A Transient 3D CFD Model of a Progressive Cavity Pump

2016 ◽  
Author(s):  
K. R. Mrinal ◽  
Md. Hamid Siddique ◽  
Abdus Samad
Keyword(s):  
Oil And Gas ◽  
Complex Geometry ◽  
Transient Behavior ◽  
Oil And Gas Industry ◽  
High Viscosity ◽  
Solid Content ◽  
Operating Conditions ◽  
Cfd Model ◽  
Ansys Fluent ◽  
Flow Variables

A progressive cavity pump (PCP) is a positive displacement pump and has been used as an artificial lift method in the oil and gas industry for pumping fluid with solid content and high viscosity. In a PCP, a single-lobe rotor rotates inside a double-lobe stator. Articles on computational works for flows through a PCP are limited because of transient behavior of flow, complex geometry and moving boundaries. In this paper, a 3D CFD model has been developed to predict the flow variables at different operating conditions. The flow is considered as incompressible, single phase, transient, and turbulent. The dynamic mesh model in Ansys-Fluent for the rotor mesh movement is used, and a user defined function (UDF) written in C language defines the rotor’s hypocycloid path. The mesh deformation is done with spring based smoothing and local remeshing technique. The computational results are compared with the experiment results available in the literature. Thepump gives maximum flowrate at zero differential pressure.

Fully Parametric High-Fidelity CFD Model for the Design Optimisation of the Cyclic Stagger Pattern of a Set of Fan Outlet Guide Vanes

2009 ◽  
Author(s):  
Andrea Milli ◽  
Olivier Bron
Keyword(s):  
Complex Geometry ◽  
Single Point ◽  
Sensitivity Study ◽  
Operating Conditions ◽  
High Fidelity ◽  
Cfd Model ◽  
Design Optimisation ◽  
Guide Vanes ◽  
High Loss ◽  
Design Variables

The present paper deals with the redesign of cyclic variation of a set of fan outlet guide vanes by means of high-fidelity full-annulus CFD. The necessity for the aerodynamic redesign originated from a change to the original project requirement, when the customer requested an increase in specific thrust above the original engine specification. The main objectives of this paper are: 1) make use of 3D CFD simulations to accurately model the flow field and identify high-loss regions; 2) elaborate an effective optimisation strategy using engineering judgement in order to define realistic objectives, constraints and design variables; 3) emphasise the importance of parametric geometry modelling and meshing for automatic design optimisation of complex turbomachinery configurations; 4) illustrate that the combination of advanced optimisation algorithms and aerodynamic expertise can lead to successful optimisations of complex turbomachinery components within practical time and costs constrains. The current design optimisation exercise was carried out using an in-house set of software tools to mesh, resolve, analyse and optimise turbomachinery components by means of Reynolds-averaged Navier-Stokes simulations. The original configuration was analysed using the 3D CFD model and thereafter assessed against experimental data and flow visualisations. The main objective of this phase was to acquire a deep insight of the aerodynamics and the loss mechanisms. This was important to appropriately limit the design scope and to drive the optimisation in the desirable direction with a limited number of design variables. A mesh sensitivity study was performed in order to minimise computational costs. Partially converged CFD solutions with restart and response surface models were used to speed up the optimisation loop. Finally, the single-point optimised circumferential stagger pattern was manually adjusted to increase the robustness of the design at other flight operating conditions. Overall, the optimisation resulted in a major loss reduction and increased operating range. Most important, it provided the project with an alternative and improved design within the time schedule requested and demonstrated that CFD tools can be used effectively not only for the analysis but also to provide new design solutions as a matter of routine even for very complex geometry configurations.

A Novel Methodology for Optimal Design of Compressor Plants Using Probabilistic Plant Design

2013 ◽  
Vol 135 (11) ◽  
Author(s):  
Rainer Kurz ◽  
J. Michael Thorp ◽  
Erik G. Zentmyer ◽  
Klaus Brun
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Operating Conditions ◽  
Process Conditions ◽  
Plant Design ◽  
Well Performance ◽  
Worst Case ◽  
Gas Industry ◽  
Machine Performance ◽  
Equipment Sizing

Equipment sizing decisions in the oil and gas industry often have to be made based on incomplete data. Often, the exact process conditions are based on numerous assumptions about well performance, market conditions, environmental conditions, and others. Since the ultimate goal is to meet production commitments, the traditional method of addressing this is to use worst case conditions and often adding margins onto these. This will invariably lead to plants that are oversized, in some instances, by large margins. In reality, the operating conditions are very rarely the assumed worst case conditions, however, they are usually more benign most of the time. Plants designed based on worst case conditions, once in operation, will, therefore, usually not operate under optimum conditions, have reduced flexibility, and therefore cause both higher capital and operating expenses. The authors outline a new probabilistic methodology that provides a framework for more intelligent process-machine designs. A standardized framework using a Monte Carlo simulation and risk analysis is presented that more accurately defines process uncertainty and its impact on machine performance. Case studies are presented that highlight the methodology as applied to critical turbomachinery.

