Deep shale gas horizontal well full well section geology-engineering-seam network construction potential dessert identification method

Abstract

The invention discloses a deep shale gas horizontal well full-well section geology-engineering-fracture network construction potential dessert identification method. The method comprises the steps that reservoir physical property quality parameters, rock mechanical parameters, rock ground stress parameters and fracture network construction potential parameters of a target well are determined according to full-well section original logging and interpretation data of a horizontal well section of the target well; calculating a reservoir physical property quality index, a rock stress brittleness index and a fracture network construction potential index of the whole well section of the horizontal well section of the target well; determining a reservoir physical property quality index threshold value, a rock stress brittleness index threshold value and a fracture network construction potential index threshold value; and according to comparison of the reservoir physical property quality index, the rock stress brittleness index and the fracture network construction potential index with corresponding threshold values, sweet spot identification grades are divided for the target well, and a targeted fracturing process is recommended according to field construction experience. According to the method, the prediction accuracy of the geological engineering dessert of the deep shale reservoir with strong heterogeneity is improved, and a favorable theoretical basis is provided for differential staged fracturing design of deep shale gas.

Description

Technical Field

[0001] The invention relates to a method for identifying potential sweet spots in the whole-well section geology-engineering-fracture network construction of a deep shale gas horizontal well, and belongs to the technical field of unconventional oil and gas production increase and transformation. Background Art

[0002] With the continuous consumption of conventional oil and gas reserves, unconventional oil and gas such as deep shale gas have entered the commercial development stage. Fracture network fracturing is currently an effective means of deep shale gas extraction. Shale reservoirs are highly heterogeneous, with good physical properties in some areas and abundant recoverable resources, poor physical properties in some areas and low recoverable value, and uneven distribution of geological sweet spots along horizontal well sections; from an engineering perspective, factors such as formation structure type, geostress distribution characteristics, rock mechanical properties, natural fractures and bedding development determine the extension pattern of hydraulic fractures and ultimately affect the fracturing effect. Effectively predicting the distribution of geological-engineering sweet spots in shale reservoirs and designing differentiated fracturing for horizontal wells based on this are of great significance to improving the ultimate recovery rate of shale gas and improving economic benefits.

[0003] At present, scholars at home and abroad have carried out the following research on the identification of sweet spots in shale gas horizontal well fracture network fracturing. Soumen Deshmukh (2020) estimated the rock mechanical parameters of shale gas reservoirs through pre-stack synchronous angle correlation seismic inversion technology, and used probabilistic neural network technology based on seismic data to predict TOC, porosity, saturation and other data from logging data. TOC, porosity, saturation and rock brittleness were analyzed to determine the sweet spots in the study area; Wu Shiqing (2020) studied the occurrence state of shale gas through various adsorption experiments, analyzed the relationship between the methane occurrence characteristics and TOC of the Niutitang Formation shale reservoir, studied the influence of increased organic matter content on rock mechanical parameters, and identified sweet spots from the perspective of gas content; Li Guorong (2022) compared the correlation between the gas content of shale gas reservoirs and sweet spot evaluation parameters, selected lithofacies, mudstone thickness, organic matter maturity and clay mineral content and other factors to identify shale gas reservoir sweet spots, and studied the regional distribution characteristics of sweet spots.

[0004] Traditional sweet spot identification methods only unilaterally consider the impact of rock strength factors such as rock brittleness and fracture toughness on fracturing effects, or analyze the correlation between reservoir physical properties such as TOC and porosity and the gas content of shale gas reservoirs. There is a lack of comprehensive sweet spot identification methods that consider the oil and gas distribution and difficulty of transformation in deep shale reservoirs, including the impact of geostress on fracture network construction, and a comprehensive evaluation method that considers the impact of natural microcracks and shale bedding on the potential of fracture network construction. It is urgent to establish a deep shale gas horizontal well geological-engineering-fracture network construction potential sweet spot identification method for the entire well section to provide a theoretical basis for horizontal well fracturing design. Summary of the invention

[0005] In order to overcome the defects existing in the prior art, the present invention aims to provide a method for identifying potential sweet spots in the geological-engineering-fracture network construction of the entire well section of a deep shale gas horizontal well. This method improves the accuracy of predicting geological-engineering sweet spots in deep shale reservoirs with strong heterogeneity, and provides a favorable theoretical basis for the differentiated staged fracturing design of deep shale gas.

