Search

Earthquake hypocentres are routinely obtained by a common inversion problem of P - and S -phase arrivals observed on a seismological network. Improving our understanding of the uncertainties associated with the hypocentral parameters is crucial for reliable seismological analysis, understanding of tectonic processes and seismic hazard assessment. However, current methods often overlook uncertainties in velocity models and variable trade-offs during inversion. Here, we propose to unravel the effects of the main sources of uncertainty in the location process using techniques derived from the Global Sensitivity Analysis (GSA) framework. These techniques provide a quantification of the effects of selected variables on the variance of the earthquake location using an iterative model that challenges the inversion scheme. Specifically, we consider the main and combined effects of (1) variable network geometry, (2) the presence of errors in the analyst's observations and (3) errors in velocity parameters from a 1-D velocity model. These multiple sources of uncertainty are described by a dozen of random variables in our model. Using a Monte Carlo sampling approach, we explore the model configurations and analyse the differences between the initial reference location and 100 000 resulting hypocentral locations. The GSA approach using Sobol's variance decomposition allows us to quantify the relative importance of our choice of variables. It highlights the critical importance of the velocity model approximation and provides a new objective and quantitative insight into understanding the sources of uncertainty in the inversion process. [ABSTRACT FROM AUTHOR]

Muography is a promising and rapidly developing physical prospecting technique based on the attenuation of muon flux. The feasibility and potential of applying muography to mining were presented in a small number of previous case studies. In this work, we aimed to address three challenges that limit the applicability and efficiency of muography in mineral exploration: (1) application to low-density-contrast ore body exploration, (2) analysis of altitudinal impacts on measurements and (3) precise and efficient reconstruction. We conducted the first case of applying muography to the exploration for low-density-contrast ore bodies. Six muon imaging systems were placed underground to collect surviving muons for roughly half a year. We analysed the altitudinal impact on the data measurements and proposed a simplified method to eliminate it. We also developed the seed algorithm, a novel 3-D reconstruction algorithm, that can reconstruct anomalies located far away from the detectors and avoid their elongation along the observed directions. Benefitting from the seed algorithm, a low-density-contrast ore body and a limonitic siliceous slate structure were reconstructed, demonstrating the sensitivity of this technique in density distinction; discoveries of several mined-out areas are important for accident avoidance; and reconstruction of the stope and scarps served as strong circumstantial evidence of the reliability of the result. The success of this experiment shows the great value of muography in the economic, research and safety aspects of mineral exploration and inspection. Moreover, the overcoming of challenges is helpful for the development of muography, making it an effective and competitive technique in this field. [ABSTRACT FROM AUTHOR]

This paper proposes the use of the parametric bootstrap as a simple way of obtaining reliable confidence intervals for the parameters in the space–time epidemic-type aftershock sequence (ETAS) model. Using an earthquake data catalogue spanning almost 20 yr of seismic activity in the Pacific Ocean off the shores of Vancouver Island (British Columbia, Canada), the authors show through simulation that the confidence intervals based on asymptotic maximum-likelihood theory can sometimes be misleading. In contrast, confidence intervals based on empirical quantiles from bootstrap samples have reliable nominal coverage, provided that edge effects are properly taken into account, both in the bootstrap procedure and in simulation studies. An R package called ETASbootstrap , developed by the authors, facilitates the use of this resampling procedure. [ABSTRACT FROM AUTHOR]

We present a method to calculate local spherical harmonic power spectra directly from spacecraft magnetic and gravity data with varying spacecraft altitude. Previously published applications of local spherical harmonic power spectra have been formulated for data that are available at a single collection altitude, such as data evaluated from a global spherical harmonic model. Our approach consists of first solving for local models from local data and then obtaining local multitaper spectra from the local models. We demonstrate with numerical tests that this approach can produce reliable results. Our method is particularly useful in situations where data coverage does not allow for calculating global magnetic or gravity field models, or where data quality or quantity varies regionally and where local models could yield superior resolution or quality over global models. [ABSTRACT FROM AUTHOR]

The Beni–Ilmane (BI) seismic sequence, situated in the north-central region of Algeria, began on 2010 May 14 with a main shock of M L 5.4 followed by two other shocks on May 16 and 23 of M L 5.3 for both. Using the complete data set from May 14 to August 31 and the Epidemic Type Aftershock Sequences (ETAS) model to separate background from aftershocks contribution gave a first insight around the uncertainty that surrounds the causes and mechanisms of the seismicity. According to our findings, two phases have been determined, the first one, beginning from May 14, shows low b - and p- values with most of the seismicity being self-triggered. In contrast, the second phase, beginning from May 23, demonstrates an increase of both the b- and p- values with a high number of background events. In the second phase, the background contribution involves 53 per cent of all seismic activity after May 23's peak which is high compared to typical main shock–aftershocks sequences. A possible explanation is that the main shocks began or assisted aseismic processes in addition to causing aftershocks. A sealed source at depth may have been broken by the third main shock, opening the way for the following incursion of highly pressurized fluids (hydrocarbures) confirmed by a high Vp / Vs ratios. [ABSTRACT FROM AUTHOR]

In this study, we develop a model that allows to combine gravimetric and geometric data. By the combination, we improve the spatial resolution of the resulting mass balance estimate compared to a purely gravimetric one. The equivalent ice or firn density of the changing ice volume is estimated within a mathematical inversion model, which includes geometric information about the volumetric change of the ice sheet and the resulting gravity change. This gravity change is computed from monthly GRACE gravity fields. They have a limited spatial resolution of a few 100 km, but allow direct conclusions about the true mass changes over Greenland. The ice-volume changes are described by a product by the Climate Change Initiative of European Space Agency, which is based on altimetry data. They have a very fine spatial resolution (down to a few km), but are not directly sensitive to mass changes. By combining both data sets in a common mathematical model, the advantages of both data types (direct sensitivity to mass versus high spatial resolution) are made use of. In this way, we improve the spatial resolution of mass balance estimates over Greenland. This leads to a map of mass trends, which has the same spatial resolution as the input map of geometric changes, but which is consistent with the input gravity fields. It will enable improving the localization of mass change signals of ice sheets and glaciers, which are usually rather small-scale. We compare our estimates to the results of complementary studies regarding the total mass loss of the Greenland ice sheet and its surrounding land surface. Our study leads to a value of |$-213\pm 37\, \text{Gt}\,\text{a}^{-1}$| in the time span from 2011 to 2015. We also discuss the problem of separating the mass contribution of the Greenland ice sheet itself and its surrounding region. [ABSTRACT FROM AUTHOR]

The precise estimation of the mass changes in Madagascar is a challenge by using the Gravity Recovery and Climate Experiment (GRACE) mission Level-2 products since they are contaminated by noise. Although this issue can be alleviated by the empirical destriping method or spatial filtering, they result in potential signal distortion or signal leakage. To improve this, we propose a reconstructive filter, whose parameters are optimized by the signal-to-noise ratio. Subsequently, our optimal filter corresponding to the best signal-to-noise ratio (5.63) is used to estimate the mass changes (2002–2017) in Madagascar. Eventually, our results are compared with two reliable GRACE mascon products and other independent observations. Correspondingly, here are our major conclusions: (1) Compared with groundwater storage from the mascon products, our estimates have the highest Pearson correlation (0.5) with in situ observation and can detect the rapid increase of groundwater storage during the rainy season. (2) The Fourier spectrum analysis detects a ∼3.8-yr periodic signal in the terrestrial water storage changes in Madagascar, which is contributed from the interannual precipitation driven by climate factor (Indian Ocean Dipole) and the aliasing error for imperfect GRACE pre-process. Our work introduces an effective filter for processing GRACE Level-2 data and presents novel insights into mass changes in Madagascar. [ABSTRACT FROM AUTHOR]

Instrumental earthquake monitoring in Greece started in 1899–1906 with the first five seismic stations of the National Observatory of Athens, Institute of Geodynamics (NOA). Subsequent upgrades and expansions led to today's Unified National Seismic Network, which includes almost all permanent seismic stations in Greece and provides waveform and parametric data. We examine the detection capabilities of the Greek seismic networks using phase, location and magnitude data from the International Seismological Centre (ISC) and the various National Institutes. We apply two methods to measure the network performance. In one, we form a grid, and find the 50 per cent probability detection threshold for each station-grid cell pair for different times. In the other, we find the probability-based magnitude of completeness grid for every three months from 1970 to 2014. Both methods show that in 1990 the detection threshold improved significantly in the north part of Greece. A much greater improvement took place in 2010 throughout Greece, yielding a completeness magnitude of |$M_p\, \sim$| 1. [ABSTRACT FROM AUTHOR]

