of strain localization. The more the deformation is localized, the higher are the healing and healing rate, and thus, the fault strength. Our data provide a framework for understanding variations in fault strength over the seismic cycle and the role of brecciation and strain localization on spatiotemporal variations in fault strength.

58 GEOSCIENCES↗
DOE OSTI2022

Transient evolution of permeability and friction in a slowly slipping fault activated by fluid pressurization

The mechanisms of permeability and friction evolution in a natural fault are investigated in situ. During three fluid injection experiments at different places in a fault zone, we measured simultaneously the fluid pressure, fault displacements and seismic activity. Changes in fault permeability and friction are then estimated concurrently. Results show that fault permeability increases up to 1.58 order of magnitude as a result of reducing effective normal stress and cumulative dilatant slip, and 19-to-60.8% of the enhancement occurs without seismic emissions. When modeling the fault displacement, we found that a rate-and-state friction and a permeability dependent on both slip and slip velocity together reasonably fit the fault-parallel and fault-normal displacements. This leads to the conclusion that the transient evolution of fault permeability and friction caused by a pressure perturbation exerts a potentially dominant control on fault stability during fluid flow.

58 GEOSCIENCES↗
DOE OSTI2022

Spatio-Temporal Clustering of Seismicity Enabled by Off-Fault Plasticity

While significant progress has been made in understanding earthquake source processes in linear elastic domains, the effect of more realistic rheologies including plasticity is poorly understood. Here, in this work, we simulate the sequence of earthquake and aseismic slip of a 2D antiplane rate-and-state fault embedded in a full-space elastic-plastic bulk. We show that off-fault plasticity may lead to partial ruptures as well as temporal clustering of seismic events. Furthermore, the interaction of fault slip and off-fault plasticity results in pockets of slip deficit. While the energy dissipated through plastic deformation remains a small fraction of the total energy budget, its impact on the source characteristics is disproportionally large through the redistribution of stresses and viscous relaxation. Our results suggest a new mechanism of dynamic heterogeneity in earthquake physics that may have important implications on earthquake size distribution and energy budget.

58 GEOSCIENCES↗
DOE OSTI2021

Frequency–Magnitude Statistics of Laboratory Foreshocks Vary With Shear Velocity, Fault Slip Rate, and Shear Stress

Understanding the nucleation phase of earthquakes is key for advancing earthquake hazard assessment and improving earthquake early warning systems. However, little progress has been made in this area due to a poor understanding of nucleation processes and incomplete seismic and fault zone measurements. The ability to integrate measured fault zone properties with seismic data could significantly improve our understanding of how earthquakes begin and whether there are systematic variations in seismic properties preceding failure. In this work, we use high-resolution laboratory measurements of fault zone properties along with acoustic emission data to document temporal variations of foreshock properties. Our data show that foreshock size increases with shear stress, loading rate, and fault slip rate. We propose that the preseismic fault slip rate and fault zone thickness (i.e., porosity) work in concert to modulate foreshock properties.

15 GEOTHERMAL ENERGY↗