Improved Models May Help Multiphase Flow Conditioning
In trying to reduce the footprint of facilities, operators often select the wrong piping components, thus hampering the performance of the processing facilities. Selection of the right piping components and configurations may help in the conditioning of multiphase flow and avoidance of separation issues. However, in order to improve the selection process, more research is needed to address the problems found in conventional multiphase flow modeling, an expert said.
In a webinar, “Multiphase Flow Conditioning: Industry Gaps,” hosted by the SPE Flow Assurance Technical Section, Carlos Avila discussed ways to close the gaps in multiphase flow modeling. Avila is a senior facilities engineer for advanced production systems at Chevron.
Avila said that current modeling technology is insufficient in predicting gas/liquid entrainment in oilfield applications: He cited a field in which various models predicted between 4% and 90% entrainment. The performance of large separators depends on the expected amount of entrainment, and a wide range of uncertainty between models makes it difficult to set a reasonable expectation.
“We have many fields that are producing large amounts of gas with liquid entrainment,” Avila said. “There are many models out there. Which model are you going to use to predict?”
Slug mitigation is another issue. Avila said there is no effective way to map the operational envelope of mitigation technologies or quantify the probability of success for a specific laboratory-proven technology. Three-phase flow is also a problem. Avila noted a lack of models for gas/oil/water flow pattern mapping and for partial water entrainment. He said the development of a more effective oil-soluble corrosion inhibitor, when combined with a better understanding of three-phase flow, can help operators improve corrosion management in their pipelines, particularly with long-distance tiebacks.
A better understanding of flow pattern uncertainty may help improve management of top-of-the-line corrosion. Multiphase flow modeling assumes a sudden change in flow pattern after crossing the transition boundary, which Avila said could lead to faulty predictions of the pattern itself. He said models should better predict a discontinuity in pressure drop, and new methods must be developed to validate models against available multiphase flow pattern data.
Conditioning chokes also contribute to a large extent to the uncertainty of separation design in the upstream devices used to control flow, which Avila said could be a problem for fields with oil/water separation issues or emulsions.
He said it is important to understand the inherent risks in devising solutions to address the gaps in modeling technology.
The first issue is the difficulty in validating small-scale experiments in large-scale field conditions. He said compiling field data and conducting field trials in safe conditions can help mitigate this problem. If possible, companies should conduct experiments in high-pressure facilities and define the scaling laws and phenomena in models for wide application.
The second technological risk is the validity of a model’s prediction. Unreliable models are useless in the field, so Avila said companies should challenge their predictions with difficult field cases, both in-house and with commercially available software.
The third risk is the characterization of uncertainty in models. Uncertainty must be established in the decision analysis when comparing different modeling technologies.
“If we’re going to be comparing competing technologies and how they benefit a field, we have to make sure that the benefits we are promising are beyond the uncertainties of the technology. We need to understand the limitations of our predictions,” Avila said.
This webinar is available at https://webevents.spe.org/products/multiphase-flow-conditioning-industry-gaps.
Addressing the Gaps in Subsea Produced Water Treatment
Operators are looking for ways to better handle water coming from subsea wells, which is typically treated at topside facilities. Subsea separation systems are not equipped to discharge water back into the reservoir, so how do companies close the gaps?
Neural Networks Plus CFD Speed Up Simulation of Fluid Flow
High-fidelity 3D engineering simulations are valuable in making decisions, but they can be cost-prohibitive and require significant amounts of time to execute. The integration of deep-learning neural networks with computational fluid dynamics may help accelerate the simulation process.
Greedy Pursuit: Algorithms Show Promise in Measuring Multiphase Flow
“Greedy pursuit” in the realm of algorithms is a good thing. Saudi Aramco studied such algorithms to produce images simulating the flow inside a pipe’s cross section, possibly reducing the need for separator-based multiphase flowmeters.
Don't miss out on the latest technology delivered to your email every two weeks. Sign up for the OGF newsletter. If you are not logged in, you will receive a confirmation email that you will need to click on to confirm you want to receive the newsletter.
18 June 2019
19 June 2019