I N NOVATI N G WH I LE DR I LLI N G
Digital technologies
support new workflows
in drill bit forensics
AI and machine learning allow for dull wear data to be easily collected,
digitized and analyzed, leading to better bit designs, optimized drilling
BY STEPHEN FORRESTER, CONTRIBUTOR
A mong the equipment and technology necessary to drill
a well, the drill bit is arguably the most critical piece
of the puzzle. Bit design, a fast-paced world of iterative
enhancements and improvements that enable wells to be drilled
more rapidly and efficiently, considers many downhole factors—
geology, lithology, wellbore geometry, potential interactions with
the bottomhole assembly (BHA)—as specialized engineers seek to
develop bits that can overcome the challenges inherent in today’s
more complex wells.

Highlights Automated digital dull grading
Advanced software that can analyze bit
photos/scans are allowing post-run bit
data to be collected in digital formats, then
analyzed in context with other data sets as
part of advanced forensics analyses.

Automating the bit dull grading process
removes human subjectivity and helps
ensure the data collected is consistent,
accurate and usable.

Both bit and cutter manufacturers can now
get faster, more detailed insights to drive
enhancements to their designs.

14 While drill bits may be the metaphorical tip of the spear, the
process of grading their condition after a run has seen limited
changes over time. Typically, rig crews perform onsite analysis
of the bit, taking photographs of its condition and assigning it
a dull grade based on industry-accepted methodology. However,
this process can be time-consuming and fraught with human
error and inconsistency. To advance drill bit design in line with
the industry’s desire to digitize and automate processes, several
companies have developed new technologies that augment or
replace previous methods.

Dustin Lyles, Vice President of Technology for Taurex Drill Bits,
said the industry has to advance beyond archaic methods for dull
grading of PDC bits.

“The best insight that we have into what’s going on in that
rock-to-bit interaction that’s occurring miles below the earth’s
surface is that dull drill bit that comes back out,” he explained.

“That’s a fingerprint of what type of drilling dysfunctions and
environment the drill bit is seeing while downhole, and being able
to analyze that bit is what gives us insight to produce our digital
workflow and feedback system.”
Knowing that there is intrinsic value in a drill bit is one thing,
but obtaining actionable data is another. Digitizing bit condition
data so it can be used across every drill bit design decision Taurex
makes has been key, Mr Lyles said. Drilling and highly detailed
dull data is fragmented in nature. Runs might be captured for
projects with one specific operator and/or bit part number in
Delaware Basin Wolfcamp B laterals, for example, and decisions
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



I N NOVATI N G WH I LE DR I LLI N G
Above: The Automated Metrology Laboratory (AML) puts
every drill bit that Taurex runs through an automated 3D
robotic scanning procedure.

Right: Data from the initial AML analysis on each drill bit is
pushed into a database containing other data sets to help
“paint a picture about what type of drilling dysfunction
occurred, or what was the driving factor behind the wear and
tear seen on the drill bit,” said Dustin Lyles, Vice President of
Technology for Taurex Drill Bits.

made relative to necessary actions to improve performance with-
in that narrow scope. Taurex, however, believes that understand-
ing the correlative relationship among drill bit design, wear and
application is critical to making more holistic design decisions.

To accomplish this, the company produced a digital dull analysis
model/workflow, which leads into forensic analysis and root
cause failure analysis on a large-scale basis.

The Automated Metrology Laboratory (AML) is the company’s
innovation in automated digital dull grading. Deployed at the
company’s central repair and maintenance facility, every drill bit
that it runs goes through an automated, 3D, robotic scanning pro-
cedure. Within three to four minutes, Mr Lyles said, that scan is
pushed to a remote server, allowing engineers to access and quan-
tify the amount of diamond loss on every individual cutter on that
bit. “Data from the initial AML analysis on each drill bit is pushed
into a relational database to tether dull trends with application,
design, electronic drilling recorder (EDR) and other relevant data
sets necessary to put the pieces of the puzzle together,” he noted.

“Then, we can paint a picture about what type of drilling dysfunc-
D R I L L I N G C O N T R AC T O R • M A R C H/A P R I L 202 2
15