Abstract: A system and method that can include training a deep neural network using time series data that represents functions of a non-linear Kalman filter that represents a dynamic system of equipment and environment and models a pre-defined operational procedure as a temporal sequence. The system and method can also include receiving operation data from the equipment responsive to operation in the environment and outputting an actual operation as an actual sequence of operational actions by the deep neural network. The system and method can additionally include performing an operation-level comparison to evaluate the temporal sequence against the actual sequence using a distance function in a latent space of the deep neural network and outputting a score function that quantifies the distance function in the latent space. The system and method can further include controlling an electronic component to execute an electronic operation based on the score function.

Abstract: A method for drilling a well includes generating a plurality of proposed drilling actions using a plurality of working agents based on a working environment, simulating drilling responses to the proposed drilling actions using a plurality of validation agents in a validation environment that initially represents the working environment, determining rewards for the proposed drilling actions based on the simulating, using the validation agents, selecting one of the proposed drilling actions, and causing a drilling rig to execute the selected one of the proposed actions.

Abstract: A system and method that can include training a deep neural network using time series data that represents functions of a non-linear Kalman filter that represents a dynamic system of equipment and environment and models a pre-defined operational procedure as a temporal sequence. The system and method can also include receiving operation data from the equipment responsive to operation in the environment and outputting an actual operation as an actual sequence of operational actions by the deep neural network. The system and method can additionally include performing an operation-level comparison to evaluate the temporal sequence against the actual sequence using a distance function in a latent space of the deep neural network and outputting a score function that quantifies the distance function in the latent space. The system and method can further include controlling an electronic component to execute an electronic operation based on the score function.

Abstract: A method can include receiving scheduled tasks associated with subsystems of a wellsite system wherein the scheduled tasks are associated with achievement of desired states of the wellsite system; transmitting task information for at least a portion of the scheduled tasks to computing devices associated with the subsystems; receiving state information via the wellsite system; assessing the state information with respect to one or more of the desired states; based at least in part on the assessing, scheduling a task; and transmitting task information for the task to one or more of the computing devices associated with the subsystems.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media for dynamically utilizing offset drill-well data generated within a threshold geographic area to determine formation-top trends and identify formation-top depths at a subject drill-well site. To do so, in some embodiments, the disclosed systems estimate a variogram for observed formation-top depths of a subset of offset drill-wells, and, in turn, map a predicted response from the estimated variogram. For example, using weighted combinations (e.g., with Kriging weights) of the formation-top depths of the subset of offset drill-wells, the disclosed systems can map a continuous surface of a formation and identify a top-depth thereof. Moreover, the disclosed system can do so for multiple formations at the subject drill-well site, and (in real-time in response to a user input) provide for display at a client device, the associated formation-top depths, various predicted drilling events and/or predicted drilling metrics.

Abstract: A method can include training a deep neural network to generate a trained deep neural network where the trained deep neural network represents functions of a nonlinear Kalman filter that represents a dynamic system of equipment and environment via an internal state vector of the dynamic system; generating a base internal state vector, that corresponds to a pre-defined operational procedure, using the trained deep neural network; receiving operation data from the equipment responsive to operation in the environment; generating an internal state vector using the operation data and the trained deep neural network; and comparing at least the internal state vector to at least the base internal state vector.

Abstract: A method can include receiving sensor data; determining a rate of penetration drilling parameter value using a trained neural network and at least a portion of the sensor data; and issuing a control instruction for drilling a borehole using the determined rate of penetration drilling parameter value.

Abstract: A method for drilling a well includes generating a plurality of proposed drilling actions using a plurality of working agents based on a working environment, simulating drilling responses to the proposed drilling actions using a plurality of validation agents in a validation environment that initially represents the working environment, determining rewards for the proposed drilling actions based on the simulating, using the validation agents, selecting one of the proposed drilling actions, and causing a drilling rig to execute the selected one of the proposed actions.

Abstract: Disclosed is a tuning guide for tuning a brass musical instrument having a tuning slide. The tuning guide includes (1) visual markings provided along one arm of the tuning slide indicating a plurality of tuning positions of the tuning slide and (2) a tuning log for logging a tuning history specific to both the instrument and a particular player of the instrument. The tuning log includes a plurality of tuning records, each tuning record including (i) one or more conditions fields, each conditions field for recording an environmental condition and (ii) a tuning position field for specifying a tuning position at which the instrument is properly tuned under the environmental conditions recorded in the one or more conditions fields.

