Abstract: A general-purpose workflow for automatic borehole sonic data classification to identify data into different physical categories and logging conditions, which are traditionally manually evaluated. The workflow uses machine learning techniques and physical knowledge for data classification, including pre-processing the high-dimensional high-quality dispersion modes extracted using a recently developed physical-driven ML enabled approach.

Abstract: A method of producing a geothermal well includes obtaining site information including at least a site volume; obtaining drilling parameters; determining lengths and orientations of planned wellbores based at least partially on the site information and the drilling parameters.

Abstract: A method can include acquiring acoustic signals responsive to emissions into equipment: and generating an output signal by inputting the acoustic signal into a machine learning model, where the output signal is indicative of a positional arrangement of two pieces of the equipment.

Abstract: A method may include receiving, via one or more processors, a first dataset associated with a plurality of projects that corresponds to performing hydrocarbon exploration or processing operations. The method may then involve receiving a second dataset associated with a plurality of assets, such that at least a portion of the plurality of assets is used to complete at least a portion of the plurality of projects. The method may also involve determining a plurality of schedules for deploying the at least a portion of the plurality of assets for use with the at least a portion of the plurality of projects, identifying a portion of the plurality of schedules based on an optimization algorithm with respect to revenue, and sending a notification indicative of the portion of the plurality of schedules to a computing device, wherein the computing device is configured to display the notification via an electronic display.