Geophysical measurements are a sort of averaging a physical property over a volume of investigation (VOI). Within the VOI, the spatial elements closer to the detector contribute more to the measured value compared to farther elements. In this study, a VOI-oriented algorithm is proposed which establishes a relation between the localization probability, the sampling spacing and the size of the exploration target. Hence, the probability of localizing a target could be calculated as a function of sampling spacing when the target dimension is known. The novelty of this work is the use of VOI in the sampling optimization, which is important for geophysical survey design in environmental sampling and mineral exploration. Although the published sampling optimization methods are often variogram-oriented, the one presented here is based on the spatial variability of the measured property. Finally, coupling the VOI-oriented algorithm with a variogram model could be recommended in order to consider both the measurement mechanism and the spatial variability in the sampling design. [ABSTRACT FROM AUTHOR]

SUMMARY: This study derives the spatial variation of the elastic thickness (Te) and its implications for understanding the structure, geodynamic and seismicity of the lithosphere for the Zagros fold and thrust belt region of the Arabia–Eurasia collision zone. Te is calculated using the coherence function in the fan wavelet domain based on recent terrestrial Bouguer gravity and topography data as input signals. Utilizing the load deconvolution method and Brent's method of 1-D minimization, the final Te for the survey region is estimated for each grid node of the studied area. To illustrate the mass distribution in the studied area, the subsurface loading fraction (F) is calculated simultaneously with Te in the inversion. The crust thickness and density from three different global crustal models are tested and the results obtained for these input models do not yield substantially different Te patterns. The final results are in accord with the global Te models as well as previous rheological, geodynamical and flexural studies, however, this study establishes much more detailed regional information. The calculations yield a mean value of Te of 61 km for the Zagros, with a mean estimated error of about 5 km. The high-Te values (>70 km) are observed in the southeast of the studied area (some parts of the Sanandaj–Sirjan zone, Urumieh–Dokhtar magmatic arc and most of the Central Iranian blocks); while over most of the northwest of the studied area, the value of Te is about 58 km. The Te results are consistent with the lithospheric structure of the study area and also support the idea of the crust–mantle decoupling. Further, there is a positive and negative correlation between the surface wave velocity and surface heat flow, respectively. The mean value estimated for the internal loading friction (F) of 0.4 means in most of the studied areas we may consider that the surface loading is dominant, or at least the ratio of the surface and subsurface loading can be assumed equal. Based on earthquake distribution in the period 1900–2020, seismicity is more likely to occur in areas with a relatively low value of Te. [ABSTRACT FROM AUTHOR]

SUMMARY: We have modified a method for estimation of location errors distribution for local seismic networks in area with intense shallow seismicity. We have used the variance-covariance matrices in a regular grid of points. The traveltime residuals variance is calculated as a function of source–receiver distance, while the new idea is to estimate the detection range of seismic stations on the basis of the probability of detection plots. In consequence, the method enables the evaluation of the applied velocity models during the analysis of traveltime residuals, as well as evaluation of the usefulness of individual stations with the use of probability plots. Ultimately, it provides assessment of the station configuration by analysing the distribution of location errors. The data needed for the analysis are a seismic catalogue containing earthquakes locations together with traveltime residuals and the velocity model, as well as stations metadata. The method is tested on using the real data which come from the LUMINEOS local seismic network, the network used for induced seismicity monitoring in the Legnica–Głogow Copper District in Poland. [ABSTRACT FROM AUTHOR]

Reflector-normal angles and reflector-curvature parameters are the principal geometric attributes used in seismic interpretation for characterizing the orientations and shapes, respectively, of geological reflecting surfaces. Commonly, the input data set for their computation consists of fine 3-D grids of scalar fields representing either the seismic-driven reflectivities (e.g. amplitudes of 3-D seismic migrated volumes) or model-driven reflectivities, computed, for example, from the derived elastic impedance parameters. Conventionally, the computation of curvature parameters at each gridpoint is based on analysing the local change in the inline/crossline dips, considering the potential existence of a local quadratic reflecting surface in the vicinity of that point. This assumption breaks down for subsurface points in the vicinity of either complex reflecting surfaces (e.g. brittle/rough/tilted synclines/anticlines, ridges/troughs and saddles) and/or sharp, discontinuous geological features (e.g. fault edges/tips, pinch-outs, fracture systems, channels and small geobodies), where the values of the computed curvature become extremely high. However, while these high values can indicate the existence of non-reflecting objects, they do not deliver their specific geometric characteristics. In this study, we present a novel method that better characterizes the shapes of these complex geological features by extending the assumption of local surfaces (2-D surfaces in 3-D space) into local hypersurfaces (3-D hypersurfaces in 4-D space), with their corresponding (three rather than two) principal (and effective) curvature parameters. We demonstrate the advantages of our method by comparing the conventional dip-based surface curvature parameters with the hypersurface curvature parameters, using a synthetic model/image with different types and shapes of geological features and a seismic image of real data containing a complex fault and hidden buried channels. [ABSTRACT FROM AUTHOR]

Seismic attenuation has a considerable impact on resolution reduction and the increase in the dominant frequency period of seismic data. The absorption coefficient estimates, which measure inelastic attenuation, provide a deep understanding of the medium property changes in different geological settings. Conventional absorption coefficient estimation technologies always use time–frequency methods for seismic energy absorption analysis. However, despite continuing efforts to improve the absorption coefficient estimation, the limitation of the time–frequency methods still causes insufficient accuracy of the attenuation estimates, imposing major challenges in oil and gas hydrate exploration. In this study, a quantum mechanics-based seismic absorption coefficient estimation method was proposed for hydrocarbon detection. The seismic data were first projected on a specific basis constructed using the resolution of the Schrödinger equation. Seismic energy absorption analysis was then conducted in the potential-wave function domain. Finally, the quantum absorption coefficient estimates are given by the procedure after using a logarithmic operation and the least-squares fitting method. We examined the merits of these methods using model and field data. The gas reservoir was accurately targeted, which demonstrates that the proposed method has great potential for hydrocarbon detection. [ABSTRACT FROM AUTHOR]

Studies of controlled hydraulic stimulation experiments with active and passive seismic monitoring conducted in Underground Research Laboratories (URLs) benefit from specific knowledge of hydraulic parameters, close by microseismic monitoring revealing structural details of the rock mass, and detailed evolution of seismicity in response to injection operations. Microseismic monitoring is commonly used to characterize a stimulated reservoir volume, for example, in terms of damage evolution of the rock mass. Since seismic attenuation is affected by damage of the rock volume, active seismic sources covering sizes from the centimetre to decimetre scale may help us to investigate space–time varying attenuation properties in a reservoir. This may allow us to monitor damage evolution of the stimulated rock volume in more detail, also since active seismic sources produce stronger signals leading to a broader frequency range that can be analysed compared to passive seismic signals. Within the STIMTEC project in the URL Reiche Zeche (URL-RZ) in Freiberg (Germany), more than 300 active Ultrasonic Transmission (UT) measurements were performed before and after hydraulic stimulations in two boreholes in the targeted rock volume, an anisotropic metamorphic gneiss. The signal-frequency content ranges between 1 and 60 kHz. Assuming scattering attenuation to dominate over intrinsic attenuation, we here apply the single isotropic scattering model. S -coda waves of 88 spatially representative UT measurements are used to estimate the coda quality factor (Q C). We obtain stable Q C estimates for centre frequencies of octave-width frequency bands between 3 and 21 kHz. We group neighbouring UT measurements to stabilize the observations and form eight UT groups in total, covering different depth intervals in three boreholes and four different time periods to investigate scattering attenuation changes in a spatiotemporal manner. Our final mean Q C (⁠|$\overline {{Q}_C} $|⁠) estimates show characteristic frequency-dependence as observed at the field scale in geological reservoirs. We find temporal variations of Q C are strongly connected to hydraulic stimulation, and these variations are more significant than those resolved from velocity changes. |$\overline {{Q}_C} $| estimates at frequencies above 15 kHz indicate healing of injection-induced small-scale fractures during a two-months post-stimulation phase. Larger fractures, mostly sampled by lower frequencies (<15 kHz), seem to be more persistent with time (over 15 months). We observe spatial differences of |$\overline {{Q}_C} $| values near the mine galleries (driftway and vein drift) and relate these observations to different extents and characteristics of the galleries' excavation damage zones. Our results further support previous assumptions based on borehole televiewer logs and mapped structures of an existing fault with larger damage zone that crosses the stimulated rock volume NW-SE between the galleries. We conclude that the coda analysis of active UT measurements complements established imaging methods used during experiments in URLs. In particular, coda analysis is a powerful tool for the detection of damage zones and for monitoring local fracture networks with immediate application for imaging georeservoirs considered for exploitation or underground storage of gases and liquids. [ABSTRACT FROM AUTHOR]

