Numerical Vortex-Induced Vibration Prediction of Marine Risers in Time-Domain Based on a Forcing Algorithm

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Peter Ma ◽  
Wei Qiu ◽  
Don Spencer
Keyword(s):  
Experimental Data ◽  
Time Domain ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Analysis Tool ◽  
Time Step ◽  
Vortex Induced Vibration ◽  
Marine Risers ◽  
Hydrodynamic Damping ◽  
Vibration Prediction

Vortex-induced vibration (VIV) of marine risers poses a significant challenge as the offshore oil and gas industry moves into deep water. A time-domain analysis tool has been developed to predict the VIV of marine risers based on a forcing algorithm and by making full use of the available high Reynolds number experimental data. In the formulation, the hydrodynamic damping is not treated as a special case but simply an extension of the experimentally derived lift curves. The forcing algorithm was integrated into a mooring analysis program based on the global coordinate-based finite element method. At each time step, the added mass, lifting force, and drag force coefficients and their corresponding loads are computed for each element. Validation studies have been carried out for a full-scale rigid riser segment and a model-scale flexible riser. The numerical results were compared with experimental data and solutions by other programs.

Time-Domain VIV Prediction of Marine Risers

2012 ◽  
Author(s):  
Peter Ma ◽  
Wei Qiu ◽  
Don Spencer
Keyword(s):  
Experimental Data ◽  
Time Domain ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Time Domain Analysis ◽  
Analysis Tool ◽  
Time Step ◽  
Marine Risers ◽  
Hydrodynamic Damping ◽  
High Reynolds

Vortex Induced Vibration (VIV) of marine risers poses a significant challenge as the offshore oil and gas industry moves into deep water. A time-domain analysis tool has been developed to predict the VIV of marine risers based on a forcing algorithm and by making full use of the available high Reynolds number experimental data. In the formulation, the hydrodynamic damping is not treated as a special case but simply an extension of the experimentally derived lift curves. The forcing algorithm was integrated into a mooring analysis program based on the global-coordinate based finite element method. At each time step, the added mass, lifting force and drag force coefficients and their corresponding loads are computed for each element. Validation studies have been carried out for a full-scale rigid riser segment and a model-scale flexible riser. The numerical results were compared with experimental data and solutions by other programs.

Numerical Simulation on Mooring Performance of LNG-FPSO System in Realistic Seas

2005 ◽  
Author(s):  
Yoshiyuki Inoue ◽  
Md. Kamruzzaman
Keyword(s):  
Time Domain ◽  
Oil And Gas ◽  
Three Dimensional ◽  
Time Domain Analysis ◽  
Analysis Tool ◽  
Motion Response ◽  
Non Linear ◽  
Floating System ◽  
Exciting Forces ◽  
The Time Domain

The LNG-FPSO concept is receiving much attention in recent years, due to its active usage to exploit oil and gas resources. The FPSO offloads LNG to an LNG carrier that is located close to the FPSO, and during this transfer process two large vessels are in close proximity to each other for daylong periods of time. Due to the presence of neighboring vessel, the motion response of both the vessels will be affected significantly. Hydrodynamic interactions related to wave effects may result in unfavorable responses or the risk of collisions in a multi-body floating system. Not only the motion behavior but also the second order drift forces are influenced by the neighboring structures due to interactions of the waves among the structures. A study is made on the time domain analysis to assess the behavior and the operational capability of the FPSO system moored in the sea having an LNG carrier alongside under environmental conditions such as waves, wind and currents. This paper presents an analysis tool to predict the dynamic motion response and non-linear connecting and mooring forces on a parallel-connected LNG-FPSO system due to non-linear exciting forces of wave, wind and current. Simulation for the mooring performance is also investigated. The three-dimensional source-sink technique has been applied to obtain the radiation forces and the transfer function of wave exciting forces on floating multi-bodies. The hydrodynamic interaction effect between the FPSO and the LNG carrier is included to calculate the hydrodynamic forces. For the simulation of a random sea and also for the generation of time depended wind velocity, a fully probabilistic simulation technique has been applied. Wind and current loads are estimated according to OCIMF. The effects of variations in wave, wind and current loads and direction on the slowly varying oscillations of the LNG and FPSO are also investigated in this paper. Finally, some conclusions are drawn based on the numerical results obtained from the present time domain simulations.

