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Prior studies have shown an ambiguous relationship between gas-hydrate saturation and seismic attenuation in different regions, but the effect of gas-hydrate morphology on seismic attenuation of hydrate-bearing sediments was often overlooked. We have combined seismic data with rock-physics modeling to elucidate how gas-hydrate saturation and morphology may control seismic attenuation. To extract P-wave attenuation, we process the vertical seismic profile data within a frequency range of 30–150 Hz and the sonic logging data within 10–15 kHz from three wells in the south Hydrate Ridge, offshore Oregon (USA), collected during Ocean Drilling Program Leg 204 in 2000. We calculate the P-wave attenuation using spectral matching and centroid frequency shift methods, and we use Archie’s relationship to derive gas-hydrate saturation from the resistivity data above the bottom-simulating reflection at the same wells. To interpret the observed seismic attenuation in terms of the effects of the gas-hydrate saturation and the morphology, we use the hydrate-bearing effective sediment rock-physics model. By comparing the observed and model-predicted attenuation values, we infer that (1) seismic attenuation appears to not be dominated by any single factor — instead, its variation is likely governed by the gas-hydrate saturation and the morphology; (2) the relationship between seismic attenuation and gas-hydrate saturation varies with different hydrate morphologies; (3) the squirt flow, occurring at different compliances of adjacent pores driven by pressure gradients, may be responsible for the significantly large or small attenuation over a broad frequency range.

Thunderstorms are a common atmospheric phenomenon that cause abundant acoustic disturbances, which can interact with the ground surface, creating a link between atmospheric and solid Earth processes. This article reports seismological observations of four thunderstorms through the spring and summer of 2019, as recorded by the distributed acoustic sensing fiber-optic array (4.9 km) on the Penn State campus in State College, Pennsylvania. With a dense sensor array in the local region, we are able to construct the seismic full waveform response of the thunderstorm events (hereafter referred to as thunderquakes) and track the wave propagation across the array. We use a time-domain grid search to obtain the back azimuth and slowness of the waves, and a modified Geiger’s method to pinpoint source locations of the thunderquakes. Correlated with the time of the recorded signal, this data allows reconstruction of thunderstorm movement as well as offering measurements of the seismic velocity.

SUMMARY Seismic attenuation (quantified by the quality factor Q) has a significant impact on the seismic waveforms, especially in the fluid-saturated rocks. This dissipative process can be phenomenologically represented by viscoelastic models. Previous seismological studies show that the Q value of Earth media exhibits a nearly frequency-independent behaviour (often referred to as constant-Q in literature) in the seismic frequency range. Such attenuation can be described by the mathematical Kjartansson constant-Q model, which lacks of a physical representation in the viscoelastic sense. Inspired by the fractal nature of the pore fluid distribution in patchy-saturated rocks, here we propose two fractal mechanical network (FMN) models, that is, a fractal tree model and a quasi-fractal ladder model, to phenomenologically represent the frequency-independent Q behaviour. As with the classic viscoelastic models, the FMN models are composed of mechanical elements (spring and dashpots) arranged in different hierarchical patterns. A particular parametrization of each model can produce the same complex modulus as in the Kjartansson model, which leads to the constant-Q. Applying the theory to several typical rock samples, we find that the seismic attenuation signature of these rocks can be accurately represented by either one of the FMN models. Besides, we demonstrate that the ladder model in particular exhibits the realistic multiscale fractal structure of the saturated rocks. Therefore, the FMN models as a proxy could provide a new way to estimate the microscopic rock structure property from macroscopic seismic attenuation observation.

