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AF hierarchy best practice in Upstream O&G

César_CF_PLU

Good afternoon guys,

 

Just wondering if you are aware of some standards or best practices already defined regarding the most efficient way to structure an upstream asset hierarchy in AF. I mean, we could organize an AF tree by following a "choke model" (4 groups of reservoir, wells, facilities, delivery), or simply following a field's "natural" organisation (field - north/south region - cluster a/b/c - wells/pumps/vessels/etc - pressure/temperature/etc), or even alphabetically (then a naming convention would be a key issue to resolve first)...so just wondering if some arrangement type has already been identified as optimal for our business. Considering the amount of re-work that would be involved in modifying it, it seems no trivial decision...or is it?

 

Thanks and regards.

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  • Hi,

    I'm firmly of the opinion that there isn't "an" optimal structure for organising things in AF (and this is for any industry).   The most optimal configuration is the one that solves your problems for you.

     

    That may mean you have more than one tree (or even database) in AF that arranges things differently in order to solve different problems.  For example you may arrange wells, etc. by field because you want to get insights into field related problems or you might organise things by geographic (or other grouping) because you want to get insights into energy consumption related problems.  You can minimise the work involved in maintaining that by using the "weak reference" model  to build trees - but that doesn't always work very well and you just have to accept a certain amount of duplication.

     

    I've seen many clients try and build a "one size fits all" structure and they end up spending so long chasing that "holy grail" that they don't solve any business problem or having sub-optimal solutions to different problems.

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  • Hi,

    I'm firmly of the opinion that there isn't "an" optimal structure for organising things in AF (and this is for any industry).   The most optimal configuration is the one that solves your problems for you.

     

    That may mean you have more than one tree (or even database) in AF that arranges things differently in order to solve different problems.  For example you may arrange wells, etc. by field because you want to get insights into field related problems or you might organise things by geographic (or other grouping) because you want to get insights into energy consumption related problems.  You can minimise the work involved in maintaining that by using the "weak reference" model  to build trees - but that doesn't always work very well and you just have to accept a certain amount of duplication.

     

    I've seen many clients try and build a "one size fits all" structure and they end up spending so long chasing that "holy grail" that they don't solve any business problem or having sub-optimal solutions to different problems.

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  • in reply to Ian Gore

    Hi Cesar:

     

    This is great question.  As pointed out earlier, there is no one-way to define the way to build the PI AF hierarchy with the required Analysis, Event Framing and Notifications.  The PI AF hierarchy depends on the Business Process that we need to solve.  There some standards that can be adapted such S95 and others.

     

     

    We have provided some ideas for the process industries in a draft that you get (A Journey towards a Digital Transformation (draft C1-4) in PI Square).  Here, we present a fictitious story of a person that get in charge to implement an operational excellence strategy for their enterprise.  One of the first things that they do was to analyze the current business processes in their plant.  He finds that the planning and operations there is variance huge gap between projected production targets and actuals.  Based on these findings, they designed a Digital Plant Template to solve this particular goal.  The message for you here is to identify one of key problem that you would like to solve.

     

    The Digital Plant Template uses a UNIT Template with the proper metadata (parameters), analytics and event frame generation to transform raw data into operational insights. This is idea is coming from the work that I started in my previous company for monitoring wells.  These are running on target, in troubles, idle. down or maintenance.   Wells were classified according to their life (new, normal, trouble, old).

    In this story, they used the S95 general hierarchy to model a process plant and we included the event frame generation to aggregate the data into meaningful information based on operational events.  The events framed data is then visualized using PI Vision and Microsoft Power Bi (desktop and AZURE).  We created a TechCon Hands-on Lab with a step-by-step procedure to get a plant simulator example to learn from it. (Search for Digital Plant Template and you can find in PI Square). Attached is one of the versions for you.

     

    The suggested strategy starts from the top production level for each unit. Then, it goes inside the unit to define the quality for the each unit and start building soft sensors.  The strategy is to find the operational insights that identify the production constraints and to build predictive models.

     

    You could look at the example and see if you can adapt to the upstream asset hierarchy that you have in mind. 

     

    Warm Regards,

    Osvaldo

    A Digital Plant Template for transforming raw data into Operational Insights.

    JourneyDigitalTransformation DRAFT C1-4 Binder1.pdf