Abstract: The disclosed technology provides solutions for identifying noise in seismic profile data sets. In some aspects, a process of the disclosed technology includes steps for receiving wellbore data including seismic measurements, processing the wellbore data to generate a seismic input image including visual representations of the one or more seismic measurements, and processing the seismic input image to identify a noise region in the seismic input image. Systems and machine-readable media are also provided.

Abstract: System and methods for image gap-filling are provided. An image of a rock formation is obtained from an imaging tool disposed within a borehole. The obtained image is analyzed to identify gaps of missing image data. One or more image masks corresponding to the identified gaps are generated. A machine learning model is trained to produce modeled image data for filling in the missing image data in the identified gaps, based on the generated image mask(s). The image is reconstructed by filling the gaps of missing image data with the modeled image data. The reconstructed image is analyzed to identify geological features of the rock formation.

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

Abstract: The disclosed technology provides solutions for identifying noise in seismic profile data sets. In some aspects, a process of the disclosed technology includes steps for receiving wellbore data including seismic measurements, processing the wellbore data to generate a seismic input image including visual representations of the one or more seismic measurements, and processing the seismic input image to identify a noise region in the seismic input image. Systems and machine-readable media are also provided.

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: Disclosed herein are methods and systems that determine a microfacies or a microfacies characteristic of a sample of a subterranean formation based on a segmented image of a petrographic image of the sample, wherein the segmented image is derived from the petrographic image using a machine-learning algorithm.

Abstract: Disclosed herein are methods and systems that determine a microfacies or a microfacies characteristic of a sample of a subterranean formation based on a segmented image of a petrographic image of the sample, wherein the segmented image is derived from the petrographic image using a machine-learning algorithm.

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: 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.