Denoising and improving the quality of seismic data using combination of DBM filter and FX deconvolution

Seismic data denoising, random noise attenuation (RNA) and spike-like noise suppression, is a main consideration for improving the quality of records. RNA could increase signal to noise ratio (S/N) to avoid misinterpretation of seismic data. In this research, a novel method is created by using the combination of frequency-offset deconvolution (FXD) and decision-based median (DBM) filter for RNA from seismic data. The method is applied in two main phases; FXD is focused to remove the Gaussian noise and DBM filter is focused to attenuate the impulsive noise and spikes. To implement and verify the method, three types of data are used: two synthetic models (a model with linear events and a model with hyperbolic events) and an observed seismic section. The ability of the proposed method (FXD-DBM) in comparison of applying each in seismic RNA application is proven. The noise level is reduced obviously, and hence, the S/N of all examined seismic records is increased considerably after denoising by the combination of FX deconvolution and DBM filter. About the real seismic section, suppressing random noise and spikes show up improving the seismic reflector continuity and hence enhancing the interpretability of data. Moreover, some masked events by random noise are clarified in different parts of data after denoising using the planned method.     

Paleoenvironmental reconstruction using biological markers for the Upper Triassic-Middle Jurassic sedimentary succession in Tabas Basin, central Iran

The Upper Triassic-Middle Jurassic sedimentary succession in the Tabas Basin, with a thickness of about 1600 m, provides a case showing geochemical property changes through the Triassic-Jurassic boundary. The studied section (Kamarmacheh Kuh) is composed of the marine Nayband Formation (Norian-Rhaetian) overlain by siliciclastic sediments of Ab-e-Haji Formation (Lower Jurassic-Aalenian). Detailed geochemical analyses were conducted on selected samples from both formations and the results were used to infer paleo-depositional conditions. Most of the studied samples contain <1 wt% TOC composed mostly of oxidized organic matter with insignificant generative potential. Extract analysis of four representative samples indicate that the rocks also contain minor amounts of preserved algal organic matter along with a secondary contribution of higher plant organic matter from the adjacent watershed. Biomarker analyses show subtle variations in the relative contribution of land plant material that are consistent with the widespread occurrence of coal seams in the upper parts of the Nayband and basal parts of the Ab-e-Haji formations. Although the samples from the Kamarmacheh Kuh Section have low source potential, the extractable hydrocarbons indicate that conditions existed that were conducive to organic matter preservation and that regions of the Tabas Basin with higher primary productivity or lower sedimentation rates may have greater potential.     

Time-frequency decomposition of seismic signals via quantum swarm evolutionary matching pursuit

Matching pursuit belongs to the category of spectral decomposition approaches that use a pre-defined discrete wavelet dictionary in order to decompose a signal adaptively. Although disengaged from windowing issues, matching point demands high computational costs as extraction of all local structure of signal requires a large size dictionary. Thus in order to find the best match wavelet, it is required to search the whole space. To reduce the computational cost of greedy matching pursuit, two artificial intelligence methods, (1) quantum inspired evolutionary algorithm and (2) particle swarm optimization, are introduced for two successive steps: (a) initial estimation and (b) optimization of wavelet parameters. We call this algorithm quantum swarm evolutionary matching pursuit. Quantum swarm evolutionary matching pursuit starts with a small colony of population at which each individual, is potentially a transformed form of a time-frequency atom. To attain maximum pursuit of the potential candidate wavelets with the residual, the colony members are adjusted in an evolutionary way. In addition, the quantum computing concepts such as quantum bit, quantum gate, and superposition of states are introduced into the method. The algorithm parameters such as social and cognitive learning factors, population size and global migration period are optimized using seismic signals. In applying matching pursuit to geophysical data, typically complex trace attributes are used for initial estimation of wavelet parameters, however, in this study it was shown that using complex trace attributes are sensitive to noisy data and would have lower rate of convergence. The algorithm performance over noisy signals, using non-orthogonal dictionaries are investigated and compared with other methods such as orthogonal matching pursuit. The results illustrate that quantum swarm evolutionary matching pursuit has the least sensitivity to noise and higher rate of convergence. Finally, the algorithm is applied to both modelled seismograms and real data for detection of low frequency anomalies to validate the findings.     

Sequence signal processing of 2012 Ahar–Varzaghan earthquake (<Emphasis Type="Italic">M</Emphasis><Subscript>W</Subscript> 6.4) of NW Iran

Before starting seismic cycle of Ahar–Varzaghan 2012 event, a partial gap in the form of a pre-seismic calm sequence (seismicity rate, r = 0.46 event/year, b = 1.4) with duration of 303 days spatially has dominated over the entire seismogenic area. From April 17, 2012, to May 31, 2012, r significantly increased to 2.16, indicating strong foreshock sequence, and b value changed to 1.9, remarkably. In the last two months before the mainshock, foreshocks have partially migrated toward the earthquake fault (with a decrease in size, b = 2.0). Significantly, high rate of seismicity and low V _P /V _S (1.64) in the foreshocks sequence and also very high seismicity rate (17.3) and high V _P /V _S (1.76) in the aftershocks sequence make substantial differences between the seismic cycle and the background seismicity. Moreover, a significant E–W migration of the microseismicity was confirmed in the study area.     

