Abstract: A method for removing a guided wave noise in a time-domain may include recording one or more acoustic signals with one or more receivers at a first location, wherein the one or more acoustic signals are raw data. The method may further include determining a slowness range, estimating a downward guided wave noise by stacking the one or more acoustic signals based at least in part on a positive slowness, estimating an upward guided wave noise by stacking the one or more acoustic signals based at least in part on a negative slowness, and identifying a dominant direction of propagation. The method may further include identifying a slowness from a highest stacked amplitude for the dominant direction of propagation, estimating a downward guided wave noise with the slowness, estimating an upward guided wave noise with the slowness, and subtracting the downward guided wave noise and the upward guided wave noise.

Abstract: According to embodiments of the present invention, a gateway device operable in a system for monitoring a plurality of bio-signals is provided. The gateway device includes a receiver unit configured to receive data and reconstruct the received data to obtain a digital sound signal representative of the plurality of bio-signals; a processing unit configured to determine at least one biometric from the digital sound signal and form a digital signal representative of the plurality of bio-signals and the determined at least one biometric, and to reconstruct the digital signal into two or more data segments, wherein each data segment includes a portion of the digital signal; and a transmitter unit configured to transmit information including the two or more data segments to an external processing module for further processing. According to further embodiments, a system and a method for monitoring a plurality of bio-signals are also provided.

Abstract: The disclosed embodiments include a method of downhole leak detection. The method of downhole leak detection includes obtaining physical signals detected by at least one physical sensor traveling along a wellbore. Additionally, the method includes detecting correlated sequences from the physical signals and constructing a covariance matrix based on the correlated sequences. The method also includes computing a spatial spectrum indicative of a location of a leak based on the covariance matrix.

Abstract: Disclosed are systems and methods for processing broadband acoustic signals acquired by a plurality of acoustic sensors, using an array-signal-processing technique to compute fused-signal maps in the frequency domain for a plurality of frequency bins. In accordance with various embodiments, the fused-signal maps are combined across the frequency bins, with respective weightings that are based on eigenvalues of covariance matrices computed for the plurality of frequency bins. The combined maps can be used to locate an acoustic source in a wellbore.

Abstract: Disclosed are acoustic logging systems and methods that involve correlating broadband acoustic signals acquired by a plurality of acoustic sensors at multiple depths within a wellbore to compute covariance matrices and their eigenvalues in the frequency domain for a plurality of frequency bins. In accordance with various embodiments, acoustic sources are detected and located based on the eigenvalues viewed as a function of depth and frequency.

Abstract: The disclosed embodiments include leak detection systems and methods of downhole leak detection. In one embodiment, the method includes obtaining physical signals detected by a physical sensor over a period of time while the physical sensor is traveling along a wellbore, wherein the physical signals are acoustic signals of a leak. The method also includes performing a sequence extraction operation on the physical signals of the physical sensor to obtain a plurality of virtual signals associated with an array of virtual sensors, wherein each virtual sensor of the array of virtual sensors is located at a respective virtual distance relative to the physical sensor. The method further includes determining a signal strength of the plurality of virtual signals. The method further includes determining a location of the leak based on the signal strength of the plurality of virtual signals.

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.

Abstract: System and method for telemetry communication provide enhance noise cancellation in well intervention operations. The system and method employ a surface panel operable to transmit and receive a telemetry signal through a wireline extending along a wellbore. A power converter receives and converts electrical power from the cable to operating power for a downhole tractor motor. A modem coupled to the cable processes and provides the telemetry signal to a microcontroller. A noise signal pathway provides a noise signal from the tractor motor directly to the microcontroller, the noise signal representative of electrical noise generated by the downhole tractor. The microcontroller performs noise cancellation on the telemetry signal to produce a de-noised telemetry signal by obtaining an estimated noise channel transfer function for the noise signal, and applying the estimated noise channel transfer function and the noise signal to the telemetry signal from the modem.

Abstract: System and method for telemetry communication provide enhance noise cancellation in well intervention operations. The system and method employ a surface panel operable to transmit and receive a telemetry signal through a wireline extending along a wellbore. A power converter receives and converts electrical power from the cable to operating power for a downhole tractor motor. A modem coupled to the cable processes and provides the telemetry signal to a microcontroller. A noise signal pathway provides a noise signal from the tractor motor directly to the microcontroller, the noise signal representative of electrical noise generated by the downhole tractor. The microcontroller performs noise cancellation on the telemetry signal to produce a de-noised telemetry signal by obtaining an estimated noise channel transfer function for the noise signal, and applying the estimated noise channel transfer function and the noise signal to the telemetry signal from the modem.

Abstract: A passive array of acoustic sensors capture acoustic signals produced by sand movement. The array tool is deployed downhole where it passively listens for acoustic energy generated by sand movement in the well. Once acoustic signals are acquired, model-based frameworks are used to extract single and multiple sensor features from the acoustic signals. The extracted features are used as signatures to detect or classify the production of sand.