Effective elastic thickness, |${T_\mathrm{ e}}$|⁠ , is a measure of the lithosphere's mechanical strength, and describes the flexural response of the lithosphere to applied loads in the same way as a thin elastic plate. In this study, a new method for estimating |${T_\mathrm{ e}}$| in the spatial domain is presented based on the Veining Meinesz regional isostatic theory. By comparing the absolute values of the correlation coefficients between the observed Moho flexure model and different Veining Meinesz Moho flexure models, the optimal |${T_\mathrm{ e}}$| is determined. Also, the estimated correlation coefficients can be used to examine the effect of the unknown subsurface loads, which are usually difficult to evaluate in the spatial domain. This method is verified to be capable of recovering |${T_\mathrm{ e}}$| variations through synthetic tests for the models with predefined |${T_\mathrm{ e}}$| variations. Finally, the effective elastic thickness is globally determined for the continents using the topography data and recent seismically-derived Moho model. These results are compared with two published |${T_\mathrm{ e}}$| models obtained with different methods. For the areas with relatively small Moho uncertainties and high correlation coefficients, the estimated |${T_\mathrm{ e}}$| variations generally agree with previous results. The differences between three |${T_\mathrm{ e}}$| estimates could characterize the advantages of different methods in specific cases. [ABSTRACT FROM AUTHOR]

The relationship between climate and the magnetic properties of surface soils on the Chinese Loess Plateau (CLP) have been widely used to provide the basis for palaeoclimatic reconstruction, based on the underlying loess/palaeosol sequences. To date, however, there are few investigations of variations in the magnetic properties of surface soils on the Tibetan Plateau (TP), especially on the southern TP. Therefore, it remains unclear whether magnetic properties could be used as proxies for palaeoclimatic reconstruction in the region. In this study, environmental magnetic parameters and bulk sediment grain-size measurements were made on a set of surface samples from the Yarlung Zangbo River Basin (YZRB), on the southern TP, and their environmental significance was evaluated. The results reveal spatial differences in the magnetic properties of the surface soils, likely caused by regional climatic factors. The input of primary magnetic minerals is the driver of the magnetic properties of the samples from the western (Gar-Saga) part of the YZRB, where the magnetic variations are controlled by the influence of wind intensity on the local source material. However, the samples from the eastern region (Gongga-Nyingchi) are significantly affected by the topographic and sedimentary conditions, and there is no relationship between the magnetic properties and climate. The samples from the central part of the study area (Saga-Gongga) show obvious signs of a pedogenic influence on magnetic properties and ultrafine superparamagnetic (SP) and single domain (SD) ferrimagnetic minerals dominate the magnetic susceptibility. Combined with the variation of grain size, this implies the influence of wind intensity and pedogenesis contribute to the magnetic enhancement. However, the pedogenic intensity closely related to precipitation and temperature could offer the possibility of using sedimentary magnetic properties for palaeoclimatic reconstruction. Furthermore, the existence of a distinct pedogenic alteration boundary in the Saga area is consistent with the location of the Indian summer monsoon, which may be the dominant control on the pedogenic intensity. [ABSTRACT FROM AUTHOR]

The behaviour of discontinuities in rock mass have been experimentally investigated extensively for decades by a type of laboratory analogue of flawed rock specimens, taking the artificially prepared flaw(s) as the analogue of rock mass discontinuity(ies). The role of macroscale flaw(s) as controlling structure has been generally neglected. Here, we conduct detailed characterizations of the acoustic emission (AE) from the rock fracture process on the pre-flawed specimens under loading. Though the same phenomena from the literature can be reproduced within our tests, detailed spatial-temporal investigation on the AE events at the nucleation point suggests a different physical interpretation. Artificial flaw(s) play a non-negligible role as a controlling structure for the following rock fracture process including a series of nucleation points alteration via stress transfer. The interlocking parallelogram (IP) control and single-large-structural (SLS) control are two fundamental mechanisms initiated by the artificial flaws. Each of these two mechanisms are observed under a wide range of flaw settings and can potentially coexist within the across length scales. The scale-invariance feature is observed to be fundamentally different within the scale of specimens under SLS and/or IP control, suggesting the incompleteness at the specimen-scale for IP control. Therefore, no 'fracture coalescence' zone can be separately investigated without considering its external rock fracture evolution and confirming scale-invariance. Therefore, structural controlling mechanisms must be considered due to the pattern and AE characterization results. [ABSTRACT FROM AUTHOR]

Summary: Bayesian inversion generates a posterior distribution of model parameters from an observation equation and prior information both weighted by hyperparameters. The prior is also introduced for the hyperparameters in fully Bayesian inversions and enables us to evaluate both the model parameters and hyperparameters probabilistically by the joint posterior. However, even in a linear inverse problem, it is unsolved how we should extract useful information on the model parameters from the joint posterior. This study presents a theoretical exploration into the appropriate dimensionality reduction of the joint posterior in the fully Bayesian inversion. We classify the ways of probability reduction into the following three categories focused on the marginalization of the joint posterior: (1) using the joint posterior without marginalization, (2) using the marginal posterior of the model parameters and (3) using the marginal posterior of the hyperparameters. First, we derive several analytical results that characterize these categories. One is a suite of semi-analytic representations of the probability maximization estimators for respective categories in the linear inverse problem. The mode estimators of categories (1) and (2) are found asymptotically identical for a large number of data and model parameters. We also prove the asymptotic distributions of categories (2) and (3) delta-functionally concentrate on their probability peaks, which predicts two distinct optimal estimates of the model parameters. Secondly, we conduct a synthetic test and find an appropriate reduction is realized by category (3), typified by Akaike's Bayesian information criterion. The other reduction categories are shown inappropriate for the case of many model parameters, where the probability concentration of the marginal posterior of the model parameters no longer implies the central limit theorem. The main cause of these results is that the joint posterior peaks sharply at an underfitted or overfitted solution as the number of model parameters increases. The exponential growth of the probability space in the model-parameter dimension makes almost-zero-probability events finitely contribute to the posterior mean and distributions of categories (1) and (2) be pathological. One remedy for this pathology is counting all model-parameter realizations by integrating the joint posterior over the model-parameter space of exponential multiplicity. Hence, the marginal posterior of the hyperparameters for categories (3) becomes appropriate and can conform to the law of large numbers even with numerous model parameters. The exponential rarity of the posterior mean and ABIC estimates implies the exponential time complexity of ordinary Monte Carlo methods in population mean and ABIC computations. We also present a geophysical application to estimate a continuous strain-rate field from spatially discrete global navigation satellite system data, demonstrating denser basis function expansions of the model-parameter field lead to oversmoothed estimates in naive fully Bayesian approaches, while detailed fields are resolved with convergence by the reduction of category (3). We often naively believe a good solution can be constructed from a finite number of samples with high probabilities, but the high-probability domain could be inappropriate, and exponentially many samples become necessary for generating appropriate estimates in the high-dimensional fully Bayesian posterior probability space. [ABSTRACT FROM AUTHOR]

Gravity Recovery and Climate Experiment (GRACE) Spherical Harmonics (SH) solutions are usually provided together with the corresponding formal errors, however, all multichannel singular spectrum analysis (MSSA) approaches neglect the formal errors of SH coefficients in processing the GRACE time-series. In this contribution, we propose a weighted MSSA to directly process the incomplete time-series of GRACE monthly gravity models by taking the formal errors into account. A 14-yr time-series of Release 06 (RL06) monthly gravity field models from the Center for Space Research (CSR) truncated to degree and order 60 for the period April 2002 to August 2016 is analysed by weighted MSSA, the results are compared with those from the improved MSSA that directly processes the incomplete time-series without considering the formal errors. The first 10 principal components derived by using the weighted MSSA can capture the variance in total up to 82.05 per cent, higher than 80.19 per cent by the improved MSSA. All the fitting errors of GRACE SH coefficients by the weighted MSSA are smaller than those by the improved MSSA, which indicates that weighted MSSA can extract more geophysical signals than the improved MSSA approach. To evaluate the efficiency of the weighted MSSA to eliminate noise, the ratios of the latitude weighted RMS of signals over lands and oceans are computed. Based on all the available months of GRACE solutions, the mean RMS ratio of signals over lands relative to oceans derived by the weighted MSSA is 5.04, higher than 4.96 by the improved MSSA. Therefore, we can conclude that the proposed weighted MSSA can suppress noise more efficiently and extract more geophysical signals from the GRACE time-series, which highlights the necessity of considering formal errors and the effectiveness of the weighted MSSA in post-processing the GRACE monthly gravity field models. [ABSTRACT FROM AUTHOR]

Modern geophysical data acquisition technology makes it possible to measure multiple geophysical properties with high spatial density over large areas with great efficiency. Instead of presenting these co-located multigeophysical data sets in separate maps, we take advantage of cluster analysis and its pattern exploration power to generate a cluster map with objectively integrated information. Each cluster in the resulting cluster map is characterized by multigeophysical properties and can be associated with certain geological attributes or rock types based on existing geological maps, field data and rock sample analysis. Such a cluster map is usually high in resolution and proven to be more helpful than single-attribute maps in terms of assisting geological mapping and interpretation. In this paper, we present the workflow and technical details of applying cluster analysis to multigeophysical data of a study area in the Trøndelag region in Mid-Norway. We address the importance of carefully designed pre-processing procedures regarding the input data sets to ensure an unbiased data integration using cluster analysis. Random forest as a supervised machine learning method for classification/regression is strategically employed post-clustering for quality evaluation of the results. The multigeophysical data used for this study include airborne magnetic, frequency electromagnetic and radiometric measurements, together with ground gravity measurements. Due to the nature of these input data, the resulting cluster map carries multidepth information. When associated with available geological information, the cluster map can help interpret not only bedrock outcrops but also rocks underneath the sediment cover. [ABSTRACT FROM AUTHOR]

