Agroecometría: una caja de herramientas para el diseño de una agricultura virtual

Agriculture has rarely been an area of great attraction for technologicaland scientific innovations. Nevertheless, as there is evidently a risk ofa non-sustainable management of agroecosystems, it is necessary touse better the technological opportunities. One of these oportunities isto use the advances in of high-yield computation (and in parallel)mathematical modeling in order to unify the information data bases(Smith et al., 2002), that arise in areas as diverse as the study ofnatural resources, economics, and sociology, or rural revelopment,aiming them towards a common purpose. The objective of this studywas to answer one specific question: Is there a way to measure thestructural patterns of the physical, chemical, and biological systemsas well as the economic and social structural patterns with one and thesame variable, and visualize their competitive contribution to thesustainability of an agroecosystem? We have constructed themathematical bases and those of computer simulation to answer theaforementioned questions and to introduce a new discipline toagricultural sciences, whose theoretic-methodological frame seemspromising in the field of unification of the extensive, multifacetedinformation. This new discipline which we call Agroecometry, has asits fundamental objetive to construct metric spaces effective foragricultural sciences, and visualize the performance of anagroecosystem in all its the richness its in the frame of virtual model.La agricultura raramente ha sido el área de mayor atracción para lasinnovaciones tecnológicas y científicas. Sin embargo, en el contexto dela evidencia de riesgo de un manejo no sustentable de los agroecosistemas,surge la necesidad de un mejor aprovechamiento de las oportunidadestecnológicas. Una de estas oportunidades consiste en utilizar losavances del cómputo de alto rendimiento (y en paralelo), la modelaciónmatemática para unificar los bancos de información (Smith et al., 2002)que surgen en áreas tan diversas como el estudio de los recursos naturales,la economía y la eociología o el desarrollo rural, dirigiéndolos aun propósito común. La pregunta específica en este trabajo de investigaciónes: ¿Hay manera de medir no sólo los patrones estructurales delos sistemas físicos, químicos, biológicos, sino también los económicosy sociales con una misma variable y visualizar su contribucióncompetitiva a la sustentabilidad de un agroecosistema? En este trabajose exponen las bases matemáticas y de simulación computacional paracontestar esa pregunta, e introducir en las ciencias agrícolas unanueva disciplina cuyo marco teórico-metodológico parece prometedorpara unificar la cuantiosa información disponible. La nueva disciplina,que llamamos Agroecometría, tiene como objetivo básico construirespacios métricos efectivos para las ciencias agrícolas y visualizar elfuncionamiento de un agroecosistema en toda la riqueza de susparámetros característicos dentro de un modelo virtual

Entropy of Shortest Distance (ESD) as Pore Detector and Pore-Shape Classifier

The entropy of shortest distance (ESD) between geographic elements (“elliptical intrusions”, “lineaments”, “points”) on a map, or between "vugs", "fractures" and "pores" in the macro- or microscopic images of triple porosity naturally fractured vuggy carbonates provides a powerful new tool for the digital processing, analysis, classification and space/time distribution prognostic of mineral resources as well as the void space in carbonates, and in other rocks. The procedure is applicable at all scales, from outcrop photos, FMI, UBI, USI (geophysical imaging techniques) to micrographs, as we shall illustrate through some examples. Out of the possible applications of the ESD concept, we discuss in details the sliding window entropy filtering for nonlinear pore boundary enhancement, and propose this procedure as unbiased thresholding technique

Entropy of Shortest Distance (ESD) as Pore Detector and Pore-Shape Classifier

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3D GEOSTATISTICAL MODELING OF FACIES AND PETROPHYSICAL PROPERTIES OF THE UPPER KHARTAM OUTCROP OF KHUFF FORMATION, CENTRAL SAUDI ARABIA

Oolitic grainstones can contain significant hydrocarbon reserves. The heterogeneity in carbonate reservoir ascribes to the depositional and digenetic processes. Within the studied interval, facies were analyzed and grouped into four depositional sub-environment which stacked in five cycle sets (4th order sequences). The porosity and permeability were measured from core plug of outcrop samples. However, the measured porosity and permeability values showed patterns of distributions when statistically analyzed based on the rock typing and stratigraphic intervals. Based on the outcrop observations, the 3D framework was constructed which comprises of five zones separated by six surfaces. In the context of depositional environment, these zones are; foreshoal and shoal (zones 1 and 2), shoal and backshoal (zones 3 and 4) and tidal flat deposits (zone 5). The sea level within these zones was relatively high, fluctuated and dropped within deposits of zones 1 and 2, zones 3 and 4 and zone 5, respectively. In the context of 3D modelling, lithofacies within each zone was populated separately by using different geostatistical algorithm. Based on the relative sea level, the dominated lithofacies and the presence or absence of marine fauna, the studied interval was subdivided into three broad intervals. These intervals are; lower (zones 1 and 2), middle (zones 3 and 4) and the upper interval (zone 5). The porosity evolution was investigated within each zone and incorporated within the 3D outcrop model. The results showed how the incorporation of the porosity scenarios within the 3D framework can provide a realistic and to some extent the exact vertical stacking of reservoir units. This approach could be applied to predict and enhance the reservoir quality in the analogous oolitic reservoir