[0006] The technical solution provided by the present invention to solve the above technical problems is: a method for identifying potential sweet spots in the geological-engineering-fracture network construction of a deep shale gas horizontal well, comprising the following steps:

[0007] Step 1: Determine the reservoir physical quality parameters, rock mechanics parameters, rock geostress parameters, and fracture network construction potential parameters of the target well based on the original logging and interpretation data of the entire horizontal well section of the target well;

[0008] Step 2: Calculate the reservoir physical quality index, rock stress brittleness index, and fracture network construction potential index of the entire horizontal well section of the target well according to the reservoir physical quality parameters, rock mechanical parameters, rock geostress parameters, and fracture network construction potential parameters of the entire horizontal well section of the target well;

[0009] Step 3: Determine the reservoir physical property quality index threshold, rock stress brittleness index threshold, and fracture network construction potential index threshold according to the reservoir physical property quality index, rock stress brittleness index, and fracture network construction potential index of the entire horizontal well section of the target well;

[0010] Step 4: According to the comparison between reservoir physical quality index, rock stress brittleness index, fracture network construction potential index and their corresponding thresholds, the target well is classified into sweet spot identification levels, and targeted fracturing technology is recommended based on field construction experience.

[0011] A further technical solution is that the reservoir physical quality parameters include TOC, porosity, and gas saturation.

[0012] A further technical solution is that the rock mechanics parameters include Young's modulus and Poisson's ratio.

[0013] A further technical solution is that the rock in-situ stress parameters include maximum horizontal principal stress, minimum horizontal principal stress, vertical stress, and horizontal in-situ stress difference.

[0014] A further technical solution is that the fracture network construction potential parameters include the degree of development of natural fractures and the degree of development of horizontal bedding.

[0015] A further technical solution is that the calculation formula of the reservoir physical quality index is:

[0016]

[0017] Where: B Gis the reservoir physical quality index; V f ' is the intermediate parameter of free gas reserves; a1 and b1 represent the weight coefficients of adsorbed gas and free gas reserves respectively; TOC is the TOC content along the well section; TOC' is the normalized TOC content; TOC max is the maximum TOC content of the entire well section; TOC min is the minimum TOC content of the entire well section; S g is the gas saturation along the well section; S g ' is the normalized gas saturation; S gmax is the maximum gas saturation of the entire well section; S gmin is the minimum gas saturation of the entire well section; φ is the porosity along the well section; φ′ is the normalized porosity; φ max is the maximum porosity of the entire well section; φ min It is the minimum porosity of the entire well section.

[0018] A further technical solution is that the calculation formula of the rock stress brittleness index is:

[0019]

[0020]

[0021] Where: B E is the rock stress brittleness index; B N is the rock brittleness coefficient; B n is the intermediate parameter of rock brittleness; S Δ is the normalized geostress difference coefficient; S d is the geostress difference coefficient; e B and e are the weights of the rock brittleness coefficient and the ground stress difference coefficient that constitute the rock stress brittleness index; B N is the normalized intermediate parameter of rock brittleness; B nmax is the maximum intermediate parameter of rock brittleness in the entire well section; B nmin is the minimum intermediate parameter of rock brittleness in the whole well section; υ is Poisson's ratio; υ n is the normalized Poisson's ratio; max is the maximum Poisson's ratio of the entire well section; min is the minimum Poisson's ratio of the entire well section; E is Young's modulus; E n is the normalized Young's modulus; E max is the maximum Young's modulus of the entire well section; E min is the minimum Young's modulus of the entire well section; S dmax is the maximum geostress difference coefficient of the whole well section; S dmin is the minimum geostress difference coefficient of the whole well section; S x is the minimum horizontal principal stress; S y is the maximum horizontal principal stress.

