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Steady State The simplest form of horizontal well Production productivity calculations are the steady-state analytical solutions, which assume that the pressure at any point in the reservoir does not change with time. In these instances, pseudo-steady state equations are employed. Pseudo-steady state or depletion state begins when the pressure disturbance created by the well is felt at the boundary of the well drainage area.

It is best to read this reference before applying the equation. The equation is based upon the Pseudo-steady state IPR well model applied to a rectangular drainage area. Distributed This option uses straight line PI value for Productivity liquid or gas. PIPESIM uses a technique in which the horizontal completion is subdivided into vertical cross-sections, and flow is treated independently from other cross-sections.

This multiple source concept leads to a pressure gradient from the blind-end toe to the producing-end heel which, if neglected, results in over- predicting deliverability. Construct the physical horizontal well model shown in the figure, using the tubing data in the tables that follow. Keep all other options as default. Specify Beggs-Brill Revised for both horizontal and vertical flow. For an outlet pressure of psia, evaluate the optimal length of a horizontal well up to approximately 10, feet and the pressure loss from the toe to the heel of the horizontal well.

Exercise 3 Specifying Multiple Horizontal Perforated Intervals Additional geological information suggests that the reservoir consists of four sand intervals that are , , , and feet in width, with equally spaced impermeable intervals of feet in width. To specify multiple intervals: 1. Specify separate horizontal completions for each interval with flowline objects to connect the completion intervals, as shown.

Development costs can be substantial and many new production systems must be designed to accommodate subsea multiphase flow across long distances to be economically viable. Managing costs over extended distances introduces a number of complex risks and reliability becomes a key concern due to high intervention costs and potential for downtime. Characterizing and managing these risks requires detailed multidisciplinary engineering analysis and has led to the emergence of a new field called flow assurance.

Design of subsea tiebacks requires multiphase flow simulation to assure that fluids will be safely and economically transported from the bottom of the wells all the way to the downstream processing plant. Four flow assurance issues are discussed in this module, including hydrates, heat loss, erosion, and liquid slugging.

The oil and gas will be separated, with the oil pumped to shore and the gas compressed to shore. To enter the pure components noted in the preceding tables, select the pure hydrocarbon components from the component database. TIP: Make multiple selections by holding down the Ctrl key. Return to the Component Selection tab to see that petroleum fraction displays in the component list table on the right. Leave all other options as default. Generate the hydrocarbon phase envelope by clicking Phase Envelope.

Exercise 2 Constructing the Model In this exercise, you construct the subsea tieback model. To construct the model: 1. Using the Single Branch toolbar, insert the objects shown 2. Specify each object based on the data provided in the tables that follow.

Ensure that your Riser Elevation survey matches that shown below. The expected production rate is 14, STBD. The riser must be the same ID as the tieback, and you must not exceed the erosional velocity. Perform a System analysis with the minimum, maximum, and expected flow rates as the X-axis variable and the available IDs for the flowline and riser as Change in Step with Sensitivity variable 1 sensitivity variables.

Determine the minimum flowline ID that satisfies the separator pressure requirement psia for the maximum flow rate. Verify that the selected flowline ID does not exceed an erosional velocity ratio of 1.

Separator pressure for selected ID Max. Hydrate formation temperature increases with increasing pressure, therefore, hydrates risk increases at higher pressures and lower temperatures.

When hydrates form inside the pipeline, the flow can be blocked by hydrate plugs. Hydrate forming molecules most commonly include methane, ethane, propane, carbon dioxide, and hydrogen sulfide.

The properties of Structures I and II hydrates are well defined. Structure H hydrates are relatively new, and their properties are less well defined. Hydrates can very easily form downstream of a choke where fluid temperature can drop into the hydrate formation region due to Joule-Thompson cooling effects.

Figure 37 shows a typical gas hydrate curve which is very useful for subsea pipeline design and operations. On the left side of the curve is the hydrate formation region.

When pressure and temperature are in this region, water and gas will start to form hydrate. Many factors impact the hydrate curve, including fluid composition, water salinity and presence of hydrate inhibitors.

Thermal insulation carries a higher upfront capital cost whereas chemical inhibition carries a higher operational cost. Input U value is an overall heat transfer coefficient U value based upon the pipe outside diameter is entered.

Calculate U value includes the following information, which can be entered to compute the overall Heat Transfer coefficient. Chemical Inhibitors Thermodynamic inhibitors can be used to shift the hydrate curve towards the left, thereby lowering the hydrate formation temperature.

Examples of inhibitors include methanol and ethylene glycol. These inhibitors do not lower the hydrate formation temperature; instead, they help prevent the nucleation and agglomeration of hydrates to avoid blockage formation. To select tieback insulation thickness: 1. Double-click on the Report tool and ensure that Phase Envelope is checked. Specify Separator outlet pressure as the calculated variable and the three design flow rates as the sensitivity variables.

