CN117967270A - A method for adjusting and intensifying well pattern deployment in low-permeability tight gas reservoirs - Google Patents

Abstract

The invention relates to the technical field of development and design of low-permeability tight gas reservoirs, in particular to a method for adjusting and encrypting well pattern deployment of a low-permeability tight gas reservoir. The invention aims to provide a set of encryption well pattern adjusting method capable of effectively improving well pattern deployment accuracy for a hypotonic compact gas reservoir, wherein the method adopts a method combining numerical simulation and gas reservoir engineering to study the specific implementation steps of encryption well pattern adjustment of the hypotonic compact gas reservoir; through optimizing the encryption-planned area, researching the EUR and the pressure drop degree of the encryption-planned well, optimizing the well type and the well spacing of the encryption-planned well, a set of method for economically and effectively adjusting the encryption well pattern is provided, the reservoir where the encryption-planned well is located is analyzed more accurately, and the deployment of the low-yield encryption well can be effectively reduced.

Description

A method for adjusting and infilling well pattern deployment in low-permeability tight gas reservoirs

Technical Field

The invention relates to the technical field of low-permeability tight gas reservoir development design, and in particular to a method for adjusting and deploying an infill well pattern.

Background technique

Low-permeability tight gas reservoirs often have complex reservoir structures, strong heterogeneity, and are difficult to achieve high-precision exploration in the early stages of development. As gas field development continues, there will be problems such as a continuous reduction in high-quality reserve areas and a gradual decline in reservoir quality. Low-permeability tight gas reservoirs are often developed using a fixed well pattern in the early stages of development, but the initial well pattern is usually difficult to mobilize all the reserves of the gas reservoir, so it is necessary to adjust the well pattern and increase density in the middle and late stages of development. At present, the common methods for well densification of low-permeability tight gas reservoirs are: determining the feasibility of well densification of the target gas reservoir by analyzing the average cumulative gas production, increased gas production of the densified wells and the incremental recovery rate corresponding to different well densities (a method and device for determining the feasibility of well densification CN107939371A); performing simple abundance calculations and final cumulative gas production predictions on completed wells, and quickly and accurately calculating the number of wells that can be densified by gas production-reserves-recovery rate correlation analysis (a method for evaluating the potential of well densification of tight gas reservoirs CN112031757B); based on the known sand body logging permeability and reserve abundance, quickly predicting the reasonable well network density and the timing of densification adjustment (a method and system for predicting the reasonable well network density and the timing of densification adjustment of tight gas reservoirs CN115936232A); improving the oil displacement efficiency by allowing the new fluid distribution pattern to purge oil from those areas of the formation that are least affected by the original fluid distribution pattern (a well densification US4610301A). By analyzing the development of the target block reservoirs and combining the reserve abundance, the target blocks are classified, and the relationship between different well pattern densities and recovery rates is studied for each reserve type (HU Yong, MEI Qingyan, WANG Jiping et al. Well pattern infilling optimization for tight sandstone gas reservoirs [J]. Natural Gas Geoscience, 2020, 31(09): 1326-1333); a comprehensive evaluation based on geological models, numerical simulations, and dense well pattern test data verification shows that a reasonable dense well pattern should match the effective reservoir combination type and be closely related to gas prices and cost conditions (JIA Ailin, WANG Guoting, MENG Dewei, GUO Zhi, JI Guang, CHENG Lihua. Well pattern infilling strategy to enhance oil recovery of giant low-permeability tight gasfield; a case study of Sulige gasfield, Ordos Basin [J]. Acta Petrolei Sinica, 2018, 39(7): 802-813).

At present, the common way to infill the well network is to demonstrate the relationship between the density of the infill well network and the recovery rate and the cumulative gas production of a single well for the entire block, and then select the optimal well network density. However, low-permeability tight reservoirs are extremely complex and highly heterogeneous. When selecting infill potential areas, the reserve abundance is mainly used as a reference. Although this parameter can represent the planar distribution of reserves in each block, it cannot reflect the vertical development of the reservoir. Therefore, when using the existing well network infill method to arrange wells in low-permeability tight gas reservoirs, it is inevitable that some infill wells will have unsatisfactory production effects after they are put into production, increasing the cost of gas reservoir exploitation. There is an urgent need for a method that can accurately analyze the adaptability of well layout in a small range of reservoirs.

