Subsurface Reflectivity Research Articles

Eliminating above-surface diffractions from ground-penetrating radar data using iterative Stolt migration

Above-surface diffractions (ASDs) received by unshielded ground-penetrating radar (GPR) antennas are known to contaminate subsurface reflections and diffractions. Existing ASD-removal methods either leave relatively strong residual ASDs within subsurface reflections or attenuate them excessively. We have developed an iterative migration-based ASD-removal method to address this issue that separates ASDs from subsurface reflections via surgical mute. First, we isolate ASDs within the GPR profile using an optimal window function, generated using the focal center of ASDs within the migrated domain. The remainder signifies the zeroth-order separation of subsurface reflections. Second, we perform Stolt migration on the isolated ASDs using the speed of light in air. Then, we mute out the regions dominated by ASDs from the migration results, characterized by highly focused ASDs that are well separated from the majority of subsurface reflections. Following that, we demigrate the separated ASDs and subsurface reflections back to the unmigrated domain using the speed of light in air. Next, we combine the demigrated subsurface reflections with the zeroth-order subsurface reflections, thereby completing the first iteration of the separation process. The entire aforementioned process is then repeated twice on the residual data to obtain further residual subsurface reflections from ASDs, using a lower velocity and a higher velocity in sequence. Our method is verified to suppress ASDs more effectively than existing approaches by retaining a greater proportion of subsurface reflections, and its residual error is negligible. It is robust with respect to energy levels, window widths of ASDs, and clustered ASDs.

Human Skin Gloss Perception Based on Texture Statistics

We propose objective, image-based techniques for quantitative evaluation of facial skin gloss that is consistent with human judgments. We use polarization photography to obtain separate images of surface and subsurface reflections, and rely on psychophysical studies to uncover and separate the influence of the two components on skin gloss perception. We capture images of facial skin at two levels, macro-scale (whole face) and meso-scale (skin patch), before and after cleansing. To generate a broad range of skin appearances for each subject, we apply photometric image transformations to the surface and subsurface reflection images. We then use linear regression to link statistics of the surface and subsurface reflections to the perceived gloss obtained in our empirical studies. The focus of this paper is on within-subject gloss perception, that is, on visual differences among images of the same subject. Our analysis shows that the contrast of the surface reflection has a strong positive influence on skin gloss perception, while the darkness of the subsurface reflection (skin tone) has a weaker positive effect on perceived gloss. We show that a regression model based on the concatenation of statistics from the two reflection images can successfully predict relative gloss differences.

Subsurface Reflectors Detected by SHARAD Reveal Stratigraphy and Buried Channels Over Central Elysium Planitia, Mars

AbstractThe Central Elysium Planitia (CEP) is one of the youngest geological units on Mars and displays evidence of volcanic and fluvial activities on the surface. The origin of the CEP material has long been debated with a range of hypotheses from purely fluvial to solely volcanic origins. This study presents a comprehensive investigation of SHAllow RADar (SHARAD) data to reveal subsurface radar reflectors over the CEP region. Distribution of the detected radar reflectors show possible connections between the CEP and outflow channels, such as Athabasca Valles and Marte Vallis. Analysis of the radar reflectors in the CEP region show six subsurface layers implying multiple depositional and erosional episodes. One detected subsurface layer is found to correspond to the upper exposed layers of one terraced crater. By measuring the depth accurately of these exposed layers in the derived HiRISE (High Resolution Imaging Scientific Experiment) and CTX (Context Camera) DTMs (Digital Terrain Models) and inverting the dielectric constant combining the layers in radargrams, an interpretation that the filling material contains water ice is favored.

