Glossary of Technical Terms Used in Communication & Reporting: Data Item Description ("DID")

Data Item Description ("DID")

Data Item Description (DID): The Blueprint for Oil & Gas Data Exchange

In the intricate world of oil and gas, seamless data exchange is crucial for efficient operations, decision-making, and regulatory compliance. This is where the Data Item Description (DID) comes into play. A DID acts as a standardized, comprehensive blueprint for a specific data element, ensuring consistent understanding and utilization across the entire industry.

What is a DID?

A DID is a structured document that defines a specific data element, providing detailed information about its:

  • Name: A clear and unambiguous identifier for the data item.
  • Definition: A concise and comprehensive explanation of the data item's meaning and purpose.
  • Data Type: The format and structure of the data, including units of measurement, allowed values, and data ranges.
  • Source: The origin of the data and how it is collected or generated.
  • Usage: The intended applications and purposes of the data item.
  • Relationships: Links to other related data items or relevant documents.

Why are DIDs essential in Oil & Gas?

  • Standardization: DIDs promote consistency in data definitions, eliminating ambiguity and misunderstandings across different organizations and systems.
  • Interoperability: They facilitate seamless data exchange between various software applications and platforms, enabling efficient collaboration and information sharing.
  • Data Quality: DIDs enforce data integrity by defining strict rules and validation criteria, ensuring accurate and reliable information.
  • Regulatory Compliance: DIDs help organizations meet regulatory requirements by providing clear and standardized data definitions for reporting and documentation purposes.

Content Outline of a DID Document:

A well-structured DID document typically includes the following sections:

  1. General Information:

    • DID Number/Identifier
    • Data Item Name
    • Version Number
    • Date of Issue
    • Author/Owner
    • Approval Status
  2. Definition and Purpose:

    • Definition of the data item.
    • Purpose and intended use of the data.
  3. Data Attributes:

    • Data Type: (e.g., numeric, text, date)
    • Units of Measurement: (e.g., meters, barrels)
    • Allowed Values: (e.g., specific options, ranges)
    • Data Range: (e.g., minimum, maximum values)
    • Data Format: (e.g., date format, decimal places)
  4. Source and Collection:

    • Source of the data: (e.g., sensor readings, manual input)
    • Method of collection or generation: (e.g., measurement, calculation)
    • Frequency of data collection: (e.g., daily, monthly)
  5. Usage and Applications:

    • Applications of the data item: (e.g., operational analysis, reporting)
    • Relevant workflows or processes: (e.g., production monitoring, risk assessment)
  6. Relationships:

    • Links to other related data items: (e.g., parent-child relationships)
    • Cross-references to relevant documentation: (e.g., industry standards, regulations)
  7. Validation and Quality Control:

    • Data validation rules: (e.g., range checks, consistency checks)
    • Quality control procedures: (e.g., data cleaning, error handling)

Documentation Requirements Description:

For successful implementation, a clear and comprehensive Documentation Requirements Description (DRD) is essential. This document should outline:

  • The scope of the DID project: (e.g., specific data elements, target audience)
  • Methodology for defining and documenting DIDs: (e.g., templates, guidelines)
  • Roles and responsibilities: (e.g., DID owners, reviewers)
  • Workflow for DID creation, review, and approval: (e.g., submission, feedback, acceptance)
  • Data management procedures: (e.g., version control, storage, retrieval)

Conclusion:

DIDs are essential for efficient and accurate data exchange in the oil and gas industry. By standardizing data definitions, promoting interoperability, and ensuring data quality, they facilitate informed decision-making, operational optimization, and regulatory compliance. With a well-defined DID documentation process and robust DRD, organizations can reap the full benefits of this critical data management tool.


Test Your Knowledge

DID Quiz

Instructions: Choose the best answer for each question.

1. What is the primary purpose of a Data Item Description (DID)?

a) To store raw data in a structured format. b) To define and standardize a specific data element. c) To analyze data trends and patterns. d) To automate data collection processes.

Answer

b) To define and standardize a specific data element.

2. Which of the following is NOT typically included in a DID document?

a) Data Item Name b) Data Type c) Software used for data collection d) Units of Measurement

Answer

c) Software used for data collection

3. How do DIDs contribute to regulatory compliance in the oil and gas industry?

a) By providing a framework for data encryption. b) By automating regulatory reporting processes. c) By ensuring accurate and standardized data for reporting purposes. d) By replacing manual data collection with automated systems.

Answer

c) By ensuring accurate and standardized data for reporting purposes.

4. What is the primary benefit of using DIDs for data exchange between different organizations?

a) Improved data security. b) Increased data storage capacity. c) Enhanced data visualization capabilities. d) Seamless interoperability and reduced ambiguity.

Answer

d) Seamless interoperability and reduced ambiguity.

