Introduction

One of the ongoing challenges in oil and gas production is accurately measuring multiphase flow rates. This complexity arises because traditional single-phase flow meters struggle when gas, oil, and water coexist within the same pipeline1. Multiphase Flowmeters (MPFMs) have revolutionized the industry by providing a more robust solution tailored for such mixed-phase scenarios. Unlike conventional meters, MPFMs are designed to handle simultaneous flow of multiple phases and provide accurate, real-time measurements of each component2. This innovation improves measurement accuracy and operational efficiency by leveraging advances in sensor technology, data processing algorithms, and materials engineering. These improvements not only optimize resource management and production strategies but also lower operational costs. Specifically, MPFMs eliminate the need for large and expensive separation facilities, minimize equipment footprint, and reduce the frequency of maintenance—benefits particularly critical for Normally Unmanned Facilities (NUFs).

Several field studies have reported that replacing traditional test separators and wet gas meters with MPFMs can result in capital expenditure (CAPEX) reductions of up to 30–40% and operational expenditure (OPEX) savings of 20–25% over the equipment life cycle3. These savings stem from the elimination of large separation infrastructure, lower installation costs, reduced deck space requirements, and decreased need for manual intervention in Normally Unmanned Facilities (NUFs). For example, in offshore settings, the cost of installing and operating a three-phase test separator system can exceed $500,000 USD, while compact MPFMs may cost less than half that amount and require minimal ongoing servicing.

Moreover, MPFM systems contribute to environmental sustainability by reducing emissions associated with separation processes and enabling more compact, energy-efficient offshore platforms4. Their ability to deliver continuous, accurate flow data enables better reservoir management and ensures compliance with increasingly stringent environmental regulations. As the industry moves toward digitalisation and automation, MPFMs play a key role in integrating with advanced monitoring and control systems. This allows operators to detect anomalies early, fine-tune production in real time, and respond rapidly to dynamic field conditions. Ultimately, MPFM adoption supports safer, more efficient, and environmentally responsible oil and gas production.

The versatility of multiphase flowmeters (MPFMs) extends beyond their core function of accurately measuring flow rates in multiphase environments. These sophisticated tools optimize the operational and design performance of oil and gas facilities by enabling real-time detection of abnormal flow conditions, supporting valve actuation optimization, and providing actionable data for adjusting production parameters on the fly. By providing detailed and actionable insights into fluid behavior and composition, MPFMs empower operators to fine-tune production processes with precision5. This optimization results in substantial operational advantages, such as adjusting flow rates and production parameters in real time, enhancing system responsiveness and efficiency. Furthermore, MPFMs facilitate early detection of anomalies and potential pipeline issues, minimizing downtime through proactive maintenance and troubleshooting6. This capability is essential for maintaining uninterrupted production and avoiding costly shutdowns. Additionally, the accurate data provided by MPFMs supports maximum resource recovery, ensuring efficient and thorough extraction processes.

Adopting MPFM technology also aligns closely with the industry’s emphasis on sustainability and environmental responsibility. As the energy sector faces growing pressure to reduce its environmental impact, the precise measurement of multiphase flows becomes crucial for effective reservoir management7. By delivering accurate data, MPFMs enable operators to optimise extraction processes, reducing waste and minimising emissions. This capability is vital for complying with strict environmental regulations and fostering sustainable practices across the industry. Enhanced operational efficiency through waste reduction and emission control further underscores the role of MPFMs in achieving the industry’s sustainability objectives, reflecting a commitment to environmental stewardship.

This study aims to evaluate and improve the efficiency of MPFM technology in offshore oil and gas production environments with high gas volume fractions (GVF). Specifically, it will assess the accuracy and reliability of MPFMs in measuring multiphase flows under these conditions, ensuring compliance with industry standards for precision. The research also analyses the cost-effectiveness of using MPFMs in typically unmanned facilities (NUFs), comparing potential cost savings to traditional wet gas meters and highlighting their financial benefits. Additionally, the study will explore the operational advantages of MPFMs on offshore platforms, focusing on their compatibility with lightweight structures, reduced maintenance needs, and enhanced real-time data acquisition. Proposed optimisations in MPFM design, calibration, and data processing will address existing challenges, aiming to improve measurement accuracy and operational performance. Lastly, the research will evaluate the environmental impact of MPFM technology, examining how precise multiphase flow measurement can promote sustainability and minimise the environmental footprint of offshore oil and gas operations.

Literature reviews

Multiphase flowmeters in wet gas fields

Multiphase flowmeters (MPFMs) play a vital role in measuring the flow rates of oil, gas, and water phases in wet gas fields (Ng et al., 2023). These fields, characterized by high gas volume fractions (GVF), present significant challenges for accurate flow measurement and operational management. Traditional wet gas meters, typically designed for conditions with a Lockhart-Martinelli parameter of ≤ 0.3, often fall short of meeting modern offshore operations’high accuracy and reliability requirements8.

The evolution of MPFM technology over the decades has transformed these devices from basic measuring tools into advanced systems—such as those incorporating gamma-ray densitometry or electrical capacitance tomography—that can accurately handle the dynamic behavior of high-GVF multiphase flows. Early MPFMs, which heavily relied on empirical correlations and assumptions, were often inadequate for the highly variable conditions in wet gas fields9. However, advancements in sensors, computational algorithms, and real-time data processing have significantly enhanced accuracy and reliability in modern designs10. Comprehensive reviews such as11 have highlighted this evolution, comparing early-generation MPFMs to current high-performance systems and identifying the performance benchmarks now used in offshore applications.

Recent technological developments have introduced advanced techniques such as phase fraction analysis, which leverages differential pressure and dielectric constant measurements to improve the accuracy of phase separation12. Additionally, gamma-ray densitometry and electrical capacitance tomography have been instrumental in enhancing the precision of multiphase flow measurements, solidifying MPFMs as indispensable tools in offshore oil and gas production11. The integration of machine learning algorithms into MPFMs has further refined flow measurement by dynamically adapting to changing field conditions, reducing errors, and improving predictive accuracy.

