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Citations since 2017
5 Research Items
August 2015 - August 2017
Field of study
- Joint stochastic simulation of petrophysical properties with Bernstein copulas using seismic attributes as secondary variables at the well log scale
The spatial stochastic co-simulation method based on copulas is a general method that allows simulating variables with any type of dependency and probability distribution functions. This flexibility comes from the use of a copula model for the representation of the joint probability distribution function. The method has been mainly implemented thro...
This work presents a comparison between the convolutional neural networks (a machine learning estimation method) with the Bernstein copula quantile regression (a geostatistical estimation method) for petrophysical property prediction from seismic data.
A new methodology for the prediction of spatially distributed petrophysical properties using elastic seismic attributes as secondary variables is presented. The method is based on copula function for the estimation of the joint probability distribution function. The proposed method can model linear and complex nonlinear dependency relationships bet...
A new methodology for the simulation of spatially distributed petrophysical properties conditioned by elastic attributes as secondary variables is presented. The method, namely Bernstein copula-based spatial cosimulation (BCSCS), is based on Bernstein copula for the estimation of the joint probability function and simulated annealing for the spatia...
In this work we showed a method of modeling the 3D spatial stochastic distribution of petrophysical properties using a model of dependence based on copula with the seismic attributes, where a prior not require specific functions or a high linear dependence between them. Subsequently, it is compared with the traditional method as a Gaussian sequenti...