Friction Factor Determination for Horizontal Two-Phase Flow Through Fully Eccentric Annuli

Abstract

In this study, empirical friction factor correlations were developed for two-phase stratified- and intermittent-flow patterns through horizontal fully eccentric annuli. Two-phase flow hydraulics were investigated, and a flow pattern prediction model is proposed. The friction factor correlations were validated using experimental data collected at the multiphase flow loop METU-PETE-CTMFL. Two different geometrical configurations were used during experiments—that is, 0.1143 m inner diameter (ID) casing, 0.0571 m outer diameter (OD) drillpipe; and 0.0932 m ID casing, 0.0488 m OD drillpipe. The eccentric annuli has been represented by representative diameter d _r . A new mixture Reynolds number based on liquid holdup is proposed for friction factor determination.     

Modelling of Two-Phase Flow Through Concentric Annuli

Abstract

A mathematical model is introduced in order to predict the flow characteristics of multiphase flow through an annulus. Flow patterns and frictional pressure losses estimated using the proposed model are compared with the experimental data of a wide range of liquid and gas flow rates recorded at a flow loop consisting of numerous circular pipes and annulus. The results showed that the model predictions for flow patterns and frictional pressure losses are reasonably accurate. Moreover, it is observed that geometry and liquid phase viscosity have a significant influence on flow pattern transitions and frictional pressure losses.     

A Mathematical Model and Solution for Mass Transfer and Diffusion After a Polymer Flood with Flow Channel

Abstract

Reservoirs in eastern China are now characterized by serious flow channels due to long-term waterflooding, and thus the general one-dimensional mass transfer and diffusion equation and its analytical model are no longer applicable because no transversal dispersion was considered. For reservoirs with breakthrough flow channels, the physical model is abstracted and a mathematical model for in-layer mass transfer and diffusion with longitudinal and transversal dispersion considered is also established. Analytical and numerical solutions are obtained. The analytical and mathematical solutions help us to deepen the understanding of the physical process of mass transfer and diffusion.     

Computerized Solution of the Dynamic Sorption Process for Binary System in Heterophase Medium

Abstract

A mathematical model equation for binary adsorption-reaction process is developed and illustrated for the catalytic dehydrogenation of cyclohexane to benzene on Platinum-Rhenium/Alumina catalyst with unadsorbed hydrogen in inert (argon, he lium) and active (hydrogen) carrier gases using pulse and continuous flow techniques. The optimization routine of Nelder-Mead simplex algorithm is developed with a view to estimating surface reaction rate and adsorption equilibrium constants at different temperatures, which in turn are used to determine activation energies and adsorption equilibrium energies for cyclohexane dehydrogenation in inert and active carrier gases using pulse and continuous flow techniques.     

Two-phase Inflow Performance Relationship Prediction Using Two Artificial Intelligence Techniques: Multi-layer Perceptron Versus Genetic Programming

Abstract

A genetic programming model has been compared with multi-layer perceptron (MLP) and empirical correlations to predict the inflow performance of vertical oil wells experiencing two-phase flow. The genetic programming under discussion in this work relies on tree-like building blocks, and thus supports process modeling with varying structure. The necessary training data have been obtained from 16 different simulated reservoir models, covering a wide range of fluid properties and relative permeabilities. The results show that the fitted genetic programming model gives the smallest error for unseen data, when compared with MLP and empirical correlations.     

An Analysis of Oil Well Testing for Non-Newtonian Fluid in a Fracture-Dominated Reservoir

Abstract

A mathematical model based on a composite geometry was developed for a non-Newtonian power-law fluid in a fracture-dominated reservoir. An analytic solution in Laplace space for this reservoir model was used to determine the type-curves for various composite parameters. The dynamic behavior of the bottom hole pressure at early and later stages was also analyzed. Therefore, the model can be used to analyze the fluid flow and fractures in some polymer-flooding reservoirs.     

A Mechanistic Model for Predicting Frictional Pressure Losses for Newtonian Fluids in Concentric Annulus

Abstract

A mathematical model is introduced estimating the frictional pressure losses of Newtonian fluids flowing through a concentric annulus. A computer code is developed for the proposed model. Also, extensive experiments with water have been conducted at Middle East Technical University, Petroleum and Natural Gas Engineering Department Flow Loop and recorded pressure drop within the test section for various flow rates. The performance of the proposed model is compared with computational fluid dynamics (CFD) software simulated annulus flow section and various criteria such as crittendon, hydraulic diameter and slot flow approximation as well as experimental data. The results showed that the proposed model and experimental results are in good agreement for almost all cases when compared with the other criteria and CFD software. Also, the proposed model could estimate the frictional pressure losses for both laminar and turbulent flow regimes within an error range of ±10%.     

