Marcelo Monteiro da Rocha

Relationship between first polar body morphology before intracytoplasmic sperm injection and fertilization rate, cleavage rate, and embryo quality

To evaluate the influence of the morphology of the first polar body (PB) on intracytoplasmic sperm injection (ICSI) outcomes.

Comparison Between Kriging Variance and Interpolation Variance as Uncertainty Measurements in the Capanema Iron Mine, State of Minas Gerais—Brazil

The Capanema Mine, an iron ore deposit, is located in the central portion of the Quadrilátero Ferrífero, State of Minas Gerais, southeastern Brazil. Mine development data from approximately 7000 drillholes were used for a comparative study between kriging variance and interpolation variance as uncertainty measurements associated with ordinary kriging estimates. As known, the traditional kriging variance does not depend on local data and, therefore, does not measure the actual dispersion of data. On the other hand, the interpolation variance measures adequately the local dispersion of data used for an ordinary kriging estimate. This paper presents an application of the concept of interpolation variance for measuring uncertainties associated with ordinary kriging estimates of Fe and silica grades. These data were selected for their distinct statistical characteristics with Fe presenting a negatively skewed distribution and, consequently, a low dispersion, and silica a positively skewed distribution and, therefore, a high variability. Comparative studies between the two uncertainty measurements associated with ordinary kriging estimates of Fe and silica proved the superiority of the interpolation variance as a reliable and precise alternative to the kriging variance.

Aplicação de krigagem com correção do efeito de suavização em dados de potenciometria da cidade de Pereira Barreto - SP

This work deals with geostatistical analysis and the estimation of hydraulic head data using two methods: ordinary kriging and kriging with correction of the smoothing effect. Both methods were applied in order to verify which one better reproduces the potentiometric surface of Pereira Barreto - SP. The data were drawn from the Tres Irmaos Reservoir, and are composed of 186 sample points with hydraulic head information, measured during the installation of the dam. The studied variable presented non stationary semivariograms, interpreted as the result of a regional drift. To remove this drift a first-degree polynomial surface was computed, and geostatistics evaluated the residuals. The kriging procedure with correction of the smoothing effect gives a more faithful reproduction of the potentiometric data, since the variance was greater than that obtained by ordinary kriging.

Studying the influence of a secondary variable in Collocated Cokriging estimates

In this paper the influence of a secondary variable as a function of the correlation with the primary variable for collocated cokriging is examined. For this study five exhaustive data sets were generated in computer, from which samples with 60 and 104 data points were drawn using the stratified random sampling method. These exhaustive data sets were generated departing from a pair of primary and secondary variables showing a good correlation. Then successive sets were generated by adding an amount of white noise in such a way that the correlation gets poorer. Using these samples, it was possible to find out how primary and secondary information is used to estimate an unsampled location according to the correlation level.

Groundwater Level Prediction/Forecasting and Assessment of Uncertainty Using SGS and ARIMA Models: A Case Study in the Bauru Aquifer System (Brazil)

Best water management practices should involve the prediction of the availability of groundwater resources. To predict/forecast and consequently manage these water resources, two known methods are discussed: a time series method using the autoregressive integrated moving average (ARIMA) and a geostatistical method using sequential Gaussian simulation (SGS). This study was conducted in the Ecological Station of Santa Barbara (EEcSB), located at the Bauru Aquifer System domain, a substantial water source for the countryside of São Paulo State, Brazil. The relevance of this study lies in the fact that the 2013/2014 hydrological year was one of the driest periods ever recorded in São Paulo State, which was directly reflected in the groundwater table level behavior. A hydroclimatological network comprising 49 wells was set up to monitor the groundwater table depths at EEcSB to capture this response. The traditional time series has the advantage that it has been created to forecast and the disadvantage that an interpolation method must also be used to generate a spatially distributed map. On the other hand, a geostatistical approach can generate a map directly. To properly compare the results, both methods were used to predict/forecast the groundwater table levels at the next four measured times at the wells’ locations. The errors show that SGS achieves a slightly higher level of accuracy and considered anomalous events (e.g., severe drought). Meanwhile, the ARIMA models are considered better for monitoring the aquifer because they achieved the same accuracy level as SGS in the 2-month forecast and a higher precision at all periods and can be optimized automatically by using the Akaike information criterion.

Simulation-based risk quantification: a reconciliation-based performance analysis

Abstract Recent studies have demonstrated the utilisation of stochastic simulation to quantify uncertainty in mineral deposits and allowing better management of the geological risk during mining scheduling. This paper describes an approach to evaluate the suitability of stochastically simulated models to characterise the real, but unknown, deposit represented in this study by an orebody model geostatistical estimate based on an extensive grade control drilling data-set. Traditional reconciliation techniques and the related mine call factors (or indicators) are evaluated against uncertainty measures derived from the set of stochastically simulated models. A case study carried out at the main mineral deposit of the Sossego copper mine in Brazil is presented in order to illustrate the practical aspects of the approach and how this approach is validated by traditional reconciliation studies using historical data of a mined out part of the orebody.

Krigagem indicadora aplicada aos litotipos do depósitode Ni-Cu de Americano do Brasil, GO

Este trabalho apresenta o modelo geologico gerado a partir da estimativa de litologias por krigagem de variaveis indicadoras. A base de dados utilizada e composta de amostras de furos de sondagem proveniente do deposito de Americano do Brasil, GO, uma suite de rochas mafico-ultramaficas com mineralizacao sulfetada niquel-cuprifera associada. A variavel abordada foi a descricao litologica, que compreende informacoes categoricas e qualitativas. O modelo geologico estimado e util no entendimento das relacoes geometricas e estratigraficas dos corpos rochosos de onde pode-se concluir que a krigagem de variaveis indicadoras e uma interessante alternativa para auxiliar estudos de avaliacao de depositos minerais.