Multiphase flow online real-time metering artificial intelligence model construction method

A technology of artificial intelligence and construction methods, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as poor model accuracy and model iteration errors, and achieve improved accuracy, reduced complexity, and high measurement. The effect of precision

Active Publication Date: 2020-07-28
SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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AI Technical Summary

Benefits of technology

Inventions described in this patents have improved techniques for measuring multiple phases simultaneously during fluid flows within specific areas or locations called wellbores. These improvements include advanced models that combine various measurements into one single set, eliminating complex calculations associated with separate systems, enabling faster analysis times, reduced computational load, increased efficiency, and greater precision than current technologies. Additionally, these advancements aimed at simplifying the overall structure of the system itself through modularization and automated assembly processes. Overall, they provide technical benefits over existing solutions like ventilation/oil pressure monitors and electric conductivity probings.

Problems solved by technology

Technological Problem: Current Online Real Time Flow Measurement Technology has limitations with regards to accurately measuring complex flows like oil field breathing or fluid dispersion by separating them into two phases before they reach the end user. Existing techniques require separate measurements at several locations along pipes leading to errors during analysis processes. There is currently no complete solution available for all types of oil fields while maintaining their economics over longer periods.

Method used

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  • Multiphase flow online real-time metering artificial intelligence model construction method
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  • Multiphase flow online real-time metering artificial intelligence model construction method

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Embodiment Construction

[0038] In the following, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. According to these detailed descriptions, those skilled in the art can clearly understand the present application and can implement the present application. Without violating the principle of the present application, the features in various embodiments can be combined to obtain new implementations, or to replace some features in some embodiments to obtain other preferred implementations.

[0039] The existing online metering equipment for multiphase flow of oil, gas and water produced in oil fields mainly uses a combination of multiple equipment to measure the key parameters of the three-phase flow of oil, gas and water. The key parameters usually measured are gas flow and liquid flow. And three key values ​​of moisture content. Among them, the total flow measurement of the three-phase oil, gas and water usually uses Venturi to measure the

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Abstract

The invention belongs to the technical field of flow measurement, and particularly relates to a multiphase flow online real-time metering artificial intelligence model construction method. Oil-gas-water multiphase flow physical property parameters are various, and the flow process is complex, so that the development of a real-time flow measurement technology in an oil-gas production process is seriously restricted. The invention provides a multiphase flow online real-time metering artificial intelligence model construction method. The method comprises the steps of adopting Venturi measurementequipment, an electrical tomography sensor and a microwave sensor to cooperatively measure signals; by means of a deep encoding-decoding mode, under the condition that a large number of real flow sample tags do not exist, fully utilizing a large number of flow-tag-free measurement signals, and extracting the most basic constituent unit signals in the measurement signals; and constructing an artificial intelligence identification model of the flow of the measurement signal, the gas phase, the oil phase and the water phase according to the extracted minimum measurement signal forming unit. And meanwhile, the label-free measurement signal is fully utilized, so that higher measurement precision is realized.

Description

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Claims

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Application Information

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Owner SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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