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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Seeking Repeating Anthropogenic Seismic Sources: Implications for Seismic Velocity Monitoring at Fault Zones

Abstract Seismic velocities in rocks are highly sensitive to changes in permanent deformation and fluid content. The temporal variation of seismic velocity during the preparation phase of earthquakes has been well documented in laboratories but rarely observed in nature. It has been recently found that some anthropogenic, high‐frequency (>1 Hz) seismic sources are powerful enough to generate body waves that travel down to a few kilometers and can be used to monitor fault zones at seismogenic depth. Anthropogenic seismic sources typically have fixed spatial distribution and provide new perspectives for velocity monitoring. In this work, we propose a systematic workflow to seek such powerful seismic sources in a rapid and straightforward manner. We tackle the problem from a statistical point of view, considering that persistent, powerful seismic sources yield highly coherent correlation functions (CFs) between pairs of seismic sensors. The algorithm is tested in California and Japan. Multiple sites close to fault zones show high‐frequency CFs stable for an extended period of time. These findings have great potential for monitoring fault zones, including the San Jacinto Fault and the Ridgecrest area in Southern California, Napa in Northern California, and faults in central Japan. However, extra steps, such as beamforming or polarization analysis, are required to determine the dominant seismic sources and study the source characteristics, which are crucial to interpreting the velocity monitoring results. Train tremors identified by the present approach have been successfully used for seismic velocity monitoring of the San Jacinto Fault in previous studies.

58 GEOSCIENCES↗
DOE OSTI2020

Inversion of Time-Lapse Seismic Reservoir Monitoring Data Using CycleGAN: A Deep Learning-Based Approach for Estimating Dynamic Reservoir Property Changes

Carbon capture and storage is being pursued globally as a geoengineering measure for reducing the emission of anthropogenic CO 2 the atmosphere. Comprehensive monitoring, verification, and accounting programs must be established for demonstrating the safe storage of injected CO 2 . One of the most commonly deployed monitoring techniques is time-lapse seismic reservoir monitoring (also known as 4-D seismic), which involves comparing 3-D seismic survey data taken at the same study site but over different times. Analyses of 4-D seismic data volumes can help improve the quality of storage reservoir characterization, track the movement of injected CO 2 plume, and identify potential CO 2 spillover/leakage from the storage reservoirblue. However, the derivation of high-resolution CO 2 saturation maps from 4-D seismic data is a highly nonlinear and ill-posed inverse problem, often requiring significant computational effort. In this research, we apply a physics-based deep learning method to facilitate the solution of both the forward and inverse problems in seismic inversion while honoring physical constraints. A cycle generative adversarial neural network (CycleGAN) model is trained to learn the bidirectional functional mappings between the reservoir dynamic property changes and seismic attribute changes, such that both forward and inverse solutions can be obtained efficiently from the trained model. We show that our CycleGAN-based approach not only improves the reliability of 4-D seismic inversion but also expedites the quantitative interpretation. Our deep learning-based workflow is generic and can be readily used for reservoir characterization and reservoir model updates involving the use of 4-D seismic data.

58 GEOSCIENCES↗
DOE OSTI2020

CO 2 Injection Monitoring with a Scalable, Automated Sparse Seismic Array

Conference presentation at American Institute of Chemical Engineers (AIChE) Annual Meeting, Virtual, November 16–20, 2020. The scalable, automated sparse seismic array (SASSA) method has been ideated as a cost-effective alternative or complementary to conventional 3D seismic methods. Based on a sparse array of receivers deployed strategically on Earth’s surface and one or more fixed seismic sources, the SASSA method can be used to study specific portions of the subsurface to detect the movement of CO 2 in a reservoir with lower environmental footprint and shorter turnaround time to deliver results than conventional 3D seismic methods. Energy & Environmental Research Center (EERC) carried out seismic monitoring of an oilfield undergoing CO 2 enhanced oil recovery in Montana, USA, using the SASSA method.

02 PETROLEUM↗
DOE OSTI2023

Moment tensor reconstruction

A seismic monitoring system includes a plurality of seismic monitors and a processing device operatively coupled to the plurality of seismic monitors. The processing device receives recordings of waveforms of motion detected at the plurality of seismic detectors in a geographic area. The processing device applies the respective recordings to corresponding positions of the seismic detectors in a three-dimensional geological model that describes its elastic attributes and tests a plurality of moment tensors at a plurality of locations. Based on the testing, the processing device determines a globally convergent source location and moment tensor in the three-dimensional model based on the testing.

