This is an academic lecture for Diploma in Engineering 7th Semester Mining and Mine Survey Technology. The Course related to this presentation is Well completion and testing
Production Optimization using nodal analysis. The nodal systems analysis approach is a very flexible method
that can be used to improve the performance of many well
systems. The nodal systems analysis approach may be used to analyze
many producing oil and gas well problems. The procedure can
be applied to both flowing and artificial
Selection of the best artificial lift systems for the well depend on location, depth, estimated production, reservoir properties, and many other factors. Here is an overview on selection criteria for the best results
WellCare Oil Tools Pvt. Ltd., prides itself on offering great service and being able to deliver accurate formal quotes to clients within 48 hours of receiving an enquiry.
We keep a large inventory of standard flow control tools and completion packers in stock, enabling quick delivery anywhere in the world. We ensure high quality and traceability, full certification including Mill Test Reports (MTR's), certificate of Conformance, Certificate of Origin, Function Test and Pressure Test Results are available free of charge upon request for each order and are kept on file and available on request at any time in the future.
Premium thread connections like: Tenaris-Hydril, Vam and Hunting connections are available upon request and threads are cut by premium licenced machine shops in Dubai & Singapore.
Special elastomer are available: AFLAS, HNBR, Viton and HSN, Hi-Nitrile are available along with non-elastomeric seal stacks to confirm to sour well conditions.
Category Products :
Cementation Systems
Cementing Equipment
Completion Systems
Mechanical Set Packer
Seal Bore Packer
Bridge Plugs
Hydraulic Set Packer
Cement Retainer
Completion Equipment
Liner Hanger Systems
Liner Hanger
Flow Control Systems
Sliding Sleeve
Landing Nipples
Flow Control Equipment
Inflatable Packers
Inflatable Packer
Various other factors that have enabled us to gain an edge over our competitors are:
Qualitative product range
World renowned vendor base
Experienced professionals
Efficient logistics and widespread distribution network
Industry leading prices
Timely delivery
--
With Best Regards
Surender Yadav ( Marketing Manager)
Cell: +91 8696934503
For WellCare Oil Tools Private Limited, India.
Water coning is a serious issue for the oil and gas industry. This poses a big
concern regarding the costs that to be incurred for separation and equipment
capacity. Coning is the production of an unwanted phase with a desired phase. Over
the years, many techniques and control methods has been birthed, however, the issue
of coning can only be mitigated and not completely discharged. Reservoir and
production engineers need to understand the basic framework; the parameters that
greatly influence coning and how effective manipulation of it can deal with it. With the
introduction of horizontal wells, the production rate is two to four times that of
vertical wells, and coning is reduced and the breakthrough time is increased.
Numerous papers has been written regarding to coning and vertical wells, only a few
emphasize on horizontal wells and simultaneous water coning and gas coning. The
objective of this research is to study the post breakthrough performance in
simultaneous coning and a black oil simulator was use for the research. Sensitivity
analysis was carried out on: the production rate of oil (qt), horizontal permeability,
vertical permeability, perforation length, the height above perforation, extent of
reservoir area and the formation porosity. A generalized correlation was developed
for predicting coning behavior using non-linear analysis
This is an academic lecture for Diploma in Engineering 7th Semester Mining and Mine Survey Technology. The Course related to this presentation is Well completion and testing
Production Optimization using nodal analysis. The nodal systems analysis approach is a very flexible method
that can be used to improve the performance of many well
systems. The nodal systems analysis approach may be used to analyze
many producing oil and gas well problems. The procedure can
be applied to both flowing and artificial
Selection of the best artificial lift systems for the well depend on location, depth, estimated production, reservoir properties, and many other factors. Here is an overview on selection criteria for the best results
WellCare Oil Tools Pvt. Ltd., prides itself on offering great service and being able to deliver accurate formal quotes to clients within 48 hours of receiving an enquiry.
We keep a large inventory of standard flow control tools and completion packers in stock, enabling quick delivery anywhere in the world. We ensure high quality and traceability, full certification including Mill Test Reports (MTR's), certificate of Conformance, Certificate of Origin, Function Test and Pressure Test Results are available free of charge upon request for each order and are kept on file and available on request at any time in the future.
Premium thread connections like: Tenaris-Hydril, Vam and Hunting connections are available upon request and threads are cut by premium licenced machine shops in Dubai & Singapore.
Special elastomer are available: AFLAS, HNBR, Viton and HSN, Hi-Nitrile are available along with non-elastomeric seal stacks to confirm to sour well conditions.
Category Products :
Cementation Systems
Cementing Equipment
Completion Systems
Mechanical Set Packer
Seal Bore Packer
Bridge Plugs
Hydraulic Set Packer
Cement Retainer
Completion Equipment
Liner Hanger Systems
Liner Hanger
Flow Control Systems
Sliding Sleeve
Landing Nipples
Flow Control Equipment
Inflatable Packers
Inflatable Packer
Various other factors that have enabled us to gain an edge over our competitors are:
Qualitative product range
World renowned vendor base
Experienced professionals
Efficient logistics and widespread distribution network
Industry leading prices
Timely delivery
--
With Best Regards
Surender Yadav ( Marketing Manager)
Cell: +91 8696934503
For WellCare Oil Tools Private Limited, India.
Water coning is a serious issue for the oil and gas industry. This poses a big
concern regarding the costs that to be incurred for separation and equipment
capacity. Coning is the production of an unwanted phase with a desired phase. Over
the years, many techniques and control methods has been birthed, however, the issue
of coning can only be mitigated and not completely discharged. Reservoir and
production engineers need to understand the basic framework; the parameters that
greatly influence coning and how effective manipulation of it can deal with it. With the
introduction of horizontal wells, the production rate is two to four times that of
vertical wells, and coning is reduced and the breakthrough time is increased.