Accurate models of the spatial structure of ionospheric magnetic fields in the diurnal variation (DV) band (periods of a few hours to a day) would enable use of magneto-variational methods for 3-D imaging of upper mantle and transition zone electrical conductivity. Constraints on conductivity at these depths, below what is typically possible with magnetotellurics, would in turn provide valuable constraints on mantle hydration and Earths deep water cycle. As a step towards this objective, we present here a novel approach to empirical modelling of global DV magnetic fields. First, we apply frequency domain (FD) principal components analysis (PCA) to ground-based geomagnetic data, to define the dominant spatial and temporal modes of source variability. Spatial modes are restricted to the available data sites, but corresponding temporal modes are effectively continuous in time. Secondly, we apply FD PCA to gridded surface magnetic fields derived from outputs of the physics-based Thermosphere–Ionosphere–Electrodynamics General Circulation Model (TIEGCM), to determine the dominant modes of spatial variability. The TIEGCM spatial modes are then used as basis functions, to fit (or interpolate) the sparsely sampled data spatial modes. Combining the two steps, we have a FD model of DV band global magnetic fields that is continuous in both space and time. We show that the FD model can easily be transformed back to the time domain (TD) to directly fit time-series data, allowing the use of satellite, as well as ground-based, data in the empirical modelling scheme. As an illustration of the methodology we construct global FD and TD models of DV band source fields for 1997–2018. So far, the model uses only ground-based data, from 127 geomagnetic observatories. We show that the model accurately reproduces surface magnetic fields in both active and quiet times, including those at sites not used for model construction. This empirical model, especially with future enhancements, will have many applications: improved imaging of electrical conductivity, ionospheric studies and improved external field corrections for core and crustal studies. [ABSTRACT FROM AUTHOR]

Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image. [ABSTRACT FROM AUTHOR]

Seismicity along subduction interfaces is usually dominated by large main-shock–aftershock sequences indicative of a continuum distribution of highly coupled large asperities. In the past decades, however, the increased resolution of seismic catalogues at some subduction zone seems to indicate instead a more complex rheological segmentation of the interface. Large and megathrust earthquake ruptures seem interspersed among regions of low seismic coupling and less stress buildup. In this weaker zone, the strain is primarily released via a combination of moderate-size swarm-like seismicity and aseismic slip. Along the Chilean subduction zone, the densification of the seismic network allowed for the identification of localized seismic clusters, some of them appearing in the form of swarms before megathrust earthquakes. The origin and driving processes of this seismic activity have not yet been identified. In this study, we follow a systematic approach to characterize the seismicity at two persistent clusters in Central Chile, one located offshore Navidad and one inland, at ∼40 km depth beneath Vichuquén, which occurred throughout ∼20 yr. We investigated these clusters, by deriving high-resolution hypocentral locations and moment tensors and performing a detailed analysis of spatio-temporal patterns, magnitude and interevent time distributions of the clustered earthquakes. Both clusters are characterized by weak to moderate seismicity (below M w 6) and stand out as clear seismicity rate and Benioff strain anomalies. At the Navidad cluster, seismicity occurs in the form of swarms, with a characteristic duration of 2–7 d and location and thrust mechanisms compatible with activity on the slab interface. Conversely, we find at Vichuquén activity dominated by thrust earthquakes occurring as repeaters on the slab interface, with a slip rate of approximately ∼5.0 cm yr−1. We attribute these clusters to local features of the subducting plate: the Navidad swarms are likely driven by repeated high pore pressure transients along a pre-fractured patch of the slab, while the seismicity at the Vichuquén cluster is interpreted as the result of a subducting seamount. Both clusters have been active before and after the M w 8.8 Maule earthquake and persisted afterwards with the seismicity decay following the Omori law. These interactions are especially evident for the Vichuquén cluster, where the seismicity rate increased considerably after the Maule earthquake and continues to be an area of clearly elevated seismicity rate compared to its surroundings. [ABSTRACT FROM AUTHOR]

We present new regional models, denoted CLAS, of the Chinese lithospheric field, combining the long-wavelength information provided by satellite-derived models: CHAOS-6, MF7, LCS-1 and NGDC720, and an extremely high-quality compilation of 97 994 aeromagnetic survey data with 10 km × 10 km resolution for shorter wavelength. The models are estimated using a depleted basis of global spherical harmonic functions centred on China. CLAS models are determined include harmonic degrees up to 400. Although some accuracy of aeromagnetic data is lost in order to balance the consistent of two data sets, the results show that CLAS models have a high correlation with the satellite models at low-degree terms (degree correlation > 0.9) but with more power at high-degree terms, reflecting more features of the lithospheric field in continental China. Examples of improvement include Changbai mountains, Sichuan Basin and Qinghai–Tibet Plateau. CLAS models have good agreement (coherence > 0.9) with Chinese aeromagnetic data at wavelength down to about 100 km (corresponding to spherical harmonic degree n  = 400), filling the usual gap between satellite models and aeromagnetic data. Comparison with aeromagnetic data filtered at 100 km gives good agreement (correlation > 0.95). The residuals between CLAS models and aeromagnetic data are still large (rms > 70 nT), but with most of misfits arising from shorter wavelength fields that the model cannot fit at degree up to 400; such misfit could be reduced by increasing the model degree. We provide a geological example of how the inclusion of satellite data can change the geological conclusions that can be drawn from the magnetic information. However, the two data sets are not completely consistent, future models should start from a reanalysis of the aeromagnetic data and its line levelling to ensure consistency with the satellite model. [ABSTRACT FROM AUTHOR]

Earthquake ruptures are generally considered to be cracks that propagate as fracture or frictional slip on pre-existing faults. Crack models have been used to describe the spatial distribution of fault offset and the associated static stress changes along a fault, and have implications for friction evolution and the underlying physics of rupture processes. However, field measurements that could help refine idealized crack models are rare. Here, we describe large-scale laboratory earthquake experiments, where all rupture processes were contained within a 3-m long saw-cut granite fault, and we propose an analytical crack model that fits our measurements. Similar to natural earthquakes, laboratory measurements show coseismic slip that gradually tapers near the rupture tips. Measured stress changes show roughly constant stress drop in the centre of the ruptured region, a maximum stress increase near the rupture tips and a smooth transition in between, in a region we describe as the earthquake arrest zone. The proposed model generalizes the widely used elliptical crack model by adding gradually tapered slip at the ends of the rupture. Different from the cohesive zone described by fracture mechanics, we propose that the transition in stress changes and the corresponding linear taper observed in the earthquake arrest zone are the result of rupture termination conditions primarily controlled by the initial stress distribution. It is the heterogeneous initial stress distribution that controls the arrest of laboratory earthquakes, and the features of static stress changes. We also performed dynamic rupture simulations that confirm how arrest conditions can affect slip taper and static stress changes. If applicable to larger natural earthquakes, this distinction between an earthquake arrest zone (that depends on stress conditions) and a cohesive zone (that depends primarily on strength evolution) has important implications for how seismic observations of earthquake fracture energy should be interpreted. [ABSTRACT FROM AUTHOR]

Relative location of microearthquakes that occurred at Mt Pollino (Italy) from 2011 to 2013 have been analyzed with the aim of a detailed imaging of the geometry of active faults. We identified 27 clusters composed of a number of earthquakes from 9 to 33, with local magnitude in the range 0.6–2.7. The relative location shows that the distribution of hypocentres in each cluster is characterized by extension from few tens of meters to at most 350 m. For each cluster the hypocentre distribution was fitted by a plane to infer the fault orientation, and results were compared with the fault plane solutions corresponding to the focal mechanism of earthquakes of the same cluster. The comparison shows a good agreement in most of the cases. The relative location analysis, generally applied to earthquakes with similar waveform, has been improved to permit also the relative location of earthquakes characterized by not similar signals. To achieve this purpose a modified procedure that overcome the condition of very similar waveforms has been applied to estimate the time delay between first pulses of the master events. The relative location of master events of all clusters shows a precise imaging of the relative position of all analysed sources and allows also to follow with high accuracy the evolution in time of the seismic swarm within the selected periods. The hypocentre position of master events and the nearly parallel fitting planes of any clusters suggest that most of the analyzed earthquakes were produced by different patches of the same fault. The final results depict a main fault plane characterized by NW–SE strike, dip of about 35–45° and depth between 4.5 and 6.5 km b.s.l. Focal mechanisms, used also to evaluate the local stress field, are mostly of normal type with few strike slip solutions for the shallowest events. This result is in good agreement with the local tectonic stress regime that is characterized by predominant NE–SW transtension, as inferred from structural, seismological and geophysical data. [ABSTRACT FROM AUTHOR]