Petrov, Petr↗
DOE OSTI2021

Intelligent Monitoring Systems and Advanced Well Integrity and Mitigation

Long-term seismic monitoring of carbon capture and storage projects is needed to verify that the injected gas is safely stored in the subsurface until permanence can be assured. Conventional surface seismic monitoring techniques are usually expensive, require highly invasive surface operations, and need significant time investments on the part of personnel for both the field effort and processing the acquired data. For these reasons, permanent reservoir monitoring technologies are preferred, as they can offer a cost-effective solution for long-term monitoring. As part of the monitoring program of the Archer Daniels Midland’s large-scale injection of CO 2 in Decatur, Illinois, USA, a continuous seismic monitoring array was installed using a combination of surface orbital vibrator (SOV) sources and fiber-optic cables for distributed acoustic sensing (DAS) acquisition with the objective to build a continuous monitoring array. The aim of the presented project was to build a monitoring array and platform that integrates real-time seismic data with conventional data streams and provides continuous data analysis using dynamic computational models to deliver a comprehensive real-time assessment of subsurface conditions. It is in this context that the Intelligent Monitoring Systems and Advanced Well Integrity and Mitigation project was proposed with the objective to develop an integrated architecture that utilizes a permanent seismic monitoring network, combines the real-time geophysical and process data with reservoir flow and geomechanical models to create a comprehensive monitoring, visualization, and control system that delivers critical information for process surveillance and optimization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

EGS Collab Experiment 2: Microseismic Monitoring

This dataset contains continuous seismic waveform data recorded during stimulation and thermal circulation tests for the Enhanced Geothermal Systems (EGS) Collab Experiment #2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Dakota. This experiment aimed to study and validate models of geothermal systems by injecting high-pressure fluids into rock formations 1200-1500 meters below the surface, inducing microseismic events. The seismic monitoring system included 16 three-component accelerometers and a 24-channel hydrophone array, installed in boreholes surrounding the test area. Data were recorded at high sampling rates using a continuous waveform recording system to monitor seismic activity in real time. The dataset contains the raw data stored in binary format, with files named based on timestamps, and includes calibration certificates for some sensors to facilitate corrections to real units. Users are strongly advised to consult the accompanying detailed report, which outlines the experimental setup, sensor specifications, installation procedures, and data processing methods. The report also describes important nuances, such as the hardware filters on hydrophones, sensor calibration details, and the naming conventions for the recorded data. Proper use of this dataset may require familiarity with seismic data analysis tools, such as the Obspy Python package, and an understanding of the SEED naming conventions used for channel identification.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation

SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.

58 GEOSCIENCES↗
DOE OSTI2021

Applications of seismic threshold monitoring at an Antarctic glacier [Slides]

Geophysical waveforms collected from Arctic regions provides data required for monitoring global security targets. Some seismic instruments deployed on Scandinavian and Greenlandic sites provide waveform data, but these installations include specific challenges: Sea ice and glacial ice generates waveform interference; Meltwater generates narrowband interference, resembling tonal noise.

58 GEOSCIENCES↗
DOE OSTI2025

Permanent Source - Distributed Acoustic Sensing (PESO-DAS) v1

The SOV/DAS software program focuses on seismic monitoring and data processing of permanent seismic sources Surface Orbital Vibrators (SOVs) and fiber-optics sensing Distributed Acoustic Sensing (DAS). Its key features include automated data processing of the continuous seismic monitoring data acquired with DAS, and output of processed shot gathers and QC plots. The software supports timelapse seismic for long-term reservoir monitoring, and is used for monitoring of geological carbon storage sites, geothermal reservoirs, and oil and gas, and in general subsurface resource management.

dos Santos Maia Correa, Julia [Lawrence Berkeley N↗
DOE OSTI2020

Landslide monitoring using seismic refraction tomography – The importance of incorporating topographic variations

