Hadinata, Wahyu (2025) Analisis Parameter Yang Signifikan Berpengaruh Dalam Memprediksi Retensi Surfaktan Pada Batuan Sandstone Menggunakan Metode Artificial Neural Network. Other thesis, Universitas Islam Riau.

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Abstract

Surfactant retention refers to the ability of surfactants to be adsorbed within rock pores. Once adsorbed, the surfactant adheres to and remains within the rock matrix, rendering it unusable for further displacement, which consequently diminishes its economic value. This retention can be attributed to several factors: permeability, reservoir temperature, NaCl concentration, surfactant concentration, surfactant density, and molecular weight. These factors will serve as the parameters for this study, aiming to identify the most influential factor affecting surfactant retention. This research utilized CMG reservoir simulation software, employing 500 data samples generated by the software. The dataset was split with 80% for training and 20% for testing. An Artificial Neural Network (ANN) with a backpropagation approach was then applied using selected input data to generate an output that ranks the factors influencing surfactant retention. The model achieved an R-squared value of 0.9827 for the training data and 0.9104 for the testing data, indicating a high degree of accuracy as both values approach 1. The parameters were ranked by their influence, from most to least significant, as follows: permeability, followed by NaCl concentration, surfactant concentration, molecular weight, temperature, and surfactant density.

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