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Estimating Natural-Fracture Permeability From Mud-Loss Data

Serhat AKIN

Key words
transient radial mud loss invasion, fracture permeability, artificial neural network
Conference
Stanford Geothermal Workshop
Year
2013
Session
Reservoir Engineering
Language
English
Paper number
Akin

Full text

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Abstract

Knowing locations, distributions and apertures of fractures crossing a geothermal well is of vital importance in order to minimize costs and increase efficiency of drilling. Complete or small losses of drilling fluid flowing from wellbore to the surrounding formations have been used to identify fracture zones in the past. An analytical model based on transient radial mud-loss invasion from a borehole into a fracture plane coupled with an artificial neural network approach is developed to estimate natural-fracture permeability. The developed model is compared to pressure transient test results obtained for several wells located in a liquid dominated geothermal reservoir in west Turkey. It has been observed that the model fracture permeability values are in accord with well test derived permeability values.

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