Flow assurance deals with all issues that may arise in the flowline and can cause the flow not to happen properly. It deals with issues like slugging, hydrate formation, the flow of waxy fluids, multiphase flow prediction, etc.
Flow assurance studies can be categorized to steady-state studies and transient studies.
Steady-state flow assurance studies help to draw a clear picture of the flowing system. Steady-state studies results help to understand phase behavior, operational limitations, etc.
For example, knowing what happens in turndown operation, winter, and summer conditions, different feed characteristics help to predict the borderlines of a safe operational area.
The steady-state hydraulic model is used to determine pipeline size. The criteria for line sizing is pressure constraints, erosion velocity limits, and flow regime. All steady-state prediction models assume that pressure, temperature, and physical properties of the fluid remains constant with time. But in the real world, they change with time. However, single-phase pipeline sizing by steady-state hydraulic modeling usually leads us to acceptable results.
There are general guidelines for determining pipeline size as follows:
For oil/gas gathering pipelines from wellhead to processing plants take 1/3 of the difference between wellhead pressure and separator pressure as allowable pressure drop.
As a rule of thumb, for long gas/condensate pipelines, allow 10-20 psi per mile (0.04-0.08 bar/100m) frictional pressure drop at design rate.
Allowable velocity for liquid lines is 1-2 m/s and for gas lines is 5-10 m/s. Continuous operation above 4 m/s for liquids and 20 m/s for gases should be avoided.
In order to avoid corrosive situations, liquid lines containing a separate water phase, should not be operated at too low velocities (below 1 m/s). This is important at turndown flow conditions, especially in the presence of a considerable amount of H2S or CO2.
According to API RP-14E, the maximum design velocity in the pipeline which is erosion velocity can be calculated from the following formula: Vmax = C/ sqrt(Pns) Where: Vmax=maximum mixture velocity, ft/s Pns=No-slip mixture density, lb/ft3 C=constant, 100 for continuous services, 125 for intermittent services
Phase Equilibrium and physical properties
Accurate prediction of the phase behavior of flowing fluid is essential in predicting operational constraints. Steady-state simulators generally have two models to predict physical properties. Black Oil model and Compositional Model. The black oil model uses some correlations to predict physical properties using two basic properties like specific gravity of oil and gas and boiling point. The compositional model uses an equation of state to predict all physical properties at a given temperature and pressure.
For gas-condensate systems, the compositional model shall be used. For lower gas-condensate ratios selection of the best model is difficult. The compositional model may not be as good as the Black oil model. The general practice with steady-state simulators is using the black oil model for gas oil ratios less than 3500 SCF/bbl.
Heavy ends in well fluids are usually characterized by Pseudo components or cuts. Usually, components heavier than Hexane (C6+) are demonstrated by one or more cuts. Generally, the more the number of cuts, the more accurate predictions will get. Simulators usually use two or more physical properties for modeling a heavy cut, e.g. molecular weight and normal boiling point. These properties are the results of PVT analysis.
Pipeline Elevation profile
Specifying pipeline elevation profile in the simulation should be done with great accuracy, because it may have a significant effect on pressure drop calculation. For example, a liquid holdup in inclined pipe sections with upward flow direction is greater than holdup in a downward flow. Hence, the elevational pressure drop in the uphill part is higher than the pressure recovery in the downhill part.
Interpretation of results
Ideally, a pipeline should not be operated in a slug flow regime, but in practice, it may be very difficult to design a line to avoid slug flow. Generally, to change the flow regime in a slugging pipeline, the designer can take three different actions which are: reducing the pipe size, increasing pipeline operating pressure (e.g. by choking the flow at the wellhead), and using the gas lift in the wells. However, it should be noted that pipelines may be operated successfully in slug flow as long as the downstream equipment is designed for slugging effects.
Simulation results may show that the flow regime is stratified which is an excellent flow regime. But, in turn down operations, terrain-induced slugging may happen which may cause severe operating conditions.
For most pipelines, the worst conditions for liquid holdup and slugging happen at extreme operating conditions like turndown flow, very high/ very low ambient temperatures, rich gas /condensate mixtures, etc. Simulation results for these cases should also be investigated.