Structural analysis and metamorphism of the Barlow Fault Zone, Chibougamau area, Neoarchean Abitibi Subprovince: implications for gold mineralization

Faults and deformation zones are important features of Archean terranes because of their significance for structural evolution and the formation of large gold districts. In the Chibougamau area, northeastern portion of the Abitibi Subprovince, an Apogee Metal Earth seismic reflection survey identified an association between an exceptional shallow-dipping subsurface reflector zone and the Barlow Fault Zone visible at the surface. This fault zone is located adjacent to the Opatica Subprovince and shares many characteristics with well-documented major gold-bearing faults in the more gold-endowed southern portion of the Abitibi Subprovince. This study aimed to reconstruct the kinematic evolution of the Barlow Fault Zone, determine its position within the structural setting of this section of the Abitibi Subprovince, and evaluate its importance for gold potential in the northern part of the Chibougamau area. The fault zone can be divided into three segments that differ markedly in dip. Structural reconstruction and field observations are compatible with a reverse south-over-north movement related to a ductile north–south shortening event, which culminated with amphibolite metamorphism. A late normal movement is deduced at the final stage. Geothermobarometers indicate peak metamorphism conditions of 550 ± 50 °C and 6 ± 1.2 kbar. Results from this study suggest that amphibolite facies metamorphism covers a much wider area within the Chibougamau region than previously documented. The Barlow Fault Zone shares similar geometric characteristics and evolutionary history with other gold-bearing structures in the Abitibi Subprovince, but ultimately it was unable to provide optimal conditions for channelling fluid and precipitating gold. High-grade metamorphism and the limited crustal extent of the fault likely prevented the tapping of deep metamorphic fluid and magma reservoirs. The Barlow Fault Zone is interpreted as a back-thrust fault that belongs to a more extensive south-dipping fault system encasing juxtaposed tectonic slivers. This system, with amphibolite facies metamorphism, is a defining feature of the northern portion of the Chibougamau area and developed during the accretion between the Opatica and Abitibi subprovinces.

In-situ multiple parameter calibration and mapping using a mobile soil sensor

ABSTRACT The purpose of this study was to estimate local calibration models for 30 chemical and 4 physical soil properties, based on visible and near-infrared subsurface soil reflectance spectra (VNIR-SRS). Further, we discussed a case of decision-making for precision farming by a grower, using high-resolution soil maps. The experimental sites were located in rotational upland fields of taro in Saitama Prefecture, Japan. The parent materials in the experimental sites were Light Clay, Clay Loam, and Sandy Clay Loam. A mobile soil sensor (SAS3000) attached to a tractor was used to measure the VNIR-SRS (350 to 1700 nm). A total of 231 field-moist soil samples and corresponding VNIR-SRS data were collected from 23 fields (6 growers), from 2017 to 2018 period, to estimate local calibration models for the 34 properties. A total of 34 local calibration models were estimated using the second derivative pretreatment and partial least squares regression analysis. Excluding several outliers, the coefficient of determination (R 2) for the local calibration models was 0.81 or more. Immediately after soil sensing in the field, we generated high-resolution soil property maps for the growers’ fields, using the VNIR-SRS data and the 34 local calibration models stored in the SAS3000. The grower involved in the map-based decision-making recalled past crop management, growth, yield, etc., in the target field, and selected a cost-effective soil management technique. In addition, the six growers in the study stressed the importance of understanding the high-resolution relative variability among multiple soil properties, between fields and within a given field.

Extensive and nonextensive statistics in seismic inversion

Seismic inversion is a central procedure for estimating subsurface physical parameters from observed data. In geophysical applications, the seismic inversion is usually formulated as an optimisation problem that aims to minimise the difference between modelled and observed data through the Gauss’ error law, which is linked to the extensive Boltzmann–Gibbs (BG) statistics. However, this approach is known to be sensitive to non-Gaussian errors, especially to outliers in the data set. Therefore, error laws determined by non-Gaussian statistics are essential for robust seismic inversion. In this way, we present a comparative study of seismic inversions using the extensive statistics of Rényi and also on the nonextensive statistics of Tsallis and Kaniadakis. In particular, we consider a classical seismic inversion problem so-called Post-Stack Inversion (PSI), which analyses the interaction between seismic waves and subsurface reflectivity to infer geological structures. Considering a realistic subsurface reflectivity model taking into account spike-noisy data, the numerical results show that the PSI based on generalised statistics outperforms the PSI based on standard BG statistics. We note that, the best results are for the Tsallis case in which the Lévy–Gnedenko central-limit theorem is valid (q>53).

