Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Systems and methods are provided for estimating the total base number of used oil in an engine. The systems and methods can involve characterizing the sulfur content and at least one other element content of the oil both before introduction into the engine and after passing through an engine cylinder during combustion. Depending on the aspect, a total base number of the oil prior to use can also be measured, or the total base number before use can be estimated based on the at least one element content.

A sensing system for detecting degradation of a machine fluid is disclosed. The sensing system may comprise a tag having electrical contacts. The tag may be configured to transmit a wireless signal when the electrical contacts are in electrical communication. The sensing system may further comprise a dissolvable element separating the electrical contacts and obstructing electrical communication between the electrical contacts. The dissolvable element may be configured to dissolve and allow electrical communication between the electrical contacts when an acid content of the machine fluid reaches a level indicative of the degradation of the machine fluid.

Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.

Embodiments of the present disclosure provide for systems, apparatuses, and methods for real-time fluid analysis. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and real-time data may be collected from the fluid via the sampling system. The sampling system may process and transmit the real-time data to the analytical system. The analytical system may include a command and control system that may receive and store the real-time data in a database and compare the real-time data to existing data for the fluid in the database to identify conditions in the fluid.

Described herein are systems and methods for evaluating and mitigating the fouling potential of a given crude oil. The system and methods enable the refiner to rapidly and readily identify the particular mechanisms by which a crude oil may foul, and to select the optimal chemical treatment and/or crude blend to mitigate fouling potential.

The present disclosure provides systems, apparatuses, and methods for fluid analysis. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and real-time data may be collected from the fluid via the sampling system. The sampling system may process and transmit the real-time data to the analytical system. The analytical system may include a command and control system that may receive and store the real-time data in a database and compare the real-time data to existing data for the fluid in the database to identify conditions in the fluid.

The invention relates to a method of characterization of one petroleum, wherein the petroleum is placed in contact with a metal part, and which includes the following steps: i. Modifying the water content (W) of the petroleum, ii. Measuring the corrosion (CR) of said metal part by the petroleum whose water content (W) has hence been modified, iii. Building, by reiterating several times the two previous steps (i, ii), a database containing a plurality of different values of water content (W) of the petroleum and a plurality of values of corrosion (CR) each corresponding to one of said values of water content (W), iv. Determining, by processing said database, an optimum value or an optimum range of values of water content (M.sub.W) of the petroleum for which the corrosion of the metal part shows a minimum value (M.sub.CR).

Problems of corrosion in the petroleum exploitation plants.

A method and system for monitoring the quality of fluids, wherein comprising the different features of a fluid with at least two different methods are measured and a measure for the quality of the fluid is derived and/or a process of the fluid deterioration is identified by comparing the results of the measurements of the at least two different methods, where the methods includes at least one optical absorption measurement and at least one electron paramagnetic resonance measurement.

Systems, methods, and computer-program products for fluid analysis and monitoring are disclosed. Embodiments include a removable and replaceable sampling system and an analytical system connected to the sampling system. A fluid may be routed through the sampling system and data may be collected from the fluid via the sampling system. The sampling system may process and transmit the data to the analytical system. The analytical system may include a command and control system to receive and store the data in a database and compare the data to existing data for the fluid in the database to identify conditions in the fluid. Fluid conditions may be determined using machine learning models that are generated from well-characterized known training data. Predicted fluid conditions may then be used to automatically implement control processes for an operating machine containing the fluid.