Challenges in measuring high GVF conditions

Despite significant technological advancements, accurately measuring multiphase flows in high-GVF conditions remains challenging. A key issue is phase slip, where the differing velocities of gas and liquid phases result in inaccurate flow rate calculations13. This challenge is further exacerbated by the fluctuating composition of the phases, which complicates precise flow measurements. Moreover, the presence of entrained water droplets in gas streams often leads to misinterpretations of flow dynamics, adversely affecting the accuracy of MPFMs14.

Calibration and maintenance of MPFM systems present additional hurdles. Calibration must accommodate various flow regimes, ranging from stratified to annular flow patterns, requiring advanced techniques and frequent updates to ensure measurement accuracy15. Offshore environments pose further difficulties, with extreme conditions such as high pressure, temperature fluctuations, and exposure to corrosive substances impacting the performance and lifespan of MPFMs. These challenges necessitate the development of robust designs and durable materials capable of withstanding such harsh conditions.

Advantages of MPFMs in offshore platforms

A key advantage of MPFMs is their compatibility with lightweight structures. Unlike traditional wet gas meters, which often require heavy and robust infrastructure to function making them costly and impractical for NUFs16, MPFMs are designed to integrate into lighter, more adaptable structures. This reduces the overall weight and complexity of the facility17. Such compatibility not only simplifies installation but also decreases the structural demands on the platform, resulting in substantial cost savings in construction and maintenance.

Another significant benefit of MPFMs is their ability to reduce operational costs. Traditional wet gas meters require frequent maintenance and calibration, which can be expensive and time-consuming. In contrast, MPFMs are engineered for low maintenance and high reliability, minimizing the need for regular servicing. This reduced maintenance demand leads to lower operational costs, less downtime, and enhanced overall efficiency and profitability in offshore operations.

Performance evaluation of MPFMs

Evaluating the performance of Multiphase Flow Meters (MPFMs) involves analyzing their accuracy, reliability, and efficiency in measuring the flow rates of oil, gas, and water within production streams. This assessment is essential for determining how effectively MPFMs operate under varying conditions and their suitability for specific applications, such as offshore oil and gas platforms or typically unmanned facilities (NUFs).

Accuracy and precision are critical performance evaluation components18. Accuracy measures how closely MPFM readings align with actual flow rates, which is vital for optimizing production, managing reservoirs, and meeting regulatory requirements. Precision, on the other hand, reflects the consistency of measurements under identical conditions. Even if an MPFM is highly accurate, it must also deliver consistent readings to be deemed reliable19.

Response time is another key factor, especially in dynamic production environments where flow rates can change rapidly. MPFMs must quickly adapt to such variations to maintain measurement accuracy20. Durability and low maintenance are also critical, particularly in challenging conditions like extreme temperatures, high pressures, and corrosive environments common to offshore platforms. Low maintenance requirements reduce operational costs and minimize downtime.

Operational cost savings are a significant aspect of MPFM performance. These devices help lower costs by reducing maintenance needs, minimizing production downtime, and providing accurate data to improve production efficiency. Their compatibility with lightweight structures is especially beneficial for NUFs and offshore platforms, as it reduces overall weight and structural complexity, leading to considerable savings in construction and maintenance.

Calibration and adaptability are also vital considerations. MPFMs should require minimal calibration and be capable of adapting to different flow conditions and fluid compositions to ensure long-term accuracy and reliability across diverse operational scenarios21. The ultimate measure of an MPFM’s performance is its validation through field testing. Deploying MPFMs in real-world conditions and comparing their measurements to established techniques is essential for ensuring confidence in their accuracy, reliability, and operational efficiency.

Importance of the study

This study holds significant importance for several key reasons. Firstly, operational efficiency is critical in offshore oil and gas production, particularly in wet gas fields where precise and efficient measurement technologies are indispensable. This research aims to evaluate and optimise MPFM technology to address existing limitations and enhance operational performance. Secondly, cost reduction is a major motivation for utilising MPFMs in normally unmanned facilities (NUFs). Minimising structural weight and reducing operational costs are essential priorities. By validating the suitability of MPFMs in high-GVF conditions, this study could pave the way for more cost-effective designs and operations on offshore platforms.

Thirdly, access to accurate real-time data on multiphase flow rates is vital for informed decision-making. The study’s evaluation of MPFM performance can improve operational strategies, optimise production processes, and enhance resource management. Real-time data ensures efficiency and maximises productivity across offshore operations. Additionally, this research contributes to advancing MPFM design, calibration, and data processing technologies. The study pushes the boundaries of flow measurement technology by addressing existing challenges and proposing innovative solutions. These advancements refine current practices and create a foundation for future innovations in the field.

While prior studies have examined MPFM functionality in multiphase flow conditions, few have rigorously validated their performance under blind testing scenarios with high GVF ranges (up to 99.5%) and across diverse flow conditions. This study addresses that gap by offering empirical performance benchmarking—aligned with ISO/API acceptance thresholds—using a third-party, controlled test environment. Moreover, the analysis connects MPFM accuracy with real-world operational considerations for Normally Unmanned Facilities (NUFs), providing practical deployment insights. Unlike general discussions in previous literature, this work links specific measurement deviations to likely mechanical and signal-processing limitations, offering a foundation for targeted sensor and algorithmic optimization in future MPFM development.

Finally, improved measurement accuracy has broader implications for resource management and environmental sustainability. Accurate flow measurements ensure efficient resource utilization, minimize waste, and aid in monitoring and controlling emissions. Consequently, this study has the potential to significantly enhance operational efficiency while promoting environmentally sustainable practices in offshore oil and gas production.

Methodology

The test was conducted at 64 points, including 13 blind test points, where the manufacturer had no prior knowledge of the specific conditions under which the meter would be evaluated. This approach ensured an unbiased assessment of the meter’s performance. The meter was provided with a performance curve, and the company needed to verify that the meter functioned according to its design specifications. To maintain data integrity during testing, no personnel from the manufacturer were allowed access to the testing facility or control room. Although the manufacturer could configure their MPFM software before blind testing, they were prohibited from making any alterations once the testing had started.

