It's the answers of featman and ibrahim questions: Sorry I'm late. Unfortunately your comments wasn't sent to me. I reinstalled pipesim , there's no problem. As previous the program runs and generates graphs. It also works on xp and 7. I write the procedure again for you. First: Download mflash. Originally Posted by motaleby. Could you explain how to "join" the cousin Olga with PP? I also coppied two dll files.
It does not work. Could anyone help me with instruction on how to install the programe step by step. I am using windows 7 professional. Krebs - AM. Cancel Changes. Go to Profile Mark as Read. Blog Categories. Best Solution Provided for Unconverged Network Simulation Cases: Certain networks that are either ill conditioned or encounter issues generally flow regime discontinuities or unstable well behavior that may prevent solution to a tight convergence tolerance will return the best solution achieved as opposed to no solution if the iteration limit is reached without reaching the target tolerance.
A warning message is prominently displayed which indicated the target tolerance has not been reached. By studying the best solution, causes for not reaching the target tolerance can be more easily investigated. Additionally, the online help system has been significantly expanded, including new tutorials and further technical details on a number of features. This has been updated to version 3.
The CPA equation of state has been added. The compositional dialogue has been redesigned to make it easier to manage these extra flash packages. A new compositional template dialogue has been added, acting as a single place where the PVT package and models can be defined. The component template also stores the master list of all components in the model, ensuring that petroleum fractions have the same properties for all fluids.
New and faster Moody friction factor calculation methods Two additional methods have been added for the calculation of the Moody friction factor. Sonnad and C. Goudar, Ind. Res, , 46, pp. The default calculation method for the friction factor is the explicit method.
The Moody friction factor calculation method also has an impact on the horizontal and vertical flow correlations as the friction factor used to compute the pressure gradient in the flow correlations will be evaluated based on the method specified by the Moody friction factor calculation method.
Improved Network topology analysis and checks A new method for analysis and checking network topology has been introduced. This allows valid and invalid intersections to be distinguished and the data for the valid ones to be displayed accurately. They are also available in the output report. The remaining points on the curves are distributed to ensure they are clustered in regions where the slope changes fastest.
This in turn allows multiple inflow curves to be displayed on the same plot for wells with 2 or more completions. The default behavior is to keep all branches skipped in the restart file permanently skipped. An advanced engine option allows you to activate the second type of behavior.
Retirement of flowrate lower limits option The flowrate limits on branch and wells has been reworked. Those limits apply both to forward and reverse flows. Enhancements to PsPlot The following enhancements have been made to PsPlot in the version supplied with Option of adding multiple dataset series to the X axis. This allows the display of multiple inflow curves for individual completions when the well contains multiple completions. Added line formatting capabilities allowing for broken and thick lines and symbol styles 3.
Improved formatting of axes annotation and data table entries 4. Improved automatic calculation of axes data range to give sensible number of increments 5. Retirement of 32 bit Linux network engine The 32 bit Linux network engine has been retired. The 64 bit version is still available. The package comes with data files describing the performance of 13 Framo pumps and new files can be added when available.
The results are continuous through the entire range of burial configurations from buried to exposed and are accurate to within 2. The Calculation uses the Ramey Model and allows the user to enter the time the well has been operating together with physical dimensions and thermal properties of the various insulating layers. There are two models available — the Kaminsky model and the Kreith separate Reynolds number model.
Use debug flag 58 to select the previous model. Improved calculation of blackoil enthalpy A new, improved, model for the prediction of the total enthalpy of a black oil fluid has been added. This has been replaced by a rigorous calculation taking into account heat loss and potential energy terms. Changes in kinetic energy are still ignored. A steep penalty function is used to predict discharge pressure. Limits can be set for maximum differential pressure and available power. The initial model is designed for a Rod Pump that is operating under steady state operation.
This allows the user to select parameters which will be automatically set using an optimizer to minimize the difference between measured and simulated data. Modified Holdup factor The way the holdup factor is used in flow correlations has been modified in the light of experiments with the new Data Matching operation. Previously, to allow the correlation to be tuned to measured data, a linear factor could be used to multiply the liquid hold up predicted by a flow correlation.
