Introduction to Data Management for Operations

DATA/DAMAOPE

Who should attend?

  • From the top floor to the drill floor it is frequently said that “data is an asset”. The purpose of this 3 days course is to illustrate:
  • why data is an asset,
  • what are the main data types used in the E&P industry,
  • the data life circle,
  • various data storing strategies and implementations,
  • the data quality insurance and governance.
Audience :
  • This training has been designed for all technicians and decision makers of the drilling, construction, production and maintenance domain but out of the data-management discipline.

Level : Discovery

Course Content

  • INTRODUCTION

      • The value of a data asset.
      • The main data categories for the drilling (FP), construction, reservoir, production, maintenance and HAS discipline.
      • The data management function as seen by DAMA.
  • DATA GOVERNANCE

      • What is data governance, why it matters.
      • The asset life cycle/the data life cycle.
      • The data shareholder, role and responsibility (RACI).
      • The role of the data stewards, data manager, data scientist…
  • DATA ARCHITECTURE MANAGEMENT USING THE DATA RELATED TO THE WELL DESCRIPTION

      • What is a well (using the PPDM guideline), the importance of using a common vocabulary/semantic.
      • The CFIHOS IOGP data standard.
      • The energistic standards (PRODML, WITSML, RESQML).
      • The OSDU initiative.
  • DATA DEVELOPMENT

      • Develop and maintain logical and physical data models for the production data.
  • DATA OPERATION MANAGEMENT

      • The notion of SLA.
      • Cloud storage.
      • The notion of big data and data lake backups and archives.
      • Data visualization (incl. BI).
      • Data in a GIS.
  • DATA SECURITY MANAGEMENT

      • Manage users (role, privileges…), monitor users authentication.
      • The information confidentiality classification.
      • Data security audit, introduction to ISO 27001.
  • REFERENCE & MASTER DATA MANAGEMENT

      • Definition of both terms:
      • Reference data: used taxonomy, semantic definition of the drilling data (e.g.: API).
      • Master data: drilling data values.
      • Well data integration: the well UWI.
  • DATA WAREHOUSING

      • Descriptive (content description) and transactional data.
      • Use case based on the management of spare part using SAP-PM and SAP-MM
  • DOCUMENT & CONTENT MANAGEMENT

      • Unstructured data: e.g. the installation PIDs.
      • Implementing a Document Management Systems (EDMS).
      • Retention and disposition of document.
  • DATA QUALITY MANAGEMENT

      • The different aspects of “Data Quality”.
      • Make the data “trustable”.
      • Lean and 6-sigma methodologies.
      • Define data quality metrics, measure and control the data quality.
      • Data audit.
  • PROFESSIONAL DEVELOPMENT OF DATA MANAGERS

      • Data management as a recognized discipline.
      • How the oil companies digitalization journey impacts the data manager role.
      • Data managers in others industries.
  • TAKEAWAYS

      • 10 key points about data management to remember.

Learning Objectives

  • Upon completion of the course, participants will be able to:
  • understand the data architecture of their organization,
  • evaluate the quality of the data they consume,
  • participate to the data quality improvement.

Ways & Means

  • Daily lecture and exercises and filed case studies.