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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An explainable variational autoencoder model for three-dimensional acoustic emission source localization in hollow cylindrical structures

We introduce an explainable variational autoencoder for three-dimensional (3D) localization of acoustic emission sources in hollow cylindrical structures, with an unsupervised approach. This research capitalizes on multi-arrival waveforms generated by helical path propagation in cylindrical geometries to enable efficient two-receiver localization. By integrating the modal characteristics of Lamb modes under multi-path conditions, we demonstrate that two sets of time-of-arrival differences and peak amplitudes extracted from one receiver can serve as effective localization features. This initial approach identifies four potential source locations, highlighting the feasibility of two-receiver source localization using traditional feature extraction methods. However, direct extraction can be challenging when mode overlaps occur, complicating the localization process. To address this, our work proposes a novel waveform-based method. This method leverages the consistent dispersion characteristics within isotropic materials, where each unique combination of mode arrival times and peak amplitudes constructs a distinct waveform. This distinctiveness overcomes the ambiguities associated with mode overlaps, significantly enhancing the method’s precision and robustness. Our approach adopts a data-driven strategy for waveform-based localization using variational autoencoder (VAE). VAE discerns waveform patterns for localization, while also addressing data uncertainties. The VAE’s encoder and decoder networks capture the localization process and the source’s influence on waveform generation, respectively, guiding latent variables to segregate waveforms by source in the latent space. The design of the learning process focuses on specific localization characteristics to enhance result explainability. Localization predictions are generated by projecting test waveforms, not included in the training set, onto a trained latent space. The prediction is determined using a nearest-neighbor approach based on the closest latent representation of a source. Validation with pencil-lead-break tests on a metallic pipe confirmed our method’s effectiveness, achieving an averaged 3D localization accuracy of 0.84.

Lee, Guan-Wei↗
DOE OSTI2023

Data-assimilated time-lapse visco-acoustic full-waveform inversion: Theory and application for injected CO 2 plume monitoring

Continuous seismic monitoring for quantifying CO 2 plume migration and detection of any potential leakages in the subsurface is essential for the security of long-term anthropogenic carbon dioxide geologic storage. Traditional time-lapse full-waveform inversion (TLFWI) methods aim to map the CO 2 distribution by estimating seismic velocity changes, but recent studies find that CO 2 -induced attenuation is an important complement to seismic velocity for tracking the CO 2 plumes and even quantifying the CO 2 saturation. We have developed a novel data-assimilated TLFWI method to construct high-resolution time-lapse velocity and attenuation changes from dense time-lapse monitoring data. This method consists of two theoretical developments: visco-acoustic full-waveform inversion (QFWI) and multiparameter hierarchical matrix-powered extended Kalman filter (mHiEKF). The method is capable of (1) posing temporal constraints to retrieve time-lapse information from dense monitoring data by using mHiEKF, (2) accurately recovering high-spatial-resolution velocity and attenuation perturbations using first-order equation system-based QFWI, and (3) providing the model uncertainty by estimating their model standard deviation. With numerical examples, we first find the effectiveness of the new QFWI on estimating accurate velocity and attenuation models simultaneously. Then, a CO 2 leakage case and a realistic Frio-II CO 2 monitoring case are presented to find the advantages and applicability of our data-assimilated QFWI method for estimating time-lapse changes using dense time-lapse monitoring surveys. Here, by assimilating time-lapse seismic monitoring data over time, our data-assimilated QFWI method can improve the resolution of velocity and attenuation changes and decrease their model uncertainties.

