A well cutting tool, comprising a housing including a chamber, the housing having at least one nozzle, the chamber being loaded with thermite, and a gas-generating additive an ignitor such that when the ignitor is actuated to ignite the thermite, the gas-generating additive is caused to create an increase in pressure which discharges energised molten thermite from the chamber and out of the housing through the at least one nozzle.

The hybrid battery system includes a primary battery pack, a secondary battery pack, a battery control unit, a battery pack positive terminal, and a battery pack negative terminal. The battery control unit includes a management module and a variable resistor. The primary battery pack supplies power at lower temperatures, while the secondary battery pack supplies power at higher temperatures. The primary battery pack is unsafe at higher temperatures, and the primary cells within the primary battery pack are modified to mitigate the dangers that previously rendered the primary battery pack unusable in a hybrid battery pack at higher temperatures. The invention includes the method of safely operating the hybrid battery system with the modified primary battery cells of the primary battery pack.

A method for reducing gas pressure at or nearby a wellhead, the method for comprising the steps of

Providing an intake for high pressure natural;

Conveying the high pressure natural gas to a motion creating element;

Utilizing the motion creating element to reduce the pressure of the natural gas;

Communicating the turning motion into a power generating element; whereby the high pressure gas leaves the motion creating element having less pressure than when it was conveyed to the motion creating element.

An actuator of a downhole tool used in oil and gas exploration and production operations is operable to actuate a first implement in a first direction. A biasing device of the downhole tool is operable to actuate the first implement in a second direction, opposite the first direction. A dampener of the downhole tool is operable to slow an actuation speed of the first implement in the first direction, the second direction, or both. Actuating the first implement in the first direction also actuates a second implement of a flow control device (“FCD”) of the downhole tool, to which the first implement is connected, in the first direction, placing the FCD in a first (e.g., open) configuration. Actuating the first implement in the second direction also actuates the second implement of the FCD in the second direction, placing the FCD in a second (e.g., closed) configuration.

An actuator of a downhole tool used in oil and gas exploration and production operations is operable to actuate a first implement in a first direction. A biasing device of the downhole tool is operable to actuate the first implement in a second direction, opposite the first direction. A dampener of the downhole tool is operable to slow an actuation speed of the first implement in the first direction, the second direction, or both. Actuating the first implement in the first direction also actuates a second implement of a flow control device (“FCD”) of the downhole tool, to which the first implement is connected, in the first direction, placing the FCD in a first (e.g., open) configuration. Actuating the first implement in the second direction also actuates the second implement of the FCD in the second direction, placing the FCD in a second (e.g., closed) configuration.

The present invention relates to alternating stress fatigue testing equipment. The alternating stress fatigue testing equipment includes a pedestal on which linear guide rails are arranged; a deflection loading device which is arranged on the pedestal and configured to, in response to a clamped to-be-measured object being driven to slide to a first position, enable the to-be-measured object to be bent to a target degree and keep the to-be-measured object after the to-be-measured object is bent to the target degree, wherein the deflection loading device is rotatably connected to the to-be-measured object; two hinged shaft supports which are arranged on the linear guide rails, wherein the hinged shaft supports are symmetrically arranged about a longitudinal center line of the deflection loading device, connected to both ends of the to-be-measured object respectively, and configured to be adjusted obliquely to adapt to the bending of the to-be-measured object to the target degree.

A method for isolating a horizontal tie-in pipeline of an inactive hydrocarbon-producing well from a main pipeline to prevent flow of hydrocarbons into the tie-in pipeline includes the steps of: identifying a location of a junction of the tie-in pipeline and the main pipeline and cleaning the tie-in pipeline by deploying a locating and cleaning assembly into the tie-in pipeline, withdrawing the locating and cleaning assembly, deploying a plug device having a longitudinally extending forward probe and a sealing element to the location of the junction, and remotely actuating the sealing element. The locating and cleaning device includes a pipeline junction sensing element longitudinally extending from a forward end of the locating and cleaning device. The sensing element is connected to a valve which, when open, relieves pressure in the locating and cleaning assembly as an indicator of the location of the junction.

A method for a hyperparameter optimization for an automated ensemble machine learning model includes: generating an initial population of a plurality of machine learning (ML) models with a plurality of randomly chosen hyperparameters; calculating a loss function for each of the plurality of machine learning models; creating a new population of ML models and generating a base learner model using the hyperparameters of the best model. The method for creating the new population include the steps of: (a) selecting multiple best models with least errors as parents from a previous generation; (b) creating an offspring of the new population of ML models with a crossover probability and a mutation probability; and (c) repeating the steps (a) and (b) until a number of generations is reached and reporting the hyperparameters of the best model.

A method for a hyperparameter optimization for an automated ensemble machine learning model includes: generating an initial population of a plurality of machine learning (ML) models with a plurality of randomly chosen hyperparameters; calculating a loss function for each of the plurality of machine learning models; creating a new population of ML models and generating a base learner model using the hyperparameters of the best model. The method for creating the new population include the steps of: (a) selecting multiple best models with least errors as parents from a previous generation; (b) creating an offspring of the new population of ML models with a crossover probability and a mutation probability; and (c) repeating the steps (a) and (b) until a number of generations is reached and reporting the hyperparameters of the best model.

A cleaning system for oil and gas core samples includes a vapor extraction chamber configured to receive and drain liquid solvents, a movable portion including a movable tray, a lid and a sample cooler, a heater configured to provide heat to the chamber to produce heated and vaporized solvents, a vapor extraction chamber chiller, a controller, and a dryer. A method of cleaning oil and gas core samples includes a vapor extraction step and a drying step. The vapor extraction step includes transferring core samples into and sealing the vapor extraction chamber, heating liquid solvents and maintaining an elevated temperature and a positive pressure in the chamber until an extraction time expires, cooling and transferring the core samples out of the chamber. The drying step includes transferring the cleaned core samples into a dryer, drying the core samples until substantially free of solvents, and cooling the core samples.