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Geostatistic in Reservoir Characterization: from estimation to simulation methods
Author(s) -
H. Mata Lima
Publication year - 2005
Publication title -
estudios geológicos
Language(s) - Spanish
Resource type - Journals
SCImago Journal Rank - 0.276
H-Index - 27
eISSN - 1988-3250
pISSN - 0367-0449
DOI - 10.3989/egeol.05613-651
Subject(s) - reservoir modeling , estimation , reservoir simulation , geology , environmental science , petroleum engineering , computer science , engineering , systems engineering
In this article objective have been made to reviews different geostatistical methods available to estimate and simulate petrophysical properties (porosity and permeability) of the reservoir. Different geostatistical techniques that allow the combination of hard and soft data are taken into account and one refers the main reason to use the geostatistical simulation rather than estimation. Uncertainty in reservoir characterization due to variogram assumption, which is a strict mathematical equation and can leads to serious simplification on description of the natural processes or phenomena under consideration, is treated here. Mutiple-point geostatistics methods based on the concept of training images, suggested by Strebelle (2000) and Caers (2003) owing to variogram limitation to capture complex heterogeneity, is another subject presented. This article intends to provide a review of geostatistical methods to serve the interest of students and researchers. Este artículo presenta una revisión de diversos métodos geoestatísticos disponibles para estimar y para simular características petrofísicas (porosidad y permeabilidad) de la formación geológica (roca depósito del petróleo). Se presentan diversas técnicas geostatísticas que permiten la combinación de datos hard y soft y se explica la razón principal para utilizar la simulación geoestatística en vez de estimación. También se explica la incertidumbre en la caracterización del depósito debido a la asunción del variogram. El hecho de que el variogram sea una simple ecuación matemática conduce a la simplificación seria en la descripción de los procesos o de los fenómenos naturales bajo consideración. Los «métodos geostatísticos del Multiplepoint » (Multiple-point geostatistics methods) basados en el concepto de training images, sugerido por Strebelle (2000) y Caers (2003), debido a la limitación del variogram para capturar heterogeneidad compleja es otro tema presentado. Este artículo se propone proporcionar una revisión de métodos geostatísticos que sean de interés para estudiantes e investigadores

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