Research on Economic Evaluation Model and Application of Deep Reservoir Based on Break-even Method

In order to strengthen the economic level of deep reservoir development, this article takes the oil reservoirs in the Zhungeer Basin, Xinjiang as an example, and uses the break-even method to evaluate and analyze the economic benefits of regional reservoir development. Based on the characteristics of the economic structure of reservoir development, a deep reservoir economic evaluation model was constructed and applied to the evaluation of the economic benefits of the reservoirs in the northwestern margin, the southern margin, and the eastern Zhunge. The application results show that the overall economic benefits of the northwestern margin are the highest, and the economic benefits of category A in the south margin are the highest. In order to further improve the economic development level of deep reservoirs, it is recommended to focus on the geology of reservoir distribution in Class I economic reliability areas.


Introduction
The exploitation of oilfield resources is an important means of my country's economic development. By exploiting such resources, it can drive the development of other fields [1]. At present, the exploration of shallow and middle oil and gas resources is more difficult, and oil and gas buried below 3,500 m is easier to find [2]. Therefore, my country is experimenting with oil and gas resources below 3500m underground. Due to the uneven distribution of oil and gas reserves, it is necessary to evaluate the reserves of various regions in order to improve the economic development level of deep reservoirs [3]. This paper uses the break-even method as a research tool to establish an economic evaluation model for deep reservoirs, and applies it to the Zhungeer Oilfield in Xinjiang for exploration.

Reservoir classification
When exploring the types of oil reservoirs, this article uses the latest resource evaluation categories proposed by China National Petroleum Corporation as the standard to accurately classify the buried depth of Xinjiang oil and gas reservoirs: (1) Shallow layers: oil and gas reservoirs with a buried depth of less than 2000m; The buried depth range is 2000m～3500m; (3) Deep layer: the buried depth range of oil and gas reservoir is 3500m～4500m; (4) Ultra deep layer: The buried depth of oil and gas reservoir is higher than 4500m. [4][5] During the exploration of Xinjiang oil and gas reservoirs in this study, according to the distribution structure of oil and gas reservoirs in the region, deep oil reservoirs are defined as reservoirs with a burial depth higher than 3000m.

Exploration of deep reservoirs in the Zhungeer Basin
In this paper, the Zhungeer Basin is used as a deep reservoir exploration site. The number of wellheads in this area with a drilling depth of more than 4500m is about 70. It can be roughly divided into 5 areas to predict oil reserves: (1) Basin 4 well area, The predicted reservoir reserves are about 1906×104t; (2) Penshen 2 Well, predicted reservoir reserves are about 5293×104t; Xiayan 2 Well, predicted reservoir reserves are about 3993×104t; Badaowan Formation, predicted natural gas reserves are 388.66× 108m 3 ; Well Jiuyun 1, predicted natural gas reserves 117.52.66×108m 3 ; Well Mo 10, predicted natural gas reserves 102.09×108m 3 . In summary, the deep oil reservoirs in the Zhungeer Basin have large reserves and great development potential. Therefore, selecting this area as a research area for deep reservoir economic evaluation has certain research value. The Zhungeer Basin has multi-cycle characteristics. For many years, it has been affected by the Himalayan movement and produced different types of traps. These traps are suitable for oil and gas accumulation and their locations are called oil and gas reservoir sites. Due to the relatively low degree of exploration in the basin, seismic survey lines in the hinterland of the area are sparsely distributed. Therefore, the number of traps found in this survey is relatively small. In this study, 74 traps were selected as the economic evaluation objects of deep reservoirs. Among them, there are 28 traps in the northwestern margin; 31 traps in the southern margin; 15 traps in the eastern Zhunge area.

Break-even method
The break-even method is also known as the cost-profit analysis method, which is mainly due to the exploration of the income or output decision-making problem at the critical point of non-loss and unprofitable economic operations [6]. Among them, the critical point is a point at which the profit and loss reaches a balance, which is called the break-even point. Obviously, if the sales volume or production volume is lower than the sales volume (or production volume) corresponding to the equilibrium point, a loss will occur, and vice versa [7][8]. This paper uses the break-even method to evaluate the economic performance of deep reservoir reserves.

