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COUPLED CAPACITANCE RESISTANCE MODEL AND AQUIFER MODEL FOR WATERFLOOD PERFORMANCE PREDICTION & OPTIMIZATION

Penulis : Dinny Khalbia [12217066]
Kontributor / Dosen Pembimbing :
  • Prof. Dr. Ir. Hasian P. Septoratno Siregar, DEA
  • Billal Maydika Aslam, S.T., M.T.
Jenis Koleksi : Tugas Akhir
Penerbit : Teknik Perminyakan
Fakultas : Fakultas Teknik Pertambangan dan Perminyakan
Subjek :
Kata Kunci : CRMT, Model Analitikal Aquifer, Waterflood, Water Influx
Sumber :
Staf Input/Edit : Suharsiyah  
File : 2 file
Tanggal Input : 21 Jun 2021

ABSTRAK Dinny Khalbia
PUBLIC Suharsiyah
2021 TA PP DINNY KHALBIA 1.pdf?
PUBLIC Suharsiyah

Waterflood method is one of the methods chosen to increase oil recovery in mature fields in order to meet the target of increasing recovery. In analyzing the performance of waterflood, it is usually done using a simulation but this method will take a long time. This study proposes a Capacitance-Resistance Model method that can provide faster results, with one of the CRM methods, namely CRMT, by observing the field as a whole. The CRMT method requires production history and injection history data. This method examines how waterflood injection affects a field. However, it is realized that the effect on the reservoir is not only from waterflood injection but also influenced by water influx. Therefore, to identify the effect of waterflood and water influx on the reservoir, it is proposed the development of the CRMT model by combining the CRMT and the aquifer model, which is usually called the “Coupled CRM Aquifer Model. This model can also be used to analyze and predict reservoir performance for fields that have not been injected. In this study an aquifer in an unstable formulation state, without requiring the function of a dimensionless aquifer. And in this study Carter and Tracy formulation that allows treatment of both unsteady-state and pseudosteady-state flow behaviors with the simplified form of the van Everdingen and Hurst (vEH) formulation is used. This model is generated using synthetic data, the first synthetic data with 4 producers without injectors and the second synthetic data with 5 injectors and 4 producers. After estimating the total liquid rate and oil rate for 2 different cases, history matching was carried out and in the end the results were matched enough so that it can be said that this model can be used to predict waterflood performance. It is better to do history matching after a balance condition occurs. In this study, forecasts were also carried out by increasing the injection water rate and the results showed that increasing the injection water rate could increase the production rate.

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