Abstract: A model is used to generate corrections to mitigate ideal condition artifacts in acoustic property values of an annular material in a cased wellbore. A mathematical model that generates acoustic property values at ideal conditions introduces artifacts into the acoustic property values. Acoustic measurements of an annular material are used to generate features that represent wellbore conditions and are not accounted for in the mathematical model that generates acoustic property values. A model will generate corrections for acoustic property values of an annular material with the features to yield a more accurate acoustic property profile for the annular material of a cased hole.

Abstract: A system can apply an unsupervised machine-learning model to ultrasonic waveform data received about a wellbore for identifying channels in the wellbore. A system can receive ultrasonic waveform data about a wellbore using an arrangement of transducers positionable in the wellbore. The ultrasonic waveform data can include a set of ultrasonic waveforms. The system can generate a set of attributes for each ultrasonic waveform of the set of ultrasonic waveforms. The system can apply an unsupervised machine-learning model to the set of ultrasonic waveforms for clustering the set of attributes of ultrasonic waveform into a set of clusters. The system can output the set of clusters for categorizing the ultrasonic waveform data.

Abstract: A method and system for logging. The method may include disposing an acoustic logging tool into a wellbore, insonifing a pipe string within the wellbore with the acoustic logging tool, recording a plurality of flexural waves with the acoustic logging tool as one or more traces, and identifying a condition of a material behind the pipe string using the plurality of flexural waves. The acoustic logging tool may include one or more transmitters for insonifing a pipe string within a wellbore and one or more receivers configured to record a plurality of flexural waves. Additionally an information handling system may be configured to identify a condition of a material behind the pipe string using the plurality of flexural waves.

Abstract: A seismic source is positioned at the surface of a geologic formation and a plurality of seismic receivers is positioned in a wellbore of the geologic formation. Seismic wavefield data is obtained based on the seismic source outputting seismic energy into the wellbore and the plurality of seismic receivers receiving the seismic energy. A velocity profile is determined along the wellbore based on the seismic wavefield data. P and S wave data in a downgoing direction is separated from the seismic wavefield data based on an inversion and the velocity profile. The P and S wave data in the downgoing direction is adaptively subtracted from the seismic wavefield data to form residual wavefield data. The P and S wave data in a upgoing direction is separated from the residual wavefield data based on the inversion and an updated velocity profile. The P and S wave data in the upgoing and downgoing direction is output.

Abstract: A method for identifying a material behind a pipe string. The method may comprise disposing an acoustic logging tool into a wellbore, insonifying a pipe string within the wellbore with the acoustic logging tool, recording sonic or ultrasonic data. The method may further comprise inputting the sonic or ultrasonic data into trained a machine learning model and identifying the material behind the pipe string using the trained machine learning model.

Abstract: An apparatus obtains measurements from a seismic sensor, wherein the seismic measurements include a set of seismic waves having at least a subset of seismic multiples and a machine-readable medium having program code executable by a processor to cause the apparatus to determine seismic measurements of the seismic waves, fit reflectivity model based on a set of reflectivity models using a nonlinear scheme to the seismic measurements, and identify a subset of the seismic measurements corresponding to the subset of seismic multiples. The apparatus also includes program code to cause the apparatus to generate a set of reduced-noise seismic measurements based on attenuation of the subset of the seismic measurements.

Abstract: Systems, methods, and computer-readable media are provided for detecting a channel behind casing and generating an image that represents the channel.

Abstract: Various embodiments include apparatus and methods implemented to simulate geophone data from distributed acoustic sensing data, such as simulating vertical component geo phone waveform data from distributed acoustic sensing data. Embodiments include measuring vertical component of strain at a plurality of vertical positions along an optical fiber disposed along a wellbore at a well site. The measured vertical component of strain can be processed to generate a vertical component of displacement. The vertical component of displacement can be used to generate a vertical component of velocity from which a waveform simulating a waveform of geophone data can be output. Additional apparatus, systems, and methods are disclosed.

Abstract: A method to generate a vertical seismic profile includes acquiring a set of distributed acoustic sensing measurements from a set of overlapping measurement channels on an optical fiber, wherein each of the set of distributed acoustic sensing measurements are measured at a gauge length. The method also includes generating a set of virtual seismic measurements corresponding with subdivisions in the set of overlapping measurement channels based on the set of distributed acoustic sensing measurements and generating the vertical seismic profile based on the set of virtual seismic measurements.

Abstract: Systems, methods, and computer-readable media are provided for detecting a channel behind casing and generating an image that represents the channel. An example method can include receiving data samples associated with at least one casing, each data sample representing channel information behind a representative casing, training a machine learning model using the data samples to generate a mapping between waveform information in each of the data samples and the channel information behind the representative casing, receiving acoustic data from a tool, the acoustic data representing a particular casing, and using the machine learning model to analyze the acoustic data from the tool and determine one of a presence and an absence of a channel behind the particular casing at a plurality of depths.

Abstract: A seismic source is positioned at the surface of a geologic formation and a plurality of seismic receivers is positioned in a wellbore of the geologic formation. Seismic wavefield data is obtained based on the seismic source outputting seismic energy into the wellbore and the plurality of seismic receivers receiving the seismic energy. A velocity profile is determined along the wellbore based on the seismic wavefield data. P and S wave data in a downgoing direction is separated from the seismic wavefield data based on an inversion and the velocity profile. The P and S wave data in the downgoing direction is adaptively subtracted from the seismic wavefield data to form residual wavefield data. The P and S wave data in a upgoing direction is separated from the residual wavefield data based on the inversion and an updated velocity profile. The P and S wave data in the upgoing and downgoing direction is output.