Wheel Box Test Aeromechanical Verification of New First Stage Bucket With Integrated Cover Plates for MS5002 GT

2019 ◽  
Author(s):  
Marco Mariottini ◽  
Nicola Pieroni ◽  
Pietro Bertini ◽  
Beniamino Pacifici ◽  
Alessandro Giorgetti
Keyword(s):  
Gas Turbine ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Response Assessment ◽  
Operating Conditions ◽  
Analytical Models ◽  
Gas Industry ◽  
Improved Performance ◽  
Cover Plates

Abstract In the oil and gas industry, manufacturers are continuously engaged in providing machines with improved performance, reliability and availability. First Stage Bucket is one of the most critical gas turbine components, bearing the brunt of very severe operating conditions in terms of high temperature and stresses; aeromechanic behavior is a key characteristic to be checked, to assure the absence of resonances that can lead to damage. Aim of this paper is to introduce a method for aeromechanical verification applied to the new First Stage Bucket for heavy duty MS5002 gas turbine with integrated cover plates. This target is achieved through a significantly cheaper and streamlined test (a rotating test bench facility, formally Wheel Box Test) in place of a full engine test. Scope of Wheel Box Test is the aeromechanical characterization for both Baseline and New bucket, in addition to the validation of the analytical models developed. Wheel Box Test is focused on the acquisition and visualization of dynamic data, simulating different forcing frequencies, and the measurement of natural frequencies, compared with the expected results. Moreover, a Finite Elements Model (FEM) tuning for frequency prediction is performed. Finally, the characterization of different types of dampers in terms of impact on frequencies and damping effect is carried out. Therefore, in line with response assessment and damping levels estimation, the most suitable damper is selected. The proposed approach could be extended for other machine models and for mechanical audits.

scholarly journals Stochastic Simplex Approximate Gradient for Robust Life-Cycle Production Optimization: Applied to Brugge Field

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Bailian Chen ◽  
Jianchun Xu
Keyword(s):  
Life Cycle ◽  
Net Present Value ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Optimization Techniques ◽  
Production Optimization ◽  
Operating Conditions ◽  
Optimization Under Uncertainty ◽  
Theoretical Argument ◽  
Gas Industry

In oil and gas industry, production optimization is a viable technique to maximize the recovery or the net present value (NPV). Robust optimization is one type of production optimization techniques where the geological uncertainty of reservoir is considered. When well operating conditions, e.g., well flow rates settings of inflow control valves and bottom-hole pressures, are the optimization variables, ensemble-based optimization (EnOpt) is the most popular ensemble-based algorithm for the robust life-cycle production optimization. Recently, a superior algorithm, stochastic simplex approximate gradient (StoSAG), was proposed. Fonseca and co-workers (2016, A Stochastic Simplex Approximate Gradient (StoSAG) for Optimization Under Uncertainty, Int. J. Numer. Methods Eng., 109(13), pp. 1756–1776) provided a theoretical argument on the superiority of StoSAG over EnOpt. However, it has not drawn significant attention in the reservoir optimization community. The purpose of this study is to provide a refined theoretical discussion on why StoSAG is generally superior to EnOpt and to provide a reasonable example (Brugge field) where StoSAG generates estimates of optimal well operating conditions that give a life-cycle NPV significantly higher than the NPV obtained from EnOpt.

scholarly journals Comparative Study of CFD and LedaFlow Models for Riser-Induced Slug Flow

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3733
Author(s):  
Rasmus Thy Jørgensen ◽  
Gunvor Rossen Tonnesen ◽  
Matthias Mandø ◽  
Simon Pedersen
Keyword(s):  
Slug Flow ◽  
Oil And Gas ◽  
Cfd Simulation ◽  
Numerical Models ◽  
Oil And Gas Industry ◽  
Test Facility ◽  
Cfd Model ◽  
Two Phase ◽  
Transient Model ◽  
Vof Model