Numerous papers has been written regarding to coning and vertical wells, only a few
emphasize on horizontal wells and simultaneous water coning and gas coning. The
objective of this research is to study the post breakthrough performance in
simultaneous coning and a black oil simulator was use for the research. Sensitivity
analysis was carried out on: the production rate of oil (qt), horizontal permeability,
vertical permeability, perforation length, the height above perforation, extent of
reservoir area and the formation porosity. A generalized correlation was developed
for predicting coning behavior using non-linear analysis
UntitledExcessive Water Production Diagnostic and Control - Case Study Jake O...Mohanned Mahjoup
For mature fields, Excessive water production is a complex subject in the oil and gas industries and has a serious economic and environmental impact. Some argue that oil industry is effectively water industry producing oil as a secondary output. Therefore, it is important to realize the different mechanisms that causing water production to better evaluate existing situation and design the optimum solution for the problem. This paper presents the water production and management situation in Jake oilfield in the southeast of Sudan; a cumulative of 14 MMBbl of water was produced till the end of 2014, without actual plan for water management in the field, only conventional shut-off methods have been tested with no success. Based on field production data and the previously applied techniques, this work identified the sources of water problems and attempts to initialize a strategy for controlling the excessive water production in the field. The production data were analyzed and a series of diagnostic plots were presented and compared with Chan’s standard diagnostic plot. As a result, distinction between channeling and conning for each well was identified; the work shows that channeling is the main reason for water production in wells with high permeability sandstone zone while conning appears only in two wells. Finally, the wells were classified according to a risk factor and selections of the candidate wells for water shut off were presented.
Spe 163367-ms-p Modelling of regional aquifer.....Burgan Field Minagish Reser...Stephen Crittenden
Bergan Field Kuwait. The Minagish Reservoir comprising oolite shoals, is aquifer pressure connected to other fields in the region which interact with each other.
Analysis for predicting the Input Interactions of HBF Performance at -10 μm P...journal ijrtem
ABSTRACT: Dewatering is an important process in any mineral industry. It is a process which removes the unwanted material from
the liquid solid suspension called slurry by using a filter element which separates the unwanted fluid material from the solids from the
feed. The paper attempts to establish the way towards analysis of Hyper Baric Filter (HBF) performance at -10μm particle size
treating iron ore fines (24% to 29%). Dewatering in HBF, requires reduction in moisture and material throughput rate in terms of per
hour so as to increase the performance of HBF. The present work carried out illustrates a method to predict the influence of process
input parameter such as vessel pressure, snap blow and filter disk rotation for reduction in moisture percentage level and material for
reduction moisture percentage level and material throughput rate for particle size in the range of 24% to 29%. Using Design of
Experiments (DOE) a linear regression model is developed to study the performance of HBF full factorial design method using
ANOVA to analyze the data. Validation of the results is performed by comparing the experimental values and predicted values for
Material through put rate in terms of cycles/hr and reduction in moisture percentage by weight and hot spots.
Keywords: Hyper Baric Filter, dewatering, design of experiments, size of particles, vessel pres
Optimization of Bajaj three wheeler carburetor fuel tube for better performancedbpublications
This paper presents the analysis of Bajaj three wheeler carburetor for better performance using Ansyss fluent computational fluid dynamics software. Carburetor is a device which mixes air and fuel before entering into the engine. If the mixture is not proper it results in excess fuel consumption, increase in pollution due to improper burning and also increase in running cost of the Bajaj. In this regard an effort has been made to optimize the design of the carburetor to minimize these problems. In Mettu town more than one thousand Bajaj three wheelers are running and it needs better optimization in order to achieve fuel saving thereby reducing the pollution. In this regard carburetor size was determined from the Bajaj three wheeler and it is simulated using Ansyss computational fluid dynamics software for different modification in fuel tube and size. Analysis has been done and different results were plotted, the results show there will be a better saving in fuel for modified design. The simulation has been done for different fuel tube size and modification of inlet obstacle. Modified design can be suggested to the manufacturer for the better performance thereby reducing the fuel consumption, environmental pollution and running cost of the Bajaj three wheeler.
Reserve Estimation of Initial Oil and Gas by using Volumetric Method in Mann ...ijtsrd
This research paper is focused to estimate the current production rate of the wells and to predict field remaining reserves. The remaining reserve depends on the production points that selected to represent the real well behavior, the way of dealing with the production data, and the human errors that might happen during the life of the field. Reserves estimating methods are usually categorized into three families analogy, volumetric, and performance techniques. Reserve Estimators should utilize the particular methods, and the number of methods, which in their professional judgment are most appropriate given i the geographic location, formation characteristics and nature of the property or group of properties with respect to which reserves are being estimated ii the amount and quality of available data and iii the significance of such property or group of properties in relation to the oil and gas properties with respect to which reserves are being estimated. In this research paper, the calculation of collecting data and sample by volumetric method are suggested to estimate the oil and gas production rate with time by using the geological configuration and the historical production data from CD 3700 3800 sand in Mann Oil Field. San Win "Reserve Estimation of Initial Oil and Gas by using Volumetric Method in Mann Oil Field" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27945.pdfPaper URL: https://www.ijtsrd.com/engineering/petroleum-engineering/27945/reserve-estimation-of-initial-oil-and-gas-by-using-volumetric-method-in-mann-oil-field/san-win
How can identify sensitivity of hydraulic characteristics of irrigation systems?AI Publications
Due to the benefits of center pivot irrigation system into the other techniques, especially surface irrigation, more accurate design of these systems for saving in water resources, increasing irrigation efficiency, and finally encourage farmers to use of this system (when using this method is economical), recognition of effective parameters on center pivot have a great importance. In this study, using PipeLoss software, amounts of pressure loss, friction slope, inflow velocity, velocity head, and Reynolds number in center pivot systems survived. The results showed that: Pipe inside diameter was more effective than other parameters. Changes of pressure loss, in all cases (except Qs), were the maximum. Changes of velocity head were the maximum in scenarios related to the changes of system discharge. In center pivot system design, should be noted to pipe inside diameter and system discharge as input and pressure loss as output, more than other inputs and outputs parameters.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
1. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 14
Research Publish Journals
Production Optimization Using Bean Size
Selection for Niger Delta Oil Wells
Idongesit Effiong Essen1
, Dulu Appah2
, Mfon Godwill Udoaka3
1,3
Department of Petroleum Engineering, University of Uyo, Uyo, Akwa Ibom State, Nigeria
2
Department of Petroleum and Gas Engineering, University of Port Harcourt, Choba, Rivers State, Nigeria
Abstract: The oil and gas production system requires energy in the form of pressure, and the choke plays an
important role in controlling the flow rate. In this work, Nodal Analysis method was used to optimize oil
production using bean size selection for two wells B40 and B50, respectively. PIPESIM was used to build the
models for the two wells using the test production data acquired. For well B40, when there is bean-up from 0.2” to
0.8”, flow rate increases from 363.957STB/D to 2132.306STB/D at bottomhole and 359.535STB/D to 1890.4
71STB/D at wellhead nodes, respectively. For well B50, when there is bean-up from 0.2” to 0.8”, flow rate increases
from 195.648STB/D to 4464.972STB/D at bottomhole and 500.005STB/D to 3870.941STB/D at wellhead nodes,
respectively. This is evident in the plots whereby the operating point shifts repeatedly to the right as the bean size
is increased successively. Finally, at the end of the study, the bean size for well B40 was re-selected from 0.25” (1/4)
at a flow rate of 605.171STB/D to 0.28” (17.92/64) at a flow rate of 728.019STB/D. Similarly, for well B50, the
initial bean size prior to optimization was 0.4” (25.6/64) and the flow rate was 1962.357STB/D. However, a bean-up
to 0.5” (1/2) produced at a flow rate of 2882.492STB/D thus production optimization is achieved.
