Shale gas well production system optimization method

Abstract

The invention discloses a shale gas well production system optimization method, which comprises the following steps of: aiming at a shale gas well in a net-shaped crack area, utilizing a complex crack net formed by natural cracks and artificial cracks, and taking the maximum output as a target; for the shale gas well in the one-way seam area, benefit development is completed on the premise that fracture closing is delayed, and shale gas well production system optimization methods of the net-shaped seam area and the one-way seam area are established respectively. According to the method, different reasonable pressure control intervals can be defined for shale gas wells under different geological conditions, and shale gas well development policy adjustment can be guided in time.

Description

Technical Field

[0001] This invention relates to the field of shale gas development research technology, and in particular to a method for optimizing the production system of shale gas wells. Background Technology

[0002] Shale reservoirs are ultra-dense rock formations with Nadarsian permeability levels. Shale gas development primarily relies on large-scale hydraulic fracturing to create complex volumetric fracture networks, with artificial fractures serving as the main seepage channels. During fracturing, a large amount of fracturing fluid is pumped into the formation, accompanied by proppant embedding, ultimately forming a complex fracture network system consisting of two sets of artificial fractures coupled with natural fractures: self-supporting artificial fractures opened by the fracturing fluid and supported by proppant. On the one hand, due to the poor stability of self-supporting artificial fractures, they will close to varying degrees during actual production with different pressure drop rates. On the other hand, large production pressure differentials cause proppant to easily break and deform, leading to the closure of supported artificial fractures. Both exhibit strong stress-sensitive effects, ultimately resulting in fracture closure, loss of conductivity, and blockage of gas production channels. This not only results in the loss of production within the closed fractures but also in the production within the artificial and natural fractures connected by the closed fractures.

[0003] To delay fracture closure as much as possible and maximize output within a limited timeframe, optimizing the production regime is the key focus. Too low a pressure drop rate limits output within a finite timeframe (based on multi-year EUR cutoff time), hindering profitable development; too high a pressure drop rate leads to premature fracture closure, reducing total output. Therefore, it is crucial to define reasonable pressure control ranges under different geological conditions to support on-site production regime optimization and adjustments. Summary of the Invention

[0004] In view of this, this invention provides a method for optimizing the production system of shale gas wells under different geological conditions, which clarifies the differentiated and reasonable pressure control range and provides timely guidance for the adjustment of shale gas well development policies.

[0005] This invention discloses a method for optimizing the production regime of shale gas wells, comprising:

[0006] For shale gas wells in reticular fracture zones, the goal is to maximize production by utilizing the complex fracture network formed by natural and artificial fractures. For shale gas wells in unidirectional fracture zones, the goal is to ensure profitable development while delaying fracture closure. Optimization methods for production systems of shale gas wells in reticular and unidirectional fracture zones are established respectively.

[0007] Furthermore, the method for optimizing the production regime of shale gas wells by establishing network fracture zones and unidirectional fracture zones respectively includes:

[0008] Step 1: Establish numerical models for shale gas wells with reticular fracture zones and unidirectional fracture zones respectively, and invert stress sensitivity curves through historical fitting;

[0009] Step 2: By establishing multiple sets of pressure control regimes and stress sensitivity curve combinations, conduct multi-year EUR predictions, and by comparing EUR differences, finally form a differentiated and reasonable pressure control regime design method to determine the balance point between the highest output and the slowest crack closure.

[0010] Further, step 1 includes:

[0011] Step 11: Select shale gas wells distributed in the network fracture zone or strip fracture zone, and establish a numerical model that considers multi-directional network natural fractures;

[0012] Step 12: Fit an iterative numerical model based on the actual production data of shale gas wells;

[0013] Step 13: Inversion of uncertain parameters.

[0014] Further, step 11 includes:

[0015] Based on the horizontal section length of the shale gas well, the section lost due to casing deformation, the actual fractured section length, the number of fractured sections, the bottom hole closure pressure, the reservoir pore pressure, the reservoir permeability, and the bottom hole closure pressure gradient, an equivalent mechanism model is built using EDFM numerical simulation software, thus obtaining the numerical model.

[0016] Further, step 12 includes:

[0017] By using actual production data from shale gas wells, the bottom hole flowing pressure and daily water production are fitted using a constant gas production method. Through multiple rounds of fitting iterations, when the final fitting error is less than the corresponding set error value, the numerical model can represent the actual production situation of the shale gas well. The actual production data includes casing pressure, oil pressure, daily gas production, cumulative gas production, daily fluid discharge, cumulative fluid discharge, and flowback rate.

