New Item 1.4
PDF: /data/art72.pdf
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The Bibliography lists the papers and presentations that were available at the time the book was written. This page lists additional material that has since become avaiable and is likely to be helpful.
If you would like to suggest (or provide) some more articles, presentations or downloads that you think would be of value to those looking at the site please contact us using the form at the bottom of this page.
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New Item 1.4 | Are you spending too little on data? |
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PDF: /data/art72.pdf |
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New Item 1.3 | There are many ways to understand and improve complex systems, knowing what they are helps |
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PDF: /data/art65.pdf |
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New Item 1.2 | What are the things a data manager in the oil industry should know? |
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PDF: /data/art49.pdf |
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New Item 1.1 | What are data, information and knowledge? |
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New Item 2.17 | Data management should be considered a core competency for all oil companies |
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New Item 2.16 | Should oil companies be expanding or cost saving? |
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New Item 2.15 | Noah Consulting's 'Industry Insight: IM Benchmarking' event April 2013 | http://www.noah-consulting.com/papers/industry-insight-im-benchmarking |
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New Item 2.14 | A paper from the Molten group about the value of good sub-surface data management | http://www.molten-group.com/wp-content/uploads/2013/09/Molten-Data-Management-White-Paper.pdf |
 New Item 2.13 | A comparison of how different industries manage their data, from Oracle | http://www.oracle.com/us/industries/industry-scorecard-1683398.html |
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New Item 2.12 | Detailed models often deliver the most accurate results |
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New Item 2.11 | Sometimes a strategic model delivers better results than a detailed one |
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PDF: /data/art42.pdf |
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New Item 2.10 | Why using decision trees has limited strategic application |
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New Item 2.9 | Using a time budget approach to showing value is of limited utility |
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New Item 2.8 | Five different models that have the potential to demonstrate data's value |
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New Item 2.7 | Changing scale means doing things differently |
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New Item 2.5 | How do you work out the value of a single process? |
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New Item 2.4 | The benefits of being just a little bit better than the next guy |
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PDF: /data/art27.pdf |
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New Item 2.3 | Short introduction to data, information and knowledge |
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PDF: /data/art18.pdf |
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New Item 2.2 | The lessons that a TV Gameshow teaches about risk |
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PDF: /data/art15.pdf |
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New Item 2.1 | Should you be telling other oil companies about your data handling successes? |
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 New Item 3.6 | Carlos Damski has written a book about Drilling from a data perspective, worth looking at | http://drillingdatavortex.com/ |
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New Item 3.5 | Randy Clark (of Noah) on Well Files, Coffee Stains and Cigarette Burns | http://www.noah-consulting.com/papers/of-well-files-coffee-stains-and-cigarette-burns |
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New Item 3.4 | Randy Clark (of Noah) explains the keys to managing Well Files | http://www.noah-consulting.com/papers/how-to-manage-electronic-well-files |
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New Item 3.3 | Introduction to wellbore positioning data | http://www.uhi.ac.uk/en/research-enterprise/wellbore-positioning-download |
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New Item 3.2 | If the strucural model is valuable, shouldn't it be kept for posterity? |
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New Item 3.1 | Building a geological model is not just assembly of pieces |
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PDF: /data/art19.pdf |
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New Item 4.11 | Contrasing the impact of people, process, tools and data helps clarify current issues |
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 New Item 4.10 | Jane McConnell's list of 10 things she hates about current data management | http://blogs.teradata.com/international/title-10-things-hate-subsurface-data-management/ |
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New Item 4.9 | The data landscape emerges from the decisions of data users |
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New Item 4.8 | All good data managers know that paranoia is a good thing |
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New Item 4.7 | A duty of confidentiality holds for all the work data managers do |
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New Item 4.6 | The concept of Maturity for data management is now fairly mature |
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PDF: /data/art17.pdf |
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New Item 4.5 | The rapid increase in data volumes is a sign of past success, not future problems |
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PDF: /data/art10.pdf |
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New Item 4.4 | Why defining standards is complex the Petris view | http://www.petris.com/productfiles/Letter/Dynamic_Standards_Neutral-UT1007.pdf |
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New Item 4.3 | Checklists make it easier to be consistent, why would you not use them? |
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PDF: /data/art04.pdf |
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New Item 4.2 | Nigel Corbin's original introduction of the Data Management roundabout | /data/ECIM2010-corbin.pdf |
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New Item 4.1 | This is intended just for fun, a cutout and make version of Nigel Corbin's Data Management roundabout | /data/roundabout-cutout.pdf |
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New Item 5.6 | Should we have a formal group to coordinate the topic? |
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New Item 5.5 | You have to have a theory in order to see what isn't there |
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New Item 5.4 | What would be in the oil industry Body of Knowledge? |
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New Item 5.3 | Finding a new way to seeing the world is always a good thing |
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New Item 5.2 | Could this whole approach be wrong? What to ask a sceptic |
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New Item 5.1 | A short piece on why even a distorted map can help understand complex territory |
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PDF: /data/art08.pdf |
