Services
COURSE
Advanced Machine Learning, Real-Time Analytics and Digital Deployment for Oil and Gas
An Executive-Level, Deployment-Focused Advanced Training Program
Kaynix Global Link LLC,
Loumos Group LLC, and
Texas Southern University, Houston, Texas
Course Overview
As machine learning adoption matures in the oil and gas sector, the challenge shifts from model building to enterprise deployment, governance, integration, and strategic value realization.
Organizations must now design real-time systems, manage sensor connectivity, govern analytical outputs, integrate ML into operational workflows, and ensure regulatory credibility. Poor deployment and governance can erode trust, while well-structured systems can transform performance, safety, compliance, and profitability.
This advanced program equips senior professionals with the skills required to design, deploy, govern, and scale machine learning solutions across
petroleum operations.
The training is practical, technically rigorous, and strategically focused, positioning participants as digital transformation leaders within Nigeria’s petroleum sector.
Target Audience
- Senior engineers and technical leads
- Digital transformation and data leads
- Asset managers and operations managers
- Regulatory technical leadership
- Reliability, integrity, and HSE managers
- Corporate planning and performance leaders
Learning Outcomes
Participants will be able to:
- Design real-time and batch ML deployment architectures
- Apply advanced analytics to drilling, production, reliability, and safety
- Integrate sensor and SCADA data into ML systems
- Develop governance frameworks for ML adoption
- Interpret analytics for executive and regulatory decision-making
- Lead organizational digital transformation initiatives
- Justify ROI and manage deployment risks
COURSE MODULES
MODULE 1: Real-Time Drilling and Operations Analytics
- ROP prediction models
- Drilling dysfunction detection
- Kick and stuck pipe early warning
- WITSML data stream analytics
- Rig decision support systems
- Performance benchmarking
MODULE 2: Production and Field Optimization
- Well test ML interpretation
- ESP and pump diagnostics
- Gas lift optimization
- Brownfield redevelopment analytics
- Flow assurance anomaly detection
MODULE 3: Reliability, Safety and Asset Integrity
- Predictive maintenance systems
- Equipment reliability modeling
- Shutdown prediction
- HSE incident forecasting
- Facility sensor fusion
MODULE 4: ESG, Emissions and Carbon Analytics
- Methane detection models
- Flaring reduction forecasting
- Emissions reconciliation
- Environmental compliance analytics
- CCUS assessment modeling
MODULE 5: Deployment, Governance and Digital Transformation
- Real-time vs batch system design
- SCADA and sensor connectivity
- Dashboards and alert systems
- ML governance and ethics
- Change management strategies
- Capability building in Nigerian organizations
- ROI justification and adoption barriers
Practical Integration Sessions
Participants will:
- Review deployment case studies
- Design enterprise ML workflows
- Map governance frameworks
- Develop digital transformation roadmaps
- Practice executive-level communication of analytics outcomes
Course Duration and Delivery
Duration: 5 Days
Delivery: Executive lectures, technical deep dives, workshops, deployment
simulations
Cost: $6,500 per participant
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