Petrotechnical Data Management - G & G Data

DATA/DATAMNGT

Who should attend?

  • This course proposes an overview of geoscientific Data Management (DM) specifically regarding the subsurface domain. It provides in a practical and effective way, an understanding of DM principles and concepts, as well as methods and tools necessary to participate in structured DM workflow.
Audience :
  • Data managers, information managers, technical managers and assistants, technologists, geologists, geophysicists requiring an introduction to management of specific data types.

Level : Foundation

Course Content

  • INTRODUCTION TO DATA MANAGEMENT

      • Introduction to information management.
      • Data types: definitions.
      • Common Data Management issues.
      • Geo-referenced data: geodesy, topometry, cartography and Geographic Information System (GIS).
  • DATA MANAGEMENT METHODS

      • Data Management best practices, business impact.
      • Overview of Data Management: definitions.
      • Data life-cycle: from inception to destruction (planning, implementation and control activities).
  • THE VALUE OF DATA & DATA MANAGEMENT

      • Benefits of good Data Management.
      • Business case aspects and barriers.
      • Data governance: strategy, organization, policies and standards, projects and issues.
      • Data Management architecture: modeling, technology and tools.
      • Data Management framework, governance, architecture, security.
      • Difference between reference and Master Data Management.
      • Data quality management: definition and dimensions of data quality (accuracy, currency, coverage, relevance, accessibility and comparability).
      • Data quality tools and capabilities.
  • GEOSCIENTIFIC DATA MANAGEMENT

      • Seismic data.
      • Borehole data (drilling report, logs and cores).
      • Well data (production data, well test, workovers).
      • Fluid data: PVT tests and reports.
  • PROJECT DATA MANAGEMENT

      • Project data base construction.
      • Sharing projects:
      • Geomodeling.
      • Material balance model.
      • Reservoir simulation model.
  • INTEGRATION MANAGEMENT SERVICE

      • How integration happens in the real world.
      • Data integration challenges.

Learning Objectives

  • Upon completion of the course, participants will be able to:
  • describe data management and understand data as an asset,
  • describe data life-cycle, the benefits of good data management and its potential value,
  • describe the core data types in the E&P industry and the corresponding best practices,
  • discuss common data management issues and challenges,
  • discuss and manipulate the important components of a data management framework,
  • describe how to map issues with a data management framework.

Ways & Means

  • Interactive presentations and document analysis.