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Archive » Abstracts » Search	*2004/ 2005 SEASON* **STAVANGER OCTOBER MEETING Venue: Rica Forum Hotel, Stavanger Date: Wednesday, October 6th 2004 Time: 11:00 a.m. Lunch will be provided at 12:00 Thin Bed Analysis and Permeability Estimation by Monica Vik Constable, Schlumberger Abstract: In formations which contains thinly laminated sand beds standard log suites do not provide sufficient resolution to resolve these thin beds. Thin bed analysis can be performed by utilizing the log response from a high-resolution image log to sharpen the responses of the standard resolution curves. The primary concept for sharpening log curves in clastic formations is that the bed boundaries and facies definition can be obtained from a high-resolution shallow resistivity log derived from the image tool. This concept is based on the assumption that the volume of clay is driving the conductivity of the image. In a hydrocarbon filled reservoir the high resolution resistivity responds to the bound water content, and hence the quality of the sand. Once the sharpening process has been completed the sharpened logs can be used as input into an Artificial Neural Network in combination with core data to train the network for permeability. The trained network can be used to estimate a high resolution estimated permeability in the uncored section of the well. About the author:** Monica Vik Constable is a Petrophysicist for Schlumberger and is based in Stavanger. Monica first joined Schlumberger as a Field Engineer in 1997 after obtaining a Masters Degree in Chemical Engineering at the Norwegian University of Science and Technology. She worked as a field engineer mainly in the UK and Holland, but also on some shorter projects in the US and in Poland. In 2002 she started working as a Petrophysicist in Aberdeen, before transferring to Stavanger in 2003.

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2004/ 2005 SEASON

STAVANGER OCTOBER MEETING

Venue: Rica Forum Hotel, Stavanger

Date: Wednesday, October 6th 2004

Time: 11:00 a.m.

Lunch will be provided at 12:00

Thin Bed Analysis and Permeability Estimation

by Monica Vik Constable, Schlumberger

Abstract:

In formations which contains thinly laminated sand beds standard log suites do not provide sufficient resolution to resolve these thin beds. Thin bed analysis can be performed by utilizing the log response from a high-resolution image log to sharpen the responses of the standard resolution curves. The primary concept for sharpening log curves in clastic formations is that the bed boundaries and facies definition can be obtained from a high-resolution shallow resistivity log derived from the image tool. This concept is based on the assumption that the volume of clay is driving the conductivity of the image. In a hydrocarbon filled reservoir the high resolution resistivity responds to the bound water content, and hence the quality of the sand. Once the sharpening process has been completed the sharpened logs can be used as input into an Artificial Neural Network in combination with core data to train the network for permeability. The trained network can be used to estimate a high resolution estimated permeability in the uncored section of the well.

About the author:

Monica Vik Constable is a Petrophysicist for Schlumberger and is based in Stavanger. Monica first joined Schlumberger as a Field Engineer in 1997 after obtaining a Masters Degree in Chemical Engineering at the Norwegian University of Science and Technology. She worked as a field engineer mainly in the UK and Holland, but also on some shorter projects in the US and in Poland. In 2002 she started working as a Petrophysicist in Aberdeen, before transferring to Stavanger in 2003.