Simultaneous Sources Research Articles

Classification of simultaneous multiple partial discharge sources based on probabilistic interpretation using a two-step logistic regression algorithm

In online condition assessment monitoring of high voltage (HV) insulators, it is often required to identify multiple, simultaneously activated partial discharge (PD) sources that happen in the insulation of the HV apparatus. Phased resolved partial discharge (PRPD) patterns are commonly used to identify PD sources. However, multiple, concurrent PD sources sometimes result in partially overlapped patterns, which make them hard to be identified. In this paper, we develop an accurate, reliable algorithm by constructing a novel two-step logistic regression (LR) model to conduct probabilistic identification of multi-source PDs. To this end, principal component analysis is applied on a database to construct a low dimensional space associated with single-source PDs. Samples of multi-source PDs are then projected onto this space and one-class kernel support vector machine is adopted to distinguish multi-source PDs from single-source ones. Finally, classification is performed by estimating the probability (degree of membership) of each PRPD pattern arising from different multi-source PDs following two rounds of LR modeling. To evaluate the performance of our proposed method, we study a number of multi-source PD models to simulate common defects of Gas-Insulated Switchgear (GIS) in small-scale laboratory test cells with realistic SF6 gas condition. Observations are obtained using fingerprints generated by a novel approach from recorded PRPD patterns. Comprehensive performance evaluation of the proposed algorithm and its advantages are conducted and the development of analytical equations is presented. The results of this paper can be used to design a solid basis for an automated multi-source classification system, which facilitates multi-source PD identification in early stages and safe operation of HV apparatus.

A POCS method for iterative deblending constrained by a blending mask

A recently emerging seismic acquisition technology called simultaneous source shooting has attracted much attention from both academia and industry. The key topic in the newly developed technique is the removal of intense blending interferences caused by the simultaneous ignition of multiple airgun sources. In this paper, I propose a novel inversion strategy with multiple convex constraints to improve the deblending performance based on the projection onto convex sets (POCS) iterative framework. In the POCS iterative framework, as long as the multiple constraints are convex, the iterations are guaranteed to converge. In addition to the sparse constraint, I seek another important constraint from the untainted data. I create a blending mask in order to fully utilize the useful information hidden behind the noisy blended data. The blending mask is constructed by numerically blending a matrix with all its entries set to be one and then setting the non-one entries of the blended matrix zero. I use both synthetic and field data examples to demonstrate the successful performance of the proposed method.

Multiple criteria decision analysis based on Shapley fuzzy measures and interval-valued hesitant fuzzy linguistic numbers

Hesitant fuzzy sets (HFSs) are powerful tools in managing simultaneous sources of vagueness. Inspired by HFSs, interval-valued hesitant fuzzy linguistic sets (IVHFLSs) combine linguistic term sets and interval-valued hesitant fuzzy sets (IVHFSs) together to flexibly characterize uncertain information from simultaneous sources. The purpose of this paper is to investigate effective ways to aggregate such uncertain information and then apply them to multiple criteria decision analysis (MCDA). First, two interval-valued hesitant fuzzy linguistic Choquet integrals are proposed to characterize the interdependent characteristics between criteria. Then, based on the Shapley fuzzy measures, we develop two kinds of generalized interval-valued hesitant fuzzy linguistic Shapley Choquet integrals to globally characterize interactions between criteria combinations. A model designed to obtain the optimal Shapley fuzzy measures is then constructed. Furthermore, an approach to interval-valued hesitant fuzzy linguistic MCDA is developed based on the proposed aggregation operators. Finally, a numerical example and a detailed discussion are provided to illustrate the application of the proposed approach and to demonstrate its practicality and effectiveness, respectively.

