Title:

Discrete Fracture Network Modeling of Alaşehir Geothermal Field

Authors:

Hakki AYDIN, Serhat AKIN

Key Words:

Discrete Fractures, Modeling

Conference:

Stanford Geothermal Workshop

Year:

2019

Session:

Modeling

Language:

English

Paper Number:

Aydin2

File Size:

1976 KB

View File:

Abstract:

Understanding of fractures network and fracture characteristic properties is essential for an effective geothermal reservoir management. Discrete Fracture Network (DFN) is one of the widely used approach to characterize fractured reservoirs. DFN modeling approach uses fracture geometry, conductivity and connectivity to create a fracture network. In this study, DFN modeling is used to characterize Alaşehir geothermal reservoir, which consists from heavily fractured marble and schist. Fracture parameters such as fracture permeability, aperture, intensity and fracture radius are conditioned for model calibration. Most of the required fracture parameters are retrieved from different data sources. Stochastic correlations related with known parameters are used to estimate unavailable parameters. The dynamic model results are verified with pressure transient buildup tests conducted in the field. Upscaled fracture properties are in accord with well test analysis and tracer test results. DFN model shows that all wells are interconnected by strong fractures network. Fractures network is validated with a tracer test and reservoir monitoring in the field.


ec2-3-140-188-16.us-east-2.compute.amazonaws.com, you have accessed 0 records today.

Press the Back button in your browser, or search again.

Copyright 2019, Stanford Geothermal Program: Readers who download papers from this site should honor the copyright of the original authors and may not copy or distribute the work further without the permission of the original publisher.


Attend the nwxt Stanford Geothermal Workshop, click here for details.

Accessed by: ec2-3-140-188-16.us-east-2.compute.amazonaws.com (3.140.188.16)
Accessed: Saturday 20th of April 2024 05:33:45 AM