A method for optimizing fracturing well distribution parameters of a three-dimensional well pattern in a thick shale oil reservoir

Abstract

This invention discloses a method for optimizing well layout parameters in a three-dimensional well network for fracturing in thick shale oil reservoirs. The optimization method includes: Step S1: Inputting the logging curve interpretation results of the pilot test well, and calculating the physical and geomechanical parameters of the target reservoir rock; Step S2: Calculating the reservoir quality, completion quality, and overall quality based on the physical and geomechanical parameters, and initially selecting the vertical landing sites for horizontal wells; Step S3: Establishing a reservoir fracturing geological model based on the physical and geomechanical parameters, building an unconventional oil and gas fracturing fracture propagation model, and simulating the vertical fracture height propagation of the initially selected vertical landing sites for horizontal wells; Step S4: Determining the optimal lateral well network density for each sub-layer based on single-well productivity; Step S5: Outputting the three-dimensional well network layout results. This method maximizes reservoir stimulation volume by drilling the fewest horizontal wells, meeting the needs of cost reduction and efficiency improvement.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation, and in particular to a method for optimizing well layout parameters in a three-dimensional well network for fracturing in extremely thick shale oil reservoirs. Background Technology

[0002] The three-dimensional well network fracturing technology involves arranging multiple horizontal wells in the same oil and gas block to carry out fracturing and drilling plug production in a concentrated manner. This increases the complexity of hydraulic fractures and expands the reservoir stimulation volume from a single well or single layer to a multi-layer system of three-dimensional well networks, or even the entire reservoir stimulation, in order to achieve one-time three-dimensional development of shale oil reservoirs and effectively reduce fracturing construction and production maintenance costs.

[0003] Thick shale oil reservoirs are often composed of multiple stacked sub-strata. A key challenge in three-dimensional well network fracturing technology is determining the vertical and lateral distribution of all horizontal wells. The goal is to maximize reservoir stimulation volume with the fewest horizontal wells drilled, thus meeting the requirements for cost reduction and efficiency improvement. However, field hydraulic fracturing tests are costly, have long operation cycles, and involve many uncertainties in the research results. Therefore, it is necessary to establish an efficient design method that optimizes well placement parameters for three-dimensional well network fracturing in thick shale oil reservoirs, thereby providing guidance for the layout of three-dimensional well networks in fracturing operations.

[0004] Thick shale oil reservoirs are often composed of multiple stacked sub-strata. The challenge of three-dimensional well network fracturing technology lies in determining the vertical and lateral distribution of all horizontal wells. The goal is to maximize reservoir stimulation volume with the fewest horizontal wells drilled, thus meeting the requirements for cost reduction and efficiency improvement. However, field hydraulic fracturing tests are costly, have long operation cycles, and involve many uncertainties in the research results. Existing design methods cannot provide efficient and accurate guidance for the layout of three-dimensional well networks in fracturing operations. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method for optimizing the fracturing well layout parameters of a three-dimensional well network in a very thick shale oil reservoir to overcome or at least partially solve the above problems.

[0006] According to one aspect of the present invention, a method for optimizing the fracturing well layout parameters of a three-dimensional well network in a super-thick shale oil reservoir is provided, the parameter optimization method comprising:

[0007] Step S1: Input the interpretation results of the pilot test well logging curves, and calculate the physical and geomechanical parameters of the target reservoir rock;

[0008] Step S2: Calculate reservoir quality, well completion quality, and overall quality based on physical and geomechanical parameters, and preliminarily select the vertical landing site for horizontal wells;

[0009] Step S3: Based on the physical and geomechanical parameters, establish a reservoir fracturing geological model, build an unconventional oil and gas fracturing fracture propagation model, and conduct vertical fracture height propagation simulation for the initially selected horizontal well vertical landing site.

[0010] Step S4: Based on the final established vertical drilling layout results, determine the optimal lateral well density for each sub-layer by single-well productivity;

[0011] Step S5: Obtain the optimization parameters for fracturing and well placement of the three-dimensional well network in the thick shale oil reservoir, and output the three-dimensional well network layout results.

[0012] Optionally, the three-dimensional well network layout results specifically include reservoir comprehensive quality evaluation results, optimized vertical well placement results, and corresponding horizontal well network density results and single-well productivity prediction results.

