Experimental verification of effective anisotropic crack theories in variable crack aspect ratio medium

Physical modelling of cracked/fractured media using downscaled laboratory experiments has been used with great success as a useful alternative for understanding the effect of anisotropy in the hydrocarbon reservoir characterization and in the crustal and mantle seismology. The main goal of this work was to experimentally verify the predictions of effective elastic parameters in anisotropic cracked media by Hudson and Eshelby–Cheng's effective medium models. For this purpose, we carried out ultrasonic measurements on synthetic anisotropic samples with low crack densities and different aspect ratios. Twelve samples were prepared with two different crack densities, 5% and 8%. Three samples for each crack density presented cracks with only one crack aspect ratio, whereas other three samples for each crack density presented cracks with three different aspect ratios in their composition. It results in samples with aspect ratio values varying from 0.13 to 0.26. All the cracked samples were simulated by penny‐shaped rubber inclusions in a homogeneous isotropic matrix made with epoxy resin. Moreover, an isotropic sample for reference was constructed with epoxy resin only. Regarding velocity predictions performed by the theoretical models, Eshelby–Cheng shows a better fit when compared with the experimental results for samples with single and mix crack aspect ratio (for both crack densities). From velocity values, our comparisons were also performed in terms of the ε, γ, and δ parameters (Thomsen parameters). The results show that Eshelby–Cheng effective medium model fits better with the measurements of ε and γ parameters for crack samples with only one type of crack aspect ratio.     

Synthetic scenario generation of monthly streamflows conditioned to the El Niño–Southern Oscillation: application to operation planning of hydrothermal systems

Stochastic Environmental Research and Risk Assessment - The Brazilian Interconnected Power System is hydro dominated and characterized by large reservoirs presenting multi-year regulation...     

Geostatistical facies simulation with geometric patterns of a petroleum reservoir

During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.     

Field Trials of Chaotic Advection to Enhance Reagent Delivery

Chaotic advection is a novel approach that has the potential to enhance contact between an injected reagent and target contaminants, and thereby improve the effectiveness of in situ treatment technologies. One configuration that is capable of generating chaotic advection is termed the rotated potential mixing (RPM) flow. A conventional RPM flow system involves periodically reoriented dipole flow driven by transient switching of pressures at a series of radial wells. To determine whether chaotic advection can be engineered using such an RPM flow system, and to assess the consequent impact on the spatial distribution of a conservative tracer, a series of field-scale experiments were conducted. These experiments involved the injection of a tracer in the center of a circular array of wells followed by either mixing using an engineered RPM flow system to invoke chaotic advection, or by natural processes (advection and diffusion) as the control. Pressure fluctuations from the mixing tests using the RPM flow system showed consistent peak amplitudes during injection and extraction at a frequency corresponding to the switching time, suggesting that the target hydraulic behavior was achieved with the time-dependent flow field. The tracer breakthrough responses showed oscillatory behavior at all monitoring locations during the mixing tests which indicated that the desired RPM flow was generated. The presence of chaotic advection was supported by comparisons to observations from a previous laboratory experiment using RPM flow, and the Fourier spectrum of the temporal tracer data. Results from several quantitative metrics adopted to demonstrate field-scale evidence of chaotic advection showed that mixing led to improved lateral tracer spreading and approximately uniform concentrations across the monitoring network. The multiple lines of evidence assembled in this proof-of-concept study conclusively demonstrated that chaotic advection can be engineered at the field scale. This investigation is a critical step in the development of chaotic advection as a viable and efficient approach to enhance reagent delivery.     

Spatial and temporal changes in reef fish assemblages on disturbed coral reefs,north Pacific coast of Costa Rica

