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Arthur Ayres Neto Vanessa Alves da Costa Clara Pinto Ferreira Maia Porto Thais Cristina Vargas Garrido Jean-Pierre Hermand 《Marine Georesources & Geotechnology》2020,38(4):437-449
AbstractMarine mining is the ocean’s new exploration frontier, and polymetallic crusts (PMCs) and ferromanganese nodules are considered a strategic resource for the future. Acoustic geophysical methods are a valuable tool for oceanic research and have been employed for several decades in the exploration of marine resources and environmental evaluations. The main objective of this work was to investigate the correlation between the chemical composition of PMCs from three different areas along the Brazilian continental margin and their physico-acoustic attributes (P-wave velocity, density and acoustic impedance). The results show that the geoacoustic properties of PMCs are correlated to their chemical composition. Measurements showed positive and negative trends between acoustic impedance and studied elements (Fe, Mn, Co, Cu, Zn, W and Ni) according to the direction of measurement, indicting high anisotropy levels. Our study sheds initial light on the correlation between acoustic properties and metal content of PMCs. The study facilitates assessments of the acoustic responses of PMCs allowing more efficient prospection and exploitation compared to ship-board geophysical techniques that are too qualitative to identify PMCs. The results can contribute to determining the best procedures and techniques for more efficient future exploration of this resource. 相似文献
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Geostatistical estimations of the hydraulic conductivity field (K) in the Carrizo aquifer, Texas, are performed over three regional domains of increasing extent: 1) the domain corresponding
to a three-dimensional groundwater flow model previously built (model domain); 2) the area corresponding to the 10 counties
encompassing the model domain (County domain), and; 3) the full extension of the Carrizo aquifer within Texas (Texas domain).
Two different approaches are used: 1) an indirect approach where transmissivity (T) is estimated first and K is retrieved through division of the T estimate by the screen length of the wells, and; 2) a direct approach where K data are kriged directly. Due to preferential well screen emplacement, and scarcity of sampling in the deeper portions of
the formation (> 1 km), the available data set is biased toward high values of hydraulic conductivities. Kriging combined
with linear regression, simple kriging with varying local means, kriging with an external drift, and cokriging allow the incorporation
of specific capacity as secondary information. Prediction performances (assessed through cross-validation) differ according
to the chosen approach, the considered variable (log-transformed or back-transformed), and the scale of interest. For the
indirect approach, kriging of log T with varying local means yields the best estimates for both log-transformed and back-transformed variables in the model domain.
For larger regional scales (County and Texas domains), cokriging performs generally better than other kriging procedures when
estimating both (log T)∗ and T∗. Among procedures using the direct approach, the best prediction performances are obtained using kriging of log K with an external drift. Overall, geostatistical estimation of the hydraulic conductivity field at regional scales is rendered
difficult by both preferential well location and preferential emplacement of well screens in the most productive portions
of the aquifer. Such bias creates unrealistic hydraulic conductivity values, in particular, in sparsely sampled areas. 相似文献