Value of Information in the Oil and Gas Industry: Past, Present, and Future

2009 ◽  
Vol 12 (04) ◽  
pp. 630-638 ◽  
Author(s):  
Reidar B. Bratvold ◽  
J. Eric Bickel ◽  
Hans Petter Lohne
Keyword(s):  
Value Of Information ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Relevant Information ◽  
Information Gathering ◽  
Information Value ◽  
Analysis Tool ◽  
Well Test ◽  
Gas Industry ◽  
Decision Context

Summary An important task that petroleum engineers and geoscientists undertake is to produce decision-relevant information. Some of the most important decisions we make concern what type and what quality of information to produce. When decisions are fraught with geologic and market uncertainties, this information gathering may such forms as seismic surveys, core and well test analyses, reservoir simulations, market analyses, and price forecasts--which the industry spends billions of US dollars each year. Yet, considerably less time and resources are expended on assessing the profitability or value of this information. Why is that? This paper addresses how to make value-of-information (VOI) analysis more accessible and useful by discussing its past, present, and future. On the basis of a survey of SPE publications, we provide an overview of the use of VOI in the oil and gas industry, focusing on how the analysis was carried out and for which types of decisions VOI analysis has been performed. We highlight areas in which VOI methods have been used successfully and identify important challenges. We then identify and discuss the possible causes for the limited use of VOI methods and suggest ways to increase the use of this powerful analysis tool. Introduction One of the most useful features of decision analysis is its ability to distinguish between constructive and wasteful information gathering. VOI analysis evaluates the benefits of collecting additional information before making a decision. Such information gathering may be worthwhile if it holds the possibility of changing the decision that would be made without further information. VOI attributes no value to "uncertainty reduction" or "increased confidence" per se. Rather, value is added by enabling the decision maker (DM) to better "tune" his/her choice to the underlying uncertainty. Thus, information value is forever an entanglement of uncertainty and decision making; one cannot value information outside of a particular decision context.

A Comparative Analysis and Evaluation of Model Selection Criteria

2017 ◽  
Author(s):  
Ahmed H. Kamel ◽  
Ali S. Shaqlaih ◽  
Arslan Rozyyev
Keyword(s):  
Experimental Data ◽  
Model Selection ◽  
Selection Criteria ◽  
Oil And Gas ◽  
Information Criterion ◽  
Oil And Gas Industry ◽  
Absolute Error ◽  
Ongoing Research ◽  
Model Selection Criteria ◽  
Innovative Strategy

The ongoing research for model choice and selection has generated a plethora of approaches. With such a wealth of methods, it can be difficult for a researcher to know what model selection approach is the proper way to proceed to select the appropriate model for prediction. The authors present an evaluation of various model selection criteria from decision-theoretic perspective using experimental data to define and recommend a criterion to select the best model. In this analysis, six of the most common selection criteria, nineteen friction factor correlations, and eight sets of experimental data are employed. The results show that while the use of the traditional correlation coefficient, R2 is inappropriate, root mean square error, RMSE can be used to rank models, but does not give much insight on their accuracy. Other criteria such as correlation ratio, mean absolute error, and standard deviation are also evaluated. The Akaike information criterion, AIC has shown its superiority to other selection criteria. The authors propose AIC as an alternative to use when fitting experimental data or evaluating existing correlations. Indeed, the AIC method is an information theory based, theoretically sound and stable. The paper presents a detailed discussion of the model selection criteria, their pros and cons, and how they can be utilized to allow proper comparison of different models for the best model to be inferred based on sound mathematical theory. In conclusion, model selection is an interesting problem and an innovative strategy to help alleviate similar challenges faced by the professionals in the oil and gas industry is introduced.

Statistical Time Domain Feature Based Approach to Assess the Performance Degradation of Rotary Seals

2018 ◽  
Author(s):  
Madhumitha Ramachandran ◽  
Zahed Siddique
Keyword(s):  
Time Domain ◽  
Oil And Gas ◽  
High Reliability ◽  
Accelerated Aging ◽  
Oil And Gas Industry ◽  
Oil Field ◽  
Classification Model ◽  
Severity Estimation ◽  
Feature Based ◽  
Statistical Time

In oil and gas industry, machineries and mechanical components are designed with high reliability to meet the demand of the oil field. Rotating machinery is a widely used equipment and any failure of critical components within the machinery could lead to delays and large expenses. Failure of rotary seal is one of the foremost causes of breakdown in rotary machinery and such a failure can affect the other process operations in oil and gas plants. Assessing seal degradation and severity estimation are very important for maintenance decision-making. Extracting meaningful and sensitive features that can show seal degradation from raw signals is a challenging task of degradation assessment. However, no extensive works are dedicated in this area of seals. In this paper, we perform accelerated aging and testing to capture the behavior of seals through their cycle of operation and demonstrated a statistical time domain feature based approach for extracting the sensitive features that can show seal degradation. Out of eleven statistical features extracted, seven extracted features such as mean, RMS, maximum, squared mean rooted absolute amplitude, impulse factor, crest factor, margin factor are found to be significant factors which have a potential to differentiate severity levels in seals. The findings from our work show that our approach has a potential to assess the severity in seals. As a possible extension, extracted features can be used to build a classification model to classify severity in seals which could be of great interest to the users and manufacturers of rotary seals.