58 GEOSCIENCES↗
DOE OSTI2024

Revealing complex subsurface dynamics with continuous seismic monitoring: Observations using distributed acoustic sensing and surface orbital vibrators during hydraulic fracturing

Understanding hydraulic fracturing is crucial to improving the stimulation of unconventional reservoirs and increasing fluid production. This study develops a novel seismic monitoring technology using distributed acoustic sensing (DAS) and surface orbital vibrators (SOV) to capture fracture seismic response and mechanical properties at high temporal intervals. We analyze continuous time-lapse vertical seismic profiling (VSP) data acquired every hour during the first nine days of treatment of an unconventional reservoir in the Austin Chalk/Eagle Field Laboratory. The VSP data contain clear seismic signals scattered from the activated fractures. The spatiotemporal changes of the fracture reflectivity revealed by the SOV/DAS data correlate well with the observations of fracture locations inferred from low-frequency DAS data. These results capture the fracture opening and closure processes, as well as highlight potential prestage activations of the fractures due to hydraulic connectivity with preexisting fracture systems. Therefore, analysis of the presented data set provides a unique opportunity to understand fracture initiation and subsequent evolution, not only in the context of unconventional resources but also in enhanced geothermal systems.

Correa, Julia↗
DOE OSTI2025

Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation

ABSTRACT Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.

Glubokovskikh, Stanislav↗
DOE OSTI2023

PubDAS: A PUBlic Distributed Acoustic Sensing Datasets Repository for Geosciences

During the past few years, distributed acoustic sensing (DAS) has become an invaluable tool for recording high-fidelity seismic wavefields with great spatiotemporal resolutions. However, the considerable amount of data generated during DAS experiments limits their distribution with the broader scientific community. Such a bottleneck inherently slows down the pursuit of new scientific discoveries in geosciences. Here, we introduce PubDAS—the first large-scale open-source repository where several DAS datasets from multiple experiments are publicly shared. PubDAS currently hosts eight datasets covering a variety of geological settings (e.g., urban centers, underground mines, and seafloor), spanning from several days to several years, offering both continuous and triggered active source recordings, and totaling up to ~90 TB of data. Here this article describes these datasets, their metadata, and how to access and download them. Some of these datasets have only been shallowly explored, leaving the door open for new discoveries in Earth sciences and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Detection of a Space Capsule Entering Earth’s Atmosphere with Distributed Acoustic Sensing (DAS)

On 24 September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer sample return capsule (SRC) entered Earth’s atmosphere after successfully collecting samples from an asteroid. The known trajectory and timing of this return provided a rare opportunity to strategically instrument sites to record geophysical signals produced by the capsule because it travelled at hypersonic speeds through the atmosphere. For this work, we deployed two distributed acoustic sensing (DAS) interrogators to sample over 12 km of surface-draped fiber-optic cables, as well as six collocated seismometer-infrasound sensor pairs, spread across two sites near Eureka, Nevada. This campaign-style rapid deployment is the first reported recording of an SRC re-entry with any distributed fiber-optic sensing technology. The DAS interrogators recorded an impulsive arrival with an extended coda which had features that were similar to recordings from both the seismometers and infrasound sensors. While the signal-to-noise ratio of the DAS data was lower than the seismic-infrasound data, the extremely dense spacing of fiber-optic sensors allowed for more phases to be clearly distinguished and the visualization of the continuous transformation of the wavefront as it impacted the ground. Unexpectedly, the DAS recordings contain less low-frequency content than is present in both the seismic and infrasound data. The deployment conditions strongly affected the recorded DAS data; in particular, we observed that fiber selection and placement exert strong controls on data quality.

58 GEOSCIENCES↗
DOE OSTI2025

Acoustic Observations of the OSIRIS-REx Sample Return Capsule Re-Entry from Wendover Airport

The Origins, Spectral Interpretation, Resource Identification, and Security‐Regolith Explorer sample return capsule (SRC) re‐entered the Earth’s atmosphere at hypersonic speeds from interplanetary space on 24 September 2023. The current work reports on 18 ground‐based acoustic sensors deployed at Wendover Airport, the same location that the Genesis and Stardust SRC re‐entries were recorded. Four different sensors (Chaparral Physics, Gem, Wilson Engineering Research and Development [WERD], and RedVox) were deployed in close proximity to compare their performance. All the sensors captured an N‐wave signal associated with the SRC re‐entry shock wave followed by a broadband coda. The Chaparral Physics array served as the high‐fidelity reference measurement. The N‐wave signal had a peak‐to‐peak amplitude of 4.07 Pa with a fundamental frequency of 4.98 Hz from 167.5° measured clockwise from north, nearly perpendicular to the SRC trajectory. In addition, high coherence in the coda was shown to be associated reflections from the surrounding mountains. In general, the more economical sensors (Gem, WERD, and RedVox) produced results that were consistent with these observations and sensor specifications. Beamforming with these single sensors arranged as an array showed agreement with the high‐fidelity array to within a couple of degrees. Furthermore, the current high‐fidelity results were compared with the measurements during the Genesis and Stardust SRC re‐entries. All three entries produced a broadband fundamental peak at a frequency that was inversely related to the SRC diameter as well as evidence of reflections from the surrounding topography.