Keywords: Optimization, Bean size, Flow rate, Wellhead pressure, Gas-oil ratio, Nodal Analysis.
1. INTRODUCTION
The oil and gas production system comprises of flow of hydrocarbon fluids from the reservoir to the surface production
facilities through the production tubing. It include inflow performance (flow from the reservoir into the wellbore), as well
as outflow performance (flow across the down-hole completion and restriction, safety valve, and up the tubing string to
the surface facilities).
In practice, all flowing wells make use of some surface restrictions in order to regulate the flowing rate. Only very few
wells are produced with absolutely no restrictions for getting maximum production rate [1]. The overall performance of a
production well is a function of several variables. Examples of these variables are tubing size, choke size, flow line size,
and perforation density. The flow rate (Q) is a measure of the rate at which a reservoir fluid is produced and is a function
of the perforation density, reservoir pressure, tubing size, choke/bean size, diameter of flow-line, and separator pressure
[2]. This implies that changing any of these variables will alter the performance of the well.
Surface or wellhead chokes are utilized in the oil and gas industry to regulate the flow rate so as to maintain well
allowable, to protect surface equipment, to prevent water and gas coning, and to provide the necessary backpressure to
avoid formation damage due to excessive drawdown [3].
There are numerous oil and gas wells around the world that have not been optimized to achieve the desired flow rate. The
implication is that the wells are not produced at the most efficient rate (MER). At times, large amounts of money have
been wasted on stimulating the formation when the well's producing capacity was actually being restricted because of
wrong choice of bean size. Implications of small bean size include low flow rate, unstable flow, and high gas-oil ratio
(HGOR).
2. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 15
Research Publish Journals
Another source of error in completion design is the installation of chokes/beans that are too large. This often happens on
wells that are expected to produce at high rates. Increased well performance can be achieved by larger bean size on the
wellhead. A bean size that is too large can actually increase the rate at which a well will flow, but if not properly
monitored, will result in high pressure drawdown which causes sanding and water production. This can also cause liquid
load up which leads to early depletion or eventual death of the well. In fact, many wells have been completed in this
manner and their maximum potential rate could not be achieved.
The first theoretical investigation on two phase flow across chokes was performed by [4]. However, this theory can be
useful when the phase is continuous and the gas liquid ratio is lower than one [4]. In 1960, a new theory based on
Tangren’s theory was proposed by Ros for a continuous gas phase. This analysis led to the development of an equation
relating mass flow of gas and liquid, upstream pressure and choke size [5]. To make Ros’ correlation available to oil field
workers, Poetmann and Beck converted the correlation to oil field units and reduced it to a graphical form [6].
In 1969, Omana, Brown, Brill and Thompson conducted experimental field tests at the facilities of Union Company of
California’s Tiger Lagoon Field in Louisiana to study the multiphase flow of gas and liquid (gas-water system) through a
small-sized choke in a vertical position, and used dimensional analysis to obtain their empirical equation [7]. In 1975, a
theoretical model relating dynamic orifice performance in both critical and sub critical flow regimes was developed [8].
Many empirical equations have been developed to estimate the relationship between production rate and wellhead
pressure for two-phase critical flow. The first empirical correlation for choke selection was done by Gilbert in 1954. He
developed an empirical correlation for critical flow through a choke. He used production data from flowing oil wells in
the Ten Section field of California [9]. Gilbert’s equation consists mainly of a three parameter equation in which the flow
rate is linearly proportional to the upstream pressure.
PWH (1)
Where ql is liquid production rate (bbl/day)
R is gas liquid ratio (SCF/STB)
PWH is the well or tubing head pressure (psig)
S is the bean size (1/64) inch
The second experimental relation was proposed by Baxendell in 1957. He revised Gilbert’s equation to update the
coefficients based on incremental data [10]. The revised equation of Baxendell is given by:
PWH (2)
The third experimental relation was proposed by Achong in 1961. He modified Gilbert’s equation to match the
performance of wells in Lake Maracaibo field in Venezuela [11]. The rate of multiphase flow through a choke, and the
upstream pressure are, according to Achong, correlated by the following relationship:
PWH (3)
Omana, Brown, Brill and Thompson carried out some experiments in the Tiger Lagoon field of Louisiana by using natural
gas and water flowing through restrictions [7]. In 1972, Fortunati introduced two correlations for subcritical and critical
flow through chokes [12].