This article explains a method to determine the location factor as a crucial item in determining the fate of industrial projects during a feasibility study. It is based on historical data of oil & gas projects executed in Iran, but the methodology is applicable anywhere in the world.
In countries where there are not well-documented data of project costs, determining the location factor cannot be easily and accurately achieved. In this article, a method described by AACE is used and all local data are developed based on Corporate past experiences in the projects executed in Iran.
Using a well-known method such as AACE’s practice to determine the location factor empowers the feasibility study report and can convince capital investors and bankers that a reliable and sound analysis can lead them to a good judgment for investment.
The results show that the Location Factor for Iran is 0.89.
In the economically declining world and in the era of stagnation and depression, where profit rates are in a continuous declining track, the results of a feasibility study which specifies whether an investment should be financed and executed, becomes even more important than before and is a determining factor in project study and execution.
It is important to note that industrial firms are now multinational and they execute projects in various countries. Hence, it is becoming increasingly important for cost estimators to be able to estimate the cost of a project in different countries. Cost estimators may be very well familiar with the rates and cost data in their home country, but they are not necessarily familiar with other countries’ cost data sources.
Usually there is not enough data available about the target location, and since during the feasibility study the project is at its early stages, estimators must use cost indexes, location factors and historical cost data.
A location factor is a way of converting the cost of a plant from one geographical location to another location. It is defined as the ratio of the investment cost of a plant in a specific location to the cost of the same plant when built in the base location.
The location factor must be indicative of the local labor productivity, wages, main equipment and bulk material costs, freight, tax, custom duty, engineering and project management rates, etc. and it requires a well-formulated basis and well-registered data.
Location Factor Determination
The methodology used in this article is based on the Factoring method, described in AACE Recommended Practice 28R-03 [Ref. 1], which relies on a relationship between the cost of the main equipment and the other non-equipment cost items. This relationship is quantified by a set of factors, which are called distribution factors. In this method, the cost of the main equipment is first determined and then all other costs are estimated using appropriate factors.
Using factoring method to determine the location factor involves:
developing the distribution factors for base location. Base location is usually taken as the US Gulf Coast ;
determining the distribution factors for target location considering the differences in local labor, material and equipment factors, etc;
calculating the ratio of the new estimate to the base estimate to determine the location factor.
Developing Location Factor for Iran
Considering that the AACE method been used in order to be acceptable for international financers, therefore, a US split of costs has been used. A set of rather simplified distribution factors is used here, which is a cost breakdown for a typical US chemical plant:
Items of cost
Engineering/Procurement Service/ Field Indirect
Table 1: Historical US split of costs for a typical chemical plant (Based on AACE practice 28R-03)
As can be seen, labor and services, which are essentially determined by local rates, have a significant effect on the total, around 50%.
Based on the above factors for base location, the breakdown in the target location is evaluated. Parameters like labor rate, labor productivity, the percentage of the material procured locally and the local add-on costs like freight rate, duty and tax are major items, which affect the distribution factors. These parameters are categorized as follows:
% of locally produced equipment and bulk material
% of local and non-local workforce
% of local and non-local engineering workforce
Import add-on costs:
% custom duty, % freight, % VAT
Local material factor
Labor rate for construction:
Construction all-in rate, labor productivity
Labor rate for services:
Engineering all-in rate, engineering productivity
Table 2, Summarizing the Parameters Affecting the Location Factor
Relative cost differences between locally supplied equipment and material and imported items, and also the degree of import material are among parameters that affect the location factor.
Labor rate for construction, engineering and project management, labor productivity and the extent of using non-local workforce are also important parameters.
Labor productivity is usually determined by comparing the man-hour required to do a specific job at base location to the same job in target location. Productivity is affected by parameters like sociological factors, location-specific parameters, project and contract characteristics, human factors, field organization and management factors.
There are some methods to determine productivity. Some companies develop worksheets and checklists to evaluate productivity. Another method is using Monte Carlo statistical modeling technique [Ref. 3].