[0013] Optionally, step S4: determining the optimal lateral well density of each sub-layer based on the final established vertical drilling layer layout results and single-well productivity specifically includes:

[0014] Based on the final established vertical drilling layout, simulations of fracture propagation morphology were conducted for each layer under different well density conditions.

[0015] The fracture propagation morphology is imported into the reservoir numerical model to evaluate production capacity, and the production capacity of a single well under different well density conditions in each sub-layer is obtained. The optimal lateral well density of each sub-layer is determined by the production capacity of the single well.

[0016] Optionally, establishing a reservoir fracturing geological model based on physical property parameters and geomechanical parameters specifically includes: establishing a reservoir fracturing geological model using integrated geological engineering software based on physical property parameters and geomechanical parameters.

[0017] Optionally, step S1: inputting the interpretation results of the pilot test well logging curves and calculating the physical and geomechanical parameters of the target reservoir rock specifically includes:

[0018] The interpretation results of pilot test well logging curves refer to the results of gamma logging, natural point logging, density logging, resistivity logging, and sonic transit time logging.

[0019] Calculate the reservoir clay content V based on gamma logging data. sh :

[0020]

[0021] In the formula, ΔGR is the standardized natural gamma and spontaneous potential logging curve value; GR and SP are the natural gamma and spontaneous potential curve values; GR min GR max and SP minSP max These are the minimum and maximum values ​​of the natural gamma and natural potential curves, respectively;

[0022] Calculate the effective porosity of the reservoir based on sonic transit time logging data:

[0023]

[0024] In the formula, Porosity, %; DT is the acoustic transit time of the target layer, μs / m; Δt mp The time difference of acoustic waves in the rock skeleton is expressed in μs / m; T f V represents the acoustic transit time of formation fluids, in μs / m. sh T is the clay content index, a decimal; sh Sonic transit time in mud, μs / m;

[0025] Since there is a correlation between permeability and porosity, based on the permeability results, we obtain the following permeability results:

[0026] lgK=D1-2.622ΔGR+7.11lgφ (3)

[0027] In the formula, K is the permeability (mD); D1 is the formation empirical coefficient; lg is the logarithmic sign;

[0028] Calculate oil saturation based on resistivity logging results:

[0029]

[0030] In the formula, S o Oil saturation, %; R w R is the resistivity of formation water, in Ω·m; t denoted as resistivity of the oil and gas-bearing rock, in Ω·m; a is a lithology coefficient related to rock properties, taken as 0.5–1.5; b is a lithology-related coefficient, taken as 2; m is the cementation index, related to porosity and structure; n is the saturation index, taken as 2.

[0031] Key parameters that determine reservoir quality include: clay content, porosity, permeability, and oil saturation.

[0032] Key parameters that determine well completion quality are calculated based on well logging data, including Young's modulus, Poisson's ratio, rock tensile strength, triaxial stress distribution, and rock brittleness index.

[0033] Calculate the Young's modulus and Poisson's ratio of the reservoir based on acoustic transit time data:

[0034]

[0035]

[0036] In the formula, E is Young's modulus, GPa; v is Poisson's ratio, dimensionless; ρ b The actual density value from the well logging curve is in g / cm³. 3 β is the conversion factor, with a value of 10. 6 ;Δt s Transverse wave time difference, μs / m; Δt p The longitudinal wave time difference is expressed in μs / m.

[0037] Calculate the tensile strength of the rock based on Young's modulus and clay content:

[0038]

[0039] In the formula, σ t The tensile strength is expressed in MPa. The triaxial in-situ stress of the reservoir includes vertical stress, maximum horizontal principal stress, and minimum horizontal principal stress. The vertical stress is calculated using an integral formula over the formation density.

[0040]

[0041] In the formula, σ v For vertical stress, MPa; ρ b The density of the formation is kg / m³. 3 H is the target layer depth, in meters; g is the scaling factor, 9.8 N / kg.