Abstract: A distributed acoustic sensing (DAS) system is coupled to an optical fiber along a plurality of channels. The system generates a DAS seismic profile of the subsurface formation based on detected seismic data, identifies at least one region having coherent noise, and identifies which of the plurality of channels are within the identified at least one region. For each trace of data associated with the plurality of noisy channels, the system converts, from a time to a wavelet domain, the trace of data and a reference trace having less coherent noise, and suppresses the wavelet coefficients of the trace of data based on the wavelet coefficients of the reference trace. After the system mitigates the noise in the wavelet domain, an inverse wavelet transform is applied to the trace of data to convert back to the time domain and create a reduced noise DAS seismic profile.

Abstract: A method for identifying a location of a distributed acoustic system channel in a distributed acoustic system. The method may comprise generating a two or three dimensional layer model interface with an information handling system, preparing a P-wave first arrival pick time table, estimating an initial model layer properties, estimating a location of the distributed acoustic system channels, preparing an overburden file of layer properties, running an anisotropic ray tracing, defining an upper and a lower limits for model parameters, specifying parameters for the inversion, running an inversion, selecting a solution based at least in part on stored error predictions, and calculating a mean and a standard deviation of an inverted model parameter.

Abstract: A method to process vertical seismic profile (VSP) data includes receiving VSP data, migrating the VSP data output using an initial velocity model to produce migrated depth values associated with the respective receivers, sorting and collecting the migrated depth values corresponding to each receiver to produce a migrated common receiver gather (CRG) associated with each receiver, stacking the migrated depth values of the CRGs corresponding to respective fixed lateral positions in an image volume to produce a common image gather (CIG) associated with each lateral position, and generating a semblance panel having the stacked depth migration values plotted as contours on a first axis for velocity ratio (vr), which is based on migration velocity and true velocity) and a second axis for true depth (Zt). The method further includes updating the initial velocity model based on a plurality of data points selected from the semblance panel to provide an updated velocity model.

Abstract: An apparatus includes a seismic sensor to detect seismic waves having at least a subset of seismic multiples and a machine-readable medium having program code executable by a processor to cause the apparatus to determine seismic measurements of the seismic waves, generate a fitted reflectivity model based on a set of reflectivity models using a nonlinear scheme, and identify a subset of the seismic measurements corresponding to the subset of seismic multiples. The apparatus also includes program code to cause the apparatus to generate a set of reduced-noise seismic measurements based on the subset of the seismic measurements.

Abstract: High fidelity velocity models are generated for acoustic vertically transverse isotropic media by taking advantage of full-waveform based modeling using VSP data. The present disclosure determines VTI parameters in acoustic media using pseudo-acoustic equations which can eliminate the contribution from shear waves, and thus significantly reduce the time needed to perform inversion. The methods disclosed herein provide workflows for performing full waveform inversion to provide velocity models used to generate seismic images with high quality and resolution.

Abstract: A method to generate a vertical seismic profile includes acquiring a set of distributed acoustic sensing measurements from a set of overlapping measurement channels on an optical fiber, wherein each of the set of distributed acoustic sensing measurements are measured at a gauge length. The method also includes generating a set of virtual seismic measurements corresponding with subdivisions in the set of overlapping measurement channels based on the set of distributed acoustic sensing measurements and generating the vertical seismic profile based on the set of virtual seismic measurements.

Abstract: A method for processing vertical seismic profiling (VSP) data is provided. The method includes receiving VSP data in response to seismic energy applied to the formation, processing a down-going portion of the VSP data associated with a down-going wave field, outputting a first set of estimation values based on processing the down-going portion of the VSP data, the first set of estimation values estimating at least one of slowness or velocity, processing an up-going portion of the VSP data associated with an up-going wave field, outputting a second set of estimation values based on processing the up-going portion of the VSP data, the second set of estimation values estimating at least one of slowness or velocity, and determining an estimation associated with the formation based on the first and second sets of estimation values.

Abstract: A method for identifying a location of a distributed acoustic system channel in a distributed acoustic system. The method may comprise generating a two or three dimensional layer model interface with an information handling system, preparing a P-wave first arrival pick time table, estimating an initial model layer properties, estimating a location of the distributed acoustic system channels, preparing an overburden file of layer properties, running an anisotropic ray tracing, defining an upper and a lower limits for model parameters, specifying parameters for the inversion, running an inversion, selecting a solution based at least in part on stored error predictions, and calculating a mean and a standard deviation of an inverted model parameter.

Abstract: A distributed acoustic sensing (DAS) system is coupled to an optical fiber along a plurality of channels. The system generates a DAS seismic profile of the subsurface formation based on detected seismic data, identifies at least one region having coherent noise, and identifies which of the plurality of channels are within the identified at least one region. For each trace of data associated with the plurality of noisy channels, the system converts, from a time to a wavelet domain, the trace of data and a reference trace having less coherent noise, and suppresses the wavelet coefficients of the trace of data based on the wavelet coefficients of the reference trace. After the system mitigates the noise in the wavelet domain, an inverse wavelet transform is applied to the trace of data to convert back to the time domain and create a reduced noise DAS seismic profile.