Abstract: A chemical injection system for a resource extraction system includes a controller having a memory and a processor. The memory stores instructions that cause the processor to receive a first pressure from a first pressure sensor of the resource extraction system, receive a second pressure from a second pressure sensor of the resource extraction system, determine a flowrate of a produced fluid of the resource extraction system based on the first pressure and the second pressure, determine an ion concentration of the produced fluid, and adjust an injection rate of a chemical into the resource extraction system based on the flowrate of the produced fluid, the ion concentration of the produced fluid, or both.

Abstract: A method can include receiving results from a field device at a field site, where the results are generated using a trained machine learning model at the field site and real-time field equipment data from field equipment at the field site; issuing a signal responsive to an assessment of the results, where the signal indicates a performance-related issue of the trained machine learning model; updating training data with at least a portion of the real-time field equipment data to address the performance-related issue; and generating a new trained machine learning model for deployment to the field site using at least a portion of the updated training data.

Abstract: A method, apparatus, and program product may utilize data associated with one or more electric submersible pumps (ESPs) to train a machine learning model and/or use a machine learning model to perform ESP failure analysis. In addition, one or more features from the data may be encoded into a machine-readable format to facilitate ingestion by the machine learning model.

Abstract: A method, apparatus, and program product may build parent-child well pairs from data associated with one or more wells in a basin and use one or more parameters associated with such well pairs to train or use a machine learning model to predict a production impact of an infill well on one or more neighboring wells in the basin.

Abstract: Provided herein are ready-to-use premixed pharmaceutical compositions of nicardipine or a pharmaceutically acceptable salt and methods for use in treating cardiovascular and cerebrovascular conditions.

Abstract: Provided herein are ready-to-use premixed pharmaceutical compositions of nicardipine or a pharmaceutically acceptable salt and methods for use in treating cardiovascular and cerebrovascular conditions.

Abstract: Disclosed herein are multivalent and multispecific binding proteins, methods of making the binding proteins, and their uses in the diagnosis, monitoring, inhibition, prevention and/or treatment of cancers, tumors, and/or other angiogenesis-dependent diseases diseases characterized by aberrant DLL4 and/or VEGF expression or activity.

Abstract: A method for optimizing oil production includes receiving historical production data for one or more wells. A first model is generated based at least partially upon the historical production data. The production in the one or more wells is predicted based at least partially upon the first model. A second model is generated based at least partially on the predicted production. A production allocation is determined in the one or more wells to maximize production based at least partially upon the second model. The production allocation is then implemented.

Abstract: A chemical injection system for a resource extraction system includes a controller having a memory and a processor. The memory stores instructions that cause the processor to receive a first pressure from a first pressure sensor of the resource extraction system, receive a second pressure from a second pressure sensor of the resource extraction system, determine a flowrate of a produced fluid of the resource extraction system based on the first pressure and the second pressure, determine an ion concentration of the produced fluid, and adjust an injection rate of a chemical into the resource extraction system based on the flowrate of the produced fluid, the ion concentration of the produced fluid, or both.

Abstract: The electrical submersible pump (ESP) is currently the fastest growing artificial-lift pumping technology. Deployed across 15 to 20 percent of oil-wells worldwide, ESPs are an efficient and reliable option at high production volumes and greater depths. However, ESP performance is often observed to decline gradually and reach the point of service interruption due to factors like high gas volumes, high temperature, and corrosion. The financial impact of ESP failure is substantial, from both lost production and replacement costs. Therefore, ESP performance in extensively monitored, and numerous workflows exist to suggest actions in case of break-downs. However, such workflows are reactive in nature, i.e., action is taken after tripping or failure. Therefore, a data-driven analytical framework is proposed to advance towards a proactive approach to ESP health monitoring based on predictive analytics to detect impending problems, diagnose their cause, and prescribe preventive action.

Abstract: A method includes generating a structured data object from a plurality of data files in a data repository, preprocessing the structured data object based on one or more features from the structured data object, executing an unsupervised machine-learning technique to identify one or more clusters of data files from the plurality of data files in the data repository, presenting at least one set of text from the one or more clusters to a user along with a word cloud for each of the one or more clusters, and receiving one or more labels for respective clusters of the one or more clusters.

Abstract: A method for analyzing data includes obtaining data objects from a data repository. The data objects include observational data related to one or more oil wells, oil fields, or a combination thereof. The method also includes classifying the data objects based on data contained therein using a machine-learning algorithm, and determining output data from the data objects after classifying the data objects. The output data represents one or more historical data analytics for the one or more oil wells, oil fields, or a combination thereof. The method further includes visualizing the output data including the one or more historical data analytics.

Abstract: Provided herein are ready-to-use premixed pharmaceutical compositions of nicardipine or a pharmaceutically acceptable salt and methods for use in treating cardiovascular and cerebrovascular conditions.

Abstract: The electrical submersible pump (ESP) is currently the fastest growing artificial-lift pumping technology. Deployed across 15 to 20 percent of oil-wells worldwide, ESPs are an efficient and reliable option at high production volumes and greater depths. However, ESP performance is often observed to decline gradually and reach the point of service interruption due to factors like high gas volumes, high temperature, and corrosion. The financial impact of ESP failure is substantial, from both lost production and replacement costs. Therefore, ESP performance in extensively monitored, and numerous workflows exist to suggest actions in case of break-downs. However, such workflows are reactive in nature, i.e., action is taken after tripping or failure. Therefore, a data-driven analytical framework is proposed to advance towards a proactive approach to ESP health monitoring based on predictive analytics to detect impending problems, diagnose their cause, and prescribe preventive action.

Abstract: Provided herein are ready-to-use premixed pharmaceutical compositions of nicardipine or a pharmaceutically acceptable salt and methods for use in treating cardiovascular and cerebrovascular conditions.

Abstract: A method includes receiving historical well-production data, and determining curve parameters based on the historical well production data. Determining the curve parameters includes accounting for uncertainty. The method also includes determining curve fits for the historical data based on the curve parameters using a plurality of models, calculating accuracy for each of the models based on a comparison of the curve fits to the well-production data, comparing the accuracy for each of the models using an information criteria that accounts for uncertainty, selecting one of the models based on the comparison, and determining an estimated ultimate recovery (EUR) for the well using at least the selected one of the models.

Abstract: A method for optimizing oil production includes receiving historical production data for one or more wells. A first model is generated based at least partially upon the historical production data. The production in the one or more wells is predicted based at least partially upon the first model. A second model is generated based at least partially on the predicted production. A production allocation is determined in the one or more wells to maximize production based at least partially upon the second model. The production allocation is then implemented.

Abstract: Disclosed herein are multivalent and multispecific binding proteins, methods of making the binding proteins, and their uses in the diagnosis, monitoring, inhibition, prevention and/or treatment of cancers, tumors, and/or other angiogenesis-dependent diseases diseases characterized by aberrant DLL4 and/or VEGF expression or activity.

Abstract: Provided herein are ready-to-use premixed pharmaceutical compositions of nicardipine or a pharmaceutically acceptable salt and methods for use in treating cardiovascular and cerebrovascular conditions.

Abstract: Disclosed herein are multivalent and multispecific binding proteins, methods of making the binding proteins, and their uses in the diagnosis, monitoring, inhibition, prevention and/or treatment of cancers, tumors, and/or other angiogenesis-dependent diseases diseases characterized by aberrant DLL4 and/or VEGF expression or activity.