2.3 Gas Liquid Split Sampling and Metering Technology

The principle of gas-liquid split sampling and metering technology is to proportionally separate a small portion of a representative multiphase mixture (separated fluid) from the multiphase flow, then separate it into single-phase gas and liquid, measure the flow rates of each phase with a conventional flowmeter, and finally determine the total flow rate based on the proportional relationship. Due to the implementation of split sampling, the fluid to be processed only accounts for a small portion of the total flow rate, thus the volume of the required separator can be significantly reduced; At the same time, by separating and measuring, the flow measurement of multiphase fluids is converted into the flow measurement of single-phase fluids, fundamentally ensuring the stability, reliability, and measurement accuracy of the measuring instrument.Currently, various sampling structures have been developed, including space-based samplers such as sampling tubes and wall samplers, as well as time-based samplers such as rotary distributors.

The gas-liquid split sampling and metering technology has the following difficulties.①Unlike single-phase flow, gas-liquid two-phase mixtures usually undergo phase separation when passing through sampling devices, resulting in the loss of representativeness of the sampled fluid. ②The sampling ratio is difficult to maintain stability due to the influence of upstream flow patterns and downstream pressure fluctuations. ③Samplers with moving parts such as wheels are difficult to operate stably in harsh on-site conditions for a long time.

The gas-liquid split sampling and metering technology combines the high accuracy and stable performance of traditional complete separation metering methods with the advantages of small volume, simple and compact structure, and clear physical mechanism of non separation methods. It is a multiphase pipeline flow metering method with broad development prospects.

3. Research Progress on Virtual Measurement Technology for Pipeline Flow

3.1 Principles and Characteristics of Virtual Metrology Technology

Virtual Metering System (VMS) belongs to soft sensing methods. This technology was proposed as early as the 1990s and first applied to the measurement of oil and gas two-phase flow.Virtual metering technology does not use physical flow measurement equipment, but utilizes normal process signals on the pipeline system, such as pressure, temperature, and flow control valve opening degree, to invert the pipeline flow through an inference model, and can update the model parameters based on periodic calibration data.Therefore, virtual metering technology is essentially a predictive metering method based on mathematical models, which establishes a mapping relationship between input production parameters and oil and gas flow rates through mathematical models.

Compared with traditional physical flow meter measurement methods, virtual measurement technology does not require physical flow meters. It can be measured with the help of existing temperature, pressure difference, and pressure sensors in the production system, without the need for additional instrument investment. Adopting virtual measurement technology can save a lot of physical measurement equipment investment, with low cost, environmental protection, and safety;High work reliability and strong environmental adaptability, suitable for applications that are difficult to measure in practice, such as underwater measurement in deepwater oil and gas development; Suitable for multiple flow patterns, wide measurement range, and large range ratio. For example, in the field of multiphase pipeline flow measurement, the multiphase flow model suitable for the target oil and gas field can be modified based on the dynamic changes in production data, thereby expanding its applicability.

3.2 Implementation of Virtual Metrology Technology

There are two implementation methods for current virtual metrology technology: one is based on physical models, and the other is based on data-driven approaches.The physical mechanism embedding establishes a hydraulic and thermal multiphase flow model for the target pipeline, and uses the collected production data as feature input vectors to achieve flow prediction.However, data-driven methods do not require the establishment of models. Based on a large amount of production testing data, traffic mapping relationships can be established through machine learning algorithms. Common methods include K-Nearest Neighbor (KNN), Decision Tree, statistical analysis based linear regression, Support Vector Machine (SVM), and Artificial Neural Network (ANN).

In the field of single-phase pipeline flow measurement technology, European energy company E ON has developed the natural gas pipeline network simulation software SmartSim, which can simulate the operation status of the pipeline network and track the gas components in the pipeline network in real time, and then be used for energy metering. It has been widely used in Germany's Minkwitz pipeline network, Germany's Ferngas gas distribution pipeline network, Denmark's Fyn West pipeline network, Sweden's Malmö gas distribution pipeline network, and so on.China University of Petroleum (East China) has applied virtual metrology technology to the detection of mixed oil length in the sequential transportation of finished oil products. A fusion algorithm was constructed using a mixed oil physical model and Gaussian mixture regression algorithm, which achieved good results.

