Petroleum Data Analytics and CPDA Preparation Course

Name: Advanced Petroleum Data Analytics & CPDA Exam Preparation Masterclass Course
Availability: InStock

Technical integration, quality controls and analytical workflows for experienced upstream data professionals

Petroleum Data Analytics and CPDA Preparation Course

At a glance

Duration: 2 Weeks
Format: Classroom
Cities: Toronto, Cape town, London, Tokyo, Kuwait, Amman and more
Next session: 8 – 19 November 2026, Toronto
Average fee: 13,950 €

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Advanced Petroleum Data Analytics & CPDA Exam Preparation Masterclass Course

Overview

Advanced Petroleum Data Analytics & CPDA Exam Preparation Masterclass Course is a two-week course for experienced upstream data specialists who leave with an Asset Data Integration and Quality Blueprint. Participants connect petroleum data architectures, well log quality automation, production performance analytics, drilling telemetry analysis, and CPDA examination preparation. The course uses PPDM and OSDU concepts, Python and SQL workflows, geospatial checks, and technical case exercises to reconcile fragmented exploration and production records. Agile Leaders Training Center presents petroleum data analytics and CPDA preparation.

Who Should Attend

Functions responsible for petroleum data analysis, upstream data engineering and enterprise architecture
Teams responsible for subsurface information, well logs and technical data stewardship
Reservoir and production functions responsible for integrated engineering datasets
Drilling and real-time operations functions responsible for sensor records
Data governance, quality and GIS functions responsible for petroleum master records
Technical professionals responsible for CPDA preparation and petroleum information management

The course assumes participants work with petroleum datasets and basic data queries; SQL or Python familiarity supports the exercises, and introductory petroleum engineering is outside scope.

Departments and Industries

The course supports technical departments that integrate asset information across energy operations and service organizations.

Upstream exploration, production and subsurface data management
Reservoir engineering, production optimization and drilling operations
Petroleum data engineering, enterprise architecture and digital oilfield units
GIS, technical mapping, data governance and quality management
Oil and gas operators and oilfield technology service providers
Geothermal energy and carbon storage operations

Learning Objectives

By the end of this course, participants will be able to:

Build petroleum data architectures and master records using PPDM and OSDU concepts.
Apply WITSML, RESQML and PRODML exchange structures and geospatial validation.
Analyze well logs, drilling telemetry and production datasets using Python and SQL.
Evaluate data quality rules, decline forecasts, anomalies and operational performance.
Apply stewardship, security and lifecycle controls to integrated technical information.
Build an asset quality blueprint and analyze CPDA competency scenarios.

Course Agenda

Day 1: Enterprise Exploration and Production Data Architecture

PPDM Well Identification Taxonomy and Petroleum Asset Lifecycle Definitions
Enterprise Well Master Data Schemas and Technical Information Repositories
Upstream Data Architecture Across Exploration, Development and Abandonment
OSDU Data Platform Architecture, Core Services and Common Data Models
Petroleum Metadata Cataloging, Data Lineage and Enterprise Data Discovery; Suggested Exercise: Design an Integrated E&P Data Architecture

Day 2: Subsurface Data Interoperability and Industry Exchange Standards

PPDM Data Modeling for Well, Seismic, Spatial and Petroleum Asset Records
Energistics WITSML Standards for Drilling and Wellbore Data Exchange
RESQML Reservoir Characterization Models and Grid Data Integration
PRODML Standards for Production Surveillance and Operational Information
Coordinate Reference Systems, EPSG Definitions and Spatial Data Validation; Suggested Exercise: Map Technical Data Across PPDM, OSDU and Energistics Structures

Day 3: Automated Petroleum Data Quality Engineering

DAMA-DMBOK Data Quality Principles Applied to Upstream Technical Information
Automated Petroleum Data Profiling, Validation Rules and Quality Thresholds
LAS File Header Normalization and Well Log Mnemonic Standardization
Wellbore Deviation Survey Validation and Trajectory Quality Verification
Production Allocation Reconciliation and Operational Data Consistency Checks; Suggested Exercise: Develop Automated Data Quality Rules and Exception Reports