Table 1 presents a detailed overview of the fluid and metering variables tested within specific ranges. For gas volumetric flow, the range tested spans from 48,172 to 564,029 standard cubic meters per day (SM3/D). This testing was conducted using an upstream pipe with a diameter of 4 inches. Liquid volumetric flow rates were tested from 0 to 238 SM3/D, while gas volume fraction (GVF) was assessed within a range of 78.6% to 99.5%. Oil volumetric flow varied from 0 to 225 SM3/D, and the corresponding liquid volume fraction (LVF) was tested between 0.5% and 21.4%. Water volumetric flow rates were examined from 0 to 37 SM3/D, with water-cut (WC) percentages ranging from 5.4% to 21.1%. These parameters and ranges provide a comprehensive framework for understanding fluid metering systems’variability and performance metrics. These parameter ranges in Table 1 were selected to simulate realistic offshore production conditions, particularly in high-GVF environments typically encountered in gas-dominant fields. The tested values reflect operational envelopes observed in Normally Unmanned Facilities (NUFs) and other offshore platforms, ensuring that the evaluation of the MPFM reflects field-representative challenges.

Table 1 MPFM wet gas tested range.
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These parameters were meticulously chosen to cover the full operational range of the MPFM and rigorously evaluate its performance under various flow conditions. By adhering to these stringent testing methods, the company aimed to ensure that the MPFM would deliver reliable and accurate measurements in real-world applications. The testing was carried out at an accredited third-party facility, with precise reference mass flowrate uncertainties for gas (± 0.33%), oil (± 0.2%), and water (± 0.2%). The test configuration is illustrated in Fig. 1, which depicts the closed-loop wet gas circulation system used for meter evaluation. This includes the injection points for oil and water, the Meter Under Test (MUT), and downstream separators, compressors, and measurement instruments.The diagram, combined with the additional context, provides a detailed overview of the circulation of natural gas within a closed-loop system in a third-party laboratory, along with the injection of oil and water/saltwater upstream of the Meter-Under-Test (MUT). The fluid enters the system through the MUT, where its performance and accuracy are evaluated. It then flows into an oversized three-stage gas–liquid separator equipped with 8-foot-long 2-micron filtering elements to separate the gas from the liquid components. The separated gas flows through a series of natural gas compressors to maintain pressure and flow before being directed to a heat exchanger for temperature control. The liquid portion, directed into an oversized oil–water separator, is further separated into oil and water. To minimize emulsions, oil and water are pumped separately and supplemented by special de-emulsification bottles.

Fig. 1
figure 1

Schematic drawing of the multiphase wet gas flow facility used for testing. The system includes gas injection, oil/water injection, the Meter Under Test (MUT), and downstream separation and measurement infrastructure.Schematic drawing of multiphase wet gas flow facility.

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The separated water flows through water pumps to Coriolis meters for accurate flow measurement, while the oil follows a similar path through oil pumps to its respective Coriolis meters. Various flow paths and control valves manage the fluid flow throughout the system, with pressure and temperature sensors monitoring conditions at critical points. The facility features over 100 instruments meticulously measuring pressures, temperatures, liquid levels, and other critical parameters to ensure precise reporting of gas, oil, and water/saltwater flow rates.

Additionally, ultrasonic and turbine meters further measure and validate flow rates at different stages. The gas exiting the heat exchanger is collected at designated gas collection points. This comprehensive setup ensures precise measurement and separation of gas, oil, and water, facilitating accurate data collection and system efficiency during the testing and metering. The extensive testing spanned two days, covering all 13 selected blind points. Before testing, the manufacturer was responsible for commissioning the MUT and verifying its functionality. Third-party laboratory personnel recorded MUT memory registers and averaged the values across test points. Ultimately, the meter manufacturer was responsible for ensuring the validity of the MUT output, as presented in the report.

Acceptance criteria

The third-party laboratory’s data acquisition system recorded the multiphase flow meter (MPFM) output and compared to the laboratory reference meters. The differences between the MPFM readings and the reference meters were calculated. These differences were then compared to the agreed acceptance criteria, which is defined as 2% of full scale plus 5% of the rate. This criterion means that for any given flowrate measurement, the allowable deviation from the reference value is calculated as:

$${\text{Allowed}} {\text{Error}}\, = \,\left( {0.0{2}\, \times \,{\text{Full}} {\text{Scale}} {\text{Value}}} \right)\, + \,\left( {0.0{5}\, \times \,{\text{Measured}} {\text{Rate}}} \right)$$
(1)

For example, if the full scale for gas flowrate is 5000 Am3/day and the measured flowrate is 3000 Am3/day, the maximum acceptable error would be:

$$\left( {0.0{2}\, \times \,{5}000} \right)\, + \,\left( {0.0{5}\, \times \,{3}000} \right)\, = \,{1}00\, + \,{15}0\, = \,{25}0{\text{Am}}^{{3}} /{\text{day}}$$
(2)

Therefore, any measured value that deviates from the reference by more than ± 250 Am3/day would be considered outside the acceptable limit. This approach balances a fixed full-scale margin with proportional flexibility at various flow rates, ensuring that performance is fairly assessed across different operating conditions.

To ensure fairness, the third-party laboratory incorporates the additional uncertainty of its reference measurements (including random error) into the acceptance criteria using quadrature addition. This practice prevents the meter under test (MUT) from being unfairly penalised due to uncertainties in the reference meter. For instance, if the acceptance criteria for the meter is 5% and the reference meter has an expanded uncertainty of 3%, the combined pass/fail acceptance criteria would be calculated as follows: During testing, it was noted that the MPFM MUT actuated control valves behaved in a choking flow manner to maintain the liquid level in its centrifugal compact separator vessel. The liquid was released by suddenly opening the control valves, which allowed the measurement of the accumulated liquid. This sudden opening and closing of the valves introduced random error to the laboratory reference gas meters over the test duration. Multiple reference meters were used to reduce the random error caused by this, and their measurements were combined using a statistical method called the Pooled Standard Deviation of Two Independent Samples. The following Eq. 3 for Pooled Standard Deviation of Two Independent Samples was used:

$$\begin{gathered} {\text{Combine acceptance criteria}}{\kern 1pt} = {\kern 1pt} \sqrt {5^{2} + 3^{2} } \, = {\kern 1pt} 5.8 \hfill \\ \sqrt {\frac{{\left( {n_{1} \, - 1} \right)s_{1}^{2} \, + \left( {n_{2} \, - 1} \right)s_{2}^{2} }}{{\left( {n_{1} \, + n_{2} - 2} \right)}}} \hfill \\ SE\left( {\overline{Y}_{2} - \overline{Y}_{1} } \right)\, = \,S_{p} \sqrt {\frac{1}{{n_{1} }} + \frac{1}{{n_{2} }}} \hfill \\ \end{gathered}$$
(3)

