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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Utah FORGE: Seismic DAS and Geophone Borehole Data Processing and 3D Imaging of Vp/Vs Ratio in the 2024 Stimulated Reservoir

This dataset includes a final report and a 3D velocity model derived from seismic DAS and geophone borehole data collected during the April 2024 stimulation of the reservoir at Utah FORGE. The report details the processing of over 50,000 P- and S-wave travel times used in a tomographic inversion to estimate the Vp/Vs ratio, revealing anomalies adjacent to wells 16A and 16B that may be associated with injected fracturing fluids. Additionally, Wadati analysis of more than 27,000 pairs of differential P- and S-wave travel times supports this interpretation with a high Vp/Vs estimate of 1.86, averaged over the dimensions of the earthquake cluster. The accompanying data file provides a 3D model of P- and S-wave velocities and Vp/Vs ratios, structured with spatial coordinates and velocity values.

15 GEOTHERMAL ENERGY↗
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 OSTI2022

Image-domain DAS 3D VSP elastic transmission tomography

SUMMARY Full-wavefield elastic imaging of active-source seismic data acquired by downhole receivers commonly offers higher-resolution subsurface images in the vicinity of a borehole compared to conventional surface seismic data sets, which can lack higher-frequency wavefield components due to longer travel paths and increased attenuation. An increasingly used approach for downhole acquisition is vertical seismic profiling (VSP), which has become more attractive when coupled with distributed acoustic sensing (DAS) using optical fibres installed in wells. The main difficulty for generating high-quality images with full-wavefield imaging tools for DAS VSP data, though, is the need for an accurate velocity model. To build plausible velocity models using active-source DAS VSP data, we adopt a 3-D image-domain elastic transmission tomography technique, originally developed for surface-recorded passive (microseismic) data, by exchanging the source and receiver positions (i.e. reciprocity) to mimic a passive-seismic surface monitoring scenario. The inversion approach exploits various images for each source constructed through time-reverse imaging (TRI) of downgoing P- and S-wave first-arrival waveforms. The TRI process uses the kinetic term of the (extended) PS energy imaging condition that exhibits sufficient sensitivity to velocity model errors. The method automatically updates the P- and S-wave velocity models to optimize image focusing via adjoint-state inversion. We illustrate the efficacy of the adopted elastic inversion technique using an active-source DAS 3-D VSP field data set acquired in the North Slope of Alaska. The numerical experiments demonstrate that the inverted elastic velocity models can be further used in full-wavefield acoustic/elastic imaging algorithms to obtain accurate subsurface images.

Oren, Can (ORCID:000000019534265X)↗
DOE OSTI2022

3D Time-Lapse Electrical Resistivity Imaging of Rock Damage Patterns and Gas Flow Paths Resulting from Two Underground Chemical Explosions

Abstract Rock damage from underground nuclear explosions (UNEs) has a strong influence on sub-surface gas movement and on seismic waveform characteristics, both of which are used to detect UNEs. Although advanced numerical simulation capabilities exist to predict rock damage patterns and corresponding detection signals, those predictions are dependent on (generally) unknown properties of the host rock. For example, the effects of in-situ mechanical heterogeneities on the explosively generated damage/fractures that provide gas flow pathways to the surface are not well understood, due largely to the difficulty in accessing and characterizing the near-source region. In this paper we demonstrate the emerging use of electrical resistivity tomography (ERT) for imaging rock damage and gas flow patterns resulting from two relatively small-scale underground chemical explosions. Pre-explosion ERT and crosshole seismic imaging revealed a natural fracture zone within the test bed. Post-explosion imaging revealed that the damage zone was non-symmetric and was focused primarily within the pre-existing fracture zone, located 10 m above the first explosion and 5 m above the second explosion. Time-lapse ERT imaging of heated air injected into the detonation borehole revealed the primary gas flow paths to be within the upper margin of the same primary damage zone. These results point to the utility of ERT imaging for understanding rock damage and gas flow patterns under experimental conditions, and to the importance of understanding the effects of geologic heterogeneity on UNE detection signals, particularly gas surface breakthrough times.