The Reputational Effects of Textual Information in Operational Risk Announcements

This paper performs textual content analysis of 288 operational risk announcements from 80 financial institutions in 18 countries which hit the public media news following the global financial crisis (2010-2014). The “Cheap Talk” theory does not seem to apply to operational risk announcements as the net negative tone, uncertainty tone, and litigious tone in the relevant media news have considerable effects on the equity-based reputation, as measured by the loss-adjusted abnormal stock returns, and the debt-based reputation, as measured by the abnormal CDS spread changes. We find that the net negative tone and litigious tone have adverse reputational effects and that the uncertainty tone causes debt investors to give the loss firms the benefit of the doubt, thus mitigating the adverse debt-based reputational impact of operational risk announcements. Additionally, alternative, simultaneous sources of information neutralise the reputational effects of textual tones in the media news on operational risk events. Loss amount disclosure dissolves the favourable (adverse) equity-based reputational effects of the uncertainty tone (litigious tone) whilst regulatory announcements counteract the favourable (adverse) debt-based reputational consequences of the uncertainty tone (litigious tone). Moreover, loss amount disclosure and firm recognition effectuate the adverse equity-based reputational impact of the net negative tone. Furthermore, by resolving most of the ambiguity underlying the operational risk event, final settlements remove, if not reverse, the favourable reputational impact of the uncertainty tone. Overall, this paper documents the ‘equity-based’ and ‘debt-based’ reputational effects of financial sentiment tones in unexpected adverse media news and shows how such reputational effects are moderated by alternative sources of public information.

Simultaneous Sources Separation via an Iterative Rank-Increasing Method

Simultaneous sources acquisition attracts intensive attention from both academia and industry due to its greatly improved efficiency in acquiring high-density seismic data. Unfortunately, its merits are compromised by the strong interference noise between adjacent shots. In this letter, we propose a stepwise rank-increasing (RI) method to estimate the crosstalk noise in simultaneous sources acquisition. The proposed algorithm assumes that an ideal common offset gather (COG) can be represented via a low-rank matrix in the time-space domain. The coherent signals are estimated from low-rank decomposition and transformed to the crosstalk noise by employing a priori information about random dithering code, and then the blending noise is subtracted from the blended data. By increasing the rank of coherent signals step-by-step, the crosstalk noise can be gradually estimated with high accuracy. In this letter, singular value decomposition is utilized to increase the rank of COG data. Applications on synthetic and field data sets demonstrate the better performance of the proposed RI method not only by more effectively suppressing noise but also by accelerating the convergence rate.

Advanced Deblending Scheme for Independent Simultaneous Source Data

Independent Simultaneous Source (ISS®) technology is an attractive way to provide high acquisition production rates and affordable higher density seismic imaging. In this paper, we propose an advanced deblending scheme to address the source separation requirement of ISS® data. The deblending scheme includes a) 3D low-rank decomposition based iterative noise modelling, and subtraction, b) signal-to-noise ratio map guided residual denoise and c) erratic noise attenuation. The application is tested on actual shallow water OBC dataset, which was pseudo-blended using a realistic dual vessel acquisition plan. The result shows that this advanced deblending scheme can successfully recover individual source responses. The deblended data have a minimal difference compared with the actual unblended data.

Signal apparition applied to towed marine simultaneous sources – a case study on synthesized real data from the Viking Graben

Encoding sources using random dithers for simultaneous source acquisition offers significant scope for enhanced towed marine operations. However, so far it has proven to be challenging to reduce the decoding residual noise from these techniques to a level that is widely accepted by the industry. The emerging technology of signal apparition offers a new approach to overcome this challenge. In contrast to established thinking, the signal apparition concept capitalizes on periodic rather than random shot-to-shot modulation functions to facilitate shot separation. The approach allows us to efficiently populate the available data space in, for instance, the frequency wavenumber domain with energy from different simultaneous sources. The introduction of periodic modulation functions in seismic acquisition produces an effect where parts of the energy of one or more sources are shifted to different empty parts within the frequency wavenumber (f-k) domain. This so-called apparated energy can then be used to perfectly predict at low frequencies the remaining part of the signal in the regions of the f-k domain where the wavefields from the different sources overlap and to deterministically separate the sources. On a synthesized real data set from the Viking Graben in the North Sea, the suitability of this concept to marine seismic simultaneous sources is demonstrated. An operational scenario for a single vessel is designed where the source arrays are excited simultaneously. Having two closely spaced simultaneous sources is a challenging case for shot separation but, if successful, such a cost-effective single-vessel configuration offers highly significant productivity gains. The wavefield decoding results analysed pre-stack and post-stack are very encouraging and indicate that the signal apparition concept indeed has the potential to deliver the high quality source decoding required for many seismic applications.