[0018] Further, step 13 includes:

[0019] Uncertain parameters of the reservoir and fractures were obtained by inversion using EDFM artificial intelligence numerical simulation technology; stress sensitivity curves were also obtained for subsequent production regime optimization simulation; the uncertain parameters include artificial fracture geometry, water saturation, conductivity and compressibility.

[0020] Further, step 2 includes:

[0021] By historical fitting and inversion of uncertain parameters, a set of combined relationships between wellhead pressure drop paths and stress sensitivity curves in actual production processes is established. Based on this, the daily average pressure drop is increased or decreased proportionally, and the stress sensitivity is increased or decreased proportionally, ultimately forming multiple sets of combined relationships between pressure drop paths and stress sensitivity curves.

[0022] Furthermore, in step 2, similar pressure drop paths are re-characterized based on the actual pressure drop path, and different pressure drop paths and corresponding stress-sensitive curves are set respectively. EUR prediction is carried out by simulating multiple sets of different pressure drop paths.

[0023] Furthermore, in step 2, for shale gas wells in the network-fractured zone, by comparing the predicted EUR results over many years under different pressure control regimes, when the daily average pressure drop is within the first value range, production capacity can be increased based on the current EUR, which is the optimal pressure control range; when the daily average pressure drop is less than the preset value, the predicted EUR value is greater than the first specified value, reaching the internal rate of return, and profitable development can be achieved; when the daily average pressure drop is greater than the first preset value, the predicted EUR is less than the specified value, the internal rate of return is not reached, and profitable development cannot be supported.

[0024] Furthermore, in step 2, for shale gas wells in unidirectional fracture zones, by comparing the predicted EUR results over many years under different pressure control regimes, when the daily average pressure drop is within the second value range, the production capacity can be increased based on the current EUR, which is the optimal pressure control range; when the daily average pressure drop is less than the minimum value in the second value range or greater than the maximum value in the second value range, the predicted EUR is less than the specified value, the internal rate of return has not been reached, and it cannot support profitable development.

[0025] Due to the adoption of the above technical solution, the present invention has the following advantages: the method of the present invention can achieve the best production effect; the present invention clarifies the differentiated and reasonable pressure control range for shale gas wells with different geological conditions, and can guide the adjustment of shale gas well development policies in a timely manner. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in the embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0027] Figure 1(a) is a schematic diagram of the distribution of natural crack features in the mesh-like fissures according to an embodiment of the present invention;

[0028] Figure 1(b) is a schematic diagram of the distribution of natural crack features in the mesh-like fissures according to an embodiment of the present invention;

[0029] Figure 2This is a schematic diagram of the numerical model of an embodiment of the present invention;

[0030] Figure 3 This is a gas extraction curve diagram according to an embodiment of the present invention;

[0031] Figure 4(a) is a schematic diagram of the daily gas production curve of an embodiment of the present invention;

[0032] Figure 4(b) is a schematic diagram of daily water production fitting according to an embodiment of the present invention;

[0033] Figure 4(c) is a schematic diagram of bottom hole flow pressure fitting according to an embodiment of the present invention;

[0034] Figure 5 This is a schematic diagram of a parallel coordinate system for uncertain parameters according to an embodiment of the present invention;

[0035] Figure 6 This is a schematic diagram of the stress sensitivity curve obtained by inversion in an embodiment of the present invention;

[0036] Figure 7 This is a schematic diagram illustrating the relationship between the pressure drop path and the stress sensitivity curve in an embodiment of the present invention.

[0037] Figure 8 This is a schematic diagram illustrating the cumulative gas production changes under different pressure drop paths according to an embodiment of the present invention.

[0038] Figure 9 This is a statistical diagram of EUR for different pressure drop paths in an embodiment of the present invention;

[0039] Figure 10 This is a natural fracture distribution map and gas production curve diagram of well H75-1 according to an embodiment of the present invention.