The goal of this study is to compare mainstream Computational Fluid Dynamics (CFD) with the widely used 1D transient model LedaFlow in their ability to predict riser induced slug flow and to determine if it is relevant for the offshore oil and gas industry to consider making the switch from LedaFlow to CFD. Presently, the industry use relatively simple 1D-models, such as LedaFlow, to predict flow patterns in pipelines. The reduction in cost of computational power in recent years have made it relevant to compare the performance of these codes with high fidelity CFD simulations. A laboratory test facility was used to obtain data for pressure and mass flow rates for the two-phase flow of air and water. A benchmark case of slug flow served for evaluation of the numerical models. A 3D unsteady CFD simulation was performed based on Reynolds-Averaged Navier-Stokes (RANS) formulation and the Volume of Fluid (VOF) model using the open-source CFD code OpenFOAM. Unsteady simulations using the commercial 1D LedaFlow solver were performed using the same boundary conditions and fluid properties as the CFD simulation. Both the CFD and LedaFlow model underpredicted the experimentally determined slug frequency by 22% and 16% respectively. Both models predicted a classical blowout, in which the riser is completely evacuated of water, while only a partial evacuation of the riser was observed experimentally. The CFD model had a runtime of 57 h while the LedaFlow model had a runtime of 13 min. It can be concluded that the prediction capabilities of the CFD and LedaFlow models are similar for riser-induced slug flow while the CFD model is much more computational intensive.

Electrical Submersible Pump Prognostics and Health Monitoring Using Machine Learning and Natural Language Processing

2021 ◽  
Author(s):  
Rajeev Ranjan Sinha ◽  
Supriya Gupta ◽  
Praprut Songchitruksa ◽  
Saniya Karnik ◽  
Amey Ambade
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Operating Conditions ◽  
Learning Approaches ◽  
Submersible Pump ◽  
Gas Industry ◽  
Electrical Submersible Pump ◽  
Low Efficiency

Abstract Electrical Submersible Pump (ESP) systems efficiently pump high volumes of production fluids from the wellbore to the surface. They are extensively used in the oil and gas industry due to their adaptability, low maintenance, safety and relatively low environmental impact. They require specific operating conditions with respect to the power, fluid level and fluid content. Oilfield operation workflows often require extensive surveillance and monitoring by subject-matter experts (SMEs). Detecting issues like formation of unwanted gas and emulsions in ESPs requires constant analysis of downhole data by SMEs. The lack of adequate and accurate monitoring of the downhole pumps can lead to low efficiency, high lifting costs, and frequent repair and replacements. There are 3 workflows described in the paper which demonstrate that the maintenance costs of the ESPs can be significantly reduced, and production optimized with the augmentation of machine learning approaches typically unused in ESP surveillance and failure analysis.

Risk-based Winterization for Vessels Operations in Arctic Environments

2013 ◽  
Vol 29 (04) ◽  
pp. 199-210 ◽  
Author(s):  
Ming Yang ◽  
Faisal I. Khan ◽  
Leonard Lye ◽  
Heri Sulistiyono ◽  
John Dolny ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Temperature Data ◽  
Operating Conditions ◽  
Hydrocarbon Exploration ◽  
The Arctic ◽  
Gas Industry ◽  
Arctic Regions ◽  
Exploration And Production

Because the oil and gas industry has an increasing interest in the hydrocarbon exploration and development in the Arctic regions, it becomes important to design exploration and production facilities that suit the cold and harsh operating conditions. In addition to well-established minimum class requirements for hull strengthening, winterization should be considered as a priority measure early in the design spiral for vessels operating in the Arctic environments. The development of winterization strategies is a challenging task, which requires a robust decision support approach. This article proposes a risk-based approach for the selection of winterization technologies and determination of winterization levels or requirements on a case-by-case basis. Temperature data are collected from climatology stations located in the Arctic regions. Loading scenarios are defined by statistical analysis of the temperature data to obtain probabilistic distributions for the loadings. Risk values are calculated under different loading scenarios. Based on the risk values, appropriate winterization strategies can be determined. A case study is used to demonstrate how the proposed approach can be applied to the identification of heating requirements for gangways.

