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US 12,709,978 B2Granted
Movement noise suppression in a moving array for downhole leakage localization
AssigneeHalliburton Energy Services, Inc.
InventorsYi Yang Ang, Yao Ge
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Abstract
The disclosed technology provides ways to suppress or eliminate the effects of roadnoise when performing acoustic leak detection in a wellbore environment. In some aspects, a method of the technology includes steps for receiving acoustic training data, wherein the acoustic training data comprises signals representing acoustic tool contact with a wellbore surface, and generating a suppression model based on the acoustic training data, wherein the suppression model is configured to suppress roadnoise received at a hydrophone array disposed within the wellbore. Systems and machine-readable media are also provided.
Claims20
A method, comprising:
- receiving acoustic training data, wherein the acoustic training data comprises signals representing extraneous noise signals;
- generating a suppression model including an acoustic sensor signal correlation matrix based on the acoustic training data and machine-learning implementations, wherein the suppression model is configured to learn and model extraneous noise present in an environment of a wellbore, wherein the suppression model is based on a source correlation matrix, an interference correlation matrix, and a noise correlation matrix;
- logging acoustic well log data from the wellbore using at least one acoustic sensor to acquire at least two measurements, wherein the acoustic well log data is captured at a depth corresponding to an acoustic well log operation of the at least one acoustic sensor;
- adjusting one or more beamformer weights based on the suppression model for controlling suppression of extraneous noise included in the acoustic well log data;
- processing the acoustic well log data based on the adjusted one or more beamformer weights to suppress the extraneous noise included in the acoustic well log data;
- and
- processing the acoustic well log data based on the adjusted one or more beamformer weights to identify a leak or a flow in a casing within the wellbore or in proximity to the wellbore.
4 more elements
A system comprising:
- one or more processors;
- and
- at least one computer-readable storage medium having stored therein instructions which, when executed by the one or more processors, cause the one or more processors to:
- receive acoustic training data, wherein the acoustic training data comprises signals representing extraneous noise signals;
- generate a suppression model including an acoustic sensor signal correlation based on the acoustic training data and machine-learning implementations, wherein the suppression model is configured to learn and model extraneous noise present in an environment of a wellbore, wherein the suppression model is based on a source correlation matrix, an interference correlation matrix, and a noise correlation matrix;
- log acoustic well log data from the wellbore using at least one acoustic sensor, wherein the acoustic well log data is captured at a depth corresponding to an acoustic well log operation of the at least one acoustic sensor;
- adjust one or more beamformer weights based on the suppression model for controlling suppression of extraneous noise included in the acoustic well log data;
- process the acoustic well log data based on the adjusted one or more beamformer weights to suppress the extraneous noise included in the acoustic well log data;
- process the acoustic well log data based on the adjusted one or more beamformer weights to identify a leak or a flow in a casing within the wellbore or proximity to the wellbore.
6 more elements
A non-transitory computer-readable storage medium storing instructions for causing one or more processors to:
- receive acoustic training data, wherein the acoustic training data comprises signals representing extraneous noise signals;
- generate a suppression model including an acoustic sensor signal correlation matrix based on the acoustic training data and machine-learning implementations, wherein the suppression model is configured to learn and model extraneous noise present in an environment of a wellbore, wherein the suppression model is based on a source correlation matrix, an interference correlation matrix, and a noise correlation matrix;
- log acoustic well log data from the wellbore using at least one acoustic sensor to acquire at least two measurements, wherein the acoustic well log data is captured at a depth corresponding to an acoustic well log operation of the at least one acoustic sensor;
- adjust one or more beamformer weights based on the suppression model for controlling suppression of extraneous noise included in the acoustic well log data;
- process the acoustic well log data based on the adjusted one or more beamformer weights to suppress the extraneous noise included in the acoustic well log data;
- and
- process the acoustic well log data based on the adjusted one or more beamformer weights to identify a leak or a flow in a casing within the wellbore or in proximity to the wellbore.
4 more elements
Dependencies are inferred from the claim text.