Application of covariance table for geostatistical modeling in the presence of an exhaustive secondary variable

• Autor(a) principal: Oliveira, Carlos Alexandre Santana
• Data de Publicação: 2021
• Outros Autores: Bassani, Marcel Antônio Arcari, Costa, Joao Felipe Coimbra Leite
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/221293
• topic: Análise de covariância; Simulação geoestatística; Covariance table; Collocated cokriging; Sequential Gaussian simulation

Two-point geostatistical modeling requires the variogram model of the variable of interest. However, this variogram is difficult to obtain when the variable of interest has few data sparsely spaced. This situation occurs often in the early process of mineral exploration, when the data spacing is wide. If a more densely sampled secondary variable, preferably correlated with the primary variable, is available, this variable may help to infer the variogram model of the primary one. Exhaustive secondary variables are common in the petroleum industry. These secondary variables are obtained by seismic survey. In this study, a methodology is presented for geostatistical estimation/simulation of primary variables that present few samples with the aid of an exhaustive secondary variable. The spatial continuity of the primary variable will be described using the covariance table of the exhaustive secondary variable. This methodology is used when the amount of data for the primary variable is insufficient to obtain a stable experimental variogram. The use of the covariance table of the exhaustive secondary variable replaces the calculation and adjustment of the variogram of the primary variable, a fact that motivated the development of the methodology. The results of the presented case study revealed that the estimates/simulations of the primary variable using the covariance table of the adjusted exhaustive secondary variable produced satisfactory results.