Al Huwaysah 010: The most reduced brachinite,so far

Al Huwaysah 010 is an ungrouped achondrite meteorite, recently referred to as a brachinite-like meteorite. This meteorite, showing a fine-grained assemblage of low-Ca pyroxene and opaque phases, is strongly reduced in comparison to other reduced brachinites. The occurrence of some tiny plates of graphite and oldhamite in this meteorite suggests that a partial melt residue has experienced a further reduction process. Olivine, the most abundant phase, is compositionally homogeneous (Fo_83.3) as well as the clinopyroxene (En_45.5Fs_10.8Wo_43.7) and the plagioclase (Ab_69.5). Orthopyroxene (En_85.4Fs_13.9Wo_0.7) also occurs but only in a fine intergrowth. Other accessory phases are Fe metal grains (Ni-free or Cr-bearing Fe-Ni alloy), troilite, chlorapatite, pentlandite (as inclusions in chromite). The sample shows two different closure temperatures: the highest (≈900°C) is determined via the olivine–chromite intercrystalline geothermometer and the lowest temperature (≈520°C) is determined via the pyroxene-based intracrystalline geothermometer. These temperatures may represent, respectively, the closure temperature associated with the formation and a subsequent impact event excavating the sample from the parental body. The visible to near-infrared (VNIR) reflectance spectra of Al Huwaysah 010 exhibit low reflectance, consistent with the presence of darkening components, and weak absorptions indicative of olivine and pyroxene. Comparing the spectral parameters of Al Huwaysah 010 to potential parent bodies characterized by olivine–pyroxene mineralogy, we find that it falls within the field previously attributed to the SIII type asteroids. These results lead us to classify the Al Huwaysah 010 meteorite as the most reduced brachinite, whose VNIR spectral features show strong affinities with those of SIII asteroids.     

Atmospheric Deposition of Trace Elements in Romania Studied by the Moss Biomonitoring Technique

The first systematic study in Romania of atmospheric pollution from heavy metals and other toxic elements based on moss analysis was undertaken as a Romanian–Russian–Norwegian collaboration, primarily in order to assess the general state of heavy metal pollution in Romania. An additional goal was to contribute to the European heavy metals in mosses survey, conducted under the auspices UNECE ICP Vegetation which reports to the Working Group of Effects of the Long-range Transboundary Air Pollution Convention. Samples of the moss species Hypnum cupressiforme, Hylocomium splendens and Brachytechium salebrosum and B. rutabulum were collected during the period 1995–2001. A total of 40 elements were determined using NAA and AAS. The total concentrations of arsenic, cadmium, copper, nickel, vanadium and zinc are presented in the form of contour maps. Generally, the observed concentrations in Romania are markedly higher than those observed in most other countries of Europe using the moss technique.     

Non-ENSO interannual rainfall variability in central Chile during austral winter

The first principal component (PC1) of seasonal rainfall anomalies in central Chile during winter (June–August) is used to analyze the circulation anomalies related to wet and dry conditions, when near-normal or neutral SST anomalies are observed in the equatorial Pacific, i.e., during non-ENSO conditions. Eight wet and eight dry winter seasons were defined as the upper and lower terciles of PC1 for 24 non-ENSO winters in the period 1958–2000. Unlike the single process attributed to ENSO, during non-ENSO winter seasons, there are several sources triggering or modifying the propagation of the stationary waves that impact the rainfall regime in central Chile. Unfortunately, the multiple processes that seem to be involved in the modulation of the interannual rainfall variability in central Chile, as seen in this work, limit the predictability of rainfall during non-ENSO conditions.     

Parameter identification of minifrac numerical tests using a gradient boosting-based proxy model and genetic algorithm

In recent years, the petroleum industry has devoted considerable attention to studying fluid flow inside fracture channels due to the discovery of naturally fractured reservoirs. The behavior prediction of these reservoirs is a well-known challenging task, in which the initial stage consists of identifying reservoir hydromechanical parameters. This work proposes an artificial intelligence-based approach to identify hydromechanical parameters from borehole injection pressure curves acquired through minifrac tests. This approach combines proxy modeling with a stochastic optimization algorithm to match observed and predicted borehole pressure curves. Therefore, a gradient boosting-based proxy model is built to predict borehole pressure curves, considering a proper strategy to develop time series modeling. Moreover, a Bayesian optimization algorithm is applied to compute the gradient boosting hyperparameters. In this optimization scenario, this paper proposes an appropriate objective function established from the assumed time series prediction strategy and the k-fold cross-validation. Finally, a genetic algorithm is adopted to identify unknown hydromechanical parameters, solving an inverse problem. Based on the proposed workflow, a study of the importance of the hydromechanical parameters is developed. To assess the methodology applicability, the approach is employed to identify parameters in synthetic and field minifrac tests. The results present how this approach can adequately identify hydromechanical parameters of hydraulic fracturing problems.