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US5031155A Expired / Lapsed US ⏱️ 0.0 years remaining

Compression and reconstruction of sonic data

Assignee: Schlumberger Technology Corp
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Filing: 1990-05-21
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Granted: 1991-07-09
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Expires: 2010-05-21
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Abstract

Abstract Methods of compressing sonic data acquired as the result of well logging procedures are disclosed. Samples of each digitized formation wave component are characterized as a vector. Eigenvectors based on the formation wave component vectors are obtained, and selected wave components are correlated to the eigenvectors to obtain scaler correlation factors. The eigenvectors and correlation factors together provide a compressed representation of the selected formation wave component, particularly since only a few eigenvectors and correlation factors are required to provide an excellent reconstruction of the formation wave component.

Inventors

  • 👤 Kai Hsu

Bibliographic Details

Application Number —
Jurisdiction US
Data Source google_patents
Last Synchronized 2026-10-31 01:22
CPC Classifications
G; G01; G01V; G01V1/00; G01V1/40; G01V1/44; G01V1/48

Claims Analysis

Total Claims: 17
Claim 1
Independent Claim 121 words
A method of compressing acquired sonic data, the sonic data comprising a data set of m waveforms, each of the waveforms including a formation wave component digitized into n samples, said method comprising the steps of: characterizing the n samples of each digitized formation wave component as a vector; obtaining a first eigenvector based on said formation wave component vectors; selecting a formation wave component; correlating said selected wave component to said first eigenvector, thereby obtaining a first scalar correlation factor; and retaining said first eigenvector and said first scalar correlation factor as a representation of said selected formation wave component in lieu of digitized formation wave component samples for said selected formation wave component, thereby compressing said acquired sonic data.
Claim 2
Independent Claim 121 words
A method of compressing acquired sonic data, the sonic data comprising a data set of m waveforms, each of the waveforms including a formation wave component digitized into n samples, said method comprising the steps of: characterizing the n samples of each digitized formation wave component as a vector; obtaining a first eigenvector based on said formation wave component vectors; selecting a formation wave component; correlating said selected wave component to said first eigenvector, thereby obtaining a first scalar correlation factor; and retaining said first eigenvector and said first scalar correlation factor as a representation of said selected formation wave component in lieu of digitized formation wave component samples for said selected formation wave component, thereby compressing said acquired sonic data.
Claim 3
Dependent Claim 38 words
The method of claim 1, said method further reconstructing said compressed sonic data, said method further comprising the step of: multiplying said first eigenvector by said first scalar correlation factor, thereby substantially reconstructing said selected formation wave component.
Claim 4
Dependent Claim 70 words
A method of claim 1, said method further comprising the steps of: obtaining a second eigenvector based on said formation wave component vectors; correlating said selected wave component to said second eigenvector, thereby obtaining a second scalar correlation factor; and further retaining said second eigenvector and said second scalar correlation factor, said second eigenvector and said second scalar correlation factor further comprising said representation of said selected formation wave component.
Claim 5
Dependent Claim 72 words
The method of claim 3, said method further reconstructing said compressed sonic data, said method further comprising the steps of: multiplying said first eigenvector by said first scalar correlation factor, thereby obtaining a first reconstructed wave component; multiplying said second eigenvector by said second scalar correlation factor, thereby obtaining a second reconstructed wave component; and adding said first and second reconstructed wave components together, thereby substantially reconstructing said selected formation wave component.
Claim 6
Dependent Claim 86 words
The method of claim 3, said method further comprising the steps of: obtaining at least one additional eigenvector based on said formation wave component vectors; correlating said selected wave component to said at least one additional eigenvector, thereby obtaining at least one additional scalar correlation factor; further retaining said at least one additional eigenvector and said at least one additional correlation factor, said at least one additional eigenvector and said at least one additional correlation factor further comprising said representation of said selected formation wave component.
Claim 7
Dependent Claim 101 words
The method of claim 5, said method further reconstructing said compressed sonic data, said method further comprising the steps of: multiplying said first eigenvector by said first scalar correlation factor, thereby obtaining a first reconstructed wave component; multiplying said second eigenvector by said second scalar correlation factor, thereby obtaining a second reconstructed wave component; multiplying said at least one additional eigenvector by said at least one additional scalar correlation factor, thereby obtaining at least one additional reconstructed wave component; and adding said first, second and at least one additional reconstructed wave components together, thereby substantially reconstructing said selected formation wave component.
Claim 8
Independent Claim 118 words
