6 Common Data Quality Issues and the PPDM Data Model

In Production Operations, more and more devices have data collection and the type and frequency of the data collected is growing exponentially. We often hear from organizations about their struggles with their available data. It may be collection, or retention, or the quality. This is even regardless of the size of the organization. At OspreyData, we are specifically focused around Production Operations, and see that there is an industry wide issue with data quality. We asked Pam to share her insights on the data quality challenges that her organization sees and how their efforts with industry have assisted in solving each challenge.

Graphic provided from PPDM.
  1. Everyone wants to have data that can be trusted and using the data rules in the PPDM Rules Library is a way to confirm that your data and third-party data is correct.
  2. Moving data between systems is often difficult and can lead to structural incompatibility. That can be resolved through vendor neutral data formats as found in the PPDM Data Model.
  3. Oil and gas terms like “well”, “completion”, “curve type”, “oil”, “gas” are often best described as hierarchies or taxonomies to help users leverage the data that best supports their needs. Data granularity is best supported through disciplined thinking, faceted taxonomies, and harmonious rules.
  4. Increasing the competence of your staff is made possible by certification and the many training options that are available through PPDM.
  5. Clear asset identification is key in formulating and processing analytics about your assets. Considering that information comes from many sources and is collected from cradle to grave, clarity, integration, transparency and stability are a must.
  6. Semantic clarity is making sure everyone is talking about the same thing. What is a Well, what is a Completion and what is a Well Status contain standard vocabularies, concept based clarity and explicitness which can resolve semantic confusion.

After reviewing these issues, we asked Pam – Do you see a common set of solutions that can be applied to the industry?

Graphic provided from PPDM.

She invited us to look at the PPDM Data Model. It is important because it embeds the industry expertise of hundreds of oil and gas professionals as they understand how data needs to look and behave for them to do their work effectively. The vast amount of business knowledge in the PPDM Data Model is unparalleled, and that’s why it is so often used as a master data store. It is a robust relational data model ideal for Master Data Management strategies. The data model is designed using a process known as the PPDM Way by subject matter experts, data management professionals, developers, regulators, data vendors, application vendors and more.

Today, this knowledge repository is expressed in relational form, but going forward PPDM will be separating the business knowledge from relational technology so that this knowledge can be leveraged in other kinds of data stores.

For more info on these data quality issues and the solutions offered, we invite you to request the “The Evolving State of Data Management in Oil and Gas” webcast with Pam Koscinski, PPDM’s USA Representative, and Ron Frohock, CTO of OspreyData.

We invite you to learn more about PPDM directly at their website!

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