Selection & Optimization of Artificial Lift Using Delphi, TOPSIS, and SAW Methods for Natural Flow Oil Wells at HAS Field

The HAS field started producing oil and gas in 2004 until 2018, production wells in HAS experienced a decrease in oil production from 45,000 bopd to 6,190 bopd and an increase in water production from 0 bwpd to 20,463 bwpd. The decline in production occurs due to increased water production. The decrease in production was caused by a decrease in reservoir pressure, causing a larger water cut. Therefore, it is necessary to optimize production wells by considering the things mentioned above. The artificial lift selection method used is the Delphi method which has 21 screening parameters combined with the Topsis method; helps facilitate Decision-Making from various complex alternatives, by conducting comprehensive comparisons between each alternative and using the Simple Additive Weighting (SAW) method; known as the weighted addition method. The selection of the Artificial Lift in the HAS Field was carried out based on the reservoir parameters, production, well construction, and the economic factors of the artificial lift used. The artificial lift method that will be used in the HAS Field is the Electrical Submersible Pump (ESP). Based on the results of the selection of an artificial lift with a combined method of Delphi, Topsis, and SAW, Efforts to increase production with an electric submersible pump (ESP) are carried out by optimizing the number of stages and setting the frequency to a value of 45 Hz. Further optimization is carried out by gradually changing the pump frequency up to a maximum of 60 Hz, without changing the pump type. From the results of the economic analysis in the HAS Field, it was found that the most economical scenario was to use an ESP pump with the highest NPV@10 % value than the other scenarios, namely 434.85 MUS$.


PRELIMINARY
The HAS field produces oil and gas through production wells in PAD-A and PAD-B. Several things behind the implementation of this research are the long-term plan for the HAS field, optimization of oil well production in the HAS field, and the efficiency of gas production to increase oil well production. The purpose of this study is to analyze oil wells in the HAS Field that have the potential to increase their production with Artificial Lift and obtain recommendations and the results of Artificial Lift designs for suitable and efficient well candidates.
Problems arise when oil production drops drastically followed by a significant increase in water cut during the period from 2012 to 2018. It can be seen in Figure 1 that oil production was 40,000 bopd in 2012 and decreased to 6,190 bopd in 2018. The main cause is a decrease reservoir pressure of natural flow oilwell, this can be indicated due to a decrease in the rate of liquid production. After drilling and scoring for each parameterthen an assessment can be made for the wells in the HAS field, as shown in Table 3 .  After assessing each parameter for the wells in the HAS field, the next step is to conduct an assessment using the Topsis method and the Simple Additive Weighting (SAW) method.

TOPSIS method
Topsis is a method for multi-criteria decision analysis (Hwang and Yoon, 1981), which is an attempt to help facilitate Decision-Making from various complex alternatives, by making comprehensive comparisons between each alternative.
This method is carried out by evaluating 21 parameters as was done in the Delphi method. After assessing each parameter, the next step is to add up the scores for each parameter. Then calculate the Distance (Di) for the positive solution and the negative solution as shown in Table 4. Then calculate the Relative Closeness (Ci) value for each artificial lift. If the relative close (Ci) value is close to 1, then artificial lift is the optimal artificial lift solution/method to be used. Distance (Di) positive formula:

Table 4. Tabulation of Di+ and Di-Value Calculation Results (HAS-12)
Based on the values of Di+ and Di-in each of the parameters shown in Table 4, the calculation of the Relative Value (Ci) for each artificial lift is carried out, the next step is to calculate the value of relative closeness (Ci). Artificial Lift with a relative proximity value close to 1 is the optimal artificial lift solution/method.

Table 5. Calculation results of Di and Ci values (HAS-12)
From the results of the calculation of the Ci value, it can be seen that the optimal artificial lift for the HAS-12 Well based on 21 screening parameters using the TOPSIS method is ESP for rank 1 and Gas Lift for rank 2.

Simple Additive Weighting (SAW) Method
The next step is to validate the results of the TOPSIS screening method by comparing the results of the TOPSIS screening method using the results of the artificial lift screening with the Simple Additive Weighting (SAW) method.
The SAW method is often known as the weighted addition method. The basic concept of the SAW (Simple Additive Weighting) method is to find the total weight of each parameter. This method is done by determining the value (score) for each parameter and then multiplying the parameter score by the weighting factor for that parameter. The artificial lift with the highest total score is the optimal artificial lift to apply. The SAW method is a scoring combination method assigned to the parameter with the expected effect on each possible alternative. This is the most frequently used method because it is relatively simple. (Rodriguez. et al, 2018).
If the results between the selection using the Topsis method are the same as the SAW method, it can be seen that the results of the selection based on these 21 parameters can be used/applied to the HAS-12 well.
In this SAW method, the calculation for the value of each parameter is carried out by multiplying the score parameter by the weighting factor of the parameter, an example of the calculation for the depth parameter is as follows,  Parameter 1 (Depth -ESP) Aj ESP : Weighting Factor x ESP Score Aj ESP : 8 x 3 Aj ESP : 24  Parameter 1 (Depth -Gas Lift) Aj GL : Weighting Factor x GL Score Aj GL : 8 x 3 Aj GL : 24 After that, do the sum of 21 parameters for each artificial lift, as shown in Table 6.