Optimizing near-orthogonal air-gun firing sequences for marine simultaneous source separation

Air-gun arrays can be encoded by firing individual air guns sequentially over a range of time. This marine source encoding is shown to be particularly beneficial for simultaneous source separation, which can exploit the orthogonality of the encoding sequences to improve the source separation. We have developed a method to design encoding sequences for air-gun arrays having minimized crosscorrelation and optimized autocorrelation properties. By varying the firing times of the individual air-gun subelements, different encoding sequences are constructed using a simulated annealing approach so that their orthogonality properties are optimized. These optimized sequences are then used for time-dithered simultaneous source encoding. Realistic synthetic data examples show a significant improvement of simultaneous source separation. We have also determined the robustness of the method for take-off angle variations and possible errors in sequence estimation.

Exploiting the control of phase in marine vibrators

Marine seismic vibrators are considered to be more environmentally friendly than air guns and this has prompted a resurgence of interest in their use. However, these devices have novel features that are potentially of great benefit to seismic imaging and that have not yet been exploited - in particular, we can control the phase. With marine vibrators, the emitted waveform can be chosen freely, provided that it lies within the envelope of what the device can emit. Typically, the waveform is a swept-frequency sinusoid. In this paper, we show how the sweep phase can be used to suppress the residual shot noise (RSN) and to separate simultaneous sources of high multiplicity. This work is also described by Laws and Halliday (2013) and is closely related to that of Laws (2012). The control of phase is a benefit of marine vibrators that can be exploited to great effect. First, we look at the RSN situation. The conventional wisdom is that roughly a 10s shot-time interval is required in marine seismic data acquisition so that the RSN is acceptably small relative to the signal. Because both signal and RSN originate from the seismic source, the ratio of signal/RSN is not improved by using a larger source (pace Landro, 2008). We show a simple case of RSN attenuation using alternating sine and cosine sweeps. That is to say, the sequence of source phases goes, for successive shots, [0° 90° 0° 90° 0° 90° 0° 90°... and so on]. We show schematically how this ‘phase sequencing’ leads to a dramatic attenuation of the RSN. It does so by moving the RSN into parts of the frequency-wavenumber spectrum where there is no signal. We then use frequency-wavenumber filtering to remove the RSN. This can be done with simple filtering up to the limit imposed by spatial aliasing and beyond that limit by using wavefield reconstruction methods, such as generalized matching pursuit (Ozbek et al., 2010; Vassallo et al., 2010). Reconstruction methods decompose the seismic wavefield into a set of basis functions that allow the signal and RSN to be identified and separated. Then, we look at the simultaneous source situation. The RSN removal problem can be considered as a special case of the more general simultaneous source separation problem. As an example, in the case of two simultaneous sources, one source can be swept with consistent phase, while the other source is swept with alternating phase, i.e., the sequence of relative phases is [0° 180° 0° 180° 0° 180° 0° 180°... and so on]. The simultaneous source separation is demonstrated using the same type of reconstruction method as described above for the RSN. See also Moore et al. (2008) and Ji et al. (2012). The use of phase sequencing opens up possibilities for simultaneous source separation using large numbers of sources. By having complete control over the phases of all the sources it is possible, in certain domains, to make simultaneous source data look similar to aliased data from a single source. This opens the door to using many established wavefield interpolation and dealiasing-techniques to perform high-multiplicity simultaneous source separation.

High-productivity seabed time-lapse seismic data acquisition using simultaneous sources enabled by seismic apparition: A synthetic-data study

Seismic apparition is a recent signal-processing advance that trades signal interference and aliasing between different spatial (and temporal) dimensions. In particular, an important application of seismic apparition is for simultaneous-source separation to better exploit the available data space in the frequency-wavenumber (f-k) domain with energy from different simultaneous sources. The introduction of periodic modulation functions in seismic acquisition produces an effect where parts of the energy of one or more sources are partially shifted to different empty parts within the f-k domain. This so-called apparated energy then can be used to perfectly predict (at low frequencies) the remaining part of the signal in the regions of the f-k domain where the wavefields from the different sources overlap and to deterministically separate the sources at predetermined (repeated) positions — a prerequisite for 4D seismic processing. At higher frequencies, the apparition separation is dealiased using directional information, taking full advantage of the perfect separation at lower frequencies to achieve the required low-error separation. To apparate seismic energy to different portions within the f-k domain, we introduce a periodic modulation function, consisting for instance of a small time delay/advance or an amplitude scaling to every second shot. Our simultaneous-source approach is thus opposite to established industry practices of maximizing randomness using dithered sources. A deterministic simultaneous-source-separation approach in which shot points and simultaneous-source patterns are repeated accurately is a major advantage over industry-standard stochastic simultaneous-source-acquisition approaches, particularly for 4D applications. We demonstrate the suitability of the seismic-apparition simultaneous-source technique to time-lapse seismic, having a permanent-reservoir-monitoring context in mind, by investigating two operational scenarios of single-vessel acquisition where two sources are excited simultaneously. Single-vessel simultaneous-source acquisition represents the most challenging case for shot separation in general and for time-lapse seismic applications in particular. The quantitative and qualitative wavefield decomposition results analyzed pre- and poststack are highly encouraging on synthetic data and warrant further testing of seismic-apparition technology in a real 4D seismic test case.

Sub-Micrometer Magnetic Nanocomposites: Insights into the Effect of Magnetic Nanoparticles Interactions on the Optimization of SAR and MRI Performance.

There is increasing interest in the development of new magnetic polymeric carriers for biomedical applications such as trigger-controlled drug release, magnetic hyperthermia (MH) for the treatment of cancer, and as contrast agents in magnetic resonance imaging (MRI). This work describes the synthesis of sub-micrometer and magnetic polymer nanocomposite capsules (MPNCs) by combining in one single platform the biodegradable polymer poly-ε-caprolactone (PCL) and different concentrations of ∼8 nm oleic acid (OA)-functionalized magnetite nanoparticles (Fe3O4@OA), employing the oil-in-water emulsion/solvent evaporation method. The MPNCs showed a significant increase in particle size from ∼400 to ∼800 nm as the magnetic loading in the organic-inorganic hybrids increases from 1.0% to 10%. The MPNCs presented high incorporation efficiency of Fe3O4@OA nanoparticles, good colloidal stability, and super-paramagnetic properties. Interestingly, electron microscopy results showed that the Fe3O4@OA nanoparticles were preferentially located at the surface of the capsules. Evaluation of the magnetic properties showed that the saturation magnetization and the blocking temperature of the MPNCs samples increased as a function of the Fe3O4@OA loading. All the MPNCs exhibited heating when subjected to MH, and showed good specific absorption rates. Use of the formulations decreased the longitudinal (T1) and transverse (T2) relaxation times of water protons' nuclei, with excellent transverse relaxivity (r2) values, especially in the case of the formulation with lowest Fe3O4@OA loading. Furthermore, the MPNCs-cell interaction was studied, and MPNCs showed lower cellular toxicity to normal cells compared to cancer cells. These findings help in understanding the relationships between magnetic nanoparticles and polymeric capsules, opening perspectives for their potential clinical uses as simultaneous heating sources and imaging probes in MH and MRI, respectively.