KC, Real J. [Oklahoma State University, Stillwater↗
DOE OSTI2025

Rapid and Temporary Deployment of Fiber-Optic Arrays to Measure Surface Chemical Explosion Series with Distributed Acoustic Sensing

Rapid and temporary distributed acoustic sensing (DAS) deployments are crucial for accurately capturing the seismic wavefield following major events, such as earthquakes, or in anticipation of known events of interest, such as chemical explosions. We provide an overview of two DAS campaigns conducted in May and October 2024 to record the seismoacoustic waves generated by two series of surface chemical explosions in New Mexico, United States, involving 1- and 10-ton trinitrotoluene-equivalent charges. In both campaigns, we deployed approximately 2 km of fiber-optic cables in a dry riverbed, about 12 km east of the explosion sites. For the October campaign, seven geophones and two anemometers were collocated with the fiber. We describe the field deployments and present preliminary results from the recorded signals. Specifically, we cross analyze the data recorded in May and October, validate the DAS data with geophone measurements, and highlight the benefits of burying fibers to reduce wind noise and improve signal-to-noise ratios. This study demonstrates the potential of DAS to record the seismoacoustic waves generated by surface chemical explosions of varying sizes at distances of approximately 10 km from the source.

58 GEOSCIENCES↗
DOE OSTI2025

Applying Machine Learning and Bayesian Inference to Identify and Locate Moving Anthropogenic Sources Using Distributed Acoustic Sensing Data

Distributed acoustic sensing (DAS) systems, which use existing telecommunication fibers, offer high‐resolution capabilities ideal for recording anthropogenic sources. However, the complexity of urban environments and the large amount of data recorded by DAS require automated methods to efficiently detect and categorize anthropogenic sources. Here, we evaluate how well three machine learning models (k‐nearest neighbor [k‐NN], convolutional neural networks, and recurrent‐convolutional neural networks) can identify various anthropogenic sources recorded by DAS. Our findings reveal that both k‐NN and neural network methods perform well in high signal‐to‐noise ratio (SNR) settings. However, their accuracy decreases at SNRs <4. We also use Kalman filtering, a form of Bayesian inference, on backprojected locations of these sources to recover locations that generally fall within standard smartphone Global Positioning System errors. By combining machine learning and Kalman filter results, we calculate a multidimensional model of moving anthropogenic sources. These results demonstrate the potential of DAS data in urban seismology for accurately identifying and locating such sources. Depending on the research objectives, these sources can be further studied or filtered out to improve the quality of seismic data for earthquake studies. Such methods provide a valuable tool for urban seismology and seismic hazard analysis.

