Systems and methods for transmitting power to wirelessly powered sensors using a pipeline as a circular waveguide are disclosed. In an embodiment, a transmitter transmits electromagnetic waves to at least one wirelessly powered sensor positioned along the pipeline, wherein the pipeline is used as a waveguide to transmit the electromagnetic waves using a particular waveguide mode form of electromagnetic radiation, where the at least one wirelessly powered sensor is configured to be operated without a battery and to be powered by the electromagnetic waves emitted by the electromagnetic transmitter and senses at least one characteristic of the pipeline.

Techniques for determining a thermal condition of a pipeline include identifying a pipeline that carries a first fluid at a first temperature that includes a tubular conduit that includes a bore that carries the first fluid, and a layer of insulation installed over the tubular conduit; circulating a second fluid at a second temperature from a bypass conduit that is fluidly coupled to the tubular conduit through the layer of insulation into the bore; based on circulating the second fluid into the bore, detecting a thermal gradient between the first fluid carried in the bore and the tubular conduit or the layer of insulation at a particular location of the pipeline; and based on the detected thermal gradient, determining a presence of at least one of water or water vapor between the tubular conduit and the layer of insulation at the particular location of the pipeline.

A method for an underground gas storage reservoir management may include obtaining feed from a domestic master gas system. The method further includes simultaneously injecting and reproducing in an underground gas storage via a plurality of dual producer and injector wells. The method further includes enhancing the underground gas storage reservoir management to maximize gas and condensate recovery. The method further includes improving a switching cycle between dual operation modes in the underground gas storage for faster reaction times through a completely segregated injection and reproduction lines.

A system may automatically control a pipeline heating system to maintain a desired temperature and/or to provide flow assurance of process fluid along a pipeline. The system may identify the occurrence and location of the solidification of a given process fluid or the melting of the given process fluid by monitoring temperatures along the pipeline and identifying from the monitored temperatures the occurrence and location of a latent heat signature associated with the solidification or melting of the given process fluid. The system may calculate and display fill percentages of the solidified process fluid at locations along the pipeline. The system may determine the percentage of a given section of pipeline that is filled with solid and/or liquid process fluid on a meter-by-meter basis. The system may perform automated re-melt operations to resolve plugs of solidified process fluid that may occur in the pipeline.

A method of inspection or maintenance of a curved ferromagnetic surface using an unmanned aerial vehicle (UAV) having a releasable crawler is provided. The method includes: flying the UAV from an initial position to a pre-perching position in a vicinity of the ferromagnetic surface; autonomously perching the UAV on the ferromagnetic surface; maintaining magnetic attachment of the perched UAV to the ferromagnetic surface; releasing the crawler from the magnetically attached UAV onto the ferromagnetic surface; moving the crawler over the curved ferromagnetic surface while maintaining magnetic attachment of the released crawler to the ferromagnetic surface; inspecting or maintaining the ferromagnetic surface using the magnetically attached crawler; and re-docking the released crawler with the perched UAV.

A system and methodology for launching, flying and perching on a cylindrically curved surface in an environment without human intervention. The system and methodology include an environment awareness sensor device suite having a depth camera arranged to capture and output image data and 3D point cloud data of a field of view; an asset targeting unit arranged to set an asset as a destination location for a landing; a trajectory path determiner arranged to calculate a trajectory path to the destination location; a flight controller arranged to launch and fly the autonomous aerial vehicle to the destination location according to the trajectory path; a situational status determiner arranged to, in real-time, predict a location of an object with respect to the autonomous aerial vehicle based on 3D point cloud data for the object, determine the object is the asset based on a confidence score and autonomously land on the asset.

A magnetic crawler configured to navigate on and inspect a ferromagnetic cylindrical surface is provided. The crawler includes a chassis, a controller configured to control the crawler, a probe configured to inspect the cylindrical surface under the control of the controller, and only three articulated magnetic wheels configured to tangentially contact and magnetically adhere to the cylindrical surface. The wheels include two drive wheels respectively coupled to the chassis by two articulation joints and configured to drive the crawler in a desired direction on the cylindrical surface by actively rotating the two drive wheels independently about respective drive axes of rotation by respective drive motors under the control of the controller; and a rear wheel coupled to the chassis by a rear articulation joint and configured to passively rotate about a rear drive axis of rotation in response to the active rotations of the two drive wheels.

The present disclosure provides a method for smart gas pipeline life prediction based on safety. The method includes: obtaining the operation information of the target gas pipeline section within the first time period; determining, based on operation information, the first performance parameter of the target gas pipeline section of at least one moment within the first time period, the first performance parameter including at least the transport performance of the target gas pipeline section within the first time period; determining, based on the first performance parameter of at least one moment, the first performance parameter sequence of the target gas pipeline section within the first time period, the first performance parameter sequence being the sequence obtained by arranging the first performance parameters of at least one moment in chronological order; and determining, based on the first performance parameter sequence, the remaining life of the target gas pipeline section.

The present invention provides a method and a machine-learning system for predicting pipeline corrosion. The pipeline corrosion prediction according to the method and system comprises steps of i) generating a predictive model (100) based on a neural network algorithm; ii) applying a supervised machine learning technique for training the predictive model (100) from step i); and iii) applying the predictive model (100) from step ii) to other sets of the input data in order to predict a depth of metal loss rate (122). The predictive model (100) includes multiple modules relevant to a water condensation rate module, a flow regime module, a corrosion rate module, and an operating data module. Each module is integrated into a concatenate layer (114) and then processing through hidden layers (116), a long short-term memory layer (118) and hidden layers (120) respectively, in order to generate the depth of metal loss rate with high accuracy.

A method of remote facilities monitoring for the detection of contamination, leaks or failures in petrochemical and related facilities. Remote cameras are used to capture images of equipment to be inspected, which are transmitted to a central server. A software component on the central server applies artificial intelligence and image processing methods to detect the presence of anomalies in the images for display to an operator and potential subsequent dispatch of in person follow-up. Parallel data streams from sensors at the remote sites can be used by the software on the server to enhance the level of confidence in anomaly detection. The rl server software uses an adaptive object-detection function to analyze image data and learns over time to provide enhanced detection of interest regions and failure conditions.