Seismic Simultaneous Source Separation via Patchwise Sparse Representation

The concept of simultaneous source has recently become of interest in seismic exploration, due to its efficient or economic acquisition or both. The blended data overlapped between shot records are acquired in simultaneous source acquisition. Separating the blended data and recovering the single-shot seismic signals (the recovery) are of great importance in the scenario of current workflows, which can be called seismic simultaneous source separation. In the context of general random time-dithering firing, we propose an alternative method to separate the blended data by combining patchwise dictionary learning with sparse inversion, in which the dictionary is directly learned from the measured blended data. Apart from the sparse coding used for the coefficients, an additional regularization term on the dictionary is particularly designed to remove the severe interference noise. The efficient and flexible alternating direction method of multipliers (ADMM) is used to update the dictionary in the used alternating optimization scheme. The results obtained from the synthetic and real examples reasonably suggest that the separated seismic signals by using dictionary learning are more accurate and robust compared with that using the fixed transform basis, such as the local discrete cosine transform. The learned dictionary tailors for the recovery and is similar to the local seismic waveform, which improves the sparsity of the recovery substantially and is highly advantageous for producing the promised results.

Effects of an Auditory Lateralization Training in Children Suspected to Central Auditory Processing Disorder.

Background and ObjectivesCentral auditory processing disorder [(C)APD] refers to a deficit in auditory stimuli processing in nervous system that is not due to higher-order language or cognitive factors. One of the problems in children with (C)APD is spatial difficulties which have been overlooked despite their significance. Localization is an auditory ability to detect sound sources in space and can help to differentiate between the desired speech from other simultaneous sound sources. Aim of this research was investigating effects of an auditory lateralization training on speech perception in presence of noise/competing signals in children suspected to (C)APD.Subjects and MethodsIn this analytical interventional study, 60 children suspected to (C)APD were selected based on multiple auditory processing assessment subtests. They were randomly divided into two groups: control (mean age 9.07) and training groups (mean age 9.00). Training program consisted of detection and pointing to sound sources delivered with interaural time differences under headphones for 12 formal sessions (6 weeks). Spatial word recognition score (WRS) and monaural selective auditory attention test (mSAAT) were used to follow the auditory lateralization training effects.ResultsThis study showed that in the training group, mSAAT score and spatial WRS in noise (p value≤0.001) improved significantly after the auditory lateralization training.ConclusionsWe used auditory lateralization training for 6 weeks and showed that auditory lateralization can improve speech understanding in noise significantly. The generalization of this results needs further researches.

Fast Frequency-Domain Forward and Inverse Methods for Acoustic Scattering from Inhomogeneous Objects in Layered Media

The fast scattering and inverse scattering algorithms for acoustic wave propagation and scattering in a layered medium with buried objects are an important research topic, especially for large-scale geophysical applications and for target detection. There have been increasing efforts in the development of practical, accurate, and efficient means of imaging subsurface target anomalies. In this work, the acoustic scattering problem in layered media is formulated as a volume integral equation and is solved by the stabilized bi-conjugate gradient fast Fourier transform (BCGS-FFT) method. By splitting the layered medium Green’s function interacting with the induced source into a convolution and a correlation, the acoustic fields can be calculated efficiently by the FFT algorithm. This allows both the forward solution and inverse solution to be computed with only [Formula: see text] computation time per iteration, where [Formula: see text] is the number of degrees of freedom. The inverse scattering is solved using a simultaneous multiple frequency contrast source inversion (CSI). The stable convergence of this inversion process makes the multiple frequency simultaneous CSI reconstruction practical for large acoustic problems. Some representative examples are shown to demonstrate the effectiveness of the forward and inverse solvers for acoustic applications.