However, this can lead to liquid holdups of 1, even when gas is flowing. The new holdup factor must be between 0 and 2. To restore the old behavior, debug flag can be used. Wax sensitivity The wax deposition operation has been enhanced to provide sensitivity analysis for the Schlumberger DBR wax deposition models. Multiphase wax deposition modeling A new Schlumberger DBR wax multiphase deposition model has been added to this release. This model is complements the original single phase model released in DBR-Solids 4.
The program provides workflows for the prediction of wax and asphaltene precipitation regions and for the prediction of Wax deposition in pipelines.
The results of the wax deposition prediction are then fed to the PIPESIM wax deposition operation to calculate the rate of wax deposition and the change in bulk flow rate due to the wax deposited on the walls. Multiflash 3. In this mode, all water ends up in the water phase, which contains only the water component. Olgas for Linux 64 Version 5.
This requires version 2. Olgas 5. People wishing to use the Shell flow correlations should contact Shell directly. Licensing of the Shell Features is still carried out by Schlumberger. The 64 bit engine is installed in a Programsx64 directory, alongside the 32 bit engine in the Programs directory. Note that the 32 bit engines can also be used on 64 bit operating systems. PsPlot Localization The display of axis and data series labels can be translated into the local language using a dictionary file called PsPlotdict.
Only single byte language strings are catered for. A plot label template is provided PsPlotdict. A Russian dictionary partial is also provided as PsPlotdict. Use the system plot to evaluate erosional velocity ratio over time.
Is erosional velocity in the flowline-riser a problem? If so, what actions can be taken to mitigate erosion? In the following module, you will learn how to determine the optimal amount of gas lift and injection pressure at a given time. To do this, the system developed in Module 1 must be converted into a network model for detailed gas lift optimization.
In Module 2, you will investigate artificial lift optimization applied to a system that is in the operations phase of development. You will update and expand the model built in Module 1 to reflect operating conditions during production. Based on this data, the optimal artificial lift conditions will be determined. Lesson 1 Gas Lift Optimization Optimization, by definition, is a mathematical procedure that aims to determine the optimal configuration of a set of control variables for a prescribed objective function that is to be optimized, possibly including constraints.
In production operations, the objective function may be to maximize oil or gas production rates, minimize gas-oil or water-oil ratios, or maximize economic KPIs. The production system must be modeled as an interconnected network to account for the interaction among the wells.
Additionally, field equipment must be incorporated into the model and operating constraints properly accounted for. Schlumberger Public Figure 16 Gas lift production network Basic Principle The basic principle behind gas lift injection in oil wells is to lower the density of the produced fluid in the tubing.
In terms of the overall pressure gradient, the trade-off to the increased presence of gas is an increased frictional pressure gradient. As shown in Figure 17 on page 69, as the rate of injection gas increases, a point is reached where the benefits of reducing the elevational gradient equals the drawback of increasing the frictional gradient. Figure 17 Gas lift vs. Liquid production Schlumberger Public In practice, when dealing with a network of many gas lifted wells, the optimal injection rate is largely dependent on the flowline hydraulics where a reduced elevational pressure gradient may provide little benefit.
Additionally, the complex interaction of wells producing into a common gathering network determines the backpressure against which the individual wells must produce. Furthermore, operating constraints may restrict the amount of gas that can be injected into the well. Thus, optimization of the complete system necessitates an optimal allocation of the available lift gas amongst all the gas lifted wells. For networks with hundreds of wells this becomes a mathematically complex problem.
Constraints Careful consideration must be given to operating constraints including handling capacities, compression requirements and the availability of lift gas. In addition, local, global or mid-level constraints may be specified.
Finally, global constraints are those that apply to the entire network. Noticeably, as the wellhead pressure increases the potential liquid flowrate decreases for a given level of lift gas injection.