Seismic data for studying the near surface have historically been extremely sparse in cities, limiting our ability to understand small-scale processes, locate small-scale geohazards, and develop earthquake hazard microzonation at the scale of buildings. In recent years, distributed acoustic sensing (DAS) technology has enabled the use of existing underground telecommunications fibers as dense seismic arrays, requiring little manual labor or energy to maintain. At the Fiber-Optic foR Environmental SEnsEing array under Pennsylvania State University, we detected weak slow-moving signals in pedestrian-only areas of campus. These signals were clear in the 1 to 5 Hz range. We verified that they were caused by footsteps. As part of a broader scheme to remove and obscure these footsteps in the data, we developed a convolutional neural network to detect them automatically. We created a data set of more than 4000 windows of data labeled with or without footsteps for this development process. We describe improvements to the data input and architecture, leading to approximately 84% accuracy on the test data. Performance of the network was better for individual walkers and worse when there were multiple walkers. We believe the privacy concerns of individual walkers are likely to be highest priority. Community buy-in will be required for these technologies to be deployed at a larger scale. Hence, we should continue to proactively develop the tools to ensure city residents are comfortable with all geophysical data that may be acquired.

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

The generation of microseismic events is often associated with induced fractures/faults during the extraction/injection of fluids. A full characterization of the spatiotemporal distribution of microseismic events provides constraints on fluid migration paths in the formations. We have developed a high-resolution source imaging method — a hybrid multiplicative time-reversal imaging (HyM-TRI) algorithm, for automatically tracking the spatiotemporal distribution of microseismic events. HyM-TRI back propagates the data traces from groups of receivers (in space and time) as receiver wavefields, multiplies receiver wavefields between all groups, and applies a causal integration over time to obtain a source evolution image. Using synthetic and field-data examples, we revealed the capability of the HyM-TRI technique to image the spatiotemporal sequence of asynchronous microseismic events, which poses a challenge to standard TRI methods. Moreover, the HyM-TRI technique is robust enough to produce a high-resolution image of the source in the presence of noise. The aperture of the 2D receiver array (azimuth coverage in 3D) with respect to the microseismic source area plays an important role on the horizontal and vertical resolution of the source image. The HyM-TRI results of the field data with 3D azimuthal coverage further verify our argument by producing a superior resolution of the source than TRI.

Quantifying the dynamics of sequestered CO2 plumes is critical for safe long-term storage, providing guidance on plume extent, and detecting stratigraphic seal failure. However, existing seismic monitoring methods based on wave reflection or transmission probe a limited rock volume and their sensitivity decreases as CO2 saturation increases, decreasing their utility in quantitative plume mass estimation. Here we show that seismic scattering coda waves, acquired during continuous borehole monitoring, are able to illuminate details of the CO2 plume during a 74-h CO2 injection experiment at the Frio-II well Dayton, TX. Our study reveals a continuous velocity reduction during the dynamic injection of CO2, a result that augments and dramatically improves upon prior analyses based on P-wave arrival times. We show that velocity reduction is nonlinearly correlated with the injected cumulative CO2 mass and attribute this correlation to the fact that coda waves repeatedly sample the heterogeneous distribution of cumulative CO2 in the reservoir zone. Lastly, because our approach does not depend on P-wave arrival times or require well-constrained wave reflections it can be used with many source-receiver geometries including those external to the reservoir, which reduces the risk introduced by in-reservoir monitoring wells. Our results provide an approach for quantitative CO2 monitoring and plume evolution that increases safety and long-term planning for CO2 injection and storage.

Recent world-wide quieting of seismic noise caused by COVID-19 lockdown measures has been observed by seismometers. However, current seismic network that has a few seismometers or none in a city-sc...

A continuous active source seismic monitoring (CASSM) dataset was collected with crosswell geometry during CO2 injection at the Frio-II brine pilot, near Liberty, TX. Previous studies have shown that spatio-temporal changes in the P-wave first arrival time reveal the movement of the injected CO2 plume in the storage zone. To further constrain the CO2 saturation, particularly at higher saturation levels, we investigate spatial-temporal changes in the seismic attenuation of the first arrivals. The attenuation changes over the injection period are estimated by the amount of the centroid frequency shift computed by local time-frequency analysis. We observe that: (1) at receivers above the injection zone seismic attenuation does not change in a physical trend; (2) at receivers in the injection zone attenuation sharply increases following injection and peaks at specific points varying with distributed receivers, which is consistent with observations from time delays of first arrivals; then, (3) attenuation decreases over the injection time. The attenuation change exhibits a bell-shaped pattern during CO2 injection. Under Frio-II field reservoir conditions, White's patchy saturation model can quantitatively explain both the P-wave velocity and attenuation response observed. We have combined the velocity and attenuation change data in a cross-plot format that is useful for model-data comparison and determining patch size. Our analysis suggests that spatial-temporal attenuation change is not only an indicator of the movement and saturation of CO2 plumes, even at large saturations, but also can quantitatively constrain CO2 plume saturation when used jointly with seismic velocity.

