Vol. 10 No. 2 (2012): Fuentes, el reventón energético
Articles

Metodología de interpretación sísmica para identificación de zonas prospectivas y posicionamiento de pozos

Daniela Torres
Universidad Industrial de Santander.
Bio
Andrés Calle
Instituto Colombiano del Petróleo
Bio
Freddy Niño
Instituto Colombiano del Petróleo
Bio
César Pineda
Universidad Industrial de Santander.
Bio

Published 2012-11-28

Keywords

  • Bayesian probability,
  • quantitative interpretation,
  • seismic methodology,
  • well logs,
  • fuid substitution

How to Cite

Torres, D., Calle, A., Niño, F., & Pineda, C. (2012). Metodología de interpretación sísmica para identificación de zonas prospectivas y posicionamiento de pozos. Fuentes, El reventón energético, 10(2). Retrieved from https://revistas.uis.edu.co/index.php/revistafuentes/article/view/3326

Abstract

 

The seismic interpretation in the exploration of hydrocarbon resources is subject to a high level of uncertainty when trying to set the rock properties and the amount of fuids with commercial interest.

The seismic interpretation methodology employed in this work allows to predict quantitatively the fuid present in the rock, by integrating stochastic techniques based on statistical analysis of the main parameters characterizing the reservoir, using seismic data (speed, impedance amplitude) [1], well logs (gamma ray, density, resistivity, etc.) and rock physics relationships (lithology, porosity, permeability, pore fuid and net to gross).

By means of Bayes probabilistic method are obtained probability density functions (pdf) conditionated   to theparameters that will be studied, they describe the expected distribution of the properties whenthe saturation state of the reservoir rock is specifed. These pdfs are used to predict the most likely area for thelocation of new wells.

This research aims to encourage decision-making processes based on the application of combined statistical inference techniques in a methodology for a quantitative seismic interpretation. The methodology integratesmultiple sources of information to quantify exploratory probability of fuids in reservoirs.

 

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References

1. CAERS, J., et al. “Stochastic integration of seismic data and geologic scenarios: A West Africa submarine channel saga”. 2003.

2. AVSETH, P., MUKERJI, T and MAVKO, G., “Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk”, 2005.

3. GUNNING, James and GLINSKY, Michael. “Delivery: an open-source model-based Bayesian seismic inversion program”, 2004.

4. GLINSKY, Michael, et al. “The value of using relative amplitude changes”, 2007.

5. GONZALES, Ezequiel, et al. “Near and far offset P-to-S elastic impedance for discriminating Fizz water from Commercial Gas”, 2003.

6. GARCÍA, Víctor. “Aplicación de un algoritmo de inversión sísmica Bayesiana pre-apilamiento para estimación de propiedades elásticas en un yacimiento gasífero costa afuera, Trinidad & Tobago”. 2006.

7. GIRALDO, L., et al. “Discriminación entre gas fizz y gas comercial en el Caribe Colombiano mediante atributos AVO y modelado de substitución de fluidos”. Fuentes, El Reventón Energético ISSN: 1657-6527 ed: Ediciones Universidad Industrial De Santander v.7 fasc.2 p.29 - 36, 2009.