Where:

\({S}_{p}\) = pooled estimate of standard deviation (the pooled Standard Deviation)

\(SE\left({\overline{Y} }_{2}- \overline{{Y }_{1}}\right)\) = Standard Error for the difference

\({n}_{1}={n}_{2}\) = number of samples

The pooled standard deviation is then used to derive the combined acceptance criteria, incorporating both systematic and random error. This ensures that the performance of the Meter Under Test (MUT) is evaluated fairly against reference meters with known uncertainty levels.

Results

The multiphase flowmeter (MPFM) was tested against independent third-party laboratory reference meters. The third-party laboratory’s data acquisition system recorded the MPFM’s output. The results were then calculated and documented according to the approved procedures and acceptance criteria, defined as 2% of full scale plus 5% of the rate. Refer to Table 2 below for the percentage of passing points for the MPFM. This table presents the performance of the multiphase flowmeter (MPFM) across various metering variables. The acceptance criteria for each variable is set at 2% of full scale plus 5% of the rate. For the liquid standard volumetric flowrate, 6 points fell within the acceptance criteria, resulting in 46% of points passing. For the gas standard volumetric flowrate, all 13 points met the criteria, yielding a 100% pass rate. For the water-liquid ratio (WLR), 5 points were within the criteria, corresponding to a 45% pass rate.

Table 2 MPFM MUT percentage of points passing procedure accuracy acceptance criteria.
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In practical field deployment, a metering system is generally considered acceptable when it consistently meets the defined acceptance criteria—2% of full scale plus 5% of rate—for at least 80–90% of operating conditions across critical flow parameters such as gas and total volumetric flowrates. Based on this threshold, the MPFM demonstrated field-deployable performance for gas measurement (100% pass rate), while liquid and WLR results indicate the need for calibration improvements before broader application.

Out of the 13 blind points tested, 46% met the liquid standard volumetric flowrate acceptance criteria, demonstrating moderate accuracy in this parameter, with observed relative errors ranging up to approximately ± 10–15% at lower flowrates, where measurement deviations were most pronounced. The gas standard volumetric flowrate acceptance criteria were fully satisfied, with 100% of the points passing, indicating excellent performance in measuring gas flowrate. Additionally, 92% of the points conformed to the gas actual volumetric flowrate acceptance criteria, reflecting high accuracy in actual gas flowrate measurements. However, only 45% of the points passed the Water-Liquid Ratio (WLR) and Water-Cut (WC) acceptance criteria, suggesting a need for improvement in these areas. This comprehensive evaluation highlights both the strengths and potential areas for enhancement in the multiphase flowmeter’s (MPFM) performance, providing valuable insights for improving its accuracy and reliability across various fluid measurement parameters.

Comparison of MUT reported total actual volumetric flowrate vs. laboratory reference meter actual volumetric flowrate

Figure. 2 compares the total volumetric flow rate reported by a Meter Under Test (MUT) with the actual volumetric flow rate measured by a laboratory reference meter, represented on a scatter plot where the x-axis indicates the reference flow rate (Am3/day) and the y-axis shows the MUT-reported flow rate (Am3/day). Each data point corresponds to a pair of measurements, illustrating the relationship between the two sets of values. A dashed 45-degree line signifies perfect agreement, where the MUT’s reported flow rate would match the reference meter’s measurements exactly. The clustering of data points around this line suggests a strong correlation, although some deviations, particularly at higher flow rates, indicate minor discrepancies between the MUT and reference measurements, thus highlighting the overall accuracy and reliability of the MUT.

Fig. 2
figure 2

MUT reported total actual volumetric flowrate vs. Laboratory reference meter actual volumetric flowrate.

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The results provided in Fig. 1 visual comparison between the volumetric flowrate measurements of a Meter Under Test (MUT) and those obtained from a laboratory reference meter. The close clustering of data points around the 45-degree line, representing perfect agreement between the two measurements, indicates a strong positive correlation and suggests that the MUT generally provides accurate readings. However, some deviations, especially at higher flowrates, highlight instances where the MUT either overestimates or underestimates the flowrate compared to the reference meter.

This discrepancy at higher flowrates could be due to several factors such as limitations in the MUT’s measurement capabilities, calibration errors, or environmental conditions affecting the readings. The deviations, although relatively small, are important to consider as they may impact the reliability of the MUT in applications requiring high precision.

In practical terms, while the MUT demonstrates overall accuracy and can be considered reliable for most measurements, further calibration or adjustments may be necessary to improve its performance, particularly in high flowrate scenarios. Additional testing under varied conditions and with different flow rate ranges could help understand and mitigate these discrepancies. This analysis underscores the importance of continuous validation and calibration of measurement instruments to ensure their accuracy and reliability in different operational contexts.

MUT total actual volumetric flowrate error (Relative %) vs. total actual volumetric flowrate

The Fig. 3 presents a scatter plot that visualizes the relative error in the total actual volumetric flow rate reported by a Meter Under Test (MUT) compared to the actual volumetric flow rate measured. The x-axis represents the total actual volumetric flow rate (Am3/day), while the y-axis shows the relative deviation in the reported flow rate as a percentage.

Fig. 3
figure 3

MUT total actual volumetric flowrate error (Relative %) vs. Total actual volumetric flowrate.

