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Mind the Gap: Data Migration and Metadata Quality

02/07/2018

Acquiring new assets and the accompanying datasets often means dealing with another organization’s data quality and completeness standards. Geoscientists and data managers must find a way to “mind the gap” caused by missing data records as they begin to reconcile their seismic database through a data compliance process.  Having a methodical approach to dividing and conquering the volumes of records associated with seismic data assets will help ensure that the new datasets are truly complete and workstation ready.

This article reviews the first step of a larger three part data compliance process that should be at the core of every oil and gas company’s data management program. After reviewing data migration and metadata quality, the second step is to evaluate the data contracts. The third and final phase would be to reconcile the data contracts to the data itself.

Reviewing Migration and Metadata Quality

If an organization has acquired the assets from another company, data management standards and data governance will come into play as the data migration process begins. Data is typically handled in silos – the geoscientists work with the data, operations handle the database and the legal department handles the contracts, but they may not communicate as often as they should across departments.

When doing a migration into the company’s environment, it’s important to have a compliance process in place.  Integrating assets across departments, even though they don’t report to the same person, will ensure that the data streams flow in concert to have a compliant dataset.

Evaluating the Data

Following a structured migration process means profiling the data that is being brought into a new environment. Loading the new data into an Oracle database that is separate from the production database will help to create a profile of the new data and identify potential issues. The reference data and the metadata will provide insight into the data, values and attributes.

Once that is completed, the next step is to map those attributes into the subsurface data management database. When a company has data coming in from a new source, it’s recommended that the new data is flagged so that it can be differentiated  from the existing data once it’s all mixed together. Companies should determine the key attributes and what fields matter most to the organization and focus on getting those loaded into the database.

After making these evaluations, quite often companies will find that portions of the imported datasets are missing records, such as stacks, field data, observer’s notes and navigation. Without these attributes, the data cannot be reprocessed or sent to workstations, and the company loses the value of the dataset.

Reconciling the Data

Once the seismic dataset has been ingested into the data management database, it’s a good idea to run a health check and see how the data measures up to existing standards within the organization. Most data management applications have some kind of health check, smart maps or analytics that are embedded directly into the data management application.

This process will identify the problem areas where data managers need to focus on “minding the gap” of missing information.  The areas missing metadata will help determine the cleanup projects and the focus that will be required.  Following this exercise, data owners should then investigate their contracts and tie them back to the data records.

Katalyst Data Management has over 40 years of experience assisting oil and gas companies with seismic data asset organization following asset acquisition. The company offers a free online webinar series reviewing the entire data compliance process.  Katalyst’s cloud-based data management solution iGlass is utilized by some of the largest operators in the world.

Contributed by Sue Carr and Trish Mulder for the Day 3 issue of Hart’s E&P Daily News at EAGE Copenhagen.

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