Skip to main content
U.S. flag

An official website of the United States government

USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Slip and Dilation Tendency Data

January 12, 2022

This package contains data in a portion of northern Nevada, the extent of the ?Nevada Machine Learning Project? (DE-EE0008762). Slip tendency (TS) and dilation tendency (TD) were calculated for the all the faults in the Nevada ML study area. TS is the ratio between the shear components of the stress tensor and the normal components of the stress tensor acting on a fault plane. TD is the ratio of all the components of the stress tensor that are normal to a fault plane. Faults with higher TD are relatively more likely to dilate and host open, conductive fractures. Faults with higher TS are relatively more likely to slip, and these fractures may be propped open and conductive. These values of TS and TD were used to update a map surface from the Nevada Geothermal Machine Learning Project (DE-FOA-0001956) that used less reliable estimates for TS and TD. The new map surface was generated using the same procedure as the old surface, just with the new TS and TD data values.