The Boom Clay is being investigated as a host rock for disposal purposes of radioactive wastes. Although the formation is relatively uniform and homogeneous, there are embedded septaria bodies (carbonates) or layers of septaria that may constitute a problem regarding the integrity of the clay. It is therefore essential to locate these geobodies, particularly with seismic experiments. Since the medium shows strong attenuation it is necessary to correct for this amplitude loss if true amplitudes of the reflections are required when imaging these bodies after the stack. To achieve this task, we implement a reverse-time migration algorithm based on a dispersionless anelastic rheology, that is, the phase velocity and attenuation factor are frequency independent, and back-propagation is performed with a negative quality factor, Q. The algorithm is tested on synthetic data. For this we assume that the septaria are diffractors generating waves synchronously to simulate a stacked seismic section, that is, the result of an exploding-reflector experiment. In this case, back-propagation is stopped when all the diffraction points are imaged at the same time. The examples consider layers of septaria and isolated septaria embedded in homogeneous and inhomogeneous Boom Clay with zones of low Q. The amplitude of the geobodies is recovered and the resolution is improved, even in the presence of noise.

Distributed acoustic sensing (DAS) has seen many advances in recent years with many different applications. This special section contains six papers featuring applications that vary from microseismic event detection to subsea applications to surface deployments, fracture characterization, and well irregularity identification. Each paper introduces a unique problem and then poses the use of DAS in an appropriate way to solve the problem. Special sections on DAS are relatively frequent in the literature currently, so these papers are a snapshot of the work done with the technology. We hope you enjoy these publications.

A knowledge of hydrate morphology is essential for assessing its resource potential, understanding its formation, and determining optimum strategies for exploitation. Previous studies have suggested two general morphologies of gas hydrates distributions in sediment settings: pore- and fracture-filling. However, because of a lack of effective morphology identification methods, it is currently difficult to quantitatively model gas hydrates. Here we propose a joint analysis of P-wave velocity and resistivity to identify hydrate morphology and estimate hydrate saturation in a continuous depth profile. First, we perform numerical modeling to investigate the effects of hydrate morphology on the P-wave velocity and resistivity properties of gas hydrate-bearing sediments (GHBS). The results demonstrate that, in the case of identical hydrate concentration, fracture-filling GHBS typically exhibit higher resistivity but lower P-wave velocity than those of pore-filling GHBS. Consequently, the cross plot between these two properties are strikingly different for the two types of GHBS. By comparing the cross plot of field measurements to the theoretical cross plot, we hypothesize that hydrate morphology can be identified and hydrate saturations estimated. We test and verify the hypothesis using the velocity and resistivity log data at different sites in China's second gas hydrate expedition in 2013 in the South China Sea, where the two morphologies were confirmed via core samples. Cross plots of field measurements agree closely with the theoretical results, and gas hydrate morphologies are successfully identified. The estimated hydrate saturations are comparable to measurements of pore-water freshening in the majority of cases.

A one-day postconvention workshop held during the 2018 SEG Annual Meeting in Anaheim, California, focused on seismic attenuation model building and compensation through imaging in the morning and on frequency-dependent seismic interpretation and rock physics in the afternoon. The workshop was organized by Dhananjay Kumar (BP), Yi Shen (Shell), Kui Bao (Shell), Mark Chapman (University of Edinburgh), Doug Foster (The University of Texas at Austin), Wenyi Hu (Advanced Geophysical Tech Inc.), and Tieyuan Zhu (Pennsylvania State University). The main topics discussed were: attenuation and Q model building using seismic, vertical seismic profiling, well-log and core data, seismic attenuation compensation, rock-physics modeling, seismic modeling, and frequency-dependent seismic interpretation.

