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    <subfield code="a">Stochastic Modeling of Rock Heterogeneities Applying New Autocorrelation Estimators and Simulated Annealing</subfield>
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    <subfield code="a">12/09/06 ; 17/07/01</subfield>
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    <subfield code="a">Two new integral estimators of spatial autocorrelation are put forward and studied. The first is LV (Local Variance), based on the variance of the distribution. It is also an estimator of the average value of the semivariogram within a region. The second, SLV (Semivariogram from the Local Variance), is related to the derivatives of the former. It is an estimator of the semivariogram itself. The behavior of these two estimators is compared to that of the classical semivariogram estimator (CSV) using different data sets. SLV behavior is similar to that of CSV. Both are noisy and present fluctuations that increase with lag distance. Instead, LV is smoother and more resistant to outliers, making it easier to be represented by a theoretical model. Also, LV is less affected by individual values of samples, honoring the general statistics of data. Afterwards, the ability of the three estimators to model actual spatial variability is tested using the Simulated Annealing optimization technique. This technique has a good performance when any of the three estimators is included in the objective function. It is able to reproduce actual porosity or permeability fields, even when there is a specific spatial structure (such as cyclic, staircase-like, etc). However, LV has a main advantage: it still preserves the main features of the spatial structure even though it is very smooth.</subfield>
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    <subfield code="a">Latin American and Caribbean Petroleum Engineering Conference (7th : 2001 mar. 25-28 : Buenos Aires, Argentina)</subfield>
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    <subfield code="a">Latin American and Caribbean Petroleum Engineering Conference (7th : 2001 mar. 25-28 : Buenos Aires, Argentina)</subfield>
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