OG90
Course Contents
Module 1: Foundations of Oil and Gas Data Analytics
- Introduction to analytics in upstream, midstream and downstream operations
- Data types across the asset lifecycle: structured, unstructured, real-time and spatial
- The analytics value chain: descriptive, diagnostic, predictive and prescriptive
- Overcoming data silos: integrating engineering, subsurface and business records
- Formulating business questions and defining analytical objectives
- Understanding variance, distributions and data quality parameters in operations
- Role of domain experts in verifying analytical insights and recommendations
Module 2: Data Preparation, Statistics and Visualisation
- Data cleaning workflows: handling missing values, outliers and sensor noise
- Time-series data analytics: sorting trends, tracking seasonality and moving averages
- Statistical analysis: identifying correlation, assessing causation and regression lines
- Principles of effective visualization: selecting charts for technical audiences
- Dashboard design parameters: tracking key performance indicators and alerts
- Communicating technical data insights clearly through structured reporting
- Evaluating data profile summaries and validating data integrity baselines
Module 3: Subsurface, Drilling and Well Data Analytics
- Data workflows for seismic records, well logs and geological metrics
- Reservoir surveillance analytics, decline curve tracking and production forecasting
- Drilling performance benchmarking, non-productive time (NPT) and bit wear analysis
- Evaluating well test records, pressure transients and completion effectiveness
- Production allocation models, cross-flow diagnostics and well performance checks
- Analysis of deferment logs, downtime events and well workover interventions
- Data-driven decision support for subsurface risk and asset placement optimization
Module 4: Production, Reliability and Operational Analytics
- Equipment condition monitoring, degradation analysis and predictive maintenance lines
- Process performance tracking, energy efficiency metrics and emissions monitoring
- Flow assurance data tracking: predicting constraints, wax, hydrates and scale
- Alarm systems analytics, chattering alarm management and event log filtering
- HSE leading indicators, incident trend analytics and safety risk profiles
- Supply chain analytics: inventory tracking, lead times and marine logistics logs
- Commercial metrics: connecting operating performance with cost and asset margins
Module 5: Predictive Analytics, Governance and Implementation
- Conceptual frameworks for predictive modeling and prescriptive automation
- Feature engineering: selecting, scaling and transformational variables
- Introduction to classification, clustering and anomaly detection in operations
- Factoring uncertainty, probability profiles and scenario selections into models
- Model deployment pathways, software versions, validation and human oversight
- Data governance protocols, operational security, and responsible technology application
- Developing a phased site-specific data analytics roadmap and implementation case