Attenuation compensation in reverse-time migration has been shown to improve the resolution of the seismic image. In this paper, three essential aspects of implementing attenuation compensation in reverse-time migration are studied: the physical justification of attenuation compensation, the choice of imaging condition, and the choice of a low-pass filter. The physical illustration of attenuation compensation supports the mathematical implementation by reversing the sign of the absorption operator and leaving the sign of the dispersion operator unchanged in the decoupled viscoacoustic wave equation. Further theoretical analysis shows that attenuation compensation in reverse-time migration using the two imaging conditions (cross-correlation and source-normalized cross-correlation) is able to effectively mitigate attenuation effects. In numerical experiments using a simple-layered model, the source-normalized cross-correlation imaging condition may be preferable based on the criteria of amplitude corrections. The amplitude and phase recovery to some degree depend on the choice of a low-pass filter. In an application to a realisticMarmousi model with added Q, high-resolution seismic images with correct amplitude and kinematic phase are obtained by compensating for both absorption and dispersion effects. Compensating for absorption only can amplify the image amplitude but with a shifted phase.

Delineating reservoir units is still a challenge for seismic approaches. Even high-resolution crosswell tomographic approaches that produce smooth velocity models to match traveltime data usually provide limited information about the boundaries of subsurface targets. A recent development of seismic traveltime tomography incorporated with a boundary-preserving regularization constraint promisingly helps to resolve ambiguities in reservoir boundaries, while allowing lateral variations. We applied a kind of boundary-preserving traveltime tomography to delineate boundaries of the reservoir and [Formula: see text]-saturated zones. We chose the minimum gradient support as the regularization to preserve boundaries of the geologic target by penalizing smaller model gradients and smoothing small model variations caused by noise. We evaluated several synthetic and real data applications. Synthetic examples demonstrated that the boundary-preserving algorithm produced improved recovery of the profile shape and velocity values of the blocky targets. Two real applications were for delineating the top and base of the reservoir in the King Mountain field, and for delineating a [Formula: see text]-saturated zone in the McElroy field. These inversion results suggested that the boundary-preserving inversion is able to provide better delineation of the top and base boundaries of the reservoir and boundaries of the [Formula: see text]-saturated zone than the conventional smooth-constrained inversion.

To test the effectiveness of the [Formula: see text]-compensated reverse time migration ([Formula: see text]-RTM) method, we applied it to crosswell seismic data from western Texas. This crosswell field survey was aimed at determining the boundaries and even the internal features of the reservoir. In this area, the reservoir geologic body exhibits strong attenuation that reduces high frequencies more rapidly. Thus, conventional acoustic RTM produces a dimmed image (reduced amplitude and low resolution) of the reservoir area and structures underneath. In contrast, [Formula: see text]-RTM is able to compensate for the attenuation effects during imaging. The [Formula: see text] and [Formula: see text] profiles needed for [Formula: see text]-RTM were produced by joint traveltime and frequency shift tomography. Preprocessing of the data was carried out to reduce noise, remove tube waves, and to separate up- and downgoing wavefields. Along with recovered high wavenumbers, the final [Formula: see text]-RTM image provided many details about geologic layers and structures. The lateral and vertical extent and internal structures within the reservoir unit were clearly determined. These geologic features were also correlated to the velocity profile and sonic logs. We concluded that [Formula: see text]-RTM imaging practically improved the image resolution in attenuating geologic media.

