Advanced Oil and Gas Data Management and Analytics Training Course

Why select this training course?

Data management and analytics involve extracting valuable insights from data. Oil and gas companies use data analytics to improve production, increase efficiency, and make better decisions about where to drill for oil and gas. Oil and gas companies can identify and exploit previously undetected oil and gas reserves by analyzing good logs, seismic data, and production data. Data analytics can also help oil and gas companies improve their safety records. By analyzing data from incident reports, operators can identify and correct dangerous patterns in their operations.

Does a lack of competent oil and gas data management affect companies adversely?

Oil and gas data management has evolved into an essential business process and is critical to ensure that oil and gas companies remain competitive. In the past, companies have made poor choices based on the belief that data management was costly. The result was often expensive, slow, ineffective and inaccurate processing with an unacceptably high risk for human error. Today, oil and gas organizations are turning to technology to improve operational efficiency, reduce costs and gain insight into their businesses.

Why are efficient data management and analytics needed by oil and gas companies?

Data management is essential in today’s business environment, particularly because of its importance to risk mitigation, productivity and profitability. Data is flooding into Oil and Gas companies at an accelerating rate – from seismic data, seismic processing software, well logs, well completions, production monitoring systems, and production data management software. Managing this vast volume of information is important to be leveraged effectively. Oil and Gas Data Management Systems collect and organize data based on the company’s needs. These systems enable companies to monitor their activities, analyze their performance and take corrective actions when situations warrant it.

Rcademy’s Advanced Oil and Gas Data Management and Analytics Training Course equip participants with the knowledge to understand the importance of data management in the oil and gas industry and how it can be applied to make business processes more efficient. The oil and gas industry is facing unique challenges. Companies must keep pace with the latest technology and practices to remain competitive. This course will help you to understand the importance of data management in your business processes, from gathering to analyzing information and making decisions based on that knowledge. It will also show how to protect this valuable asset, both physically and technically. Take this oil and gas data management course to learn how to better manage your oil and gas resources. From good data to production and distribution systems, this course will equip you with the tools and techniques needed to improve the efficiency of your business operations.

Who should attend?

The Rcademy’s Advanced Oil and Gas Data Management and Analytics Training Course is suitable for professionals and beginners of Oil and Gas companies:

• Data managers
• Data analyst
• Business analysts
• Graduates and Scholars
• Management consultants
• IT professionals
• Project and product managers
• Entrepreneurs
• Quality Analysts

What are the course objectives?

Rcademy has designed the course revolving around the following objectives:

• To appreciate the need for data management in the Oil and Gas industry
• To gain an understanding of upstream, midstream and downstream operations as well as understand data generated by them
• To learn the application of Big Data analytics in the Oil and Gas industry
• To develop a competitive advantage over peers with efficient Oil and Gas Data Management
• To recognize the best methods for data collection and data organization
• To uncover foundational concepts of data management in Oil and Gas industry

How will this course be presented?

• Interactive sessions
• Use of case studies
• Management games
• Learning preparation of reports, charts, graphs
• Real-time exercises
• Problem-solving and Group discussion sessions

What are the topics covered in this course?

Module 1: Introduction to Data Management

• Data management cycle
• Upstream Oil and Gas Data Management
• Data Domains
• Collection and types of field data
• Data management platforms
• Understanding databases

Module 2: Big Data Analytics

• Five V of Big Data
• Increase of Big Data in the Oil and Gas Industry
• Analyzing seismic data
• Applications of Big Data in the Oil and Gas Industry
• Challenges of Big Data in the Oil and Gas Industry

Module 3: Data Collection

• Reservoir management
• Data collection through downhole sensors
• Structured, unstructured and semi-structured data
• Upstream, downstream and midstream data

Module 4: Data Organization

• Classifying data
• Why is data organization important?
• Making data scalable
• Making data adaptable and customizable

Module 5: Centralized Data Management System

• Advantages of a Centralised data management system
• Integrated data management system
• During price volatility in Oil and Gas industry
• Target areas for cost saving

Module 6: Skills for Data Management Professionals

• Identifying patterns
• Analyzing data
• Navigating through database software
• Maintaining data integrity
• Database designing and planning

Module 7: Geospatial Data

• Geospatial Data Quality
• Data Storage
• Data Architecture and repositories
• Geographical Information system technology
• Sources of geospatial data

Module 8: Data Quality in Oil and Gas Industry

• Data Quality management
• Data Accuracy
• Data Completeness
• Data quality issues
• Problems with data Quality in the Oil and gas industry

Module 9: Data Management in Exploration and Referencing

• Master Data and Reference Data
• Drilling data management
• Logical and Physical Data Model

Module 10: Data Security

• Methods of securing data
• Visualizing security data
• Data security technologies: data encryption, data masking
• Data resilience

Module 11: Data Transfer and Integration

• Analyzing source products
• Data transfer tool
• Data migration
• Delivering migrated data

Module 12: Data Governance

• Need for Data Governance in businesses
• Data Governance delivery framework
• Case study on data Governance