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Each data point on the plot corresponds to a specific flow rate measurement, with green circles indicating gas data that passes the acceptance criteria and red triangles representing data that fails the acceptance criteria. The plot includes two dashed lines depicting error criteria: one at ± 1.913% (400 psi) and another at ± 0.625% (740 psi). These criteria lines serve as benchmarks to evaluate whether the MUT’s measurements fall within acceptable error margins. The majority of the data points fall within the acceptance criteria boundaries, indicating that most of the MUT’s measurements are within the acceptable error range. However, some points lie outside these boundaries, highlighting instances where the MUT’s reported flowrate deviates beyond the permissible limits. This error distribution provides insights into the accuracy and reliability of the MUT across different flow rate ranges and conditions. Overall, this figure is critical for assessing the MUT’s performance, demonstrating its accuracy within specified limits, and identifying areas where further calibration may be necessary to enhance measurement precision.

MUT gas actual volumetric flowrate error (Relative %) vs. gas actual volumetric flowrate

Figure. 4 displays a scatter plot that illustrates the relative error in the gas actual volumetric flowrate reported by a Meter Under Test (MUT) compared to the actual gas volumetric flowrate measured. The x-axis represents the gas actual volumetric flowrate (Am3/day), while the y-axis represents the relative deviation in the reported flowrate as a percentage.

Fig. 4
figure 4

MUT gas actual volumetric flowrate error (Relative %) vs. Gas actual volumetric flowrate.

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Each data point signifies a measurement of relative error corresponding to a specific flowrate. Green circles indicate gas data that passes the acceptance criteria, while red triangles represent data that fails the criteria. The plot includes two sets of dashed lines depicting error criteria: one at ± 1.913% (400 psi) and another at ± 0.625% (740 psi). These criteria lines serve as benchmarks to assess whether the MUT’s measurements fall within acceptable error margins.

The majority of the data points fall within the acceptance criteria boundaries, suggesting that most MUT measurements are within the acceptable error range. However, a few points lie outside these boundaries, indicating instances where the MUT’s reported flowrate deviates beyond the permissible limits. This distribution of error provides insights into the accuracy and reliability of the MUT across different flowrate ranges and conditions. This figure is essential for evaluating the MUT’s performance, showing how well it maintains accuracy within specified limits, and identifying areas where further calibration may be necessary to enhance measurement precision.

Analysis of MUT liquid actual volumetric flowrate error: Evaluation of measurement accuracy across various flow conditions

The graph in Fig. 5 presents the relationship between the MUT Liquid Actual Volumetric Flowrate Error (expressed as a Relative %) and the Liquid Actual Volumetric Flowrate (measured in Am3/day). This analysis is crucial for understanding the accuracy of flow measurements under varying flow conditions. The x-axis of the graph represents the Liquid Actual Volumetric Flowrate, ranging from 0 to 300 Am3/day, indicating different flow conditions being tested. The y-axis displays the Relative Deviation (%), measuring the percentage error between the measured and actual flowrate, scaled from −15% to 15%.

Fig. 5
figure 5

MUT liquid actual volumetric flowrate error (Relative %) vs. Liquid actual volumetric flowrate.

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The data points on the graph are color-coded for clarity: green circles represent data points that have passed the acceptance criteria for flowrate measurement accuracy, indicating they fall within a predefined acceptable error range. In contrast, red triangles highlight data points that have failed the acceptance criteria, suggesting significant deviations from the actual flowrate. The two horizontal black lines, labelled as Error Criteria, delineate the boundaries for acceptable error levels. Data points within this range are considered accurate, while those outside indicate poor measurement performance. A curve passing through the data points illustrates the trend of relative deviation as the actual flowrate changes, revealing a non-linear relationship where error deviations are more pronounced at lower flowrates.

A consistent trend of systematic deviation was observed at low liquid flowrates (0–50 Am3/day), where a significant portion of the data points exceeded the acceptable error range. This indicates a recurring measurement bias or sensitivity limitation in the MPFM when operating under low-flow liquid conditions, requiring further calibration refinement. However, as the flowrate increases beyond 100 Am3/day, the data points converge within the acceptance criteria, indicating improved measurement accuracy. The majority of these points lie within the acceptable range, demonstrating the reliable performance of the measurement system at higher flowrates. The systematic pattern of errors, particularly at lower flowrates, hints at potential calibration issues with the flow measurement device (MUT), necessitating recalibration or adjustment to enhance performance across all flow conditions.

In conclusion, this graph is a critical tool for evaluating the performance of the MUT (Meter Under Test) in measuring liquid volumetric flowrates. The presence of outliers and systematic errors at specific flow conditions indicates the need for further investigation into the device’s calibration and potential adjustments to ensure accuracy and reliability across all operating conditions. Understanding these trends allows engineers and researchers to make informed decisions to enhance measurement systems, ensuring they meet industry standards and provide accurate data essential for process optimization and control.

Evaluation of MUT oil actual volumetric flowrate error: Measurement accuracy across varying flow conditions

The graph in Fig. 6 presents a detailed analysis of the relationship between Oil Actual Volumetric Flowrate Error, expressed as a Relative %, and the Oil Actual Volumetric Flowrate, measured in Am3/day. This analysis is essential for understanding the accuracy of the measurement system (MUT) for oil flowrates under various operational conditions. The x-axis of the graph represents the Oil Actual Volumetric Flowrate, ranging from 0 to 300 Am3/day, encompassing different flow conditions. The y-axis shows the Relative Deviation (%), which quantifies the percentage error between the measured and actual oil flowrate, scaled from −150% to 150%.

Fig. 6
figure 6

MUT oil actual volumetric flowrate error (Relative %) vs. Oil actual volumetric flowrate.

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The data points in the graph are distinguished by color and shape: green circles denote data points that meet the acceptance criteria for flowrate measurement accuracy, indicating they lie within the accepted error threshold. Conversely, red triangles represent data points exceeding the acceptance criteria, suggesting significant deviations from the flowrate. Two horizontal black lines indicate the Error Criteria for oil flow, defining the acceptable range of deviation. Data points outside this range suggest inaccuracies in the measurement system. The curve fitting through the data points shows the trend of relative deviation as the actual flowrate changes, revealing a non-linear relationship where error deviations are more pronounced at lower flowrates, underscoring potential challenges in measurement accuracy at these levels.

