Pedro Alvarez

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Pedro Alvarez
BSc Geophysical Engineering
MSc Petroleum Geophysics
BSc university Universidad Central de Venezuela
MSc university Centro Superior de Formacion (Madrid) and the Heriot-Watt University (Edinburgh)

Pedro Alvarez received a B.Sc. (2002) in geophysical engineering from the Universidad Central de Venezuela, ranking first in his class, and a M.Sc. (2007) in petroleum geophysics from a joint program between the Centro Superior de Formacion (Madrid) and the Heriot-Watt University (Edinburgh). He worked for eight years as a seismic interpreter and reservoir geophysicist for PDVSA focusing in structural and quantitative seismic interpretation of clastic and carbonate reservoirs. Since 2012, he has been working for Rock Solid Images, where he currently has the position of team lead/Sr. QI geoscientist. In this position, his primary responsibility is the development and application of methodologies for the quantitative interpretation of post-stack, AVO, seismic inversion, and CSEM attributes using a geologic, geostatistical, and rock-physics framework. He has experience working with projects from Venezuela, Colombia, Mexico, Alaska, Gulf of Mexico, Australia, West Africa, the Falkland Islands, the Middle East, and Norway. He is author or coauthor of more than 15 papers presented in international conferences and/or journals. He is a member of SEG, AAPG, and EAGE, and he has served these societies by chairing technical sessions and reviewing journal papers.

2016 SEG Honorary Lecturer, Latin America

Rock-property estimation from seismic and CSEM attributes using a rock-physics framework

Rock-property estimation (fluid saturation, porosity, and lithology) is the final goal of geologists, geophysicists, and reservoir engineers. We all try to combine well and surface measurements to generate a model of rock properties that can be used to generate an exploration, appraisal, or exploitation plan and quantify the hydrocarbon resources available. Since hydrocarbon exploration began in the 19th century, technology and innovation have driven the process of subsurface rock-property prediction, from exploration, solely based on surface geology, to the progressive inclusion of 2D seismic (early 1920s), gravity, magnetic, 3D seismic (late 1960s), AVO analysis (Ostrander, 1984) and, most recently, control source electromagnetic (CSEM) data (Ellingsrud et al., 2002).

Nowadays, the integration of pre-stack seismic inversion attributes with CSEM attributes using a rock-physics framework constitutes one of the most modern and robust methodologies to carry out seismic reservoir characterization. Each method provides independent physical measurements of the subsurface that complement each other and can be validated by well-log measurements and forward-modeled at different reservoir conditions through the application of rock-physics principles. Seismic provides the structural framework and, from AVO information, the possibility to derive P- and S-wave impedance volumes, which are two valuable, independent measurements, that can be linked to porosity, lithology, geomechanical properties, and, under certain conditions, to fluid saturation prediction. On the other hand, CSEM data provide a lower resolution measure of resistivity, which, when constrained with the structural framework and seismically derived volumes of porosity and lithology, can be linked to fluid saturation and hydrocarbon reserves estimation, and overcome seismic ambiguity related to similar AVO responses in both low- and high-saturated hydrocarbon reservoirs.

The lecture will cover different methodologies to estimate rock-property volumes from different types of seismic attributes, including AVO and inversion attributes using empirical and theoretical rock-physics principles calibrated with well-log data. Next, we will show how the results of quantitative seismic interpretation can be used to feed an integrated seismic-CSEM interpretation allowing us to create a geologic model of rock properties that honors both data sets and how it can be used to de-risk a prospect and spatially characterize the petrophysical properties of the reservoir.

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