These lift profiles are generated for each well in a pre-processing step and are employed in an offline optimization procedure in which the well performance is accounted for without directly having to run the entire network. This decoupling significantly aids the speed up of the optimization procedure, which will be elaborated below. Figure 18 Lift performance curves The Gas-Lift Allocation Problem Determining the optimal gas lift allocation over the set of gas lifted wells is a non-linear optimization problem.
In addition, as Schlumberger Public discussed above, there may be many constraints imposed on the system. Alternately, stochastic based solvers, such as the Genetic Algorithm GA , can be employed. However, one shortcoming of simply applying these solvers for direct optimization optimizing the system as given is the cost associated with running the network simulation for each objective function call. If numerical derivatives are required the problem is further compounded.
To overcome this computational and time burden, a new solution approach is presented that uses an iterative offline-online procedure to provide greater solution flexibility and performance. Offline-Online Optimization Procedure The optimization scheme calculates the optimal injection rates for all of the wells based initially on given wellhead pressures using the extracted lift profiles.
Subsequently, an online call to the real network model provides updated well pressures. The procedure repeats iteratively until convergence of wellhead pressures is reached. The actual optimal allocation can be run to maximize on either total liquid produced or total oil produced based on specified available injection gas or the constrained total permissible produced gas.
This approach achieves a significant solution speed up while maintaining the rigor of the full network model. The choice of which method is used depends on the constraints applied to the network model. Selection can be made automatically. In general terms, the NRM technique does not handle mid-level constraints, such as those imposed on a manifold.
The GA on the other hand, penalizes those solution candidates that exceed the constraint. Following is a description of each of these methods. That is, the sum of the gas lift injection rates will always equal the amount of gas made available.
Treating the available lift gas as an equality constraint enables NRM to convert the original multi-dimensional problem to a solution of a composite residual function of one variable. It must be called several times to ensure true solution optimality with respect to the original inequality constraint. It is fast, but limited with respect to manifold branch level constraints and used for networks that Schlumberger Public have only primary well-level and global constraints. Genetic Algorithm GA The GA is a probabilistic solver that belongs to the class of evolutionary algorithms that use the principles of evolution to stochastically evolve a population of candidate seeds to progressively better states.
The best candidate after a given number of generations is accepted to be the optimal. The GA performs a multi-dimensional parallel search and does not require derivative information.
Because of the higher number of function evaluations required and potentially a greater number of network solves, it can be more costly in calculation time, but is generally robust. The GA is most useful when mid level constraints for example, maximum flow at a manifold are imposed in the network model.
The GA solver is useful in these situations, as its use of implicit global search through the use of a population of search points allows it to overcome poorer local solutions. Select a production well icon from the left-side toolbar and insert it into the flow diagram. Right-click the well icon and select Import single branch model. To perform an optimization study, the wells need to be treated independently in a network model.
Close the single branch window for the well in order to enter the network modeling environment. Using the icons on the toolbar at the left, construct the following network diagram and name the branches and Schlumberger Public junctions by right-clicking and selecting General: 7.
Move the topsides choke and pipe to the correct branch in the network model. Double-click Well 1. Right-click and select Cut. Close the single branch window, double-click the choke- A branch and select Paste. Select the default flowline surrounded by the red box and press Del. Reconnect the topsides-A junction to the flowline inlet and, using the connector tool, connect the topsides-A and Header junctions to the flowlines upstream and downstream of the choke respectively.
Close the single branch window. Move the flowline-riser pair and multipliers to the respective network branch. Highlight the connector leaving the multiphase booster and click Delete.
Schlumberger Public e. Close the single branch window, double-click the tieback- A branch, and select Paste. Using the connector tool, connect the upstream adder- multiplier to the DC-A junction and the downstream adder-multiplier to the topsides-A junction. Remove remaining objects from the imported well model.
Click Delete. The well should appear as shown below: For optimization purposes, assume that all gas lift is injected Schlumberger Public in the lowermost orifice valve and will therefore replace the gas lift valve system with a single injection point. Double-click the tubing and select the Downhole Equipment tab. Select the Edit valve details checkbox. Select Remove all valves and click OK. In the Downhole Equipment tab, specify a gas lift injection point at a MD of ft.