The elevated relative errors observed at low liquid flowrates are likely due to phase slip and reduced signal-to-noise ratios. In high-GVF conditions, the liquid phase moves slower than the gas phase and may be unevenly distributed (e.g., as film or slugs), making it difficult for the sensor to consistently detect and quantify the liquid component. These conditions degrade the accuracy of standard calibration curves and signal interpretation, leading to systematic under- or over-estimation.

From the graph, several key observations can be made. At lower flow rates (0–50 Am3/day), the graph indicates significant error deviations, with numerous data points failing to meet the acceptance criteria, suggesting the measurement system struggles to maintain accuracy at lower oil flow conditions. As the flow rate increases to moderate levels (50–200 Am3/day), the deviation remains notable, with a mix of passing and failing data points, indicating variability in measurement accuracy that could be attributed to specific flow characteristics or calibration issues with the device. At higher flow rates, beyond 200 Am3/day, a slight convergence of data points towards the acceptance criteria suggests improved accuracy. For oil measurements, significant deviations at low to moderate flow rates may result from difficulty distinguishing oil from water and gas under low-conductivity and high-velocity flow regimes. Additionally, sensor performance can degrade when oil volume is low relative to gas, increasing uncertainty due to incomplete phase resolution or electrical property overlap with water phases. This contributes to the inconsistent accuracy seen in this flow range.

However, several data points still fail to meet the criteria, indicating that there is room for further improvement in the system’s calibration or device performance. The systematic pattern of errors across different flow rates suggests potential calibration issues with the MUT (Meter Under Test) or inherent limitations of the measurement device when handling varying oil flow conditions. This necessitates further investigation and potential recalibration to ensure accuracy across all flow levels.

This graph is a vital tool for assessing the performance of the MUT in measuring oil volumetric flow rates. The presence of significant deviations, particularly at low and moderate flow rates, indicates a need for closer scrutiny of the measurement device’s calibration and operational settings to enhance accuracy and reliability. Understanding these trends is crucial for engineers and researchers aiming to optimize measurement systems, ensuring they comply with industry standards and provide precise data for effective process management and optimization.

Analysis of MUT water actual volumetric flowrate error: Assessing measurement accuracy across various flow conditions

The graph in Fig. 7 illustrates the relationship between the Water Actual Volumetric Flowrate Error, expressed as a Relative %, and the Water Actual Volumetric Flowrate, measured in Am3/day. This graph serves as a crucial tool for evaluating the performance of the Meter Under Test (MUT) in accurately measuring water flowrates under different conditions. The x-axis of the graph represents the Water Actual Volumetric Flowrate, which ranges from 0 to 50 Am3/day, capturing a range of flow conditions. The y-axis indicates the Relative Deviation (%), measuring the percentage error between the measured and actual water flowrate, scaled from −150% to 100%. The data points on the graph are categorized by color and shape for clarity: green circles signify data points that have passed the acceptance criteria for flowrate measurement accuracy, indicating they lie within the acceptable error range. Red triangles, on the other hand, denote data points that fail to meet the acceptance criteria, suggesting significant deviations from the actual flow rate. Two black lines represent the Error Criteria for water flow, delineating the boundary of acceptable deviation. Data points outside these boundaries indicate inaccuracies in the measurement system.

Fig. 7
figure 7

MUT water actual volumetric flowrate error (Relative %) vs. Water actual volumetric flowrate.

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A curve is drawn through the data points, showing the trend of relative deviation as the actual flowrate changes. This curve exhibits a non-linear relationship, where the errors are more pronounced at lower flowrates, highlighting potential challenges in measurement accuracy at these levels. From the graph, several key observations can be noted. At low flowrates (0–10 Am3/day), there are noticeable error deviations, with several data points failing to meet the acceptance criteria. This indicates that the measurement system may struggle with accuracy at these lower flow conditions. However, as the flow rate increases to a moderate range (10–30 Am3/day), the data points generally fall within the acceptance criteria, demonstrating improved measurement accuracy. This suggests that the system performs more reliably at these moderate flow conditions, though some variability is still present. At higher flow rates (above 30 Am3/day), the data points again begin to exhibit more significant deviations, with a number of them falling outside the acceptable range. This pattern indicates that the measuring device may have difficulties maintaining accuracy at higher water flowrates, potentially due to signal attenuation caused by increased water content, limited phase separation resolution, or sensor lag under high-volume transient conditions, which are known challenges in multiphase metering (Karami et al., 2017; Amir Sattari et al., 2021).

The systematic pattern of errors across varying flow rates suggests potential calibration issues with the MUT (Meter Under Test) or limitations of the measurement device. This calls for further investigation and possible recalibration to enhance performance across all flow conditions. Understanding these trends is crucial for engineers and researchers seeking to optimize measurement systems, ensuring they meet industry standards and provide accurate data for process management and control.

This graph provides essential insights into the performance of the MUT in measuring water volumetric flowrates. The presence of deviations, particularly at low and high flowrates, underscores the need for careful calibration and potential adjustments to improve measurement accuracy and reliability. By analyzing these trends, professionals can make informed decisions to enhance the functionality and precision of their measurement systems, ensuring they deliver reliable data essential for effective operational management and optimization.

Summary of the result

Table 3 summarises the key observations and performance metrics for the Multiphase Flow Meter (MPFM) as compared to the reference data as displayed in Fig. 2 to Fig. 7. Here is a table summarising these key points for the blind test:

Table 3 Summarisation of the key performance metrics.
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The evaluation of Multiphase Flowmeter (MPFM) performance across various flow types in high gas volume fraction conditions presents a nuanced picture of its capabilities and limitations. The results show that MPFM demonstrates excellent accuracy for total volume flow, with nearly all data points adhering to the error criteria of ± 2.25% for 440 psi and ± 2.625% for 740 psi, indicating high reliability in measuring total flow rates. Similarly, gas volume flow measurements are highly reliable, as the majority of data points fall within the acceptable error limits, though minor adjustments could further enhance precision.