[0042] Calculate the horizontal principal stresses based on the transversely isotropic model:

[0043]

[0044] In the formula, σ h The minimum horizontal principal stress is given in MPa; σ H ρ is the maximum horizontal principal stress, MPa; α is the pore pressure coefficient; p p ε represents the pore pressure at the target layer depth, in MPa; h ε is the minimum horizontal principal stress coefficient; H E is the maximum horizontal principal stress coefficient. horz v is the horizontal Young's modulus; horz E is the horizontal Poisson's ratio. vert For vertical Young's modulus; v vert This represents the vertical Poisson's ratio. The overall rock brittleness index is calculated based on the proportion of brittle minerals in the reservoir.

[0045]

[0046] In the formula, BI is the rock brittleness index, V is the mass percentage of mineral components, a is the weighting factor of mineral components, qua is quartz, fel is feldspar, pyr is pyrite, car is calcite, cly is clay, and TOC is the total organic matter content.

[0047] Optionally, step S2: calculating reservoir quality, well completion quality, and overall quality based on physical property parameters and geomechanical parameters specifically includes:

[0048] The reservoir quality includes clay content, porosity, permeability, and oil saturation.

[0049] Reservoir quality, which characterizes reservoir properties, is obtained by weighted combination:

[0050]

[0051] In the formula, Q RQ G is the reservoir quality index. Ii Let be the normalized parameter value of the i-th reservoir quality evaluation index; 'a' is the weight of the i-th index; L = 4;

[0052] Well completion quality includes Young's modulus, Poisson's ratio, rock tensile strength, triaxial stress distribution, and rock brittleness index.

[0053] Reservoir quality, which characterizes reservoir properties, is obtained by weighted combination:

[0054]

[0055] In the formula, Q CQ F represents the well completion quality index, dimensionless. Ii Let α be the normalized parameter value of the i-th well completion quality evaluation index. i Let L be the weight of the i-th indicator of well completion quality, which is dimensionless; L = 5.

[0056] Calculation of the reservoir's comprehensive quality index (CQI):

[0057] Q CQI =W1Q RQ +W2Q CQ (14)

[0058] In the formula, Q CQI The reservoir's overall quality index is dimensionless; W1 and W2 are Q... RQ and Q CQ The weight values ​​are dimensionless.

[0059] Optionally, the preliminary preferred horizontal well longitudinal landing site specifically includes:

[0060] Based on the normalized reservoir comprehensive quality, four categories were divided with 1, 0.45, 0.25, 0.1 and 0 as the boundaries, which are classified as Category I, Category II, Category III and Category IV from best to worst; the small layer with the comprehensive reservoir quality of Category I was selected as the preliminary preferred landing layer for vertical horizontal wells.

[0061] Optionally, step S3: establishing a reservoir fracturing geological model based on physical and geomechanical parameters, constructing an unconventional oil and gas fracturing fracture propagation model, and conducting vertical fracture height propagation simulation for the preliminarily selected horizontal well vertical landing site specifically includes:

[0062] The reservoir fracturing geological model includes reservoir fluid pressure, porosity, permeability, saturation, Young's modulus, Poisson's ratio, rock tensile strength, compressive strength, and triaxial geostress distribution field properties.

[0063] Convert and import wellhead data, well inclination data, stratification data, and logging data using integrated geological engineering software;

[0064] The geological model of the target reservoir is divided into grids, and the three-dimensional attribute model results are obtained by interpolation calculation. Based on this, an unconventional oil and gas fracture propagation model is further established.

[0065] The unconventional oil and gas fracturing fracture propagation model includes a basic parameter input module, a fluid-structure interaction equation calculation module, a laminar / natural fracture weak surface failure criterion, and a fracture propagation module.

[0066] The basic parameter input module includes the results of the three-dimensional geological attribute model, as well as the completion parameters and pumping parameters for on-site fracturing operations. The completion parameters include the horizontal section length, the fracturing section length, and the perforation parameters; the pumping parameters include the fracturing fluid discharge rate, the fluid viscosity, the sand concentration, and the construction fluid volume.

[0067] Optionally, step S4: determining the optimal lateral well density of each sub-layer based on the final established vertical drilling layer layout results and single-well productivity specifically includes:

[0068] Based on the determined vertical well placement layers, and using the established unconventional oil and gas fracture propagation numerical model, fracture propagation simulations were carried out sequentially from bottom to top for different vertical well placement layers.

