Technical Screening of Enhanced Oil Recovery Methods - A Case Study of Block C in Offshore Angolan Oilfields

Geraldo Andre Raposo Ramos, Lateef Akanji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a technical screening of enhanced oil recovery (EOR) methods by using an Artificial Intelligence (AI) model based on neuro-fuzzy (NF) algorithm. The presented NF approach will enable the user to select a suitable EOR method based on available worldwide successful EOR data and field under investigation. The NF approach presented in this study is a five layered feedforward-backpropagation neural networks where the knowledge pattern is extracted by combining both the searching potential of fuzzy-logic and the learning capability of neural network to make a priori decision. The extracted knowledge from the NF system can be expressed in the form of fuzzy rules by computing weights, number of rules and fuzzy set parameters and validated against reservoir properties data trained from worldwide successful EOR projects. The successfully trained and validated model is then tested on the Angolan oilfield data (Block C) where EOR application is yet to be fully established. The test results show that the NF presented in this study can be used for technical selection of suitable EOR techniques. Within the area investigated (Block C) polymer, hydrocarbon gas, and combustion were identified as the suitable techniques.
Original languageEnglish
Title of host publicationFirst EAGE/ASGA Workshop on Petroleum Exploration: Challenges and Solutions for Deep Water Exploration in Angola
PublisherEAGE
Pages1 - 14
Number of pages14
DOIs
Publication statusPublished - 2 Oct 2017
EventFirst EAGE/ASGA Workshop on Petroleum Exploration: Challenges and Solutions for Deep Water Exploration in Angola - Total Guest House, Luanda, Angola
Duration: 2 Oct 20174 Oct 2017
https://events.eage.org/en/2017/first-eageasga-petroleum-exploration-workshop/technical-programme/proceedings

Workshop

WorkshopFirst EAGE/ASGA Workshop on Petroleum Exploration
CountryAngola
CityLuanda
Period2/10/174/10/17
Internet address

Fingerprint

Screening
Recovery
Neural networks
Fuzzy rules
Fuzzy systems
Fuzzy sets
Backpropagation
Fuzzy logic
Artificial intelligence
Oils
Hydrocarbons
Polymers
Gases

Cite this

Ramos, G. A. R., & Akanji, L. (2017). Technical Screening of Enhanced Oil Recovery Methods - A Case Study of Block C in Offshore Angolan Oilfields. In First EAGE/ASGA Workshop on Petroleum Exploration: Challenges and Solutions for Deep Water Exploration in Angola (pp. 1 - 14). EAGE. https://doi.org/10.3997/2214-4609.201702357

Technical Screening of Enhanced Oil Recovery Methods - A Case Study of Block C in Offshore Angolan Oilfields. / Ramos, Geraldo Andre Raposo; Akanji, Lateef.

First EAGE/ASGA Workshop on Petroleum Exploration: Challenges and Solutions for Deep Water Exploration in Angola. EAGE, 2017. p. 1 - 14.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ramos, GAR & Akanji, L 2017, Technical Screening of Enhanced Oil Recovery Methods - A Case Study of Block C in Offshore Angolan Oilfields. in First EAGE/ASGA Workshop on Petroleum Exploration: Challenges and Solutions for Deep Water Exploration in Angola. EAGE, pp. 1 - 14, First EAGE/ASGA Workshop on Petroleum Exploration, Luanda, Angola, 2/10/17. https://doi.org/10.3997/2214-4609.201702357
Ramos GAR, Akanji L. Technical Screening of Enhanced Oil Recovery Methods - A Case Study of Block C in Offshore Angolan Oilfields. In First EAGE/ASGA Workshop on Petroleum Exploration: Challenges and Solutions for Deep Water Exploration in Angola. EAGE. 2017. p. 1 - 14 https://doi.org/10.3997/2214-4609.201702357
Ramos, Geraldo Andre Raposo ; Akanji, Lateef. / Technical Screening of Enhanced Oil Recovery Methods - A Case Study of Block C in Offshore Angolan Oilfields. First EAGE/ASGA Workshop on Petroleum Exploration: Challenges and Solutions for Deep Water Exploration in Angola. EAGE, 2017. pp. 1 - 14
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