This document details Datarock’s products Fracture Frequency and Spacing.
Contents
Dependent Models
The outputs of the following models are used to determine Fracture Frequency and Spacing:
Model Name | Model Type |
Fracture Detection and Classification | Object Detection |
Drillers Break | Object Detection |
Data Processing
The outputs of the Fracture Detection & Classification and Drillers Break models are combined to create an understanding of natural fractures, allowing fracture frequency to be calculated.
Detection of Fractures and Mechanical Breaks
Several fracture types are detected by the Fracture Detection and Classification model, and are summarised in the table below.
In addition, drillers break marks are detected by the Drillers Break model to differentiate between natural and mechanical breaks. If a drillers break mark is located within 5cm of a fracture detection, the fracture will be flagged as mechanical.
The following images show example detection and classifications of fractures. In the second row, first fracture from the left, it can be seen that no fracture shown due to the presence of the drillers break marks.
Fracture Counts
To calculate the fracture frequency, Datarock calculates an Equivalent Fracture Count for a given interval using the equivalent counts shown below. In addition to counting each fracture detection, the equivalent fracture counts are applied to incoherent zones.
Fracture Type | Description | Equivalent Fracture Count |
Measurable | A fracture, with single interface and clear shadow line that allows structural measurements automatically approximated. | 1 |
Displaced | A fracture, with single interface, however either one or both pieces of core have dislodged/ rotated from their original position creating a physical gap between fracture edges. | 1 |
Jigsaw | Multiple fractures that intersect each other with pieces well fitted together or slightly displaced | 2 fractures / 100mm |
Broken | Multiple fractures that intersect each other that do not fit together well with larger spaces between them between them | 4 fractures / 100mm |
Rubble | Multiple pieces of small rocks, pebbles, fine rubble and/or powder between two pieces of core | 5 fractures / 100mm |
The resultant equivalent fracture count is then used to calculate the fracture frequency and spacing for given intervals. These counts can be configured via the Fracture detection tab access via the settings cog next to the name of your project page.
Once in this tab, you can then edit the equivalent fracture counts for Jigsaw, Broken and/or Rubble to better match your own equivalent fracture counts (see below). These are preset to the default counts Datarock uses as described above.
NB: you will need to click Submit to save the edits and then re-run the Fracutres product to process the results using the new equivalent fracture counts.
Product Configuration Options
There are no configuration aspects to this product.
Output Intervals
Default interval length: 1.0m
Customisable interval available: Yes, via uploading sample table to platform (see User Data below)
User Data
User data may be uploaded to the platform via csv in the following format:
· HoleID_sampling_intervals_fractures.csv
CSV file to contain the following headers:
File Header | Description |
depth_from | Start of interval |
depth_to | End of interval |
fractures | Number of natural fractures counted on site |
Data Output
Results from this class of models can be obtained using the Download artefacts option from the Actions button in the Model Review tab of Datarock. The available CSV files include the following:
· ProjectID_HoleID_fracture_frequency_by_metre.csv
· ProjectID_HoleID_fracture_frequency_by_user_intervals.csv
· ProjectID_HoleID_fracture_location.csv
The first two CSV files contain the following headers:
File Header | Description |
hole_id | Customer’s Hole ID |
depth_from_m | Start of interval (metres) |
depth_to_m | End of interval (metres) |
depth_from_ft* | Start of interval (feet) |
depth_to_ft* | End of interval (feet) |
interval_metres | Length of interval in metres |
fracture_count | Number of simple fractures detected |
equivalent_fracture_count | Fracture_count plus equivalent fracture count for jigsaw, broken and rubble zones |
mechanical_fracture_count | Number of detected fractures within threshold distance from detected drillers break marks |
driller_break_mark_count | Number of drillers break marks detected |
fractures_per_metre | Calculation of fracture_count divided by interval_metres |
equivalent_fractures_per_metre | Calculation of equivalent_fracture_count divided by interval_metres |
timestamp | Time of model prediction |
fracture_spacing | Inverse of equivalent_fractures_per_metre |
fracture_spacing_category | Categorised description of the fracture spacing |
version | A model version identifier |
*Only included if project depths are in feet.
ProjectID_HoleID_fracture_location.csv provides data for each individual fracture and contains the following headers
File Header | Description |
hole_id | Customer’s Hole ID |
fracture_uuid | Universally unique identifier for the fracture |
depth_from_m | Start depth of the fracture bounding box (metres) |
depth_to_m | End depth of the fracture bounding box (metres) |
depth_from_ft* | Start depth of the fracture bounding box (feet) |
depth_to_ft* | End depth of the fracture bounding box (feet) |
depth_centre | Centre depth of the fracture bounding box. This is used as the actual depth of the fracture |
fracture_class | The class of fracture as predicted by the object detection model |
probability | The probability, or model’s confidence, of the fracture detection |
type | Natural or mechanical fracture |
row_uuid | Universally unique identifier for the row that contains the fracture |
row_url | Datarock URL that contains the fracture |
bounding_box_scaled | Coordinates in the image of the depth registered fracture bounding box |
inference_timestamp | Time of model prediction |
version | A model version identifier |
*Only included if project depths are in feet.
Product Limitations
Limitations | Comments |
Fracture count based on assumed equivalent fracture count in broken zones | This method is based on counting individual simple, single interface fractures, and assumed equivalent fracture counts for broken zones. It is recommended that these assumptions be verified based on customer’s logging schema. |
Reliance on drillers break mark detection | Mechanical breaks are very difficult to classify from a photo, therefore Datarock’s Fracture analysis relies on these breaks being visually identified, usually with a cross adjacent to the break. If mechanical breaks are not identified, the resulting fracture counts will generally be higher than the site logging. |
Document Version
Version | Date | Author | Rationale |
1 | 6 October 2022 | S Johnson | Initial release |
2 | 25 January 2023 | S Johnson | Update mechanical break description |
3 | 29 January 2024 | S Johnson | Update to include depths in feet |
4 | 02 May 2024 | N Pittaway | Update to include editing equivalent fracture counts |