Click the Properties button next to the gas lift injection point and specify the following: Injection rate 0 mmscfd Surface injection Temp. For completion design purposes, the wells were modeled using the pseudo-steady state flow model. However, during the operational phase, the availability of downhole pressure measurements coupled with knowledge of the average reservoir pressure allows for an accurate characterization of the inflow performance using a simple productivity index method.
Double-click the completion. Change the completion model from pseudo-steady state to Well PI. Return to the main network diagram. These wells are piggy-backed along a separate tieback-riser pair and produce to a common header. Add the following branches and junctions to the network and name them as shown below: The choke-BC branch is identical to the choke-A branch.
The tieback-BC branch is nearly identical to the tieback-riser-A branch. Copy the objects in the tieback-A branch into the tieback-riser-BC branch. Ensure that the DC-B junction is connected to the adder-multiplier attached to the flowline. Modify the length of the tieback flowline to ft. Be careful with the units.
The tieback-C branch contains a dual flowline configuration. Copy the contents of the tieback-BC branch into the tieback-C branch. Delete the riser object and reconnect the flowline outlet from the riser-base report tool to the outlet adder- multiplier. Connect the outlet adder-multiplier to the DC-B junction with the connector tool. Connect the inlet adder-multiplier to the DC-C junction. Delete the riser-base report tool. Modify the flowline object so that the length is 5 miles and the elevation difference is feet.
Update the well models with current production data. Right-click and select Copy. Right-click and select Paste 9 times. Hold down Shift, select the branch icon, and connect the wells to the drill centers as shown below, noting the well names: Modify the individual well models based on the properties given in the following table.
Each well group will be defined by a separate fluid model as shown in the following table. Click Import and select Group A from the dropdown list. Click Apply. By default, all wells will use the Group A fluid model. Change the fluid properties according to the table above. From the Fluid Models list, ensure that Wells 5 and 6 are using local fluid models based on the Group B template. NOTE: Local fluid models must have different names. Repeat the previous two steps for Group C wells The Fluid Models table should appear as shown in the table below: Schlumberger Public To ensure that the model runs without gas lift and to validate the data entry, assume for the moment that all reservoir pressures are 8, psia and the separator pressure is psia.
Specify reservoir pressures for the wells and the separator pressure. Check the results against the table below. Schlumberger Public Exercise 2 Optimizing Gas Lift To optimize gas lift: 1.
Perform the gas lift optimization. Also allows reporting and comparison of key performance indicators KPIs and comparison of multiple archived runs. Define groups corresponding to the drill centers in our network model. Holding the Ctrl key, select wells 1, 2, 3 and 4.
Right-click and select Create Group. Define local constraints for all wells. Ensure that the top-level node Gas Lift Wells is selected so that the settings may be easily applied to all wells. This ensures that the gas lift injection rate is sufficient to ensure well stability and avoid issues such as heading. Select the checkbox in the Select column for the above constraints and click Apply Selected Constraints. This applies the specified constraints for all gas lift wells.
Alternatively, individual well or group constraints can be specified individually. Lift per Well 10 mmscfd 9. The marginal gradient specifies the minimum amount of oil that is acceptable to produce per unit of gas injected.
Therefore, use the Marginal Gradient field to specify a positive gradient that will force a solution point to the left of the flat region of the performance curve. Click Run to start the optimization and observe messages in the message log. NOTE: In the verbose messages, the gas lift injection lower and upper limits associated with the stability and drawdown constraints vary by iteration.
Depending on the complexity of the model and constraints, the maximum number of iterations in the Advanced tab may need to be adjusted. NOTE: When specifying the total maximum lift gas, a series of runs are performed at various fixed total gas lift injection rates.
To monitor the results from each of these runs, select the Iteration View button from the Global Constraints tab. Once the optimization is complete, select the Results tab and the Lift Curves and Rates sub-tab.
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