Abstract: The disclosed computer-implemented method for enabling multi-factor authentication for seamless website logins may include (1) generating a numerical sequence utilized for authenticating a user for multi-factor authentication on a website, (2) detecting user login credentials for initiating a multi-factor authentication session on the website, (3) receiving, in response to the user login credentials, a request for multi-factor authentication data associated with the numerical sequence from the website, (4) retrieving, utilizing an application programming interface (API), the multi-factor authentication data from a secure storage associated with the user, and (5) providing, utilizing the API, the multi-factor authentication data to the website to login the user. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A method can include training a deep neural network to generate a trained deep neural network where the trained deep neural network represents functions of a nonlinear Kalman filter that represents a dynamic system of equipment and environment via an internal state vector of the dynamic system; generating a base internal state vector, that corresponds to a pre-defined operational procedure, using the trained deep neural network; receiving operation data from the equipment responsive to operation in the environment; generating an internal state vector using the operation data and the trained deep neural network; and comparing at least the internal state vector to at least the base internal state vector.

Abstract: A drilling rig site may include at least one tubular configured to be inserted into a wellbore at the drilling rig, at least one imaging device configured to detect a location of an end of the at least one tubular or a feature of the at least one tubular, and a processor receiving an input from the at least one imaging device and configured to calculate a distance between the end of the at least one tubular and another element, a diameter of the at least one tubular, or movement of the at least one tubular. A method for completing a drilling operation at a rig site, may include capturing an image of a tubular at a rig site, the tubular configured to be inserted into a wellbore at the rig site, detecting a location of an end of the tubular or a feature of the tubular from the image, and determining a diameter of the tubular, a distance between the detected end of the tubular and another element, or movement of the tubular.

Abstract: A method for controlling an automatic drilling system includes measuring at least one drilling operating parameter applied to a drill string disposed in a wellbore when the drill string is suspended above the bottom of a wellbore. The drill string is lowered to drill the wellbore when the wellbore. At least one relationship is established between the at least one measured drilling operating parameter and corresponding values of a drilling response parameter at the surface and at the bottom of the drill string. A value of a rate of penetration parameter at surface is selected to operate the automatic drilling system so as to optimize a rate of penetration parameter at the bottom of the drill string.

Abstract: A method can include receiving scheduled tasks associated with subsystems of a wellsite system wherein the scheduled tasks are associated with achievement of desired states of the wellsite system; transmitting task information for at least a portion of the scheduled tasks to computing devices associated with the subsystems; receiving state information via the wellsite system; assessing the state information with respect to one or more of the desired states; based at least in part on the assessing, scheduling a task; and transmitting task information for the task to one or more of the computing devices associated with the subsystems.

Abstract: A method can include receiving state information for a wellsite system; receiving contextual information for a role associated with a workflow; generating a natural language report based at least in part on the state information and based at least in part on the contextual information; and transmitting the natural language report via a network interface based at least in part on an identifier associated with the role.

Abstract: The disclosed computer-implemented method for anonymizing user accounts may include (i) receiving an instruction to anonymize a user account to protect a user's personally identifiable information, (ii) accessing, by a security program, a settings portal for the user account in response to receiving the instruction to anonymize the user account, (iii) replacing, by the security program, original values within at least two fields within the settings portal for the user account with anonymized values to mask the user's personally identifiable information, and (iv) storing the anonymized values within a protected vault to enable the user to login to the user account. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A method can include receiving scheduled tasks associated with subsystems of a wellsite system wherein the scheduled tasks are associated with achievement of desired states of the wellsite system; transmitting task information for at least a portion of the scheduled tasks to computing devices associated with the subsystems; receiving state information via the wellsite system; assessing the state information with respect to one or more of the desired states; based at least in part on the assessing, scheduling a task; and transmitting task information for the task to one or more of the computing devices associated with the subsystems.

Abstract: The disclosed computer-implemented method for detecting unauthorized data shares may include (1) providing a user of an anonymized inbox with an email alias to use for a particular online entity, (2) identifying one or more emails sent to the email alias from one or more different entities that are different from the particular online entity, (3) determining, based on the one or more emails having been sent by the different entities, that the particular online entity has shared the user's email alias with other entities, and (4) creating a privacy score for the particular online entity based at least in part on the determination that the particular online entity has shared the user's email alias with other entities. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A method can include receiving data associated with a drilling operation in a geologic environment; determining a state based at least in part on the data; representing the state using a symbolic representation scheme that includes letters; storing the represented state in a database; and, for a combination of letters that represents a combination of states, performing a search engine based search of the database to generate a search result.

Abstract: A security device for use with an item of merchandise may include a rigid housing adapted for insertion into a pocket of the item, an alarm disposed within the housing, and a sensor mounted to the housing. The sensor may be configured to indicate whether the security device is outside the pocket of the item, whereby an indication that the security device is outside the pocket of the item causes the alarm to generate a human-perceptible alert.