Maria Santacreu, 2015 [Ref.2] suggested a method to determine local productivity, based on easily measurable and country-specific variables: GDP. This method is used in this article to drive Iran’s productivity in Section 3.
General facts about Iran
Iran has huge deposits of oil and gas, has plenty of educated population, and many skilled workers who have industrial experience with mega projects.
Type of government
Tehran, 12.5 million
1,650,000 sq km
79.70 million *
Ocean freight from USA
39000 Rials/ $
Table 3, General Facts about Iran * CBI. Key Economic Indicators report. No. 85. (2016-17), [Ref. 5]
Distribution Factors for Iran
There is not much information available about how expensive is the total cost of a project in Iran relative to other countries. Cost data used in this paper is based on the recent projects executed in Iran.
The following figures can be indicative of the projects performed in Iran:
General engineering and supervision services: 100% local (except for patented licensed units)
Fabrication and installation of fixed equipment: 95% local
Fabrication of machinery equipment: 20% local
Installation of machinery: 100% local
Fabrication and installation of electrical bulk material: 100% local
Fabrication of instrumentation bulk material: 10% local
Installation of instrumentation: 100% local
Fabrication of piping bulk material: 90% local for carbon steel piping and 20% for stainless steel/ alloy piping
Installation of piping material: 100%
Fabrication and installation of civil and structure: 100% local
The local material index is the ratio of the local prices supplied by a local supplier to the one in the USA.
Based on the history of the projects executed in Iran, this factor is estimated. It is 0.9 for main equipment and 0.8 for bulk material.
Table below summarizes above figures, which will then be used to determine the local distribution factors:
Local Main Equipment Index (LMI):
Local Bulk Material Index (LBMI):
% Locally Procured Equipment:
% Locally Procured Bulk Material:
All-In Rate For Local Construction Workforce:
23 $/h (1)
All-In Rate For Local Engineering Activities:
35 $/h (1)
Standard All-In Rate For Expat (WE) Construction Activities:
Standard All-In Rate For Expat (WE) Engineering Activities:
Local Construction Labor Productivity:
Local Engineering Services Productivity:
Expat Construction Labor Productivity:
Expat Engineering Services Productivity:
Table 4, Determining the Distribution Factors for Iran Note 1: All-in rate includes base wage plus 15-30% for total fringe benefit, 5-10% for supervision, 15-20% for insurance, 15-20% for overheads, 10-15% for profits [Ref. 4].
Using the data in above table, the local distribution factors are determined as follows:
Engineering/Procurement/ Field Indirect
Location Factor = 2.55 / 2.86 =0.89
Table 5, Distribution Factors for Iran
The location factor of 0.89, which is less than 1.0, is indicative of:
The lower labor rate, which is typical of the Developing countries;
Globalization of education and availability of training / software / hardware, which increase the productivity of the skilled workers in the developing countries;
Industrialization of Iran and many other developing countries.
The above two points are the main reasons that the capital investment in industrialized developing countries, has been increased.
Table 6, Location factors for some countries Reference: Compass International [Ref. 4]
Productivity Estimation Methodology
Labor productivity varies significantly from country to country. Cost estimators collect the data on area productivity to be accounted for in their cost estimation. Typically, one area is selected as the base location with productivity of 1.0. Other location’s productivity is measured relative to the base area (usually, USA, Washington DC). Productivity less than 1.0 means it is more productive and productivity greater than 1.0 means less productive.
One of the methods to determine the productivity in a specific country is comparing the GDP relative to GDP of USA.
Gross Domestic Product (GDP) per capita (or GDP/ hours worked), are often used to determine labor productivity. GDP per capita is reported for every country. GDP/ hours worked can be calculated using the following equation [Ref. 2]:
Iran’s productivity can then be calculated as the ratio of GDP/ hours worked for US per GDP/ hours worked for Iran:
1- Economically active population: The economically active population comprises the population of 10 years old and over (minimum defined age) who either participated in the production of goods and services (were employed), based on the definition of labor, in the immediate week before the data collection week (reference week) or were unemployed but capable of participation. (Reference: CBI Annual Review-[Ref. 6]) 2-Unemployment: According to Iran’s Statistics Department, all people older than 10 years who work at least one hour during the week are called employed. 3- Working hours: working hours in the base year, 2015 (1394 in Iranian calendar) was 1943 hours, taking into account bank holidays and annual leave. Average workers worked 1707 hours in the United States in 2015.