Multichannel singular spectrum analysis (MSSA) is a powerful tool to extract spatiotemporal signals and filter errors from the noisy time-series of monthly gravity field models from the satellite data of gravity recovery and climate experiment (GRACE). Since the GRACE monthly gravity models are missed about 17 months, we develop an improved MSSA approach, which can directly process the incomplete time-series without either data interpolation or iteration. The time-series of 14-yr (2002.04–2016.08) monthly gravity field models of CSR-RL06 up to degree and order 60 are analysed with improved MSSA compared to the MSSA with linear data interpolation and iteration MSSA. By using our improved MSSA approach, the first 11 principal components derived can capture 91.18 per cent of the total variance, higher than 85.80 and 86.44 per cent of the total variance, derived by linear interpolation MSSA and iteration MSSA, respectively. The ratios of the latitude weighted RMS over the land and ocean signals are used to evaluate the efficiency of eliminating noise by the MSSA approach. For improved MSSA, the mean RMS ratio of land and ocean signals of all available months is higher than linear interpolation and iteration MSSA, which indicates that improved MSSA can suppress noise more efficiently and extract more geophysical signals from real GRACE data. Furthermore, the 50 repeated experiments show that all the root mean squared errors and mean absolute errors derived by our improved MSSA are smaller than other MSSA approaches. Moreover, the improved MSSA performs still better than other MSSA based approaches for the cases of large data gaps. [ABSTRACT FROM AUTHOR]

Considering spatial correlation of multiple earthquake intensity measures (IMs) is of particular importance in loss assessment of spatially distributed assets. This subject has been investigated in previous studies under the assumption of isotropy. Considering the fact that the assumption of isotropy is not valid in general, the present study employs a non-separable covariance model based on latent dimensions method to investigate anisotropic properties of spatial correlations and cross-correlations of intra-event residuals of multiple earthquake IMs. This method leads to the generation of valid covariance matrix in order to model anisotropic spatially distributed multivariate random fields. Two sets of IMs are considered in this study; the first set consists of peak ground intensity values (acceleration, velocity, and displacement), and the second set consists of spectral accelerations at three different periods. Data of 10 earthquake events in California and Japan are utilized in this study to estimate parameters of marginal and cross-covariance models. Moreover, parameters of covariance model of regional site condition, which is considered as average shear wave velocity of top 30 m of soil profile (Vs30), are obtained in order to investigate the effect of local sited conditions on spatial correlations of IMs. It is shown that maximum range and anisotropy ratio of covariance models of intra-event residuals of IMs are correlated with those of Vs30 values. Also, it is observed that the anisotropy direction of residuals of IMs is consistent with anisotropy direction of Vs30 values. Finally, predictive models are proposed to obtain marginal and cross-covariance functions for different earthquake IMs considering anisotropy. [ABSTRACT FROM AUTHOR]

Understanding fracturing processes and the hydromechanical relation to induced seismicity is a key question for enhanced geothermal systems (EGS). Commonly massive fluid injection, predominately causing hydroshearing, are used in large-scale EGS but also hydraulic fracturing approaches were discussed. To evaluate the applicability of hydraulic fracturing techniques in EGS, six in situ , multistage hydraulic fracturing experiments with three different injection schemes were performed under controlled conditions in crystalline rock at the Äspö Hard Rock Laboratory (Sweden). During the experiments the near-field ground motion was continuously recorded by 11 piezoelectric borehole sensors with a sampling rate of 1 MHz. The sensor network covered a volume of 30×30×30 m around a horizontal, 28-m-long injection borehole at a depth of 410 m. To extract and characterize massive, induced, high-frequency acoustic emission (AE) activity from continuous recordings, a semi-automated workflow was developed relying on full waveform based detection, classification and location procedures. The approach extended the AE catalogue from 196 triggered events in previous studies to more than 19 600 located AEs. The enhanced catalogue, for the first time, allows a detailed analysis of induced seismicity during single hydraulic fracturing experiments, including the individual fracturing stages and the comparison between injection schemes. Beside the detailed study of the spatio-temporal patterns, event clusters and the growth of seismic clouds, we estimate relative magnitudes and b -values of AEs for conventional, cyclic progressive and dynamic pulse injection schemes, the latter two being fatigue hydraulic fracturing techniques. While the conventional fracturing leads to AE patterns clustered in planar regions, indicating the generation of a single main fracture plane, the cyclic progressive injection scheme results in a more diffuse, cloud-like AE distribution, indicating the activation of a more complex fracture network. For a given amount of hydraulic energy (pressure multiplied by injected volume) pumped into the system, the cyclic progressive scheme is characterized by a lower rate of seismicity, lower maximum magnitudes and significantly larger b -values, implying an increased number of small events relative to the large ones. To our knowledge, this is the first direct comparison of high resolution seismicity in a mine-scale experiment induced by different hydraulic fracturing schemes. [ABSTRACT FROM AUTHOR]

Demarcating the continental–oceanic boundary (COB) is extremely important as it contributes to an understanding of the tectonic environments of marginal basins through plate reconstructions. In general, the COB is estimated by jointly interpreting the features of the basement geomorphology, bathymetry and geophysical datasets, including gravity, magnetic, seismic and geochemical data. We propose a novel methodology named the tilt-theta angles correlation (TTAC), a second-order filtering approach to estimate the COB using high-resolution satellite gravity data. This method computes the angular difference or correlation angle between the vectors computed from the gradients of the tilt and theta derivative-based first-order filters. Oceanic regions generally exhibit small correlation angles (∼0°), thereby indicating a direct correlation; in contrast, continental regions depict large correlation angles (∼180°) and thus display an inverse correlation. The TTAC method marks the COB at the spatial position where the correlation angles abruptly shift from inverse to direct. Tests using synthetic data and the larger spectral energy content of TTAC for long wavelengths over tilt, theta and minus of the sign of vertical derivative (-SiVD) filters attest the effectiveness of the new methodology over first-order derivative based filters. Additionally, tests utilizing real data over both the West African Transform Margin (WATM) and across the South Atlantic Conjugate Margin (SACM) provide favourable results compared with the previous methodologies used to demarcate the COB. The COB estimates derived using the new methodology are consistent with the COB estimates obtained during recent plate-reconstruction studies. We also compare our results with an earlier interpretation along a conjugate margin encompassing magma-poor and magma-rich regions. In the complex rifted environments of the SACM, in which volcanic rocks are dominant, the TTAC methodology substantially improves the previous COB estimates, thereby establishing it as an efficient edge marker by simultaneously reducing small-scale geological noise and enhancing regional-scale geological contributions. [ABSTRACT FROM AUTHOR]

We present a new Moho depth model of the British Isles and surrounding areas from the most up-to-date compilation of Moho depth estimates obtained from refraction, reflection and receiver function data. We use a probabilistic, trans-dimensional and hierarchical approach for the surface reconstruction of Moho topography. This fully data-driven approach allows for adaptive parametrization, assessment of relative importance between different data-types and uncertainties quantification on the reconstructed surface. Our results confirm the first order features of the Moho topography obtained in previous work such as deeper Moho (29–36 km) in continental areas (e.g. Ireland and Great Britain) and shallower Moho (12–22 km) offshore (e.g. in the Atlantic Ocean, west of Ireland). Resolution is improved by including recent available data, especially around the Porcupine Basin, onshore Ireland and Great Britain. NE trending features in Moho topography are highlighted above the Rockall High (about 28 km) and the Rockall Trough (with a NE directed deepening from 12 to about 20 km). A perpendicular SE oriented feature (Moho depth 26–28 km) is located between the Orkney and the Shetland, extending further SW in the North Sea. Onshore, our results highlight the crustal thinning towards the N in Ireland and an E–W oriented transition between deep (34 km) and shallow (about 28 km) Moho in Scotland. Our probabilistic results are compared with previous models showing overall differences around ±2 km, within the posterior uncertainties calculated with our approach. Bigger differences are located where different data are used between models or in less constrained areas where posterior uncertainties are high. [ABSTRACT FROM AUTHOR]

The METAFORET experiment was designed to demonstrate that complex wave physics phenomena classically observed at the meso- and microscales in acoustics and in optics also apply at the geophysics scale. In particular, the experiment shows that a dense forest of trees can behave as a locally resonant metamaterial for seismic surface waves. The dense arrangement of trees anchored into the ground creates anomalous dispersion curves for surface waves, which highlight a large frequency band-gap around one resonant frequency of the trees, at ∼45 Hz. This demonstration is carried out through the deployment of a dense seismic array of ∼1000 autonomous geophones providing seismic recordings under vibrating source excitation at the transition between an open field and a forest. Additional geophysical equipment was deployed (e.g. ground-penetrating radar, velocimeters on trees) to provide essential complementary measurements. Insights and interpretations on the observed seismic wavefield, including the attenuation length, the intensity ratio between the field and the forest and the surface wave polarization, are validated with 2-D numerical simulations of trees over a layered half-space. [ABSTRACT FROM AUTHOR]

