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.     

Reproductive cycle,size at first maturation and fecundity in the golden ling,Genypterus blacodes,in Chile

Reproductive aspects of the golden ling, Genypterus blacodes, from the southern Chilean fishery are presented. Gonad samples were obtained from commercially caught fish between September 1999 and October 2000. Stage of sexual maturity, gonadosomatic index (GSI), and size of females at 50% maturation determined by logistic methods and by plotting the mean GSI by total length, are presented for both years. Batch fecundity was calculated from subsampling mature ovaries containing oocytes in advanced stages of maturity. Changes in GSI and monthly diameters of oocytes showed that ling had a spawning season which extended between August and November. The sizes at first maturity in 1999 and 2000 were 86.6 and 84.8 cm total length (TL), respectively, using the logistic model, and 84 cm for both years using the mean GSI‐size plotting method. The mean batch fecundity was 333 330 oocytes per individual for fish sized 85–120 cm TL. Fecundity increased with increasing weight and total length.     

Modeling the potential impact of climate change in northern Mexico using two environmental indicators

Modeling the deterioration of natural resources, especially water and soil that results from the global effects of climate change has become a powerful tool in the search for mitigation and adaptation measures. The objectives of this research were: (1) to model the potential impact of climate change for the period 2010-2039, and (2) to offer advice about future risks based on local radiative forcing or critical areas and taking into account two indicators of environmental quality, the aridity index (AI) and laminar wind erosion (LWE). Evaluation techniques for natural resources, similar to those applied by the Instituto Nacional de Ecología y Cambio Climático (National Institute of Ecology and Climate Change) were used for studies of ecological land use. The inputs include climate information (current and future), soil cover and edaphic properties related to the municipality of Gómez Palacio, Durango, Mexico (25.886° N, 103.476° W). According to calculations estimated from the anomalies for the mean annual rainfall and mean annual temperature, in a future climate change scenario, an average impact of approximately 63% would be caused by LWE, and the AI would change from its historical value of 9.3 to 8.7. It is estimated that the average impact on the AI in the future will be 0.53 ± 0.2.     

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.     

What happens to the ocean surface gravity waves when ENSO and MJO phases combine during the extended boreal winter?

The safety of vulnerable coastal and offshore infrastructures requires an in-depth understanding of wave variability and climate drivers. We investigate the association of significant wave height (Hs) and peak wave period (Tp) with the co-occurrence of El Niño–Southern Oscillation (ENSO) and the Madden–Julian Oscillation (MJO) at the global scale. We calculate composites of daily anomalies in modelled Hs, Tp, and surface wind for periods of ENSO–MJO phase combinations. Calculations spanned November–March seasons over the period 1979–2018. Wave anomalies are widespread across the world’s oceans, with remarkable strength during several ENSO–MJO phase combinations, demonstrating strong tropic–tropic and tropic-extratropic teleconnections. Positive Hs anomalies are strongest in the Pacific Ocean during El Niño–MJO phase 8, in the Atlantic Ocean during ENSO-neutral-MJO phase 3, and in the Indian Ocean during ENSO-neutral-MJO phase 4. Positive Tp anomalies are strongest in the Pacific Ocean during La Niña–MJO phase 8, in the Atlantic Ocean during El Niño–MJO phase 1, and in the Indian Ocean during El Niño–MJO phase 8. In the Southern Ocean, the strongest Hs anomalies occur during El Niño–MJO phase 8, whereas in the Maritime Continent, they appear during ENSO-neutral-MJO phases 5–6. Despite previous studies finding low correlations of ENSO indices with wave parameters in the North Atlantic, our results suggest that ENSO-related conditions play a significant role in the area when combined with certain MJO-related conditions. This study also reveals that the wave anomalies associated with ENSO–MJO phase combinations can be twice as strong as those found in previous work, related only to the MJO. Therefore, considering multiple concurrent climate patterns in the analysis of wave anomalies is essential to developing more reliable coastal management plans.