Luckie, Thomas William [Sandia National Laboratori↗
DOE OSTI2022

Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional Neural Networks

Summary Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, examine well stimulation efficacy, and estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture hits because hydraulic fractures propagate and create strain rate variations in the rock. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated live by DAS poses the opportunity for more efficient and accurate real-time data-driven analysis. The objective of this study is to develop a machine learning-based workflow that can identify and locate fracture-hit events in simulated strain rate responses correlated with low-frequency DAS data. In this paper, “fracture hit” refers to a hydraulic fracture originating from a stimulated well intersecting an offset well. We start with building a single fracture propagation model to produce strain rate patterns observed at a hypothetical monitoring well. This model is used to generate two sets of strain rate responses with one set containing fracture-hit events. The labeled synthetic data are then used to train a custom convolutional neural network (CNN) model for identifying the presence of fracture-hit events. The same model is trained again for locating the event with the output layer of the model replaced with linear units. We achieved near-perfect predictions for both event classification and localization. These promising results prove the feasibility of using CNN for real-time event detection from fiber-optic sensing data. Additionally, we use edge detection techniques to recognize fracture-hit event patterns in strain rate images. The fracture-hit location can be identified using recognized pixels in the image. The accuracy of edge detection-based location identification is also plausible, but edge detection is dependent on the assumption of pattern shape and image quality, hence it is less robust compared to CNN models. This comparison further supports the need for CNN applications in image-based real-time fiber-optic sensing event detection.

Engineering↗
DOE OSTI2021

Thermal Effects on Far-Field Distributed Acoustic Strain-Rate Sensors

Summary Fiber-optic cables cemented outside of the casing of an unconventional well measure crosswell strain changes during fracturing of neighboring wells with low-frequency distributed acoustic sensing (LF-DAS). As a hydraulic fracture intersects an observation well instrumented with fiber-optic cables, the fracture fluid injected at ambient temperatures can cool a section of the sensing fiber. Often, LF-DAS and distributed temperature sensing (DTS) cables are run in tandem, enabling the detection of such cooling events. The increasing use of LF-DAS for characterizing unconventional hydraulic fracture completions demands an investigation of the effects of temperature on the measured strain response by LF-DAS. Researchers have demonstrated that LF-DAS can be used to extract the temporal derivative of temperature for use as a differential-temperature-gradient sensor. However, differential-temperature-gradient sensing is predicated on the ability to filter strain components out of the optical signal. In this work, beginning with an equation for optical phase shift of LF-DAS signals, a model relating strain, temperature, and optical phase shift is explicitly developed. The formula provides insights into the relative strength of strain and temperature effects on the phase shift. The uncertainty in the strain-rate measurements due to thermal effects is estimated. The relationship can also be used to quantify uncertainties in differential-temperature-gradient sensors due to strain perturbations. Additionally, a workflow is presented to simulate the LF-DAS response accounting for both strain and temperature effects. Hydraulic fracture geometries are generated with a 3D fracture simulator for a multistage unconventional completion. The fracture width distributions are imported by a displacement discontinuity method (DDM) program to compute the strain rates along an observation well. An analytic model is used to approximate the temperature in the fracture. Using the derived formulae for optical phase shift, the model outputs are then used to compute the LF-DAS response at a fiber-optic cable, enabling the generation of waterfall plots including both strain and thermal effects. The model results suggest that before, during, and immediately following a fracture intersecting a well instrumented with fiber, the strain on the fiber drives the LF-DAS signal. However, at later times, as completion fluid cools the observation well, the temperature component of the LF-DAS signal can be equal to or exceed the strain component. The modeled results are compared to a published field case in an attempt to enhance the interpretation of LF-DAS waterfall plots. Finally, we propose a sensing configuration to identify the events when “wet fractures” (fractures with fluids) intersect the observation well.

Engineering↗
DOE OSTI2022

Experimental Investigation of Low-Frequency Distributed Acoustic Strain-Rate Responses to Propagating Fractures