[0040] Figure 11 A schematic diagram of a numerical model of a well considering multidirectional network of natural fractures in an embodiment of the present invention;

[0041] Figure 12 This is a schematic diagram of the gas production curve of well H75-1 in an embodiment of the present invention;

[0042] Figure 13(a) is a schematic diagram of the bottom flow pressure fitting of well H75-1 according to an embodiment of the present invention;

[0043] Figure 13(b) is a schematic diagram of the daily water production fitting of well H75-1 in an embodiment of the present invention;

[0044] Figure 13(c) is a schematic diagram of the optimal fitting of the bottom hole flowing pressure of well H75-1 according to an embodiment of the present invention;

[0045] Figure 13(d) is a schematic diagram of the optimal fitting of daily water production of well H75-1 in an embodiment of the present invention;

[0046] Figure 14This is a schematic diagram of the 20-year production design pressure drop path for Well H75-1 according to an embodiment of the present invention;

[0047] Figure 15 This is a schematic diagram of the stress closure curve of well H75-1 according to an embodiment of the present invention;

[0048] Figure 16 This is a statistical diagram of EUR under different pressure control regimes in well H75-1 according to an embodiment of the present invention;

[0049] Figure 17 This is a schematic diagram of the natural fracture distribution in well H3-8 according to an embodiment of the present invention;

[0050] Figure 18 A schematic diagram of the numerical model of well H3-8 considering multidirectional network natural fractures in an embodiment of the present invention;

[0051] Figure 19 This is a gas production curve diagram of well H3-8 according to an embodiment of the present invention;

[0052] Figure 20(a) is a schematic diagram of the bottom flow pressure fitting of well H3-8 according to an embodiment of the present invention;

[0053] Figure 20(b) is a schematic diagram of the daily water production fitting of well H3-8 in an embodiment of the present invention;

[0054] Figure 20(c) is a schematic diagram of the optimal fitting of the bottom flow pressure of well H3-8 in an embodiment of the present invention;

[0055] Figure 20(d) is a schematic diagram of the optimal fitting of daily water production of well H3-8 in an embodiment of the present invention;

[0056] Figure 21 This is a schematic diagram of the 20-year production design pressure drop path for well H3-8 according to an embodiment of the present invention;

[0057] Figure 22 This is a schematic diagram of the stress closure curve of well H3-8 in an embodiment of the present invention;

[0058] Figure 23 This is a statistical diagram of EUR under different pressure control regimes in well H3-8 according to an embodiment of the present invention. Detailed Implementation

[0059] The present invention will be further described in conjunction with the accompanying drawings and embodiments. The described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art should fall within the protection scope of the present invention.

[0060] Referring to Figure 1, this invention provides an embodiment of a method for optimizing the production regime of shale gas wells, which includes:

[0061] 1. Typical planar distribution characteristics of natural cracks:

[0062] Since the Indosinian period, influenced by three phases of tectonic movement, the shale gas in southern Sichuan has exhibited a broom-like structural characteristic, with multi-scale and multi-phase fracture development. Due to the complex structure, synclinal areas have a network of fractures, while slopes and anticlines have a unidirectional fracture network. Natural fractures with a multidirectional network distribution are beneficial for working in conjunction with artificial fractures formed during shale reservoir fracturing to form a complex fracture network, improving the stimulation effect, increasing the stimulation volume, and helping to increase single-well production. Natural fractures with a unidirectional strip distribution serve as channels between platform wells, which can easily lead to the filtration of fracturing fluid along the natural fractures during fracturing, causing inter-well interference, casing deformation, and other complex construction situations, seriously affecting the construction rhythm and gas well production. In addition, the positional relationship between large-scale unidirectional fractures and the wellbore is either parallel or oblique, which limits the expansion range of artificial fractures, resulting in a lower complexity of the stimulation fractures. Ultimately, unidirectional fractures will affect gas well productivity, as shown in Figures 1(a) and 1(b).

[0063] To maximize production from gas wells in crisscross and unidirectional fracture zones, differentiated production regimes need to be developed based on the different distribution characteristics of natural fractures. For crisscross fracture zone wells, the design goal is to maximize production by rationally utilizing the complex fracture network formed by natural and artificial fractures. For unidirectional fracture zone wells, the goal is to ensure profitable development while delaying fracture closure. Therefore, optimization methods for production regimes in crisscross and unidirectional fracture zone wells are established separately.

