Disclosed is an acoustic sensor system comprising an electrical connector, at least one transducer connected to the electrical connector, a fluid compensating piston connected to the electrical connector, a housing having the electrical connector, the at least one transducer, and the fluid compensating piston arranged in a linear arrangement, and a collar having the housing mounted along an interior surface of the collar.

Disclosed is an acoustic sensor system comprising an electrical connector, at least one transducer connected to the electrical connector, a fluid compensating piston connected to the electrical connector, a housing having the electrical connector, the at least one transducer, and the fluid compensating piston arranged in a linear arrangement, and a collar having the housing mounted along an interior surface of the collar.

A method of probabilistically estimating a velocity of a plunger of a beam pump may comprise continuously monitoring well acoustics using a plurality of passive acoustic sensors attached to external structures of the beam pump; digitizing outputs of the plurality of passive acoustic sensors and sending the digitized outputs to a computing device for storage and processing; and using the digitized outputs of the plurality of passive acoustic sensors, estimating a probability of the velocity of the plunger using a hidden Markov model (HMM) to represent a probability of a position and the probability of the velocity of the plunger, the HMM comprising a state space model and an observational model.

A method of probabilistically estimating a velocity of a plunger of a beam pump may comprise continuously monitoring well acoustics using a plurality of passive acoustic sensors attached to external structures of the beam pump; digitizing outputs of the plurality of passive acoustic sensors and sending the digitized outputs to a computing device for storage and processing; and using the digitized outputs of the plurality of passive acoustic sensors, estimating a probability of the velocity of the plunger using a hidden Markov model (HMM) to represent a probability of a position and the probability of the velocity of the plunger, the HMM comprising a state space model and an observational model.

A method for evaluating a sealing material positioned between a casing of a wellbore and a subsurface formation in which the wellbore is formed includes emitting an acoustic waveform outward from a position within the casing and detecting a return waveform that is generated in response to the acoustic waveform interacting with a region of interest that includes at least a portion of the sealing material. The method includes determining a first time window of the return waveform associated with the region of interest and trimming the return waveform based on the first time window. The method further includes determining a first spectral power density for the first time window of the trimmed return waveform and determining a composition ratio for the region of interest based on the first spectral power density.

An apparatus for use in acoustically assessing a wellbore, comprises a tubular body, an acoustic transmitter supported on the body, first and second acoustic receivers supported on the body with the second receiver being farther from the transmitter, wherein at least one of the inner and outer body surfaces includes a helical groove between the acoustic transmitter and the first acoustic receiver and the helical groove is filled with a composite material. The body may include a second helical groove that has the same pitch as the first helical groove and is diametrically opposite the first helical groove and may further include a third helical groove between the first and second receivers. At least one of the grooves may an opening width that is less than the maximum groove width and may have a cross-sectional area that includes a neck. The composite material may comprise tungsten particles in rubber.

An apparatus for use in acoustically assessing a wellbore, comprises a tubular body, an acoustic transmitter supported on the body, first and second acoustic receivers supported on the body with the second receiver being farther from the transmitter, wherein at least one of the inner and outer body surfaces includes a helical groove between the acoustic transmitter and the first acoustic receiver and the helical groove is filled with a composite material. The body may include a second helical groove that has the same pitch as the first helical groove and is diametrically opposite the first helical groove and may further include a third helical groove between the first and second receivers. At least one of the grooves may an opening width that is less than the maximum groove width and may have a cross-sectional area that includes a neck. The composite material may comprise tungsten particles in rubber.

Methods, systems, and program products are disclosed for implementing acoustic logging and determining wellbore material characteristics. In some embodiments, a method may include determining a polar differential signal for each of one or more pairs of azimuthally offset acoustic measurements within a wellbore. A reference azimuth is identified based, at least in part, on comparing the polar differential signals to a modeled bonding differential signal within a target response window. The method further includes determining differences between an acoustic measurement at the reference azimuth and acoustic measurements at one or more other azimuths and determining a wellbore material condition based, at least in part, on the determined differences.

The present disclosure provides a method of processing data obtained from distributed optical fiber sensors to detect acoustic energy generated by a poroelastic effect of fractures in a structure, such as a rock formation. The sensing fiber of an optical fiber distributed sensing system may be deployed in the vicinity of the region where fracturing is occurring, for example, along a well that is offset from a treatment well undergoing hydraulic fracturing. The DAS data obtained from along the sensing fiber is processed to measure changes in the low-frequency strain caused by the poroelastic effects in the rock as the fractures open and close. This measured strain rate data is iteratively processed at each instant time to identify fracture opening features (characterised as compression-tension-compression) that are correlated with fracture closing features (characterised as tension-compression-tension) as a function of depth, to thereby identify and locate fracture hits in the vicinity of the sensing fiber.

The present disclosure provides a method of processing data obtained from distributed optical fiber sensors to detect acoustic energy generated by a poroelastic effect of fractures in a structure, such as a rock formation. The sensing fiber of an optical fiber distributed sensing system may be deployed in the vicinity of the region where fracturing is occurring, for example, along a well that is offset from a treatment well undergoing hydraulic fracturing. The DAS data obtained from along the sensing fiber is processed to measure changes in the low-frequency strain caused by the poroelastic effects in the rock as the fractures open and close. This measured strain rate data is iteratively processed at each instant time to identify fracture opening features (characterised as compression-tension-compression) that are correlated with fracture closing features (characterised as tension-compression-tension) as a function of depth, to thereby identify and locate fracture hits in the vicinity of the sensing fiber.