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A system to capture store and re use decisions within and across business functions

IP.com Disclosure Number: IPCOM000244236D
Publication Date: 2015-Nov-24
Document File: 6 page(s) / 344K

Publishing Venue

The IP.com Prior Art Database

Abstract

Decisions are complex concepts that are created using a combination of observations algorithms and contextual information The invention describes a system that will capture the building blocks of a decision using an inheritance approach where decisions can be specialized instances within a space or sub space and across business functions The schema modeling the decisions will facilitate not only record keeping for future audit justifications trusted operations but also in an inference drawing exercise where past decisions themselves play the role of input for newer future decision making It can be applied to the Oil and Gas industry to safely optimize production and increase the operational efficiency

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A system to capture, store and re-use decisions within and across business functions

Abstract

Decisions are complex concepts that are created using a combination of observations, algorithms and contextual information. The invention describes   a system that will capture the building blocks of a decision using an inheritance approach where decisions can be specialized instances within a space or sub-space and across business functions.  The schema modeling the decisions will facilitate not only record keeping for future audit/justifications/trusted operations but also in an inference drawing exercise where past decisions themselves play the role of input for newer/future decision making. It can be applied to the Oil and Gas industry to safely optimize production and increase the operational efficiency.

Concept

A decision depends on three fundamental building blocks:

1.       Observable facts

2.       Changeable facts

3.       Historical facts

Facts are observations, measurements, and variables that trigger or prompt a decision making process.  The decision making process outputs or changes one or more changeable facts that will result in the change of the state of a system.  For instance, when the room is stuffy (state), one of the observations or measurements could be the current temperature displayed by the thermostat (an observable fact).  The historical fact in this case could be that when the temperature is above 75oF the room gets stuffy. These two facts go into the decision making process and result in the decision to change the “desired temperature” (the changeable fact) to 72oF.  This could change the state of the room from being stuffy to comfortable.  This is shown in the included figure below:

Figure 1

This invention captures this concept formally by utilizing a hierarchical schema.  At the very top of the tree is a Decision class that will have attributes that are common to every DECISION that is made. Attributes such as:

·         Decision-first-made-on (date/time)

·         Decision-last-modified (date/time)

·         Revision (monotonically increasing number)

·         Area – this could be line of business

·         Decision-makers (one or more individuals or groups)

·         Problem-statement

·         Final approver (one or more individuals or groups)

·         Area-specific-attributes (this leads into the specialization) or facts.

As this DECISION is made in the context of a specific business area or space, the more space specific set of facts is maintained as illustrated in the included figure in UML notation. By capturing facts and decisions a framework for future audits, justifications, or trusted operations is established.

Figure 2

For instance, in the design of a drilling optimization solution the corresponding DECISION object consists of:

·         Observable facts:  measured depth, total vertical depth, mud resistivity, and unconfined compressive strength of the formation

·         Factors that can be changed:  weight on bit, rate of penetration, hook load, etc.

·         Historical facts:  t...