In 1975, Ashford and Peirce developed a mathematical model relating dynamic orifice performance in both critical and
subcritical flow regimes [8]. In 1986, Sachdeva, Schmidt, Brill and Blais developed a model to calculate flow rate of a
choke by investigating a two-phase flow through wellhead chokes, including both critical and subcritical flow [13].
Ajienka and Ikoku analysed several correlations, including those by Gilbert, Baxendell, Ros, Achong, and Ashford, and
proposed two well models [1], [14].
In 1996, Elgibaly and Nashawi developed a correlation to describe the choke performance of the Middle-East oil wells
[15]. In 2007, Ghareeb and Shedid attempted to overcome the limitations of the existing correlations for artificially
flowing wells by developing a new correlation capable of calculating precisely the wellhead flow production [16]. In
2007, Alrumah and Bizanti used actual data production tests from vertical wells from Sabriyah fields in Kuwait to
3. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 16
Research Publish Journals
establish a new generalized multiphase flow choke correlation that predicts liquid flow rates as a function of flowing
wellhead pressure, surface choke size and gas-liquid ratio [17].
In 2015, Okon used sixty four (64) field test data from oil producing wells in the Niger Delta region of Nigeria to develop
wellhead pressure-production rate correlations based on Gilbert and modified Gilbert equations [18]. The developed
equation is given by:
PWH (4)
In 2014, Ebuka used an integrated production model (Prosper software) to optimize production in a mature Niger Delta
field where continuous declining rates greatly limited the economics for routine production optimization activities [19]. In
2007, Vidovic and Gluscevic optimized production in geothermal wells by performing system analysis at bottomhole and
wellhead nodes [20].
2. METHODOLOGY
The method deployed in this work is called “Nodal Analysis”. Nodal Analysis involves breaking the system into nodes
(characteristic points like tubing, wellhead, choke, etc.) in order to study the performance of the well with reference to
fluid flow variables (pressure, flow rate) at the nodes.
In this work, production was optimized by using nodal analysis method to select bean size for two oil wells B40 and B50.
The following sets of production data variables were acquired from the industry: bean sizes, flow rates, flowing tubing
head pressures, flowing tubing head temperatures, reservoir pressures, reservoir temperatures, tubing sizes, well depths,
and gas – oil ratios. Pipeline Simulation Module (PIPESIM) software simulator was used to build the models for the two
wells using the test production data acquired from the field. Simulation and choke sensitivity analysis was carried out at
two nodes of interest: bottomhole (Pwf) and wellhead (Pwh) for each of the wells. The sensitivity analysis was done by
simulating the different bean sizes with oil flow rates and pressures to study the effect of the bean size on the
inflow/outflow curves and the oil production operating points of the wells. The graphs depicting the sensitivity of
increasing or decreasing the choke sizes on the inflow and outflow (operating point) were also plotted.
3. RESULTS
The results for the bottomhole as well as the wellhead nodal analyses simulated for wells B40 and B50 are as presented
below:
Table 4.1 presents the operating points (coordinates of the intersection) of inflow and outflow curves (pressures and
corresponding flow rates) for each of the different bean sizes for Well B40 at the bottomhole node.
TABLE 4.1: WELL B40 BOTTOMHOLE NODAL ANALYSIS OPERATING POINTS
BEAN SIZE (inches) PRESSURE AT NA POINT (psia) LIQUID FLOWRATE AT NA POINT (STB/D)
0.20 4013.605 415.957
0.25 4000.000 685.824
0.28 3959.732 728.436
0.30 3919.463 929.208
0.40 3825.503 1275.978
0.50 3718.121 1685.516
0.70 3625.263 2029.920
0.80 3612.632 2132.306
1.00 3574.737 2271.923
1.50 3566.737 2327.077
2.00 3557.684 2337.769
3.00 3562.105 2365.001
NA – Nodal Analysis
Table 4.2 presents the operating points (coordinates of the intersection) of inflow and outflow curves (pressures and
corresponding flow rates) for each of the different bean sizes for Well B40 at the wellhead node.
4. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 17
Research Publish Journals
TABLE 4.2: WELL B40 WELLHEAD NODAL ANALYSIS OPERATING POINTS
BEAN SIZE (inches) PRESSURE AT NA POINT (psia) LIQUID FLOWRATE AT NA POINT (STB/D)
0.20 958.050 359.535
0.25 971.365 575.171
0.28 959.732 728.019
0.30 945.190 833.668
0.40 860.850 1210.690
0.50 793.960 1496.312
0.70 735.794 1816.209
0.80 724.161 1890.471
1.00 712.528 1970.445
1.50 711.409 2010.432
2.00 709.172 2016.145
3.00 702.461 2021.857
NA – Nodal Analysis
Table 4.3 presents the operating points (coordinates of the intersection) of inflow and outflow curves (pressures and
corresponding flow rates) for each of the different sizes for Well B50 at the bottomhole node.
TABLE 4.3: WELL B50 BOTTOMHOLE NODAL ANALYSIS OPERATING POINTS
BEAN SIZE (inches) PRESSURE AT NA POINT (psia) LIQUID FLOWRATE AT NA POINT (STB/D)
0.20 4394.183 195.648
0.25 4373.602 438.223
0.28 4342.729 705.056
0.30 4332.438 947.631
0.40 4239.821 1796.644
0.50 4136.913 2888.233
0.70 4023.714 4125.366
0.80 3982.550 4464.972
1.00 3941.387 4828.834
1.50 3920.805 5095.667
2.00 3917.207 5107.813
3.00 3910.515 5119.925
NA – Nodal Analysis
Table 4.4 presents the operating points (coordinates of the intersection) of inflow and outflow curves (pressures and
corresponding flow rates) for each of the different bean sizes for Well B50 at the wellhead node.
