APPARATUS, SYSTEM AND METHOD FOR THE EFFICIENT STORAGE AND RETRIEVAL OF 3-DIMENSIONALLY ORGANIZED DATA IN CLOUD-BASED COMPUTING ARCHITECTURES

• US 20160063091A1
• Filed: 11/09/2015
• Published: 03/03/2016
• Est. Priority Date: 10/18/2011
• Status: Active Grant

• Current Assignee: Ubiterra Corporation
• Original Assignee: Ubiterra Corporation
• Inventors: Flanagan, Peter W.
• Granted Patent: US 10,482,107 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01V 1/302 in 3D data cubes
• CPC Class Codes: G01V 1/345 Visualisation of seismic data or attributes, e.g. in 3D cubes
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 3/0611 in relation to response time
• CPC Class Codes: G06F 3/064 Management of blocks
• CPC Class Codes: G06F 3/067 Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
• CPC Class Codes: H04L 67/568 Storing data temporarily at an intermediate stage, e.g. caching

Abstract

A cloud based storage system and methods for uploading and accessing 3-D data partitioned across distributed storage nodes of the system. The data cube is processed to identify discrete partitions thereof, which partitions may be organized according to the x (e.g., inline), y (e.g., crossline) and/or z (e.g., time) aspects of the cube. The partitions are stored in unique storage nodes associated with unique keys. Sub-keys may also be used as indexes to specific data values or collections of values (e.g., traces) within a partition. Upon receiving a request, the proper partitions and values within the partitions are accessed, and the response may be passed to a renderer that converts the values into an image displayable at a client device. The request may also facilitate data or image access at a local cache, a remote cache, or the storage partitions using location, data, retrieval, and/or rendering parameters.

Claims

1. A method of efficiently managing a data set in a cloud storage array comprising the operations of:

partitioning a three dimensional data set into a plurality of related data sets; and

storing each of the plurality of related data sets into a plurality of respective storage nodes within a storage cloud.

2. The method of claim 1 wherein:

each data set of the plurality of related data sets has a first axis identifier, a second axis identifier and a plurality of values along the third axis;

the plurality of related data sets comprising a plurality of groups of data sets with each group comprising a range of x-axis identifiers and a range of y-axis identifiers;

the operation of storing comprising;

storing each group of data sets into the plurality of respective storage nodes.

3. The method of claim 2 wherein each data set comprises a set of seismic trace data with the x-axis identifier comprising an inline value of the seismic trace data, the y-axis identifier comprising a crossline value of the seismic trace data, and the plurality of values along the third axis comprising reflection data at intervals wherein the intervals are time intervals or depth intervals.

4. The method of claim 2 further comprising generating a unique partition key for each group of data sets, the unique partition key associated with one of the plurality of respective storage nodes.

5. The method of claim 4 wherein the unique partition key is based upon a combination of the integer values of:

x-axis identifier/x-axis group length and y-axis identifier/y-axis group length.

6. The method of claim 5 wherein the x-axis identifier is an inline value and the x-axis group length is 32 and wherein the y-axis identifier is a crossline value and the y-axis group length is 32.

7. The method of claim 4 further comprising generating a unique sub partition key for each data set within a group of data sets.

8. The method of claim 7 wherein the unique sub-partition key is based upon a combination of x% (x-axis group length) and y% (y-axis group length)

9. The method of claim 8 wherein x is an inline value, the x-axis group length is 32, y is a crossline value, and the y-axis group length is 32.

10. The method of claim 5 wherein the unique partition key is based further on the combination with the integer values of z-axis identifier/z-axis group length, and further comprising generating a unique sub-partition key using z% (z-axis group length).

11. The method of claim 1 wherein each of the plurality of respective storage nodes is a virtual storage node.

12. A method of obtaining data from cloud storage comprising:

generating a request that determines whether a data image is available in a local cache, determines whether data values are available in a remote cache to render the data image when the data image is not available in the local cache, and obtains the data values for the data image from a plurality of remote storage nodes when the data values are not available in the remote cache.

13. The method of claim 12 wherein the request comprises a uniform resource locator comprising a network location, a retrieval parameter and a rendering parameter.

14. The method of claim 13 wherein the data values comprise a plurality of seismic traces data values, and wherein the network location is a network address for a server managing a retrieval of the data trace data values from the plurality of remote storage nodes, the retrieval parameter includes at least one trace identifier, and the rendering parameter includes data processing information applied by a rendering application run against the data values.

15. The method of claim 13 wherein the network location comprises the network address of a server that manages the retrieval and rendering of data images from a cloud storage, the retrieval parameter includes at least one of an inline value, a cross line value and a time value.

16. The method of claim 12 wherein the local cache is a browser cache and wherein:

a full uniform resource locator comprising a network location, a retrieval parameter and a rendering parameter are used to access the data image in the browser cache;

the network location and the retrieval parameter are used to access the data image in the remote cache, the rendering parameter being used by a rendering application to generate the data image; and

the retrieval parameter use to generate a plurality of partition keys to retrieve the data values from the plurality of remote storage nodes.

17. The method of claim 12 wherein each of the plurality of remote storage nodes is a virtual storage node.

18. A computing system comprising:

at least one server computing device configured to execute a plurality of executable instructions to perform the operations of;

partitioning a seismic data set into a plurality of data partitions, each of the plurality of data partitions comprising a group of related seismic trace data values;

generate a plurality of unique storage keys for the plurality of data partitions such that each of the plurality of unique storage keys is associated with a respective plurality of unique storage partitions.

19. The computing system of claim 18 wherein the plurality of executable instructions are further configured to provide the operation of:

storing each group of related seismic trace data values in a respective one of the unique storage partitions according to one of the plurality of unique storage keys.

20. The computing system of claim 19 wherein the plurality of executable instructions are further configured to provide the operation of:

generating the plurality of unique partition keys based on the combination of the integer division operations;

inline value/denominator one and crossline value/denominator two, wherein denominator one comprises a range of inline values and denominator two comprises a range of crossline values.

21. The computing system of claim 20 wherein the plurality of executable instructions are further configured to provide the operations of:

receiving a request for a seismic data slice; and

obtaining the seismic trace data values from the respective unique storage partitions using the unique storage keys.

22. The computing system of claim 21 wherein the seismic data slice is an inline slice, a crossline slice, a time slice, an arbitrary slice or a complex surface.

23. The computing system of claim 21 wherein the plurality of executable instructions are further configured to provide the operation of:

obtaining the at least one trace and a plurality of additional traces from the data partition; and

passing the at least one trace and the plurality of additional traces to a renderer whereby the traces are rendered into an image.

24. The computing system of claim 23 wherein the traces are rendered into the image based on one or more rendering parameters received in the request.

25. The computing system of claim 18 wherein each of the plurality of unique storage partitions are virtual storage partitions.