Detectable Changes in U1a Data [Slides]
This is an update presentation on U1a data analytics for the Advanced Data Analytics for Proliferation Detection Tech Exchange Meeting.
97 MATHEMATICS AND COMPUTING↗
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Results for “seismic data processing”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Holography: A survey
The development of holography and the state of the art in recording and displaying information, microscopy, motion, pictures, and television applications are discussed. In addition to optical holography, information is presented on microwave, acoustic, ultrasonic, and seismic holography. Other subjects include data processing, data storage, pattern recognition, and computer-generated holography. Diagrams of holographic installations are provided. Photographs of typical holographic applications are used to support the theoretical aspects.
Dudley, D. D.↗
An automated system for continuous monitoring of CO 2 geosequestration using multi-well offset VSP with permanent seismic sources and receivers: Stage 3 of the CO2CRC Otway Project
Time-lapse seismic is an essential tool for monitoring CO 2 injection into the subsurface but suffers from high cost and long intervals between surveys. An alternative approach is continuous monitoring using permanent sources and receivers capable of mapping CO 2 plume evolution on an almost daily basis and drastically reduce human effort, cost and survey turnaround. As part of the CO2CRC Otway project, a continuous monitoring system is employed to monitor a small (15,000 tonnes) CO 2 injection within the CO2CRC Otway Project. The permanent monitoring system employs distributed acoustic sensors (DAS) installed in boreholes as seismic receivers and seismic orbital vibrators (SOV) as seismic sources. The monitoring approach is based on vertical seismic profiling using five wells equipped with DAS cemented behind the casing and nine SOVs and is acquiring the data continuously in an autonomous manner. The data is then automatically processed on-site producing a seismic image every 2.5 days, which is then transmitted to a remote office. The data has good repeatability with NRMS of about ~10-15%.
58 GEOSCIENCES↗
Near-Field Imaging of Shallow Chemical Explosions in Granite Using Change Detection Methods with Surface and Borehole Seismic Data
Explosions detonated in geologic media damage it in various ways via processes that include vaporization, fracturing, crushing of interstitial pores, etc. Seismic waves interact with the altered media in ways that could be important to the discrimination, characterization, and location of the explosions. As part of the Source Physics Experiment, we acquired multiple pre- and post-explosion near-field seismic datasets and analyzed changes to seismic P-wave velocity. Our results indicate that the first explosion detonated in an intact media can cause fracturing and, consequently, a decrease in P-wave velocity. After the first explosion, subsequent detonations in the pre-damaged media have limited discernible effects. We hypothesize this is due to the stress-relief provided by a now pre-existing network of fractures into which gasses produced by the explosion migrate. We also see an overall increase in velocity of the damaged region over time, either due to a slow healing process or closing of the fractures by subsequent explosions.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
The Silencing of U.S. Campuses Following the COVID-19 Response: Evaluating Root Mean Square Seismic Amplitudes Using Power Spectral Density Data
In response to the COVID-19 global pandemic, many populated and active regions have become deserted and show significant reductions in their background seismicity, especially campuses across the United States (U.S.). Seismic sensors located in the vicinity of or within U.S. campuses show that anthropogenic seismic noise remains elevated during the ordinary, nonpandemic, academic year, only subduing during periods of recess (e.g., winter break). Here, we use power spectral density (PSD) data computed by the Incorporated Research Institutions for Seismology Data Management Center for quality assessment to calculate root mean square (rms) amplitude and analyze the effects of the COVID-19 school closures. We processed and analyzed PSD data for 46 seismic stations located within 50 m of a U.S. university or college. Results show that 42 campus stations show an overall rms drop following a statewide school closure.
58 GEOSCIENCES↗
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to advance geothermal exploration and safe geothermal energy production. As part of the project, this submission provides data arrays for 149 microearthquakes between the year 2012 and 2013 at the Newberry EGS Site for use with the Deep Learning Algorithm that has been developed. The data provided includes raw waveform data, location data, normalized waveform data, and processed waveform data. Penn State Geothermal Team has shared the following files from the project: - 149 microearthquakes (MEQs) between 2012 and 2013 at Newberry EGS sites, 'Normalized Waveform Inputs.npz' are normalized waveforms. - labels of 149 MEQs: Processed Waveform Inputs.npz - location labels of 149 MEQs: Location Data.npz Note: .npz is the python file format by NumPy that provides storage of array data.