TABLE 4.4: WELL B50 WELLHEAD NODAL ANALYSIS OPERATING POINTS
BEAN SIZE (inches) PRESSURE AT NA POINT (psia) LIQUID FLOWRATE AT NA POINT (STB/D)
0.20 840.492 500.005
0.25 814.318 790.325
0.28 796.868 983.872
0.30 793.960 1139.784
0.40 738.702 1962.357
0.50 607.830 2882.492
0.70 465.324 3672.018
0.80 427.517 3870.941
1.00 389.709 4085.993
1.50 369.351 4193.518
2.00 365.403 4218.917
3.00 363.535 4220.400
NA – Nodal Analysis
Table 4.5 presents Well B40 flow characteristics at the wellhead node. The flow rate, pressure ratio, category of flow, and
flow regime is specified for each of the bean sizes. Any pressure ratio above 0.55 is not desirable because the choke will
not operate at critical flow, thus exposing surface equipment to pressure surges and consequent damage.
5. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 18
Research Publish Journals
TABLE 4.5: WELL B40 FLOW CHARACTERISTICS AT THE WELLHEAD NODE
BEAN SIZE
(inches)
FLOWRATE (STB/D) PRESSURE
RATIO
CATEGORY OF
FLOW
FLOW REGIME
0.20 359.535 0.53233 Critical Bubble
0.25 575.171 0.52528 Critical Bubble
0.28 728.019 0.52500 Critical Bubble
0.30 833.668 0.52500 Critical Bubble
0.40 1210.690 0.55720 Sub-critical Bubble
0.50 1496.312 0.56175 Sub-critical Bubble
0.70 1816.209 0.59726 Sub-critical Slug
0.80 1890.471 0.66602 Sub-critical Slug
1.00 1970.445 0.70003 Sub-critical Slug
1.50 2010.432 0.72576 Sub-critical Slug
2.00 2016.145 0.80344 Sub-critical Slug
3.00 2021.857 0.90836 Sub-critical Slug
Table 4.6 presents Well B50 flow characteristics at the wellhead node. The flow rate, pressure ratio, category of flow, and
flow regime is specified for each of the bean sizes. Any pressure ratio above 0.55 is not desirable because the choke will
not operate at critical flow, thus exposing surface equipment to pressure surges and consequent damage.
TABLE 4.6: WELL B50 FLOW CHARACTERISTICS AT THE WELLHEAD NODE
BEAN SIZE
(inches)
FLOWRATE
(STB/D)
PRESSURE
RATIO
CATEGORY OF
FLOW
FLOW REGIME
0.20 500.005 0.62213 Sub-critical Huge Liquid
0.25 790.325 0.56220 Sub-critical Huge Liquid
0.28 983.872 0.52528 Critical Huge Liquid
0.30 1139.784 0.52528 Critical Huge Liquid
0.40 1962.357 0.52500 Critical Huge Liquid
0.50 2882.492 0.52500 Critical Huge Liquid
0.70 3672.018 0.56220 Sub-critical Huge Liquid
0.80 3870.941 0.59816 Sub-critical Huge Liquid
1.00 4085.993 0.67765 Sub-critical Huge Liquid
1.50 4193.518 0.76041 Sub-critical Huge Liquid
2.00 4218.917 0.82823 Sub-critical Huge Liquid
3.00 4220.400 0.94493 Sub-critical Huge Liquid
Figure 4.1 presents well B40 bottomhole nodal analysis plot of inflow and outflow curves for different bean sizes. As the
bean size is increased successively from 0.2” to 3”, the outflow curves shift repeatedly to the right; hence the points of
intersection (operating points) also shift to the right. The plot is as shown below:
Fig.4.1: Well B40 Bottomhole Nodal Analysis Plot of Inflow and Outflow Curves for Different Bean Sizes
6. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 19
Research Publish Journals
Figure 4.2 presents well B40 wellhead nodal analysis plot of inflow and outflow curves for different bean sizes. As the
bean size is increased successively from 0.2” to 3”, the outflow curves shift repeatedly to the right; hence the points of
intersection (operating points) also shift to the right. The plot is as shown below:
Fig.4.2: Well B40 Wellhead Nodal Analysis Plot of Inflow and Outflow Curves for Different Bean Sizes
Figure 4.3 presents well B50 bottomhole nodal analysis plot of inflow and outflow curves for different bean sizes. As the
bean size is increased successively from 0.2” to 3”, the outflow curves shift repeatedly to the right; hence the points of
intersection (operating points) also shift to the right. The plot is as shown below:
Fig.4.3: Well B50 Bottomhole Nodal Analysis Plot of Inflow and Outflow Curves for Different Bean Sizes
Figure 4.4 presents well B50 wellhead nodal analysis plot of inflow and outflow curves for different bean sizes. As the
bean size is increased successively from 0.2” to 3”, the outflow curves shift repeatedly to the right; hence the points of
intersection (operating points) also shift to the right. The plot is as shown below:
7. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 20
Research Publish Journals
Fig.4.4: Well B50 Wellhead Nodal Analysis Plot of Inflow and Outflow Curves for Different Bean Sizes.