[0022] A further technical solution is that the calculation formula of the seam network construction potential index is:

[0023]

[0024] Where: B NF I is the potential index for seam network construction; N is the normalized crack development intensity; S N is the normalized bedding intensity; I n is the crack development strength; S n is the bedding intensity; I nmax is the maximum Young's modulus fracture development intensity in the entire well section; I nmin is the minimum fracture development intensity of the entire well section; S nmax is the maximum bedding development intensity of the entire well section; S nmin It is the minimum bedding development intensity of the whole well section.

[0025] A further technical solution is that the calculation formula in step three is:

[0026]

[0027] Where: is the reservoir physical quality index threshold; is the rock stress brittleness index threshold; is the fracture network construction potential index threshold; G is the reservoir physical quality index judgment coefficient, Ψ G =0.38; E is the rock stress brittleness index determination coefficient, Ψ E =0.35; NF is the fracture network construction potential index judgment coefficient, Ψ NF =0.4; is the maximum reservoir physical quality index of the entire well section; is the minimum reservoir physical quality index of the entire well section; is the maximum rock stress brittleness index of the entire well section; is the minimum rock stress brittleness index of the entire well section; It is the maximum fracture network construction potential index of the whole well section; It is the potential index of minimum fracture network construction in the whole well section.

[0028] A further technical solution is that the specific process of classifying the target well into sweet spot recognition levels in step 4 is as follows:

[0029] when When; the dessert recognition level is 1;

[0030] when When; the dessert recognition level is 2;

[0031] when When; the dessert recognition level is 3;

[0032] when When; dessert recognition level is 4;

[0033] when When; dessert recognition level is 5;

[0034] when When; dessert recognition level is 6;

[0035] when When; dessert recognition level is 7;

[0036] when ; The dessert recognition level is 8.

[0037] The present invention has the following beneficial effects: based on the geological and engineering characteristics of deep shale, the present invention statistically analyzes the on-site logging curve data, and for the first time proposes a sweet spot identification method that takes into account the "geology-engineering-fracture network construction potential" index, which provides technical support for on-site differentiated fracturing construction design, can solve the problem of identifying and judging the sweet spots in the horizontal section of the on-site target well, and is easy for engineering application. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the calculation process of the present invention;

[0039] Figure 2 It is a schematic diagram of the composition of the fine characterization model of reservoir physical quality;

[0040] Figure 3 The schematic diagram of the fine characterization model of rock stress brittleness;

[0041] Figure 4 Schematic diagram of the model composition for the fine characterization of fracture network construction potential;

[0042] Figure 5 It is a curve diagram of key characterization parameters of the horizontal section of the target well;

[0043] Figure 6 The calculation diagram of the sweet spot identification method for the horizontal section of the target well;

[0044] Figure 7 A schematic diagram of the recommended segmentation of the horizontal section of the target well according to the sweet spot level;

[0045] Figure 8 It is a comparison chart of sweet spot grade, fluid intensity and production in each horizontal section of the target well. DETAILED DESCRIPTION

[0046] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. 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.

[0047] like Figure 1 As shown, a method for identifying potential sweet spots in the geological-engineering-fracture network construction of a deep shale gas horizontal well of the present invention comprises the following steps:

[0048] Step 1: Based on the original logging and interpretation data of the entire horizontal well section of the target well, calculate the reservoir physical quality parameters such as TOC, porosity, gas saturation, rock mechanics and geostress parameters such as Young's modulus, Poisson's ratio, and triaxial geostress, and fracture network construction potential parameters such as natural fracture development intensity and horizontal bedding development intensity;

[0049] According to the logging interpretation data, the ΔLogR method is used to regress TOC:

[0050] TOC=a TOC ×ΔLogR+b TOC

[0051] ΔLogR=lg(R / R min )+K×(v p -v pmax ) (1)

[0052] K = lg(R max / R min ) / (v pmax -v pmin )

[0053] Where: TOC is the calculated TOC content along the well section; a TOC , b TOC is the TOC regression coefficient of the ΔLogR method, a TOC =2.5779, b TOC =3.9725, a TOC , b TOC Only applicable to shale reservoirs with density less than 2.7; v p is the P-wave velocity; R is the GR logging; K is the intermediate parameter.