15 GEOTHERMAL ENERGY↗
Auto-Curation of Seismic Event Data for Signal Denoising
Denoising contaminated seismic signals for later processing is a fundamental problem in seismic signals analysis. Neural network approaches have shown success denoising local signals when trained on short-time Fourier transform spectrograms. One challenge of this approach is the onerous process of hand-labeling event signals for training. By leveraging the SCALODEEP seismic event detector, we develop an automated set of techniques for labeling event data. Despite region specific challenges, training the neural network denoiser on machine curated events shows comparable performance to the neural network trained on hand curated events. We showcase our technique with two experiments, one using Utah regional data and one using regional data from the Korean peninsula.
58 GEOSCIENCES↗
Passive seismic tomography application for cave monitoring in DOZ underground mine PT. Freeport Indonesia
It is already known that tomography has a great impact for analyzing and mapping unknown objects based on inversion, travel time as well as waveform inversion. Therefore, tomography has used in wide area, not only in medical but also in petroleum as well as mining. Recently, tomography method is being applied in several mining industries. A case study of tomography imaging has been carried out in DOZ ( Deep Ore Zone ) block caving mine, Tembagapura, Papua. Many researchers are undergoing to investigate the properties of DOZ cave not only outside but also inside which is unknown. Tomography takes a part for determining this objective.The sources are natural from the seismic events that caused by mining induced seismicity and rocks deformation activity, therefore it is called as passive seismic. These microseismic travel time data are processed by Simultaneous Iterative Reconstruction Technique (SIRT). The result of the inversion can be used for DOZ cave monitoring. These information must be used for identifying weak zone inside the cave. In addition, these results of tomography can be used to determine DOZ and cave information to support mine activity in PT. Freeport Indonesia.
58 GEOSCIENCES↗
Denoising Seismograms in the Time Domain Using a Deep Learning Model
Deep learning has emerged as a transformative tool for enhancing the extraction of reliable information from seismograms, addressing the increasing demand for precise and efficient seismic data analysis. We introduce an innovative encoder–decoder deep learning model, named WaveDenoiser, designed for noise reduction in the time domain, thereby eliminating the need for spectrogram computations that have been used for existing deep learning tools and significantly improving processing speed. Utilizing the benchmark dataset that is Stanford Earthquake Dataset, we developed three models of varying sizes: base, medium, and large. Notably, the large (referred to as WaveDenoiser) model demonstrated superior performance, achieving a median signal‐to‐noise ratio improvement of 8.8 dB on in‐distribution unseen data (in the same geographic region) and 7.7 dB on out‐distribution unseen data (in a new geographic region), outpacing both the base and medium models. Further evaluation of the WaveDenoiser model revealed a reduction in median arrival‐time errors by 0.02 s for P waves and 0.01 s for S waves when processing waveforms prior to phase picking using PhaseNet on in‐distribution unseen data. When tested on out‐distribution unseen data, the model also effectively reduced the P‐wave median arrival‐time error by 0.02 and 0.01 s in median arrival‐time error for S waves. Importantly, the application of WaveDenoiser resulted in a significant reduction of phase picking outliers by 1.1% to 3.6% for both P and S waves. In addition, we achieved over five times acceleration in processing speed compared with the seisBench implementation of DeepDenoiser. Our findings underscore the potential of WaveDenoiser as a powerful tool for improving seismic data analysis and processing efficiency.
