PNEC Data Integration, Houston

The 12th international conference on petroleum data and information management broke all records with a final head count of 430. Data quality, master data management and unique identifiers remain at the top of the data managers’ wish list. We report on clean-up initiatives from ExxonMobil, Shell, Aera Energy. Petrobras and ENI—and from an enthusiastic panel discussion on the merits of metrics.

According to Robert Meith (Shell E&P Americas) seismic data vendors internal standards are not necessarily aligned with the Shell workspace. To assure consistency in data delivery, Shell drafted a 13 page document ‘Guidelines for Seismic Data Formats and Delivery.’ The document provides details of roles responsibilities, formats (SEG/UKOOA) and transmittals.


Raul Dias Damasceno described how Petrobras used to have multiple SeisWorks projects, many servers and poor project organization. Today there is a single project per basin stored on a filer provided and managed by the IT department. A move from 3DV to CMP files resulted in a 90% disk space saving. Petrobras has also been working on seismic amplitudes in the Santos basin, mistie correction and on the SIRGAS (Geocentric Reference System for the Americas) cartographic reference system cleanup. Petrobras’ seismic data amounts to some 3 petabytes of data.


Mario Fiorani outlined ENI’s essentially in-house developed E&P data and document management system. This spans G&G, production, physical and electronic documents—along with a uniform GIS/Portal interface. Vendor-supplied components include DecisionPoint, Petrobank and the Windchill document management system. The system uses the business object concept as federator, well and other object names are defined in the corporate database and presented in controlled lists—’you never type in a well name!’ Measuring the value of such a system is hard—tangible savings rarely justify the cost of implementation. A better approach is to assess the value of productivity and production improvements. ENI is generally disappointed with vendor’s interoperability offerings.


The issue of data quality is being addressed bottom up—by the ‘quality’ community and top down, by the master data managers. ExxonMobil (XOM) has been using a phased quality improvement approach to its well log curve repository as John Ossage described. XOM is merging its Recall projects to one domain, removing duplicates and synching ids. Data profiling involves locating and validating existing data and deciding where to put the clean-up effort. A composite ‘usability factor’ (UF) was established to facilitate the evaluation. Data quality tests are run as Unix cron jobs and the results presented as a table of UF metrics. UF metrics drive ‘proactive data management.’ Every couple of months ExxonMobil checks its legacy data to make sure there are no process busts. Answering a question on standard mnemonics, Ossage explained that although one might think that ExxonMobil had the kind of clout that would oblige its suppliers to conform, the reality is different. Richard Wylde (XOM) noted how hard it was to execute a sustainable long term quality initiative. Cleanup is too often justified by an initiating event—but sustainability needs a different paradigm. XOM’s engineers have joined the E&P quality initiative. Exprodat’s IQM toolset is used to color code quality and show a scorecard of trends by asset and data type. This initiative is helping to avoid engineers hoarding data in local spreadsheets—still one of the biggest barriers to good data management.

Aera Energy

Bob Bates presented Aera Energy’s enterprise architecture at last year’s PNEC. Since then, the Shell/Exxon joint venture ‘flipped the switch’ to find that it didn’t work! Only around 50% of data was accessible because of quality issues. A data governance program was quickly put into place with process owners, steering teams and data stewards. It’s working now as the data quality improves.


John Kievt described Shell’s search for the holy grail of E&P, a unique well identifier (UWI). A consistent descriptor is required to map between data sets. Mistakes are easily made and hard to fix later and the risk of mistakes increases with inclusion of meaningless numbers or well coordinates. Shell’s UWI is a unique, non-changing identity for the well lifecycle. The system provides a single authoritative source along with aliases used in other systems. Landmark’s Jeremy Eade demoed the system. The process begins in the well design workshop and the UWI is broadcast to engineering systems—along with sequential well bore numbers. A nightly synch pushes data out to other systems (GIS, subsurface projects). Post drill workflows add a definitive directional survey to the corporate database. Geomatics then check it over before pushing the data out to other systems. One commentator remarked that this was all very well but the UWI problem remains with the 5 million or so wells outside of Shell! In which context, the Energistics GWUI project is still completing ‘real soon now.’

Search in E&P

Under the guise of a general paper on search in E&P, Andy James (Halliburton) offered a moderately commercial introduction to the new web interface to Landmark’s Petrobank. After a comparison of search technology from various vendors and a prompt from a questioner, James revealed that Landmark has selected Autonomy’s search engine to power Petrobank Explorer.


A panel session looked at the thorny question of data metrics. Total asked what is the ROI of a $10mm investment in data management? Metrics are in general not done. For Shell, the reserves issue was a ‘wake up call’ that led to more investment in ‘holistic’ IM, bringing databases together. This has reduced time spent looking for stuff by over 50%. Another speaker pointed out that metrics are not to be had for free. They may add 5% to the cost of a project and this money is not usually there. Furthermore the value of metrics is subjective—it could be a week of data loader’s time—or a lost well. Some are uncomfortable with the idea that a digital well log system will help find more oil! Sometimes the metrics have to be dumbed-down to make them believable. Production data often gets more attention, ‘C-level people are more interested in production data than a gamma ray log.’

This article is taken from a longer report produced as part of The Data Room’s subscription-based Technology Watch Service. More from

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