Summary of the invention

The purpose of the present invention is to provide a method for adjusting and filling well patterns that can effectively improve the accuracy of well pattern deployment for low-permeability and tight gas reservoirs. The method combines numerical simulation with gas reservoir engineering. When optimizing the potential area for filling, in addition to the reserve abundance, the pressure drop of the proposed filling wells is also considered. The reservoir where the proposed filling wells are located is analyzed more accurately, which can effectively reduce the deployment of low-yield filling wells and achieve the purpose of reducing costs and increasing efficiency. To achieve the above purpose, the present invention adopts the following technical solutions:

The steps include:

Step S1. Establish a gas reservoir geological model based on the well logging interpretation report and geological data of the early stage of the development of the target gas reservoir. Establish a numerical model of the target gas reservoir based on the production dynamic data of the current production wells in the target block, such as gas production, water production, and oil-casing pressure, and fit the block reserves, oil-casing pressure, and production. On this basis, predict the cumulative gas production EUR and formation pressure of a single well in 30 years of production, and determine the distribution of the remaining reserves of the target gas reservoir;

Step S2. According to the numerical simulation results, the single-well EUR values of the existing production wells are counted, and the production wells are divided into Class I high-yield wells, Class II medium-yield wells and Class III low-yield wells according to normal and skewed normal distribution.

Step S3. Analyze the distribution of remaining reserves in the target block, and select the potential area for infilling based on the reserve abundance, average effective thickness, porosity and permeability of the reservoir. The optimization principle is: on the basis of step S2, count the various physical parameters of the reservoir where the Class II wells are located, and use the reserve abundance, average effective thickness, thickness-weighted porosity and permeability of the Class II wells as the lower limit for screening the potential area for infilling.

Step S4. Determine the well type and reasonable well spacing of the infill wells according to the reservoir properties and geological conditions of the potential area to be infilled.

Step S5. In the proposed infill area selected in step S3, preliminarily determine the locations and number of infill wells to be deployed according to the infill well types and well spacings determined in step S4.

Step S6. In the numerical simulation model established in step S1, define the proposed infill wells, simulate their production for 30 years, and analyze the changes in the single well EUR, formation pressure, etc. of the proposed infill wells;

Step S7. Calculate the economic limit EUR of the optimal well type for the target gas reservoir;

Step S8. Screen the wells to be infilled in step S6 so that their EUR is greater than or equal to the economic limit EUR, and the pressure drop of the wells to be infilled is less than the average single-well pressure drop of the Class II medium-producing wells in step S2.

Step S9: Determine the wells screened out in step S8 as the final infill wells for the target gas reservoir.

Furthermore, in step S2:

The EUR of each single well predicted in step S1 is statistically analyzed using skewed distribution and normal distribution, and the EUR probability distribution curve is drawn. The classification boundaries of Class I high-yield wells, Class II medium-yield wells, and Class III low-yield wells are determined by the curve inflection points. The first inflection point value close to the origin in the EUR probability distribution curve is the upper limit of Class III wells and the lower limit of Class II wells, and the second inflection point value is the upper limit of Class II wells and the lower limit of Class I wells.

Furthermore, the step S4 comprises:

Step S41. Based on the reservoir properties and geological conditions of the infill potential area, combined with the implementation results of the horizontal wells that have been put into production and the adjacent vertical wells, the average daily gas production, EUR and single well investment of the put into production wells are compared to demonstrate the adaptability of the vertical and horizontal wells in the planned well location.

Step S42: Evaluate the rationality of the well spacing of the target gas reservoir by analogy, economic limit well spacing, economic reasonable well spacing, and production instability analysis. The rational well spacing obtained by comprehensive evaluation should be within the range of the well spacing obtained by the analogy method and greater than the economic limit well spacing.

Furthermore, the economic limit well pattern density refers to the well pattern density when the total output is equal to the total input, that is, the total profit is zero, and the calculation formula is as follows:

In the formula: F _min is the economic limit well network density, wells/km ² ; _ER is the recovery factor, %; α is the gas commodity rate, %; N is the geological reserves, 10 ⁸ m ³ ; T _is the gas tax rate, decimal; P is the gas unit price, yuan/m ³ ; O is the gas operating cost, yuan/m ³ ; A is the gas-bearing area, km ² ; I is the total investment in a single well, ten thousand yuan; R is the loan interest rate, decimal; T is the evaluation period, years; D _{min is} the economic limit well spacing, m.