Attributing Atmospheric Methane to Anthropogenic Emission Sources.

Methane is a greenhouse gas, and increases in atmospheric methane concentration over the past 250 years have driven increased radiative forcing of the atmosphere. Increases in atmospheric methane concentration since 1750 account for approximately 17% of increases in radiative forcing of the atmosphere, and that percentage increases by approximately a factor of 2 if the effects of the greenhouse gases produced by the atmospheric reactions of methane are included in the assessment. Because of the role of methane emissions in radiative forcing of the atmosphere, the identification and quantification of sources of methane emissions is receiving increased scientific attention. Methane emission sources include biogenic, geogenic, and anthropogenic sources; the largest anthropogenic sources are natural gas and petroleum systems, enteric fermentation (livestock), landfills, coal mining, and manure management. While these source categories are well-known, there is significant uncertainty in the relative magnitudes of methane emissions from the various source categories. Further, the overall magnitude of methane emissions from all anthropogenic sources is actively debated, with estimates based on source sampling extrapolated to regional or national scale ("bottom-up analyses") differing from estimates that infer emissions based on ambient data ("top-down analyses") by 50% or more. To address the important problem of attribution of methane to specific sources, a variety of new analytical methods are being employed, including high time resolution and highly sensitive measurements of methane, methane isotopes, and other chemical species frequently associated with methane emissions, such as ethane. This Account describes the use of some of these emerging measurements, in both top-down and bottom-up methane emission studies. In addition, this Account describes how data from these new analytical methods can be used in conjunction with chemical mass balance (CMB) methods for source attribution. CMB methods have been developed over the past several decades to quantify sources of volatile organic compound (VOC) emissions and atmospheric particulate matter. These emerging capabilities for making measurements of methane and species coemitted with methane, rapidly, precisely, and at relatively low cost, used together with CMB methods of source attribution can lead to a better understanding of methane emission sources. Application of the CMB approach to source attribution in the Barnett Shale oil and gas production region in Texas demonstrates both the importance of extensive and simultaneous source testing in the region being analyzed and the potential of CMB method to quantify the relative strengths of methane emission sources.

Development of a compact scintillator-based high-resolution Compton camera for molecular imaging

The Compton camera, which shows gamma-ray distribution utilizing the kinematics of Compton scattering, is a promising detector capable of imaging across a wide range of energy. In this study, we aim to construct a small-animal molecular imaging system in a wide energy range by using the Compton camera. We developed a compact medical Compton camera based on a Ce-doped Gd3Al2Ga3O12 (Ce:GAGG) scintillator and multi-pixel photon counter (MPPC). A basic performance confirmed that for 662keV, the typical energy resolution was 7.4% (FWHM) and the angular resolution was 4.5° (FWHM). We then used the medical Compton camera to conduct imaging experiments based on a 3-D imaging reconstruction algorithm using the multi-angle data acquisition method. The result confirmed that for a 137Cs point source at a distance of 4cm, the image had a spatial resolution of 3.1mm (FWHM). Furthermore, we succeeded in producing 3-D multi-color image of different simultaneous energy sources (22Na [511keV], 137Cs [662keV], and 54Mn [834keV]).

Penning plasma based simultaneous light emission source of visible and VUV lights

In this paper, a laboratory-based penning plasma discharge source is reported which has been developed in two anode configurations and is able to produce visible and VUV lights simultaneously. The developed source has simultaneous diagnostics facility using Langmuir probe and optical emission spectroscopy. The two anode configurations, namely, double ring and rectangular configurations, have been studied and compared for optimum use of the geometry for efficient light emissions and recording. The plasma is produced using helium gas and admixture of three noble gases including helium, neon, and argon. The source is capable to produce eight spectral lines for pure helium in the VUV range from 20 to 60 nm and total 24 spectral lines covering the wavelength range 20–106 nm for the admixture of gases. The large range of VUV lines is generated from gaseous admixture rather from the sputtered materials. The recorded spectrum shows that the plasma light radiations in both visible and VUV range are larger in double ring configuration than that of the rectangular configurations at the same discharge operating conditions. To clearly understand the difference, the imaging of the discharge using ICCD camera and particle-in-cell simulation using VORPAL have also been carried out. The effect of ion diffusion, metastable collision with the anode wall and the nonlinear effects are correlated to explain the results.