Assessing the influence of watershed characteristics on soil erosion susceptibility of Jhelum basin in Kashmir Himalayas

Soil erosion, a serious environmental problem, is a global challenge. Once a portion of a fertile soil is lost, it is very difficult to replace it, and this leads to decrease in crop production, damage to drainage networks, and siltation of dams and reservoirs. Human practices like intensive agriculture, overgrazing, and deforestation have intensified the rate of soil erosion all over the world. The Jhelum basin which forms the north-western part of the complex mountain system Himalayas is not only highly vulnerable to natural hazards like earthquakes, landslides, and floods but is also highly susceptible to soil erosion. There is an immediate need to device strategies to reduce adverse impacts of soil erosion and to conserve natural resources like soil, water, and forests by means of proper watershed management programs in the Himalayan region. The present study is carried out for eight upper watersheds of Jhelum basin, an area which are facing serious issues like boulder extraction, deforestation, and unplanned urbanization. The present work demonstrates the use of morphometry, land use, and slope coupled with the multicriteria analytical (MCA) framework to estimate the soil erosion susceptibility of these watersheds using Remote Sensing and Geographical Information System techniques. The present study revealed that out of eight upper watersheds, Arapal, Lidder, and Bringi fall in high priority and need immediate attention and measures to reduce soil erosion in the area. Sandran, Rembiara, and Romshii fall in medium priority. Kuthar and Vishav fall in the low-priority category and are least susceptible to soil erosion.     

Hydrochemistry, mineralogy and chemical fractionation of mine and processing wastes associated with porphyry copper mines: A case study from the Sarcheshmeh mine, SE Iran

The Sarcheshmeh is one of the largest Oligo-Miocene porphyry Cu deposits in the world. Comparative hydrochemical, mineralogical and chemical fractionation associated with mining efflorescence salts and processing wastes of this mine are discussed. Hydrochemical results showed that rock waste dumps, reject wastes and old impoundments of tailings are the main sources of acid mine drainage waters (AMD) that contain potentially toxic metals such as Cd, Co, Cu, Mn, Ni and Zn as well as Al. Episodic fluxes of highly contaminated acidic waters were produced in a tailings dam over a short period of time. Secondary soluble minerals provide important controls on the quality of AMD produced, especially in old, dry tailings impoundments. Secondary sulfate minerals such as gypsum, magnesiocopiapite, hydronium jarosite, kornelite and coquimbite were found in rock waste drainages and in old weathered reject wastes. Highly soluble secondary minerals such as gypsum, eriochalcite, and bonattite are also observed in an evaporative layer on old tailings impoundments. Chemical fractionation patterns of potentially toxic elements showed that the geochemical behavior of metals is primarily controlled by the mineralogical composition of waste samples. Elements such as Co, Cr, Cu, Mn, Ni and Zn are readily released into the water soluble fraction from efflorescence salts associated with rock waste drainages, as well as from the evaporative layer of old tailings. Potentially toxic elements, such as As, Mo and Pb, are principally adsorbed or co-precipitated with amorphous and crystalline Fe oxides, but they may also be associated with oxidizing, primary sulfides and residual fractions. Following the development of the dammed tailings pond, the secondary minerals were dissolved, producing acidic waters contaminated by Al (154 mg L⁻¹), Cu (150 mg L⁻¹), Cd (0.31 m gL⁻¹), Co (2.13 mg L⁻¹), Mn (73.7 mg L⁻¹), Ni (1.74 mg L⁻¹), Zn (20.3 mg L⁻¹) and Cl (1690 mg L⁻¹). Therefore, the potential use of recycled water from the Sarcheshmenh dammed tailings pond is diminished by the presence of corrosive ions like Cl⁻ in highly acidic fluids that promote corrosion of pipes and pumps in the water recycling system.     

Modélisation de la relation pluie-ruissellement par durée d'épisode pluvieux dans un bassin du nord de la Tunisie

Résumé

Un modèle hydrologique global a été calé sur des épisodes pluvieux de durée très variable (de un à plus de dix jours). Les épisodes pris en compte sont ceux qui sont encadrés par au moins un jour sec et ne provoquant pas de déversement du barrage. L'entrée de ce modèle comprend la pluie moyenne du bassin versant et l'indice des précipitations antérieures de Kohler & Linsley. Les expressions du modèle hydrologique du début et au cours de la saison humide, selon un seuil du cumul des pluies de la saison depuis le début de l'automne, sont de la forme non linéaire polynomiale du second ordre. Le modèle s'est montré performant dans l'évaluation de la lame ruisselée malgré le faible nombre de postes pluviométriques (un) pour la taille du bassin versant de 48 km². L'absence d'autres postes pluviométriques sur le bassin versant n'a pas permis d'étudier la précision du modèle en considérant une pluie moyenne sur le bassin versant au lieu de la pluie uniquement au site du Barrage Ghézala.

Citation Mathlouthi. M. & Lebdi, F. (2010) Modélisation de la relation pluie–ruissellement par durée d'épisode pluvieux dans un bassin du nord de la Tunisie. Hydrol. Sci. J. 55(7), 1111–1122.