[0064] 2. Numerical simulation method based on typical shale gas wells:

[0065] (1) Model establishment:

[0066] Taking a key shale gas well in southern Sichuan as an example, the horizontal section is 1560m long, with 510m lost due to casing deformation, resulting in an actual fractured section length of 1021.84m and 14 fractured sections. DFIT interpretation results show a bottomhole closure pressure of 90.01MPa, reservoir pore pressure of 80.03MPa, reservoir permeability of 0.30765mD, and a bottomhole closure pressure gradient of 0.0232MPa / m. An equivalent mechanism model was quickly built using EDFM numerical simulation software, such as... Figure 2 As shown.

[0067] (2) Capacity simulation:

[0068] The well was put into production on January 22, 2019, and has accumulated 1433 days of production to date, with a casing pressure of 17.53 MPa, an oil pressure of 2.59 MPa, a daily gas production of 14,000 cubic meters, and a cumulative gas production of 108 million cubic meters. The average daily production in the first year was 160,000 cubic meters. The gas production curve is shown below. Figure 3 As shown.

[0069] Using actual production data from this well, the bottom hole flowing pressure and daily water production were fitted using a constant gas production method. Through multiple rounds of iterative fitting, the final fitting errors were less than 5% and 30%, respectively, indicating good fitting performance. The model can represent the actual production situation. Figures 4(a) to 4(c) As shown.

[0070] (3) Key parameter inversion:

[0071] See Figure 5 and Figure 6 After fitting, the uncertain parameters of the reservoir and fractures, such as the geometry of artificial fractures, water saturation, conductivity, and compressibility, can be obtained by inverting the EDFM artificial numerical simulation technology. At the same time, stress sensitivity curves can be obtained for subsequent production system optimization simulation.

[0072] 3. Consideration of stress-sensitive production system optimization methods:

[0073] By historical fitting and key parameter inversion, a set of combined relationships between wellhead pressure drop paths (hereinafter referred to as pressure drop paths) and stress sensitivity curves in actual production processes can be established. Based on this, the daily average pressure drop is increased or decreased proportionally, and the stress sensitivity is increased or decreased proportionally, ultimately forming multiple sets of combined relationships between pressure drop paths and stress sensitivity curves.

[0074] Taking this well as an example, to facilitate proportional scaling of the daily average pressure drop, a similar pressure drop path was re-characterized based on the actual pressure drop path (daily average pressure drop of 0.9 MPa / day). Pressure drop paths and corresponding stress-sensitive curves were set for 0.2 MPa / day, 0.4 MPa / day, 0.5 MPa / day, 0.7 MPa / day, 1.6 MPa / day, 1.8 MPa / day, 2 MPa / day, and 2.2 MPa / day, respectively. For subsequent comparison of ultimate pressure control conditions, a control group of 0.07 MPa / day was added. Figure 7 As shown.

[0075] See Figure 8 and Figure 9 EUR prediction was conducted by simulating nine different pressure drop paths (actual historical pressure drop + four pressure control paths + four pressure release paths), and the results showed significant differences. Among them, pressure drop path 1 (average daily pressure drop of 2.2 MPa / day) predicted an EUR of only 0.19 billion cubic meters. Due to the rapid pressure drop, the fractures closed quickly in the early stage, resulting in a small total volume of gas-producing fractures and a low total output. Pressure drop path 9 (average daily pressure drop of 0.07 MPa / day) predicted an EUR of only 0.67 billion cubic meters. Although it delayed fracture closure and preserved the gas production channel as much as possible, the gas production rate was slow. It could not fully utilize the gas well's production capacity within a limited time (usually 20 years as the EUR prediction cutoff time), and required a longer production time to achieve higher output, thus failing to achieve profitable development.

[0076] Therefore, a balance needs to be found between maximizing production and fracture closure. Taking pressure drop path 8 as an example, due to the pressure control system, the average daily pressure drop is 0.2 MPa / day. In the early stage of production, the cumulative gas production is lower than other paths with larger pressure drops. As production progresses, the reasonable degree of fracture closure and gas production rate enable the cumulative gas production to gradually surpass other paths, and the final predicted EUR is 187 million cubic meters, which is 6% higher than the actual predicted EUR of this well.

[0077] The results comparison shows that pressure drop paths 5 to 8 can increase the EUR by 0.06 to 0.18 billion cubic meters compared with the current actual predicted EUR of this well. The recommended reasonable pressure control range for this well is an average daily pressure drop of 0.2 to 0.7 MPa / day.