Estimate of income
Due to the special nature of oilfield exploitation, it is divided into two stages, one of which is the gradual decrease in output, which is called the period of decline in output, and the other stage that the output tends to stabilize, called the period of stabilization of output [10]. With the change of time, the income of the oil field has changed. Among them, the formula for calculating income during stable production period: The formula for calculating income in decline period: In formula (1) and formula (2), P represents the crude oil commodity rate, unit: %; D represents the comprehensive decline rate in years, unit: %; NC represents the reserves of economic traps, unit: t; Ir Represents internal rate of return, unit: %; K represents unit price of crude oil, unit: yuan/t; Tx represents comprehensive tax rate, unit: %; VP represents reservoir exploitation speed, unit: %; n represents evaluation period; n2 represents reservoir exploitation Decrease years; n1 represents the stable years of reservoir production.

Estimate of profitable expenditure
Estimated income and expenditure during stable production period: In formula (3) and formula (4), A represents the period expense rate, unit: %; C0 represents operating cost, unit: yuan/t.

Estimation of capital expenditure
Expenses in this area can be divided into three investment indicators: production capacity construction, exploration drilling, and exploration seismic [11]. The estimation formula for each expenditure indicator is as follows: Investment estimate for capacity construction: Investment estimate for exploration drilling: Estimation of exploration seismic investment: In formula (6) and formula (7), represents the seismic exploration investment cost, unit: yuan; represents the production capacity construction investment cost, unit: yuan; represents the seismic expenditure per unit area, unit: yuan/km2; represents the exploration well exploration investment cost, Unit: Yuan; f stands for well pattern density, unit: mouth/km2; stands for the proportion of water injection wells, unit: %; stands for the cost of unit footage of a single well for oil testing, unit: Yuan/m; h stands for well depth, unit: m; M On behalf of the ground construction cost coefficient, unit: %; on behalf of the exploratory well unit footage expenditure, unit: yuan/m; on behalf of the number of exploratory wells, unit: mouth, if the value is less than or equal to 1, then the value is 1, if it is greater than 1, not greater than 2 , The value is 2, and when it is greater than 2, the value is 3.

Establishment of evaluation model
The break-even point in the economic evaluation of deep reservoirs is that the net present value of income is equal to the present value of fixed asset investment. According to the numerical solution formula of the above parameters, the economic evaluation model of deep reservoirs can be sorted out, and the economic reserves of traps can be obtained:

Determination of different parameters and values
The difference parameter refers to the regional difference, and the difference in the oil reservoir production environment in different regions leads to different parameters. In this study, the three regions of Zhundong, South and Northwest are the research objects, and the values of various difference parameters in each region are determined respectively, as shown in Table 1.

Variables and test points value
This model is used to obtain the economic reserves of oil reservoirs, expressed by the symbol of Nc, and the unit is ten thousand tons. There are three model variables, which are internal rate of return, reservoir depth, and trap area. Among them, the internal rate of return variable is represented by the symbol IRR, the value range is 8-20, the unit: %; the reservoir depth variable is represented by the symbol h, the value range is 3000 ~ 7000, the unit: m; the trap area variable is the symbol Sqb Indicates that the value range is 10 to 110, the value interval is set to 20, and the unit is km2.

Calculation results of economic evaluation of deep reservoir reserves
Using the economic evaluation model designed in the previous section, that is, formula (8), comprehensive evaluation and analysis of the economic performance of deep reservoir reserves in different regions are carried out, and the parameter values and test point values are substituted into the formula, and the following calculation results can be obtained.

Economic evaluation calculation results of deep reservoirs in the northwestern marginal area
In this study, SPSS software was used to sort out parameter data such as the internal rate of return and economic reserves of deep reservoirs in the northwestern margin, and obtain regression accuracy statistics, variance and regression coefficient calculation results, as shown in Table 2, Table 3, and Table 4.  Table 2, the correlation coefficient corresponding to the trap area, economic reserves, reservoir depth, and internal rate of return is 0.679. From this, it can be judged that there is a strong linearity among the economic calculation parameters of the reservoir in this area. Related features. From the statistical results in Table 3, the associated probability value of deep reservoirs in this area is not higher than 0.001, and the F value is 107.22. It can be inferred from this that there is a linear regression characteristic between the calculation parameters of the reservoir in this area. When the value of the independent variable changes, the dependent variable will also change.