[0069] The simulation of fracture propagation in different longitudinal well layouts involves selecting a certain longitudinal layer, arranging multiple horizontally adjacent wells at the same depth in the current layer, conducting a multi-well zipper fracturing fracture propagation simulation, and obtaining fracture morphology results.

[0070] The simulation results of fracture propagation morphology were imported into the integrated geological engineering simulation platform to calculate the daily and cumulative oil production of each horizontal well.

[0071] Based on the production prediction data obtained from reservoir numerical model simulation, and after correcting the accuracy of the reservoir numerical model by combining it with existing field production data, further production capacity simulation is carried out.

[0072] The simulation results show the fracture propagation morphology of multiple horizontal wells and the numerical simulation results of the reservoir.

[0073] Optionally, step S5: obtaining the optimized parameters for fracturing and well placement of the three-dimensional well network in the thick shale oil reservoir, and outputting the three-dimensional well network layout results specifically includes:

[0074] The optimization of the three-dimensional well network layout includes: initially selecting the vertical landing layer based on comprehensive quality; further selecting the vertical horizontal well landing layer based on fracture height expansion pattern; and selecting the horizontal well network density of each sub-layer based on fracturing fracture expansion pattern and production capacity performance.

[0075] This invention provides a method for optimizing well layout parameters in a three-dimensional well network for fracturing in thick shale oil reservoirs. The optimization method includes: Step S1: Inputting the logging curve interpretation results from a pilot test well, and calculating the physical and geomechanical parameters of the target reservoir rock; Step S2: Calculating reservoir quality, completion quality, and overall quality based on the physical and geomechanical parameters, and initially selecting the vertical landing sites for horizontal wells; Step S3: Establishing a reservoir fracturing geological model based on the physical and geomechanical parameters, building an unconventional oil and gas fracturing fracture propagation model, and simulating the vertical fracture height propagation of the initially selected vertical landing sites for horizontal wells; Step S4: Determining the optimal transverse well network density for each sub-layer based on the final established vertical drilling layer layout results and single-well productivity; Step S5: Obtaining the optimized well layout parameters for the three-dimensional well network in the thick shale oil reservoir, and outputting the three-dimensional well network layout results. This method maximizes reservoir stimulation volume by drilling the fewest horizontal wells, meeting the needs of cost reduction and efficiency improvement.

[0076] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0077] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0078] Figure 1 A flowchart illustrating a method for optimizing well placement parameters in a three-dimensional well network for massive shale oil reservoirs, provided as an embodiment of the present invention;

[0079] Figure 2 A schematic diagram illustrating the quality, completion quality, and overall quality evaluation results of a super-thick shale oil reservoir provided in an embodiment of the present invention;

[0080] Figure 3 A schematic diagram of the three-dimensional geological modeling results of a super-thick shale oil reservoir provided in an embodiment of the present invention;

[0081] Figure 4 A schematic diagram of the mesh discretization of the unconventional oil and gas fracturing fracture propagation model provided in an embodiment of the present invention;

[0082] Figure 5 A schematic diagram of the simulation results of fracture height propagation in a three-dimensional well network fracturing system provided in an embodiment of the present invention;

[0083] Figure 6 A schematic diagram illustrating the numerical simulation results of fracture propagation and production in multiple horizontal wells provided in an embodiment of the present invention;

[0084] Figure 7 This is a schematic diagram showing the cumulative oil production and normalized production loss results of all wells in the vertically optimized sub-layer obtained from the simulation provided in this embodiment of the invention.

[0085] Figure 8 This is a schematic diagram of the optimized three-dimensional well network layout result provided in an embodiment of the present invention. Detailed Implementation

[0086] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0087] The terms "comprising" and "having," and any variations thereof, in the specification, embodiments, claims, and drawings of this invention are intended to cover non-exclusive inclusion, such as including a series of steps or units.

[0088] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0089] Three-dimensional well pattern fracturing in thick shale oil reservoirs can effectively increase reservoir stimulation volume, improve oil production rate, and enhance recovery efficiency. A key aspect of this technology is determining the optimal vertical and lateral distribution of horizontal wells to reduce drilling costs and maximize production, thereby achieving maximum economic benefits. However, due to the high cost and significant uncertainties of field hydraulic fracturing tests, efficient and accurate optimization design methods for three-dimensional well pattern layout parameters are currently lacking. Therefore, researching optimization methods for three-dimensional well pattern layout parameters in thick shale oil reservoirs is of significant practical importance for promoting efficient development through three-dimensional well pattern fracturing.