Day 4: Python, SQL and Petroleum Data Integration Workflows

Python Data Processing Using Pandas and Petroleum Data Analysis Libraries
SQL Queries, Joins and Window Functions for Upstream Operational Datasets
Data Transformation and Integration of Completion Reports and Well Test Information
Geospatial Analysis Using GeoPandas and Petroleum Well Geometry Data
API-Based Data Ingestion from SCADA and Operational Information Systems; Suggested Exercise: Build a Petroleum Data Processing and Reconciliation Pipeline

Day 5: Advanced Well Log and Formation Evaluation Analytics

Digital Well Log Interpretation and Petrophysical Data Preparation
Automated Lithology Classification Using Supervised Machine Learning
Multivariate Anomaly Detection in Geological and Petrophysical Measurements
Gamma Ray Normalization and Well Log Calibration Methods
Predictive Regression Techniques for Missing or Incomplete Log Measurements; Suggested Exercise: Analyze and Validate Multi-Well Petrophysical Datasets

Day 6: Production Engineering and Reservoir Performance Analytics

Production Decline Curve Analysis Using Arps Models and Numerical Fitting
Reservoir Pressure Data Filtering and Operational Trend Interpretation
Virtual Flow Metering and Multiphase Production Estimation Techniques
Waterflood Performance Analysis Using Hall and Chan Diagnostic Plots
Well Shut-In Detection, Downtime Classification and Production Loss Analysis; Suggested Exercise: Develop Production Performance Models and Forecasting Outputs

Day 7: Real-Time Drilling Analytics and Operational Optimization

WITSML-Based Drilling Data Streams and Rate of Penetration Monitoring
Real-Time Rig Sensor Data Validation and Operational Anomaly Detection
Weight on Bit, Torque and Standpipe Pressure Data Interpretation
Predictive Models for Bit Wear and Drilling Performance Indicators
Wellbore Trajectory Reconciliation and Anti-Collision Data Quality Controls; Suggested Exercise: Analyze Drilling Telemetry and Identify Operational Exceptions

Day 8: Enterprise Petroleum Data Governance, Security and Lifecycle Management

Upstream Data Governance Maturity Models and Enterprise Capability Analysis
Petroleum Data Stewardship, Ownership and Responsibility Assignment Matrices
Master Data Management, Authoritative Records and Technical Metadata Governance
Petroleum Information Security, Classification and Controlled Data Sharing
Legacy Petroleum Data Migration, Archiving and Lifecycle Preservation; Suggested Exercise: Develop an Enterprise Petroleum Data Governance and Quality Control Framework

Day 9: CPDA Competency Applications and Integrated Examination Preparation

CPDA Examination Blueprint, Domain Weightings and Technical Preparation Strategies
Petroleum Data Analysis, Integration and Analytical Decision-Making Scenarios
Data Quality Management, Governance and Master Data Management Case Studies
Spatial Data, E&P Lifecycle, Security and Communication Competency Applications
Full-Length CPDA-Style Mock Examination: 200 Multiple-Choice Questions in Four Hours; Examination Performance Analysis, Answer Rationales and Technical Knowledge Gaps

Day 10: Petroleum Data Integration Capstone Practice

Suggested Exercise: Multi-Asset Petroleum Data Quality Audit and Remediation Planning
Suggested Exercise: Real-Time Drilling Telemetry Parsing and Automated Anomaly Classification
Suggested Exercise: Production Data Harmonization and Decline Curve Forecast Calibration
Suggested Exercise: PPDM Schema Mapping and Unified Enterprise Well Master Data Development
Integrated Petroleum Analytics Dashboard and Technical Decision Reporting; Suggested Capstone Exercise: Develop an End-to-End E&P Data Integration and Asset Quality Blueprint

Practical Exercises

The course uses suggested activities with representative petroleum datasets and technical case material.

Suggested activity: map PPDM and OSDU entities and validate petroleum spatial records.
Suggested activity: normalize LAS headers, reconcile SQL and Python datasets, and automate log quality checks.
Suggested activity: fit production decline models, classify drilling telemetry exceptions and assign governance responsibilities.
Suggested activity: complete CPDA-style questions and assemble the Asset Data Integration and Quality Blueprint.

FAQs

Who suits advanced petroleum data analytics training?

