Spatio-temporal and context-based indexing and representation of subterranean networks and means for doing the same

• US 8,041,517 B2
• Filed: 01/25/2007
• Issued: 10/18/2011
• Est. Priority Date: 01/25/2006
• Status: Active Grant

• Current Assignee: RedZone Robotics, Inc.
• Original Assignee: RedZone Robotics, Inc.
• Inventors: Ommert, William, Thayer, Scott M., Close, Eric C., Velagapudi, Prasanna Kumar, Reverte, Carlos Felipe
• Primary Examiner(s): Barbee; Manuel L
• Application Number:
  US11/627,334
• Publication Number:
  US 20070195712A1
• Time in Patent Office: 1,727 Days
• Field of Search: 702 33- 40, 735/92, 735/98, 736/00, 348/84, 348/125, 382/141
• US Class Current: 702/33
• CPC Class Codes: E21B 47/00 Survey of boreholes or wells monitoring pressure or flow of drilling fluid E21B21/08
• CPC Class Codes: G06F 16/2272 Management thereof
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Abstract

Systems, methods and devices for indexing, archiving, analyzing and reporting pipe and other void network data. Specifically, multi-dimensional indexing and correlation of spatial, temporal, feature, environmental, uncertainty and/or context-based data is synchronized, indexed and analyzed across a wide variety of pipe networks at various times. The present invention preferably includes data represented at several different levels of reference including: referenced to the sensor with which it was collected; referenced to the robot or platform upon which the sensor is attached; and the world. The structure and functionality of the system provides for extensive querying, trouble-shooting and predictive analysis for pipe networks.

Claims

1. A method, implemented at least in part by a computing device having one or more processors, for managing a multi-dimensional data system, the method comprising the steps of:

collecting first pipe data of a first type at a first location and at a first time;

collecting second pipe data of a second type at a second location and at a second time;

processing said first and second data such that the first and second data have a common 3-dimensional spatio and temporal reference frame, wherein said processing is performed by the computing device;

storing said processed data in a data store; and

analyzing said stored data.

2. The method of claim 1, wherein said common 3-dimensional spatio and temporal reference frame is based upon a sensor with which the first pipe data was collected.

3. The method of claim 1, wherein said common 3-dimensional spatio and temporal reference frame is based upon a platform from which a first sensor collected said first pipe data and a second sensor collected said second pipe data.

4. The method of claim 1, wherein said common 3-dimensional spatio and temporal reference frame is based upon a world coordinate system external to the pipe.

5. The method of claim 1, wherein said common 3-dimensional spatio and temporal reference frame is three different reference frames, and

further wherein a first common 3-dimensional spatio and temporal reference frame based upon a sensor with which the first pipe data was collected,

further wherein a second common 3-dimensional spatio and temporal reference frame based upon a platform from which a first sensor collected said first pipe data and a second sensor collected said second pipe data;

and

further wherein a third common 3-dimensional spatio and temporal reference frame is based upon a world coordinate system external to the pipe.

6. The method of claim 1, wherein said collecting steps include the direct collection of data via sensing.

7. The method of claim 1, wherein said collecting steps include the collection of non-sensed data.

8. The method of claim 1, wherein said processing step further comprises the step of multi-dimensionally indexing the processed data to facilitate a user query of the data.

9. The method of claim 1, wherein said analyzing step includes the steps of

creating derivative data based upon said analysis, and

storing said derivative data back into the data store.

10. The method of claim 1, wherein said first location and said second location are the same spatial location, and the first and second times are different from each other but are of similar scale (macro or micro).

11. The method of claim 1, wherein said first and second times are the same.

12. A method, implemented at least in part by a computing device having one or more processors, for managing a multi-dimensional data system, the method comprising the steps of:

gathering source data in spatial, temporal and contextual format related to a pipe segment;

synchronizing said gathered sensor data with existing data of another type, wherein the synchronizing is performed by the computing device;

multi-dimensionally indexing said synchronized data; and

analyzing said data.

13. The method of claim 12, wherein said source data is directly gathered from a sensor.

14. The method of claim 12, wherein said source data is gathered from a non-sensing source.

15. The method of claim 12, further comprising the step of:

Incorporating metadata into said source data.

16. The method of claim 12, wherein said temporal data is micro-time data.

17. The method of claim 12, wherein said temporal data is macro-time data.

18. The method of claim 12, wherein said source data further comprises uncertainty data.

19. The method of claim 12, wherein said source data further comprises feature data.