[0078] For ease of understanding, the present invention provides a more specific embodiment:

[0079] 1. Optimization method for reasonable pressure control range of typical shale gas wells in reticular fracture zones:

[0080] (1) Model establishment:

[0081] See Figure 10 and Figure 11 Well H75-1 is located in a network of fractured areas, with a horizontal section length of 2100m, a fractured section length of 2055m, 31 fractured sections, and a total of 199 clusters. The model size is 2200x400x20 meters, simulating geological reserves of 242 million cubic meters, which is consistent with the design plan of 286 million cubic meters, with a consistency of 85%.

[0082] (2) Capacity simulation:

[0083] Well H75-1 has been producing for 753 days. Currently, the casing pressure is 4.12 MPa, the oil pressure is 4.3 MPa, the daily gas production is 25,000 cubic meters, and the cumulative gas production is 55.82 million cubic meters. The daily fluid discharge is 14 cubic meters, and the cumulative fluid discharge is 26,582 cubic meters, with a flowback rate of 47.14%. Figure 12 As shown.

[0084] Using actual production data from this well, the bottom hole flowing pressure and daily water production were fitted using a constant gas production method. Through multiple rounds of iterative fitting, the final fitting errors were less than 5% and 30%, respectively, indicating good fitting performance. The model can represent the actual production situation. Figures 13(a) to 13(d) As shown.

[0085] (3) Reasonable pressure control system design

[0086] Based on the stress closure curves and pressure control path combinations obtained from the inversion, 36 sets of stress closure curve and pressure control path combinations were established, with pressure drops controlled between 0.01 MPa / day and 5 MPa / day. Figure 14 and Figure 15 As shown.

[0087] By comparing the projected EUR under different pressure control systems over 20 years, the optimal pressure control range is when the average daily pressure drop is between 0.03 and 0.3 MPa / d, which allows for a 1% to 4% increase in EUR from the current level. When the average daily pressure drop is <1 MPa / d, the projected EUR is >125 million cubic meters, achieving an internal rate of return (IRR) of 6% and realizing profitable development. When the average daily pressure drop is >1 MPa / d, the projected EUR is <125 million cubic meters, failing to achieve an IRR of 6% and making it difficult to support profitable development. Figure 16 As shown.

[0088] 2. Optimization method for reasonable pressure control range of typical shale gas wells in unidirectional fracture zones:

[0089] (1) Model establishment:

[0090] See Figure 17 and Figure 18 Well H3-8 is located in a strip-shaped fracture zone, with a horizontal section length of 1950m, a fractured section length of 1790m, 29 fractured sections, and a total of 197 clusters. The established model has dimensions of 2100x400x20 meters and simulates geological reserves of 249 million cubic meters, which is 94% consistent with the design plan of 266 million cubic meters.

[0091] (2) Capacity simulation:

[0092] Well H3-8 has been producing for 775 days. Currently, the casing pressure is 2.75 MPa, the oil pressure is 1.59 MPa, the daily gas production is 29,000 cubic meters, and the cumulative gas production is 44.05 million cubic meters. The daily fluid discharge is 13 cubic meters, and the cumulative fluid discharge is 33,495 cubic meters, with a flowback rate of 80.66%. Figure 19 As shown.

[0093] Using the actual production data of the well, the bottom hole flowing pressure and daily water production were fitted using a constant gas production method. Through multiple rounds of fitting iterations, the final fitting errors were less than 10% and 30%, respectively, indicating a good fitting effect. The model can represent the actual production situation, as shown in Figures 20(a) to 20(d).

[0094] (3) Reasonable pressure control system design:

[0095] Based on the stress closure curves and pressure control path combinations obtained from the inversion, 36 sets of stress closure curve and pressure control path combinations were established, with pressure drops controlled between 0.01 MPa / day and 5 MPa / day. Figure 21 and Figure 22 As shown.

[0096] By comparing the projected EUR under different pressure control systems over 20 years, the optimal pressure control range is when the average daily pressure drop is between 0.03 and 0.4 MPa / d, which can increase the current EUR by 4% to 8%. When the average daily pressure drop is <0.03 MPa / d or >0.4 MPa / d, the projected EUR is <125 million cubic meters, failing to reach an internal rate of return of 6%, making it difficult to support profitable development. Figure 23 As shown.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing the production regime of shale gas wells, characterized in that, include: For shale gas wells in the network fracture zone, the goal is to maximize production by utilizing the complex network of fractures formed by natural and artificial fractures. For shale gas wells in unidirectional fracture zones, to ensure profitable development while delaying fracture closure, optimization methods for production systems of shale gas wells in both network fracture zones and unidirectional fracture zones are established.