Summary Low-frequency distributed acoustic sensing (LF-DAS) responds to strain changes due to far-field fracture propagation. To better understand the LF-DAS response to fracture propagation, we performed laboratory-scale hydraulic fracture experiments with embedded optical strain sensors. The objectives of this research are to generate hydraulic fractures of known geometry, measure the strain response along the embedded fiber-optic cable comparable to LF-DAS measurements, and use the results to inform the interpretation of field-derived LF-DAS data. The experiments were conducted in unconfined transparent cubic blocks with a dimension of 8 in. on each side. The block was made of transparent epoxy to visualize the fracture propagation. Fiber-optic sensing cables were embedded in the block at different distances to the source of injection. We injected dyed water through an injection tubing to generate a transverse, radial fracture along an initial flaw. An optical interrogator recorded the response of offset fiber Bragg grating (FBG) strain sensors normal to the plane of the fracture. The strain data were visualized on a waterfall plot, akin to visualizations of field-derived LF-DAS data. Dimensional analysis was used to scale the laboratory results to field conditions. We compared the evolution of the strain response at the fiber-optic cable, injection pressure, and rate with known fracture geometry. The measured strains were compared with Sneddon’s (1946) linear elastic solution for a penny-shaped crack and found to follow this behavior. The generated radial fractures in transparent media can be modeled with Sneddon’s linear elastic radial fracture model and a Mode I critical stress intensity factor. The LF-DAS characteristic response of a narrowing region of extension surrounded by compression was exhibited as a fracture that approached and intersected the fiber-optic cable. The experimentally derived strain and strain-rate waterfall plots with known fracture geometry, injection rate, and pressure response provide insight in understanding LF-DAS responses in the field. Furthermore, we developed a method to estimate fracture geometry evolution from the fiber-optic strain data and validated the method against the experimental data.

Engineering↗
DOE OSTI2023

Interpretation of Fracture Initiation Points by In-Well Low-Frequency Distributed Acoustic Sensing in Horizontal Wells

Summary Low-frequency distributed acoustic sensing (LF-DAS) exploits the optical phase shift of Rayleigh backscatter in fiber-optic cables to obtain distributed measurements of changes in strain and temperature. Fiber-optic cables are often installed for multistage hydraulic fracture diagnostics in horizontal wells. LF-DAS in an untreated well provides far-field strain measurements, while offset wells are hydraulically fractured. Such a configuration is called crosswell LF-DAS sensing. Crosswell LF-DAS measurements have proved useful in diagnosing fracture hits, fracture azimuth, planarity, cluster efficiency, fracture propagation rates, and the dynamic distance to the fracture front. In contrast, in-well LF-DAS is conducted on the actively fractured well. Due to cool fracture fluid being injected at high injection rates, the strain component of the LF-DAS response is largely obscured by temperature changes. In permanent fiber-optic cable installations, distributed temperature sensing (DTS) is often conducted simultaneously with LF-DAS. An opportunity exists to decouple the temperature and strain components of LF-DAS sensors to observe strain changes on in-well LF-DAS. The LF-DAS response is modeled as linearly dependent on strain and temperature changes. Theoretical LF-DAS temperature and strain sensitivity coefficients are derived based on the changes to the index of refraction and length of the fiber. Using the DTS measurements, temperature changes are computed, smoothed, filtered, and compared to the LF-DAS response. Crossplots of the in-well LF-DAS measurements and temperature changes from DTS measurements far from the actively fractured region are used to validate the theoretical sensitivity coefficients. Uncertainty in the temperature component of the LF-DAS response is quantified. The difficulty in corresponding the different spatial and temporal resolutions of the DTS and LF-DAS measurements is overcome by comparing the responses over a moving temporal and spatial window. If the LF-DAS response at the center of the window agrees with the DTS response within uncertainty, the measurement is filtered out. After filtering, the remaining nonzero in-well LF-DAS measurements are due to changes in strain. The data are then visualized in waterfall plots. The results indicate that the theoretical and observed strain and temperature coefficients agree within 10%. After the temperature component of the in-well LF-DAS response is extracted, the remaining nonzero measurements are located primarily within the actively treated region. Locations with peaks in the strain response are interpreted to indicate fracture initiation points. These fracture initiation points are compared with in-well DTS and high-frequency DAS noise measurements across multiple stages to better understand fracture initiation along the horizontal well.