[0054] The porosity distribution along the well is calculated using the environmental correction model:

[0055] φ=φ CNL ·a φ +φ ρ ·(1-a φ ) (2)

[0056] in:

[0057] φ ρ =(ρ shale -ρ DEN ) / (ρ shale -ρ f ) (3)

[0058] Where: φ is the porosity; φ CNL is neutron porosity (well logging); a φ is the porosity calculation proportional factor, which is 0.137; φ ρ is the density porosity; ρ shale is the shale matrix density; ρ f is the fluid volume density (water); ρ DEN is the bulk density (well logging).

[0059] According to the well logging interpretation data, the water saturation is calculated:

[0060] S g =1-S w (4)

[0061] Where: S g is the gas saturation along the well section; S w is the water saturation.

[0062] Maximum horizontal principal stress:

[0063]

[0064] Minimum horizontal principal stress:

[0065]

[0066] Vertical stress:

[0067]

[0068] Intermediate parameters:

[0069]

[0070] Horizontal stress difference:

[0071] S xy =S y -S x (9)

[0072] Young's modulus:

[0073]

[0074] Poisson's ratio:

[0075]

[0076] Where: v s is the shear wave velocity; E is Young's modulus; υ is Poisson's ratio; S X is the minimum horizontal principal stress; S Y is the maximum horizontal principal stress; S V is the vertical stress; S XY is the horizontal stress difference; k is the intermediate parameter.

[0077] Natural fracture development intensity

[0078] In deep shale reservoirs, the intensity of natural fracture development is related to the content of calcium minerals (such as carbonate minerals, silica minerals such as quartz, etc.) and clay minerals (such as illite, etc.) in the reservoir. It is proposed that the intensity of natural fracture development in deep shale can be described by the corresponding regression coupling relationship of silica minerals, calcium minerals and clay minerals:

[0079] I n =0.4×f Si +1.6×f Ca -1.4f Sh +164.0 (12)

[0080] Horizontal bedding development intensity

[0081] The change of provenance structure during the sedimentation process is the reason for the development of shale bedding. The contents of calcium minerals, silica minerals and clay minerals obtained in the experiment were selected as the main parameters for regression, and it was proposed that the intensity of horizontal bedding development in deep shale can be described by the corresponding regression coupling relationship of silica minerals, calcium minerals and clay minerals:

[0082]

[0083] Where: I n - Crack development strength, bar·m -1 ; S n -Bedding intensity, bar·m -1 ;f Si -Silica mineral content; f Ca - calcium mineral content; f Sh -Clay mineral content.

[0084] Step 2: Calculate the reservoir physical quality index, rock stress brittleness index, and fracture network construction potential index of the entire horizontal well section of the target well according to the reservoir physical quality parameters, rock mechanical parameters, rock geostress parameters, and fracture network construction potential parameters of the entire horizontal well section of the target well;

[0085] The TOC, porosity and gas saturation in the logging data are used to characterize the heterogeneous gas distribution in the reservoir, and the calculation formula of the reservoir physical quality index is established:

[0086]

[0087] in:

[0088]

[0089] Where: B G V is the reservoir physical quality index; f ' is the intermediate parameter of free gas reserves; a1 and b1 represent the weight coefficients of adsorbed gas and free gas reserves, respectively, which are derived from the regional geological characteristics; TOC is the TOC content along the well section; TOC' is the normalized TOC content; TOC max is the maximum TOC content of the entire well section; TOC min is the minimum TOC content of the entire well section; S g is the gas saturation along the well section; S g ' is the normalized gas saturation; S gmax is the maximum gas saturation of the entire well section; S gmin is the minimum gas saturation of the entire well section; φ is the porosity along the well section; φ′ is the normalized porosity; φ max is the maximum porosity of the entire well section; φ min is the minimum porosity of the entire well section;

[0090] The rock matrix brittleness is proportional to Young's modulus and inversely proportional to Poisson's ratio. The rock brittleness coefficient is established:

