Development of a Discrete Fracture Network Model for Utah FORGE Using Microseismic Data Collected During Stimulation of Well 16A(78)-32



Key Words:

FORGE, DFN, 16A(78)-32, microseismic


Stanford Geothermal Workshop




Enhanced Geothermal Systems



Paper Number:


File Size:

876 KB

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Previous fracture models for the Utah FORGE geothermal reservoir were developed using data from well logs and outcrop. Recent hydraulic stimulation of well 16A(78)-32 allowed for collection of high quality microseismic data which has been used to create a new fracture model based on fitting planar features to the microseismic point cloud. These planar features are interpreted to be large fractures or collections of smaller fractures sharing common orientations and locations. Fifteen hexagonal fractures are included in the new Discrete Fracture Network (DFN) model: eleven are fit from the microseismic data and four are added based on previous characterization work to provide connectivity between the fractures and the injection intervals. Previous DFN models of the site included hundreds to thousands of discrete fractures and relied on stochastic generation of features. This new simplified DFN model is created to provide an alternative fracture network having fewer discrete features and potentially captures the most significant flow pathways created by the stimulation of 16A(78)-32. This DFN can be used for further modeling of the long-term thermal and mechanical evolution of flow paths between 16A(78)-32 and a planned production well. Our workflow for defining fractures from microseismic points is presented along with a comparison of fracture sizes and orientations between these discovered features and the fracture sets used in previous DFN models for the site.

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