eprintid: 16648
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/66/48
datestamp: 2023-12-19 03:23:10
lastmod: 2023-12-19 03:23:10
status_changed: 2023-12-19 03:06:38
type: article
metadata_visibility: show
creators_name: Ayoub Mohammed, M.A.
creators_name: Alakbari, F.S.
creators_name: Nathan, C.P.
creators_name: Mohyaldinn, M.E.
title: Determination of the Gas-Oil Ratio below the Bubble Point Pressure Using the Adaptive Neuro-Fuzzy Inference System (ANFIS)
ispublished: pub
note: cited By 7
abstract: Determining the solution gas-oil ratio (Rs) below the bubble point is a vital requirement that aids in multiple production engineering and reservoir analysis issues. Currently, there are some models available for the determination of the solution gas-oil ratio under the bubble point. However, they still may prove unreliable due to the applied assumptions and their specification to operate only under a particular range of data. In this study, the neuro-fuzzy, i.e., the adaptive neuro-fuzzy inference system (ANFIS) approach, is utilized to develop an accurate and dependable model for determining the Rs below the bubble point pressure. A total of 376 pressure-volume-temperature datasets from Sudanese oil fields were used to establish the proposed ANFIS model. The trend analysis was applied to affirm the proper relationships between the inputs and outputs. Furthermore, using different statistical error analyses, the developed model was benchmarked against widely used empirical methods to evaluate the proposed method's performance in predicting the Rs at pressures below the bubble point. The proposed ANFIS model performs with an average absolute percent relative error of 10.60 and a correlation coefficient of 99.04, surpassing the previously studied correlations. © 2022 The Authors. Published by American Chemical Society.
date: 2022
publisher: American Chemical Society
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132011799&doi=10.1021%2facsomega.2c01496&partnerID=40&md5=914a6366406bc9ce40d9522a99f34ad9
id_number: 10.1021/acsomega.2c01496
full_text_status: none
publication: ACS Omega
volume: 7
number: 23
pagerange: 19735-19742
refereed: TRUE
issn: 24701343
citation:   Ayoub Mohammed, M.A. and Alakbari, F.S. and Nathan, C.P. and Mohyaldinn, M.E.  (2022) Determination of the Gas-Oil Ratio below the Bubble Point Pressure Using the Adaptive Neuro-Fuzzy Inference System (ANFIS).  ACS Omega, 7 (23).  pp. 19735-19742.  ISSN 24701343