I N NOVATI N G WH I LE DR I LLI N G
The IADC ART Committee recently held
a Virtual Panel Discussion to detail its
progress to upgrade IADC’s bit dull
grading system, which had been widely
used for decades but had become
outdated in today’s environment.
off, washout, cracks, fracture) for different
components within the BHA (bit, MWD,
positive displacement motor, RSS, stabi-
lizer, formation evaluation and perforation
enhancement). Users can also note rea-
sons for pulling the BHA.
Level 2 is designed to give users a
detailed method for reporting issues with
individual components within the BHA. In
addition to the six main damage codes, it
contains separate codes for the location of
the damage, wear severity and field obser-
vations. Users can also note primary and
secondary causes of damage or failure.
Level 3 will standardize classifications
when performing root cause analysis and
conducting post-run investigations of the
BHA, although work on this section is not
scheduled to begin until later this year.
This year, the BHA team expects to
finalize the field coding system for each
of its five sub-groups. So far, the BHA team
has added 13 new categories to describe
the reasons for pulling the BHA, and it
established 46 new damage/failure codes.
Mr Neil said the team will continue to
update these codes once it conducts field
testing later this year.
Case studies
This team focused on collecting case
studies for the most common modes of
dysfunctions encountered while high-
lighting their corresponding post-run
forensic evidence. These case studies will
be used for training, as well as to ensure
that the codes developed by the other
teams are adequate for forensics and con-
tinuous improvement investigations.
Willie Watson, Well Engineering
Manager for Shell, described this team’s
work as a means of synthesizing the work
done by the other teams. It is linking the
damage identified in the new codes from
the drill bit and BHA teams with informa-
tion gathered from its own investigations
and polling of subject matter experts.
“As you start to investigate, you see what
damage is caused by specific drilling dys-
functions,” Mr Watson said. “Our goal is to
pull the information from our investiga-
tions together, combine the forensic evalu-
ation with the actual conditions that drill
bits and the BHAs have been exposed to,
and use that to help us diagnose the failure.”
The team’s work to identify potential
case studies focusing on common failures,
which will be included in a best practice
document, is still ongoing. A group of
subject matter experts continue to review
examples of failures and damage to see
which ones are best suited for develop-
ment as case studies and as best practices.
This group is also reviewing the codes
proposed by the drill bit and BHA code
definition teams to make sure they are
necessary, unique and well understood,
and that accurately describe the damage
and current status of a given component.
This work should be completed by the end
of Q1 2022.
By Q2 this year, the team aims to define
the standards for critical and the “nice to
have” data required for each study and
establish consensus among the teams on
each standard. It will also gather and label
a set of photo and digital data examples of
various damage/failure codes for human
and machine training.
By Q3 2022, when field trials of the updat-
ed bit dull grading system are complete, the
team will document the frequency of occur-
rence of different degradation modes to use
as a priority guide for human and machine
training. After that, the team hopes to cre-
ate a forensics evaluation workflow and
continuous improvement best practices
document for industrywide rollout.
“More and more people are involved
with the data collection process, data
management process, exchanging data
and essentially getting a hold of data so
that it could help them make good deci-
sions,” said David Shackleton, IDS Business
Development Manager at Schlumberger.
To create the guideline, the team inves-
tigated best practices for bit, BHA and sur-
rounding data formats, and for collecting
and classifying digital visualizations such
as photos, videos and 3D models. In one
chapter of the document, the team looks
at different ways of storing and accessing
data, data model types, and current stan-
dards such as PPDM and WITSML. Another
chapter covers good practices in data man-
agement, focusing on the proper ontology,
validation and verification for data.
Collection and storage of example data
was facilitated by cooperation among the
workgroup’s various teams. Based on these
examples, the data management team was
tasked with creating a training data set of
forensics photos with agreed upon codes.
Work is still ongoing for the design,
construction and eventual launch of the
training data set. However, the guideline
offers some suggestions for the industry
to consider. It outlines possible structures
for a training data set, as well as the role-
based permissions companies can use to
establish who gets access to the data. DC
Click here to watch
the Virtual Panel
Discussion on the dull
grading project.
Data management
The data management team focused on
developing a guideline to store codes, digi-
tal images and other metadata about drill
bits. This digital data exchange guideline
will be usable for machine learning tools
and real-time data exchange on the rig.
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