Location factor is an indicative factor parameter for the level of industrialization of a country, the country’s infrastructure, the availability of skilled workers, the labor rate, etc.
This parameter has a considerable effect on the results of feasibility studies and can change the fate of the business decisions. Hence, it is important to determine the location factor with good accuracy. It is also important that the location factor be updated regularly.
In 1930, Hydrate management started to become the biggest challenge in the pipeline. Pipelines blocked by ice-like plugs which are crystalline compounds that occur when water forms a cage-like structure around smaller guest molecules. Hydrate looks like water ice but its properties are much different. It’s been known as burning ice because it burns when it gets closed to a lighted match.
Hydrate normally forms in one of the repeating crystal structures: structure I (SI), structure II (SII), structure H (SH). Structure I (SI) is a body-centered cubic structure form with small natural gas molecules found in deep oceans. Structure II (SII), is a diamond lattice within a cubic framework, which forms when natural gases or oils contain molecules larger than ethane but smaller than pentane. Structure II (SII) commonly occurs in hydrocarbon production and processing conditions. Structure H (SH) named for its hexagonal framework has cavities large enough to contain molecules the size of common components of naphtha and gasoline.
The three major elements of hydrate formation are:
Water either free, dissolved or in vapor phase
Hydrocarbon molecules: molecules ranging in size from methane to Butane including CO2, H2S, N2.
Low temperature and high pressure (e.g. 4°C and 20 barg or 20°C and 100 barg)
And the three conditions which favor hydrate formation are:
There are different statements in literature about importance of free water in hydrate formation. Previously, it was believed that free water phase is essential and pipelines don’t usually have enough residence time for hydrates to form from water vapor in gas phase. But recently, cases have been observed where hydrate forms in gases containing water vapor, without free water condensation. Hydrate from water vapor forms snow-like particles which may form a plug in restrictions. Although free water is not essential, but it enhances the hydrate formation very much. In addition, Gas –water interface is a good nucleation site for hydrate.
Hydrate causes many operational problems like blocking of pipeline, valves and instruments, plugging of heat exchangers, etc. This is specially important in control valves which have small orifices
Hydrate formation is usually a problem in gas flowlines but not in oil flowlines (except for areas such as ultra-deep offshore production) because:
Oil systems mainly contain heavier hydrocarbons like C5+ which are not hydrate forming molecules. In addition, they interfere with the growth of hydrate crystals.
Produced water from oil wells contains salts, whereas the water accompanying a gas is generally condensed fresh water. Electrolytes inhibit substantially the formation of hydrates (1C by 20g/l of equivalent of NaCl)
Hydrate Management: Inhibition
There are four classical mitigations for Hydrate formation:
Remove water from the system, generally by the Glycol process. This method is reliable and mainly used for drying gases for gas export. This method may not be cost-effective for gases at wellheads or at the flowlines entry.
Temperature preservation, keeping the temperature above the hydrate formation region by heating or insulating the lines.
Hydrate inhibitor injection. Continuous injection of inhibitors is cost-effective only for systems with low water contents and required temperature depression of 15-20° C. Two different types of inhibitors are available: 1- Thermodynamic inhibitors (THI) like Methanol and Glycols act like anti-freeze chemicals and displace the hydrate region. 2- Low dosage hydrate inhibitors (LDHI), including Kinetic hydrate inhibitors (KHI) and Anti-agglomerates (AA). Kinetic inhibitors prevent hydrate crystal growth and anti-agglomerates use a surfactant to stabilize the water-hydrate phase as small droplets in the liquid phase and prevents hydrate growth at the agglomeration stage.
Glycol vs. Methanol
Among all types of glycols, TEG and TREG are too soluble and too viscous for general use. The most popular inhibitors are MEG, DEG, and methanol. Methanol may be used effectively at any temperature. DEG is not recommended below -10°C because of its viscosity and the difficulty of separation if the oil is present. Above -10°C it might be preferred as there is less vaporization on loss than MEG or Methanol. Recovering methanol is not economical. However, if the gas stream is dried downstream in a TEG unit, methanol can be easily recovered in the TEG regenerator overhead.