Development of a Neural Fuzzy System for Advanced Prediction of Bottomhole Circulating Pressure in Underbalanced Drilling Operations

Abstract

Precise prediction of bottomhole circulating pressure (BHCP) is the major concern in the designing stage of an underbalanced drilling (UBD) operation. A successful UBD operation hinges tightly on the accurate control of downhole pressures. In order to predict the pressure gradient, complex two-phase flow correlations are employed and the flow pattern is defined. The problems arising from such methods are the significant errors relative to the nature of a UBD and the need for localization of the parameters or the shift from one correlation to another from case to case. In this study, different types of fuzzy inference systems are developed to construct new models. The resulting average percentage relative error (APE) of 13.83% for a Sugeno model and 13.11% for a Mamdani model indicated that the generated fuzzy models have the capability of precise BHCP prediction with higher accuracies in comparison with the popular mechanistic models.     

The Investigation of Vertical Wells' Optimum Two-phase Flow Empirical Correlation for the Ab-Teymour Reservoir

Abstract

There are different procedures for predicting pressure drop in two-phase flow pipelines. However, for each reservoir one or two correlations or mechanistic models give more accurate results. The authors investigated various correlations and mechanistic models in order to match fluid pressure losses considering all parameters such as friction, liquid holdup, superficial velocities, densities, viscosities, and interfacial tension. Commercial software, Pipesim, was used to simulate the fluid pressure losses. Drift flux modeling for predicting pressure profile was also investigated. A program for calculating pressure drops and average deviation of calculated pressures using this drift flux model was developed and the results were compared with other correlations.     

An Artificial Neural Network Model for Design of Wellhead Chokes in Gas Condensate Production Fields

Abstract

The subcritical flow behavior of gas condensates through wellhead chokes under different flow conditions are studied by use of an artificial neural network (ANN). The proposed network is trained using the Levenberg-Marquardt back-propagation algorithm and the hyperbolic tangent sigmoid activation function is applied to calculate the output values of the neurons of the hidden layer. The proposed neuromorphic model outperforms the existing empirical correlations both in accuracy and generality. The results of this work are very important in the design of wellhead chokes under a wide range of flow conditions usually encountered during the flow of gas condensates.     

A Derivation of the Averaging Model for Cuttings Transport: Multi-Region Model

Abstract

The aim of this paper is to derive a mathematical model for cuttings transport in horizontal wellbores using the volume averaging method, which is a technique used to derive transport equations for multiphase systems and one of the main approaches in two-phase flow modeling.

The theoretical derivation of the cuttings transport problem is for a two-region system composed of a fluid bed and a stationary bed of drill cuttings, which is considered as a porous medium. A one-equation model for fluid bed was derived and was used to obtain the multi-region model. This model can be used to study the hydraulic transport of solid particles in horizontal wellbores.     

Numerical Study of Stratified Gas-Liquid Flow

Abstract

In this work the effects of empirical correlations of friction factors (wall and interfacial) on the numerical stability and parameters predictions in stratified gas-liquid pipelines flow, was studied using the two-fluid model, where unequal phase pressure effects were considered. To study the effects of such empirical correlations without taking into account the instabilities due to ill-posed initial-value problems or multiple solutions, the two-fluid model was solved using input data, which satisfies a linear stability criterion where multiple solutions do not occur. In general, we found that the empirical correlations are not important for numerical stability but do, however, affect significantly the parameters predictions.     

Modeling Biosurfactant-Enhanced Bioremediation Processes for Petroleum-Contaminated Sites

Abstract

In situ bioremediation is an effective technology for cleaning up petroleum-contaminated sites. To improve efficiencies of conventional bioremediation processes, biosurfactant treatment has received much attention. In this study, an integrated mathematical modeling system was developed for simulating biosurfactant-enhanced bioremediation (BEB) processes. The model includes modules of multiphase, multicomponent flow and transport, biological degradation, and biosurfactant-enhanced remediation. A pilot-scale physical modeling system, with rhamnolipid as biosurfactant, was designed to simulate the BEB process. The results demonstrated that the developed mathematical model is effective in examining the coupled effects of biodegradation and biosurfactant enhancement and can be used for supporting management of petroleum-contaminated sites.     