Seismic refraction tomography provides images of the elastic properties of subsurface materials in landslide settings. Seismic velocities are sensitive to changes in moisture content, which is a triggering factor in the initiation of many landslides. However, the application of the method to long-term monitoring of landslides is rarely used, given the challenges in undertaking repeat surveys and in handling and minimizing the errors arising from processing time-lapse surveys. This work presents a simple method and workflow for producing a reliable time-series of inverted seismic velocity models. This method is tested using data acquired during a recent, novel, long-term seismic refraction monitoring campaign at an active landslide in the UK. Potential sources of error include those arising from inaccurate and inconsistent determination of first-arrival times, inaccurate receiver positioning, and selection of inappropriate inversion starting models. At our site, a comparative analysis of variations in seismic velocity to real-world variations in topography over time shows that topographic error alone can account for changes in seismic velocity of greater than ±10% in a significant proportion (23%) of the data acquired. The seismic velocity variations arising from real material property changes at the near-surface of the landslide, linked to other sources of environmental data, are demonstrated to be of a similar magnitude. Over the monitoring period we observe subtle variations in the bulk seismic velocity of the sliding layer that are demonstrably related to variations in moisture content. This highlights the need to incorporate accurate topographic information for each time-step in the monitoring time-series. The goal of the proposed workflow is to minimize the sources of potential errors, and to preserve the changes observed by real variations in the subsurface. Following the workflow produces spatially comparable, time-lapse velocity cross-sections formulated from disparate, discretely-acquired datasets. These practical steps aim to aid the use of the seismic refraction tomography method for the long-term monitoring of landslides prone to hydrological destabilization.

Whiteley, J. S.↗
DOE OSTI2024

CO 2 rock physics modeling for reliable monitoring of geologic carbon storage

Monitoring, verification, and accounting (MVA) are crucial to ensure safe and long-term geologic carbon storage. Seismic monitoring is a key MVA technique that utilizes seismic data to infer elastic properties of CO 2 -saturated rocks. Reliable accounting of CO 2 in subsurface storage reservoirs and potential leakage zones requires an accurate rock physics model. However, the widely used CO 2 rock physics model based on the conventional Biot-Gassmann equation can substantially underestimate the influence of CO 2 saturation on seismic waves, leading to inaccurate accounting. We develop an accurate CO 2 rock physics model by accounting for both effects of the stress dependence of seismic velocities in porous rocks and CO 2 weakening on the rock framework. We validate our CO 2 rock physics model using the Kimberlina-1.2 model (a previously proposed geologic carbon storage site in California) and create time-lapse elastic property models with our new rock physics method. We compare the results with those obtained using the conventional Biot-Gassmann equation. Our innovative approach produces larger changes in elastic properties than the Biot-Gassmann results. Using our CO 2 rock physics model can replicate shear-wave speed reductions observed in the laboratory. Our rock physics model enhances the accuracy of time-lapse elastic-wave modeling and enables reliable CO 2 accounting using seismic monitoring.

58 GEOSCIENCES↗
DOE OSTI2021

Central Asia Seismic Hazard Assessment (Casha) "Complete" Catalog of Earthquakes

Probabilistic Seismic Hazard Assessments (PSHA) greatly benefit from reliable earthquake catalogs. Central Asia, while rich in seismic monitoring history, reports a fraction of their earthquake data to international data collection centres. Furthermore, since the collapse of Soviet Union until now, monitoring and data collection efforts in Central Asia have not been centralized, making monitoring and reporting uneven and disconnected in this time period. Lawrence Livermore National Laboratory (LLNL) has undertaken a multi-year effort to systematically work with national seismic monitoring and data centres and seismic networks in Kazakhstan, Kyrgyzstan, and Tajikistan to compile a unified seismological bulletin for Central Asia. In tandem with this effort, an earthquake catalog that is processed to be PSHA ready was also generated. The processing for this effort included further duplicate identification and removal, magnitude harmonization and catalog completeness analyses. This report describes the “complete” PSHA-ready earthquake catalog, including the completeness intervals that were applied.

58 GEOSCIENCES↗
DOE OSTI2025

Monitoring Fracture Hydromechanical Evolution in the Lab and Field Using Unsupervised Metric Learning

Fractures evolve in time through thermal‐hydraulic‐mechanical‐chemical (THMC) processes that alter their long‐range hydraulic transport properties and modify subsurface behavior and activities. The location of subsurface fractures makes it necessary to use remote sensing techniques such as passive or active seismic monitoring for fracture characterization. In this paper, we develop a machine learning approach to monitor the evolution of fracture properties using passive seismic sources in a laboratory setting and using active seismic monitoring from the Sanford Underground Research Facility in Lead, South Dakota, at a depth of 1.25 km in amphibolite rock during stimulation of natural fractures as well as during induced fracturing. The unsupervised metric learning technique applies tandem neural networks (twin (Siamese) or triplet) with contrastive loss and adaptive margins to track slowly varying systems for which class or similarity labels are not available. The approach adopts locality‐sensitive hashing to divide time‐ordered contiguous data into an arbitrary number of pseudo‐classes. Contrastive‐loss training with many hash bins generates an evolving latent‐space trajectory. This approach enables unsupervised metric learning for seismic data stacks under the condition of contiguous state sampling and slowly varying fracture properties. The displacement discontinuity theory provides a mechanistic foundation for the fracture‐dependent trajectories that are related to relaxation of fractures with time‐dependent specific stiffness responding to changes in stress or fluid saturation.