However, liquid volume flow measurements exhibit moderate accuracy, with several data points deviating from the ± 5% error criteria, suggesting that further improvements are needed to achieve consistent results. The challenges are more pronounced in oil volume flow measurements, where significant discrepancies were observed, as many data points failed to meet the ± 10% error criteria. This indicates a need for enhanced measurement techniques and recalibration to improve accuracy. Although mostly within the ± 10% error criteria, water volume flow measurements reveal opportunities for optimization to ensure all measurements consistently meet the acceptable limits.

Water flowrate measurement deviations appear more frequently at both low and high flowrates. At low flowrates, poor signal resolution and transient mixing can introduce noise, while at higher flowrates, sensor lag and dielectric interference may distort readings. The rapid changes in flow composition in dynamic high-GVF environments create challenges in real-time signal interpretation for water detection. To contextualize the MPFM’s performance, the blind test results were compared against recognized industry standards, particularly ISO/TR 12,748:2015 and API MPMS Chapter 22.2, which outline acceptable accuracy ranges for multiphase flowmeters across different flow types. Table 4 summarizes how the tested MPFM aligns with these benchmarks.

Table 4 MPFM Performance metrics vs. Industry standards (ISO/API).
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Discussion

The results of this study highlight the significant role that Multiphase Flowmeters (MPFMs) play in optimizing operations in offshore wet gas fields, particularly in environments characterized by high gas volume fractions (GVF). The evaluation of the MPFM technology at 13 blind test points demonstrated varying success across different measurement parameters, underscoring the complex nature of multiphase flow measurement in offshore settings. This discussion will explore the implications of these findings, analyze the challenges and opportunities identified, and consider the broader impact of MPFM technology on the oil and gas industry.

Evaluation of MPFM performance in high GVF conditions

The study’s results revealed that the MPFM technology met the acceptance criteria for gas volumetric flow rates with commendable precision. This finding underscores the efficacy of MPFMs in environments with high GVF, where traditional meters often fail to deliver accurate results due to their reliance on simplified models that cannot adequately account for the complexities of multiphase flow dynamics17. The ability of MPFMs to provide precise measurements in such conditions is a testament to the advancements in sensor technology and data processing algorithms integrated into these systems.

However, the mixed results observed for liquid and water-liquid ratio measurements indicate an area where further refinement is necessary. The observed low passing rates for liquid volumetric flow rate (46%) and water-liquid ratio (45%) suggest systemic measurement challenges that extend beyond random error. A key contributing factor is likely phase slip, where gas and liquid phases travel at different velocities, particularly in stratified or annular flow regimes common at high GVF conditions. This velocity mismatch can distort sensor readings, especially in time-of-flight or impedance-based systems. Another issue is entrained droplets and transient slugs, which create rapid fluctuations in local phase composition that MPFMs struggle to resolve in real time. Additionally, sensor signal attenuation and low signal-to-noise ratios are more pronounced in small liquid volumes embedded in dominant gas flows, leading to misclassification or under-detection of liquid fractions. Calibration mismatches under these dynamic conditions can further amplify errors, especially if standard settings are not field-tuned for high-GVF wet gas streams. These challenges highlight the need for adaptive measurement algorithms and improved phase discrimination methods in future MPFM designs.

These discrepancies can be attributed to several factors, including phase slip, entrained droplets, and fluctuating phase compositions, which pose challenges in achieving consistent measurement accuracy22. Addressing these issues will require ongoing technological innovation, such as improved phase separation techniques and enhanced calibration processes, to ensure that MPFMs can maintain high accuracy across all measured parameters. In particular, the systematic deviations observed in water volumetric flowrate measurements—especially at higher flow conditions (see Fig. 7)—suggest that the MPFM may be affected by signal attenuation due to increased water content, sensor lag under transient flow changes, or limited phase separation capability at high water cuts. These challenges indicate that even with strong gas flowrate accuracy, refinements in water-phase detection algorithms and sensor response times are necessary to ensure robust performance across all flow regimes.

The ability to accurately measure multiphase flows has direct implications for operational efficiency in wet gas fields. With reliable data on phase fractions and flow rates, operators can make informed decisions that optimize production strategies, reduce operational costs, and improve resource management. For instance, accurate flow measurements enable precise allocation of resources, minimizing wastage and ensuring that production targets are met without exceeding environmental regulations. This capability is particularly valuable in normally unmanned facilities (NUFs), where remote monitoring and decision-making are crucial.

The performance outcomes of this study complement findings by Wang et al. (2023), who emphasized the limitations of traditional flow models under high-GVF conditions. However, while prior studies primarily relied on simulations or limited field datasets, this study contributes blind-test experimental validation with real gas–liquid flow ranges up to 99.5% GVF. Unlike earlier reports that focus on generalised algorithmic compensation, our results highlight the importance of phase-specific calibration and quantify systematic deviations in gas and liquid phase accuracy. This empirical insight supports the need for tailored MPFM configurations in dynamic high-GVF fields, extending beyond the scope of previous sensor-modelling frameworks.

Cost-effectiveness of MPFM deployment

One of the critical findings of this study is the potential cost savings associated with MPFM deployment compared to traditional wet gas meters. Traditional meters, while effective under specific conditions, often require frequent maintenance and recalibration to maintain accuracy, leading to increased operational costs and downtime11. In contrast, MPFMs offer a more robust solution with lower maintenance requirements and greater longevity, resulting in substantial cost savings over the long term.

The cost-effectiveness of MPFMs is further enhanced by their compatibility with lightweight structures, which reduces the need for extensive infrastructure and supports more streamlined operations. This attribute is particularly advantageous in offshore platforms where space and weight constraints are significant considerations. By reducing the physical footprint and associated costs, MPFMs present a compelling value proposition for operators seeking to optimise their offshore operations economically.

The economic implications of deploying MPFMs extend beyond direct cost savings. Accurate multiphase flow measurements contribute to improved reservoir management, enabling operators to maximise resource recovery and extend the life of their assets. This capability translates into increased revenue potential and enhanced competitiveness in the global energy market23. Moreover, the integration of MPFM technology aligns with the industry’s broader shift towards digitalization and automation, facilitating the adoption of smart technologies that enhance operational efficiency and safety24.

