The marine Paleocene and Ypresian deposits of Tunisia, within the El Haria Formation and the Metlaoui Group, have been intensively studied because of the commercial interest in phosphates and hydrocarbons. This paper presents the latest updates of isochron, lithofacies and palaeogeographical maps, and interprets the patterns identified in light of synsedimentary structure. This reveals a close association between structure, basin geometry and subsidence. Facies distribution during the Early Paleogene is thought to be structurally controlled along basement lineaments. These major fault systems were reactivated several times during the Mesozoic and Tertiary, with the last movements occurring as Neogene and post-Villafranchian events. The structural control of facies is most evident during the Ypresian, particularly along the ‘North-South Axis’ (Nosa) a sub-meridian orogenic segment of Central Tunisia. In this area the Ypresian deposits exhibit a preferred alignment with the Nosa exerting a notable influence on basin geometries and rates of local subsidence. In addition to two large islands indicated in the onshore area of Tunisia, a number of ‘bald’ highs are identified in the offshore, representing original submarine highs. The general pattern across Tunisia throughout the period is of a number of small tectonically controlled basins. The distribution of phosphorites, organic-rich shales and evaporites can be particularly linked to the development of restricted basins during the period.
Upper Paleocene to Lower Eocene phosphates of the Jebel Oum El Khecheb profile (Gafsa-Metlaoui Basin GMB, Tunisia) are mostly composed of brown phospharenites lithified or not, granular, with pellets, coproliths, bone clasts and fish teeth. The matrix in analyzed samples is reduced and constituted of various clay minerals (dominantly smectites, palygorskite, sepiolite and rare kaolinite), opal-CT and carbonates. Clinoptilolite is recognized along the series; very few amounts of quartz and feldspar grains are sparsely present. The phosphate mineral is a carbonate-fluorapatite (CFA) sulphated, sodic enriched in strontium and rare earth elements (REE). Statistical analyses of mineralogical and geochemical data highlight the associated elements in the main mineral lattice. In the CFA, the group is composed of CaO-P 2 O 5 -Na 2 O-SO 3 -F-Sr-Th-REE-U-Ba-Zr-Cr. In the silicates, the group contains SiO 2 -Al 2 O 3 -Fe 2 O 3 -MgO-K 2 O-Na 2 O-TiO 2 -Co-Cs-Rb-Sc-Ta-Sb-Mo-As and Cu. Sulphides are represented by Zn and Cd; iron oxides by mainly Fe and Ni. Dolomite and gypsum are present; SO 3 is contained in the latter, but CFA may also have some of this radical in its structure. The Upper Continental Crust (UCC) normalized REE patterns present a variably negative Ce-anomaly, suggesting that the imprint of the marine genesis environment is very well-preserved in the main phosphatic units. Positive-Eu and negativeSm anomalies were detected in some samples. The fractionation of light-REE to heavy-REE, represented by the La/Yb ratio of untreated values varies between 8.28 and 12.94, somewhat less than UCC value (13.64). Enrichment of HREE is due to phosphates. Both ratios reflect the marine genesis environment wherein the formation of the CFA took place in a confined and oxygen poor environment. Then the CFA removed the REE and the trace elements present from the interstitial waters, as was proposed for the various phosphatic basins of Tunisia.
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In this paper, we have evaluated various methods of time-frequency-selective fading channels estimation in OFDM system and some of them improved under time varying conditions. So, these different techniques will be studied through different algorithms and for different schemes of modulations (16 QAM, BPSK, QPSK,…).Channel estimation gathers different schemes and algorithms, some of them are dedicated for slowly time varying (such as block type arrangement insertion, Bayesian Cramer-Rao Bound, Kalman estimator, Subspace estimator,…) whereas the others concern highly time varying channels (comb type insertion,…) . There are others methods that are just suitable for stationary channels like blind or semi blind estimators. For this aim, diverse algorithms were used for these schemes such as Least Squares estimator LS, Least Minimum Squares LMS, Minimum Mean-Square-ErrorMMSE, Linear Minimum Mean-Square-Error LMMSE, Maximum Likelihood ML,…to refine estimators shown previously.
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