58 GEOSCIENCES↗
DOE OSTI2023

New Insights from Legacy Seismic Data regarding Basalt Elevations and Variability on the Hanford Site

Migration of groundwater contaminants in the Gable Gap area of the Hanford Site in southeastern Washington State is strongly influenced by the distribution and permeability of basalts that lie beneath an unconfined aquifer. Locally, folding and faulting of the Columbia River Basalt associated with the Yakima fold and thrust belt followed by erosion due to the Lake Missoula floods resulted in a complex basalt surface that represents either an impermeable lower boundary to the unconfined aquifer system or localized regions of increased permeability that potentially promote communication between the unconfined aquifer system and deeper, confined aquifer systems. Paleo-channels carved into the basalt by floodwaters are thought to provide preferential flow paths for groundwater contaminants. In 2011, a seismic landstreamer campaign was carried out to image the basalt surface and produced pre-stack depth migrated p-wave reflection images. The reflection images identified two large troughs that may represent paleo-channels and several areas of possible faulting. Here, the streamer data are re-analyzed using refraction travel-time and Rayleigh wave dispersion analyses to obtain images of compressional and shear wave velocities within the suprabasalt sediment sections and the upper basalt surface. The combined interpretation of reflection and seismic velocity images shows complexity in the basalt velocity and elevation, which varies by 50 m or more within the study area. These results, along with other ongoing geophysical investigations, will be used to inform the site geologic model and potentially guide placement of future boreholes needed to quantify vertical flow between the confined and unconfined aquifers.

58 GEOSCIENCES↗
DOE OSTI2024

Relocation of the 8 September 2023 High Atlas, Morocco, Earthquake Aftershock Sequence

The earthquake that occurred on 8 September 2023, with a magnitude of 6.8, was the most destructive earthquake event in Morocco in the past decade. This earthquake took place in the Al Haouz region, located in the western part of the High Atlas Mountain range. To better understand what caused and triggered this earthquake, the earthquake catalogs including P and S arrival times were collected from the Moroccan seismic network and combined with regional data from the International Seismological Centre. The mainshock and aftershocks were relocated by using iLoc, a state-of-the-art single-event location algorithm, and then by the multiple event location double-difference algorithm, hypoDD. The improved earthquake relocations using iLoc and the double-difference methods provide sharper lineation of seismicity and agree well with tomographic images of the earthquake zone. Finally, the seismicity distribution and the focal mechanism of the mainshock indicate that the earthquake sequence has occurred along the South Atlas fault system.

58 GEOSCIENCES↗
DOE OSTI2023

Examining Infrasound Propagation at High Spatial Resolution Using a Nodal Seismic Array

Infrasound—acoustic waves in the atmosphere below 20 Hz—is a useful monitoring tool. Topography and atmospheric structure strongly control infrasound propagation, and at common source–receiver distances neither of these effects can be ignored when quantitative source constraints are sought. Detailed spatial measurements of the infrasound wavefield would inform propagation models and improve source estimates. However, the “large-N” deployment strategy now well-known in seismology has not yet been realized for infrasound studies. Here, we use the 900-node seismic array from the 2014 Imaging Magma Under St. Helens (iMUSH) experiment as a proxy for a large-N infrasound network, by leveraging acoustic–seismic coupled arrivals. The active-source component of iMUSH consisted of 23 shallowly buried explosions around Mount Saint Helens volcano; these explosions produced epicentral infrasound recorded on the nodes. We find that the bulk presence of ground-coupled infrasound on the nodes is controlled by wind noise and source–receiver distance, with observed arrivals for eight explosions. Explosions with the most extensive coupling produce complex spatial waveform patterns across the array. These patterns are related to both topographic and atmospheric propagation effects, as well as spatially variable site (coupling) effects. We compare our observations to simple topographic diffraction and high-resolution wind advection models, and full-wave numerical simulations. We find strong spatial correlations between (a) coupled arrival strength and modeled topographic obstruction and (b) coupled arrival time and along-path winds. Our seismoacoustic analyses and results are applicable to other existing and future nodal seismic data sets and can expand the utility of such deployments.