Furthermore, by adding reasonable profit to Formula A, we can obtain the economically reasonable well pattern density calculation formula, namely:

Where: F _α is the economically reasonable well pattern density, wells/km ² ; _LR is the reasonable profit, yuan/m ³ .

Furthermore, typical representative wells of Class I high-yield wells, Class II medium-yield wells and Class III low-yield wells were selected, and the production instability analysis method was used to perform historical fitting on the gas production and casing pressure of the typical representative wells to determine the control radius of the typical wells, and twice the control radius was taken as the well spacing.

The typical representative wells of the Class I high-yield wells, Class II medium-yield wells and Class III low-yield wells are selected single well EUR, as well as wells with similar average EUR of Class I high-yield wells, Class II medium-yield wells and Class III low-yield wells.

Furthermore, the step S7 comprises:

The economic limit EUR is calculated using the cash flow method: net cash flow refers to the difference between the total cash inflow and the total cash outflow. Taking into account single well drilling + surface investment + boosting investment, gas price, production cost, stable production period, annual production decline rate, commodity rate, various tax rates, education surcharge, water conservancy construction fund, and internal rate of return, the cash flow is comprehensively reversed. The calculation formula D of the cash flow method is: Annual cash flow = (current year discount coefficient/(1+discount coefficient))×[original EUR×annual production decline rate×commodity rate×(sales price-production cost-resource tax-water conservancy construction fund×(1-income tax))-value added tax payable×(urban construction tax+education surcharge)+single well surface investment-single well boosting investment)×income tax]; the number of years when the cumulative cash flow changes from a negative loss to 0 is obtained, and the corresponding economic limit cumulative gas production is the economic limit EUR.

Compared with the prior art, the present invention provides a method for adjusting the deployment of an infilled well pattern, which has the following beneficial effects:

The present invention adopts a method combining numerical simulation and gas reservoir engineering to study the specific implementation steps of the infill well pattern adjustment of low-permeability tight gas reservoirs. By optimizing the proposed infill area, studying the EUR and pressure drop of the proposed infill wells, optimizing the well type and well spacing of the infill wells, a set of economical and effective methods for adjusting the infill well pattern is proposed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a method for adjusting and infilling a well pattern deployment in a low-permeability tight gas reservoir;

FIG2 is a diagram showing the current formation pressure distribution of the A3 layer in the embodiment;

FIG3 is a result of dividing the single well limit EUR in an embodiment;

FIG4 is a result of dividing the target block encryption potential area in the embodiment;

FIG5 is a well location deployment diagram of the proposed infill wells in the target block in the embodiment;

Figure 6 shows the calculation results of the economic limit EUR of a single vertical well;

FIG. 7 is a diagram showing the final deployment of infill wells in the target block in the embodiment.

Detailed ways

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

The present invention provides a technical solution:

Take a tight lithologic gas reservoir as an example. This gas reservoir is exploited by depletion. Vertically, there are four development layers A1, A2, A3, and A4 from top to bottom. The secondary production layers A1 and A2 are superimposed on the main layers A3 and A4. The current formation pressure distribution of the main layer A3 is shown in Figure 1. Currently, 179 vertical wells and 2 horizontal wells have been put into production in the target block. The existing well network does not fully control the reserves of the target gas reservoir, and it is now necessary to adjust the well network to increase density.

A method for adjusting and infilling a well pattern deployment in a low-permeability tight gas reservoir comprises the following steps:

Step S1, establish a gas reservoir geological model based on the well logging interpretation report and geological data of the early stage of the development of the target gas reservoir. According to the production dynamic data such as gas production, water production, and oil-casing pressure of the current production wells in the target block, establish a numerical simulation model of the target gas reservoir, and fit the block reserves, oil-casing pressure and production. On this basis, predict the cumulative gas production EUR and formation pressure of a single well in 30 years of production, and determine the distribution of the remaining reserves of the target gas reservoir;

Step S2, according to the numerical simulation results, the predicted single well EUR values of the existing production wells are counted, and the EUR probability distribution diagram of the single well is drawn as shown in Figure 3. The first inflection point value close to the origin in the EUR probability distribution curve is 1400×10 ⁴ m ³ , and the second inflection point value is 3800×10 ⁴ m ^3. The classification standard is established as follows: the single well EUR of Class I wells is greater than 3800×10 ⁴ m ³ , the single well EUR of Class Ⅰ wells is between 3800×10 ⁴ m ³ and 1400×10 ⁴ m ³ , and the single well EUR of Class ⅠⅠ wells is less than 1400×10 ⁴ m ³ .

