Abstract: A drillstring, in a drilling environment, operatively connected to an information handling system, where the information handling system is configured to perform a method for modifying drilling operations that includes obtaining measured drillstring data associated with the drillstring, and calculating a heat generation using the measured drillstring data, where, based on the heat generation, a drilling modification procedure is performed.

Abstract: Mathematical equations for predicting a percent drag reduction (% DR) value for friction-reducing (FR) polymer compositions including various polymer properties and base fluid properties as the independent variables such as base fluid salinity, type of salts in the base fluid, molecular weight of the FR polymers, FR polymer concentrations, degrees of ionicity of the FR polymers, and percent sulfonation of AMPS-containing FR polymers.

Abstract: Systems and methods of the disclosed embodiments include a rheometer having a housing with a fluid inlet and a fluid outlet, a cylinder with a cavity located to receive fluid that passes into the fluid inlet, a motor configured to rotate the cylinder, a torsion bob within the cavity, and a controller located remotely from the rheometer. The controller includes a pressure regulator configured to pressurize fluid to power the motor, a rotation sensor configured to receive an optical rotation signal indicating a rotation speed of the cylinder, and a torque sensor configured to receive an optical signal indicating a torque on the torsion bob. The controller may be configured to receive a rotation speed signal from the rotation sensor, a torque signal from the torque sensor, and to calculate a shear stress for the fluid based on the rotation speed signal and the torque signal.

Abstract: Systems and methods for latency-tolerant assistance of autonomous vehicles (AVs) are described herein. In one aspect, a computer-implemented method for receiving latency-tolerant assistance of an AV can include receiving sensory data from the AV; detecting from the sensory data a trigger for assistance; generating a request for assistance including at least a portion of the sensory data of the AV; receiving, in response to the request for assistance, an operator command for responding to the trigger for assistance; and initiating one or more actuation commands via an actuation subsystem of the AV in response to the received operator command.

Abstract: Systems and methods for testing, training, and instructing autonomous vehicles (AVs) are described herein. In one aspect, a computer-implemented method for live testing an AV including generating one or more test objects from a stored set of test objects, test object attributes, or a combination thereof; superimposing the one or more test objects on sensory data received from one or more sensors of the AV and corresponding to an external environment of the AV; and testing one or more software subsystems of the AV, in a manual mode, a partially autonomous mode or a fully autonomous mode, with the sensory data after superimposition.

Abstract: Methods, systems, and computer programs are presented for creating notifications for resources shared or posted by connections of a member. One method includes an operation for accessing databases to collect member information that includes first-degree connections and information about each first-degree connection. Further, a list of first-degree connections is stored in a data store with information about each first-degree connection. The method further includes operations for detecting a resource associated with a first member, and for accessing the data store to obtain network connections (first- and second-degree connections) of the first member. For each network connection of the first member, the method determines if the resource is relevant for the network connection based on the retrieved member information. Further, the method includes generating a notification about the resource for one or more of the network connections based on a relevance of the resource to the network connection.

Abstract: An illustrative computing system for a dynamic user access control management system classifies users and data resources according to their risk and importance by a user management engine with artificial intelligence, machine learning characteristics. The dynamic user access control management system analyzes the log files of data resources to measure system performance characteristics and user access behavior. This system monitors the device and network by which a data access request to a data resource is made. The dynamic user access control management system validates the leave status of a user initiating a data access request. The dynamic user access control management system automatically determines a user access level for a data resource through intelligent analysis of collected information and defers to a user's manager for an access level determination when the determination to grant an access level is outside of the knowledge base of the user management engine.

Abstract: Disclosed are methods in which measurements are obtained from a plurality of sensors secured in spaced relation to one another across at least a portion of the depth of reservoir of some form in order to identify one or more characteristics of the fluids within the reservoir. The sensors are used to monitor ambient forces exerted by fluids within the tank proximate each sensor. An example mechanism for obtaining the measurements includes a plurality of sensors, such as strain gauges, supported on a structure that supports the sensors in fixed relation to one another, and can, in some examples, support the sensors in a known relation relative to boundaries of the reservoir.

Abstract: An illustrative computing system for a dynamic user access control management system classifies users and data resources according to their risk and importance by a user management engine with artificial intelligence, machine learning characteristics. The dynamic user access control management system analyzes the log files of data resources to measure system performance characteristics and user access behavior. This system monitors the device and network by which a data access request to a data resource is made. The dynamic user access control management system validates the leave status of a user initiating a data access request. The dynamic user access control management system automatically determines a user access level for a data resource through intelligent analysis of collected information and defers to a user's manager for an access level determination when the determination to grant an access level is outside of the knowledge base of the user management engine.

Abstract: Drilling fluid can be monitored throughout a drill site and at various stages of drilling operations. The drilling fluid may be analyzed to identify components that make the drilling fluid as well as the volume of each of the components, The volume of each component can be used, for example, to determine a percentage of water in a water-based drilling fluid and the average specific gravity of the water-based drilling fluid without further decomposition of the drilling fluid. The percentage of water and the average specific gravity can then be used to modify the drilling fluid, in real-time, based on conditions in the wellbore.