58 GEOSCIENCES↗
DOE OSTI2022

Trans-crustal structural control of CO 2 -rich extensional magmatic systems revealed at Mount Erebus Antarctica

Erebus volcano, Antarctica, with its persistent phonolite lava lake, is a classic example of an evolved, CO 2 -rich rift volcano. Seismic studies provide limited images of the magmatic system. Here we show using magnetotelluric data that a steep, melt-related conduit of low electrical resistivity originating in the upper mantle undergoes pronounced lateral re-orientation in the deep crust before reaching shallower magmatic storage and the summit lava lake. The lateral turn represents a structural fault-valve controlling episodic flow of magma and CO 2 vapour, which replenish and heat the high level phonolite differentiation zone. This magmatic valve lies within an inferred, east-west structural trend forming part of an accommodation zone across the southern termination of the Terror Rift, providing a dilatant magma pathway. Unlike H 2 O-rich subduction arc volcanoes, CO 2 -dominated Erebus geophysically shows continuous magmatic structure to shallow crustal depths of < 1 km, as the melt does not experience decompression-related volatile supersaturation and viscous stalling.

58 GEOSCIENCES↗
DOE OSTI2023

NETL Plastic Pipes Project (Final Report)

Plastic or composite pipelines have been the bane of the utility locating industry because they are neither conductive nor magnetic which are the properties traditionally used to locate buried utilities. Ground penetrating radar (GPR) is an effective geophysical tool for locating plastic/composite pipelines where resistive cover allows for adequate penetration of radar energy. However, GPR has limited applicability in areas where the soil cover is conductive due to significant clay and/or salt content. This study examines complementary near-surface geophysical methods that are potentially useful for locating buried plastic/composite pipelines, either singly or in combination. Specifically, this modeling study used computational numerical methods to forward model the response of GPR, resistivity, seismic, gravity gradiometry, and photoacoustic/thermoacoustic imaging methods to plastic/composite pipelines for various scenarios including: (1) pipe diameters ranging between 2 in. to 12 in.; (2) burial depths ranging between 3 ft. to 4 ft.; (3) various degrees in contrast in physical properties (i.e., electrical permittivity, elasticity, resistivity, density); and (4) various experimental acquisition choices (e.g., GPR radar and seismic source frequencies, electrode spacing). Numerical modeling performed herein reconfirmed that GPR is the preferred method for detecting/locating plastic pipelines. A caveat for GPR detection is that the material covering the plastic pipe (trench fill material and adjacent soil) must be sufficiently resistive to allow the two-way propagation to the required depth of investigation and back to the surface. GPR was the only method modeled in this study that can be used to directly detect plastic pipelines of 2-in.-diameter and larger when buried 3-ft-deep. GPR data processing and imaging also can determine pipe depth, pipe diameter, trench dimensions, and moisture conditions. Seismic modeling results suggest that direct detection of a 12-in.-diameter plastic pipe at 3-ft.-depth may be possible under favorable conditions; however, the associated signature would be weak (e.g., surface- to S-wave, backscattered surface-waves, and/or forward scattered surface-waves to S-wave). Direct pipe detection under field conditions with noise and strong lateral geologic heterogeneity is doubtful. Numerical modeling also suggests that plastic pipelines can be indirectly located by detecting the trench in which they are buried. GPR, direct current (DC) resistivity, and seismic methods have the potential to locate the pipeline trench if there is sufficient contrast between the trench-wall and trench-fill materials for the physical property being measured by each method (i.e., electrical permittivity for GPR; resistivity for DC resistivity; or density, compressional velocity, or shear velocity for seismic). Modeling also indicated that currently available (commercial) gravity gradiometers would be unable to directly detect/locate plastic pipelines ≤ 8-in.-diameter when buried 3-ft.-deep given the typical instrument noise floor for field surveying as well as the expected density variations due to geologic heterogeneity. The numerical modeling performed in this project did not identify a universal geophysical technology that can locate buried plastic pipelines in all parts of the United States (although GPR is suggested for all areas with resistive cover). However, the project results suggest that a towed land streamer simultaneously acquiring multiple geophysical data types including multi-offset GPR, multi-channel DC resistivity, seismic geophone- and/or distributed acoustic sensing (DAS), and potentially photoacoustic/thermoacoustic data would be an appropriate platform for locating buried plastic pipeline. Moreover, the complementary multiphysics data acquired by a towed land streamer would permit the use of joint and/or cooperative inversion frameworks for a more rigorous and consistent data interpretation.

