Silvya Dewi Rahmawati
Liquid loading is a phenomenon where fluids originally dispersed in gas accumulate due to gas velocity not reaching its critical value. The accumulation in the tubing can cause erratic and slugging flow, leading to a decreased production rate and eventually killing the well. Prediction of gas critical rate was usually done using empirical equations such as (Turner et al., 1969) and (Nosseir et al., 2000). Still, the use of empirical equations requires manual adjustment for different data sets. Therefore, this study presents a more efficient and accurate method of predicting the critical rate of gas well using a machine learning algorithm.
This research uses 94 data from (Turner et al, 1969) and (Coleman et al,1991) to build a machine learning model to predict critical rate. From the dataset, variable selections were done by implementing Spearman Correlation. The model selected was XGBoost due to high R2, and low MSE, RMSE, MAE values with low differences in training and testing R2 that minimize the risks of overfitting.
The critical rate predicted with XGBoost was 1.85 MMSCFD while the actual critical rate measured was 1.84 MMSCFD. XGBoost exhibits 0.54% error compared to 7.01% with the Turner Equation, without the use of manual adjustment with a different dataset. Using decline curve analysis to forecast the production rate decline of Well-YY and to predict the time of liquid loading, the predicted time was before September 2017, whereas the actual liquid loading time was January 2018.
Mengumpulkan data sumur gas untuk melakukan training terhadap pengembangan machine learning yang dikakukan. Membangun machine learning untuk memprediksi terjadinya peristiwa liquid loading di sumur gas yang dapat menghambat produksi gas. Menambahkan analisa machine learning terkait profile produksi sumur
Pengembangan penelitian ini akan memperkaya pengembangan machine learning dan artificial intelegence terkait prediksi terjadinya liquid loading pada sumur gas. Dengan penerapan teknologi ini dapat menghindari terjadi nya sumur mati di lapangan akibat peristiwa liquid loading dan menurunkan produksi gas nasional.