CFD Analysis of Centrifugal Compressor Stage Range Extension Using Internal Flow Recirculation

2015 ◽  
Author(s):  
Uday K. Meduri ◽  
Kathiravan Selvam ◽  
Gilles Nawrocki
Keyword(s):  
Centrifugal Compressor ◽  
Gas Flow ◽  
Oil And Gas ◽  
Internal Flow ◽  
Oil And Gas Industry ◽  
Operating Conditions ◽  
Flow Coefficient ◽  
Low Flow ◽  
External Circuit ◽  
Flow Recirculation

A Centrifugal Compressor is a key component in the Oil and Gas Industry. It is used in all 3 areas of extraction, processing and transportation, namely, upstream, midstream and downstream. Generally a compressor’s life expectancy matches that of the wells it is used on. Barring retrofits and maintenance, a compressor can remain onsite for up to 20 years. However, at the end of the life of the well or in special conditions with perennial low flow rates, the reduced gas flow rate pushes the compressor to the left of its operating limit. At this point, the compressor surges. In order to bring it back to the normal operating conditions, flow is recirculated via an external circuit involving the anti-surge valve. This drops the flange to flange performance. A simpler method would be to recycle the flow internally, thus removing the losses from the external circuit. In this paper, internal flow recirculation is studied where flow is extracted from the stage diffuser and recycled back to the upstream return channel. This study was undertaken on a 2D impeller from the lowest flow coefficient stage of an OEM. Using 1D tools and detailed CFD methods to study this novel design, it is shown that the range can be shifted significantly.

Formulation and Analysis of the Probability of Detection and False Detection for Subsea Leak Detection Systems

2014 ◽  
Author(s):  
Alireda Aljaroudi ◽  
Faisal Khan ◽  
Ayhan Akinturk ◽  
Mahmoud Haddara ◽  
Premkumar Thodi
Keyword(s):  
Oil And Gas ◽  
Detection System ◽  
Oil And Gas Industry ◽  
Leak Detection ◽  
Probability Of Detection ◽  
Operating Conditions ◽  
False Detection ◽  
Potential Threat ◽  
Probability Of False Alarm ◽  
Detection Systems

Insuring the integrity of subsea process component is one of the primary business objectives for oil and gas industry. One of the systems used to insure reliability of a pipeline, is the Leak Detection System (LDS). Different leak detection systems use different technologies for detecting and locating leaks that could result from pipelines. One technology in particular that is gaining wide acceptance by the industry is the optical leak detection systems. This technology has great potential for subsea pipelines applications. It is the most suited for underwater applications due to the ease of installation and reliable sensing capabilities. Having pipelines underwater in the deep sea present a greater challenge and a potential threat to the environment and operation. Thus, there is a need to have a reliable and effective system to provide the assurances that the monitored subsea pipeline is safe and functioning as per operating conditions. Two important performance parameters that are of concern to operators are the probability of detection and probability of false alarm. This article presents a probabilistic formulation of the probability of detection and probability of false detection for fiber optic LDS based systems.

Catastrophic Events and Human Error: A Few Rotten Apples or Organizational Dysfunction?

2021 ◽  
Author(s):  
Peter Vincent Bridle
Keyword(s):  
Human Error ◽  
Oil And Gas ◽  
Wide Spectrum ◽  
Oil And Gas Industry ◽  
Operating Conditions ◽  
Oil Field ◽  
Gas Industry ◽  
Oil And Gas Producers ◽  
The North ◽  
The Uk

Abstract In July 2021, commemorations will be held to mark the 33 years since the 1988 Piper Alpha tragedy in the UK sector of the North Sea where 167 oil field workers lost their lives. Without question, the incident was a watershed event for the international oil and gas industry not simply because of the immediate toll in human lives lost, but also in terms of the devasting aftermath endured by countless friends, families and loved ones whose lives were forever changed. The tragedy also served to illustrate just how poorly the oil and gas industry really understood and managed those operating risks that possessed the potential for catastrophic loss, both in terms of business cost and overall reputational impact. In the wake of the public enquiry that followed and chaired by Lord Cullen of Whitekirk, one of the principal recommendations required that the international oil and gas industry do a much better job in determining both its major hazards (i.e. major operating risks) and also in creating the necessary operating conditions to demonstrate that such things were being well managed. The objective being to provide tangible assurance that the likelihood of the industry ever incurring such a calamitous event again in the future had been reduced to as low as reasonably practicable (ALARP). In taking its responsibilities very seriously, the international oil and gas industry responded by raising the profile of the management of Health, Safety and the Environment (HSE) across the wide spectrum of its global operations. By the mid-nineties, the industry had implemented comprehensive and structured systems of work within the framework of purposely built HSE Management Systems using templates designed and developed for the industry via the International Oil and Gas Producers (IOGP)*.

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