Abstract: A method for removing a guided wave noise in a time-domain may include recording one or more acoustic signals with one or more receivers at a first location, wherein the one or more acoustic signals are raw data. The method may further include determining a slowness range, estimating a downward guided wave noise by stacking the one or more acoustic signals based at least in part on a positive slowness, estimating an upward guided wave noise by stacking the one or more acoustic signals based at least in part on a negative slowness, and identifying a dominant direction of propagation. The method may further include identifying a slowness from a highest stacked amplitude for the dominant direction of propagation, estimating a downward guided wave noise with the slowness, estimating an upward guided wave noise with the slowness, and subtracting the downward guided wave noise and the upward guided wave noise.

Abstract: A method includes obtaining physical signals detected by a physical sensor traveling along a wellbore. The method also includes performing a first and second frame decomposition operations on a first and second set of physical signals detected by the physical sensor at first and second locations to obtain first and second pluralities of virtual signals associated with first and second arrays of virtual sensors. Each virtual sensor of the first and second arrays of virtual sensors is located at a virtual distance relative to the first and second locations, and the virtual distance corresponds to a physical distance. Additionally, the method includes computing first and second direction of arrival estimates of the first and second locations of the single physical sensor relative to a location of a downhole leak. Further, the method includes triangulating the first and second direction of arrival estimates to estimate the location of the downhole leak.

Abstract: Disclosed are acoustic logging systems and methods that involve correlating broadband acoustic signals acquired by a plurality of acoustic sensors at multiple depths within a wellbore to compute covariance matrices and their eigenvalues in the frequency domain for a plurality of frequency bins. In accordance with various embodiments, acoustic sources are detected and located based on the eigenvalues viewed as a function of depth and frequency.

Abstract: The disclosed embodiments include a method of downhole leak detection. The method of downhole leak detection includes obtaining physical signals detected by at least one physical sensor traveling along a wellbore. Additionally, the method includes detecting correlated sequences from the physical signals and constructing a covariance matrix based on the correlated sequences. The method also includes computing a spatial spectrum indicative of a location of a leak based on the covariance matrix.

Abstract: Various apparatus or methods are arranged to operate a tool in a wellbore, where the tool has a number of acoustic sensors. Scanning images obtained by the tool sensors along the borehole can be combined to increase the contrast of leak location with respect to background noise. A sequence of beamformed images, generated from signals captured by the tool as it moves over a range of depths of the wellbore, can be acquired. Each beamformed image may overlap at least one other beamformed image of the sequence. The beamformed images can be processed and the processed beamformed images can be combined, forming a stitched image. Additional apparatus, systems, and methods operable in providing stitched images can operate in a variety of applications.

Abstract: The disclosed embodiments include leak detection systems and methods of downhole leak detection. In one embodiment, the method includes obtaining physical signals detected by a physical sensor over a period of time while the physical sensor is traveling along a wellbore, wherein the physical signals are acoustic signals of a leak. The method also includes performing a sequence extraction operation on the physical signals of the physical sensor to obtain a plurality of virtual signals associated with an array of virtual sensors, wherein each virtual sensor of the array of virtual sensors is located at a respective virtual distance relative to the physical sensor. The method further includes determining a signal strength of the plurality of virtual signals. The method further includes determining a location of the leak based on the signal strength of the plurality of virtual signals.

Abstract: Tools, systems, and methods may be configured for or include detecting one or more underground acoustic sources and localizing them in depth and radial distance from a wellbore using an array of at least three acoustic sensors disposed in the wellbore in conjunction with array-signal-processing that accounts for movement of the acoustic sensors and spatial aliasing by using adaptive time dependent modelled steering vector weights.

Abstract: The disclosed embodiments include leak detection systems and methods of downhole leak detection. In one embodiment, the method includes obtaining physical signals measured by at least one physical sensor traveling along a wellbore. The method also includes performing a frame decomposition operation on the physical signals of a first of the at least one the physical sensor to obtain a plurality of virtual signals associated with an array of virtual sensors, each virtual sensor of the array of virtual sensors being located at a virtual distance relative to the first physical sensor, the virtual distance corresponding to a physical distance. The method further includes synchronizing the virtual signals of the array of virtual sensors. The method further includes computing a spatial spectrum indicative of a location of a leak based on the synchronized virtual signals.

Abstract: A method including selecting a forward model based on a modeled well structure and including a single modeled acoustic source located in a modeled wellbore and a plurality of modeled acoustic sensors located in a modeled source area, simulating an acoustic signal generated by the single modeled acoustic source and received by each modeled acoustic sensor, calculating phases of the simulated acoustic signals received at each modeled acoustic sensor, obtaining with a principle of reciprocity a plurality of modeled acoustic sources in the modeled source area and a single modeled acoustic sensor in the modeled wellbore, calculating phase delays of the simulated acoustic signals between each modeled acoustic source and the single modeled acoustic sensor, detecting acoustic signals generated by a flow of fluid using acoustic sensors in a wellbore, and processing the acoustic signals using the phase delays to generate a flow likelihood map.

Abstract: A passive array of acoustic sensors capture acoustic signals produced by sand movement. The array tool is deployed downhole where it passively listens for acoustic energy generated by sand movement in the well. Once acoustic signals are acquired, model-based frameworks are used to extract single and multiple sensor features from the acoustic signals. The extracted features are used as signatures to detect or classify the production of sand.