4.7 Article

Experimental Investigation and Modeling of Fluid and Carbonated Rock Interactions with EDTA Chelating Agent during EOR Process

期刊

ENERGY & FUELS
卷 37, 期 2, 页码 919-934

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.energyfuels.2c02702919Energy

关键词

-

向作者/读者索取更多资源

The study focuses on using a chemical called EDTA chelating agent to investigate the contact angle differences and rock dissolution in a carbonate reservoir under various conditions. The results show that at least 5 wt% of EDTA chemical is needed for oil recovery, and adding 1 and 10 wt% of EDTA to the seawater solution significantly reduces the interfacial tension. The contact angle experiments demonstrate that rock becomes more hydrophilic with increasing pH, solution temperature, and chelating agent concentration.
The injection of chemical fluids into oil reservoirs is gaining widespread attention in light of the declining conventional oil resources by recovering more hydrocarbons. This study is focused on using a chemical called ethylenediaminetetraacetic acid (EDTA) chelating agent in a carbonate reservoir to shed light on contact angle differences of 625 aged thin sections and rock dissolution under the influence of different pHs, temperatures, chelating times, and various chelating agent concentrations in seawater. According to a rock dissolution test, at least 5 wt % of EDTA chemical is needed to obtain oil recovery. A zeta potential test and scanning electron microscopy (SEM) images revealed that the mechanism of adsorption at low pH values and the expansion of the electrical double layer (EDL) at high pH values were responsible for wettability alteration, and an increase in EDTA concentration intensified each mechanism. Interfacial tension (IFT) measurements also showed that adding 1 and 10 wt % of the EDTA to the seawater solution reduced the IFT by 67.75% and 76.08%, respectively. The contact angle experiments demonstrated an increase in the mechanism that leads rock to behave more hydrophilically as pH, solution temperature, and chelating agent concentration in saltwater increased. Artificial neural network (ANN) methods also led to the introduction of a model to predict the contact angle employing multilayer perceptron neural networks (MPNN) and cascade feedforward neural networks (CFFNN). The CFFNN with two hidden neurons and trained by the Levenberg-Marquardt backpropagation algorithm is the most accurate model when comparing the accuracy of models for predicting contact angle values. The CFFNN model indicated that the weight percentage of the chelating chemical, which has a share of about 90%, had the greatest influence on the contact angle, and chelating time, with a share of less than 10%, had the least.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据