I N NOVATI N G WH I LE DR I LLI N G
A point cloud map of a scanned bit can help companies
decide if they want to change drilling parameters to avoid
the same damage seen in the visualization.
sic digitization system can be used immediately after a run . The
goal is to eliminate the inherent inconsistency and unreliability
in human interpretation, while also freeing up engineers to focus
on other critical tasks.
Before such technology was available, laboratory staff would
manually sift through and analyze post-run data. This was
always a laborious task, made more daunting by variation in the
quality of data from the field. Due to the discrepancy in the type
and quality of data coming in, aggregation of the information
into an analytical software package for diagnosis was difficult.
Furthermore, attempting to overlay this data with relevant drill-
ing parameters to truly assess bit performance was extremely
challenging, if not impossible.
“We wanted to build a machine that could be easily operated by
someone with minimal training in a shop, at a lab, at a rig site, or
The bit scanner from Trax Electronics is a roughly 4-ft cube that
can be placed on a rig, in a shop or in a lab. It automatically
takes pictures of the bit to build a 3D visualization.
18 potentially anywhere, and reliably build a 3D visualization,” said
Ron Schmitz, Executive Advisor at Trax. “We use photogramme-
try, which is basically taking photographs from various perspec-
tives around the bit, and build a visualization with that.”
Robotic-controlled, AI-enhanced photogrammetry, or the sci-
ence of making measurements from photographs, is at the core of
the system. The user places the bit within the scanner, a roughly
4-ft cube, and lets the system get to work, with a camera taking
pictures automatically at all relevant angles.
Once those images are input, the output is typically a point
cloud map, which is a drawing, measurement or 3D visualization
of some real-world object or scene. The scan takes approximately
15 to 20 minutes depending on the size of the bit, while it takes
approximately 90 minutes for the AI to compute the dull bit
forensic characteristics. By leveraging and applying this technol-
ogy to dull bit grading, the system produces highly accurate and
repeatable measurements of individual cutter wear in PDC bits, as
well as machine-generated base parameters for the IADC dull bit
grading protocol.
Trax says it sees quantifiable value in having its system on a
rig, in a shop or in a lab. “We feel that there’s a big advantage in
being able to obtain an independent analysis from a third party,”
Mr Schmitz said. “There are also time and cost factors; since we
can provide photographs on site, at a lab or in a shop, you can
view the visualization in a few hours. It may not help you decide
which bit to run, but it could help you decide that you want to
vary drilling parameters to avoid some of the damage you saw
in the scan.”
The point of collecting this data is not simply to understand
what happened to the bit, of course, but also to use the data to opti-
mize drilling. By obtaining reliable, independent cutter-by-cutter
forensics, Trax sees five key areas of bit forensics that will enable
better drilling performance.
First, companies can improve bit design and quality control,
enabling better operator/vendor collaboration and potentially
enhancing drilling and directional performance, particularly in
unconventional wells that are longer and more complex. Then,
drilling dysfunctions can be identified to eliminate cutter dam-
age, ultimately prolonging bit and BHA life and reducing the time
needed for tripping .
Next, bit wear can be managed, which Mr Schmitz said is
critical. “There are a lot of issues around bit wear instead of bit
damage,” he explained. “For example, looking at where the cutter
is located on the bit and if it’s spalled, chipped or broken, people
can get a good idea of what was going on downhole to cause that
damage.” He also noted that often, pulling a bit with no or only
“smooth” cutter wear may not be optimum, as this could indicate
that performance wasn’t maximized. Being able to assess smooth
wear down to “sub-0” levels could be very important in some
applications, as that could mean higher ROP could be achieved
without causing damage. Less wear does not necessarily mean
an optimum run.
The fourth area is increasing data granularity to make big data
analytics possible. “A typical dull code involves an overall average
for the bit as a whole,” Mr Schmitz said. “The new protocol being
considered by the IADC has information across all the cutters on
M A R C H/A P R I L 202 2 • D R I L L I N G C O N T R AC T O R