Figure 4.5A presents well B40 combined plots of inflow and outflow curves for both bottomhole and wellhead nodal
analyses (different bean sizes). At the optimum bean size, the flow rate at the bottomhole node is the same as the flow rate
at the wellhead node. The plot is as shown below:
Fig. 4.5A:Well B40 showing combined plots of Inflow and Outflow Curves for both Bottomhole and Wellhead Nodal Analyses
(different bean sizes)
Figure 4.6A presents well B50 combined plots of inflow and outflow curves for both bottomhole and wellhead nodal
analyses (different bean sizes). At the optimum bean size, the flow rate at the bottomhole node is the same as the flow rate
at the wellhead node. The plot is as shown below:
8. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 21
Research Publish Journals
Fig.4.6A:Well B50 showing combined plots of Inflow and Outflow Curves for both Bottomhole and Wellhead Nodal Analyses
(different bean sizes)
TABLE 4.7:WELL B40 SHOWING PRESSURE AND FLOWRATE BEFORE AND AFTER OPTIMIZATION
WELL B40 BEAN SIZE
(inches)
PRESSURE AT
WELL HEAD (psia)
PRESSURE
LOSS dP(psi)
FLOWRATE
(STB/D)
BEFORE OPTIMIZATION 0.25 (16/64 or 1/4) 971.365 668.084 605.171
AFTER OPTIMIZATION 0.28 (17.92/64) 959.732 469.928 728.019
Fig.4.7: Well B40 Nodal Analysis Plot of Inflow and Outflow Curves for initial and optimum bean sizes of 0.25” (before
optimization) and 0.28” (after optimization)
9. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 22
Research Publish Journals
TABLE 4.8: WELL B50 SHOWING PRESSURE AND FLOWRATE BEFORE AND AFTER OPTIMIZATION
WELL B50 BEAN SIZE
(inches)
PRESSURE AT
WH NODE (psia)
PRESSURE
LOSS dP (psi)
FLOWRATE (STB/D)
BEFORE OPTIMIZATION 0.40 (25.6/64) 738.702 360.921 1962.357
AFTER OPTIMIZATION 0.50 (32/64 or 1/2) 607.830 303.812 2882.492
Fig. 4.8: Well B50 Nodal Analysis Plot of Inflow and Outflow Curves for initial and optimum bean sizes of 0.40” (before
optimization) and 0.50” (after optimization)
TABLE 4.9: COMPARISON OF RESULTS FOR BEAN SIZE USING DIFFERENT CORRELATIONS
PARAMETERS RESULTS FOR BEAN SIZE (1/64”)
WELL Q (bbl/d) GOR
(SCF/
STB)
PWH
(psi)
SIMULA-
TED
GILBERT'S
CORR.
(EQN 3.5)
BAXENDELL'S
CORR
(EQN 3.6)
ACHONG'S
CORR.
(EQN 3.7)
OKON'S
CORR.
(EQN 3.8)
B40 728.00 543.00 959.80 17.92 18.02 16.57 15.55 14.25
B50 2882.49 148.20 607.50 32.00 32.66 29.67 26.33 28.39
Q – Flowrate; GOR – Gas-oil ratio; PWH – Wellhead pressure; CORR. – Correlation;
EQN - Equation
4. DISCUSSION
The discussion considers the sensitivity of the oil inflow and outflow rate to changes in the bean sizes of the choke. The
deduced results are studied with reference to the functions of pressure maintenance, surface equipment protection, flow
rate regulation, and bean up-bean down operations.
The oil inflow and outflow rate analysis was carried out on two oil wells (B40 and B50). Nodal analysis simulated results
on two nodes of interest (bottomhole and wellhead) was done to study the sensitivity of the point of coincidence of inflow
and outflow rate curves to changes in the bean sizes. This coincident point (which is the intersection of inflow and
outflow curves) defines the operating point. This implies that the pressure at the operating point is the optimum for the
corresponding flow rate, hence it satisfies the condition. If any change is made either in the inflow or outflow, then only
that curve will be shifted and the other will remain the same, but the operating point (intersection) will also change. For
this work, the sensitivity analysis was studied by using different bean sizes at the choke.
10. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 23
Research Publish Journals
Tables 4.1 and 4.2 show the well B40 simulated results for the bottom hole and wellhead nodal analyses respectively. The
two tables present the coordinates of the intersection of inflow and outflow curves (pressures and corresponding flow
rates) for each of the different bean diameters. These points of intersection are the operating points for each of the
different bean sizes because the pressures and flow rates at those points satisfy the conditions for well B40.
Similarly, Tables 4.3 and 4.4 show the well B50 simulated results for the bottom hole as well as the wellhead nodal
analyses. The two tables present the coordinates of the intersection of inflow and outflow curves (pressures and
corresponding flow rates) for each of the different bean diameters. These points of intersection are the operating points for
each of the different bean sizes because the pressures and flow rates at those points satisfy the conditions for well B50.
Here the sensitivity analysis was carried out on the outflow by using different bean sizes to study the relationships and
variations in the corresponding operating points (pressures and flow rates) to changes in bean sizes. From the tables, it is
observed that as the bean size increases, the nodal point pressure reduces while the corresponding flow rate increases.
This implies that increasing the bean size results in increased oil production.
In Table 4.1 for well B40 bottomhole nodal analysis, a bean size of 0.20” (12.8/64) produced a flow rate of 363.957STB/d
at a pressure of 4013.605psia. However, with a bean size of 0.3” (19.2/64), the pressure is 3919.463psia while the flow
rate is 829.208STB/d. As the bean size is further increased progressively to 0.8” (51.2/64), the pressure reduces to
3612.632psia and the corresponding flow rate increases to 2132.306STB/d.
Also, in Table 4.2 for well B40 wellhead nodal analysis, a bean size of 0.20” (12.8/64) produced a flow rate of
359.535STB/d at a nodal point pressure of 958.050psia. However, with a bean size of 0.3” (19.2/64), the pressure is
945.190psia while the flow rate is 833.668STB/d. As the bean size is further increased progressively to 0.8” (51.2/64), the
pressure reduces to 724.161psia and the corresponding flow rate increases to 1890.4716STB/d.
Similarly, in Table 4.3 for well B50 bottomhole nodal analysis, a bean size of 0.20” (12.8/64) produced a flow rate of
195.648STB/d at a pressure of 4394.183psia. However, with a bean size of 0.3” (19.2/64), the pressure is 4332.438psia
while the flow rate is 947.631STB/d. As the bean size is further increased progressively to 0.8” (51.2/64), the pressure
reduces to 3982.550psia and the corresponding flow rate increases to 4464.972STB/d.
Table 4.4 for well B50 wellhead nodal analysis follows the same trend. With a bean size of 0.2”, the pressure is
840.492psia while the flow rate is 500.005STB/d. A bean size of 0.3” produces a flow rate of 1139.784STB/d at a
pressure of 793.960psi. However, as the bean size is further increased to 0.8”, the pressure reduces to 427.517psia and the
corresponding flow rate increases to 3870.941STB/d.
Tables 4.5 and 4.6 present Wells B40 and B50 flow characteristics at the wellhead node. The flow rate, pressure ratio,
category of flow, and flow regime is specified for each of the bean sizes. Any pressure ratio above 0.55 is not desirable
because the choke will not operate at critical flow, thus exposing surface equipment to pressure surges and consequent
damage. Sub-critical flow is only desirable at the subsurface conditions.