Abstract: The equivalent circulating density (“ECD”) in a wellbore may be managed during a wellbore operation using ECD models that take into account the rheology of the wellbore fluid and the rotational speed of tubulars in the wellbore. For example, a method may include rotating a rotating tubular in a stationary conduit while flowing a fluid through an annulus between the rotating tubular and the stationary conduit; calculating an equivalent circulating density (“ECD”) of the fluid where a calculated viscosity of the fluid is based on an ECD model ?_eff=f(? ?_eff)*h(Re), wherein ?_eff is the viscosity of the fluid, ? ?_eff is an effective shear rate of the fluid, and Re is a Reynold's number for the fluid for the rotational speed of the rotating tubular; and changing an operational parameter of the wellbore operation to maintain or change the ECD of the fluid.

Abstract: An illustrative computing system for a dynamic user access control management system classifies users and data resources according to their risk and importance by a user management engine with artificial intelligence, machine learning characteristics. The dynamic user access control management system analyzes the log files of data resources to measure system performance characteristics and user access behavior. This system monitors the device and network by which a data access request to a data resource is made. The dynamic user access control management system validates the leave status of a user initiating a data access request. The dynamic user access control management system automatically determines a user access level for a data resource through intelligent analysis of collected information and defers to a user's manager for an access level determination when the determination to grant an access level is outside of the knowledge base of the user management engine.

Abstract: Systems and methods for adjusting well operations utilize measured values and curve fitting to determine predicted values of the gel strength of well-treatment fluids. The systems and methods are exemplified by first measuring a plurality of measured values representative of the gel strength of the well-treatment fluid, then determining a mathematical function that fits the plurality of measured values. From the mathematical function, the projected values are determined. The projected values are representative of the gel strength for the well-treatment fluid after a projected-value static period.

Abstract: Systems and methods of the disclosed embodiments include a rheometer having a housing with a fluid inlet and a fluid outlet, a cylinder with a cavity located to receive fluid that passes into the fluid inlet, a motor configured to rotate the cylinder, a torsion bob within the cavity, and a controller located remotely from the rheometer. The controller includes a pressure regulator configured to pressurize fluid to power the motor, a rotation sensor configured to receive an optical rotation signal indicating a rotation speed of the cylinder, and a torque sensor configured to receive an optical signal indicating a torque on the torsion bob. The controller may be configured to receive a rotation speed signal from the rotation sensor, a torque signal from the torque sensor, and to calculate a shear stress for the fluid based on the rotation speed signal and the torque signal.

Abstract: Drilling fluid can be monitored throughout a drill site and at various stages of drilling operations. The drilling fluid may be analyzed to identify components that make the drilling fluid as well as the volume of each of the components, The volume of each component can be used, for example, to determine a percentage of water in a water-based drilling fluid and the average specific gravity of the water-based drilling fluid without further decomposition of the drilling fluid. The percentage of water and the average specific gravity can then be used to modify the drilling fluid, in real-time, based on conditions in the wellbore.

Abstract: Systems and methods for adjusting well operations utilize measured values and curve fitting to determine predicted values of the gel strength of well-treatment fluids. The systems and methods are exemplified by first measuring a plurality of measured values representative of the gel strength of the well-treatment fluid, then determining a mathematical function that fits the plurality of measured values. From the mathematical function, the projected values are determined. The projected values are representative of the gel strength for the well-treatment fluid after a projected-value static period.

Abstract: Systems, computer program products, and methods are described herein for automated resource retrieval based on change detection in a technical environment. The present invention is configured to monitor states of the code test environments; electronically receive an indication of a state change associated with a first code test environment; determine that the state change is associated with a code test execution request received from a second code test environment; receive a first set of resources to execute the code test execution request on the first code test environment; determine a second set of resources associated with the first code test environment; determine that the first set of resources and the second set of resources do not meet resource requirements; transmit a request for the additional resources from the first code test environment; and receive the additional resources; and execute the code test execution request on the first code test environment.

Abstract: An illustrative computing system for a dynamic user access control management system classifies users and data resources according to their risk and importance by a user management engine with artificial intelligence, machine learning characteristics. The dynamic user access control management system analyzes the log files of data resources to measure system performance characteristics and user access behavior. This system monitors the device and network by which a data access request to a data resource is made. The dynamic user access control management system validates the leave status of a user initiating a data access request. The dynamic user access control management system automatically determines a user access level for a data resource through intelligent analysis of collected information and defers to a user's manager for an access level determination when the determination to grant an access level is outside of the knowledge base of the user management engine.

Abstract: Disclosed are methods in which measurements are obtained from a plurality of sensors secured in spaced relation to one another across at least a portion of the depth of reservoir of some form in order to identify one or more characteristics of the fluids within the reservoir. The sensors are used to monitor ambient forces exerted by fluids within the tank proximate each sensor. An example mechanism for obtaining the measurements includes a plurality of sensors, such as strain gauges, supported on a structure that supports the sensors in fixed relation to one another, and can, in some examples, support the sensors in a known relation relative to boundaries of the reservoir.

Abstract: Disclosed are methods in which measurements are obtained from a plurality of sensors secured in spaced relation to one another across at least a portion of the depth of reservoir of some form in order to identify one or more characteristics of the fluids within the reservoir. The sensors are used to monitor ambient forces exerted by fluids within the tank proximate each sensor. An example mechanism for obtaining the measurements includes a plurality of sensors, such as strain gauges, supported on a structure that supports the sensors in fixed relation to one another, and can, in some examples, support the sensors in a known relation relative to boundaries of the reservoir.