Minimum Miscibility Pressure Techniques: PEEG 334 - Spring 2020

This report discusses the determination of Minimum Miscibility Pressure (MMP), a crucial parameter in Enhanced Oil Recovery (EOR) miscible gas injection projects. It contrasts two primary laboratory techniques: the Slim-Tube (S-T) apparatus and the Rising-Bubble Apparatus (R-B). The report addresses the debate on whether MMP is a physical or petrophysical property, considering the relevance of porous media in its determination. While S-T experiments are time-consuming and utilize a Berea sand pack, R-B is faster and doesn't involve porous media. The report highlights the advantages and disadvantages of each method, noting that S-T generally yields higher MMP values and more reliable oil recovery data, despite its longer duration and higher cost. The importance of the Berea sand in the Slim Tube is discussed, emphasizing its role in establishing multiple equilibrium contacts and simulating displacement mechanisms, despite not perfectly replicating reservoir conditions. The report concludes by justifying the specific length of the coiled tube in the S-T apparatus, highlighting its efficiency in fluid transport, cost-effectiveness, and ease of maintenance.

Running head: MINIMUM MISCIBILITY PRESSURE TECHNIQUES 1
Minimum Miscibility Pressure Techniques
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Minimum Miscibility Pressure
Minimum Miscibility Pressure (MMP) is the minimum pressure at a given constant temperature
and composition where multiple or first-contact miscibility can be achieved. At such pressure,
there is interfacial tension; however, there exists no interface between the fluids (Zheng, 2019).
It can also be defined as the minimum pressure whereby crude oil remain miscible with carbon
dioxide at a given reservoir temperature. One of its main applications is the gas injection project
design where the key factor is the Minimum Miscibility Pressure which is the exact pressure that
the local displacement is at 100% efficiency (Du, 2019). Minimum Miscibility Pressure is
generally used as the main method of coming up with the most suitable solvent in oil recovery
projects. MMP is classified as a petro physical property where the use of porous media is very
critical I order to yield best results (Adekunle, 2016).
As mentioned above Minimum Miscibility Pressure -(MMP) is an essential aspect for developing
a miscible gas flooding project for both medium and light oil reservoirs. In the laboratory, Rising
Bubble Apparatus - (RBA) and Slim Tube tests (S-M) are the two most common technique used
to analyze Minimum Miscibility Pressure, however, because of time and expenses incurred
during testing Slim Tube is recommended because it is significantly faster and more cost
effective technique (Zhang, 2018). In addition, it gives satisfactorily result that are in line with
international standards. In Rising Bubble Apparatus (RBA), a bubble gas is injected to the oil
column at the bottom of the testing equipment at a given pre-specified system pressure and as
such, the Minimum Miscibility Pressure is determined by direct observation of the bubble
changes during the rising process in the apparatus (Karkevandi, 2017). The exact pressure is
recorded at a point when the bubble just rise at the top of the column and at the same time the

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bubble disappear at the bottom, the average of this two is estimated as the Minimum Miscibility
Pressure.
Although the process is sometimes used when there is a shortage of fluid, previous test results
have proved that a slim-tube (S-T) oil recovery method will often produce Minimum Miscibility
Pressure that is higher as compared to Rising Bubble Apparatus (RBA). The oil recovery breaks
from Slim Tube is of high standard as compared to the use of RBA (Zhang, 2019). However,
RBA may be the solution when time factor is the key parameter; the technique takes 1-3 hours in
each single Minimum Miscibility Pressure. determination (preparation time not considered)
while the Slim Tube Technique may take one or three weeks per a single MMP analysis,
moreover, in case there is a shortage of solvent and oil tests that are reagents for Slim Tube tests,
RBA could be employed because it uses less fluid to analyze Minimum Miscibility Pressure
(Hemmati-Sarapardeh, 2017).
Although the porous media is an important aspect in Minimum Miscibility Pressure, it makes a
lot of sense for the Slim Tube to be stuffed with Berea sand although the tested reservoir is
different, the sand packed tube displacement apparatus is an important component that brings
about multiple equilibrium contacts in the flowing fluids within the tube, however the sand
packed tube is not intended to simulate the reservoir working conditions (Bian, 2017). The Berea
sand further is an important aspect in actual displacement through various mechanisms such as
gravity override, it is therefore very important to have such medium as Berea sand or glass beads
despite the fact that porous media is an important aspect (Czarnota, 2017).
Finally, the coiled tube in the S-T apparatus has an average length between 40 to 120 feet, the
length is an important factor because it is easier and more efficient to pass chemicals through the

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coiled tube and the ability to push the fluid is much easier compared to relying on gravity which
has myriad challenges, pumping is considered to be fairly self-contained because it as a closed
system because the coiled tube is continuous instead of jointed pipes. The length of the coiled
tubing is also cost effective; there is use of minimum energy while pumping fluid and hence
cost-effective, in an event where there is no power, the length plays an important aspect sine the
fluid can flow using gravitational force (Lashkarbolooki, 2017). Finally, that average length has
been used as a cheaper version of Work-over operations, the length is good enough for the fluid
to flow and on the hand, the maintenance process is easy and less time is required. The above
explains why the coiled tube in S-T apparatus has the specified length, it as an essential
component that cannot be ignored.

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Reference
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Bian, X. Q., Han, B., Du, Z. M., Jaubert, J. N., & Li, M. J. (2016). Integrating support vector
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