Table 6. Calculation Results using the SAW Method (HAS-12)
The artificial lift with the highest total score is the optimal artificial lift to be applied to the HAS-12 well. From the results of screening using the Simple Additive Weighting (SAW) method, it can be seen that the optimal artificial lift for use in the HAS-12 Well is ESP for the first rank and Gas Lift for the second rank, as shown in Table 7.

Artificial lift optimization
Determination of the electric submersible pump (ESP) optimization method that considers the economic limit value of the well for the installation of an artificial lift of 23 BOPD and a critical rate of 1000 -1300 BLPD in the HAS field.
Optimizing with an electric submersible pump (ESP) is done by optimizing the number of stages and setting the frequency to a value of 45 Hz. Further optimization is carried out by gradually changing the pump frequency to a maximum of 60 Hz, without changing the pump type.

HAS-12
Production of HAS-12 started on August 5, 2009 until January 28, 2021, with the latest production flow rate, namely oil production rate (Qo) of 339.82 BOPD, water production rate (Qw) of 1417.08 BWPD, liquid production rate ( Ql) is 1756.89 BLPD, gas production rate (Qg) is 0.55 MMSCFD and water cut is 80.66%. The HAS-12 will be optimized with an Electric Submersible Pump (ESP) when the oil flow rate reaches 23 BOPD. After the ESP optimization was carried out, the oil production rate (Qo) became 27.2 BOPD, and the inflow vs outflow graph after optimization is shown in Figure 2. Table 9. shows the optimization of HAS-02. Figure 3 shows the results of the basecase prediction until December 31, 2030. While Figure 4 is the result of the plot between Basecase vs ESP Optimization with Cumulative oil until December 31, 2030 is 1588.94 STB.

HAS-18
HAS-18 started production on February 19, 2012 until January 28, 2021 (cut off date) with the production rate at the cut off date for oil (Qo) is 75 BOPD, water rate (Qw) is 1763.56 BWPD, liquid rate ( Ql) is 1838.56 BLPD, and the gas rate (Qg) is 0.21 MMSCFD. The HAS-18 will be optimized with an Electric Submersible Pump (ESP) when the oil flow rate reaches 23 BOPD. After the ESP optimization was carried out, the oil production rate (Qo) became 29.4 BOPD, and the graph of inflow vs outflow after optimization was shown in Figure 5. Table 10 shows the optimization of HAS-18. Figure 6 shows the results of the basecase prediction until December 31, 2030. While Figure 7 is the result of the plot between Basecase vs ESP Optimization with Cummulative oil up to December 31, 2030 of 202.68 STB.

Economic Analysis Scenario
Optimization of production carried out in the HAS Field is carried out with 2 (two) types of Artificial Lift, namely Electrical Submersible Pump (ESP) and Gas lift. Optimization with Gas Lift is carried out by 2 (two) types of gas injection, namely clean gas obtained from gas purchases at Gasuma or obtained from H2S & CO2 Removal and raw gas obtained directly from bore gas which is injected into the well using gas. lift.
Based on the optimization efforts carried out using two types of artificial lifts, namely ESP and gas lift, in the economic analysis of the HAS field, 5 (five) scenarios of economic calculation results from optimization and 1 (one) calculation of production base case are used, with the details of the scenarios as follows: 1. Basecase Basecase is the economic calculation of the HAS Field without optimization on the existing lifting conditions. 2. Scenario I (ESP Lease) Scenario I is the economic calculation of the HAS Field with the existing lifting converted into ESP which is rented from the vendor. 3. Scenario II (Gas Lift + Clean Gas From Gasuma) Scenario II is an economical calculation with the existing lifting which is converted into a gas lift by gas injection using clean gas purchased from Gasuma. 4. Scenario III (Gas Lift + Clean Gas From H2S & CO2 Removal) Scenario III is an economic calculation with the existing lifting which is converted into a gas lift by gas injection using clean gas from clean wells in the HAS Field with H2S & CO2 Removal. The time schedule for economic scenarios, 1 (one) basic economic analysis scenario and 2 (two) optimization results economic analysis scenarios are shown in Table 11.

Economic Calculation Results
The results of the field economic analysis for each scenario can be seen in Table 12. From the results of the economic analysis, it can be seen that the scenario that uses ESP is the scenario that has the highest oil production value with the lowest investment value, thus obtaining a higher NPV when compared to the scenario using gas. elevator.
From the 2 (two) economic analysis scenarios of the HAS Field, based on the obtained NPV value, it can be seen that Scenario I (ESP Lease) is the most optimal scenario when compared to the scenario using a gas lift.

Table 12. Results of the HAS Field Economic Analysis
In the economic analysis of the HAS Field, a sensitivity analysis was carried out on the existing economic indicators, namely NPV by considering changes in economic parameters, namely: 1. Operating Cost 2. Investment Value 3. Production Rate (Production) 4. The price of crude oil (Oil Price) The graph of the results of the sensitivity analysis can be seen in Figure 8.

CONCLUSION
Based on the results of the Artificial Lift Study Analysis in the HAS Field, it can be concluded that: 1. Based on the results of the artificial lift screening using the results of the integration of the Delphi method, the Topsis method and the Simple Additive Weighting (SAW) method, the artificial lift method that is suitable to be applied in the production of the HAS Field is the Electrical Submersible Pump (ESP) at first. place and Gas Lift in second place. 2. In calculating the economic analysis of Artificial Lift in the HAS Field using 6 (six) scenarios, namely: