Non-Simulation Enhanced Oil Recovery Technique Screening in X and Y Fields Using a Combination of Analytical Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution

2021 ◽  
Author(s):  
Sunni Nugraha Priadi ◽  
Hadi Ismoyo ◽  
Alexandra Sinta Wahjudewanti

Abstract The X and Y fields are among the oil fields in the Java basin, Indonesia. As oil production decreases due to exploitation activities in X and Y fields, it is necessary to carry out activities to increase production. To increase the yield of its oil production, Enhanced Oil Recovery (EOR) technology is needed. Enhanced oil recovery (EOR) technique screening analysis is needed to be carried out at the initial stage of the feasibility study in the EOR project. At present, there is no fully established method for identifying potential candidates for the EOR technique. The most common approach for selecting EOR techniques is conventional filtering, which is generally based on the "go-no go" trial and error, with a reduced chance of success. Besides, determining potential candidates for EOR techniques often uses a reservoirsimulation approach, but this is time-consuming and requires high costs in using the software license. EOR technique screening with a method that explains how to form a multi-criteria decision-making model with a combination of AHP and TOPSIS methods together as a systematic and measurable method to get the best EOR techniques in both X and Y fields. The research results found that the CO2Immiscible Technique was the most appropriate for EOR in fields X and Y because it has the highest preference value (0.676), is then followed by the Micellar technique (preference value 0.645) and HC Immiscible (preference value 0.517). With the multi-criteria decision-making technique, the best EOR technique results are obtained. Then the proposal can provide valuable recommendations for company management in both fields X and Y with a faster, accurate, and inexpensive method compared to the reservoir simulation method, which has a longer processing time and more expensive costs. This technique can support technology implementation decision-making in the early stages of EOR project development.

2021 ◽  
Vol 7 ◽  
pp. 2751-2758
Author(s):  
Zhenzhen Wei ◽  
Shanyu Zhu ◽  
Xiaodong Dai ◽  
Xuewu Wang ◽  
Lis M. Yapanto ◽  
...  

2019 ◽  
pp. 125-133
Author(s):  
Duong Truong Thi Thuy ◽  
Anh Pham Thi Hoang

Banking has always played an important role in the economy because of its effects on individuals as well as on the economy. In the process of renovation and modernization of the country, the system of commercial banks has changed dramatically. Business models and services have become more diversified. Therefore, the performance of commercial banks is always attracting the attention of managers, supervisors, banks and customers. Bank ranking can be viewed as a multi-criteria decision model. This article uses the technique for order of preference by similarity to ideal solution (TOPSIS) method to rank some commercial banks in Vietnam.


2021 ◽  
Vol 13 ◽  
pp. 184797902110233
Author(s):  
Stefania Bait ◽  
Serena Marino Lauria ◽  
Massimiliano M. Schiraldi

The COVID-19 emergency is affecting manufacturing industries all over the world. Notably, it has generated several issues in the products’ supply and the global value chain in African countries. Besides this, Africa’s manufacturing value-added rate grew only 1.5 since 2018, and the foreign direct investment (FDI) from multinational enterprises (MNEs) remains very low due to high-risk factors. Most of these factors are linked to a non-optimized location selection that can adversely affect plant performance. For these reasons, supporting decision-makers in selecting the suitable country location in Africa is crucial, both for contributing to countries’ growth and companies’ performance. This research aims at presenting a comprehensive multi-criteria decision-making model (MCDM) to be used by MNEs to evaluate the best countries to develop new manufacturing settlements, highlighting the criteria that COVID-19 has impacted. Thus, it has affected countries’ performance, impacting the plant location selection choices. A combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods have also been used for comparative analysis. The criteria used in the proposed approach have been validated with a panel of MNEs experts.


2021 ◽  
Author(s):  
Tinuola Udoh

Abstract In this paper, the enhanced oil recovery potential of the application of nanoparticles in Niger Delta water-wet reservoir rock was investigated. Core flooding experiments were conducted on the sandstone core samples at 25 °C with the applications of nanoparticles in secondary and tertiary injection modes. The oil production during flooding was used to evaluate the enhanced oil recovery potential of the nanoparticles in the reservoir rock. The results of the study showed that the application of nanoparticles in tertiary mode after the secondary formation brine flooding increased oil production by 16.19% OIIP. Also, a comparison between the oil recoveries from secondary formation brine and nanoparticles flooding showed that higher oil recovery of 81% OIIP was made with secondary nanoparticles flooding against 57% OIIP made with formation brine flooding. Finally, better oil recovery of 7.67% OIIP was achieved with secondary application of nanoparticles relative to the tertiary application of formation brine and nanoparticles flooding. The results of this study are significant for the design of the application of nanoparticles in Niger Delta reservoirs.


2020 ◽  
Author(s):  
Cong Pu

<p>Recent advancements in embedded sensing system, wireless communication technologies, big data, and artificial intelligence have fueled the development of Internet of Vehicles (IoV), where vehicles, road side unit (RSUs), and smart devices seamlessly interact with each other to enable the gathering and sharing of information on vehicles, roads, and their surrounds. As a fundamental component of IoV, vehicular networks (VANETs) are playing a critical role in processing, computing, and sharing travel-related information, which can help vehicles timely be aware of traffic situation and finally improve road safety and travel experience. However, due to the unique characteristics of vehicles, such as high mobility and sparse deployment making neighbor vehicles unacquainted and unknown to each other, VANETs are facing the challenge of evaluating the credibility of road safety messages. In this paper, we propose a blockchain-based trust management system using multi-criteria decision-making model, also referred to as Trust<sup>Block</sup><sub>MCDM</sub>, in VANETs. In the Trust<sup>Block</sup><sub>MCDM</sub>, each vehicle evaluates the credibility of received road safety message and generates the trust value of message originator. Due to the limited storage capacity, each vehicle periodically uploads the trust value to a nearby RSU. After receiving various trust values from vehicles, the RSU calculates the reputation value of message originator of road safety message using multi-criteria decision-making model, packs the reputation value into a block, and competes to add the block into blockchain. We evaluate the proposed Trust<sup>Block</sup><sub>MCDM</sub> approach through simulation experiments using OMNeT++ and compare its performance with prior blockchain-based decentralized trust management approach. The simulation results indicate that the proposed Trust<sup>Block</sup><sub>MCDM</sub> approach can not only improve fictitious message detection rate and malicious vehicle detection rate, but also can increase the number of dropped fictitious messages.<br></p>


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