The flow measurement of CO2 rich streams in Carbon Capture and Storage (CCS) processes presents a number of potential challenges. One of these challenges concerns the physical properties of CO2. For example, its compressibility exhibits significant non-ideal behavior, notably at pressures and temperatures likely to be encountered in CCS processes. Additionally, CO2 can undergo phase changes through the CCS processes ranging from single phase gas, liquid, dense phase to two-phase.

Though the properties of CO2 can be reliably predicted by several equations of state, the presence of impurities, (N2, H2, CH4, etc) can have a significant impact on these properties and therefore compromise uncertainty in the field.

The authors have presented two previous papers, at the 2019 and 2020 NSFMWs, in which advantage is taken of three differential pressure readings: primary(ΔPt), recovered (ΔPr), and permanent pressure loss (ΔPPPL) to reduce the uncertainty in the measured flow rate through an orifice meter. The 2019 paper introduced techniques from data reconciliation to reduce uncertainty. This was extended in 2020 to take advantage of temporal redundancy in the data using a Kalman Filter to further reduce uncertainty. These techniques were collectively described under the term: ‘Maximum Likelihood Uncertainty’ (MLU). The equations and methods have been further developed to reduce the uncertainty in flow to almost half that of a conventional orifice employing a single DP measurement.

The equations and method have been developed for both incompressible and compressible flow. The compressible equations have the added benefit that the expansibility factor can be calculated in two ways: first according to ISO 5167:2 and second, assuming a reversible expansion from a calculated upstream pressure and the vena contracta. This redundancy also allows the value and uncertainty of the isentropic coefficient of the gas to be improved in-situ, in accordance with the data.

This feature of the MLU Kalman approach, in which the values of the physical properties of the gas are improved, makes this flow meter an ideal candidate to measure the flow of gases whose physical properties are difficult to determine or are sensitive to flowing conditions such as CO2 (and H2).

The potential problems that may be encountered when measuring CO2 flow, place onus on diagnostic software to ensure that the meter is operating correctly. The three DP measurements can also be used to demonstrate that the meter is functioning correctly using the Prognosis software, previously presented by Steven at the 2008 NSFMW.

The efficacy of the diagnostic software and MLU method have been tested and demonstrated using:

• hypothetical but realistic data;
• real data obtained from the testing of CO2 flowing through an orifice meter with three pressure taps at a calibration facility.

This webinar presents a method of measuring CO2 flow that overcomes some of the difficulties encountered with the correct determination of its thermodynamic properties and presents a methodology that may be extended to handle the phase transitions.

This webinar is categorized under the Projects, Facilities, and Construction technical discipline.

All content contained within this webinar is copyrighted by Phil Stockton and its use and/or reproduction outside the portal requires express permission from Phil Stockton.

SPE Webinars are FREE to members courtesy of the