Sensor data compression for downhole telemetry applications

• US 10,465,504 B2
• Filed: 07/28/2015
• Issued: 11/05/2019
• Est. Priority Date: 07/28/2015
• Status: Active Grant

• Current Assignee: Halliburton Energy Services Incorporated (Halliburton Company)
• Original Assignee: Halliburton Energy Services Incorporated (Halliburton Company)
• Inventors: Gao, Chris, Marsh, Laban M., Rodney, Paul F.
• Primary Examiner(s): Betsch, Regis J
• Assistant Examiner(s): Delozier, Jeremy A
• Application Number:
  US15/027,089
• Publication Number:
  US 20170167247A1
• Time in Patent Office: 1,561 Days
• CPC Class Codes: E21B 47/0025 generating an image of the borehole wall using down-hole measurements, e.g. acoustic or electric
• CPC Class Codes: E21B 47/13 by electromagnetic energy, e.g. radio frequency
• CPC Class Codes: E21B 47/18 through the well fluid , e.g. mud pressure pulse telemetry
• CPC Class Codes: E21B 49/00 Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
• CPC Class Codes: G01V 1/40 specially adapted for well-logging
• CPC Class Codes: G01V 3/18 specially adapted for well-logging
• CPC Class Codes: H03M 7/30 Compression speech analysis-synthesis for redundancy reduction G10L19/00; for image communication H04N; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
• CPC Class Codes: H03M 7/3059 Digital compression and data reduction techniques where the original information is represented by a subset or similar information, e.g. lossy compression
• CPC Class Codes: H03M 7/3064 Segmenting
• CPC Class Codes: H03M 7/4031 Fixed length to variable length coding
• CPC Class Codes: H03M 7/42 using table look-up for the coding or decoding process, e.g. using read-only memory H03M7/4006 takes precedence
• CPC Class Codes: H03M 7/46 Conversion to or from run-length codes, i.e. by representing the number of consecutive digits, or groups of digits, of the same kind by a code word and a digit indicative of that kind
• CPC Class Codes: H03M 7/6064 Selection of Compressor

Abstract

A system having a downhole sensor device and a compression device to obtain a sparse representation of data in downhole telemetry applications is described. The downhole sensor device can collect sensor data while the downhole sensor device is within a borehole. The compression device is coupled to the downhole sensor device and configured to receive the sensor data. The compression device can determine a wavelet coefficient vector for at least one row of n-tuple vectors. The wavelet coefficient vector can have a sparse representation of one or more nonzero elements. The compression device can process the wavelet coefficient vector through a set of compression algorithms, and determine a minimal bit cost of the processed wavelet coefficient vector. The compression device can select a compression algorithm from the set of compression algorithms corresponding to the minimal bit cost. The compression device can generate compressed data based on the selected compression algorithm.

Claims

1. A system, comprising:

a downhole sensor device configured to collect sensor data while the downhole sensor device is within a borehole;

a compression device coupled to the downhole sensor device, the compression device configured to;

receive the sensor data from the downhole sensor device, the sensor data having one or more rows of n-tuple vectors where n is a positive even integer, and the sensor data corresponding to image data;

determine a wavelet coefficient vector for at least one row of the one or more rows of n-tuple vectors;

process the wavelet coefficient vector through each of a set of compression algorithms;

determine a minimal bit cost of the processed wavelet coefficient vector based, at least in part, on processing the wavelet coefficient vector through each of the set of compression algorithms;

select a compression algorithm from the set of compression algorithms based, at least in part, on the minimal bit cost;

generate compressed data from the wavelet coefficient vector based on the selected compression algorithm; and

encode an indication into the compressed data, the indication identifying the selected compression algorithm; and

a transmitter configured to transmit the compressed data uphole to facilitate a drilling operation in the borehole.

2. The system of claim 1, wherein the compression device is configured to obtain a sparse representation for each row of the one or more rows of n-tuple vectors.

3. The system of claim 1, wherein the set of compression algorithms includes one or more of a nonzero tree coding scheme, a run-length coding scheme, a priority coding scheme, or an intrinsic mode function coding scheme.

4. The system of claim 3, wherein the compression device is configured to select between the nonzero tree coding scheme or a zero tree coding scheme based on a number of zeroes in the wavelet coefficient vector.

5. The system of claim 1, wherein the compression device is configured to determine a bit cost for each compression algorithm of the set of compression algorithms, the minimal bit cost corresponding to one of the determined bit costs.

6. The system of claim 1, wherein the transmitter is configured to transmit the compressed data uphole from the borehole to a surface decoder via a low data rate communication channel.

