Abstract: Fluid flow dynamics modeling methods and system are provided. In some embodiments, such methods include determining a bottomhole pressure for the unconventional reservoir based, at least in part, on a tubing head pressure for one or more wells penetrating at least a portion of the unconventional reservoir, one or more fluid properties of a fluid in the unconventional reservoir, and a well production volume for the one or more wells; determining a Productivity Index (PI) for the unconventional reservoir, based, at least in part, on the one or more fluid properties and measured well data for the one or more wells, wherein the measured well data includes a well production rate and a well flowing pressure; and determining a fluid depletion of the unconventional reservoir based, at least in part, on the bottomhole pressure and the PI.

Abstract: A plasmid vector comprising one or more heterologous nucleic acids or genes encoding a functional therapeutic protein configured to treat a retinal or ocular includes a human GRK1 promoter and human S/MAR enhancer to express the heterologous gene in both rod and cone photoreceptors.

Abstract: A method of determining average reservoir pressure for a subterranean formation is provided. The method includes shutting in a well in the subterranean formation; measuring a plurality of buildup pressures during a period of time wherein the well is shut in via a downhole pressure gauge; performing an eigen expansion of the plurality of buildup pressures to generate a plurality of eigenvalues; determining an estimated average reservoir pressure based, at least in part, on the plurality of eigenvalues; and producing fluids from the well based, at least in part, on the estimated average reservoir pressure.

Abstract: Fluid flow dynamics modeling methods and system are provided. In some embodiments, such methods include determining a bottomhole pressure for the unconventional reservoir based, at least in part, on a tubing head pressure for one or more wells penetrating at least a portion of the unconventional reservoir, one or more fluid properties of a fluid in the unconventional reservoir, and a well production volume for the one or more wells; determining a Productivity Index (PI) for the unconventional reservoir, based, at least in part, on the one or more fluid properties and measured well data for the one or more wells, wherein the measured well data includes a well production rate and a well flowing pressure; and determining a fluid depletion of the unconventional reservoir based, at least in part, on the bottomhole pressure and the PI.

Abstract: Fluid flow dynamics modeling methods and system are provided. In some embodiments, such methods include determining a bottomhole pressure for the unconventional reservoir based, at least in part, on a tubing head pressure for one or more wells penetrating at least a portion of the unconventional reservoir, one or more fluid properties of a fluid in the unconventional reservoir, and a well production volume for the one or more wells; determining a Productivity Index (PI) for the unconventional reservoir, based, at least in part, on the one or more fluid properties and measured well data for the one or more wells, wherein the measured well data includes a well production rate and a well flowing pressure; and determining a fluid depletion of the unconventional reservoir based, at least in part, on the bottomhole pressure and the PI.

Abstract: Fluid flow dynamics modeling methods and system are provided. In some embodiments, such methods include providing an initial fluid system model including a plurality of nodes, each node characterized by one or more node fluid system parameters; and a plurality of edges between two of the plurality of nodes, each edge characterized by one or more edge fluid system parameters; and using the initial fluid system model, determining an updated fluid system model using a history-matching process.

Abstract: Fluid flow dynamics modeling methods and system are provided. In some embodiments, such methods include providing an initial fluid system model including a plurality of nodes, each node characterized by one or more node fluid system parameters; and a plurality of edges between two of the plurality of nodes, each edge characterized by one or more edge fluid system parameters; and using the initial fluid system model, determining an updated fluid system model using a history-matching process.

Abstract: The present disclosure provides a control system, a control method and a control device of an intelligent robot based on artificial intelligence. The system includes: a decision engine, disposed on the intelligent robot, and configured to generate cloud processing information according to a multimodal input signal, and to send the cloud processing information; and a cloud control center, configured to receive the cloud processing information, to obtain a user demand by analyzing the cloud processing information, and to return the user demand, such that the decision engine controls the intelligent robot according to at least one of the user demand and the multimodal input signal. The control system may make full use of great online information, enhance the capability of the intelligent robot for storage, calculation and processing complex decisions, and meanwhile may respond to the user's instruction timely, rapidly and intelligently, and improve the user experience.

Abstract: The present disclosure provides a human-computer interactive method and apparatus based on artificial intelligence, and a terminal device. The human-computer interactive method based on artificial intelligence includes: receiving a multimodal input signal, the multimodal input signal including at least one of a speech signal, an image signal and an environmental sensor signal; determining an intention of a user according to the multimodal input signal; processing the intention of the user to obtain a processing result, and feeding back the processing result to the user.

Abstract: The present disclosure provides a control system, a control method and a control device of an intelligent robot based on artificial intelligence. The system includes: a decision engine, disposed on the intelligent robot, and configured to generate cloud processing information according to a multimodal input signal, and to send the cloud processing information; and a cloud control center, configured to receive the cloud processing information, to obtain a user demand by analyzing the cloud processing information, and to return the user demand, such that the decision engine controls the intelligent robot according to at least one of the user demand and the multimodal input signal. The control system may make full use of great online information, enhance the capability of the intelligent robot for storage, calculation and processing complex decisions, and meanwhile may respond to the user's instruction timely, rapidly and intelligently, and improve the user experience.

Abstract: This disclosure provides systems, methods and apparatuses for supporting a mechanical layer. In one aspect, an electromechanical systems device includes a substrate, a mechanical layer, and a post positioned on the substrate for supporting the mechanical layer. The mechanical layer is spaced from the substrate and defines one side of a gap between the mechanical layer and the substrate, and the mechanical layer is movable in the gap between an actuated position and a relaxed position. The post includes a wing portion in contact with a portion of the mechanical layer, the wing portion positioned between the gap and the mechanical layer. The wing portion can include a plurality of layers configured to control the curvature of the mechanical layer.