[0091]

[0092] in:

[0093]

[0094] The horizontal ground stress difference is one of the factors that affect the complexity of the fracture network during the fracturing process. The calculation formula of the ground stress difference coefficient is established:

[0095]

[0096] in:

[0097]

[0098] Considering the non-uniform stress distribution along the horizontal well section and the difference in rock brittle characteristics, the rock brittleness characterization coefficient and the ground stress difference coefficient are integrated to establish the calculation formula of the rock stress brittleness index:

[0099]

[0100] Where: B E is the rock stress brittleness index; B N is the rock brittleness coefficient; B n is the intermediate parameter of rock brittleness; S Δ is the normalized geostress difference coefficient; S d is the geostress difference coefficient; e B and e are the weights of the rock brittleness coefficient and the ground stress difference coefficient that constitute the rock stress brittleness index, respectively, obtained by regression of microseismic data; B N is the normalized intermediate parameter of rock brittleness; B nmax is the maximum intermediate parameter of rock brittleness in the entire well section; B nmin is the minimum intermediate parameter of rock brittleness in the whole well section; υ is Poisson's ratio; υ n is the normalized Poisson's ratio; max is the maximum Poisson's ratio of the entire well section; min is the minimum Poisson's ratio of the entire well section; E is Young's modulus; E n is the normalized Young's modulus; E max is the maximum Young's modulus of the entire well section; E min is the minimum Young's modulus of the entire well section; S dmax is the maximum geostress difference coefficient of the whole well section; S dmin is the minimum geostress difference coefficient of the whole well section; S x is the minimum horizontal principal stress; S y is the maximum horizontal principal stress;

[0101] Horizontal bedding and natural micro-fractures are conducive to the comprehensive extension of hydraulic fractures to form a fracture network. In order to calculate the difficulty of establishing a fracture network along the horizontal well section, the development intensity of horizontal bedding and natural fractures is integrated to establish the fracture network construction potential index calculation formula:

[0102]

[0103] in:

[0104]

[0105] Where: B NF I is the potential index for seam network construction; N is the normalized crack development intensity; S N is the normalized bedding intensity; I n is the crack development strength; S n is the bedding intensity; I nmax is the maximum Young's modulus fracture development intensity in the entire well section; I nmin is the minimum fracture development intensity of the entire well section; S nmax is the maximum bedding development intensity of the entire well section; S nminis the minimum bedding development intensity of the entire well section;

[0106] Step 3: Determine the reservoir physical property quality index threshold, rock stress brittleness index threshold, and fracture network construction potential index threshold according to the reservoir physical property quality index, rock stress brittleness index, and fracture network construction potential index of the entire horizontal well section of the target well;

[0107] Establish reservoir physical quality index, rock stress brittleness index, and fracture network construction potential index thresholds:

[0108]

[0109] Where: is the reservoir physical quality index threshold; is the rock stress brittleness index threshold; is the fracture network construction potential index threshold; G is the reservoir physical quality index judgment coefficient, Ψ G =0.38; E is the rock stress brittleness index determination coefficient, Ψ E =0.35; NF is the fracture network construction potential index judgment coefficient, Ψ NF =0.4; is the maximum reservoir physical quality index of the entire well section; is the minimum reservoir physical quality index of the entire well section; is the maximum rock stress brittleness index of the entire well section; is the minimum rock stress brittleness index of the entire well section; It is the maximum fracture network construction potential index of the whole well section; It is the potential index of minimum fracture network construction in the whole well section;

[0110] Step 4: According to the comparison between reservoir physical quality index, rock stress brittleness index, fracture network construction potential index and their corresponding thresholds, the target well is classified into sweet spot identification levels, and targeted fracturing technology is recommended based on field construction experience;

[0111] According to the comparison of reservoir physical quality index, rock stress brittleness index, fracture network construction potential index and their corresponding thresholds, the target horizontal wells are divided into sweet spot identification levels, and targeted fracturing processes are recommended based on field construction experience.