A periodically varying code for improving deblending of simultaneous sources in marine acquisition

We have designed a periodically varying code that can avoid the problem of the local coherency and make the interference distribute uniformly in a given range; hence, it was better at suppressing incoherent interference (blending noise) and preserving coherent useful signals compared with a random dithering code. We have also devised a new form of the iterative method to remove interference generated from the simultaneous source acquisition. In each iteration, we have estimated the interference using the blending operator following the proposed formula and then subtracted the interference from the pseudodeblended data. To further eliminate the incoherent interference and constrain the inversion, the data were then transformed to an auxiliary sparse domain for applying a thresholding operator. During the iterations, the threshold was decreased from the largest value to zero following an exponential function. The exponentially decreasing threshold aimed to gradually pass the deblended data to a more acceptable model subspace. Two numerically blended synthetic data sets and one numerically blended practical field data set from an ocean bottom cable were used to demonstrate the usefulness of our proposed method and the better performance of the periodically varying code over the traditional random dithering code.

Performance of Virtual Full-Duplex Relaying on Cooperative Multi-path Relay Channels

We consider a cooperative multi-path relay channel (MPRC) where multiple half-duplex relays assist in the packet transmissions from a source to its destination. A virtual full-duplex (FD) relaying scheme is proposed that allows the source to transmit a new packet simultaneously with the selected best relay, with the rest of the relays attempting to decode this new packet. Thus, a new source packet can be served in each time slot, as in FD relay systems. Taking into account the effect of inter-relay interference (IRI) that is caused by simultaneous relay and source transmissions, a Markov chain analytical model is used to characterize the decoding performance at the relays, based on which the overall outage probability of MPRC is obtained in closed-form expressions. The asymptotic performance analysis reveals that in low rate scenarios, a close-to-full diversity order is achieved by the proposed scheme while substantially improving the spectrum efficiency. In high rate scenarios, the decoding performance of relays is limited by IRI and the system outage performance experiences an error floor. Simulation results demonstrate the performance gains of the proposed scheme by comparisons with existing half-duplex and FD relay systems in the literature.

Lithium- and boron-bearing brines in the Central Andes: exploring hydrofacies on the eastern Puna plateau between 23° and 23°30′S

Internally drained basins of the Andean Plateau are lithium- and boron-bearing systems. The exploration of ionic facies and parental links in a playa lake located in the eastern Puna (23°–23°30′S) was assessed by hydrochemical determinations of residual brines, feed waters and solutions from weathered rocks. Residual brines have been characterized by the Cl− (SO4 =)/Na+ (K+) ratio. Residual brines from the playa lake contain up to 450 mg/l of boron and up to 125 mg/l of lithium, and the Las Burras River supplies the most concentrated boron (20 mg/l) and lithium (3.75 mg/l) inflows of the basin. The hydro-geochemical assessment allowed for the identification of three simultaneous sources of boron: (1) inflow originating from granitic areas of the Aguilar and Tusaquillas ranges; (2) weathering of the Ordovician basement; and (3) boron-rich water from the Las Burras River. Most of the lithium input of the basin is likely generated by present geothermal sources rather than by weathering and leaching of ignimbrites and plutonic rocks. However, XRD analyses of playa lake sediments revealed the presence of lithian micas of clastic origin, including taeniolite and eucriptite. This study is the first to document these rare Li-micas from the Puna basin. Thus, both residual brines and lithian micas contribute to the total Li content in the studied hydrologic system.