Petroleum Physical Properties Prediction Application in Enhanced Oil Recovery Process

Sulistyarso, Harry Budiharjo and Irawati, Dyah Ayu and Pamungkas, Joko and Widiyaningsih, Indah (2021) Petroleum Physical Properties Prediction Application in Enhanced Oil Recovery Process. International Journal of Recent Technology and Engineering, 10 (4). pp. 139-147. ISSN 2277-3878

Text 11. J-Int-IJRTE 13 November 2021-P.pdf Download (1MB)

Abstract

The Enhanced Oil Recovery (EOR) process is one
of the ways in the petroleum exploitation process so that thick oil
can be lifted to the surface and produced. The EOR process
referred to in this study is the EOR process carried out in
previous studies at the EOR laboratory of UPN Veteran
Yogyakarta Indonesia by adding biosurfactants and adjusting the
temperature. In laboratory experiments, each time an amount of
biosurfactant concentration is added and the temperature is
adjusted, the calculation must be done repeatedly to determine
the amount of viscosity, interfacial tension (IFT), and density.
This experiments takes a long time, requires high cost and variety
limitation of the condition. The previous research has
succeeded in building a model with multivariate polynomial
regression equations to predict the value of the physical
properties of crude oil from existing data then classify it into
three categories using Naive Bayes, i.e., light oil, medium oil, and
heavy oil. The physical properties of petroleum measured in the
research are viscosity, interfacial tension, and density. The model
uses laboratory data which are taken from the test results of
Pertamina's KW-55 well as validation. The validation result
shows that Multivariate Polynomial Regression has succeeded in
predicting the value of viscosity, interfacial tension, and density
with error values ranging from 0% to 1% from the sample data.
With a low error value, the application can make forecasting with
more variable conditions. The model still cannot be used
independently without the Python environment, so to be used
easily by more users, the model must be built into an independent
application that can be installed on the user's device. In this
research, the prediction application of petroleum physical
properties has been built. The application is made using the
Multivariate Polynomial Regression method according to the
model in the previous study to predict the physical properties of
petroleum, then uses Naïve Bayes to classify the oil. The
application completed the several adjustment to shift from model
to application, including user interface, system, and database
adjustments.
Keywords: EOR; petroleum physical properties; prediction

Item Type:	Article
Uncontrolled Keywords:	EOR; petroleum physical properties; prediction
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	Ir, MT,IPM JOKO PAMUNGKAS
Date Deposited:	08 Apr 2023 01:31
Last Modified:	08 Apr 2023 01:31
URI:	http://eprints.upnyk.ac.id/id/eprint/34046

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