Engineering↗
DOE OSTI2020

Distributed Acoustic Sensing (DAS) on Opportunistic Networks_ A Feasibility Study Utilizing Fiber Optic Infrastructure at NEON Sites for DAS

This study demonstrates the feasibility of using Distributed Acoustic Sensing (DAS) on the opportunistic optical fiber infrastructure presented by NEON (National Ecological Observatory Network) sites. The test took place at the NEON Terrestrial Site designated D10 CPER. Unlit portions of the local fiber network were successfully spliced together and optimized for length and a Silixa iDAS sensor was installed. The resulting array (composed of 12 spliced fiber runs) totaled 875m in length. Over a period of 2 weeks, we gathered a high spatial and temporal resolution data set to characterize discernable signals and understand background noise. The data set was reviewed to extract wave signatures of identifiable origin, both anthropogenic and otherwise. Continent wide distribution of these sites makes them an interesting candidate for DAS and identifying measurable signal sources informs future DAS application on opportunistic fiber networks. These observations validate the utility of both the NEON and similarly small fiber networks (<1km) for geoscience, environmental, and security DAS applications and indicate possibilities for further inquiry in methods for DAS data collection and analysis.

42 ENGINEERING↗
DOE OSTI2020

Distributed Acoustic Sensing (DAS) Seismic Monitoring of CO 2 Injected for Enhanced Oil Recovery in Northern Michigan

As part of the Midwest Regional Carbon Sequestration Partnership (MRCSP) Phase III project, a monitoring study was conducted to assess the effectiveness of DAS (Distributed Acoustic Sensing) -based VSP (Vertical Seismic Profiling) technology for delineating CO 2 injected into the Silurian-age pinnacle reefs in northern Michigan, the host rocks for the MRCSP Phase III demonstration project. The DAS VSP study was conducted in the Chester 16 reef, one of several reefs in Otsego County Michigan that is operated by Core Energy, LLC, of Traverse City, Michigan.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Distributed Acoustic Sensing (DAS) Seismic Monitoring of CO 2 Injected for Enhanced Oil Recovery in Northern Michigan (Volume II.C)

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. This report describes the monitoring study conducted to assess the effectiveness of DAS (Distributed Acoustic Sensing) -based VSP (Vertical Seismic Profiling) technology for delineating CO 2 injected into the Silurian-age pinnacle reefs in northern Michigan, the host rocks for the MRCSP Phase III demonstration project. The DAS VSP study was conducted in the Chester 16 reef, one of several reefs in Otsego County Michigan that is operated by Core Energy, LLC of Traverse City, Michigan. Time-lapse DAS VSP was implemented at the Chester 16 reef to attempt to detect approximately 85,000 tonnes of CO 2 injected into the A-1 Carbonate and Brown Niagaran Formations. A baseline survey was conducted in February 2017 prior to injecting CO 2 and a repeat survey was conducted in August 2018. During the interim period between the baseline and repeat surveys, CO 2 was injected into the Chester 16 reef via the 6-16 injection well without production (withdrawal) of fluids from the reef. A grid of 181 source positions consisting of 44 vibrator positions, plus 137 dynamite shot locations, was used to give approximately continuous spatial coverage of the injection zone (A-1 Carbonate and upper Brown Niagaran) in the area between the two wells.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

High-Resolution 3D Acoustic Borehole Integrity Monitoring (Research Performance Progress Report Q2 2021)

Real-time, in-situ, high spatial resolution (sub-cm) imaging of the near-borehole environment would revolutionize wellbore diagnostics and integrity assessment by direct observation of defects. It is becoming increasingly apparent, that better understanding of the near-wellbore environment is required to meet the safety and operational needs in challenging environments such as those present in subsurface energy extraction (geothermal) and storage (CO2 sequestration) applications. Therefore, it is important to have a more robust ability to image the near-borehole and reliably detect defects. It was proposed to further develop and improve our advanced 3D imaging system to evaluate casing defects (e.g. corrosion) and cement quality in either open- or cased-borehole with the ultimate goal to develop a commercially deployable technology. The system consists of a unique acoustic source (LANL) and advanced inversion techniques for image processing (LANL, ORNL). This system will provide comprehensive borehole integrity monitoring with improved resolution over existing techniques. As an application of this imaging system, we will characterize the effectiveness of next-generation wellbore completion technology (NETL, SNL), and will demonstrate that, unlike current technology, the proposed approach can successfully characterize foamed cements.

15 GEOTHERMAL ENERGY↗