Abstract: Systems, methods, and computer-readable storage media for reinforcing and modifying the search engine behavior using aspects of federated learning. A system can receive from a user at a first time, a query for a product, then generate a vector representation of the query, and execute a search of an embedding space for the vector representation, resulting in at least one similarity score for at least one product. The system can present to the user search results based on the at least one similarity score, and receive from the user a selected product from within the search results. The system can update, based on the selected product, the at least one similarity score for the selected product, resulting in at least one updated similarity score, where when the query is received again the search of the embedding space for the vector representation produces the at least one updated similarity score.

Abstract: Systems, methods, and computer-readable storage media for reinforcing and modifying the search engine behavior using aspects of federated learning. A system can receive, from a plurality of first users at a computer system, a query for a product, and generate a vector representation of the query. The system can then execute a search of an embedding space for the vector representation, resulting in a first ranked list of at least one product, wherein the embedding space comprises vectorized product representations for a plurality of products, and wherein the first ranked list is ranked in order of similarity of the vectorized product representations to the vector representation of the query. As feedback is received from multiple users, and the query is received again, the system can generate a second ranked list which is the first ranked list modified by the feedback of the plurality of first users.

Abstract: A product management computer system that can include one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the processors, can cause the processors to: receive data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated; process the received data through a machine-learning-produced algorithm and generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transform the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm; and output data representing

Abstract: A product management computer system that can include one or more processors, and a computer-readable medium comprising instructions stored therein, which when executed by the processors, can cause the processors to: receive data representing a target product of interest to a user of the system, wherein the target product is described by a plurality of variable-value attributes associated; process the received data through a machine-learning-produced algorithm and generating data representing a first set of substitute product candidates for the target product and wherein each substitute product candidate has a corresponding match-score that represents a degree of determined similarity between that substitute product candidate and the target product; transform the generated data that represents the first set of substitute product candidates into data representing a refined set of substitute product candidates by processing the generated data utilizing a constraint-based algorithm; and output data representing

Abstract: Systems, methods, and computer-readable media for a well construction activity graph builder. An example method can include obtaining a stream of events associated with a wellbore; obtaining mapping metadata identifying data points to be included in a graph data model from a store of data associated with the wellbore; generating the graph data model based on the stream of events, the mapping metadata, and the data points identified in the mapping metadata, the graph data model including nodes representing logical entities associated with the data points, the nodes having interconnections based on data relationships defined in the mapping metadata, each logical entity corresponding to a set of data points from the data points; and generating a view of the graph data model, the view depicting at least some of the nodes and interconnections in the graph data model.

Abstract: Systems, methods, and computer-readable media are described for intelligent, real-time monitoring and managing of changes in oilfield equilibrium to optimize production of desired hydrocarbons and economic viability of the field. In some examples, a method can involve generating, based on a topology of a field of wells, a respective graph for the wells, each respective graph including computing devices coupled with one or more sensors and/or actuators. The method can involve collecting, via the computing devices, respective parameters associated with one or more computing devices, sensors, actuators, and/or models, and identifying a measured state associated with the computing devices, sensors, actuators, and/or models.

Abstract: Systems, methods, and computer-readable media for automatic classification of drilling reports with deep natural language processing. A method may involve obtaining drilling reports associated with respective well drilling or operation activities, and based on the drilling reports, generating a plurality of word vectors, wherein each word vector from the plurality of word vectors represents a respective word in the drilling reports. The method can further involve partitioning sentences in the drilling reports into respective words and, for each sentence, identifying respective word vectors from the plurality of word vectors, the respective word vectors corresponding to the respective words associated with the sentence. The method can involve classifying via a neural network, the sentences in a drilling report into at least one of respective events, respective symptoms, respective actions, and respective results. The method can also classify sentences according to any set of labels of interest.

Abstract: Systems, methods, and computer-readable media are described for the mutual improvement of physics-based and data-driven models related to an oilfield. These may involve generating, via a processor, with an oilfield related condition as a first input, a first output based on one of a physics-based model or a data-based model; generating, using the first input or a second input, a second output based on the other of the physics-based model or the data-based model not used to generate the first output; and modifying, automatically, at least one of the physics-based model, data-driven model, the first input or the second input, based on the first output or second output.

Abstract: A system and method for monitoring and predicting a gas leak at a facility involving receiving, via a server, real-time data measured via a plurality of sensors spaced throughout a facility; scrubbing, via the server, the real-time data by removing a plurality of spikes, a plurality white noise, or a combination thereof, from the real-time data to yield a set of scrubbed data; determining a gas leak location within the facility based on the scrubbed data; conducting a gas leak simulation based on the scrubbed data; determining a potential gas leak distribution based on the scrubbed data and the gas leak simulation; calculating a risk profile based on a set of predetermined risk parameters; generating a notification based on the potential gas leak distribution and the risk profile; and transmitting over a network, the risk profile and the potential gas leak distribution to at least one mobile device.

Abstract: An example method includes receiving a data set containing combinations of drilling parameter values and operating condition values for a drilling system corresponding to each combination of drilling parameter values. At least one of a frequency and a duration of use may be determined for each of the combinations of drilling parameter values in the data set. For at least some of the combinations of drilling parameter values, a contour map identifying the combinations of drilling parameter values, the operating condition values corresponding to the combinations of drilling parameter values, and at least one of the frequency and the duration of use may be displayed for at least some of the combinations of drilling parameter values.

Abstract: Tight spots in movements of a drill string in an oil well are identified by comparing a large interval hookload moving average to a short interval hookload moving average, comparing a large interval bit depth moving average to a short interval bit depth moving average, and DBSCANing the tight spots to identify a fully-stuck event.