Subsea Multiphase Flow Meter Measurement Performance Assurance with an Applied Data Validation and Reconciliation Surveillance Methodology (OTC 2022)

Subsea Multiphase Flow Meter Measurement Performance Assurance with an Applied Data Validation and Reconciliation Surveillance Methodology (OTC 2022)

This paper addresses performance assurance of subsea multiphase flow meters (MPFMs) using a surveillance methodology based on Data Validation and Reconciliation. Subsea measurements are challenging to verify because direct reference measurements are rarely available. This creates uncertainty in production monitoring and allocation.

The proposed DVR-based methodology systematically integrates multiple data sources such as pressure, temperature, fluid composition, and well test data to continuously evaluate MPFM performance. The approach supports three main objectives: direct validation against well tests, continuous monitoring during normal operations, and quantitative estimation of measurement uncertainty.

Field applications illustrate how the methodology helps detect deviations, maintain confidence in subsea measurements, and support long-term production management strategies.

Paper on OnePetro

 

Authors

Emmelyn Graham, Libsen Castill, John Yi, Tom Mooney, Amin Amin, Timothy Jadot – OTC 2022 – Houston – 2-5 May 2022 – OTC-31836-MS
 

Abstract

Measurement performance assurance for subsea multiphase flow meters (MPFM) can derive motivation from several sources of technical and/or business need, ranging from well surveillance to flow assurance monitoring, to production allocation among commingled sources of varying royalty, taxation, or ownership. Often, the more sensitive the subsea MPFM measurement is to a technical or business driver the more difficult it can be to initiate a comparison to a reference measurement or reference fluids such as topside measurement. Thus, providing assurance for subsea MPFM measurement performance requires a coordinated effort of MPFM performance surveillance – a combination of data and activities that can enable continuous indication of MPFM measurement performance, with or without periodic comparisons with reference measurements. However, utilizing MPFM performance surveillance information – which can come from a multitude of sources – can be confusing and potentially misinformative if a rigorous methodology to systematize the information isn’t applied. It was in this context that a surveillance methodology using data validation and reconciliation (DVR) was chosen to leverage the disparate surveillance information available and provide quantitative measurement performance assurance results for a subsea MPFM.

DVR was applied to assess the performance of a subsea MPFM incorporated within a subsea/topside field. Multiple sources of surveillance data and information were utilized in the application including the subsea MPFM, independent water-liquid ratio measurement, pressures and temperatures throughout the network, fluid properties, inlet separator flow measurements, and well test results.

Three main objectives were established to demonstrate efficacy of the applied DVR methodology for subsea MPFM measurement performance assurance:

1) quantified DVR results for direct MPFM validation via well test;

2) continuous DVR condition-based monitoring (CBM) of the subsea MPFM within a defined subsea/topsides topology during normal operations, and

3) DVR-derived uncertainty estimates for the subsea MPFM.

Several case studies using DVR surveillance are presented to address subsea measurement performance assurance through direct validation, CBM and uncertainty estimation. Each case study describes the workflow and detailed explanations for the steps taken in the DVR surveillance methodology.

Implementation challenges and lessons learned are also presented, along with a strategy for sustained subsea MPFM measurement performance assurance using a DVR-based surveillance approach.

 

Evaluation of Flowloop Uncertainty with Live Hydrocarbon Process Fluids for Multiphase Flowmeters Validation (OTC 2017)

Evaluation of Flowloop Uncertainty with Live Hydrocarbon Process Fluids for Multiphase Flowmeters Validation (OTC 2017)

This paper shows a data-reconciliation-based process model with integrated thermodynamics used to validate multiphase flowmeters (MPFMs) in high-pressure flowloops with live hydrocarbons. By reconciling measured and modeled fluid properties, the method produces consistent reference flowrates with quantified uncertainties, accounting for redundancy and physical constraints. Applied to generic HP test points and a real high-pressure, high-volume multiphase loop, the approach shows how input uncertainties affect MPFM evaluation and allows operators to replicate realistic subsea conditions in a controlled loop without oversimplified assumptions.

Paper on OnePetro

 

Authors

A. Amin, E. Harsono, E. Kamies, G. Heyen, G. De Vos – Offshore Technology Conference – Houston – 1-4 May 2017 – OTC-27925-MS
 

Abstract

The validation of multiphase flowmeters (MPFMs) in a controlled flowloop using live hydrocarbon fluid is examined with emphasis on the impact of measured and modelled fluid properties uncertainty on the loop reference measurements.

A customized process model based on data reconciliation with integrated thermodynamics package is built to evaluate the loop reference flowrates and their uncertainties at the multiphase flowmeter test station conditions. The process model accounts for data redundancy and physical constraints to ensure consistency of the reconciled measured and unmeasured variables used in the validation of multiphase flowmeters.

The model is applied to a generic set of test points performed in a high pressure (HP) flowloop. The paper discusses the modeling and operational aspects involved in validating the subsea meter’s measured flowrates. It also highlights the sensitivity of different inputs and their uncertainties on MPFM performance evaluation.

For the first time, the proposed approach enables operators to achieve the reality of subsea operations inside a highly controlled flowloop environment without resorting to overly simplified assumptions and practices. The approach is further validated by applying it to a high-pressure, high-volume, true multiphase flowloop using actual hydrocarbon fluids.

 

Using Measurement Uncertainty in Production Allocation (UPM 2016)

Using Measurement Uncertainty in Production Allocation (UPM 2016)

This paper shows how production measurement uncertainties can significantly affect allocation results under proportional and by-difference methods. This paper evaluates these impacts and proposes an uncertainty-based allocation using data validation and reconciliation (DVR). DVR incorporates measurement and fluid-property uncertainties, balances the full production system from subsea to custody transfer under physical constraints, and estimates the most likely sales quantities. Applied for the first time to a multi-tier allocation system, the method quantifies both measured and unmeasured variables with their uncertainties and provides diagnostics that support condition-based measurement maintenance, leading to fairer and more defensible allocations.

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Authors

Amin Amin – Upstream Production Measurement (UPM) Forum – Houston TX, – 24-25 February 2016.

 

Abstract

The effect of production measurements uncertainties is evaluated on different oil and gas production allocation methods, proportional, by difference, and uncertainty based. The scope is further expanded by examining and proposing an allocation method where measured and allocated quantities uncertainties are considered to achieve fair and equitable production allocation results.

The proposed approach uses data validation and reconciliation (DVR) methodology (governed by establish industry standards) to account for the measurement and fluids properties uncertainties rarely considered in traditional production allocation schemes. The DVR approach has the advantage to balance a complete production system, from subsea to custody transfer point, by estimating the most likely flow quantities available to sales within the known accuracies of the measurement devices and by obeying the physical constraints/laws of the producing network.

The DVR methodology is used for the first time in a multi-tier allocation system. It considers and quantifies measured and unmeasured parameters including their uncertainties in an all-encompassing production allocation scheme. The methodology also allows for measurement error diagnostics that can be integrated in a condition-based measurement maintenance program.