7. The system of claim 1, wherein the compressed data is sent in a transmission vector having a second data length, wherein a data length of the n-tuple vectors is greater than the second data length.

8. A method, comprising:

receiving sensor data relating to a formation from a downhole sensor device, the sensor data corresponding to image data having one dimensional data of data length n, where n is a positive even integer;

determining a wavelet coefficient vector for the one dimensional data, the wavelet coefficient vector representing a hierarchical arrangement of the one dimensional data;

processing the wavelet coefficient vector through each of a set of compression algorithms;

determining a minimal bit cost of the processed wavelet coefficient vector based, at least in part, on processing the wavelet coefficient vector through each of the set of compression algorithms;

selecting a compression algorithm from the set of compression algorithms based, at least in part, on the minimal bit cost; and

generating compressed data based on the selected compression algorithm; and

encoding an indication into the compressed data, the indication identifying the compression algorithm; and

sending the compressed data uphole from the borehole to a surface decoder to provide frequent image updates with respect to a drilling operation in the borehole.

9. The method of claim 8, wherein determining the minimal bit cost comprises determining a bit cost for each compression algorithm of the set of compression algorithms, the minimal bit cost corresponding to one of the determined bit costs.

10. The method of claim 9, wherein the set of compression algorithms includes one or more of a nonzero tree coding scheme, a run-length coding scheme, a priority coding scheme, or an intrinsic mode function coding scheme.

11. The method of claim 10, wherein processing the wavelet coefficient vector comprises determining one or more positions of nonzeroes in the wavelet coefficient vector based on the nonzero tree coding scheme.

12. The method of claim 10, wherein processing the wavelet coefficient vector comprises determining a length of a zero-run sequence based on the run-length coding scheme, the wavelet coefficient vector having at least one nonzero element.

13. The method of claim 10, wherein processing the wavelet coefficient vector comprises determining a power ratio of coded coefficients to total coefficients based on the priority coding scheme, the priority coding scheme comprising:

coding wavelet coefficients included in one of a plurality of levels in the hierarchical arrangement;

determining the power ratio of the coded wavelet coefficients over the total coefficients; and

determining if the power ratio is greater than a predetermined threshold, the threshold corresponding to one quantization level.

14. The method of claim 13, further comprising:

coding wavelet coefficients included in a different level of the plurality of levels based on the power ratio determined not to be greater than the predetermined threshold; and

determining that the power ratio of the coded wavelet coefficients in the different level is greater than the predetermined threshold.

15. The method of claim 10, wherein processing the wavelet coefficient vector comprises determining a codebook with alternating functions of binary values based on the intrinsic mode function coding scheme.

16. The method of claim 15, further comprising:

determining a training sample set from the wavelet coefficient vector;

determining an integer K for a desired size of the codebook;

applying a K-mean algorithm on the training sample set to divide the training sample set into K clusters;

determining a K-mean from the K clusters;

decomposing n-tuple vectors of the training sample set having the K-mean by a Hilbert-Huang transformation;

obtaining statistics on the alternating functions included in the decomposed vectors; and

forming the codebook using entropy coding based on the obtained statistics.

17. The method of claim 8, wherein the image data comprises one or more of azimuthal density data, azimuthally focused resistivity data, azimuthally deep resistivity, azimuthal acoustic compressional and shear images, acoustic borehole caliper and reflectance, and spectral natural gamma ray and non-spectral natural gamma imaging.

18. An apparatus comprising:

one or more processors; and

memory comprising instructions that when executed by the one or more processors cause the one or more processors to;

determine a wavelet coefficient vector for at least one row of one or more rows of n-tuple vectors in image data from a downhole sensor, the wavelet coefficient vector having a sparse representation of one or more nonzero elements;

process the wavelet coefficient vector through each of a set of compression algorithms;

determine a bit cost of the processed wavelet coefficient vector for each compression algorithm of the set of compression algorithms;

select a compression algorithm from the set of compression algorithms corresponding to the minimal one of the determined bit costs;

generate compressed data based on the selected compression algorithm;

encode an indication into the compressed data, the indication identifying the selected compression algorithm; and

send the compressed data uphole from the borehole to a surface decoder to facilitate a drilling operation in the borehole.

19. The apparatus of claim 18, wherein the image data comprises one or more of azimuthal density data, azimuthally focused resistivity data, azimuthally deep resistivity, azimuthal acoustic compressional and shear images, acoustic borehole caliper and reflectance, and spectral natural gamma ray and non-spectral natural gamma imaging.