Objective
time data processing, visualisation, and performance
optimisation. Participants will explore
analytical techniques to enhance operational efficiency,
reduce Non-Productive Time
(NPT), and detect drilling anomalies through machine
learning and time series analysis. By
the end of the course, learners will be proficient in using
data-driven approaches to
optimise drilling operations and improve decision-making.
Duration: 20+ hours
Prerequisites: This course is ideal for Petroleum Engineers, drilling engineers, data analysts, and professionals, as well as students seeking to innovate drilling operations through data-driven approaches. No prior data analytics experience required.
Career-Oriented Learning Objectives
Upon successful completion, participants will be able to:
1.
Perform real-time drilling analytics using
modern data visualisation techniques to identify drilling anomalies and
optimise performance.
2.
Apply machine learning techniques to optimise ROP,
WOB, and identify potential downhole tool failures.
3.
Leverage analytical workflows to mitigate NPT, including
stuck pipe analysis and cluster-based strategy evaluation.
4.
Develop insights from drilling time series data
for pattern recognition, such as wellbore instability, borehole cleaning issues,
and gas influx events.
5.
Build competency in interpreting drill string
dynamics using advanced vibration and frequency analysis to assess structural
risks and tool integrity.
Course Deliverables:
·
Course Completion Certificate
·
Access to recorded sessions (for a limited time)
·
Python-based Jupyter notebooks and codes
·
Real-world datasets (synthetic + actual usecases)
·
Reference materials and reading guides
·
Post-training career guidance session
Topics to be covered: -
1. Introduction to drilling data analytics
- Real-time drilling methodology
- Drilling dataset types and formats
- Analytical workflows
- Value Proposition
2. Real-Time Drilling Visualisations.
- 3D well trajectory visualisations
- Drilling parameters heatmap
- Radar chart for wellbore stability and drilling efficiency
- Multipaneled time series plots
- Drill string vibration spectrogram.
3. Mitigating Non-Productive Time (NPT) with Analytics
- Cluster Analysis for NPT/strategy
- Exploratory analytics for drilling performance qualifiers
- Stuck pipe analysis
4. Drilling parameters Optimization
- Drill bit optimization analytics
- Rate of Penetration (ROP) optimization with ML
- Weight on Bit (WOB) optimization with ML
5. Drilling Time Series Pattern Recognition
- Predicting downhole motor failures
- Identifying wellbore instability
- Drill bit wear estimation
- Borehole cleaning assessment
- Detecting formation changes
- Gas kicks and Influx detection
6. Drill string Dynamics and Analytics
- Dynamic analysis of stick-slip motion
- Torque and speed vs time
- Wavelet decomposition and statistics for accelerometer
signals
- Time frequency analysis of Torsional, longitudinal and
lateral vibration
- Quantification of drill string integrity risks.
Frequently
Asked Questions
Who should attend this course?
Engineers, geoscientists, data analysts, and
professionals in drilling operations looking to
upskill in data analytics.
Is programming experience required?
Basic knowledge of data handling is helpful, but the
course provides guided analytics
workflows suitable for all levels.
Will I receive a certificate?
Yes, participants will receive a course completion
certificate recognized by industry
professionals.
Are real datasets used in the course?
Yes, real and synthetic datasets simulating field
conditions will be used for practical
learning.
Can this course help in job transitions to data-centric
roles?
Absolutely. It enhances your profile for roles such as
Drilling Data Analyst, Real-time
Engineer, and Drilling Optimization Specialist.
Will there be hands-on sessions?
Yes, every module includes hands-on exercises and case
studies to ensure applied
learning.
Can I apply the concepts immediately in my job?
Yes, the course is designed for practical application
with workflows you can integrate into
ongoing drilling operations.