Step S3, based on step S2, the average value of reserves abundance of Class II medium-producing wells is ^150m3 / ^m2 , and the average effective thickness of Class II wells is 20m. Taking the effective thickness as the weight, the weighted average porosity of Class II wells is calculated to be 5%, and the weighted average permeability is calculated to be 0.45mD. The criteria for screening the infill potential area are detailed in Table 1, and the results of the infill potential area division are shown in Figure 4.

Table 1 Criteria for the division of encryption potential areas

Reserve abundance (m ³ /m ² ) Effective thickness(m) Porosity(%) Permeability (mD) >150 >20 >5 >0.45

Step S4, determining the well type and reasonable well spacing of the infill wells according to the reservoir properties and geological conditions of the potential area to be infilled.

Further, in step S41, since the secondary production layers A1 and A2 in the target block overlap with the main production layers A3 and A4, and the A1 layer has poor continuity, the A2 layer has many combined production areas, and the effective drilling rate of horizontal wells in the A3 and A4 layers is low, it is preliminarily determined that the target block is not suitable for horizontal drilling.

Further comparison of the implementation effects of the put into production horizontal wells and adjacent vertical wells: Currently, there are only two put into production horizontal wells in the target block, one in each of the A3 and A4 layers, and there are three single-production vertical wells adjacent to them. The average daily production of the two horizontal wells in the initial stage of production is 2.21×10 ⁴ m ³ /d, and the average daily production of the adjacent vertical wells in the initial stage of production is 1.05×10 ⁴ m ³ /d, which is 2.1 times that of the vertical wells; the average single well EUR of the horizontal wells is 0.7975×10 ⁸ m ³ , and the average single well EUR of the adjacent vertical wells is 0.5350×10 ⁸ m ³ , which is 1.5 times that of the vertical wells; the investment of horizontal wells is 3.92 times that of vertical wells. Comprehensive analysis of reservoir geological conditions and the input-output of horizontal wells and vertical wells shows that vertical wells are preferred as infill well types.

Further, in step S42, the geological reserves of the target block are 1149.05×10 ⁸ m ³ , the superimposed gas-bearing area is 725.38 km ² , and the average reserve abundance is 170 m ³ /m ² . The reasonable well spacing of the target block is comprehensively evaluated by analogy method, economic limit well spacing, economic reasonable well spacing and production instability analysis method, where:

(1) Analogy

The average logging permeability of the gas zone reservoir is about 0.66mD, and the average reserve abundance of the A1-A4 section is 170m ³ /m ^2. Based on the comparison with the permeability and reserve abundance of other gas fields, the analogy method estimates that the reasonable well spacing for the development of the target block is 500-800m.

(2) Economic limit well spacing

According to the formula of economic limit well spacing, the economic limit well density of the target block is calculated to be 3.41 wells/ ^km2 , and the economic limit well spacing is 611m. The calculation parameters are shown in Table 2. The specific steps are as follows:

Table 2 Calculation parameters of economic limit well spacing and economic reasonable well spacing

parameter Value parameter Value Recovery factor _ER (%) 60.3 Gas-bearing area A (km ² ) 725.38 Gas commodity rate α(%) 96 Total investment per well I (including ground) (10,000 yuan) 1126.66 Geological reserves N (10 ⁸ m ³ ) 1149.05 Loan interest rate R (decimal) 0.062 Gas tax rate _Ta (decimal) 0.4496 Evaluation period T (years) 10 Gas unit price P (yuan/m ³ ) 1.225 Reasonable profit _LR (yuan/ ^m3 ) 0.25 Gas operating cost O (yuan/m ³ ) 0.197

(3) Economically reasonable well spacing

On the basis of the economic limit well density, reasonable profit is added, and the economic reasonable well density of the target block is calculated to be 2.58 wells/km ² , and the economic reasonable well spacing is calculated to be 703m. The calculation parameters are shown in Table 2. The specific calculation steps are as follows:

(4) Yield instability analysis method

On the basis of step S2, wells with single well EUR close to the average EUR of class I, II, and III production wells are selected as typical representative wells of class I high-yield wells, class II medium-yield wells, and class III low-yield wells. The production instability analysis method is used to perform historical fitting on the gas production and casing pressure of the typical representative wells to determine the control radius of the typical wells. Twice the control radius is taken as the well spacing, as shown in Table 3 for details.

Table 3 Calculation results of yield instability analysis method

Well Type Mean discharge radius (m) Calculate well spacing (m) I 374 748 II 339 678 III 295 590 average value 336 672

According to the results of comprehensive analysis and calculation, the well spacing of infill wells should be between 550m and 800m. Since the reasonable well spacing and the calculation results of the production instability analysis method are similar, the average value of 688m is taken as the reasonable well spacing for comprehensive evaluation of infill wells. See Table 4 for details.

Table 4 Comprehensive evaluation of reasonable well spacing

Evaluation Method Calculate well spacing (m) Analogy 550～800 Economic limit well spacing 611 Reasonable well spacing 703 EUR Calculation 672 Overview 688

Step S5, in the proposed infill area selected in step S3, according to the well spacing of 688m, it is preliminarily determined that 96 vertical wells are to be deployed for infilling. The specific well location distribution is shown in FIG5.

Step S6, in the numerical simulation model established in step S1, 96 vertical wells to be infilled are defined, their production for 30 years is simulated, and changes in single well EUR, formation pressure, etc. of the wells to be infilled are analyzed;

Step S7, the target block preferably selects vertical wells as the infill well type, and uses the cash flow algorithm to calculate the economic limit EUR of the vertical wells in the target block. With 10 years as the non-profit period, according to annual cash flow = (discount factor of the current year/(1+discount factor))×[original EUR×annual production decline rate×commodity rate×(sales price-production cost-resource tax-water conservancy construction fund×(1-income tax))-value-added tax payable×(urban construction tax+education surcharge)+single well surface investment-single well boosting investment)×income tax], the economic limit EUR of the vertical wells in the target block is inferred to be 1540×10 ⁴ m ³ . The specific calculation process is shown in FIG6 .

Table 5 Standards for calculating the EUR value of a single well economic limit using the cash flow method for directional wells

Step S8, based on Step S1 and Step S2, the average single well pressure drop of Class II producing wells is calculated to be 30%, and the EUR of the wells to be infilled in Step S6 is greater than or equal to 1540×10 ⁴ m ³ , and the pressure drop of the wells to be infilled is less than 30%.

Step S9, according to the screening results in step S8, 13 wells to be infilled whose production conditions do not meet the standards are eliminated, and finally 83 vertical wells are determined to be infilled. The specific well location distribution is shown in Figure 7.

Claims (7)

1. The method for adjusting the encrypted well pattern deployment by the hypotonic tight gas reservoir is characterized by comprising the following steps of:

S1, establishing a gas reservoir geological model according to logging interpretation reports, geological data and the like in the earlier stage of target gas reservoir development, establishing a target gas reservoir numerical model according to production dynamic data such as gas production, water production, oil casing pressure and the like of a current production well of a target block, fitting block reserves, oil casing pressure and yield, and on the basis, predicting single well accumulated gas production EUR and formation pressure in production for 30 years, and determining the distribution condition of residual reserves of the target gas reservoir;

s2, counting the EUR value of a single well of the existing production well according to the numerical simulation result, and dividing the production well into a class I high-yield well, a class II medium-yield well and a class III low-yield well according to normal and abnormal distribution;

S3, analyzing the residual reserve distribution condition of the target block, and optimizing encryption potential areas by combining the reserve abundance, the average effective thickness of the reservoir, the porosity and the permeability, wherein the optimization principle is as follows: based on the step S2, counting all physical parameters of a reservoir where the production well in class II is located, and taking the abundance of the production well in class II, the average effective thickness, the porosity and the permeability weighted by the thickness as the lower limit of the screening of the encryption potential area;

S4, determining the encryption well type and the reasonable well spacing according to physical properties and geological conditions of the reservoir of the potential zone to be encrypted, wherein the step S4 comprises the following sub-steps:

s41, according to reservoir physical properties and geological conditions of the encryption potential area, combining implementation effects of the produced horizontal well and the adjacent vertical well, comparing average daily gas production, EUR and single well investment of the produced well, and demonstrating the adaptability of the vertical well and the horizontal well of the well site to be laid;

