Direct Sequential Co-simulation with Joint Probability Distributions

The practice of stochastic simulation for different environmental and earth sciences applications creates new theoretical problems that motivate the improvement of existing algorithms. In this context, we present the implementation of a new version of the direct sequential co-simulation (Co-DSS) algorithm. This new approach, titled Co-DSS with joint probability distributions, intends to solve the problem of mismatch between co-simulation results and experimental data, i.e. when the final biplot of simulated values does not respect the experimental relation known for the original data values. This situation occurs mostly in the beginning of the simulation process. To solve this issue, the new co-simulation algorithm, applied to a pair of covariates Z ₁(x) and Z ₂(x), proposes to resample Z ₂(x) from the joint distribution F(z ₁,z ₂) or, more precisely, from the conditional distribution of Z ₂(x ₀), at a location x ₀, given the previously simulated value z₁^(l)(x₀)z_{1}^{(l)}(x_{0}) (F(Z₂|Z₁=z₁^(l)(x₀)F(Z_{2}|Z_{1}=z_{1}^{(l)}(x_{0}) ). The work developed demonstrates that Co-DSS with joint probability distributions reproduces the experimental bivariate cdf and, consequently, the conditional distributions, even when the correlation coefficient between the covariates is low.     

Element-Enrichment Factors in Lichens from Terceira, Santa Maria and Madeira Islands (Azores and Madeira Archipelagoes)

In this study, more than 20 minor and trace elements have been determined by INAA (instrumental neutron activation analysis), in different species of lichens in three Portuguese islands of the Central North Atlantic (Santa Maria, Terceira, and Madeira Islands). The foliose species Parmotrema bangii, Parmotrema robustum, Parmotrema crinitum, Flavoparmelia caperata, Platismatia glauca, and the fruiticose species Ramalina canariensis, Ramalina farinacea, Ramalina implectens, Ramalina pusilla, Cladonia furcata, Cladonia coniocraea, Usnea dasaea, Usnea esperantiana, were the collected species. Samples of superficial soils were also collected and the fraction below 64 m was analysed. The enrichment factors relative to this fraction using Al as the normalising element were calculated. Fruiticose and foliose lichens displayed different EF values concerning bromine and potassium. The first was more enriched in the foliose species while the latter was more enriched in the fruiticose species and was assigned to the physiological response. Enrichment was found for Mg, Cs, As, Hg, Na, Zn, and Cl, in all the species. Lichen-based concentration patterns were shown for Na, Al, Cl, Br, Sb, Ce, and Hg and compared to similar patterns in Portugal mainland. In general, the patterns compared well except for Cl, Na, and Br. Background levels of the epiphytic lichens collected in the islands were obtained.     

Hypsometric Curves as a Tool for Paleosurface Mapping

A procedural paleosurface mapping tool, using hypsometric curves and digital elevation models, was developed and applied to three hydrographic basins that erode common areas in the coastal ranges of Brazil, in southeastern South America. The method consists of identifying areas favorable for the occurrence of paleosurfaces and their corresponding surficial formations as correlated to specific erosion events. Attributes from hypsometric curves, and logarithmic functions fitted to proper curve segments, are combined with common morphometric properties of paleosurfaces given a set of criteria. Zones satisfying the criteria are mapped as pertaining to specific paleosurfaces. Field survey confirms the agreement between predicted and observed occurrence and absence of paleosurfaces.     

Bayesian and multivariate methods applied to favorability quantification in Recôncavo Basin and Ribeira Belt, Brazil

A methology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system’s largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methdology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs.     

Experimental evidence of the transition between power law models in the high frequency range of the gravity wave spectrum

The existence of a transition in the slope of the wind-generated gravity wave spectrum from a f⁻⁴ to a f⁻⁵ power law, at a given frequency in the high frequency range, is examined. Evidence of its existence and of the non-uniqueness of the wave spectrum slope in the equilibrium range is presented. Furthermore, it is demonstrated that the statistical variability of the spectral estimates makes it difficult to obtain reliable results from limited sets of finite length wave records.     

Geostatistical seismic Amplitude‐versus‐angle inversion

Seismic inversion plays an important role in reservoir modelling and characterisation due to its potential for assessing the spatial distribution of the sub‐surface petro‐elastic properties. Seismic amplitude‐versus‐angle inversion methodologies allow to retrieve P‐wave and S‐wave velocities and density individually allowing a better characterisation of existing litho‐fluid facies. We present an iterative geostatistical seismic amplitude‐versus‐angle inversion algorithm that inverts pre‐stack seismic data, sorted by angle gather, directly for: density; P‐wave; and S‐wave velocity models. The proposed iterative geostatistical inverse procedure is based on the use of stochastic sequential simulation and co‐simulation algorithms as the perturbation technique of the model parametre space; and the use of a genetic algorithm as a global optimiser to make the simulated elastic models converge from iteration to iteration. All the elastic models simulated during the iterative procedure honour the marginal prior distributions of P‐wave velocity, S‐wave velocity and density estimated from the available well‐log data, and the corresponding joint distributions between density versus P‐wave velocity and P‐wave versus S‐wave velocity. We successfully tested and implemented the proposed inversion procedure on a pre‐stack synthetic dataset, built from a real reservoir, and on a real pre‐stack seismic dataset acquired over a deep‐water gas reservoir. In both cases the results show a good convergence between real and synthetic seismic and reliable high‐resolution elastic sub‐surface Earth models.     

Longitudinal variability of the equatorial counter electrojet during the solar cycle 24

Studia Geophysica et Geodaetica - Ground and space-based geomagnetic data were used in the investigation of the longitudinal, seasonal and lunar phase dependence of the equatorial counter...     

The influence of shrimp farms organic waste management on chemical water quality

We evaluated the physical–chemical properties and nutrient concentrations in two shrimp ponds under conventional management, intensive (I-P) and semi-intensive (SI-P), and one under organic management (O-P), three days after loading and before stoking. The mean’s total alkalinity concentrations were 2.26 ± 0.04 mM, 2.28 ± 0.01 mM and 2.59 ± 0.01 mM, respectively for I-P, SI-P and O-P. Bicarbonate and carbonate accounted for 62% and 37% in I-P, 64% and 36% in SI-P and 83–17% in O-P, respectively. Aragonite and calcite were oversaturated around Ω = 5. Mean total phosphate (TP) concentrations were 441.37 ± 92.06 μg/L, 449 ± 48 μg/L and 473.64 ± 84.17 μg/L, under I-P SI-P and O-P management respectively. Following this sequence, NO₃⁻ concentration was 2.98 ± 0.7 μg/L, 1.16 ± 0.16 μg/L and 0.32 ± 0.12 μg/L, under I-P, SI-P and O-P management respectively. Thus, the data suggest that different management of farm organic waste leads to different chemical water quality.     

Kalman filtering of vessel motions for ocean wave directional spectrum estimation

This paper proposes a high-speed iterative procedure for estimating the ocean wave directional spectrum from vessel motion data. It uses as input data, the measurements from motion sensors that are commonly available on dynamically positioned vessels and which may easily be installed on any ship. Because the necessary sensors are relatively inexpensive or may already be installed, it becomes an ideal solution to provide initial estimates to offline estimation procedures and to give spectral updates under quickly changing weather conditions. The Kalman filtering algorithm, for iterative harmonic detection, and frequency domain vessel response data are used in the estimation procedure. The results and conclusions are still based on synthesized data, but very promising.