Benthic structure of coral reefs determines the availability of refuges and food sources. Therefore, structural changes caused by natural and anthropogenic disturbances can have negative impacts on reef‐associated communities. During the 1990s, coral reefs from Bahía Culebra were considered among the most diverse ecosystems along the Pacific coast of Costa Rica; however, recently they have undergone severe deterioration as consequence of chronic stressors such as El Niño‐Southern Oscillation and harmful algal blooms. Reef fish populations in this area have also been intensely exploited. This study compared reef fish assemblages during two periods (1995–1996 and 2014–2016), to determine whether they have experienced changes as a result of natural and anthropogenic disturbances. For both periods, benthic composition and reef fish abundance were recorded using underwater visual censuses. Live coral cover (LCC) decreased from 43.09 ± 18.65% in 1995–1996 to 1.25 ± 2.42% in 2014–2016 (U = 36, p < 0.05). Macroalgal cover (%) in 2014–2016 was sixfold higher than mean values reported for the Eastern Tropical Pacific region. Mean (±SD) fish species richness in 1995–1996 (36.67 ± 14.20) was higher than in 2014–2016 (23.00 ± 9.14; U = 20, p < 0.05). Over 40% of reef fish orders observed in 1995–1996 were not detected in the 2014–2016 surveys, including large‐bodied predators. Reduction in abundance of fish predators such as sharks, grunts, and snappers is likely attributed to changes in habitat structure. Herbivorous such as parrotfishes and pufferfishes increased their abundance at sites with low LCC, probably in response to predators decline and increased algal cover. These findings revealed significant degradation and drastic loss of structural complexity in coral reefs from Bahía Culebra, which now are dominated by macroalgae. The large reduction in structural complexity of coral reefs has resulted in the loss of diversity and key ecological roles (e.g., predation and herbivory), thus potentially reducing the resilience of the entire ecosystem.     

Predicting forest fire in the Brazilian Amazon using MODIS imagery and artificial neural networks

The presented work describes a methodology that employs artificial neural networks (ANN) and multi-temporal imagery from the MODIS/Terra-Aqua sensors to detect areas of high risk of forest fire in the Brazilian Amazon. The hypothesis of this work is that due to characteristic land use and land cover change dynamics in the Amazon forest, forest areas likely to be burned can be separated from other land targets. A study case was carried out in three municipalities located in northern Mato Grosso State, Brazilian Amazon. Feedforward ANNs, with different architectures, were trained with a backpropagation algorithm, taking as inputs the NDVI values calculated from MODIS imagery acquired during five different periods preceding the 2005 fire season. Selected samples were extracted from areas where forest fires were detected in 2005 and from other non-burned forest and agricultural areas. These samples were used to train, validate and test the ANN. The results achieved a mean squared error of 0.07. In addition, the model was simulated for an entire municipality and its results were compared with hotspots detected by the MODIS sensor during the year. A histogram analysis showed that the spatial distribution of the areas with fire risk were consistent with the fire events observed from June to December 2005. The ANN model allowed a fast and relatively precise method to predict forest fire events in the studied area. Hence, it offers an excellent alternative for supporting forest fire prevention policies, and in assisting the assessment of burned areas, reducing the uncertainty involved in currently used methods.     

Protection of chemolithoautotrophic bacteria exposed to simulated Mars environmental conditions

Current surface conditions (strong oxidative atmosphere, UV radiation, low temperatures and xeric conditions) on Mars are considered extremely challenging for life. The question is whether there are any features on Mars that could exert a protective effect against the sterilizing conditions detected on its surface. Potential habitability in the subsurface would increase if the overlaying material played a protective role. With the aim of evaluating this possibility we studied the viability of two microorganisms under different conditions in a Mars simulation chamber. An acidophilic chemolithotroph isolated from Río Tinto belonging to the Acidithiobacillus genus and Deinococcus radiodurans, a radiation resistant microorganism, were exposed to simulated Mars conditions under the protection of a layer of ferric oxides and hydroxides, a Mars regolith analogue. Samples of these microorganisms were exposed to UV radiation in Mars atmospheric conditions at different time intervals under the protection of 2 and 5 mm layers of oxidized iron minerals. Viability was evaluated by inoculation on fresh media and characterization of their growth cultures. Here we report the survival capability of both bacteria to simulated Mars environmental conditions.     

Extended time weather forecasts contributes to agricultural productivity estimates

Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Paraná, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.     

Repeated glacial-lake outburst floods in Patagonia: an increasing hazard?

Five similar glacial-lake outburst floods (GLOFs) occurred in April, October, December 2008, March and September 2009 in the Northern Patagonia Icefield. On each occasion, Cachet 2 Lake, dammed by the Colonia Glacier, released circa 200-million m³ water into the Colonia River. Refilling has occurred rapidly, such that further outbreak floods can be expected. Pipeflow calculations of the subglacial tunnel drainage and 1D hydraulic models of the river flood give consistent results, with an estimated peak discharge surpassing 3,000 m³ s^?1. These floods were larger in magnitude than any flood on record, according to gauged data since 1963. However, geomorphological analysis of the Colonia valley shows physical evidence of former catastrophic outburst floods from a larger glacial-lake, with flood discharges possibly as high as 16,000 m³ s^?1. Due to potential impacts of climate change on glacier dynamics in the area, jökulhlaups may increase future flood risks for infrastructure and population. This is particularly relevant in view of the current development of hydropower projects in Chilean Patagonia.