InnerLogix User Group

Data quality management case histories from Anadarko and Chevron show quantifiable benefits.

InnerLogix* is now part of Schlumberger, but it still gets to hold its own user meeting. This year, around 50 heard client presentations on data quality case histories.

Anadarko’s Marty Davis described data prep for the upcoming OpenWorks R5000 migration. This includes legacy Kerr McGee projects (yes, they still have those!) with over 1 million wells and 4 million tops. Davis noted that it only takes about 2 weeks for projects to degrade back to their previous quality level after 6 months of QC work. To counter this, users are now asking for enforced naming standards on horizon picks after years of resisting the idea! The data quality management (DQM) project has reduced the number of projects by 43%, and wells by 31% (half by removing duplicates). Future plans include capturing value added data and adding it to their PPDM (PPDM was a recurring theme this year). Davis said his largest OpenWorks project was about 300,000 wells, and SeisWorks would not launch with that many wells loaded.

Mike Underwood (Chevron) is still one of the industry’s biggest cheerleaders for InnerLogix. Chevron maintains its focus on G&G data quality with established rules at the corporate, business and asset levels. Quality standards are aligned with other concepts like establishing for each data type both a ‘system of record’ and a ‘first source.’ Quality data has led to reduced time spent moving A2D logs from the corporate data repository to OpenWorks.

Patti Bush (Anadarko) presented the new data tracking interface in Petris’ Recall log data management system. The new release has enhanced search, visualization and reporting. Real time notification of new data reception and synch with ESRI’s SDE das also been added. Anadarko adds around 3,000 new well curves a week. The old LAS batch process took four hours and has now been reduced to 30 minutes. Direct export to OpenWorks and Petra is also supported. Rapid search for information such as mud weight in a log header is now feasible as is data export to (what else?) Excel.

During the panel session, one observer remarked that, ‘despite the still heavy focus of data quality on E&P, for many segments of an oil company, a well isn’t a well until it is in SAP.’

* www.oilit.com/links/0906_12.

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