[0112] Table 1. Sweet spot identification criteria and fracturing technology recommendations for deep shale “geology-engineering-fracture network construction potential”

[0113]

[0114]

[0115] Table 2 Fracturing process corresponding construction parameters

[0116]

[0117] Example

[0118] Take a well in a domestic shale gas block as an example. The horizontal section of the well has a vertical depth of about 1900m, a horizontal section length of 1637m, an average porosity of 4.8%, an average TOC of 4.7%, and an average brittle mineral content of 71.9%.

[0119] First, based on the original logging data and logging interpretation data of the horizontal well section of the well, reservoir physical quality parameters, rock mechanical parameters, rock ground stress parameters, and fracture network construction potential parameters are collected, and the missing parameters are calculated according to formulas (1)-(13). The calculation results of some key parameters are as follows: Figure 5 shown.

[0120] Secondly, according to the reservoir physical quality parameters, rock mechanical parameters, rock geostress parameters, and fracture network construction potential parameters of the horizontal well section of the well, the reservoir physical quality index, rock stress brittleness index, and fracture network construction potential index of the entire horizontal well section of the target well are calculated. The calculation results are as follows: Figure 6 shown.

[0121] According to formula (23), the reservoir physical quality index threshold, rock stress brittleness index threshold, and fracture network construction potential index threshold of the horizontal section of the well are calculated;

[0122] Finally, the horizontal section of the well is divided into sweet spot identification levels according to the comparison of reservoir physical quality index, rock stress brittleness index, fracture network construction potential index and their corresponding thresholds. The results are as follows: Figure 6 shown.

[0123] Most of the horizontal section of the well passes through the high sweet spot level area. The level 1 sweet spot area (3842-4118m, 4181-4219m, 4514-4617m, 4808-5272m) has good reservoir properties, high gas content, good rock brittleness, and abundant natural microcracks and bedding. It is suitable for the fracturing process of temporary plugging in the middle section and cluster. A reasonable fracturing section length is selected to ensure high fracturing displacement and single cluster perforating fluid volume, and clusters are evenly distributed. Temporary plugging is combined with temporary plugging at the seam mouth and in the seam to ensure uniform extension of the fractures and increase the complexity of the fractures, connect natural microcracks, activate weak bedding surfaces, and most efficiently build oil and gas migration channels connecting the pores of the shale matrix and the horizontal wellbore. Similarly, targeted fracturing technology is selected according to the geological engineering characteristics corresponding to each sweet spot level, and the most economical and efficient fracturing technology is used to improve the final recovery rate; the segmentation results of the horizontal section of the well by selecting targeted fracturing technology according to the sweet spot level are as follows Figure 7As shown in the figure, the specific construction parameters of each section of the well are designed according to the recommended fracturing process. After fracturing, the corresponding production of each horizontal section is as follows: Figure 8 shown.

[0124] The above description is not intended to limit the present invention in any form. Although the present invention has been disclosed through the above embodiments, it is not intended to limit the present invention. Any technician familiar with the profession can make some changes or modifications to equivalent embodiments of equivalent changes using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are within the scope of the technical solution of the present invention.

Claims

1. A method for identifying potential sweet spots in the geological-engineering-fracture network construction of a deep shale gas horizontal well, characterized in that: The following steps are involved: Step 1: Determine the reservoir physical quality parameters, rock mechanics parameters, rock geostress parameters, and fracture network construction potential parameters of the target well based on the original logging and interpretation data of the entire horizontal well section of the target well; Step 2: Calculate the reservoir physical quality index, rock stress brittleness index, and fracture network construction potential index of the entire horizontal well section of the target well according to the reservoir physical quality parameters, rock mechanical parameters, rock geostress parameters, and fracture network construction potential parameters of the entire horizontal well section of the target well; Step 3: Determine the reservoir physical property quality index threshold, rock stress brittleness index threshold, and fracture network construction potential index threshold according to the reservoir physical property quality index, rock stress brittleness index, and fracture network construction potential index of the entire horizontal well section of the target well; Step 4: According to the comparison between reservoir physical quality index, rock stress brittleness index, fracture network construction potential index and their corresponding thresholds, the target well is classified into sweet spot identification levels, and targeted fracturing technology is recommended based on field construction experience.

2. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The reservoir physical quality parameters include TOC, porosity, and gas saturation.

3. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The rock mechanics parameters include Young's modulus and Poisson's ratio.

4. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The rock in-situ stress parameters include maximum horizontal principal stress, minimum horizontal principal stress, vertical stress, and horizontal in-situ stress difference.

5. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The fracture network construction potential parameters include the development degree of natural fractures and the development degree of horizontal bedding.

6. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The calculation formula of the reservoir physical quality index is: Where: B G V is the reservoir physical quality index; f ' is the intermediate parameter of free gas reserves; a1 and b1 represent the weight coefficients of adsorbed gas and free gas reserves respectively; TOC is the TOC content along the well section; TOC' is the normalized TOC content; TOC max is the maximum TOC content of the entire well section; TOC min is the minimum TOC content of the entire well section; S g is the gas saturation along the well section; S g ' is the normalized gas saturation; S gmax is the maximum gas saturation of the entire well section; S gmin is the minimum gas saturation of the entire well section; φ is the porosity along the well section; φ′ is the normalized porosity; φ max is the maximum porosity of the entire well section; φ min It is the minimum porosity of the entire well section.

7. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The calculation formula of the rock stress brittleness index is: Where: B E is the rock stress brittleness index; B N is the rock brittleness coefficient; B n is the intermediate parameter of rock brittleness; S Δ is the normalized geostress difference coefficient; S d is the geostress difference coefficient; e B , e are the weights of rock brittleness coefficient and ground stress difference coefficient that constitute rock stress brittleness index respectively; B N is the normalized intermediate parameter of rock brittleness; B nmax is the maximum intermediate parameter of rock brittleness in the entire well section; B nmin is the minimum intermediate parameter of rock brittleness in the whole well section; υ is Poisson's ratio; υ n is the normalized Poisson's ratio; max is the maximum Poisson's ratio of the entire well section; min is the minimum Poisson's ratio of the entire well section; E is Young's modulus; E n is the normalized Young's modulus; E max is the maximum Young's modulus of the entire well section; E min is the minimum Young's modulus of the entire well section; S dmax is the maximum geostress difference coefficient of the whole well section; S dmin is the minimum geostress difference coefficient of the whole well section; S x is the minimum horizontal principal stress; S y is the maximum horizontal principal stress.

8. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The calculation formula of the fracture network construction potential index is: Where: B NF I is the potential index for seam network construction; N is the normalized crack development intensity; S N is the normalized bedding intensity; I n is the crack development strength; S n is the bedding intensity; I nmax is the maximum Young's modulus fracture development intensity in the entire well section; I nmin is the minimum fracture development intensity of the entire well section; S nmax is the maximum bedding development intensity of the entire well section; S nmin It is the minimum bedding development intensity of the whole well section.

9. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The calculation formula in step 3 is: Where: is the reservoir physical quality index threshold; is the rock stress brittleness index threshold; is the fracture network construction potential index threshold; G is the reservoir physical quality index judgment coefficient, Ψ G =0.38; E is the rock stress brittleness index determination coefficient, Ψ E =0.35; NF is the fracture network construction potential index judgment coefficient, Ψ NF =0.4; is the maximum reservoir physical quality index of the entire well section; is the minimum reservoir physical quality index of the entire well section; is the maximum rock stress brittleness index of the entire well section; is the minimum rock stress brittleness index of the entire well section; It is the maximum fracture network construction potential index of the whole well section; It is the potential index of minimum fracture network construction in the whole well section.

10. The method for identifying potential sweet spots in geological-engineering-fracture network construction of a deep shale gas horizontal well in the entire well section according to claim 1, characterized in that: The specific process of classifying the target well into sweet spot recognition levels in step 4 is as follows: when When; the dessert recognition level is 1; when When; the dessert recognition level is 2; when When; the dessert recognition level is 3; when When; dessert recognition level is 4; when When; dessert recognition level is 5; when When; dessert recognition level is 6; when When; dessert recognition level is 7; when ; The dessert recognition level is 8.

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