The Prediction of Undersaturated Crude Oil Viscosity: An Artificial Neural Network and Fuzzy Model Approach

Abstract

Viscosity is one of the most important governing parameters of the fluid flow, either in the porous media or in pipelines. So it is important to use an accurate method to calculate the oil viscosity at various operating conditions. In the literature, several empirical correlations have been proposed for predicting undersaturated crude oil viscosity. However these correlations are not able to predict the oil viscosity adequately for a wide range of conditions. An extensive experimental data of undersaturated oil viscosities from different samples of Iranian oil reservoirs was applied to develop an Artificial Neural Network (ANN) model and fuzzy model to predict and calculate the undersaturated oil viscosity. Validity and accuracy of these models has been confirmed by comparing the obtained results of these correlations and with experimental data for Iranian oil samples. It was observed that there is acceptable agreement between the ANN model and fuzzy model results with experimental data.     

Modeling of Two-Phase Flow in Oil Wells Using a Simplified Two-Fluid Model

Abstract

In this work, with the idea of finding a simplified, numerically stable, one-dimensional, time-dependent two-fluid mathematical model whose predictions are in agreement with oil wells data, a study of the accumulative terms effect on the numerical stability and predictions of a general two-fluid model, was carried out. The fluids considered in oil wells were water, oil, and gas. The liquid phase in the model is formed by water and oil with pseudoproperties. The model is able to predict pressure, volume fraction, velocity, and temperature for both phases. The numerical solution of the model, which consists of mass, momentum, and energy conservation equations, is based on the finite difference technique in the implicit scheme. The thermodynamic and transport properties of the fluids are estimated by black-oil PVT correlations. It was observed that, a numerically stable model, with acceptable predictions has to take into account the accumulative terms for the liquid volume fraction, gas velocity, and liquid temperature. Numerical results are in agreement with field data and theoretical results reported in literature.     

New Empirical Correlations for Predicting Crude Oil Properties

Abstract

Pressure–volume–temperature (PVT) properties of crude oil are essential parameters used for prediction of fluid flow both in porous media and through transmission pipelines. Whenever laboratory works are absent, the engineer should use regionally developed correlations. A large portion of all crude oil resources is located in the Persian Gulf countries, and they have more or less similar API ranges and acidities, so that any empirical PVT correlation based on data from one region can adequately predict the behavior of others in this large geological basin. In this study, a new set of black oil–type correlations for bubble point pressure (P_b), solution gas–oil ratio (GOR; R_s), and formation volume factor (Bo) is proposed based on more than 400 Iranian crude oil PVT lab data. Moreover, previous works were reviewed, most of which were not suitable to model Iranian crude PVT behavior. Although the new correlations are developed over Iranian crudes, they can be used for prediction over any crude oil with similar compositional properties (API and acidity). Then the accuracy of these correlations is compared with the newly presented set and the superiority of this work for predicting those parameters is demonstrated.     

Two-Region Average Model for Cuttings Transport in Horizontal Wellbores I: Transport Equations

Abstract

The aim of this article is to derive a mathematical model without length-scale restrictions for cuttings transport in horizontal wellbores using the non-local forms of the volume averaging method, which is a technique used to derive transport equations for multiphase systems and one of the main approaches in two-phase flow modeling. The theoretical derivation of the cuttings transport problem is for a two-region system composed of a fluid bed (ω region) and a stationary bed (η region) of drill cuttings that it is considered as a porous medium. The volume-averaged mathematical model obtained in this work consists of the mass and momentum equations for the ω and η regions. The model was the starting point to obtain one-equation models for both regions. The one-equation models together with adequate jump conditions can be used to predict the hydrodynamics of the ω and η regions. The mathematical derivations of the momentum and mass flux transfer jump conditions are presented in Part II of this article.     

Synthesis and Characterization of a New Claw Molecule as Diesel Low-Temperature Flow Improver

Abstract

Citric acid—neopentylene glycol—citric acid (CNC) triblock claw molecule as a fuel additive was applied as a diesel fuel low-temperature flow improver. Some of the other molecules—such as stearic acid and hexadecyl alcohol—are trapped with the above-synthesized claw molecule. The claw molecule, which is hydrophilic before the other molecules trapped into the suitable sites of the claw molecule, becomes soluble in diesel fuel. The claw molecule structure was further confirmed by ¹H NMR and IR spectra. The cold filter plugging point of diesel of adding the claw molecule was measured and discussed. The experimental results showed that the newly developed low-temperature flow improver has a good sensibility to diesel of different batches and different composition. When dosage is 600 μg/g, the reduction value of cold filter plugging point is up to 6 units.     

Frictional Heating or Frictional Cooling,That Is the Question

Abstract

The frictional heating and frictional cooling mechanism is first discussed briefly in the present article. A general equation has been developed for predicting the inversion curves—where neither frictional heating nor frictional cooling occurs—for any types of natural gas. The predicted inversion curves can be applied to determine whether frictional heating or frictional cooling happens for any type of gas under a specific set of reservoir and well flow conditions.