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New Item 6.11 | 'Fear has Replaced Apathy as the Number One Enemy of Data' by Thomas Redman | http://www.ocdqblog.com/home/fear-replaced-apathy-as-enemy-of-data |
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New Item 6.10 | Writing good data standards is harder than one might think |
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New Item 6.9 | Its not new tools we need, its a change in approach |
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PDF: /data/art53.pdf |
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New Item 6.8 | Dave Blosser (Chevron) and Paul Haines (Noah) on Data Governance at Chevron GOM | http://www.noah-consulting.com/papers/data-governance-at-chevron-gom |
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New Item 6.7 | Without an idea of what should be there how can we see what isn't |
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New Item 6.6 | If you want to be correctly understood you have to be paranoid about words |
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New Item 6.5 | Brevity is important in its place, but sometimes you have to be comprehensive instead |
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New Item 6.4 | Failing to plan is planning to fail, failing to analyse is stupid even when you know you're wrong |
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New Item 6.3 | Changing our outlook would make delivering data management a whole lot easier |
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New Item 6.2 | Data Governance at Devon available from the Noah Consulting site | http://www.noah-consulting.com/papers/making-data-governance-work-at-all-levels-of-the-organization |
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New Item 6.1 | 'Data Governance: We Know We Want It, But What Is It?' presented at PNEC17 Houston 2013 | /data/shawtin-17DM-paper.pdf |
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New Item 7.6 | Precise definitions overcome unexpected complexities |
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New Item 7.5 | Elegant data architecture pays dividends in the long run |
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New Item 7.4 | Jim Crompton (of Noah) on defining Enterprise Architecture | http://www.noah-consulting.com/papers/architectural-interest-enterprise-architecture-defined |
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New Item 7.3 | Pick levels of detail that match your audience not the situation |
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New Item 7.2 | It's understanding the interactions that makes business processes interesting |
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New Item 7.1 | A presentation from the 2007 ECIM conference reviewing different types of architecture pictures | /data/hawtin - ecim 2007.pdf |
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New Item 8.6 | Why is there so little integration in exploration and production data? |
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New Item 8.5 | Data Integration Technology report from 2000 (for those interested in history) | /data/ditep-2000.pdf |
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New Item 8.4 | Adopting new standards can be a difficult change to implement |
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New Item 8.3 | It can be hard to empathise with other people's reaction to change, but publicity can stop them being nasty |
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New Item 8.2 | Just because two people use the same name doesn't mean they are talking about the same thing |
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New Item 8.1 | A short explination of what really makes E&P data standards hard to define |
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New Item 9.3 | Should data management be part of IT? |
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New Item 9.2 | Boasting about the previous success of data initiatives is an essential part of the job |
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New Item 9.1 | A short piece on why contrasting the efficiency of data handling services needs careful thought |
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New Item 11.1 | Too much flexibility is not always a good thing |
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 New Item 13.4 | 'Intertwingled' is a high level overview of the discipline of 'Information Architecture' | http://www.amazon.com/dp/0692225587 |
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New Item 13.3 | When defining tags the goal is to ensure everyone ends up equally unhappy |
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New Item 13.2 | The division between structured and unstructured data is fuzzy |
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New Item 13.1 | An alternate view of the key E&P aspects defined by a PPDM workgroup | https://wiki.ppdm.org/index.php?title=Taxonomy_Dimensions |
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New Item 15.8 | Doing a good job with data quality requires a wide range of concepts |
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New Item 15.7 | When documenting quality rules both the intent and the implementation should be available |
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New Item 15.6 | ETL article on Data Quality in Oil and Gas | http://www.etlsolutions.com/data-quality-in-the-oil-gas-industry/ |
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New Item 15.5 | Gartner study on measuring the impact of data quality | https://www.data.com/export/sites/data/common/assets/pdf/DS_Gartner.pdf |
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New Item 15.3 | Once data is corrupted it can only be fixed if the system has redundancy |
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New Item 15.2 | A review of data quality dimensions as defined by various authors | http://www.information-management.com/news/dimensions-of-data-quality-under-the-microscope-10024529-1.html |
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New Item 15.1 | A short article about data quality dimensions, and how they relate to fish and ska music |
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New Item 16.2 | Making the story interesting is an essential skill |
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New Item 16.1 | Is overselling simple concepts required to get innovative tools funded? |
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New Item 17.9 | One good assessment question is to ask about people, process, tools and data |
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New Item 17.8 | Jezz Kozman and Ed Evans employ maturity metrics to define business strategy | http://www.ndbteam.com/media/2488/bim5_history_and_background_update_2014_v2_4.pdf |
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New Item 17.6 | Showing results in poster form has all sorts of advantages |
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New Item 17.5 | A2 paper sized version of the BigOil poster (6Mb file) showing more detail | /data/bigoil-poster-a2.pdf |
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New Item 17.4 | Maturity is a good metric, but it is not enough |
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New Item 17.3 | The concept of Maturity for data management is now fairly mature |
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New Item 17.2 | 'Putting the Head Back on the Chicken' by Jess Kozman presented at PPDM Perth DM Symposium Aug 2012 | https://www.ppdm.org/downloadFile/568 |
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New Item 17.1 | The standards provide some great checklists when assessing data managment |
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