During the seismic interpretation process, geoscientists rely on their experience and visual analysis to assess the similarity between seismic sections. However, evaluating all of the seismic sections in a 3D survey can be a time-consuming task. When interpreters are working on a data set, a common procedure is to divide the cube in increasingly finer grids until they are satisfied with the result of the interpretation. We have developed a method based on graph theory and image texture in which we represent a seismic data set as a complete weighted undirected graph — which we call a seismic graph. The vertices of this graph represent the seismic sections, and the weight of the edges represents the distance between the texture feature vectors of the vertices they connect, allowing for a powerful yet concise representation of potentially large data sets. We have investigated the potential of graph analysis to build an adaptive grid that is more likely to capture the underlying structures present in a survey, providing a tool for a faster and more precise interpretation. The main idea is that such a grid would be finer in regions with more geologic variations and coarser otherwise. To demonstrate the capabilities of our technique, we apply it on a public data set called Netherlands F3. Using our method, we suggest which seismic sections — key sections — should be considered in the interpretation process. The results of our experiments indicate that our methodology has great potential to aid the seismic interpretation process.
Properly modelling dynamic information that changes over time still is an open issue. Most modern knowledge bases are unable to represent relationships that are valid only during a given time interval. In this work, we revisit a previous extension to the hyperknowledge framework to deal with temporal facts and propose a temporal query language and engine. We validate our proposal by discussing a qualitative analysis of the modelling of a real-world use case in the Oil & Gas industry.
A new species of Myxosporea, Henneguya aequidens sp. n. (Myxozoa: Myxobolidae), was described based on its ultrastructural features. This is a parasite of the freshwater fish Aequidens plagiozonatus, in the Peixe-boi River, Pará, Brazil. This parasite was found in the gills, in the form of whitish ellipsoid cysts with mature spores inside them. The average spore body was 15 ± 0.9 μm in length (n = 30) and 6 ± 0.8 μm in width (n = 30), and the tail measured 27 ± 0.5 μm in length (n = 15). The spores showed typical features of the genus Henneguya with two valves of equal size and two symmetrical polar capsules of 3 ± 0.3 μm in length and 2 ± 0.3 μm in width. Each polar capsule had a polar filament forming a helix from the apical region to the polar caps, with four to six turns. Based on the ultrastructural differences in morphology of these spores, the location of the parasite, and its host specificity, this parasite was described as a new species.
Contemporary Portuguese American literature written by Thomas Braga (1943-), Frank Gaspar (1946-), and Katherine Vaz (1955-) share a profusion of topics - with ethnic food being, perhaps, the most representative one. What these writers have in common is that their roots can be traced to Portugal's Atlantic islands - the Azores - and not to continental Portugal. They are native Americans and write in English, though their characters and themes are Portuguese American. Some of them lived close to the former New England whaling and fishing centers of New Bedford and Nantucket, which Herman Melville has immortalized in Moby-Dick and in his short story, “The 'Gees,” in The Piazza Tales. These seaports were renowned worldwide and eventually attracted Azorean harpooners. The Azorean background of Thomas Braga and Frank Gaspar helps us to understand why fish and seafood feature so extensively in their writings instead of dishes containing meat as is the case in the fiction of Katherine Vaz.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.