2. The method for optimizing shale gas well production regime according to claim 1, characterized in that, The method for optimizing the production regime of shale gas wells by establishing reticular fracture zones and unidirectional fracture zones respectively includes: Step 1: Establish numerical models for shale gas wells with reticular fracture zones and unidirectional fracture zones respectively, and invert stress sensitivity curves through historical fitting; Step 2: By establishing multiple sets of pressure control regimes and stress sensitivity curve combinations, conduct multi-year EUR predictions, and by comparing EUR differences, finally form a differentiated and reasonable pressure control regime design method to determine the balance point between the highest output and the slowest crack closure.

3. The method for optimizing shale gas well production regime according to claim 2, characterized in that, Step 1 includes: Step 11: Select shale gas wells distributed in the network fracture zone or strip fracture zone, and establish a numerical model that considers multi-directional network natural fractures; Step 12: Fit an iterative numerical model based on the actual production data of shale gas wells; Step 13: Inversion of uncertain parameters.

4. The method for optimizing shale gas well production regime according to claim 3, characterized in that, Step 11 includes: Based on the horizontal section length of the shale gas well, the section lost due to casing deformation, the actual fractured section length, the number of fractured sections, the bottom hole closure pressure, the reservoir pore pressure, the reservoir permeability, and the bottom hole closure pressure gradient, an equivalent mechanism model is built using EDFM numerical simulation software, thus obtaining the numerical model.

5. The method for optimizing shale gas well production regime according to claim 3, characterized in that, Step 12 includes: By using actual production data from shale gas wells, the bottom hole flowing pressure and daily water production are fitted using a constant gas production method. Through multiple rounds of fitting iterations, when the final fitting error is less than the corresponding set error value, the numerical model can represent the actual production situation of the shale gas well. The actual production data includes casing pressure, oil pressure, daily gas production, cumulative gas production, daily fluid discharge, cumulative fluid discharge, and flowback rate.

6. The method for optimizing shale gas well production regime according to claim 3, characterized in that, Step 13 includes: Uncertain parameters of the reservoir and fractures were obtained by inversion using EDFM artificial intelligence numerical simulation technology; stress sensitivity curves were also obtained for subsequent production regime optimization simulation; the uncertain parameters include artificial fracture geometry, water saturation, conductivity and compressibility.

7. The method for optimizing shale gas well production regime according to claim 3, characterized in that, Step 2 includes: By historical fitting and inversion of uncertain parameters, a set of combined relationships between wellhead pressure drop paths and stress sensitivity curves in actual production processes is established. Based on this, the daily average pressure drop is increased or decreased proportionally, and the stress sensitivity is increased or decreased proportionally, ultimately forming multiple sets of combined relationships between pressure drop paths and stress sensitivity curves.

8. The method for optimizing shale gas well production regime according to claim 7, characterized in that, In step 2, similar pressure drop paths are re-characterized based on the actual pressure drop path, and different pressure drop paths and corresponding stress-sensitive curves are set respectively. EUR prediction is carried out by simulating multiple sets of different pressure drop paths.

9. The method for optimizing shale gas well production regime according to claim 7, characterized in that, In step 2, for shale gas wells in the network fracture zone, by comparing the predicted EUR results over many years under different pressure control regimes, when the daily average pressure drop is within the first value range, the production capacity can be increased based on the current EUR, which is the optimal pressure control range; when the daily average pressure drop is less than the preset value, the predicted EUR value is greater than the first specified value, reaching the internal rate of return, and profitable development can be achieved; when the daily average pressure drop is greater than the first preset value, the predicted EUR is less than the specified value, the internal rate of return has not been reached, and profitable development cannot be supported.

10. The method for optimizing shale gas well production regime according to claim 7, characterized in that, In step 2, for shale gas wells in unidirectional fracture zones, by comparing the predicted EUR results over many years under different pressure control regimes, when the daily average pressure drop is within the second value range, the production capacity can be increased based on the current EUR, which is the optimal pressure control range; when the daily average pressure drop is less than the minimum value in the second value range or greater than the maximum value in the second value range, the predicted EUR is less than the specified value, the internal rate of return has not been reached, and it cannot support profitable development.

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