Flow assurance

Flow Assurance-2021

Flow-assurance effects from slug-flow engineering, design, maintenance, and operations technical concerns still create and sustain challenging technical issues requiring safe, economical solutions for both onshore unconventional and offshore conventional production facilities.

Flow Assurance Intro

I sincerely hope that all JPT readers and your families, peers, and employers remain safe and healthy and have work as they read this year’s Flow Assurance feature.

Flow-assurance effects from slug-flow engineering, design, maintenance, and operations technical concerns still create and sustain challenging technical issues requiring safe, economical solutions for both onshore unconventional and offshore conventional production facilities. The recurring long-term mitigation of slugging and various flow-assurance phenomena—along with the prevention of wax, erosion, asphaltenes, corrosion, and salt deposition—and gas hydrate prediction and handling still demand attention and considerable project technical effort.

Slug-flow assessments present opportunities for significant optimization in work flows to target governing operating scenarios. Paper OTC 30172 describes an integrated iterative approach between the flow-assurance and pipeline-engineering disciplines to streamline the work flow based on the value or cost associated with changes in input parameters that affect pipeline fatigue-assessment outcomes. Case studies on two multiphase pipelines are presented to illustrate this design approach. The results show that early identification of the key pipeline profile features and dominating spans for pipeline slugging fatigue assessments facilitated the optimization of slug-flow modeling and reduced computational time.

The second paper, SPE 203448, presents decision trees that are considered as nonparametric machine-learning models. The data sets used in training and testing the predictive model are experimental and were collected from literature. Air/kerosene and air/water mixtures were used in obtaining the experimental data points. Results show that the proposed boosted decision tree regression (BDTR) model outperforms the best empirical correlations and the fuzzy-logic model used in estimating liquid holdup in gas/liquid multiphase flows. For the built model, the most important input feature in estimating liquid holdup is the superficial gas velocity. The empirical correlations developed in the past for identifying liquid holdup in multiphase flow can be applied only under the flow conditions by which they were originally developed. However, this machine-learning model does not suffer from this limitation.

The third paper, OTC 31298, describes a slugging-control solution that was rejected because of the use of a pseudovariable as the principal control point. A novel control scheme, therefore, was developed and tested on simulations for both hydrodynamic slugging and severe riser-induced slugging in an Angolan field. The project implemented the novel active slugging control using a topsides control valve and topsides instrumentation. While a pseudovariable, a pseudoflow controller, was used, it was part of a cascade scheme such that the principal control variable was a real topside pressure measurement. Upon commissioning, slugging at the facility was found to be more severe than anticipated during design, but the novel active slug-control scheme was effective in controlling incoming slugs.

The desire to understand better how to describe and improve flow assurance and multiphase flow for both offshore and onshore facilities drives new production technology research, applications, and approaches. The three papers listed for additional reading focus on developing further new analytical tools while providing safe, cost-effective, and reliable operations for flow assurance. I hope you find them as interesting as I did. In addition, I invite you to join the Flow Assurance Technical Section to augment your learning.

This Month’s Technical Papers

Streamlined Multidisciplinary Work Flow Assesses Pipeline Slugging

Decision Tree Regressions Estimate Liquid Holdup in Two-Phase Gas/Liquid Flows

Slug-Control Strategy Proves Effective in New Angola Facility

Recommended Additional Reading

OTC 30177 Real-Time Online Hydrate Monitoring and Prevention in Offshore Fields by Syahida Husna Azman, Petronas, et al.

SPE 201316 Modeling Dynamic Loads Induced by Slug Flows Considering Gas Expansion Caused by the Pressure Gradient in a Free Span Horizontal Hanging Pipeline by Gabriel Meneses Santos, Universidade Estadual de Campinas, et al.

OTC 31238 Taylor Bubbles of Viscous Slug Flow in Inclined Pipes by Longtong Abednego Dafyak, University of Nottingham, et al.


Galen Dino, SPE, is senior consultant and project manager with Dino Engineering. He has more than 38 years of experience in international and domestic project management, project engineering, process design, supervision, fabrication, and construction. Dino holds a BS degree in chemical engineering from Louisiana State University and is a registered professional engineer in Texas. He founded the Production Facilities Study Group with the SPE Houston Section and has held associate-editor and technical-editor positions for SPE Project, Facilities, & Construction and SPE Production & Operations. Dino serves on the JPT Editorial Review Committee and can be reached at gdino@consolidated.net.