Generally, using Glycol is economic where the amount of gas to be inhibited is considerable and continuous injection is required. While Methanol is usually used for temporary usages, low gas volumes, and where the required temperature depression is not much.
As a rule of thumb glycol units are used when required methanol injection exceeds 120 l/h.
The minimum inhibitor concentration may be calculated by semi-empirical correlation of Hammerschmidt or by using computer simulation.
Hammerschmidt equation matches very well with laboratory equilibrium data for hydrate inhibition with methanol solutions up to about 25% and glycol to about 60-70%:
W: Inhibitor concentration in liquid water, wt%
Δt: Hydrate formation temperature depression
M: Inhibitor molecular weight
Ki: 1297 for Methanol, 2220 for MEG & DEG
For methanol concentrations up to 50% the Nielsen-Buckling correlation provides better accuracy:
In practice, the amount of required inhibitor depends on system configuration, location and method of injection, system dynamics, etc. Most operators adjust injection rate by try and error during start-up.
Typically, the required free water concentration of methanol in onshore pipeline is 20 wt% while for offshore pipeline, it may exceed 50 wt% due to high pressures. A recent study has shown that hydrate in under-inhibited systems with methanol, forms faster and hydrate plugs stick to the pipe wall more aggressively.
For more accurate estimation of hydrate formation temperature, computer simulation is recommended. The available commercial software for hydrate prediction are:
PVTSim from Calsep, which can be linked to various simulation software like Olga.
Multiflash from Infochem; ‘Multiflash Hydrate Package’ is an optional add-on to Multiflash package in Pipesim.
‘DBR Hydrate’ package which is part of Pipeflo from Neotec
In order to estimate the required inhibitor flow rate, following steps should be followed:
Develop phase envelope together with hydrate equilibrium curve.
Simulate the pressure – temperature profile in the system at the worst case operating conditions.
Estimate the amount of subcooling in the system relative to hydrate formation curve.
For Δt<25°C consider kinetic inhibitors and for Δt>25°C, consider the use of thermodynamic inhibitors.
Draw hydrate formation curve in systems containing different amount of inhibitors in order to locate the system P-T at the ‘no hydrate’ zone of P-T curve. (See figure 2)
Inhibitor loss includes:
The amount of inhibitor lost to the gas phase
The amount of inhibitor lost to the condensate phase
The amount of inhibitor lost in regeneration system
Methanol is very volatile and its loss to the vapour phase is considerable. Methanol vaporisation loss can be estimated from figure 3.
Glycols, however, have very low vapor pressure and its vapor phase loss is very small.
As a rule of thumb, at 4°C and P>68 barg maximum amount of methanol loss to vapor phase is 1 lbm/MMscf for every wt% Methanol in free water phase. And for glycol the maximum amount of its loss to vapor phase is 0.002 lbm/MMscf of gas.
Methanol dissolves in paraffinic, naphthenic and aromatic hydrocarbons, but its solubility in aromatics is much better relative to paraffinic hydrocarbons. Methanol solubility in liquids depends on temperature and methanol concentration.
As a rule of thumb, Methanol concentration dissolved in condensate is 0.5 wt%. And for MEG, mole fraction of MEG in a liquid hydrocarbon at 4C and P>68 barg is 0.03% of mole fraction of MEG in water phase.
Methanol is often not recovered so no regeneration is needed.
MEG and DEG are lost in the regeneration system by carry-over from the regenerator and separator. The amount of carry-over is usually less than 25 kg/106 Sm3 gas flow rate.
Hydrate as a Source of Energy
Hydrates are not always undesirable. Methane hydrates are big sources of energy. There are huge amount of gas hydrates in ocean floor. Under high pressure and low temperature, methane hydrates form. To date, Extracting methane from methane hydrates and exploiting the energy within it is a big engineering and environmental challenge.
GPSA, Engineering Data Book Gas Processing, 12th ed.