Evidence map›Paper›PMID 38894191›Full record

ArticleSensors (Basel, Switzerland)2024

Characterization of Gas-Liquid Two-Phase Slug Flow Using Distributed Acoustic Sensing in Horizontal Pipes.

Sharifah Ali, Ge Jin, Yilin Fan

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sharifah AliPetroleum Engineering Department, Colorado School of Mines, Golden, CO 80401, USA.ORCID 0000-0001-6071-7271
Ge JinGeophysics Department, Colorado School of Mines, Golden, CO 80401, USA.ORCID 0000-0002-9640-7547
Yilin FanPetroleum Engineering Department, Colorado School of Mines, Golden, CO 80401, USA.ORCID 0000-0002-3027-9634

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article discusses the use of distributed acoustic sensing (DAS) for monitoring gas-liquid two-phase slug flow in horizontal pipes, using standard telecommunication fiber optics connected to a DAS integrator for data acquisition. The experiments were performed in a 14 m long, 5 cm diameter transparent PVC pipe with a fiber cable helically wrapped around the pipe. Using mineral oil and compressed air, the system captured various flow rates and gas-oil ratios. New algorithms were developed to characterize slug flow using DAS data, including slug frequency, translational velocity, and the lengths of slug body, slug unit, and the liquid film region that had never been discussed previously. This study employed a high-speed camera next to the fiber cable sensing section for validation purposes and achieved a good correlation among the measurements under all conditions tested. Compared to traditional multiphase flow sensors, this technology is non-intrusive and offers continuous, real-time measurement across long distances and in harsh environments, such as subsurface or downhole conditions. It is cost-effective, particularly where multiple measurement points are required. Characterizing slug flow in real time is crucial to many industries that suffer slug-flow-related issues. This research demonstrated the DAS's potential to characterize slug flow quantitively. It will offer the industry a more optimal solution for facility design and operation and ensure safer operational practices.

Indexed as

distributed acoustic sensingdistributed fiber-optic sensingflow monitoringgas–liquid slug flowhorizontal pipe flowmultiphase flow metermultiphase flow sensorsslug flow characterization

Identifiers

PMID38894191
PMCPMC11174950

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.