42 ENGINEERING↗
DOE OSTI2022

Summary: SEE4GEO

The seismoelectric effects technique (SEE) is a new and innovative approach for geothermal subsurface imaging and monitoring at reservoir scale. The objective of this project is to assess SEE in terms of data acquisition, cost and quality, and to determine its capability in comparison with classical imaging and monitoring techniques, particularly decoupled seismic and electromagnetic methods. This will be achieved by (1) development of a fast, true 3D numerical package, handling SEE imaging and subsurface properties characterization, including resistivity and permeability, (2) laboratory experiments performed in a controlled environment to define optimal deployment design, data quality, and inform field deployment, and (3) field surveys to ultimately test and draw lessons for practical use of SEE technology. There is a relatively extensive body of work in the literature on SEE, and members of this consortium have been involved in theoretical and numerical development of SEE modeling as well as laboratory experiments. Nevertheless, to our knowledge few, if any, documented efforts have been specifically targeting the use of SEE for geothermal subsurface imaging and monitoring. The strength and originality of our proposal rely on an integrated approach leveraging numerical, laboratory and field experiments, to properly document the practical use of SEE. Through this process, SEE in-hand technology for the geothermal industry will be able to progress from a TRL 1 to TRL 3.

58 GEOSCIENCES↗
DOE OSTI2022

Seismoelectric Effects for Geothermal Resources Assessment and Monitoring (SEE4GEO)

The seismoelectric effects technique (SEE) is a new and innovative approach for geothermal subsurface imaging and monitoring at reservoir scale. The objective of this project is to assess SEE in terms of data acquisition, cost and quality, and to determine its capability in comparison with classical imaging and monitoring techniques, particularly decoupled seismic and electromagnetic methods. This will be achieved by (1) development of a fast, true 3D numerical package, handling SEE imaging and subsurface properties characterization, including resistivity and permeability, (2) laboratory experiments performed in a controlled environment to define optimal deployment design, data quality, and inform field deployment, and (3) field surveys to ultimately test and draw lessons for practical use of SEE technology. There is a relatively extensive body of work in the literature on SEE, and members of this consortium have been involved in theoretical and numerical development of SEE modeling as well as laboratory experiments. Nevertheless, to our knowledge few, if any, documented efforts have been specifically targeting the use of SEE for geothermal subsurface imaging and monitoring. The strength and originality of our proposal rely on an integrated approach leveraging numerical, laboratory and field experiments, to properly document the practical use of SEE. Through this process, SEE in-hand technology for the geothermal industry will be able to progress from a TRL 1 to TRL 3.

58 GEOSCIENCES↗
DOE OSTI2022

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

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

Geochemistry & Geophysics↗
DOE OSTI2022

Imaging the crust and uppermost mantle structure of Portugal (West Iberia) with seismic ambient noise

SUMMARY We present a new high-resolution 3-D shear wave velocity (Vs) model of the crust and uppermost mantle beneath Portugal, inferred from ambient seismic noise tomography. We use broad-band seismic data from a dense temporary deployment covering the entire Portuguese mainland between 2010 and 2012 in the scope of the WILAS project. Vertical component data are processed using phase correlation and phase weighted stack to obtain empirical Green functions (EGFs) for 2016 station pairs. Further, we use a random sampling and subset stacking strategy to measure robust Rayleigh-wave group velocities in the period range 7–30 s and associated uncertainties. The tomographic inversion is performed in two steps: First, we determine group-velocity lateral variations for each period. Next, we invert them at each grid point using a new trans-dimensional inversion scheme to obtain the 3-D shear wave velocity model. The final 3-D model extends from the upper crust (5 km) down to the uppermost mantle (60 km) and has a lateral resolution of ∼50 km. In the upper and middle crusts, the Vs anomaly pattern matches the tectonic units of the Variscan Massif and Alpine basins. The transition between the Lusitanian Basin and the Ossa Morena Zone is marked by a contrast between moderate- and high-velocity anomalies, in addition to two arched earthquake lineations. Some faults, namely, the Manteigas–Vilariça–Bragança fault and the Porto–Tomar–Ferreira do Alentejo fault, have a clear signature from the upper crust down to the uppermost mantle (60 km). Our 3-D shear wave velocity model offers new insights into the continuation of the main tectonic units at depth and contributes to better understanding the seismicity of Portugal.