Evaluation of forward reflectance models and empirical algorithms for chlorophyll concentration of stratified waters.

For waters with stratified chlorophyll concentration (Chl), numerical simulations were carried out to gain insight into the forward models of subsurface reflectance and empirical algorithms for Chl from the ocean color. It is found that the Gordon and Clark (1980) forward model for reflectance using an equivalent homogeneous water with a weighted average Chl (⟨Chl⟩) as the input works well, but depending on the contribution of gelbstoff, the difference in reflectance between stratified and the equivalent homogeneous water can be more than 10%. Further, the attenuation of upward light is better approximated as ∼1.5times that of the diffuse attenuation coefficient of downwelling irradiance. On the other hand, although the forward model for reflectance developed in Zaneveld et al. [Opt. Express13, 9052 (2005)] using equivalent homogeneous water with a weighted average of the backscattering to absorption ratio as the input also works well, this model cannot be used to obtain equivalent ⟨Chl⟩ for reflectance. Further, for empirical Chl algorithms designed for "Case 1" waters, it has been discovered that, for surface Chl in a range of ∼0.06-22.0mg/m3, the predictability of surface Chl is basically the same as that of ⟨Chl⟩ from the blue-green band ratio or the band difference of reflectance. Because ⟨Chl⟩ is wavelength and weighting-formula dependent, and it is required to have profiles of both Chl and the optical properties, these results emphasize that for empirical Chl algorithms, it is easier, less ambiguous, and certainly more straightforward and simple to use surface Chl for algorithm development and then its evaluation, rather than to use ⟨Chl⟩, regardless of whether or not the water is stratified.

Least-squares reverse time migration with sparse regularization in the 2D wavelet domain

The inadequate sampling of seismic data in the spatial dimension results in migration artifacts. Conventional least-squares reverse time migration (LSRTM) could improve the image quality. However, even LSRTM will not work in some inadequately sampling situations. To mitigate the impact of migration artifacts, we have developed a new LSRTM method with a sparse regularization, which takes advantage of the effective sparse representation of the subsurface reflectivity model in the 2D undecimated wavelet transform (UWT) domain. Different from other sparse regularizations, a sparseness constraint in the 2D UWT domain is applied on the angle slices of the image. To efficiently solve the least-squares inversion problem, we employ an inversion scheme using the conjugate gradient method that uses a soft threshold method to achieve sparse constraint in updating the conjugate gradient direction. Compared with the sparse constraint based on the discrete wavelet transform (DWT), the threshold in this method is angle-dependent and is determined according to the energy distribution of each angle slice. To avoid overregularization that can lead to instability and increase the number of iterations, we also apply an exponential threshold strategy. Numerical tests on synthetic datasets demonstrate that our method is capable of improving the image quality by enhancing the resolution and suppressing migration artifacts caused by inadequately sampled seismic data. The method can converge more rapidly than conventional LSRTM. Because this method performs sparse regularization on several slopes, it achieves better performance on enhancing complex structures with discontinuities such as the steeply dipping faults compared to DWT-based regularization.

Estimation of bulk permittivity of the Moon\u2019s surface using Lunar Radar Sounder on-board Selenological and Engineering Explorer