Use the Series menu on the resulting plot to change the X- axis to Temperature and the Y-axis to Pressure to display the phase envelope. Observe the production path on the phase envelope and its proximity to the hydrate curve. If required, perform successive runs while increasing the insulation thickness of both the flowline and riser by 0. Results Property Value Req. Insulation thickness Exercise 2 Determining the Methanol Requirement Assume the flowline and riser have been insulated but they are under-insulated with only 0.

In this exercise, you determine the required injection volume of methanol to ensure that hydrates do not form. Insert an injector just downstream of the source, as shown. Specify Methanol as Injector Fluid. Use injection temp. To do this: a. Add Methanol to the listed of added components. Double-click on the Injector and choose Edit Composition. Specify Injection Temperature and any injection rate. Specify a liquid rate of 8, BPD and select calculated variable as the outlet pressure.

For the X-axis variable, select the Injector as the object and Rate as the Variable. Uncheck the active status on all sensitivity variables with defined values. From the plot, determine the required Methanol injection rate, such that the flowing temperature is always above the stable hydrate temperature. Lesson 3 Severe Riser Slugging Severe slugging in risers can occur in a multiphase transport system consisting of a long flowline followed by a riser.

Severe slugging is a transient phenomenon that can be split into four steps, as shown in Figure Step 1: Slug formation corresponds to an increase of the pressure in bottom of the riser. The liquid level does not reach the top of the riser. During this period, the liquid is no longer supported by the gas and begins to fall, resulting in blockage to the riser entrance and pipeline pressure buildup, until the liquid level in the riser reaches to the top. Step 3: In bubble penetration, gas is again supplied to the riser, so the hydrostatic pressure decreases.

As a result, the gas flow rate increases. Step 4: This corresponds to gas blowdown. When the gas produced at the riser bottom reaches the top, the pressure is minimal and the liquid is no longer gas-lifted.

The liquid level falls and a new cycle begins. Severe slugging is most prevalent in cases in which a long flowline precedes a riser, especially for cases in which the flowline inclination angle is negative going into the riser. In cases of severe slugging, the slug catcher must be able to receive a volume of liquid at least equal to the volume of the riser.

Deactivate the methanol injector and reset the insulation thickness to that determined to prevent hydrate formation. This reports the full output of each sensitivity value with the Report tool selections appended to the bottom of each sensitivity output.

Perform a System analysis with an inlet pressure of 1,, outlet pressure calculated and liquid rates of 8,; 14, and 16, BPD. To check for severe slugging: a. This represents the maximum value of the PI-SS number along the flowline. More detailed analysis is typically performed with transient simulators such as OLGA. For offshore platforms, you must balance the high cost of added weight to the platform with the potential of a large slug overwhelming the liquids handling capacity and shutting down the entire system.

Hydrodynamic Slugging Most multiphase production systems will experience hydrodynamic slugging. Designing systems simply to avoid hydrodynamic slugging, such as larger pipe ID, is not a common practice. Because hydrodynamic slugs grow as they progress through the pipe, long pipelines can produce very large hydrodynamic slugs. A continuous intermittent flow regime is required for this to occur. A probabilistic model again, based on Prudhoe Bay field data is applied to calculate the largest slug out of 10, and 1, occurrences.

For example, a 1 in one thousand slug length of 50 meters indicates there is only 0. Symbols that can be included in the slug output have the following meanings: 0. Figure 40 Selecting report properties Pigging In multiphase flow in horizontal and upwards inclined pipe, the gas travels faster than the liquid due to lower density and lower viscosity.

This is called slippage. To preserve continuity, recall the definition of liquid holdup discussed in Module 2. In steady-state flow, the gas travels faster, so it will slip past the liquid and occupy less pipe volume. As a pipeline is pigged Figure 42 , a volume of liquid builds up ahead of the pig and is expelled into the slug catcher as the pig approaches the exit. PIPESIM considers that the pig travels at the mean fluid velocity and, thus, the volume of liquid that collects ahead of the pig is a function the degree of slip between the gas and liquid phases such as magnitude of liquid holdup.

The slip ratio SR is also reported, which is the average speed of the fluid divided by the speed of the liquid. The volume of liquid expelled at the receiving terminal as a result of pigging can be estimated using steady-state analysis as a first order approximation. When a sudden rate increase ramp- up occurs, the liquid volume in the pipeline is accelerated resulting in a surge.

A ramp-up operation is illustrated in Figure The size of the surge is influenced by the sensitivity of liquid holdup with respect to the overall flow rate.

A simple material balance approach can be applied to estimate the volume of the associated surge. Figure 43 Ramp-up operation Evaluating Each Scenario For a more detailed analysis of slug catcher sizing, you should also consider the drainage rates of the primary separator and slug catcher. NOTE: For the purposes of sizing a slug-catcher, it is assumed that severe riser slugging can be mitigated with topsides choking or riser-based gas lift.

To size the slug catcher: 1. In the Report tool, verify that slugging values and sphere generated liquid volume are selected.

Re-run the System Analysis configured in the previous exercise. For the ramp-up case, calculate the difference in total liquid holdup, as this will be the surge volume. The conversion factor is 5. NOTE: The surge associated with ramp-up occurs over a much longer time period than the other cases.