Silveira, Graça (ORCID:0000000221102554)↗
DOE OSTI2020

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

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

58 GEOSCIENCES↗
DOE OSTI2023

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗
DOE OSTI2022

Deep learning multiphysics network for imaging CO 2 saturation and estimating uncertainty in geological carbon storage

Multiphysics inversion exploits different types of geophysical data that often complement each other and aims to improve overall imaging resolution and reduce uncertainties in geophysical interpretation. Despite the advantages, traditional multiphysics inversion is challenging because it requires a large amount of computational time and intensive human interactions for preprocessing data and finding trade-off parameters. These issues make it nearly impossible for traditional multiphysics inversion to be applied as a real-time monitoring tool for geological carbon storage. In this paper, we present a deep learning (DL) multiphysics network for imaging CO 2 saturation in real time. The multiphysics network consists of three encoders for analysing seismic, electromagnetic and gravity data and shares one decoder for combining imaging capabilities of the different geophysical data for better predicting CO 2 saturation. The network is trained on pairs of CO 2 label models and multiphysics data so that it can directly image CO 2 saturation. Here we use the bootstrap aggregating method to enhance the imaging accuracy and estimate uncertainties associated with CO 2 saturation images. Using realistic CO 2 label models and multiphysics data derived from the Kimberlina CO 2 storage model, we evaluate the performance of the deep learning multiphysics network and compare its imaging results to those from the deep learning single-physics networks. Our modelling experiments show that the deep learning multiphysics network for seismic, electromagnetic, and gravity data not only improves the imaging accuracy but also reduces uncertainties associated with CO 2 saturation images. Our results also suggest that the deep learning multiphysics network for the non-seismic data (i.e., electromagnetic and gravity) can be used as an effective low-cost monitoring tool in between regular seismic monitoring.

58 GEOSCIENCES↗
DOE OSTI2021

Determining fast-S and slow-S propagation directions with SV-P data produced by buried explosives and recorded with vertical geophones

We have evaluated the concept of practicing S-wave reflection seismology with legacy 3D seismic data generated by a P-wave source and recorded with only vertical geophones. This type of S-wave imaging is based on the principle that seismic P-wave sources not only produce a downgoing illuminating P wavefield, but they also simultaneously produce a downgoing illuminating SV wavefield that, in almost all cases, is suitable for S-wave reflection imaging. The S-mode used in this study is the SV-P, or converted-P, mode. This mode involves a downgoing illuminating SV wavefield and an upgoing reflected P-mode that is recorded by vertical geophones. In flat-layered stratigraphy, the lengths of the SV and P raypaths in SV-P imaging are identical to the lengths of the SV and P raypaths in P-SV imaging with P-sources and 3C geophones. P-SV imaging of deep rocks has been practiced for more than two decades; SV-P imaging is a new concept. SV-P data should provide the same options for investigating deep rocks as do P-SV data. We have determined one of the equivalences between SV-P data extracted from vertical-geophone data and P-SV data extracted from horizontal geophones: that both modes react to azimuth-dependent variations in the S velocity in anisotropic rocks. Azimuthal variations in the SV-P traveltime can be used to define the polarization direction of the fast-S-wave mode, which is also the azimuth of the maximum horizontal stress (SHmax). Our investigation demonstrates a noninvasive method for monitoring changes in the SHmax azimuth across a CO 2 storage reservoir, or any targeted porous rock, as fluids are cycled into, and then out of, that rock’s pore space.

Geochemistry & Geophysics↗
DOE OSTI2021

A Consensus Equilibrium Approach for 3-D Land Seismic Shots Recovery

Physical and budget constraints often result in inadequate sampling for accurate subsurface imaging. Preprocessing approaches, such as missing trace interpolation, are typically employed to enhance seismic data in such cases. The compressed sensing (CS) framework has been applied for modeling missing seismic data, which is estimated by sparsity-based computational algorithms. While existing work mainly focuses on recovering missing traces resulting from receiver subsampling, source subsampling has greater economical advantages, as sources are more expensive than receivers. Moreover, stronger image models different from sparsity have not been explored for source recovery. This work presents a consensus equilibrium (CE) approach to recover missing seismic shots, which enables to incorporate various regularization operators modeling different data priors. Here, simulation results from a real 3-D land seismic dataset demonstrate that the CE approach provides more accurate estimations of the linear and hyperbolic events in the recovered shots, compared with pure sparsity-based reconstructions.

58 GEOSCIENCES↗