Calculation results of economic evaluation of deep reservoirs in Zhundong area
Use SPSS software to sort out parameter data such as internal rate of return and economic reserves of deep reservoirs in Zhundong area, and obtain regression accuracy statistics, variance and regression coefficient calculation results, as shown in Table 5, Table 6, and Table 7.  It can be seen from the statistical results in Table 6 that the associated probability of the reservoir model in this area does not exceed 0.001, and the statistic F value is 103.98. It can be inferred from this that there is a linear regression characteristic between the calculation parameters of the reservoir in this area. When the value of the independent variable changes, the dependent variable will also change. Based on the statistical results in Table 7

Economic evaluation and calculation results of deep reservoirs in the southern margin area
Use SPSS software to sort out parameter data such as the internal rate of return and economic reserves of deep reservoirs in the southern margin area, and obtain regression accuracy statistics, variance and regression coefficient calculation results, as shown in Table 8, Table 9, and Table 10. The correlation coefficient in Table 8 is 0.674, and it can be judged that there is a strong correlation between various parameters of deep reservoirs in this area. The statistical results in Table 9 show that the associated probability of the reservoir model in this area does not exceed 0.001, and the statistic F value is 104.28. It can be inferred from this that there is a linear regression characteristic between the reservoir calculation parameters in this area. When the independent variable value changes, the dependent variable changes more significantly.

Economic reliability evaluation standard
According to the internal economic evaluation requirements of the reservoir development company, the economic reliability evaluation standards are formulated: Type I evaluation standard: internal return is higher than 16%; Type II evaluation criteria: the internal income range is 12% to 16%; Type III evaluation criteria: internal return is less than 12%.

Geological-economic reliability evaluation standard
Class A benefits: Geological reliability and economic reliability are both Class I; Class B benefits: There are one class I and one class II in geological reliability and economic reliability, or both are class II Class C benefit: There is at least one Class III in geological reliability and economic reliability.

Analysis of evaluation results
The SPSS software was used to calculate the economic reserves of oil reservoirs in each area, and the relevant parameter values of each area were substituted into regression model 9, regression model 10, and regression model 11 to evaluate the geological reliability level and economic reliability level of  Table 11 and Table 12 are obtained. The statistical results in Table 11 show that among the 74 traps, there are 10 class A benefit traps, 34 class B benefit traps, and 30 class C benefit traps. Among them, the southern marginal regional trap produces more A-class benefits. From the statistical results in Table 12, the reserves of deep reservoir traps in Xinjiang are divided into three types of beneficial reserves. Among them, Type B benefit reserves account for the largest proportion, accounting for 54.78% of the total, and the corresponding total reserves are 52588×104t. Category C benefits ranked second, accounting for 34.68% of the total, and corresponding total reserves were 33292×104t. Type A effects account for the smallest proportion of the total, with a value of 10.54%, which corresponds to a total reserve of 10113×104t. Among them, the northwestern margin has the highest economic benefit.

Recommendations for deep reservoir management
By constructing a reservoir economic evaluation model, this article can more clearly grasp the economic benefits of reservoir development in various regions, and help guide the development of reservoirs. The economic reliability evaluation standard is involved in the set evaluation standard. If the evaluation result of this index is Class I and the grade of the geological evaluation result is Class II or Class III, then it cannot be ignored when exploiting oil fields. This area should be further surveyed to fully grasp the geological structure of this area, improve the level of mining technology, and obtain higher economic benefits.

Conclusion
This paper selects the break-even method as the research tool, and takes the oil reservoir economic evaluation of the Zhungeer Basin in Xinjiang as the research content. By constructing a deep reservoir economic evaluation model, comprehensive evaluations of the economic benefits of the oil reservoirs in the northwestern margin, southern margin, and Zhundong regions were made. The evaluation results show that the overall economic benefits of the northwestern margin are the highest, and the economic benefits of category A in the south margin are the highest. In order to further enhance the economic benefits of deep reservoir development, this paper gives some management suggestions based on the evaluation criteria.