In the field of multiphase pipeline flow measurement technology, typical representatives include Shlumberger's OGLA Online system and FMC's Flow Manger module.China University of Petroleum (Beijing), together with CNOOC Research Institute and other units, conducted a study on flow soft measurement of two well production systems in offshore natural gas condensate gas fields. A data-driven flow and pressure dynamic estimation model was established, which integrates dynamic and steady-state samples. Black box identification technology based on deep learning and parameter correction technology based on transfer learning were used to establish a deep feedforward network model (DNN-NARX) library for estimating single well flow and wellhead pressure.

The virtual measurement technology has the following difficulties.

(1). The establishment of the mechanism model is complex, and the solution complexity is high.Figure 1 shows a typical virtual metering diagram of an underwater oil and gas production system. According to the principle of nodal analysis, there are three forms of flow from the bottom of the well to the oil production platform, namely seepage in the formation, multiphase flow in the wellbore and subsea pipeline, and multiphase flow at the nozzle, involving long processes, multiphase, and multi-scale, which are very complex and difficult to accurately model.As of the end of 2022, in the field of single-phase pipeline flow measurement technology, the total length of China's long-distance oil and gas pipelines has reached 15.5×10⁴ km, and the pattern of a "national network" of oil and gas pipelines has been formed.This large-scale oil and gas pipeline network involves multiple elements, strong nonlinearity, multiple functions, and complex interactions. It has extremely high requirements for the adaptability, accuracy, efficiency, stability, and fault tolerance of simulation models. The bottleneck problem of independent intellectual property rights in the core of simulation software is becoming increasingly prominent.

(2). High data accuracy, large data volume, and wide data range are required. The quality and quantity of data are crucial for traffic prediction.Usually, on-site data collection is noisy or even contaminated by human factors, and the normal production data has a narrow range of variation. The model has poor interpretability and weak generalization ability. It is particularly important to ensure that the data reflects the real physical processes while using feature engineering to screen traffic sensitive parameters and filling in missing data.Applying blockchain technology, using peer-to-peer (P2P) networks as communication carriers, pipeline traffic databases as data storage carriers, and cryptographic techniques such as asymmetric key mechanism signature verification and zero knowledge proof to determine ownership and ensure privacy, relying on distributed infrastructure and computing paradigms, will greatly enhance traffic data security and quality, providing guarantees for improving data-driven effects.

(3). The operating conditions of pipelines are constantly changing, and there are high requirements for updates and maintenance. During the operation of pipelines, changes may occur in the flow rate, fluid properties, surrounding environment, and even the structure of the pipeline network. The operating parameters may deviate from the learning conditions and require automatic calibration. We need to expand the dimensions of the model, form an open network system, regularly supplement fresh data, and achieve timely updates of the model and data.

4. Key Technologies and Challenges

4.1 Flow Measurement Technology under Extreme Parameters and Complex Environments

The traditional single-phase pipeline flow measurement technology is becoming increasingly mature, but new measurement demands and scenarios are constantly emerging. The measurement of extreme high pressure, high temperature, and low temperature scenarios poses challenges to the working range and response characteristics of traditional single-phase sensors.