We present new transfer functions (TFs) that can handle external electromagnetic (EM) sources of complex geometry. These TFs relate global expansion coefficients describing the source with a locally measured EM field. In this study, the new TFs concept was applied to the daily magnetic variations measured at the ground. The parametrization of the source in terms of spherical harmonics was adopted. We used nearly 20 yr of data from 125 mid-latitude observatories and explored how the results are affected by (i) solar activity conditions, (ii) the choice of the prior conductivity model used for the source coefficient estimation and (iii) the presence of ocean tidal magnetic signals. We found that choosing magnetically quiet periods is beneficial due to simpler source morphology, and the choice of prior conductivity model may significantly affect the source coefficients and TFs at short periods. We further observed significant contributions by ocean tidal magnetic signals at coastal and island observatories and corrected for them. Finally, the estimated TFs were inverted for the mantle conductivity at several locations representing different geological settings. [ABSTRACT FROM AUTHOR]

Thickness of cover over crystalline basement is an important consideration for mineral exploration in covered regions. It can be estimated from a variety of geophysical data types using a variety of inference methods. A robust method for combining such estimates to map the cover–basement interface over a region of interest is needed. Due to the large uncertainties involved, these need to be probabilistic maps. Predominantly, interpolation methods are used for this purpose, but these are built on simplifying assumptions about the inputs which are often inappropriate. The Bayesian estimate fusion is an alternative capable of addressing that issue by enabling more extensive use of domain knowledge about all inputs. This study is intended as a first step towards making the Bayesian estimate fusion a practical tool for cover thickness uncertainty mapping. The main contribution is to identify the types of data assumptions that are important for this problem, to demonstrate their importance using synthetic tests and to design a method that enables their use without introducing excessive tedium. We argue that interpolation methods like kriging often cannot achieve this goal and demonstrate that Markov chain Monte Carlo sampling can. This paper focuses on the development of statistical methodology and presents synthetic data tests designed to reflect realistic exploration scenarios on an abstract level. Intended application is for the early stages of exploration where some geophysical data are available while drill hole coverage is poor. [ABSTRACT FROM AUTHOR]

Measurements of seismo-acoustic events by collocated seismic and infrasound arrays allow for studying the two wavefields that were produced by the same event. However, some of the scientific and technical constraints on the building of the two technologies are different and may be contradicting. For the case of a new station, an optimal design that will satisfy the constraints of the two technologies can be found. However, in the case of upgrading an existing array by adding the complementing technology, the situation is different. The site location, the array configuration and physical constraints are fixed and may not be optimal for the complementing technology, which may lead to rejection of the upgrade. The International Monitoring System (IMS) for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) includes 37 seismic arrays and 51 infrasound arrays. Although the CTBT verification regime is fixed in the treaty, an upgrade of the existing arrays by adding more technologies is possible. The Mount Meron seismic array (MMAI), which is part of the IMS, is composed of 16 sites. Microbarometers were installed at five MMAI sites to form the Mount Meron infrasound array. Due to regulation and physical constraints, it was not possible to relocate the sites nor to install analogue noise reduction filters (i.e. a pipe array). In this study, it is demonstrated that the installation of the MMAI infrasound array is beneficial despite the non-optimal conditions. It is shown that the noise levels of the individual array sites are between the high and median global noise levels. However, we claim that the more indicative measures are the noise levels of the beams of interest, as demonstrated by analysing the microbaroms originated from the Mediterranean Sea. Moreover, the ability to detect events relevant to the CTBT is demonstrated by analysing man-made events during 2011 from the Libya region. [ABSTRACT FROM AUTHOR]

We propose a new method to test the performance of a spatial point process forecast based on a log-likelihood score for predicted point density and the information gain for events that actually occurred in the test period. The method largely avoids simulation use and allows us to calculate the information score for each event or set of events as well as the standard error of each forecast. As the number of predicted events increases, the score distribution approaches the Gaussian law. The degree of its similarity to the Gaussian distribution can be measured by the computed coefficients of skewness and kurtosis. To display the forecasted point density and the point events, we use an event concentration diagram or a variant of the Error Diagram (ED). We find forward relation between the error diagram curve and the information score as well as inverse relation for one simple model of point spatial fields. We again show that the error diagram is more informative than the likelihood ratio.We demonstrate the application of the method by using our long-term forecast of seismicity in two western Pacific regions. We compare the ED for these regions with simplified diagrams based on two-segment approximations. Since the earthquakes in these regions are concentrated in narrow subduction belts, using the forecast density as a template or baseline for the ED is a more convenient display technique. We also show, using simulated event occurrence, that some proposed criteria for measuring forecast effectiveness at EDs would be strongly biased for a small event number.

Spatial wavefield gradient data can be estimated from dense receiver arrays using a finite-difference approximation. Array-derived spatial wavefield gradient data to estimate, for example, strain and rotation components of the wavefield usually suffer from receiver perturbations, such as varying sensor coupling and/or differences in the instrument channel responses. We present a novel methodology to compute spatial seismic wavefield gradient data in the presence of receiver specific perturbation effects. We simultaneously invert the seismic wavefield recorded with an array consisting of closely spaced sensors for the spatial wavefield derivatives and station specific frequency-dependent calibration filters that remove the local receiver perturbations. Using synthetic and field data, we demonstrate that our scheme has the potential to significantly improve gradient estimation results for arrays with a low number of stations suitable, for instance, for land seismic exploration. The extracted calibration filters do not only correct for receiver perturbations but also partly compensate for the truncation error of the Taylor series expansion about the central (master) station of the array. The application of the calibration filters results in gradient estimates that are more accurate compared to conventional approaches. Multiple source recordings are used for reducing the trade-off between the extracted receiver perturbation filters and the spatial wavefield derivatives in the proposed inversion scheme. [ABSTRACT FROM AUTHOR]

We consider the case where the 'solution' to an inverse problem is an ensemble (e.g. drawn from the conditional probability density function |$p({{{\bf m}}|{{{\bf d}}^{obs}}})$| of M model parameters |${{\bf m}}$| given observed data |${{{\bf d}}^{obs}}$|⁠). Here we presume that the |${{\bf m}}$| s have a natural ordering, say in position x , so that 'resolution' means the ability of the inverse problem to distinguish physically adjacent model parameters. The trade-off curve for resolution and variance is constructed using the following steps: (1) the single solution |${{{\bf m}}^{est}}$| and its covariance |${{{\bf C}}_m}$| are estimated as the ensemble mean and covariance; (2) the eigenvalue decomposition |${{{\bf C}}_m} = {\rm{\ }}{{{\bf V} {\boldsymbol \Lambda} }}{{{\bf V}}^{\rm{T}}}$| is computed and the submatrix |${{{\boldsymbol \Lambda }}^{(N)}}$| of the N smallest eigenvalues, and submatrix |${{{\bf V}}^{(N)}}$| of the N corresponding eigenvectors, are formed; (3) the equation |${{{\boldsymbol \mu }}^{(N)}} = {{{\boldsymbol \Phi }}^{(N)}}\ {{\bf m}}$| with |${{{\boldsymbol \mu }}^{(N)}} = [ {{{{\bf V}}^{(N)}}} ]{\boldsymbol{\ }}{{{\bf m}}^{est}}$| and |${{{\boldsymbol \Phi }}^{(N)}} = {[ {{{{\bf V}}^{(N)}}} ]^{\rm{T}}}$| is formed, as is its covariance |${{\bf C}}_\mu ^{(N)} = {{{\boldsymbol \Lambda }}^{(N)}}{\boldsymbol{\ }}$|⁠ ; (4) the equation is solved to yield a localized average |${\langle {{\bf m}} \rangle ^{(N)}} = \ {{{\boldsymbol \Phi }}^{ - g}}{{{\boldsymbol \mu }}^{(N)}}$|⁠ , where |${{{\boldsymbol \Phi }}^{ - g}}$| is either the minimum length or Backus–Gilbert generalized inverse of |${{\boldsymbol \Phi }}$|⁠ ; (5) the resolution and covariance are computed as |${{{\bf R}}^{(N)}} = {{{\boldsymbol \Phi }}^{ - g}}{\boldsymbol{\ }}{{{\boldsymbol \Phi }}^{(N)}}$| and |${{\bf C}}_m^{(N)} = {{{\boldsymbol \Phi }}^{ - g}}{\boldsymbol{\ }}{{\bf C}}_\mu ^{(N)}{({{{{\boldsymbol \Phi }}^{ - g}}})^{\rm{T}}}$|⁠ ; (6) the spread |${K^{(N)}}$| of resolution and size |${J^{(N)}}\ $| of covariance are computed using either the Dirichlet or Backus–Gilbert measures and (7) the process is repeated for |$1 \le N \le M$| to build up the trade-off curve |$K(J)$|⁠. We show that, in the Dirichlet case, |${K^{(N)}} = \ M - N$| and |${J^{(N)}} = \ {\rm{tr}}({{{{\boldsymbol \Lambda }}^{(N)}}})$|⁠. We also consider the case where the model parameters correspond to spline coefficients and a sequence |${y_i}({{{\bf m}},{x_i}})$| derived from these coefficients possesses natural ordering. Layered models are an example of such a parametrization. We construct the trade-off curve for |${{\bf y}}$| by converting each member of the ensemble from |${{\bf m}}$| to |${{\bf y}}$| and applying the above procedure to them. We demonstrate the method by applying it to several simple examples. [ABSTRACT FROM AUTHOR]