Site-dependent bulk permittivities of the lunar uppermost media with thicknesses of tens to hundreds meters were estimated based on the data from Lunar Radar Sounder onboard the Selenological and Engineering Explorer (SELENE). It succeeded in sounding almost all over the Moon’s surface in a frequency range around 5 MHz to detect subsurface reflectors beneath several lunar maria. However, it is necessary to estimate the permittivity of the surface regolith of the Moon in order to determine the actual depths to those reflectors instead of apparent depths assuming a speed of light in the vacuum. In this study, we determined site-dependent bulk permittivities by two-layer models consisting of a surface regolith layer over a half-space with uniform, but different physical properties from the layer above. Those models consider the electrical conductivity as well as the permittivity, whose trade-off was resolved by utilizing the correlation between iron–titanium content and measured physical properties of lunar rock samples. Distribution of the iron–titanium content on the Moon’s surface had already been derived by spectroscopic observation from SELENE as well. Four lunar maria, Mare Serenitatis, Oceanus Procellarum, Mare Imbrium, and Mare Crisium, were selected as regions of evident reflectors, where we estimated the following four physical properties of each layer, i.e., bulk permittivity, porosity, loss tangent and electrical conductivity to conclude the actual depths of the reflectors are approximately 200 m on average. The bulk permittivity ranges from 2.96 at Mare Imbrium to 6.37 at Oceanus Procellarum, whereas the porosity takes the values between 1.8 and 41.1% in the respective maria. It was found that although the bulk permittivity of the four lunar maria differs from a mare to a mare, it shows a good correlation with their composition, viz., their iron–titanium content.

Radar Sounding of Subsurface Structure in Eastern Coprates and Capri Chasmata, Mars

AbstractWe surveyed the subsurface structure in eastern Coprates and Capri Chasmata in the equatorial region using high‐resolution visible images, digital terrain models, and radar sounding data. We identified subsurface reflectors in four areas of the chasmata. At the stratigraphic exposure on the chasmata walls, the corresponding depth of the reflector is ∼60 m. The bulk dielectric constants of the layers above the reflectors are calculated as 3.4–4.0, suggesting a rock‐air mixture with ∼39.3% and 46.1% porosity or a rock‐air‐ice mixture with <21.2% water ice fraction. This high porosity corresponds to nonwelded and unconsolidated sediments emplaced by aeolian, fluvial, and volcanic activities. If water ice actually exists, further studies and discussions are required for the mechanism to maintain it within low latitudes.

The Global Search for Liquid Water on Mars from Orbit: Current and Future Perspectives.

Due to its significance in astrobiology, assessing the amount and state of liquid water present on Mars today has become one of the drivers of its exploration. Subglacial water was identified by the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) aboard the European Space Agency spacecraft Mars Express through the analysis of echoes, coming from a depth of about 1.5 km, which were stronger than surface echoes. The cause of this anomalous characteristic is the high relative permittivity of water-bearing materials, resulting in a high reflection coefficient. A determining factor in the occurrence of such strong echoes is the low attenuation of the MARSIS radar pulse in cold water ice, the main constituent of the Martian polar caps. The present analysis clarifies that the conditions causing exceptionally strong subsurface echoes occur solely in the Martian polar caps, and that the detection of subsurface water under a predominantly rocky surface layer using radar sounding will require thorough electromagnetic modeling, complicated by the lack of knowledge of many subsurface physical parameters. Higher-frequency radar sounders such as SHARAD cannot penetrate deep enough to detect basal echoes over the thickest part of the polar caps. Alternative methods such as rover-borne Ground Penetrating Radar and time-domain electromagnetic sounding are not capable of providing global coverage. MARSIS observations over the Martian polar caps have been limited by the need to downlink data before on-board processing, but their number will increase in coming years. The Chinese mission to Mars that is to be launched in 2020, Tianwen-1, will carry a subsurface sounding radar operating at frequencies that are close to those of MARSIS, and the expected signal-to-noise ratio of subsurface detection will likely be sufficient for identifying anomalously bright subsurface reflectors. The search for subsurface water through radar sounding is thus far from being concluded.

