Digital Oilfield and Production Analytics Course

Lesson 1 • Digital Oilfield Architecture Overview

Describes the layered technology stack from field devices to cloud platforms. Prepares students to navigate system integration challenges.

Lesson 2 • Stakeholders and Organizational Roles

Maps the human ecosystem that generates, consumes, and governs oilfield data. Clarifies how analytics outputs serve different decision-makers.

Lesson 3 • Digital Oilfield Concepts and History

Traces the evolution from manual operations to integrated digital systems. Establishes vocabulary and context for all subsequent technical content.

Lesson 4 • Upstream Oil and Gas Operations Overview

Covers exploration, drilling, completion, and production phases as a system. Provides operational context needed to interpret production data accurately.

Lesson 1 • Downhole and Wellbore Monitoring

Introduces permanent downhole gauges, fiber optics, and distributed sensing. Links real-time wellbore data to production optimization decisions.

Lesson 2 • SCADA and Remote Telemetry Systems

Explains how field data is transmitted, aggregated, and displayed in control rooms. Establishes the communication backbone for digital oilfield operations.

Lesson 3 • Data Quality and Validation at the Source

Addresses common data quality issues introduced at the instrumentation layer. Teaches validation techniques that prevent errors from propagating into analytics.

Lesson 4 • Flow Measurement Technologies

Covers multiphase, fiscal, and allocation metering principles and their limitations. Accurate flow data is the foundation of all production analytics.

Lesson 1 • Historian and Time-Series Databases

Covers the architecture and query patterns of process historians and time-series stores. These systems are the primary repository for high-frequency sensor data.

Lesson 2 • Data Integration and ETL Pipelines

Teaches extraction, transformation, and loading patterns for heterogeneous oilfield data. Integrated pipelines enable the cross-domain analytics covered in later chapters.

Lesson 3 • Data Governance Frameworks

Introduces policies, roles, and processes that ensure data trustworthiness over time. Governance structures determine how analytics outputs are trusted by decision-makers.

Lesson 4 • Production Reporting and Allocation

Explains how measured volumes are allocated to wells, fields, and equity partners. Accurate allocation underpins revenue accounting and regulatory reporting.

Lesson 1 • Key Production Performance Indicators

Defines and calculates KPIs including uptime, efficiency, and production rates. These metrics form the scorecard used throughout performance analysis.

Lesson 2 • Production Loss and Deferment Analysis

Quantifies production losses by cause category and assigns accountability. Systematic deferment analysis drives workover and intervention prioritization.

Lesson 3 • Benchmarking and Peer Comparison

Applies statistical benchmarking to compare well and field performance across a portfolio. Identifies outliers and best practices for performance improvement.

Lesson 4 • Nodal Analysis and Inflow Performance

Explains inflow performance relationships and tubing performance curves. Nodal analysis identifies the system constraint limiting production rate.

Lesson 1 • Integrated Reservoir Surveillance Workflows

Combines pressure, rate, and fluid data into a unified reservoir surveillance workflow. Integration across data types improves confidence in reservoir management decisions.

Lesson 2 • Pressure Transient Analysis Fundamentals

Introduces buildup and drawdown test interpretation for reservoir characterization. PTA results calibrate reservoir models used in production forecasting.

Lesson 3 • Rate Transient Analysis

Covers flowing material balance and rate-normalized pressure methods for tight reservoirs. RTA is essential for unconventional asset surveillance and EUR estimation.

Lesson 4 • Fluid Contact and Saturation Monitoring

Explains methods for tracking gas-oil and water-oil contact movement over time. Contact monitoring informs injection strategy and prevents early breakthrough.

Lesson 1 • ESP Monitoring and Diagnostics

Uses motor current, vibration, and downhole gauge data to diagnose ESP health. Early fault detection reduces unplanned downtime and workover costs.

Lesson 2 • Artificial Lift System Types and Selection

Compares ESP, rod pump, gas lift, and other lift methods across operating conditions. System selection criteria directly affect the monitoring and analytics approach.

Lesson 3 • Rod Pump Dynamometer Analysis

Interprets surface and downhole dynamometer cards to assess pump condition. Card shape diagnosis is the primary tool for rod pump optimization.

Lesson 4 • Artificial Lift Analytics and Automation

Applies machine learning and rule-based systems to automate lift monitoring at scale. Automation enables surveillance of large well counts with limited engineering resources.

Lesson 1 • Production Forecasting with ML

Applies time-series and ensemble methods to forecast production rates at well and field level. ML forecasts complement physics-based decline models for portfolio planning.

Lesson 2 • Anomaly Detection in Production Data

Uses statistical and ML methods to identify abnormal patterns in sensor and production data. Anomaly detection is the first line of defense against data quality and operational issues.

Lesson 3 • Model Validation, Deployment, and Monitoring

Covers MLOps practices for deploying and maintaining production ML models in oilfield environments. Sustained model performance requires ongoing monitoring and retraining workflows.

Lesson 4 • Machine Learning Fundamentals for Engineers

Introduces ML concepts, terminology, and workflow from an engineering perspective. Provides the conceptual foundation needed to apply ML to production data problems.

Lesson 1 • Continuous Improvement and Value Realization

Establishes frameworks for measuring, sustaining, and scaling analytics-driven value. Continuous improvement closes the loop between insights, actions, and outcomes.

Lesson 2 • Field-Wide Production Optimization

Applies constrained optimization methods to allocate production across wells and facilities. Field-wide optimization maximizes value under surface, injection, and facility constraints.

Lesson 3 • Production Strategy and Portfolio Planning

Connects well-level analytics to field development planning and portfolio-level decisions. Strategic alignment ensures analytics investments deliver measurable business outcomes.

Lesson 4 • Real-Time Operations Centers

Describes the design and workflows of integrated operations centers that monitor assets remotely. ROCs consolidate surveillance, analytics, and decision-making into a single environment.