Despite the promising results, several challenges remain in optimizing MPFM technology for wet gas fields, particularly in high GVF environments. The primary challenge lies in achieving consistent measurement accuracy for liquid and water-liquid ratio parameters, which are susceptible to errors due to phase slip and entrained droplets25. To overcome these obstacles, continued research and development efforts are needed to refine sensor technologies, calibration methodologies, and data processing algorithms.

Innovations such as machine learning algorithms offer promising avenues for enhancing MPFM performance. By leveraging real-time data and predictive modeling, machine learning can dynamically adjust measurement parameters to account for changing field conditions, reducing errors and improving overall accuracy26. Additionally, the integration of advanced phase separation techniques, such as gamma-ray densitometry and electrical capacitance tomography, can further enhance the precision of multiphase flow measurements.

Future research directions

The study’s findings highlight several areas for future research and development in MPFM technology. Firstly, exploring the application of machine learning and artificial intelligence in flow measurement presents opportunities for significant advancements in accuracy and efficiency. These technologies can enable adaptive systems that respond to dynamic field conditions, offering real-time insights and predictive capabilities that enhance operational decision-making.

Furthermore, the development of advanced calibration techniques tailored to specific flow regimes will be crucial in addressing measurement discrepancies and improving accuracy across all phases. Collaboration between academia, industry, and technology providers will be essential in driving innovation and ensuring that MPFMs continue to evolve in line with the industry’s growing demands.

Environmental impact and sustainability

The accurate measurement of multiphase flows plays a critical role in promoting environmental sustainability in offshore oil and gas operations. By providing precise data on phase fractions and flow rates, MPFMs enable operators to optimize production processes, minimize resource wastage, and reduce emissions. This capability aligns with the industry’s commitment to sustainability and environmental stewardship, helping to mitigate the environmental impact of oil and gas production3. Moreover, the use of MPFM technology supports the development of more sustainable practices in offshore operations, such as minimizing flaring and reducing the environmental footprint of production activities. Accurate flow measurements allow operators to implement effective emissions management strategies, ensuring compliance with environmental regulations and contributing to the global effort to reduce greenhouse gas emissions.

The integration of MPFMs in offshore platforms also has regulatory implications, particularly in regions with stringent environmental standards. Accurate flow measurement is essential for demonstrating compliance with regulatory requirements and avoiding potential fines or penalties27. By providing reliable data on emissions and production metrics, MPFMs help operators maintain transparency and accountability in their operations, fostering trust and confidence among stakeholders.

Implications for offshore oil and gas production

The implementation of MPFM technology in offshore oil and gas production offers numerous operational and economic benefits. Accurate multiphase flow measurement is crucial for optimizing reservoir management, ensuring the efficient allocation of resources, and reducing environmental impact28. MPFMs provide operators with real-time insights into flow dynamics, enabling proactive decision-making that can mitigate potential issues before they escalate into costly problems23.

Furthermore, the use of MPFMs aligns with the industry’s shift towards digitalization and automation, supporting the integration of smart technologies that enhance operational safety and efficiency24. By delivering precise flow measurements, MPFMs contribute to the development of more sustainable practices in offshore operations, helping to minimize emissions and environmental disturbances.

While the study demonstrates strong MPFM performance under high-GVF conditions (78.6–99.5%) and specific pressure settings (400 psi and 740 psi), these conditions do not encompass the full range of operational scenarios encountered in the field. In particular, MPFM behavior at lower GVF levels, higher pressures, or under rapidly fluctuating conditions remains untested in this setup. Additionally, the limited sample size of 13 blind test points, although valuable for benchmarking, may not fully capture the variability present in real-world production systems. Future studies should expand the test matrix to include broader flow regimes and longer-duration field trials to enhance the generalizability and robustness of the findings.

MPFMs contribute to sustainability goals by reducing both direct and indirect environmental impacts. Field studies have shown that replacing traditional test separators and flare-reliant test setups with MPFMs can reduce associated CO₂-equivalent emissions by up to 25–35% through minimized flaring and decreased venting (Plagens et al., 2023). Additionally, the smaller equipment footprint reduces steel usage and associated embodied carbon, while lower power demand (up to 40% less compared to separation systems) contributes to more energy-efficient operations (Barbariol et al., 2020). These factors make MPFMs well-aligned with ESG targets for offshore developments, particularly in constrained environments like Normally Unmanned Facilities (NUFs).

Conclusion

This study highlights the transformative potential of Multiphase Flowmeters (MPFMs) in optimizing the efficiency of wet gas fields, particularly in offshore environments characterized by high Gas Volume Fractions (GVF). The rigorous testing and performance evaluation demonstrate that MPFMs enhance measurement accuracy, significantly reduce operational costs, and minimize infrastructure requirements. These advancements make MPFMs particularly suitable for deployment in normally unmanned facilities (NUFs), where their lightweight and versatile design simplifies installation and minimizes maintenance needs. Field implementations have demonstrated that MPFMs can reduce capital expenditure by up to 30% and lower greenhouse gas emissions through reduced flaring and elimination of large separation facilities (Plagens et al., 2023; Annamalai et al., 2019). By eliminating the need for extensive separation facilities, MPFMs contribute to the development of more compact and cost-effective offshore platforms, aligning with industry trends toward sustainable and economical operations.

The technological evolution of MPFMs, driven by innovations in sensor technology, data processing algorithms, and materials engineering, has positioned them as increasingly valuable tools in modern oil and gas extraction processes. Their ability to deliver reliable measurements in diverse and challenging conditions ensures optimized resource management, maximized operational efficiency, and minimized environmental impact. Future research should continue to explore advancements in MPFM technology, focusing on further enhancing their accuracy, reliability, and adaptability to more extreme operational conditions. Additionally, real-world case studies and long-term field trials would provide valuable insights into the practical applications and benefits of MPFMs, solidifying their role in the ongoing evolution of the oil and gas industry.