For example, in the aerospace field, low-temperature fuels represented by liquid hydrogen, liquid oxygen, and liquid methane have become the preferred propellants for future space missions due to their high specific impulse, high thrust, non-toxic and pollution-free performance advantages. The critical temperature of methane is -161.5℃, while the saturation temperature of liquid hydrogen at atmospheric pressure is about -253℃, which is an extremely low temperature. In theory, as long as the conveying medium maintains a single-phase flow state, traditional single-phase flow meters can be used for measurement.Accurate measurement of physical parameters such as density, viscosity, and conductivity of media in extreme low temperature environments is necessary. Extreme low temperature environments impose strict requirements on the brittleness, sealing, and insulation of materials in contact with liquids, and there is an urgent need to develop new materials, low temperature sensors, and sealing equipment suitable for low temperature environments.For China's manned spaceflight technology, such as spacecraft thermal and fluid management systems, space stations, and deep space probes, there are various gravity field environments such as weightlessness, overweight, and microgravity during launch, return, and in orbit operation, which affect or alter the flow and heat transfer mechanisms and behaviors in pipelines, thereby affecting the accuracy of fluid measurement and even causing complete failure of flow meters.For example, in a microgravity environment, buoyancy convection, gravity settling and stratification, liquid static pressure, etc. are greatly reduced, and the secondary effects masked by ground gravity are highlighted. Traditional float flowmeters will not be able to work properly.

The current typical traffic measurement challenge scenarios are as follows. ①In ultra-high pressure scenarios, such as those above 40 MPa, Coriolis mass flow meters, ultrasonic flow meters, etc., the impact of high pressure on sensors. ②High temperature scenarios, new methods and technologies for measuring high-temperature water (primary and secondary circuits of nuclear power plants) and high-temperature steam flow. ③Measurement of flow rate of low-temperature media such as liquid hydrogen, liquid oxygen, and liquid methane in extremely low temperature scenarios. ④Measurement of flow rates for dirty medium environments, such as blast furnace gas, coke oven gas, and high coke mixed gas in the metallurgical industry. ⑤Dynamic measurement scenarios, transient flow measurement such as engine intake, and high-frequency flow sensing technology.

In addition, there are still challenges such as inability to measure, incomplete measurement, and inaccurate measurement. It is necessary to focus on key measurement and testing technologies, measurement methods, and the development of new flow sensors in special scenarios, in order to provide full scenario and full life cycle measurement and testing services for pipeline flow measurement.

4.2 Flow Measurement Technology for Multiphase Pipelines of Oil, Gas, and Water under Phase Change Conditions

Unlike single-phase pipeline flow, gas-liquid flow in pipelines presents various flow forms such as stratified flow, wave flow, slug flow, dispersed flow, and annular flow. The gas-liquid velocity is often inconsistent, resulting in velocity slip and mass and energy exchange between the gas-liquid phases.During the flow process, as the conveying temperature and pressure change, a phase transition occurs. When the pressure decreases, a portion of the associated gas precipitates from the oil phase, causing a change in flow pattern.When the temperature drops, crude oil undergoes wax crystal precipitation, and even causes wax deposition to block fluid channels. This requires multiphase pipeline flow measurement technology to have good real-time performance, be able to capture current flow interface information in a timely manner, and have good flow assurance without blockage.

4.3 Measurement System for Bulk Crude Oil Trade Handover

With the rapid growth of the Chinese economy, China's solid demand for crude oil is increasing day by day. The measurement standard system for crude oil trade handover mainly includes five major systems: International Organization for Standardization (ISO) standards, American Petroleum Institute (API) standards, American Society for Testing and Materials (ASTM) standards, Gosudarstvennyy Stand (GOST) standards, and Chinese National Standards (GB). The transfer and measurement of crude oil trade in Europe and North America are mostly based on ISO standards, API standards, and ASTM standards. The transfer measurement of China's pipeline crude oil trade mainly applies GB standards, China's national metrological verification regulations, and metrological technical specifications; The standards for oil measurement, dynamic measurement, and oil inspection methods are mainly converted to ISO standards; Static measurement standards are mainly converted using API standards.Due to different domestic and international standards, there are differences in calculating the net mass of crude oil between foreign and domestic sources. In addition, density and water content are two factors that have a significant impact on crude oil measurement during crude oil trade handover, and are usually determined through sampling analysis.Due to differences in sampling location, sampling tools, sampling methods, and analysis methods, there is a significant deviation in the moisture content measured by both trading parties. Therefore, it is necessary to reform the current crude oil measurement system and establish an advanced oil measurement handover standard that is both in line with international standards and suitable for national conditions.