Estimating the Effect of Flow Efficiency on Oil Flow Rates Using Artificial Neural Network
Andrian Sutiadi (a*), Muhammad Taufiq Fathaddin (b*), Suryo Prakoso (b), Dwi Atty Mardiana (b)

a) PT. Prima Energi, Sahid Sudirman Centre, 53rd Floor, Jl. Jend. Sudirman Kav. 86, Jakarta Pusat 10220, Indonesia
*andrian.sutiadi[at]primaenergy.id
b) Department of Petroleum Engineering, Universitas Trisakti, Jakarta Barat, Indonesia
*muh.taufiq[at]trisakti.ac.id

Abstract

Frequently drilling activity causes formation damage. The damage can be estimated from the drill stem test analysis. Formation damage is indicated by a skin factor (S) with higher than 0 or Flow Efficiency (FE) parameter lower than 100%. Improvement of formation damage can cause an increase in flow rate. Artificial Neural Network (ANN) model is used to estimate the increase flowrate of productive zones on ^X^ Field with FE 20% to 100%.
The ANN model used reservoir pressure, temperature, permeability, formation thickness, specific gravity of oil, gas to oil ratio, oil viscosity, and flow efficiency as input parameters. While the flow rate is as the output parameter. Based on predictions with the ANN model, obtained the increase in flow rate varies between 1.1% to 78.0%. Besides, it is found that flowrate of the layers on the field is influenced by the product of kh, where kh is equivalent with the flowrate.

Keywords: artificial neural network- flow efficiency- flowrate- skin factor- oil reservoir

Topic: Reservoir engineering