Mobile Proximal Sensing with Visible and Near Infrared Spectroscopy for Digital Soil Mapping

The objective of this study was to estimate multiple soil property local regression models, confirm the accuracy of the predicted values using visible near-infrared subsurface diffuse reflectance spectra collected by a mobile proximal soil sensor, and show that digital soil maps predicted by multiple soil property local regression models are able to visualize empirical knowledge of the grower. The parent materials in the experimental fields were light clay, clay loam, and sandy clay loam. The study was conducted in Saitama Prefecture, Japan. To develop local regression models for the 30 chemical and 4 physical properties, a total of 231 samples were collected; to evaluate accuracy of prediction, 65 samples were collected. The local regression models were developed using 2nd derivative pretreatment by the Savitzky–Golay algorithm and partial least squares regression. The local regression models were evaluated using the coefficient of determination (R2), residual prediction deviation (RPD), range error ratio (RER), and the ratio of prediction error to interquartile range (RPIQ). The R2 accuracy of the 34 local regression models was 0.81 or higher. In the predicted values for 65 unknown samples, the local regression models could ‘distinguish between high and low’ for 3 of the 34 soil properties, but were ‘not useful’ as absolute quantitative values for the other 31 soil properties. However, it was confirmed that the predicted values followed the transition in measured values, and thus that the developed 34 regression models could be used for generating digital soil maps based on relative quantitative values. The grower changed the ridge direction in the field from east–west to north–south just looking at the digital soil maps.

An efficient and accurate finite-difference operator using adaptively discretized grids and its application for 3D least-squares reverse-time migration

Least-square reverse-time migration (LSRTM) is a powerful tool to image subsurface reflectivity with high resolution. It has the ability to reduce migration artifacts, balance amplitudes, and improve imaging resolution. However, the large amount of computation cost is one of its challenging problems, especially for 3D problems. We propose an efficient and accurate finite-difference modeling operator using an adaptive variable grid strategy. The resampled model’s grid intervals adapt to local velocity and wave frequency, ensuring that dispersion is mitigated to some extent. Furthermore, we apply the modeling operator to 3D LSRTM with graphics processing unit (GPU) implementation in order to mitigate the large calculation costs. The 3D modeling is applied to two synthetic examples to validate its feasibility, accuracy, and efficiency. The imaging results of the 3D SEG/EAGE overthrust model demonstrated that adaptive grid LSRTM (AGLSRTM) is capable of reducing computing time and memory requirement while producing the same imaging accuracy as traditional LSRTM.

Sparse subsurface radar reflectors in Hellas Planitia, Mars

Geomorphological features potentially related to subsurface ice, such as scalloped depressions, expanded craters, pedestal craters, and banded terrain, are present in and around Hellas Planitia, Mars. We present a radar survey of the region using the Shallow Radar (SHARAD) instrument on board the Mars Reconnaissance Orbiter (MRO) to identify candidate subsurface reflectors that may be due to the presence of potentially ice-rich deposits. We found that the majority of radar returns are likely from off-nadir surface topography (“clutter”), arising from the rough topography of the region. There is no widespread radar return from any subsurface interfaces. However, we identify a group of six reflectors adjacent to each other on a plateau in Malea Patera in which we have higher confidence. Landforms associated with a likely ice-rich mantle are associated with the plateau, but the thickness of this mantle does not correspond to the expected depth of the reflectors. However, layers beneath the mantle and marginal pitting at the edge of the plateau are similar to those associated with pedestal craters, which may be ice rich and are a similar thickness to the expected depth of the reflectors. Malea Patera has been interpreted to be a volcanic caldera, so the reflectors may be associated with a volcanic deposit within the plateau, although the evidence for this is inconclusive. Because this radar detection is localized and its origin ambiguous, we cannot use it to make conclusions about the thickness of subsurface deposits in the Hellas region as a whole. The lack of widespread radar reflectors in this region, as compared to the northern mid-latitudes where extensive radar reflections have been mapped, may be due in part to higher surface roughness, which creates radar clutter that may obscure subsurface reflectors. However on the southern rim of the basin and south of the basin, the lack of reflectors may indicate that the possible ice-rich deposits observed geomorphologically in this region are too thin to be resolved by SHARAD, are dielectrically similar to the underlying unit, or have a gradual vertical transition in ice content that is not reflective for the radar. This would imply that recent climate processes may have favored widespread, thick ice deposition or preservation in the northern hemisphere as compared to the southern hemisphere.