P-waves↗
Regolith, rock and fluid distributions at the Upper Colorado River Basin via a multicomponent seismic imaging approach
In October 2018, we conducted an exploratory seismic survey of the East River Watershed Function Science Focus Area, near Crested Butte, CO. Our survey goals were to map seismic bedrock, regolith and sediment properties and relate them to geomorphic and hydrologic processes. We acquired ~12 km of seismic data along roads with a 72-channel, 1.25m spaced streamer, an average shot spacing of 2.5m and an average acquisition rate of 3 km/day. We also obtained ~3km of planted geophone data with geophone and shot spacing between 2.5 and 5 meters and an acquisition rate of 0.5 km/day. Vp results show a sharp transition between regolith and bedrock along hillslopes suggesting a similarly abrupt change in porosity. Vp anisotropy in the Mancos Shale is observable in the lower reaches of the watershed, but is absent in regions near crystalline intrusions where contact metamorphism has likely modified pore structure within the shale. Alluvium thickness varies along the river axis from 0 to > 20 meters reflecting variations in depositional processes as function of stream gradient. We show that when strong discontinuities at the regolith base are present, inhomogeneous waves that travel along subsurface interfaces are generated and can be measured on vertical component geophones. We present a summary manuscript in the report appendix.
58 GEOSCIENCES↗
Global centroid moment tensor solutions in a heterogeneous earth: the CMT3D catalogue
SUMMARY For over 40 yr, the global centroid-moment tensor (GCMT) project has determined location and source parameters for globally recorded earthquakes larger than magnitude 5.0. The GCMT database remains a trusted staple for the geophysical community. Its point-source moment-tensor solutions are the result of inversions that model long-period observed seismic waveforms via normal-mode summation for a 1-D reference earth model, augmented by path corrections to capture 3-D variations in surface wave phase speeds, and to account for crustal structure. While this methodology remains essentially unchanged for the ongoing GCMT catalogue, source inversions based on waveform modelling in low-resolution 3-D earth models have revealed small but persistent biases in the standard modelling approach. Keeping pace with the increased capacity and demands of global tomography requires a revised catalogue of centroid-moment tensors (CMT), automatically and reproducibly computed using Green's functions from a state-of-the-art 3-D earth model. In this paper, we modify the current procedure for the full-waveform inversion of seismic traces for the six moment-tensor parameters, centroid latitude, longitude, depth and centroid time of global earthquakes. We take the GCMT solutions as a point of departure but update them to account for the effects of a heterogeneous earth, using the global 3-D wave speed model GLAD-M25. We generate synthetic seismograms from Green's functions computed by the spectral-element method in the 3-D model, select observed seismic data and remove their instrument response, process synthetic and observed data, select segments of observed and synthetic data based on similarity, and invert for new model parameters of the earthquake’s centroid location, time and moment tensor. The events in our new, preliminary database containing 9382 global event solutions, called CMT3D for ‘3-D centroid-moment tensors’, are on average 4 km shallower, about 1 s earlier, about 5 per cent larger in scalar moment, and more double-couple in nature than in the GCMT catalogue. We discuss in detail the geographical and statistical distributions of the updated solutions, and place them in the context of earlier work. We plan to disseminate our CMT3D solutions via the online ShakeMovie platform.
58 GEOSCIENCES↗
Structural and Stratigraphic Controls on Methane Hydrate occurrence and distribution: Gulf of Mexico, Walker Ridge 313 and Green Canyon 955: Final Report
The goal of this project was to determine structural and stratigraphic controls on hydrate occurrence and distribution in Green Canyon (GC) 955 and Walker Ridge (WR) 313 blocks using seismic and well data. Gas hydrate was discovered in these blocks in coarse- and fine-grained sediments during the 2009 Joint Industrial project (JIP) Leg 11 drilling expedition. Although the immediate interest of the exploration community is exclusively hydrate which is present in coarse–grained sediments, factors that control hydrate and free gas distribution in the two blocks and whether coarse and fine-grained hydrate-bearing units are related in any manner, formed the core of this research. The project spanned from 10/01/2012 to 07/31/2016. In the project, in both the leased blocks, the interval spanning the gas hydrate stability zone (GHSZ) was characterized using a joint analysis of sparse Ocean Bottom Seismic (OBS) and dense, surface–towed multichannel seismic (MCS) data. The project team had the luxury of calibrating their results with two well logs. Advance processing methods such as depth migration and full-waveform inversion (FWI) were used for seismic data analysis. Hydrate quantification was achieved through interpretation of the FWI velocity field using appropriate rock physics models at both blocks. The seismic modeling/inversion methodology (common to both