Methodology to design of synthetic sonic log (SSL), using artificial neural networks. Colorado field application

  • Carlos-Andrés Ayala-Marín Ecopetrol – Instituto Colombiano del Petróleo, Piedecuesta, Colombia
  • Christiann-Camilo García-Yela Universidad Industrial de Santander, Bucaramanga, Colombia
Keywords: Petrophysical properties,, Sonic logs, Neural networks, Spontaneous potential, Porosity, Permeability, Saturation

Abstract

A method that allows the creation of the Synthetic Sonic Log (SSL) was developed from the Spontaneous Potential (SP) logs, the resistivity logs of the flushed zone (SN), and the resistivity zone of the uninvaded zone (ILD), using Artificial Neural Networks (ANN). The SSL was obtained with the created tool called
Generation of Synthetic Sonic Logs (GSSL).

The results obtained are presented hereinafter: in the Colorado 70 well, 90% of the generated SSL data present errors of less than 10%; in the Colorado 72 well; 53% of the SSL data obtained with the tool are below 5% error, in the Colorado 75 well, 80% of the SSL data present errors of less than 10%, and finally, the SSL generated for the Colorado 38 well follows the behavior of the original Sonic Logs of the well in an accurate manner. From the foregoing we conclude that the quality of the created tool is good and that the deviations are minimal in the times of transit of synthetic sonic profile.

References

Acosta, M., Zuluga, C., & Salazar, H. (2000). Tutorial de Redes Neuronales. Facultad de Ingeniería Eléctrica, Universidad Tecnológica de Pereira, Colombia.

Bendeck, J. (1992). Perfiles Eléctricos, Una herramienta para la evaluación de yacimientos. Asociación Colombiana de Geólogos y Geofísicos del Petróleo. Bogotá, Colombia.

Mohaghegh, S., Richardson, M., & Ameri, S. (1998). Virtual Magnetic Imaging Logs: Generation of Synthetic MRI Logs from Conventional Well Logs, SPE 51075, 9-11.

November 1998, Pittsburgh, Pennsylvania.

Mohaghegh, S. (2000). Virtual intelligence applications in Petroleum Engineering: Part 1 - Artificial Neural Networks. SPE 58046, JPT, 52 (9): 64-73, September 2000.
How to Cite
Ayala-Marín, C.-A., & García-Yela, C.-C. (2020). Methodology to design of synthetic sonic log (SSL), using artificial neural networks. Colorado field application. CT&F - Ciencia, Tecnología Y Futuro, 4(2), 21-31. Retrieved from https://ctyf.journal.ecopetrol.com.co/index.php/ctyf/article/view/242

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Published
2020-04-15
Section
Scientific and Technological Research Articles

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