4.7 Article

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

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ENERGY & FUELS
卷 -, 期 -, 页码 -

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AMER CHEMICAL SOC
DOI: 10.1021/acs.energyfuels.2c02702

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This study focuses on using EDTA chelating agent in a carbonate reservoir to investigate contact angle differences of aged thin sections and rock dissolution. The results show that at least 5wt% of EDTA is needed for oil recovery. Adding 1wt% and 10wt% of EDTA to the seawater solution can reduce interfacial tension by 67.75% and 76.08% respectively. The contact angle experiments demonstrate that rock behaves more hydrophilically as pH, solution temperature, and chelating agent concentration in saltwater increase.
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.

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