A simple approach to nonstationary source waveform estimation in seismic records

A simple and practical method for source-waveform estimation from reflection seismic records is implemented by iterative identification of locally strongest reflections. Instead of conventional hypotheses about statistical properties of the whole records, the method is based on a general observation that stronger reflection peaks occur relatively sparsely and that smaller peaks adjacent to them are mutually incoherent. Tests with real well logs suggest that the subsurface often possesses such sparseness. Based on this property, the source waveform is obtained from seismic records by optimizing a combination of its practically important properties, such as the main-lobe width, side-lobe amplitudes, and phase character. Similarly, other types of optimization criteria can be used. The approach is stable with respect to noise and parameter variations and allows estimating the source waveforms without well-log control. By including inverse [Formula: see text]-filtering, time-variant amplitude scaling, and/or band-pass filtering, the approach allows correcting for reflection amplitude variations, nonstationarity due to seismic attenuation and dispersion, and also for coherent noise consisting in possible amplitude variations and phase shifts of the low- or high-frequency components of the records. By using the estimated source waveform, time-dependent waveforms and nonstationary wavelet matrices can be predicted at any reflection time. The method is illustrated by synthetic examples of logs with von Kármán distributions of velocity fluctuations and real well logs from an oil reservoir. In the synthetics, the spectral character and shape of the main lobe of the source waveform are reproduced well in all cases, and the phase character of the source is partly recovered when the subsurface reflectivity is dominated by reflections that are relatively sparse and strong compared to the adjacent reflectivity. In cases in which the phase of the source signal is unknown, the obtained waveforms are characterized by simple shapes with low-amplitude side lobes. Such waveforms are suitable for many applications from well ties and numerical modeling to deconvolution and [Formula: see text]-compensation.

Realistic weather conditions and removal of time-varying sea-surface effects: Application on ocean-bottom-cable data

In marine seismic acquisition, seismic reflections at the sea surface, such as sea-surface ghosts and multiples, affect the accuracy of the retrieved subsurface reflections and reduce the usable frequency bandwidth. These sea-surface effects tend to increase with the increasing roughness of the weather conditions. Consequently, processing techniques that neglect the roughness and time variation of the sea surface induce errors in the data that could compromise the validity of the final images and interpretations. We study the impact of time-varying rough sea surfaces using a modeling method derived from the Rayleigh reciprocity theorem for time-varying surfaces, and we analyze errors in the source-deghosting operation. We show that the source-deghosting limitations are weather dependent for data including sea-surface multiples: For calm sea states (wave heights below 1.25 m), the error made by the source-deghosting process is negligible; however, for rough seas (wave heights above 1.5 m), it becomes significant and blurs the deghosted image at the sea-surface multiple signals. To accurately remove all sea-surface effects from the seismic data, we simultaneously apply source-deghosting and multiple-removal operations to the same up-going wavefield. This procedure is shown to be weather independent based on our theoretical derivation and the synthetic results. Finally, this is tested on a 2D OBC data set. Comparing the proposed inversion to up-down deconvolution, we observe similar features in both wavefields: Source ghosts and sea-surface multiples seem to have been correctly removed from the data, and the inverted result indicates a slightly better resolution for deeper reflections.

Regularized phase retrieval for seismic wavelet estimation and blind deconvolution

Seismic data can provide more detailed information from subsurface in comparison with data gathered via other geophysical methods. This made the oil and gas exploration industry to pay considerable attention to the seismic methods. The accuracy of the information extracted from seismic data largely depends on the accuracy of the information about the seismic wavelet. Thus, wavelet estimation has become an important step in seismic data processing but the quality of the estimate depends on the complexity of the wavelet phase. In this paper, the phase of the wavelet is estimated by using a regularization method taking into account the sparse characteristics of the subsurface reflectivity model. Unlike the conventional deconvolution methods, here only the amplitude spectrum of the data are inverted as a phase retrieval problem, whereby the sparsest solution to deconvolution problem is found by matching the predicted amplitude spectrum to that of the observations. Then the accuracy of the wavelet is improved by deconvolving the recovered impulse response from the data. The results of the numerical examples from synthetic and field data demonstrate that the proposed method is able to extract complex-phase wavelets with an acceptable accuracy. Furthermore, the reflectivity series is also retrieved as the output of the algorithm. A significant advantage is that the presented algorithm is able to retrieve reflectivity series and the wavelet in only two iterations, compared with the traditional blind deconvolution algorithms.