Deterministic geophysical inversion approaches yield tomographic images with strong imprints of the regularization terms required to solve otherwise ill-posed inverse problems. While such tomograms enable an adequate assessment of the larger-scale features of the probed subsurface, the finer-scale details tend to be unresolved. Yet, representing these fine-scale structural details is generally desirable and for some applications even mandatory. To address this problem, we have developed a two-step methodology based on area-to-point kriging to generate fine-scale multi-Gaussian realizations from smooth tomographic images. Specifically, we use a co-kriging system in which the smooth, low-resolution tomogram is related to the fine-scale heterogeneity through a linear mapping operation. This mapping is based on the model resolution and the posterior covariance matrices computed using a linearization around the final tomographic model. This, in turn, allows us for analytical computations of covariance and cross-covariance models. The methodology is tested on a heterogeneous synthetic 2-D distribution of electrical conductivity that is probed with a surface-based electrical resistivity tomography (ERT) survey. The results demonstrate the ability of this technique to reproduce a known geostatistical model characterizing the fine-scale structure, while simultaneously preserving the large-scale structures identified by the smoothness-constrained tomographic inversion. Small discrepancies between the geophysical forward responses of the realizations and the reference synthetic data are attributed to the underlying linearization. Overall, the method provides an effective and fast alternative to more comprehensive, but computationally more expensive approaches, such as, for example, Markov chain Monte Carlo techniques. Moreover, the proposed method can be used to generate fine-scale multivariate Gaussian realizations from virtually any smoothness-constrained inversion results given the corresponding resolution and posterior covariance matrices. [ABSTRACT FROM AUTHOR]

In northern Europe, radiogenic heat production of surface rocks has been extensively studied in Finland and Norway alike. This paper presents a heat production analysis of Sweden, based on a rock outcrop data compilation obtained from the Geological Survey of Sweden (SGU). The study area comprises Precambrian Shield, Caledonian and platform cover areas. Altogether 39 933 samples with uranium, thorium and potassium concentration (CU, CTh and CK) and density (ρ) data were available. Heat production (HP) was calculated using raw point data, binning on a regular grid, and averaging by bedrock units in the geological map. Methods based on raw point data and grid-based binning resulted in HP values of 2.5 ± 4.1 and 2.5 ± 5.6 μW m–3, respectively, while averaging by lithology produced a lower value of 2.4 ± 1.7 μW m–3. Limiting the lithology-based averaging to Precambrian bedrockareas resulted in heat production of 2.4 ± 1.6 μW m–3. Due to the small geographic extent of area covered by sediments, this is similar to the Precambrian-only value. Regardless of the calculation method, heat production in Sweden is considerably higher than the corresponding value for Finland. The Swedish platform cover had apparently the lowestheat production (1.0 ± 1.8 μW m–3) of all units but the presence of Precambrian rocks below the sediments means that this value strongly misleads if used to represent the entire upper crust. Svecokarelian (Svecofennian) and Sveconorwegian rocks, which comprised 94.0 per cent of all individual observations, had heat production values of 2.6 ± 1.8 and 1.7 ± 1.4 µW m–3, respectively. Although the Swedish data still have large spatial gaps when compared to Finnish data, most bedrock units in Sweden are covered. It is obvious that the higher heat flow of Sweden compared to that of Finland is caused by near-surface (i.e. upper crustal) heat production, and crustal differentiation in Sweden is also larger. [ABSTRACT FROM AUTHOR]

Continuous long-term sound sources are recorded at hydroacoustic station H03S, a three-element hydrophone array south of Robinson Crusoe Island between 2014 April 23 and 2017 August 20. The origin of the signal between 3 and 20 Hz is investigated by using cross-correlation, array processing using plane wave beamforming and spectral analysis. One-bit normalization is successfully applied as a cross-correlation pre-processing step in order to suppress undesired earthquake events in the data. Traveltimes retrieved from averaged cross-correlations do not yield a coherent array direction of arrival. Averaged envelopes of the cross-correlations, however, indicate a coherent signal approaching H03S from a south–southwest direction. Beamforming indicates two dominant backazimuth directions: 172°–224° (Antarctica) and 242° (Monowai Volcanic Seamount). This continuous source field creates possibilities to investigate the applicability of acoustic thermometry at hydrophones H03 S1–S2. Cross-correlation and array processing indicate significant directional variation in local propagation, most likely related to the steep slope in the bathymetry near H03S. In addition, it is demonstrated that the ambient noise field is not sufficiently equipartitioned. It is shown that this causes a large error in the estimated temperature, primarily due to the short receiver spacing. These large errors have not been addressed in previous studies on deep-ocean acoustic thermometry. Hence, it is shown that acoustic thermometry does not perform well on small arrays such as H03S. The power spectral density yields a strong broadband signal in January–March, most likely related to iceberg noise. A narrow banded signal around 17 Hz between April and September corresponds to whale calls. The best-beam sound pressure levels towards Antarctica are compared to ERA5 climatologies for sea ice cover and normalized stress into the ocean, supporting the hypothesis of iceberg noise. [ABSTRACT FROM AUTHOR]

The application of the singular value decomposition method (SVD) for filtering of seismic data has become common in recent decades, as it promotes significant improvements of the signal-to-noise ratio, highlighting reflections in seismograms. One particular way to apply SVD in a single (or multivariate) time-series is the singular spectrum analysis (SSA) method, normally applied on constant-frequency slices in one or many spatial dimensions. We demonstrate that SSA method applied in the time domain corresponds to filtering the time-series with a symmetric zero-phase filters, which are the autocorrelations of the eigenvectors of the data covariance matrix, preserving the phase of the original data. In this paper, we explore the SSA method in the time domain, and we propose a new recursive-iterative SSA (RI-SSA) algorithm, which uses only the first eigenvector of the data covariance matrix to decompose a discrete time-series into signal components. From the analytic signal of each component we compute a time–frequency representation. By interpretation of the time signals and their time–frequency representations, groups with similar features are summed to produce a smaller number of signal components. The resulting RI-SSA signal decomposition is exact and phase-preserving, but non-unique. Applications to land seismic data for ground-roll removal and to two synthetic signals for time–frequency analysis give good results. [ABSTRACT FROM AUTHOR]

In the Sea of Marmara, areas of gas seepage or cold seeps are tightly related to the faults system and understanding the spatial and temporal dynamics in gas-related processes is crucial for geohazard mitigation. Although acoustic surveys proved to be efficient in detecting and locating cold seeps, temporal variability or trends in the gas-related processes are still poorly understood. Two arrays of 10 ocean bottom seismometers were deployed in the western part of the Sea of Marmara in 2011 and 2014, respectively. In addition to the local seismic events, the instruments recorded a large number of short duration events and long-lasting tremors. Short duration events are impulsive signals with duration <1 s, amplitude well above the noise level and a frequency spectrum with one or two narrow peaks. They are not correlated from one site to another, suggesting a very local source. Tremors consist of sequences of clustered impulsive signals lasting for minutes to more than an hour with a multipeak frequency spectrum. Based on evidence of known seepage and by analogy with volcanic and hydrothermal models, we suggest that short duration events and tremors are associated with gas migration and seepage. There is a relationship between tremors associated with gas emission and the local seismicity, although not systematic. Rather than triggering gas migration out of the seabed, locally strong earthquakes act as catalysts when gas is already present or gas emission is already initiated. [ABSTRACT FROM AUTHOR]

The most common earthquake forecasting models assume that the magnitude of the next earthquake is independent from the past. This feature severely limits the capability to forecast large earthquakes with high probabilities. Here we investigate empirically on the magnitude-independence assumption, exploring if: (i) background and triggered earthquakes have the same frequency–magnitude distribution, (ii) variations of seismicity in the space–time–magnitude domain encode some information on the future earthquakes size. For this purpose, and to verify the stability of the findings, we consider seismic catalogues covering different space–time–magnitude windows, such as the Alto Tiberina Near Fault Observatory (TABOO), the California and Japanese seismic catalogues. Our approach is inspired by the nearest-neighbour method proposed by Baiesi & Paczuski and elaborated by Zaliapin et al. to distinguish between triggered and background earthquakes. Here we implement the same metric-based correlation to identify the precursory seismicity of any triggered earthquake; this allows us to analyse, for each triggered earthquake, the space–time–magnitude distribution of the seismicity that likely contributed to its occurrence. Our results show that the magnitude-independence assumption holds reasonably well in all catalogues, with a remarkable exception that is consistent with a previous independent study; this departure from the magnitude-independence assumption shows that larger events tend to nucleate at a higher distance from the ongoing sequence. We also notice that the reliability of this assumption may depend on the spatial scale considered; it holds for seismic catalogues of large areas, but we identify possible departures in small areas, reflecting different ways to release locally seismic energy. Finally, we come across an important issue that may lead to misleading results in similar studies, that is, if a seismic catalogue appears overall complete above a fixed magnitude threshold, it may still yield spurious signals into the analysis. Specifically, we show that some significant departures from the magnitude-independence assumption do not survive when considering spatiotemporal variations of the magnitude of completeness. [ABSTRACT FROM AUTHOR]