[0090] Therefore, when faced with existing technical problems, the inventors, through creative research, discovered that, based on the fracturing operation mode of a three-dimensional well network in a massive shale oil reservoir, an optimization method for the vertical and horizontal well layout in the three-dimensional well network can be established. The entire process of optimizing the fracturing well layout parameters of the three-dimensional well network is as follows: inputting the logging curve interpretation results of the pilot test well to calculate the rock physical properties and geomechanical parameters of the target reservoir, specifically including clay content, porosity, permeability, saturation, rock mechanical strength, rock comprehensive brittleness index, triaxial stress distribution, etc.; based on the reservoir rock physical properties and geomechanical parameters, reservoir quality, completion quality, and comprehensive quality evaluation are carried out, and the layer with the best comprehensive quality is selected as the preliminary preferred landing layer for vertical horizontal wells; based on the reservoir rock physical properties and geomechanical parameters, a reservoir geomechanical model is established, and an unconventional oil and gas fracture propagation model is used to simulate the fracture height propagation of each layer, calculate the fracture propagation area of ​​each layer, and evaluate adjacent layers using the fracture morphology distribution results. The degree of layer overlap is used to further screen or supplement vertical drilling layers. Based on the results of vertical drilling layers, unconventional oil and gas fracture propagation numerical models and reservoir numerical models are used to simulate fracture propagation morphology under different well density conditions in each sub-layer. After obtaining the fracture propagation morphology, it is imported into the reservoir numerical model to evaluate single-well productivity. The optimal lateral well density of each sub-layer is determined by the normalized productivity loss of single wells. After optimizing the lateral well density for all selected landing layers in the vertical direction, it is determined that the optimization analysis of the three-dimensional well network fracturing well layout parameters for the thick shale oil reservoir has been completed. The three-dimensional well network layout results are output, including the comprehensive reservoir quality evaluation results, vertical well layout results, and corresponding lateral well network density and single-well productivity prediction results.

[0091] Example 1

[0092] like Figure 1 As shown, a method for optimizing well layout parameters in a three-dimensional well network for ultra-thick shale oil reservoirs includes the following steps:

[0093] Step 1: Input the interpretation results of the logging curves from the pilot test well to calculate the rock properties and geomechanical parameters of the target reservoir.

[0094] The interpretation results of the pilot test well logging curves refer to the results of gamma ray logging, natural point logging, density logging, resistivity logging, and sonic transit time logging. First, the reservoir clay content (V2) is calculated based on the gamma ray logging data. sh ):

[0095]

[0096] In the formula, ΔGR is the standardized natural gamma and spontaneous potential logging curve value; GR and SP are the natural gamma and spontaneous potential curve values; GR min GR max and SP min SP max These are the minimum and maximum values ​​of the natural gamma and natural potential curves, respectively.

[0097] Calculate the effective porosity of the reservoir based on sonic transit time logging data:

[0098]

[0099] In the formula, Porosity, %; DT is the acoustic transit time of the target layer, μs / m; Δt mp The time difference of acoustic waves in the rock skeleton is expressed in μs / m; T f V represents the acoustic transit time of formation fluids, in μs / m. sh T is the clay content index, a decimal; sh Sonic transit time in muddy soil, μs / m. Since there is a correlation between permeability and porosity, the permeability result is obtained from the permeability result using the following formula:

[0100] lgK=D1-2.622ΔGR+7.11lgφ (3)

[0101] In the formula, K is the permeability (mD); D1 is the formation empirical coefficient; and lg is the logarithmic sign. Then, the oil saturation is calculated based on the resistivity logging results:

[0102]

[0103] In the formula, S o Oil saturation, %; R w R is the resistivity of formation water, in Ω·m; t denoted as resistivity of the oil and gas-bearing rock (Ω·m); a is a lithology coefficient related to rock properties, ranging from 0.5 to 1.5; b is a lithology-related coefficient, taken as 2; m is the cementation index, related to porosity and structure; and n is the saturation index, equal to 2.