SUMMARY Time-reverse modelling (TRM) of acoustic wave propagation has been widely implemented in seismic migration and time-reversal source imaging. The basic assumption of this modelling is that the wave equation is time-invariant in non-attenuating media. In the Earth, attenuation often invalidates this assumption of time-invariance. To overcome this problem, I propose a TRM approach that compensates for attenuation and dispersion effects during the wave propagation in attenuating media. This approach is based on a viscoacoustic wave equation which explicitly separates attenuation and dispersion following a constant-Q model. Compensating for attenuation and dispersion during TRM is achieved by reversing the sign of the attenuation operator coefficient while leaving the counterpart dispersion parameter unchanged in this viscoacoustic wave equation. A low-pass filter is included to avoid amplifying high-frequency noise during TRM. I demonstrate the effects of the filter on the attenuation and the phase velocity by comparing with theoretical solutions in a 1-D Pierre shale homogeneous medium. Three synthetic examples are used to demonstrate the feasibility of attenuation compensation during TRM. The first example uses a 1-D homogeneous model to demonstrate the accuracy of the numerical implementation of the methodology. The second example shows the applicability of source location using a 2-D layering model. The last example uses a 2-D cross-well synthetic experiment to show that the methodology can also be implemented in conjunction with reverse-time migration to image subsurface reflectors. When attenuation compensation is included, I find improved estimation of the source location, the excitation timing of the point source, the magnitude of the focused source wavelet and the reflectivity image of reflectors, particularly for deep structures underneath strongly attenuating zones.

This paper first developed a technique to tomographically estimate a Q model from the migrated image using two-way wavefield continuation method. When compared with the previous work with a one-way downward-continuation method, this technique exhibits better capability of handling the steep structure, e.g. the salt flank. Numerical results on a complex model with a salt body demonstrate the effectiveness of this two-way method on resolving the overturned wave propagation introduced by the steep structures.

Attenuation in seismic wave propagation is a common cause for poor illumination of subsurface structures. Attempts to compensate for amplitude loss in seismic images by amplifying the wavefield may boost high-frequency components and create undesirable imaging artifacts. In this paper, rather than amplifying the wavefield directly, we develop a stable compensation operator using smooth division. The operator relies on a constant-Q wave equation with decoupled fractional Laplacians, and compensates for the full attenuation phenomena by performing wave extrapolation twice. This leads to two new imaging conditions to compensate for attenuation in reversetime migration (RTM). A time-dependent imaging condition is derived by applying Q-compensation at each time step, while a time-independent imaging condition is formed in the image space by calculating image normalization weights. Synthetic examples demonstrate an improved illumination of seismic images by applying the proposed method.

I present an application of Q-compensated reverse-time migration to the crosswell seismic field data from west Texas. A key feature of Q-RTM algorithm is the restoration of the high frequencies (in amplitude and phase) in the wavefield, thus resulting in an improved stack of source gathers. I found that the Q-compensated reverse-time migration imaging is able to provide an improved reflection image with many high-resolution details about geological layers and structures. For instance, the lateral and vertical extent and the internal features of the reservoir pay zone can be clearly determined in the Q-RTM image.

Delineating reservoir units is still a challenge for seismic studies. In this paper, we propose to use seismic crosswell inversion with a new boundary-preserving constraint for delineating the ambiguous geometry of a reservoir. The advantage of boundary-preserving constrained inversion is to preserve the geologic boundary of target reservoir. Firstly, we use synthetic examples to verify the methodology in comparison with those of conventional smoothly constrained inversion. Then we apply this boundary-preserving inversion method to field data. We found that the boundary preserving constraints improve image quality by preserving the expected boundaries top and base of reservoir.

Joint inversion of multiple geophysical data-sets is promising to reduce uncertainties in independently inverted models. Here, we present an iterative joint inversion approach for P and S traveltime data using crossgradient function as constraint term. This type of joint inversion scheme links independent inversions through iterations and the cross-gradient function. The primary advantage of this joint inversion strategy is to avoid determining relative weighting of different data-sets. To investigate the performance of this method, we test our algorithm in synthetic examples of P and S traveltime data and field data acquired in west Texas. The results of synthetic example show that the joint inversion significantly reduces the ambiguities of inverted models and improves the identification of boundaries. In results of field data, jointly inverted S velocities have better correlation with P velocities. Moreover, lithologies delineated from Vp/Vs map by joint inversion matches log data very well and also shows clearly a dipping structure below reservoir that was not shown in previous crosswell tomography results.