نتایج جستجو برای: porosity classification
تعداد نتایج: 509753 فیلتر نتایج به سال:
In clayey, swelling and more or less sodic soils, cultivation and seasonal climatic cycles induce variations in soil moisture which in turn cause variations in the soil structure. In particular, when the soil profile is saturated, some soils become impermeable because the soil porosity value does not remain sufficiently high throughout the drainage period to be effective for water movement. In ...
PLANUM, MARS . S. M. Perl, S. M. McLennan, J. P. Grotzinger, J. R. Johnson, B. C. Clark, and the Athena Science Team, Department of Geosciences, State University of New York, Stony Brook, NY 11794-2100 ([email protected]); Division of Ge ological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125; United States Geological Survey, Astrogeology Team, Flagstaff,...
The main result of this paper is a polynomial time version of Rademacher’s theorem. We show that if z ∈ R is p-random, then every polynomial time computable Lipschitz function f : R → R is differentiable at z. This is a generalization of the main result of [19]. To prove our main result, we introduce and study a new notion, p-porosity, and prove several results of independent interest. In parti...
cementation factor is a critical parameter, which affects water saturation calculation. in carbonate rocks, due to the sensitivity of this parameter to pore type, water saturation estimation has associated with high inaccuracy. hence developing a reliable mathematical strategy to determine these properties accurately is of crucial importance. to this end, genetic algorithm pattern search is emp...
Rock classification or assigning a type or class to a specific rock sample based on petrophysical characteristics is a fundamental technique to reduce the uncertainty in prediction of reservoir properties due to heterogeneity. One of the popular approaches is to classify a reservoir rock from the fundamentals of geology and the physics of flow at pore network scale. In this approach, rocks of s...
Support Vector Machines (SVM) is a new machine learning approach based on Statistical Learning Theory (Vapnik-Chervonenkis or VC-theory). VCtheory has a solid mathematical background for the dependencies estimation and predictive learning from finite data sets. SVM is based on the Structural Risk Minimisation principle, aiming to minimise both the empirical risk and the complexity of the model,...
Cementation factor is a critical parameter, which affects water saturation calculation. In carbonate rocks, due to the sensitivity of this parameter to pore type, water saturation estimation has associated with high inaccuracy. Hence developing a reliable mathematical strategy to determine these properties accurately is of crucial importance. To this end, genetic algorithm pattern search is emp...
S hale resource systems have had a dramatic impact on the supply of oil and especially gas in North America, in fact, making United States energy independent in natural gas reserves. These shale resource systems are typically organic-rich mudstones that serve as both source and reservoir rock or source petroleum found in juxtaposed organic-lean facies. Success in producing gas and oil from thes...
Evaluation of hydrocarbon reservoir requires classification of petrophysical properties from available dataset. However, characterization of reservoir attributes is difficult due to the nonlinear and heterogeneous nature of the subsurface physical properties. In this context, present study proposes a generalized one class classification framework based on Support Vector Data Description (SVDD) ...
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