GC955 and WR313 blocks) was as follows. First, the MCS data were depth migrated using a P-wave velocity (VP) model constructed using inversion of reflection arrival times of a few (four in both cases) key horizons carefully picked in the OBS data to farthest possible offsets. Then, the resolution of the traveltime VP model was improved to wavelength scale by inverting OBS gathers up to the highest frequency possible (21.75 Hz for GC955 and 17.5 for WR313) using FWI. Finally, the hydrate saturation (or the volume fraction) was estimated at the well location assuming one of the other hydrate morphology (filling the primary or the secondary porosity) was extrapolated out from the wells using the FWI VP as a guide. General outcomes were as follows. First and foremost, an imaging methodology using sparse seismic data, which is easily replicable at other sites with similar datasets, has been demonstrated. The end product of this methodology at both the leased blocks is quantitative estimates of hydrate distribution. Second, at both locations there is strong evidence that the base of the GHSZ, which does not appear as a clear Bottom Simulating Reflection (BSR), manifests in the VP perturbations created by FWI, suggesting that FWI is sensitive to subtle compositional changes in shallow sediments and establishes it as a valuable tool for investigations of hydrate-bearing basins. Third, through joint interpretation of the depth migrated image and the FWI VP model, how structure and stratigraphy jointly determine hydrate and free gas distribution in both blocks could be clearly visualized. The joint interpretation also suggests that the coarse and fine grained hydrate-bearing sediments at both leased are connected. Site specific results, in addition to general results, are as follows. At GC955 the overlying fine-grained hydrate-bearing unit could have been sourced from the underlying hydrate coarse-grained channel-levee complex through a chimney feature. The channel-levee system at GC955 is compartmentalized by faults, of which only a few may be impermeable. Although compartmentalized, the channel-levee system in the GC955 as a whole might be in communication except selected zones. At WR313 the overlying fine-grained fracture-filled hydrate unit appears to be sourced from below the GHSZ. The reason that only a particular fine-grained unit has hydrate, despite having lower porosity that the bounding units, could be the presence of secondary porosity (such as those formed from clay dewatering under compaction). In conclusion, the project was a pioneering effort in in joint analysis of OBS and MCS datasets for advancing the knowledge about a hydrate and free–gas system dynamics using advanced processing methods such as FWI and depth migration. Results obtained in this project can greatly advance the tools and techniques used for delineating specific hydrate prospects. Results obtained in this project can also be seamlessly incorporated into other DOE funded project on modeling the potential productivity and commercial viability of hydrate from sand-dominated reservoirs. The OBS and MCS data in this project were acquired in 2012 (after the JIP II drilling) by the USGS and therefore the results are a posteriori. Nonetheless, the seismic inversion workflow established through this project can be used to generate various what-if quantification scenarios even in absence of logs and serve as a valuable tool for guiding drilling operations. Results from this project can augment other DOE sponsored projects on determining the commercial viability of methane production from the Gulf of Mexico.
03 NATURAL GAS↗
Steptoe Valley NV Data Compilation: Understanding a Stratigraphic Hydrothermal Resource through Geophysical Imaging
Sandia National Laboratories partnered with a multi-disciplinary group of subject matter experts to evaluate a stratigraphic geothermal resource in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. Provided here are a compilation of newly acquired data over the area and select modeling efforts. This encompasses a 3D geological model (inclusive of full Leapfrog files, Leapfrog viewer files, and XYZ data for faults and stratigraphy) with embedded geophysical modeling, controlled-source electromagnetic (CSEM) and magnetotelluric (MT) data packages, aqueous spring geochemistry data, seismic reflection interpretations, and a gravity data package. The stratigraphic reservoir in Steptoe Valley was previously discovered during oil and gas exploration. Subsequent studies, such as the Nevada Play Fairway Analysis, added data which further highlighted potential resource targets in the basin. Geophysical surveys, complimented with refined geologic mapping and geochemical sampling, were deployed to further characterize the resource. The resulting 3D geologic interpretation, conceptual model refinements, and reservoir simulations suggest that a power-capable reservoir is economically accessible in the Paleozoic carbonates of the deep/central basin. Additional geophysical characterization and exploration drilling efforts are recommended to calibrate interpretation and determine where/how to potentially develop the Steptoe resource. The geophysical tools, interpretations, lessons learned, and publicly available data generated by this study establish an exploration methodology to inform decisions for successful development of stratigraphic reservoirs.