02 PETROLEUM↗
DOE OSTI2023

Multiwell Fiber Optic Sensing Reveals Effects of CO2 Flow on Triggered Seismicity

Induced seismicity is one of the main risks for gigaton-scale geological storage of carbon dioxide (⁠CO 2 ⁠). Thus, passive seismic monitoring is often recommended as a necessary component of the monitoring systems for CO 2 storage projects, with a particular forcus on risk mitigation. We present the first field study, CO2CRC Otway Project Stage 3 (Victoria, Australia), where distributed acoustic sensing (DAS) enabled high-precision tracking of the induced seismicity triggered by a small CO 2 injection and also informed the reservoir models. In 610 days of passive seismic monitoring of the Stage 3 injection, we detected 17 microseismic events (maximum moment magnitude Mw 0.1) using five deep boreholes equipped with enhanced-sensitivity optical fiber. The DAS array has sensitivity sufficient for detection and location of induced events with M w ~ ₋2 in a monitoring borehole located up to 1500 m away. Thanks to the dense spatial sampling by the DAS, we were able to estimate the focal mechanisms for events with M w > ₋1.5; although the monitoring boreholes provided very limited angular coverage. The main cluster of the events has the same location and source mechanism as the one triggered by the previous CO 2 injection at the Otway Project site, Stage 2C. Surprizingly, the Stage 2C and Stage 3 events closely followed the actual movement of the CO 2 saturation plume front (not the pressure front), as observed using controlled-source reflection seismic images. The nature of the plume-fault interaction remains unclear, but some alteration of the fault gouge by CO 2 might be responsible for the faults’ reactivation by the pressure perturbation. Importantly, the seismogenic fault could not be identified in the seismic images and was only revealed by DAS observations, which also demonstrated the signature of fluid–rock interaction, that may control the CO 2 flow.

58 GEOSCIENCES↗
DOE OSTI2026

Geophysical Monitoring Program Core Seismic Libraries

The Geophysical Monitoring Program Core Seismic Libraries contain a broad array of seismic and waveform analysis libraries useful for a wide range of seismic analysis processes. These include signal processing, travel time calculation, waveform correlation, array processing, geometry and geodesy, and plotting libraries.

Barno, JustinG [Lawrence Livermore National Labora↗
NASA NTRS1993

Geologic controls on the West Antarctic Ice Sheet

The stability of the West Antarctic Ice Sheet is intertwined with its geologic history. The sub-ice geology and the possibility of active rifting and associated elevated heat-flux and volcanism might be determining factors in ice-sheet behavior. Seismic monitoring of natural events at the base of Ice Stream C reveals the presence of a young sedimentary basin beneath the ice stream. The sediments are presumed to be of glacio-marine origin, similar to those beneath Ice Stream B and in the Ross Sea. The young sediments are approximately 1/2 km thick at UpC camp, but thin abruptly southward to 100 m or less. We hypothesize the presence of a fault with a throw of 400 m to account for this (though we have not directly detected the fault), rather than invoking unrealistic basement dips. To extend these studies to critical inland regions, we suggest an expanded explosive-source seismic survey of the Byrd Subglacial Basin to determine the extent and character of the hypothesized rift basin. High-resolution seismic monitoring will detect layering in the sedimentary column, as well as possibly imaging faults directly.

Anandakrishnan, Sridhar↗
DOE OSTI2023

Steam caps in geothermal reservoirs can be monitored using seismic noise interferometry

Harvesting geothermal energy often leads to a pressure drop in reservoirs, decreasing their profitability and promoting the formation of steam caps. While steam caps are valuable energy resources, they also alter the reservoir thermodynamics. Accurately measuring the steam fraction in reservoirs is essential for both operational and economic perspectives. However, steam content estimations are very limited both in space and time since current methods rely on direct measurements within production wells. Besides, these estimations normally present large uncertainties. Here, we present a pioneering method for indirectly sampling the steam content in the subsurface using the ever-present seismic background noise. We observe a consistent annual velocity drop in the Hengill geothermal field (Iceland) and establish a correlation between the velocity drop and steam buildup using in-situ borehole data. This application opens new avenues to track the evolution of any gas reservoir in the crust with a surface-based and cost-effective method.

58 GEOSCIENCES↗