5. What is the role of a Documentation Requirements Description (DRD) in the implementation of DIDs?

a) To define the data collection methods. b) To outline the process for creating and managing DID documents. c) To analyze data trends and patterns for specific data items. d) To automate data validation processes.

Answer

b) To outline the process for creating and managing DID documents.

DID Exercise

Task: Imagine you are working for an oil and gas company and are tasked with creating a DID for the data element "Wellhead Pressure". Follow the outline provided in the text to create a draft DID document, including the following sections:

  • General Information
  • Definition and Purpose
  • Data Attributes
  • Source and Collection
  • Usage and Applications
  • Relationships
  • Validation and Quality Control

Note: You can use fictitious information for specific details.

Exercise Correction

DID Document: Wellhead Pressure

1. General Information:

  • DID Number/Identifier: DID-001
  • Data Item Name: Wellhead Pressure
  • Version Number: 1.0
  • Date of Issue: 2023-10-27
  • Author/Owner: [Your Name]
  • Approval Status: Pending Approval

2. Definition and Purpose:

  • Definition: Wellhead Pressure refers to the pressure measured at the wellhead, which is the point where the wellbore connects to the surface piping.
  • Purpose: To monitor the pressure within the wellbore, providing crucial information for production optimization, safety management, and reservoir characterization.

3. Data Attributes:

  • Data Type: Numeric
  • Units of Measurement: Pounds per square inch (psi)
  • Allowed Values: Range of values based on well and reservoir conditions, with minimum and maximum limits defined based on safety and operational constraints.
  • Data Range: 0 - 5000 psi (example range)
  • Data Format: Decimal with two decimal places (e.g., 1234.56)

4. Source and Collection:

  • Source of the data: Pressure sensors installed at the wellhead.
  • Method of collection or generation: Real-time measurement from pressure sensors.
  • Frequency of data collection: Continuous monitoring, with data logged at regular intervals (e.g., every 5 minutes).

5. Usage and Applications:

  • Applications of the data item: Production monitoring, well performance evaluation, reservoir management, safety and operational control, regulatory reporting.
  • Relevant workflows or processes: Production optimization, well testing, reservoir simulation, safety protocols.

6. Relationships:

  • Links to other related data items: Wellhead Temperature, Flow Rate, Production Rate, Well ID.
  • Cross-references to relevant documentation: Industry standards for pressure measurement, safety protocols for well operations.

7. Validation and Quality Control:

  • Data validation rules: Range checks for pressure values within defined limits, consistency checks with other related data items.
  • Quality control procedures: Periodic calibration of pressure sensors, data cleaning procedures for outlier detection and correction.


Books

  • Data Management for the Oil & Gas Industry by Bruce A. Finlayson - Provides a comprehensive overview of data management practices, including DID concepts, in the oil & gas sector.
  • Petroleum Engineering Handbook by Tarek Ahmed - Covers various aspects of petroleum engineering, including data management and standardization, where DID principles are discussed.
  • Data and Information Management in the Oil and Gas Industry by M. A. Khan - Explores data management challenges in oil & gas and potential solutions, including standardized data description methodologies.

Articles

  • "Data Item Description (DID): A Foundation for Digital Transformation in the Oil & Gas Industry" by [Author Name] - (Search for articles on reputable industry platforms like SPE, AAPG, or OGJ). This hypothetical article title showcases the relevance of DIDs in digital transformation.
  • "The Role of Data Item Description (DID) in Achieving Data Integrity and Interoperability in the Oil & Gas Industry" by [Author Name] - Focuses on the benefits of DIDs in ensuring data quality and seamless data exchange between different systems.
  • "Data Item Descriptions: A Vital Tool for Collaboration and Information Sharing" by [Author Name] - Highlights the importance of DIDs in fostering effective collaboration and communication within the oil & gas industry.

Online Resources

  • Petroleum Industry Standards (POSC): Look for standards related to data exchange and data definitions within POSC documentation.
  • American Petroleum Institute (API): Search for API standards and guidelines relevant to data management and data description.
  • Society of Petroleum Engineers (SPE): Explore SPE publications, presentations, and resources on data management and standards in the oil & gas industry.
  • International Association of Oil & Gas Producers (IOGP): Investigate IOGP guidelines and recommendations for data exchange and data description.

Search Tips

  • "Data Item Description Oil & Gas": This broad search will yield results related to DID in the oil & gas context.
  • "DID Standards Oil & Gas": Refines your search to find articles and resources related to specific standards and regulations regarding DID.
  • "Data Dictionary Oil & Gas": While not identical to DID, a data dictionary is closely related and can be a good starting point to understand data definitions and structure.
  • "Oil & Gas Data Management Best Practices": Search for best practices documents and articles to uncover the role of DID in data management.
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