15 GEOTHERMAL ENERGY↗
Using Natural Gas Liquids to Recover Unconventional Oil and Gas Resources (Final Report)
This document presents final technical findings for the project Using Natural Gas Liquids to Recover Unconventional Oil and Gas Resources (FE0031782). The project is part of the U.S. Department of Energy Oil and Gas Program to develop and advance technologies that can significantly improve the recovery efficiencies of unconventional oil and gas resources. The overall objective of this project is to improve the ultimate recovery from unconventional oil and gas (UOG) resources in the United States by developing a method for using unrefined natural gas liquids (NGLs) as treatment fluids to improve hydrocarbon production. Horizontal extended-lateral drilling coupled with high volume hydraulic fracturing has significantly increased production from UOG resources in the U.S. However, the recovery efficiency is low compared to the estimated oil and gas in place. Recent data indicate that less than 10% of the oil in the liquid-rich UOG reservoirs is produced. Alternative completion methods using NGLs could increase production (Battelle, 2016; Wan et al., 2013; Wan, 2013; Downey et al, 2021); however, field validation tests are needed to develop an approach that is economical, efficient, and compatible in the UOG setting to advance towards commercial deployment. This project aims to develop and field test a method to improve recovery of oil resources in UOG shale plays by using Y-Grade NGLs, or a similar combination of NGLs, as treatment fluids. Refined NGLs have been used as a hydraulic treatment fluid in UOG plays for decades and are shown to be particularly effective because their miscibility with oil allows oil to flow more freely; however, the use of Y-Grade (unrefined) NGLs has not been studied. The use of Y-Grade NGLs would be advantageous over refined NGLs because Y-Grade NGLs do not require infrastructure or investment in refining and are already being produced from many UOG reservoirs. The concept was tested and monitored in the field at a commercial well site owned by project partner Hopco, Ltd. The project team, which consists of multiple oil and gas operators, Linde Gas North America LLC (Linde) and the Ohio Division of Geological Survey (ODGS), has extensive experience with oil and gas production in the Appalachian basin and the ability to work together quickly to solve technical issues and research needs. A key part of the proposed work was the use of existing wells for field testing and monitoring. A total of four wells (three vertical and one horizontal) were available for this project. One of the vertical wells was utilized as the test well for the NGL treatment test. A nearby vertical well was used for microseismic monitoring. The remaining vertical well and the horizontal well provided a baseline for typical UOG production in the oil window of the Utica/Point Pleasant (UPP). Major technical tasks of the project include characterization of the geotechnical properties of the UPP with an emphasis on the field site; design and planning for the NGLs testing; field testing and monitoring; analysis and integration of field data; and economic and resource/reserve assessment. The Shoman monitoring well and Doughty NGL treatment well were successfully plugged back during September-October 2020 in preparation for treatment and monitoring. A nitrogen diagnostic fracture injection test (DFIT) was completed on the Doughty well on July 22, 2021, consisting of 133,000 scf (91 Bbl.) of nitrogen. A nitrogen foam frac was completed in the Utica-Point Pleasant interval on August 17, 2021 with funding from outside sources. A microseismic monitoring array was installed in the Shoman well and monitored microseismic activity during the Doughty well frac job. Y-Grade NGL injection commenced on August 26, 2021. A total of 215 Bbl. was injected but the job was shut down due to a small leak on the suction hose on the pump truck. The Y-Grade treatment resumed on August 27, 2021 and an additional 726 Bbl. of Y-Grade NGL was injected at a well head pressure of 3850 psi. Total volume of injected Y-Grade over the two days of injection was 941 Bbl. The well was shut-in for 17 days following injection to allow the Y-Grade NGLs to soak on the formation. Y-Grade treatment flow back commenced on 9/13/2021 on a weekly basis. Production data, including surface pressures, oil, nitrogen, natural gas, and flow times was measured and recorded. Periodic gas samples were collected and analyzed to determine composition of flowback gas. As of July 2022, the treatment well had produced 726 Bbl of oil and 2,888 mcf gas. In August 2022, tubing and packer in the well were removed and a pump was installed to enhance oil recovery. Currently, the operator is producing the well about 2 days a week for a few hours. The performance of the NGL treatment test was evaluated based on reservoir simulations of the treatment process, processing of well testing data, analysis of micro seismic monitoring data, and production data analysis. This analysis suggested that oil production in the small test would continue through 2025. Upscaling the treatment to a horizontal Utica Point-Pleasant well would allow more oil recovery, but the process would involve more investment, services, and operational support. An economic analysis was conducted for scenarios aimed at upscaling the NGL treatment process for more typical horizontal UPP wells in the Appalachian Basin.
