
Daniel Vázquez RamírezNational Autonomous University of Mexico | UNAM · Institute of Geophysics
Daniel Vázquez Ramírez
PhD
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13
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Introduction
I'm a geophysicist with a background in statistics, geostatistics, inverse theory and stochastic simulation. I received my Ph.D. with honors in Earth Sciences from the National Autonomous University of Mexico on Joint seismic inversion of elastic and petrophysical properties using copula-based stochastic co-simulation models.
My research interests are related to inverse problems, subsurface characterization, stochastic simulations and data science.
Education
Publications
Publications (13)
Seismic attributes play a fundamental role in the geological-petrophysical modeling of reservoirs, especially due to their dependency relationship with petrophysical properties. Most of the existing seismic inversion methods with a stochastic approach are based on the use of the Gaussian or normal probability distribution function and linear depend...
Seismic attributes play a fundamental role in the geological-petrophysical modeling of reservoirs, especially due to their dependency relationship with petrophysical properties. Most of the existing seismic inversion methods with a stochastic approach are based on the use of the Gaussian or normal probability distribution function and linear depend...
Los atributos sísmicos juegan un papel fundamental en el modelado geológico-petrofísico de yacimientos, especialmente por su relación de dependencia con las propiedades petrofísicas. La mayoría de los métodos de inversión sísmica con enfoque estocástico existentes se basan en el uso de la función de distribución de probabilidad Gaussiana o normal y...
This report in PDF contains code in R and notes related to computational implementation of Joint stochastic simulation of petrophysical properties with elastic attributes based on parametric copula models
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...
Un programa de código abierto para aplicaciones geoestadísticas basado en R-Project.
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...