S42, performing well spacing rationality evaluation on the target gas reservoir by using an analogy method, an economic limit well spacing, an economic reasonable well spacing and an unstable yield analysis method, wherein the comprehensive evaluation reasonable well spacing is in a well spacing range obtained by the analogy method and is larger than the economic limit well spacing;

wherein, the economic limit well pattern density refers to the well pattern density with the total output equal to the total input, namely the total profit is zero, and the calculation formula is as follows:

Wherein: f _min is the economic limit well pattern density, and the open well/km ²;E_R is the recovery ratio,%; commodity rate of alpha gas,%; n geological reserves, 10 ⁸m³;T_a gas tax yields, decimal; p is monovalent, meta/m ³; o gas operating costs, yuan/m ³; a gas-containing area, km ²; i, total investment of single well, ten thousand yuan; r loan interest rate, decimal; the evaluation period and year of T; d _min economic limit well spacing, m;

adding reasonable profit on the basis of the formula A to obtain an economic and reasonable well pattern density calculation formula, namely:

Wherein: f _α is economic and reasonable well pattern density, and well opening/km ²;L_R is reasonable profit, yuan/m ³;

S5, in the preferred encryption-planned area in the step S3, the well positions and the well numbers of the encryption wells are preliminarily determined according to the encryption well type and the well distance determined in the step S4;

s6, defining a pseudo-encryption well in the numerical simulation model established in the step S1, simulating the production of the pseudo-encryption well for 30 years, and analyzing the changes of single well EUR, formation pressure and the like of the pseudo-encryption well;

s7, calculating economic limit EUR of a target gas reservoir optimal well type;

S8, screening the EUR of the to-be-encrypted well in the step S6 to be more than or equal to the economic limit EUR, wherein the pressure drop degree of the to-be-encrypted well is smaller than the average single well pressure drop degree of the production well in the class II in the step S2;

and S9, determining the well screened in the step S8 as a final encryption well of the target gas reservoir.

2. The method for adjusting the encrypted well pattern deployment of the hypotonic tight gas reservoir according to claim 1, wherein the method comprises the following steps of: and step S2, counting each single well EUR predicted in the step S1 by adopting the bias distribution and the normal distribution, drawing an EUR probability distribution curve graph, and determining classification boundaries of the class I high-yield well, the class II medium-yield well and the class III low-yield well by using curve inflection points.

3. The method for adjusting the encrypted well pattern deployment of the hypotonic tight gas reservoir according to claim 2, which is characterized in that: in the EUR probability distribution curve graph, a first inflection point value close to an origin is a class III well upper limit and a class II well lower limit, and a second inflection point value is a class II well upper limit and a class I well lower limit.

4. The method for adjusting the encrypted well pattern deployment of the hypotonic tight gas reservoir according to claim 3, wherein the method comprises the following steps of: and selecting a typical representative well of the I-type high-yield well, the II-type medium-yield well and the III-type low-yield well, performing history fitting on the gas production and the oil casing pressure of the typical representative well by adopting a production instability analysis method, determining the control radius of the typical well, and taking twice the control radius as the well distance.

5. The method for adjusting the encrypted well pattern deployment of the hypotonic tight gas reservoir according to claim 4, which is characterized in that: the typical representative wells of the I-type high-yield well, the II-type middle-yield well and the III-type low-yield well are wells with similar average EUR of the I-type high-yield well, the II-type middle-yield well and the III-type low-yield well.

6. The method for adjusting the encrypted well pattern deployment of the hypotonic tight gas reservoir according to claim 5, which is characterized in that: the step S7 includes: the calculation of the economic limit EUR uses the cash flow method: the net cash flow is the difference of the total cash inflow amount minus the total cash outflow amount, and the economic limit accumulated gas yield corresponding to the period when the accumulated cash flow is changed from the negative number of the loss to 0 is the economic limit EUR by comprehensively considering single well drilling, ground investment, pressurized investment, gas price, production cost, stable production period, annual output decreasing rate, commodity rate, various tax rates, education fee addition, water conservancy construction foundation and internal income rate.

7. The method for adjusting the encrypted well pattern deployment of the hypotonic tight gas reservoir according to claim 6, wherein the method comprises the following steps of: the calculation formula D of the cash flow method is as follows: annual cash flow = (current annual discount coefficient/(1 + discount coefficient)) × [ original EUR × annual yield decline rate × commodity rate × (sales price-production cost-resource tax-water conservancy construction foundation × (1-income tax)) -value added tax × (urban construction tax + education fee additional) +single well floor investment-single well boost investment) × income tax ].