02 PETROLEUM↗
A New Decade in Seismoacoustics (2010–2022)
Several sources of interest often generate both low‐frequency acoustic and seismic signals due to energy propagation through the atmosphere and the solid Earth. Seismic and acoustic observations are associated with a wide range of sources, including earthquakes, volcanoes, bolides, chemical and nuclear explosions, ocean noise, and others. The fusion of seismic and acoustic observations contributes to a better understanding of the source, both in terms of constraining source location and physics, as well as the seismic to acoustic coupling of energy. Here in this review, we summarize progress in seismoacoustic data processing, including recent developments in open‐source data availability, low‐cost seismic and acoustic sensors, and large‐scale deployments of collocated sensors from 2010 to 2022. Similarly, we outline the recent advancements in modeling efforts for both source characteristics and propagation dynamics. Finally, we highlight the advantages of fusing multiphenomenological signals, focusing on current and future techniques to improve source detection, localization, and characterization efforts. This review aims to serve as a reference for seismologists, acousticians, and others within the growing field of seismoacoustics and multiphenomenology research.
58 GEOSCIENCES↗
IDC Re-Engineering Phase 2 Iteration E1 Use Cases version 1.1.
This document contains 21 use cases generated from the model contained in Rational Software Architect.
97 MATHEMATICS AND COMPUTING↗
Analysis of seismicity at observed at station BCE using subspace detectors
A dynamic correlation processor (DCP) was used to process 90 days of 3-component seismic data recorded by station BCE. Two methods of detector creation were compared. The first attempted to span the signal space with a small number of subspace detectors having minimal projections on one another, and the second used a much larger number of detectors with substantial inter-template projections. After two passes over the data the results were compared, and the second approach was found to have produced more than 3 times the number of detections. For events in common, the average correlation statistic for the second approach was 0.77 compared to a statistic of 0.65 for the first approach. Also, analysis of the detection statistics as a function of SNR showed a strong functional relationship between SNR and correlation statistic for the second approach not found in the first approach. I interpret this to mean that the intra-group variability of signals produced by the second method is due primarily to noise rather than variations in source or path. These results show that (in an environment with large numbers of repeaters) if precise classification is a goal, it is better to operate a DCP with many correlators with substantial inter-template projections and that fully span the signal space. The performance of the DCP was also measured using a small set of “ground truth” picks for BCE from the Chip Brogan catalog. The catalog spanned less than three days out of the 90 days of the experiment and is also incomplete, but the comparison identified 12 signals missed by the DCP because of low SNR. Combining detections by the DCP and picks from the Brogan catalog, identifies 76 unique signals. Of these, the DCP detected 64 (84%) and the Catalog contained between 48/76 (63%) and 48/62 (77%). Analysis of time-of-day and day-of-week statistics was not useful in identifying the signal sources. However, magnitude recurrence statistics were consistent with mining induced seismicity (a preponderance of small sources). Failure of the temporal discriminants may indicate that the events being detected are not coupled in the same way to the mining activity, e.g. secondary failures. Correlation data from explosions at the Nevada test site (NTS) were used to bound the separation of events within groups. Nearly all the NTS correlations with the same passband and time bandwidth product as the detections and having a correlation statistic >= 0.8 are from sources separated by less than 1 km. Even at correlation values of 0.6 nearly all the source separations are less than about 3 km. Because the DCP detectors were formed to span the signal space at a correlation value of 0.9 and because the intra-group variability is most likely due to noise and not source variability, it is likely that the sources associated with each detector are separated by one km or less, and almost certain that the majority are separated by no more than 3 km.
47 OTHER INSTRUMENTATION↗