A numerical study on deblending of land simultaneous shooting acquisition data via rank‐reduction filtering and signal enhancement applications

ABSTRACTWe propose a workflow of deblending methodology comprised of rank‐reduction filtering followed by a signal enhancing process. This methodology can be used to preserve coherent subsurface reflections and at the same time to remove incoherent and interference noise. In pseudo‐deblended data, the blending noise exhibits coherent events, whereas in any other data domain (i.e. common receiver, common midpoint and common offset), it appears incoherent and is regarded as an outlier. In order to perform signal deblending, a robust implementation of rank‐reduction filtering is employed to eliminate the blending noise and is referred to as a joint sparse and low‐rank approximation. Deblending via rank‐reduction filtering gives a reasonable result with a sufficient signal‐to‐noise ratio. However, for land data acquired using unconstrained simultaneous shooting, rank‐reduction–based deblending applications alone do not completely attenuate the interference noise. A considerable amount of signal leakage is observed in the residual component, which can affect further data processing and analyses. In this study, we propose a deblending workflow via a rank‐reduction filter followed by post‐processing steps comprising a nonlinear masking filter and a local orthogonalization weight application. Although each application shows a few footprints of leaked signal energy, the proposed combined workflow restores the signal energy from the residual component achieving significantly signal‐to‐noise ratio enhancement. These hierarchical schemes are applied on land simultaneous shooting acquisition data sets and produced cleaner and reliable deblended data ready for further data processing.

Reflections on the anomalous ANITA events: the Antarctic subsurface as a possible explanation

AbstractThe Antarctic Impulsive Transient Antenna (ANITA) balloon experiment was designed to detect radio signals initiated by high-energy neutrinos and cosmic ray (CR) air showers. These signals are typically discriminated by the polarization and phase inversions of the radio signal. The reflected signal from CRs suffer phase inversion compared to a direct ‘tau neutrino’ event. In this paper, we study subsurface reflection, which can occur without phase inversion, in the context of the two anomalous up-going events reported by ANITA. It is found that subsurface layers and firn density inversions may plausibly account for the events, while ice fabric layers and wind ablation crusts could also play a role. This hypothesis can be tested with radar surveying of the Antarctic region in the vicinity of the anomalous ANITA events. Future experiments should not use phase inversion as a sole criterion to discriminate between down-going and up-going events, unless the subsurface reflection properties are well understood.

Permittivity Estimation of Subsurface Deposits in the Elysium–Utopia Region on Mars with MRO Shallow Radar Sounder Data

Abstract Dielectric properties of the subsurface layers provide important clues to material compositions beneath the surface. The Mars Reconnaissance Orbiter (MRO) Shallow Radar (SHARAD) observed clear subsurface reflections in the Elysium–Utopia region, where morphological features such as impact craters with rampart ejecta suggest the possible presence of volatiles, but the permittivity of the subsurface unit beneath the surface strata has not been derived yet to provide independent evidence for or against the presence of water ice. In this paper, we employed a three-layer model consisting a surface mantling layer (layer I), a shallow subsurface layer (layer II), and a deep subsurface layer (layer III) to invert the permittivity of layer III, which considers the surface roughness and attenuation of radar waves in layer II. The obtained permittivity and loss tangent in the study region confirm that the materials of layer II are dense basaltic flows. Then, the permittivity of layer III is derived as 2.6 ± 0.9, suggesting that subsurface water ice may be present, or a layer of dry and low-density deposits exists beneath the basalt layer. The hypothesis could be further tested by the ground-penetrating radar of China’s first Martian mission, to be launched in 2020. Our results also show that the surface mantling layer included in the model is essential in the calculation of permittivity values.