Coupled Analysis of Deepwater Floating System Including VIV in Time Domain

2007 ◽  
Author(s):  
Jun-Bumn Rho ◽  
Alexander A. Korobkin ◽  
Jong-Jun Jung ◽  
Hyun-Soo Shin ◽  
Woo-Seob Lee
Keyword(s):  
Finite Element ◽  
Time Domain ◽  
Torsional Stiffness ◽  
Time Step ◽  
Vortex Induced Vibration ◽  
Coupled Equations ◽  
Floating System ◽  
Vessel Motion ◽  
Floating Systems ◽  
The Way

Deepwater floating systems consist of a vessel, risers, and mooring lines. To accurately simulate the floating systems in current, wind, and waves considering (1) bending and torsional stiffness of riser, (2) elongation of the mooring/riser elements, (3) complex end conditions, (4) internal flow effects, and (5) vortex induced vibration, it is necessary to evaluate the vessel motions and mooring/riser behaviors simultaneously in time domain. However, because the size of the system matrix increases significantly as the number of mooring/riser increases, it is quite time-consuming to solve all equations including both mooring/riser and vessel dynamics simultaneously. The present study was performed in order to develop a program for this problem. The 6DOF vessel dynamics is described by the Cummins equation. And the mooring and riser are modeled with the help of finite-element beam. The Newmark method is used as the time marching scheme of the FEM equations for each mooring/riser and the vessel. The coupled equations of the mooring/riser segments and vessel are solved alternatively at each time step. Mooring/riser and the vessel motion affect to each other in the way that the components of the forces at the segment ends are determined as functions of displacements and slopes of them. This procedure makes it possible to consider the coupling effects between vessel and mooring/riser efficiently. Also no iterations are required to match the vessel motion with the riser dynamics. This new approach allows us to use parallel computations and to deal with as many mooring/riser at the same time as necessary. The hydrodynamic forces induced by current are calculated by using the Morison’s formula. The VIV (Vortex Induced Vibration) effects are included in the way that the frequency and the shape of the riser vibration due to VIV are pre-calculated by iterations in the frequency domain. Then the finite element mooring/riser model is modified to consider the hydrodynamic loads including VIV and integrated in the final equations of the floating system in time domain.

scholarly journals Predicting the Dynamic Parameters of Multiphase Flow in CFD (Dam-Break Simulation) Using Artificial Intelligence-(Cascading Deployment)

Fluids ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 44 ◽  
Author(s):  
S. Hosseini Boosari
Keyword(s):  
Artificial Intelligence ◽  
Numerical Simulation ◽  
Multiphase Flow ◽  
Fast Track ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Dam Break ◽  
Data Driven ◽  
Time Step ◽  
Gas Industry

Multiphase flow of oil, gas, and water occurs in a reservoir’s underground formation and also within the associated downstream pipeline and structures. Computer simulations of such phenomena are essential in order to achieve the behavior of parameters including but not limited to evolution of phase fractions, temperature, velocity, pressure, and flow regimes. However, within the oil and gas industry, due to the highly complex nature of such phenomena seen in unconventional assets, an accurate and fast calculation of the aforementioned parameters has not been successful using numerical simulation techniques, i.e., computational fluid dynamic (CFD). In this study, a fast-track data-driven method based on artificial intelligence (AI) is designed, applied, and investigated in one of the most well-known multiphase flow problems. This problem is a two-dimensional dam-break that consists of a rectangular tank with the fluid column at the left side of the tank behind the gate. Initially, the gate is opened, which leads to the collapse of the column of fluid and generates a complex flow structure, including water and captured bubbles. The necessary data were obtained from the experience and partially used in our fast-track data-driven model. We built our models using Levenberg Marquardt algorithm in a feed-forward back propagation technique. We combined our model with stochastic optimization in a way that it decreased the absolute error accumulated in following time-steps compared to numerical computation. First, we observed that our models predicted the dynamic behavior of multiphase flow at each time-step with higher speed, and hence lowered the run time when compared to the CFD numerical simulation. To be exact, the computations of our models were more than one hundred times faster than the CFD model, an order of 8 h to minutes using our models. Second, the accuracy of our predictions was within the limit of 10% in cascading condition compared to the numerical simulation. This was acceptable considering its application in underground formations with highly complex fluid flow phenomena. Our models help all engineering aspects of the oil and gas industry from drilling and well design to the future prediction of an efficient production.

Automated near infrared analyzer validation (ASTM D6122) for the oil and gas industry

NIR news ◽  
2019 ◽  
Vol 30 (5-6) ◽  
pp. 39-41
Author(s):  
Susan J Foulk ◽  
Ryan Lerud
Keyword(s):  
Near Infrared ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Analysis Tool ◽  
Short Article ◽  
Gas Industry ◽  
Routine Measurement ◽  
Measurement And Analysis ◽  
Complete Measurement ◽  
Process Measurements

Near infrared spectroscopy is a routine measurement and analysis tool for both liquid and solid samples in a wide variety of industries and locations, both process and laboratory. For process measurements analyzer, validation is a key component of a complete measurement system. This short article will describe an automated validation system suitable for near infrared process analyzers.

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