Advanced petroleum data analytics training suits experienced upstream data professionals, engineers and technical information specialists who work with exploration and production datasets. Basic querying skills are expected; SQL or Python familiarity supports the exercises.

How does advanced petroleum data analytics differ from introductory CPDA preparation?

Advanced petroleum data analytics adds technical integration, Python and SQL processing, exchange standards, production models and drilling telemetry to competency preparation. Introductory CPDA preparation concentrates on examination knowledge and petroleum data management fundamentals.

Which tools support petroleum data integration?

Petroleum data integration uses PPDM models, OSDU architecture concepts, WITSML, RESQML and PRODML exchange structures, Python, Pandas, SQL and geospatial analysis. Exercise software and datasets are selected during training preparation.

How does petroleum data analytics support production and drilling decisions?

Petroleum data analytics combines validated measurements with decline models, pressure trends, downtime classification and drilling sensor diagnostics. Participants examine uncertainty, quality exceptions and the limitations of predictive outputs before using technical results.

What work product results from petroleum data analytics practice?

The Asset Data Integration and Quality Blueprint combines data mapping, validation rules, analytical findings, stewardship controls and remediation recommendations. CPDA preparation remains independent professional training and does not imply accreditation or award the credential.

Conclusion

Participants take an Asset Data Integration and Quality Blueprint back to their organizations. It connects petroleum data mapping, automated quality checks, technical analyses and stewardship responsibilities across exploration, drilling, reservoir and production information. The course turns disconnected technical records into a traceable improvement plan supported by analytical evidence, exception reports and a defined path for remediation.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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Showing 1-20 of 58 events

Location	Dates	Duration	Mode	Price
Toronto	Week 45, 2026 8 – 19 November 2026	2 Weeks	Onsite	€20,000
Cape town	Week 46, 2026 15 – 26 November 2026	2 Weeks	Onsite	€10,000
London	Week 48, 2026 23 November – 4 December 2026	2 Weeks	Onsite	€14,000
Tokyo	Week 48, 2026 23 November – 4 December 2026	2 Weeks	Onsite	€18,000
Kuwait	Week 48, 2026 29 November – 10 December 2026	2 Weeks	Onsite	€14,000
Amman	Week 49, 2026 6 – 17 December 2026	2 Weeks	Onsite	€10,000
Berlin	Week 51, 2026 14 – 25 December 2026	2 Weeks	Onsite	€14,000
Trabzon	Week 51, 2026 20 – 31 December 2026	2 Weeks	Onsite	€15,000
Abu Dhabi	Week 53, 2026 28 December 2026 – 8 January 2027	2 Weeks	Onsite	€14,000
Phuket	Week 53, 2027 3 – 14 January 2027	2 Weeks	Onsite	€15,000
Addis Ababa	Week 02, 2027 11 – 22 January 2027	2 Weeks	Onsite	€10,000
Madrid	Week 03, 2027 18 – 29 January 2027	2 Weeks	Onsite	€14,000
Tbilisi	Week 04, 2027 25 January – 5 February 2027	2 Weeks	Onsite	€15,000
Marbella	Week 04, 2027 31 January – 11 February 2027	2 Weeks	Onsite	€14,000
Tashkent	Week 05, 2027 7 – 18 February 2027	2 Weeks	Onsite	€15,000
Nairobi	Week 06, 2027 14 – 25 February 2027	2 Weeks	Onsite	€10,000
Rome	Week 08, 2027 22 February – 5 March 2027	2 Weeks	Onsite	€14,000
Dubai	Week 09, 2027 1 – 12 March 2027	2 Weeks	Onsite	€13,000
Lisbon	Week 09, 2027 1 – 12 March 2027	2 Weeks	Onsite	€14,000
Bangkok	Week 09, 2027 7 – 18 March 2027	2 Weeks	Onsite	€15,000

Frequently asked questions

What does this course cover?

OverviewAdvanced Petroleum Data Analytics & CPDA Exam Preparation Masterclass Course is a two-week course for experienced upstream data specialists who leave with an Asset Data Integration and Quality Blueprint. Participants connect petroleum data architectures, well log quality automation, production performance analytics, drilling telemetry analysis, an…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

Petroleum Data Analytics and CPDA Preparation Course