Snow avalanches generate seismic signals as many other mass movements. Therefore, detection of avalanches by seismic monitoring systems is highly relevant to assess the avalanche danger level. Apart from estimating the overall activity, information on the location of individual events is also important. We deployed a seismic monitoring system consisting of seven vertical geophones at a site above Davos, Switzerland. During a major snowfall on 2017 March 9 and 10, we visually identified 19 events in the seismic data that we considered as avalanches. For all these events, we calculated the backazimuth angles as well as the apparent velocity of the incoming wavefields using two different array processing techniques: a commonly used beam-forming approach and multiple signal classification (MUSIC). One of the avalanches released directly above the array and the path was well documented in a field survey. We analysed this event in more detail and compared both array processing techniques. Using the MUSIC method we were able to reproduce the avalanche path with reasonable accuracy, whereas the beam-forming method only provided a rough direction. The results obtained using MUSIC suggest that with our seismic array mainly infrasonic waves were recorded during the event. From the remaining 18 events, 15 had a clear path and were classified as avalanches. The other three events were dismissed as falsely classified avalanches. By comparing the results for these 15 avalanches events with our field survey, we were able to map 11 avalanches within a distance of 3 km of the array. [ABSTRACT FROM AUTHOR]

The geothermal field at Brady Hot Springs, Nevada has subsided over the past decade. Between 2004 and 2014, the rate of downward-vertical displacement was on the order of 10 mm yr−1, as measured by two independent geodetic techniques: interferometric synthetic aperture radar (InSAR) and Global Positioning System. The observed deformation field forms an approximately elliptical bowl that is 4 km long and aligned with the trace of the NNE striking normal fault system. We use modelling to estimate the plausibility of pressure changes or thermal contraction as the cause of the observed subsidence. As a result, Bayesian inference favours with 'very strong evidence' thermal contraction over other hypotheses as the dominant driving mechanism for the observed subsidence. Using InSAR data spanning from 2016 July 22 to 2017 August 22, we estimate the volume change rate in the significantly deforming volume to be (−29 ± 3) thousand m3 yr−1 and the total rate of change in thermal energy between −53 and −79 MW. We infer the total volume of cubes where the estimated volumetric strain rate is significantly different from zero with 95 per cent confidence to be 119 million m3. We find that the main region of significant cooling occurs between the injection and production well locations. This result supports the idea that highly permeable conduits along faults channel fluids from shallow aquifers to the deep reservoir tapped by the production wells. [ABSTRACT FROM AUTHOR]

In this paper, we use the gravitational gradient changes from Gravity Recovery and Climate Experiment (GRACE) to extract the co-seismic signal of the 2006 M w 8.3 thrust and 2007 M w 8.1 normal-faulting Kuril earthquakes. Particularly, we show that contrary to the observed gravity change that is not suitable for detecting the co-seismic signal of two Kuril earthquakes, the gravitational gradient changes can be used to extract the co-seismic signal, provided that appropriate signal retrieval methods are considered. We use both a stacking method and the so-called time-series analysis to extract the co-seismic signal. The extracted co-seismic gravity gradient signals from the north components of Δ Vxx and Δ Vxz exhibit a dominant 'positive–negative–positive' pattern in the areas surrounding the two epicentres, but the amplitudes differ significantly between the two methods. The co-seismic signal by stacking method shows obviously larger amplitude than those from the model prediction by the PSGRN/PSCMP code, while the signal extracted from the time-series analysis has smaller amplitude in a comparison with that from the stacking method, and is closer to the model prediction. The discrepancy in amplitude between observation and model may be attributed to various factors including the uncertainties in fault-slip model as well as the strong GRACE observational noise. Uncertainty estimation from the time-series analysis indicates that the extracted co-seismic signal agrees with the model prediction within the uncertainty level. The agreement between the observed result and the model prediction demonstrates the effectiveness of gravitational gradient components in detecting relatively weaker co-seismic signals with moment magnitudes as small as the Kuril earthquakes. These relatively weaker signals are otherwise difficult to detect with the commonly used gravity changes. [ABSTRACT FROM AUTHOR]

We introduce a new Bayesian inversion method that estimates the spatial distribution of geological facies from attributes of seismic data, by showing how the usual probabilistic inverse problem can be solved using an optimization framework while still providing full probabilistic results. Our mathematical model consists of seismic attributes as observed data, which are assumed to have been generated by the geological facies. The method infers the post-inversion (posterior) probability density of the facies plus some other unknown model parameters, from both the seismic attributes and geological prior information. Most previous research in this domain is based on the localized likelihoods assumption, whereby the seismic attributes at a location are assumed to depend on the facies only at that location. Such an assumption is unrealistic because of imperfect seismic data acquisition and processing, and fundamental limitations of seismic imaging methods. In this paper, we relax this assumption: we allow probabilistic dependence between seismic attributes at a location and the facies in any neighbourhood of that location through a spatial filter. We term such likelihoods quasi-localized. Exact Bayesian inference is impractical because it requires normalization of the posterior distribution which is intractable for large models and must be approximated. Stochastic sampling (e.g. by using Markov chain Monte Carlo) is the most commonly used approximate inference method but it is computationally expensive and detection of its convergence is often subjective and unreliable. We use the variational Bayes method which is a more efficient alternative that offers reliable detection of convergence. It achieves this by replacing the intractable posterior distribution by a tractable approximation. Inference can then be performed using the approximate distribution in an optimization framework, thus circumventing the need for sampling, while still providing probabilistic results. We show in a noisy synthetic example that the new method recovered the coefficients of the spatial filter with reasonable accuracy, and recovered the correct facies distribution. We also show that our method is robust against weak prior information and non-localized likelihoods, and that it outperforms previous methods which require likelihoods to be localized. Our method is computationally efficient, and is expected to be applicable to 3-D models of realistic size on modern computers without incurring any significant computational limitations. [ABSTRACT FROM AUTHOR]

Palaeomagnetic data are of variable quality. To assist in a systematic assessment of data, a set of seven quality criteria (VQ1–VQ7) were introduced by Van der Voo. The last of those criteria 'VQ7' concerns the possibility of remagnetization when a particular palaeomagnetic pole resembles a younger palaeopole from the same stable region. While remagnetizations are often the culprit, the mere resemblance of an older pole to a younger pole does not a priori require that the rocks under investigation are remagnetized. Given that the Earth has a finite surface area, that apparent polar wander paths (APWPs) are represented as wide swathes rather than points, and that continental motion has taken place over several billion years, we ask the question 'How likely is it for an APWP to loop back on itself?' To answer this question, we constructed synthetic APWPs in an effort to evaluate the likelihood of self-intersection. We find that given 500 Myr of apparent polar wander, ∼60 per cent of the synthetic APWPs show self-intersection. Given 1000 Myr of apparent polar wander, ∼95 per cent of the synthetic APWPs show self-intersection. These results show that resemblance to younger palaeopoles, over the long term, may be governed by simple probability rather than only remagnetization. We recognize that remagnetization does occur, sometimes pervasively, and must be reckoned with in the assessment of palaeomagnetic data. Perhaps VQ7 should be amended to the first sentence in the original discussion, and focus on satisfying 'No suspicion of remagnetization' via other means rather than solely a resemblance to younger poles. [ABSTRACT FROM AUTHOR]

Water resource management is crucial for the economic and social development of Xinjiang, an arid area located in the Northwest China. In this paper, the time variations of gravity recovery and climate experiment (GRACE)-derived monthly gravity field models from 2003 January to 2013 December are analysed to study the terrestrial water storage (TWS) changes in Xinjiang using the multichannel singular spectrum analysis (MSSA) with a Gaussian smoothing radius of 400 km. As an extended singular spectrum analysis (SSA), MSSA is more flexible to deal with multivariate time-series in terms of estimating periodic components and trend, reducing noise and identifying patterns of similar spatiotemporal behaviour thanks to the data-adaptive nature of the base functions. Combining MSSA and Gaussian filter can not only obviously remove the north-south striping errors in the GRACE solutions but also reduce the leakage errors, which can increase the signal-to-noise ratio by comparing with the traditional procedure, that is, empirical decorrelation method followed with the Gaussian filtering. The spatiotemporal characteristics of TWS changes in Xinjiang were validated against the Global Land Dynamics Assimilation System, the Climate Prediction Center and in-situ precipitation data. The water storage in Xinjiang shows the relatively large fluctuation from 2003 January to 2013 December, with a drop from 2006 January to 2008 December due to the drought event and an obvious rise from 2009 January to 2010 December because of the high precipitation. Spatially, the TWS has been increasing in the south Xinjiang, but decreasing in the north Xinjiang. The minimum rate of water storage change is -4.4 mm yr-1 occurring in the central Tianshan Mountain. [ABSTRACT FROM AUTHOR]