The problem of how to accurately measure the flowrate of oil–gas–water mixtures in a pipeline remains one of the key challenges in the petroleum industry. This paper discusses why three-phase flow measurement is still important and why it remains a difficult problem to solve. The measurement strategies and principal base technologies currently used by commercial manufacturers are described, and research developments that could influence future flowmeter design are considered. Finally, future issues, which will need to be addressed by manufacturers and users of three-phase flowmeters, are discussed.

https://iopscience.iop.org/article/10.1088/0957-0233/24/1/012003/pdf

Three-phase flow measurement in the petroleum industry

https://www.repository.cam.ac.uk/bitstream/handle/1810/246007/Coriolis-draft-paper-V8.1-FMI-Larger-Fonts.pdf?sequence=1

Coriolis flowmeters: a review of developments over the past 20 years, and an assessment of the state of the art and likely future directions

A method, system, apparatus (and related computer program) for intelligent management of oil and gas offshore and onshore platform surface equipment over a computer network is disclosed. The system utilizes a data aggregator for gathering real-time data streams from surface equipment located on such platform(s), such surface equipment containing one or more sensors for monitoring in real time the performance of equipment operational parameters of interest. The data analysis engine is in network communication with the data aggregator, and comprises a trained neural network capable of generating self organizing maps, and creating predictive operational parameters regarding such surface equipment. An interface is provided for inputting into the neural network various data including, for example, the published performance operational parameters for such equipment. A network user interface is also provided for transmitting such predictive operational input to one or more end user terminals equipped with end user dashboard display software.

Method, system and apparatus for intelligent management of oil and gas platform surface equipment

This research illustrates the utilization of a new model based on artificial neural networks (ANNs) in prediction of compressibility factor (z-factor) of natural gases using experimental data based on Standing and Katz z-factor diagram. Although equations of state and empirical correlations have been applied for predicting compressibility factor, the demands for the modern, more reliable and easy-to-use models encouraged the researchers to recommend modern facilities such as intelligent systems. This investigation describes a new technique for computing z-factor of natural gases. The base of the approach is ANN in which a 2:5:5:1 structure is used as an optimum network to predict the z-factor. The statistical results show that the developed ANN is an excellent tool for estimating z-factor values; therefore, it can be confidently used for natural gases with various compositions at a specific temperature and pressure.

An intelligent approach to predict gas compressibility factor using neural network model

Natural gas is a mixture of 21 components and it is widely used in industries and homes. Knowledge of its thermodynamic properties is essential for designing appropriate processes and equipment. This paper presents simple but precise correlations of how to compute important thermodynamic properties of natural gas. As measuring natural gas composition is costly and may not be effective for real time process, the correlations are developed based on measurable real time properties. The real time properties are temperature, pressure and specific gravity of the natural gas. Calculations with these correlations are compared with measured values. The validations show that the average absolute percent deviation (AAPD) for compressibility factor calculations is 0.674%, for density is 2.55%, for Joule-Thomson coefficient is 4.16%. Furthermore, in this work, new correlations are presented for computing thermal properties of natural gas such as enthalpy, internal energy and entropy. Due to the lack of experimental data for these properties, the validation is done for pure methane. The validation shows that AAPD is 1.31%, 1.56% and 0.4% for enthalpy, internal energy and entropy respectively. The comparisons show that the correlations could predict natural gas properties with an error that is acceptable for most engineering applications.

/pdf/developing-novel-correlations-for-calculating-natural-gas-524iwiek5f.pdf

Developing novel correlations for calculating natural gas thermodynamic properties

Systems, program product, and methods to estimate and manage flowing fluid characteristics of a fluid stream flowing through a pipeline in real-time, are provided. A system can include a vertically oriented extent of a pipeline for transporting crude oil, a pair of spaced vertically apart sensors or sensor assemblies connected to the vertically oriented extent to obtain pressure and temperature readings of the crude oil, a controller in communication with the pair of sensors or sensor assemblies, and crude oil analysis and management program product stored in the memory of the controller and adapted to determine or estimate density, specific gravity, and API gravity of the crude oil to thereby manage flowing fluid characteristics of the crude oil.

System, program product, and related methods for estimating and managing crude gravity in flowlines in real-time

Analysis of Interference Tests with Horizontal Wells

Systems, program product, and methods to estimate and manage flowing fluid characteristics of a fluid stream flowing through a pipeline in real-time, are provided. A system can include a vertically oriented extent of a pipeline for transporting crude oil, a pair of spaced vertically apart sensors or sensor assemblies connected to a bypass line interfaced with or positioned across the vertically oriented extent of the pipeline to obtain pressure and temperature readings of the crude oil flowing through the pipeline, a controller in communication with the pair of sensors or sensor assemblies, and crude oil analysis and management program product stored in the memory of the controller and adapted to determine or estimate density, specific gravity, and API gravity of the crude oil to thereby manage flowing fluid characteristics of the crude oil.

System, program product, and related methods for estimating and managing crude gravity in real-time

Interference Testing with Horizontal Observation Wells

The first practical coriolis mass flowmeter was introduced in 1977. Today, there are several manufacturers which offer various coriolis mass flowmeters with different sensing tube configurations and geometry. These meters continue to evolve, gain wide acceptance, and are used in the chemical, petroleum, food and beverage industries because of the several features that they posses over other types of flow measurement devices. This paper presents a performance evaluation of three types of coriolis mass flowmeters: U-tube, modified U-tube, and straight tube meters. These meters were individually tested in a compact multiphase test unit (WellComp) located in an onshore area of a field in Saudi Arabia. The test results obtained from these meters were compared with simultaneous data obtained from turbine meters installed in a conventional test separator.

Mohammed Najim Al-Khamis

Papers

System, program product, and related methods for estimating and managing crude gravity in flowlines in real-time

Analysis of Interference Tests with Horizontal Wells

System, program product, and related methods for estimating and managing crude gravity in real-time

Interference Testing with Horizontal Observation Wells

Performance evaluation of coriolis mass flowmeters