A method of compressing acquired sonic data, the sonic data comprising a data set of m waveforms, each of the waveforms including a formation wave component digitized into n samples, said method comprising the steps of: obtaining a first template of the formation wave components, said first template representing an average value of the formation wave components; selecting a formation wave component; correlating said selected wave component to said first template, thereby obtaining a first scalar correlation factor; and retaining said first template and said first scalar correlation factor as a representation of said selected formation wave component in lieu of digitized formation wave component samples for said selected formation wave component, thereby compressing said acquired sonic data.
Claim 9
Independent Claim 118 words
A method of compressing acquired sonic data, the sonic data comprising a data set of m waveforms, each of the waveforms including a formation wave component digitized into n samples, said method comprising the steps of: obtaining a first template of the formation wave components, said first template representing an average value of the formation wave components; selecting a formation wave component; correlating said selected wave component to said first template, thereby obtaining a first scalar correlation factor; and retaining said first template and said first scalar correlation factor as a representation of said selected formation wave component in lieu of digitized formation wave component samples for said selected formation wave component, thereby compressing said acquired sonic data.
Claim 10
Dependent Claim 38 words
The method of claim 7, said method further reconstructing said compressed sonic data, said method further comprising the step of: multiplying said first template by said first scalar correlation factor, thereby substantially reconstructing said selected formation wave component.
Claim 11
Dependent Claim 72 words
The method of claim 7, said method further comprising the steps of: obtaining a Hilbert transform of said first template, thereby obtaining a Hilbert template; correlating said selected wave component to said Hilbert template, thereby obtaining a second scalar correlation factor; and further retaining said Hilbert template and said second scalar correlation factor, said Hilbert template and said second scalar correlation factor further comprising said representation of said selected formation wave component.
Claim 12
Dependent Claim 72 words
The method of claim 9, said method further reconstructing said compressed sonic data, said method further comprising the steps of: multiplying said first template by said first scalar correlation factor, thereby obtaining a first reconstructed wave component; multiplying said Hilbert template by said second scalar correlation factor, thereby obtaining a second reconstructed wave component; and adding said first and second reconstructed wave components together, thereby substantially reconstructing said selected formation wave component.
Claim 13
Independent Claim 123 words
A method of compressing acquired sonic data, the sonic data comprising a data set of m waveforms, each of the waveforms including a formation wave component digitized into n samples, said method comprising the steps of: obtaining a first template of the formation wave components, said first template representing an average value of the formation wave components; normalizing said first template; selecting a formation wave component; correlating said selected wave component to said normalized template, thereby obtaining a first scalar correlation factor; and retaining said normalized template and said first scalar correlation factor as a representation of said selected formation wave component in lieu of digitized formation wave component samples for said selected formation wave component, thereby compressing said said acquired sonic data.
Claim 14
Independent Claim 123 words
A method of compressing acquired sonic data, the sonic data comprising a data set of m waveforms, each of the waveforms including a formation wave component digitized into n samples, said method comprising the steps of: obtaining a first template of the formation wave components, said first template representing an average value of the formation wave components; normalizing said first template; selecting a formation wave component; correlating said selected wave component to said normalized template, thereby obtaining a first scalar correlation factor; and retaining said normalized template and said first scalar correlation factor as a representation of said selected formation wave component in lieu of digitized formation wave component samples for said selected formation wave component, thereby compressing said said acquired sonic data.
Claim 15
Dependent Claim 38 words
The method of claim 11, said method further reconstructing said compressed sonic data, said method further comprising the step of: multiplying said normalized template by said first scalar correlation factor, thereby substantially reconstructing said selected formation wave component.
Claim 16
Dependent Claim 72 words
The method of claim 11, said method further comprising the steps of: obtaining a Hilbert transform of said normalized template, thereby obtaining a Hilbert template; correlating said selected wave component to said Hilbert template, thereby obtaining a second scalar correlation factor; and further retaining said Hilbert template and said second scalar correlation factor, said Hilbert template and said second scalar correlation factor further comprising said representation of said selected formation wave component.
Claim 17
Dependent Claim 72 words
The method of claim 13, said method further reconstructing said compressed sonic data, said method further comprising the steps of: multiplying said normalized template by said first scalar correlation factor, thereby obtaining a first reconstructed wave component; multiplying said Hilbert template by said second scalar correlation factor, thereby obtaining a second reconstructed wave component; and adding said first and second reconstructed wave components together, thereby substantially reconstructing said selected formation wave component.

References Cited (Backward Citations)

US4509150A Cited

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