The importance of this project is influenced by the trend factor of the oil and gas industry today in the use of gas injection as an improvement of the oil recovery process. At the end of the project, the obtained result will be analyzed and documented. Meanwhile in this project the focus will be the behavior of EOS where the project will focus on the effect of the equation of state (EOS) afid ttiiiliig pat.ttiieters in the calculation of the miscibility pressure we will see the effect of the EOS tuned to the MMP predicted value by compare the MMP value from EOS and experiment.
As mentioned above and as the title of this project which is the effect of equation of state (EOS) and tuning parameters on mixture pressure calculation, the main objective of this project is to see the effect on MMP Wlieii value. EOS are tuned to match the same data from the experimental approach. As in the discussion above, there is about two-thirds of the orlgial oil in place even after primary recovery and secondary water flooding. Each of the methods has its own ways to estimate the value of MMP such as the experiment method, there are several methods that have been developed which are the displacement of the thin tube, the rising bubble apparatus and a new method, the voltage disappearance interfacial (VIT).
In the rising bubble experiment, the MMP is determined based on the observation of changes in the shape and appearance of the bubble of the injected gas as they rise through a thin colluiriri of etude oil. To overcome most of the disadvantages of the above methods, a new method called vanishing interfacial tension (VIT) has been developed. Many correlations have been proposed linking MMP to the physical properties of the oil and the displacement fluid.
Equation of State
PREOS
For pure oompoood, these three parameters are well defined, but the problem arises when there is a heavy fraction, C7+ or also called plus fraction. These three parameters are not well defined for the plus fraction and this plus fraction is present in virtually all naturally occurring gases and crude oil liquids. This limitation of the PREOS results in the incorrect procedure for calculating the characterization parameters "a, b and a" for C7+, which are very useful for the determination of MMP.
But with the apparent success of the modified Redlich-Kwong EOSin describing the volumetric behavior of C02 crude oil systems by Turek et al., it was motivated to implement the modification to PREOS by Tarek Ahmad. According to the new approach recommended by Tarek Ahmad, the characterization parameters "a, b and a" for the plus fraction are determined based on the measured molecular weight and specific gravity of the heptanes plus fraction. There are three types of components in the naturally occurring petroleum deposits: pure components (such as CO2, CO, N2, H2S, Cl, C2, etc.), mixture components (such as C7, C8, C9, etc.), and plus fraction.
Therefore, the user-input multiple fluid samples are normalized into a unique N-component normalized system that contains all the components that each fluid sample has.
Regression
The saturation point volume, V sat. is used as a reference value and the volumetric results presented are relative volumes, i.e. the volumes divided by V sat.·. GOR Volume of gas from the actual stage at standard conditions divided by the volume of the oil from the last stage (atmospheric conditions) Gas Gravity Molecular weight of the gas divided by the molecular weight of air. FVF Oil formation volume factor, which is the oil volume in the actual stage divided by the oil volume of the last stage.
Sometimes the separator GOR is reported as the standard volume of gas divided by the volume of separator oil (the volume of oil in the current stage. When gas is injected into a reservoir containing unsaturated oil, the gas can be dispersed in the oil. The saturation pressure of tli .e The inflated fiiiXttife and tli.e volume at the saturation point divided by the volume of original tank oil are recorded.
Swollen volume Volume of the mixture per volume of original reservoir fluid Density Density of swollen mixture at saturation point.
Lumping
For a given Jumped system, calculate the component properties of pseudocomponents based on the mixing rule developed above. If it is not necessary to consider any reference conditions in the common single-phase region, because the original system and all!UI11ped systems will predict the sil11e mixture properties. Compare the mixture properties 111 ca5e of three or more phases, the related phase characteristics should also be included in the Jumping error function. Before using any EOS for phase behavior calculations, it is necessary to calibrate the EOS against the experimental data by adjusting the input values of some uncertain parameters in the EOS to minimize the difference between the predicted and measured values. The effectiveness of each experimental property is introduced into the EOS model through its weight factor. Weighting factors are assigned to each property based on its accuracy and reliability, Y of measurement. The weakness of EOS regarding the calculation of certain specific properties, the reliability of data and the target for the fluid properties study affect the values of different weighting factors. However, if the input parameters of EOS are widely adjusted by assigning weighting factors other than those proposed by Coats to fit the experimental data, this would lead to unrealistic results. Danesh suggested that, in general, any leading EOS that predicts the phase behavior data reasonably well without fitting would be the most suitable choice for phase behavior calculations. The higher the weighting factor, the more accurate the measurement of this data and thus the more importance should be placed on matching this property. Tuning Parameters Based on the understanding, the report is made according to the criteria that have been coordinated for the student. While in the second semester, the project will continue to select the appropriate EOS to be used in the project. Will be SRKEOS or PREOS due to their excellent performance in determining MMP values. This stage is divided by three work which are splitting, lumping and calculation on the plus fraction properties. The plus fraction must be treated specially because of the inability to define the parameters that must be adjusted to fit the data of the experiment. Using the tuned EOS, the simulation to calculate the MMP value is done using little suggested software like ECLIPSE 300 or PVTSim. With the result obtained from the simulation, the MMP value between the EOS and the experiment will be compared to see if there is any difference. From here, we will see if the tuning parameters in EOS will affect the prediction made on the MMP value. Computer with Internet access and compatible with the software mentioned below (using Windows 7 as an operating system). From the table above we can see the experimental value that acts as the base or reference point. The tuning will be better if the tuned parameter value moves closer to the experimental value compared to the EOS calculated value or before tuning value. This concept is applied to the entire components that are under compositional mass expansion, differential depletion and swell test. The absence of the other two in reservoirs 5 and 12 is due to the experiment performed on both reservoirs, which does not include the separator test. In the separator test, the value of the EOS calculation is so large compared to the experimental value. However, in this case, the regression process was largely done through a try-and-error process and the result sought is that as long as most of the overall PVT data gets closer to the experimental value, it will be considered the best regression process. From the graph it can even become clearer to see the effect of the tuning. The other two types of data can be calculated by the software from the other three supplied data. Few graphs were generated from the simulation performed in PVTSim and this is one of the graphs. As for EOS to simulate the differential depletion experiment, the data needed from the experiment are pressure, oil formation volume factor, solution gas oil ratio, gas formation volume factor, oil density, Z factor, gravity, oil viscosity, and gas. viscosity. For solution gas oil ratio, we can see in the table where the percentage of deviation becomes larger than before the tuning value, and the worst was reservoir number 9, where the percentage of deviation comes up to 19782.17% far above the experimental value. For the elevated volume data, as in the table, no changes are made to the data, even though it has been calculated by EOS or adjusted accordingly. For example, from tank table number 3, using the Soave-Redlich-Kwong (SRK) EOS, the MMP value is calculated and the value is generated and displayed as the multi-contact fault pressure and in this case it is 349.6001 bar. From the graph above which is the simulated experiment of the thin tube, the MMP value is being generated from the experimental approach. From grap~ we are looking at the line changes in the graph. From the comparison table, it can be said that not every calculation from EOS is nearly the same as the thin tube simulation. CONCLUSION AND RECOMMENDATION Bhd.: "Evaluation of C02 Gas Injection for Major Oil Production Fields in Malaysia - A Case Study of an Experimental Approach: Dulang Field," SPE 72106. APPENDICESCHAPTER ill: METHODOLOGY
Project activities
RESULT AND DISCUSSION
CHAPTER VI: REFERENCES