Figures 4.1 and 4.2 show the plots of well B40 inflow and outflow curves for bottomhole and wellhead nodal analyses
respectively. From the two figures, the intersections of inflow and outflow curves (the operating points) are observed to
follow a common trend. As the bean size is increased successively from 0.2”, the outflow curves shift repeatedly to the
right; hence the points of intersection (operating points) also shift to the right. This implies that as the bean size is
increased, it causes the operating point to also shift to the right, thus the flow rate increases, indicating that more oil is
produced.
Similarly, Figures 4.3 and 4.4 show the plots of well B50 inflow and outflow curves for bottomhole and wellhead nodal
analyses respectively. From the two figures, the intersections of inflow and outflow curves (the operating points) are
observed to follow the same trend as that of well B40. As the bean size is increased, the outflow curves shift to the right;
hence the points of intersection (operating points) also shift to the right, causing the flow rates to increase, and
consequently resulting in the production of more oil.
Figure 4.5A shows well B40 combined plots of inflow and outflow curves for both Bottomhole and Wellhead Nodal
Analyses (with different bean sizes). These two sets of curves on the same graph show that the intersection (operating
points denoted by A and B respectively) with regards to the x-axis (which is the flow rate, denoted by point C) is the same
at both bottomhole and wellhead nodal points. From Figure 4.5A, a bean size of 0.28” produced oil at a flow rate of
11. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 24
Research Publish Journals
726.824STB/d. Hence, this quantity of produced fluid or flow rate is the same at both bottomhole and wellhead nodal
points, which is in agreement with the mass preservation law which states that “for any system closed to all transfers of
matter and energy, the mass of the system must remain constant over time, as the system mass cannot change quantity if it
is not added or removed”. Therefore, the optimum bean size for well B40 is 0.28” or 18/64 because it produces
726.824STB/d at both bottomhole and wellhead nodal points, thus obeying the mass preservation law which states that
“for any system closed to all transfers of matter and energy, the mass of the system must remain constant over time, as the
system mass cannot change quantity if it is not added or removed”.
Similarly, Figure 4.6A shows well B50 combined plots of inflow and outflow curves for both Bottomhole and Wellhead
Nodal Analyses (with different bean sizes). These two sets of curves on the same graph show that the intersection
(operating points) with regards to the x-axis (which is the flow rate) is the same at both bottomhole and wellhead nodal
points. From Figure 4.5A, a bean size of 0.50” (32/64) produced at a rate of 2882.233STB/d. Hence, this quantity of
produced fluid or flow rate is the same at both bottomhole and wellhead nodal points, which is in agreement with the
mass preservation law. Therefore, the optimum bean size for well B40 is 0.50” or 32/64. Figure 4.6B shows the operating
points for the optimum bean size of 0.5” denoted by letters A and B. Point C is the common flow rate of 2882.233STB/d
for the two nodal points.
Table 4.7 presents well B40 wellhead nodal point pressure of 971.365psia, a flow rate of 605.171STB/d and a pressure
drop of 668.084psi with an initial bean size of 0.25” (16/64) prior to optimization. However, after optimization, the
optimum bean size is 0.28” (17.92/64), pressure is 959.732psia at a flow rate of 728.019STB/d and pressure loss of
469.928psi.
Figure 4.7 shows well B40 operating points prior to optimization (point B) and after optimization (point A). The shift
from point A to B implies increased production. Similarly, Table 4.8 presents well B50 wellhead nodal point pressure of
738.702psia, a flow rate of 1962.357STB/d and a pressure drop of 360.921psi with an initial bean size of 0.4” (25.6/64)
prior to optimization. However, after optimization, the optimum bean size is 0.5” (32/64), pressure is 607.830psia at a
flow rate of 2882.4929STB/d and pressure loss of 303.81psi.
Figure 4.8 shows well B50 operating points prior to optimization (point B) and after optimization (point A). The shift
from point A to B implies increased oil production from 1962.357bbl/d to 2882.492bbl/d.
Table 4.9 shows the comparison of the bean size results using different correlations. For Well B40, the Gilbert’s
correlation (Equation 3.5) gave 18.02”, Baxendell’s correlation (Equation 3.6) gave 16.57”, Achong’s correlation
(Equation 3.7) gave 15.55”, and Okon’s correlation (Equation 3.8) gave 14.25”. For Well B50, Gilbert’s correlation gave
32.66”, Baxendell’s: 29.67”, Achong’s: 26.33” and Okon’s: 28.39”. The results gotten from this research are closest to
those of Gilbert’s correlation as shown in Table 4.9.
5. CONCLUSION
The importance of facilities re-designs (reselection of bean sizes after a period of time) in oil and gas production
operations cannot be overemphasized. This is because of effects resulting from a bean size being too small {unstable
flowrate, high gas oil ratio (HGOR), Rsi greater than 3} or too big (sand and water production). It is therefore imperative
to choose an optimum bean size so as to prevent the production of unwanted fluids at the early stage, and to maintain
stable deliverability, thus producing the reservoir at the most efficient rate (MER).
The results of the production optimization using bean size selection through nodal analysis method, performed on two oil
wells B40 and B50 at both bottomhole and wellhead nodes show that:
1. The flow rate increases with increase in the bean size, which implies that oil production also increases with increased
bean size (Tables 4.1, 4.2, 4.3 and 4.4.). In well B40, when bean size is 0.2”, flow rate is 363.957STB/D and
359.535STB/D; when bean size is 0.4”, flow rate is 1275.978STB/D and 1210.690STB/D; when bean size is 0.8”,
flow rate is 2132.306STB/D and 1890.471STB/D at bottomhole and wellhead nodes respectively.
2. The operating point (intersection of inflow and outflow curves) shifts repeatedly to the right as the bean size is
increased successively (Figures 4.1, 4.2, 4.3 and 4.4).
12. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 25
Research Publish Journals
3. At the optimum bean size, the flow rate at the bottomhole node is the same with that of the wellhead node, thus the
law of conservation of mass is obeyed (Figures 4.5A, 4.5B, 4.6A and 4.6B). At optimum bean size of 0.28” for well
B40, the flow rate is 728.019STB/D at both bottomhole and wellhead nodes.
4. Nodal point pressures at the bottomhole node are higher in values than those of the wellhead node. This is because of
the pressure losses at the vertical section of the tubing. (Tables 4.1, 4.2, 4.3 and 4.4). In well B40, at a bean size of
0.2” the bottomhole pressure is 4013.605psia and wellhead pressure is 958.050psia; at a bean size of 0.5”, the
bottomhole pressure is 3718.121psia while the wellhead pressure is 793.960psia.
REFERENCES
[1] Ajienka, J. A. and Ikoku, C. U. (1987). A Generalized Model for Multiphase Flow Metering, SPE Paper 17174-MS
presented at the Tenth Annual International Conference of Society of Petroleum Engineers held in Lagos, Nigeria,
pp. 2 – 6.
[2] Carroll, J. A. (1990). Multivariate Production Systems Optimization, A Report Submitted to the Department Of
Petroleum Engineering and The Committee on Graduate Studies of Stanford University, pp. 4 – 6.
[3] Nasriani, H. R. and Kalantariasl A. (2011). Two Phase Flow Choke Performance in High Rate Gas Condensate
Wells, presented at Society of Petroleum Engineers Asia Pacific Oil and Gas Conference and Exhibition held in
Jakarta, Indonesia, pp. 5 - 7.
[4] Tangren, R. F, Dodge, C. H. and Seifert, H. S. (1949). Compressibility Effects in Two-Phase Flow, Journal of
Applied Physics, 20(7): 637 - 645.
[5] Ros, N. C. J. (1960). An Analysis of Critical Simultaneous Gas/liquid Flow through a Restriction and its Application
to Flow Metering, Applied Science Research, 9(1): 374–388.
[6] Poettmann, F. H. and Beck, R. L. (1963). New Charts Developed to Predict Gas-Liquid Flow through Chokes,
World Oil (March 1963), pp. 95-101.
[7] Omana, R, Houssiere, C. Jr, Brown, K. E, Brill, J. P, and Thompson, R. E. (1969). Multiphase Flow through Chokes,
SPE Paper 2682 presented at the 44th
Society of Petroleum Engineers Annual Meeting held in Denver, Colorado on
September 28 – October 1, pp. 9 - 14.
[8] Ashford, F. E. and Pierce, P. E. (1975). Determining Multiphase Pressure Drops and Flow Capacities in Down-hole
Safety Valves, Journal of Petroleum Technology, (September), 27(1): 1145 - 1152.
[9] Gilbert, W.E. (1954). Flowing and Gas-Lift Well Performance. API Drilling and Production Practice, 143(1): 126 -
157.
[10] Baxendall, P. B. (1957). Bean Performance--Lake Wells, Internal Report (October), pp.4 – 8.
[11] Achong, I. (1961). Revised Bean Performance Formula for Lake Maracaibo Wells, Shell Internal Report (October),
pp. 13 – 17.
[12] Fortunati, F. (1972). Two Phase Flow through Wellhead Chokes, SPE Paper 3742 presented at the Society of
Petroleum Engineers European Meeting, Amsterdam, May 17 – 18, pp. 14 – 19.
[13] Sachdeva, R, Schmidt, Z, Brill, J. P. and Blais, R. M. (1986). Two-Phase Flow through Chokes, SPE Paper 15657,
presented at the Society of Petroleum Engineers 61st Annual Technical Conference and Exhibition, New Orleans,
October 5 – 8, pp. 1 – 12.
[14] Ajienka, J. A. (2005). Christmas Tree, Tree of Life, Tree of Knowledge. An Inaugural Lecture Series No. 47,
University of Port Harcourt, Rivers State, December 15, p. 47.
[15] Elgibaly, A. A. M. and Nashawi, I. S. (1996). Prediction of Two-Phase Flow through Chokes for Middle – East Oil
Wells.SPE Paper 36274 presented at 7th
Abu Dhabi International Society of Petroleum Engineers Exhibition and
Conference held at Abu Dhabi, United Arab Emirate, October 13 – 16, p.12.
13. International Journal of Engineering Research and Reviews ISSN 2348-697X (Online)
Vol. 5, Issue 1, pp: (14-27), Month: January - March 2017, Available at: www.researchpublish.com
Page | 26
Research Publish Journals
[16] Ghareeb, M. and Shedid, A. S. (2007). A New Correlation for Calculating Wellhead Production Considering
Influences of Temperature, GOR, and Water-Cut for Artificially Lifted Wells, International Petroleum Technology
Conference, Dubai, United Arab Emirate, pp. 23 - 27.
[17] Alrumah, M. K. and Bizanti, M. S. (2007). New Multiphase Choke Correlations for Kuwait Fields, SPE Paper
105103-MS presented at the Society of Petroleum Engineers Middle East Oil and Gas Show and Conference held in
Manama, Kingdom of Bahrain on March 11 – 14, pp. 1 – 4.
[18] Okon, A. N, Udoh, F. D. and Appah, D. (2015). Empirical Wellhead Pressure-Production Rate Correlations for
Niger Delta Oil Wells, SPE Paper 178303-MS, presented at the SPE Nigeria Annual International Conference and
Exhibition held in Lagos, Nigeria on August 4 – 6, pp. 2 - 8.
[19] Ebuka, U. G, Egelle, E, and Ogbunude, B. (2014). Integrated Production Systems Optimization: A mature Niger
Delta Field Case Study. International Journal of Science and Research (IJSR) Volume 3 Issue 8, August 2014.
[20] Slobodan Vidovic and Andreja Gluscevic. (2007). Optimization of Geothermal Wells and Production Systems,
Proceedings European Geothermal Congress, Unterhaching, Germany. 30 May-1 June, pp. 1 – 3.