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This document details Datarock’s product Geotechnical Strength Index (GSI)
The literature, "Quantification of the Geological Strength Index Chart," introduces a structured approach to quantifying the Geological Strength Index (GSI), transforming the traditional qualitative assessment into a more standardised quantitative evaluation.
Contents
Literature
This product is based on the following literature:
Item | Title | Author | Year |
---|---|---|---|
1 | The weighted joint density method leads to improved characterization of jointing | A Palmström et al | 1996 |
2 | A discussion on the Hoek–Brown failure criterion and suggested modification to the criterion verified by slope stability case studies. | Sonmez H, Ulusay R. | 2002 |
3 | Quantification of the Geological Strength Index Chart | Hoek, E., Carter, T.G., Diederichs, M.S. | 2013 |
Dependent Models
The outputs of the following computer vision models are used:
Model Name | Model Type |
Fracture Detection and Classification | Object Detection |
Drillers Break | Object Detection |
Fracture Mask | Instance Segmentation |
Geotechnical Weathering Intensity | Classification |
Data Processing
Datarock has developed a detailed method for calculating a proxy of the Geological Strength Index (GSI) by integrating various Datarock products such as Weighted Joint Density, Geotech Weathering Intensity and Joint Roughness Coefficient.
The following steps provide a structured description of the method:
Calculating Structural Rating (SR)
Weighted Joint Density as basis for Volumetric Joint Count
As described by A Palmström et al,1996, wJd is practically the same as Volumetric Joint Count (Jv), therefore our calculated wJd has been used as the basis (see wJd product description for details).
Take the wJd for a given interval. This will be called .
If residual soil exists within the interval (as detected by the Geotech Weathering Intensity model), wJd will be updated by assigning 10 fractures per 10cm of residual soil:
This value is then in the calculation of the Structural Rating.
Determining Structural Rating (SR)
The Structural Rating on the y-axis of the GSI chart is calculated using the wJd value. The relationship between SR and wJd is given by the equation as described by Sonmez H, Ulusay R., 2002:
As derived from empirical data, the Structural Rating quantifies the structural complexity of the rock mass.
Calculating Surface Condition Rating (SCR)
SCR includes considerations of infill rating, weathering, and joint roughness. However, it has been determined that it is not possible to reliable determine infill rating from a core photo, and therefore the SCR is determined based on weathering and JRC (Joint Roughness Coefficient) values. This is the primary reason we label this product as GSI proxy.
Roughness Rating (Rr)
The Roughness Rating is determined using Datarock’s Joint Roughness Coefficient as its basis (see JRC product description for details).
The JRC values are converted to a 0-6 scale using the following polynomial function (established by fitting a polyline to empirical data):
Weathering Rating (Rw)
The weathering score is determined by identifying the most dominant weathering type in the interval and assigning an associated Weathering Rating. The Weathering Score has been multiplied by 1.5 to take into account the absence of Infill Rating data.
Weathering Intensity | Weathering Score | Weathering Rating (Rw) |
---|---|---|
Residual Soil | 0 | 0 |
Completely Weathered | 0 | 0 |
Highly Weathered | 1 | 1.5 |
Moderately Weathered | 3 | 4.5 |
Slightly Weathered | 5 | 7.5 |
Fresh / Unaltered | 6 | 9 |
GSI Calculation from the Quantified Chart
The GSI value is determined by digitising the GSI plot on the surfer and obtaining the surface equation (a quadratic-second order surface). With the calculated x (SCR) and y (SR) coordinates on the GSI chart, these values are plugged into the surface equation to yield the GSI value, providing a quantified measure of the rock mass quality.
This method provides a systematic approach to quantifying the GSI by integrating various rock mass characteristics, as detailed in the paper. The use of empirical relationships and polynomial functions allows for a more objective and quantifiable assessment of the GSI, contributing to a standardised evaluation of rock mass conditions.
Output Intervals
Default interval length: 3m
Customisable interval available: Yes
User Data
User data may be provided to the Datarock team via csv in the following format:
· HoleID_sampling_intervals_GSI.csv
CSV file to contain the following headers:
File Header | Description |
depth_from | Start of interval |
depth_to | End of interval |
Data Output
Results from this product is delivered in a batch nature.
Integration of the required technologies into Datarock production is ongoing.
The available CSV files include the following:
ProjectID_HoleID_GSI_3m.csv
ProjectID_HoleID_GSI_by_user_intervals.csv
Both CSVs contain the following headers:
File Header | Description |
hole_id | Customer’s Hole ID |
depth | Depth of fracture |
depth_from | From depth for the fracture detection bounding box |
depth_to | To depth for the fracture detection bounding box |
wjd | Weighted joint density |
wjd_measurable | Weighted joint density using only “measurable” fractures |
rqd_wjd | RQD - Weighted Joint Density measures rock solidity by assessing fracture frequency and size. |
rqd_wjd_measurable | Assessment of rock quality by quantifying fracture impact on rock mass integrity. |
weathering_score | Weathering Score evaluates the degree of rock degradation due to environmental exposure. |
SRC_JRC | SRC_JRC is a measure that evaluates the shear strength and roughness of rock joints for stability analysis |
SR | Structural Rating |
SRC | Surface Roughness Coefficient |
gsi | Geotechnical Strength Index |
Product Limitations
Limitations | Comments |
---|---|
Lack of Infill Data | The absence of infill rating in the Surface Condition Rating (SCR) calculation means that the model may not fully capture the influence of infill materials on the mechanical behavior of discontinuities, despite the scaling adjustment. |
Dependence on Visual Inspection | GSI is traditionally estimated through visual inspection. The subjective nature of visual assessment can lead to variability in GSI values assigned by different assessors, potentially affecting the consistency and reliability of results. |
Document Version
Version | Date | Author | Rationale |
---|---|---|---|
1 | 22 Jan 2024 | L Yanez | Initial release |