The ramp-up volume does not consider the drainage rate of the separator or the duration of the ramp-up. Inspect the output file and observe the flow regimes along the profile for each case.

Based on the results in the table below, select a slug catcher size that will be able to handle the largest slug volume for all conditions. The wellhead pressure and, by extension, the deliverability of any particular well is influenced by the backpressure imposed by the production system. Modeling the network as a whole allows the engineer to determine the effects of such actions as adding new wells, adding compression, looping flowlines and changing the separator pressure.

In this module, you learn how to build a gathering network and perform a network simulation to evaluate the deliverability of the complete system. Lesson 1 Model a Gathering Network Network models are constructed using the network module and solved using its calculation engine. The basic stages involved in developing a network model are: 1. Build a model of the field, including all wells and flowlines. Specify the boundary conditions. Boundary nodes are those that have only one connecting branch, such as a production well, injection well, source or sink.

Solution Criteria A network has converged when the pressure balance and mass balance at each node are within the specified tolerance. The calculated pressure at each branch entering and leaving a node is averaged, and the tolerance of each pressure is calculated from the equation: If all Ptol values are within the specified network tolerance, that node has passed the pressure convergence test. This is repeated for each node. The network has converged when all of the foregoing conditions are satisfied.

Exercise 1 Building a Model of a Network In this case study, your goal is to establish the deliverability of a production network. The network connects three producing gas wells in a looped gathering system and delivers commingled product to a single delivery point. Getting Started 1. Building the Model Using the engineering data available at the end of this case study, build a model of a network. To build the model: 1. Double-click on the vertical completion to enter the inflow performance data.

Enter a gas PI of 0. NOTE: You will enter the reservoir pressure later when the network boundary conditions are specified. Double-click on the tubing and select Simple Model as the preferred tubing model. The ambient temperatures are degF at mid-perforations and 60 degF at the wellhead. The tubing has an I. NOTE: Essential data fields are shown in a red outline; if the fields are not outlined, data entry is optional.

Position the new wells, as shown. For the vertical completion, enter a gas PI of 0. The ambient temperatures are degF at the mid- perforation depth and 60 degF at the surface. Specify the composition of each production well. This step defines the compositions at the production wells. TIP: Composition data of all wells is provided at the end of this exercise in Summary data. Save the current network model. Define the global template of all components used in the network model.

Add all library components Hydrocarbon as well as aqueous components. Under the Petroleum Fraction tab, specify the name and properties of the petroleum fraction and add it to the list of template components.

Choose Fluid Model. Select Use locally defined fluid model and click Edit. Choose Local Compositional and click Edit Composition. Connect the network together. Insert a sink and some junction nodes. Be sure to release the Shift key before the final insertion. The network should now look like this: b. Click the Branch object. Release the mouse button. A connected branch is shown in the figure. Double-click on the arrow in the center of B1 to enter data for that branch.

Close the B1 window to return to the network view. The looped gathering lines are all identical, so the data for branch B1 can be used to define other looped gathering lines.

Select B1. To connect a pasted branch: i. Click the arrow in the middle of the new branch. You will see highlight boxes display at either end of the branch. Move the cursor over the right-hand, highlight box. Use this end of the branch to drag and drop onto a junction node. Position the new branches.

Click Connector to join the equipment together. Close the Single Branch window. In the Options Control tab of the Flow Correlations menu: a. Select use network options. Here, too, PIPESIM software provides a complete set of workflows — from the right choice to get the job done to identifying and migrating workflow challenges and even optimizing the completed system online. The efficiency of flow and surface line equipment can be calculated to produce complete production system analyzes.

Lost Password? Schlumberger Pipesim The foundation of proper modeling of production systems is based on the following three main scientific areas, all of which are included in PIPESIM: Multiphase current modeling: Pipesim employs a wide range of industry standard multiphase current correlations as well as advanced three-phase mechanistic models. Liquid Characterization Modeling: PIPESIM offers two choices for the user, one is related to industry standard black oil concepts, and the other is a range of hybrid models of equation states.

Other company, product, and service names are the properties of their respective owners. Contents Introduction NET framework. This architecture will allow hosting of the latest user interface components, facilitate extensibility both end-user and programmatic and enable more advanced integration with other software products. A table comparing the features in each version is presented later in this document. Gas lift and Rod pump. For higher water cut values, the curve tends to become more linear, and the effect of free gas is reduced.

Gas lift multi-pointing is a non-desirable condition that can be modeled using gas lift diagnostics task. The valve status, open, close, or throttling is also available when the multi-pointing option is enabled. Privacy Terms and Conditions Sitemap.

The new generation in multiphase flow simulation to overcome fluid flow challenges and optimize production.

Software Support Request More Info. Learn more. Safe and effective fluid transport Modern production systems require designs that ensure safe and cost-effective transportation of fluids from the reservoir to the processing facilities. Top New Features - Latest release. New Python Toolkit environment The previous Python Toolkit environment from Enthought has been replaced with a new Python distribution manager from Anaconda.

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