[0104] The clay content, porosity, permeability, and oil saturation are the four key parameters that determine reservoir quality. Then, based on well logging data, five key parameters that determine well completion quality are calculated, including Young's modulus, Poisson's ratio, rock tensile strength, triaxial stress distribution, and rock comprehensive brittleness index.

[0105] First, the Young's modulus and Poisson's ratio of the reservoir are calculated based on the acoustic transit time data:

[0106]

[0107] In the formula, E is Young's modulus, GPa; v is Poisson's ratio, dimensionless; ρ b The actual density value from the well logging curve is in g / cm³. 3 β is the conversion factor, with a value of 10. 6 ;Δt s Transverse wave time difference, μs / m; Δt p The longitudinal wave transit time is given in μs / m. The tensile strength of the rock is then calculated based on Young's modulus and clay content.

[0108]

[0109] In the formula, σ t The tensile strength is expressed in MPa. The triaxial in-situ stress of the reservoir includes vertical stress, maximum horizontal principal stress, and minimum horizontal principal stress. The vertical stress is calculated using an integral formula over the formation density.

[0110]

[0111] In the formula, σ v For vertical stress, MPa; ρ b The density of the formation is kg / m³. 3 H represents the target layer depth in meters (m); g is the scaling factor, 9.8 N / kg. The horizontal principal stresses are calculated based on a transversely isotropic model.

[0112]

[0113] In the formula, σ h The minimum horizontal principal stress is given in MPa; σ H ρ is the maximum horizontal principal stress, MPa; α is the pore pressure coefficient, dimensionless; p p ε represents the pore pressure at the target layer depth, in MPa; h ε is the minimum horizontal principal stress coefficient, dimensionless; H E is the maximum horizontal principal stress coefficient, dimensionless; horz v is the horizontal Young's modulus; horz E is the horizontal Poisson's ratio. vert For vertical Young's modulus; v vertThis represents the vertical Poisson's ratio. The overall rock brittleness index is calculated based on the proportion of brittle minerals in the reservoir.

[0114]

[0115] In the formula, BI is the rock brittleness index, V is the mass percentage of mineral components, a is the weighting factor of mineral components, qua is quartz, fel is feldspar, pyr is pyrite, car is calcite, cly is clay, and TOC is the total organic matter content.

[0116] Step 2: Based on the calculated reservoir rock physical and geomechanical parameters, calculate the reservoir quality, well completion quality, and overall quality, and preliminarily select the vertical landing site for the horizontal well.

[0117] Reservoir quality includes four key indices: clay content, porosity, permeability, and oil saturation. The reservoir quality, characterizing its physical properties, is determined by weighted combinations.

[0118]

[0119] In the formula, Q RQ G is a reservoir quality index, dimensionless; Ii Let be the normalized parameter value of the i-th reservoir quality evaluation index, which is dimensionless; a is the weight of the i-th index; L = 4.

[0120] Well completion quality includes five key indices: Young's modulus, Poisson's ratio, rock tensile strength, triaxial stress distribution, and rock brittleness index. These indices are weighted and combined to determine the reservoir quality, which characterizes the reservoir's physical properties.

[0121]

[0122] In the formula, Q CQ F represents the well completion quality index, dimensionless. Ii Let α be the normalized parameter value of the i-th well completion quality evaluation index. i Let L be the weight of the i-th indicator of well completion quality, which is dimensionless; L = 5.

[0123] The Comprehensive Quality Index (CQI) takes into account both reservoir quality and well completion quality. In sections with good reservoir quality evaluations, sections with better well completion quality are selected for fracturing stimulation. The CQI is calculated as follows:

[0124] Q CQI =W1Q RQ +W2Q CQ (14)

[0125] In the formula, Q CQI The reservoir's overall quality index is dimensionless; W1 and W2 are Q...RQ and Q CQ The weights are dimensionless. The evaluation results for reservoir quality, well completion quality, and overall quality are attached. Figure 2 As shown.

[0126] Based on the normalized reservoir overall quality, four categories were defined using 1, 0.45, 0.25, 0.1, and 0 as boundaries, ranging from best to worst: Category I, Category II, Category III, and Category IV. Layers with Category I reservoir overall quality were selected as the initial preferred landing sites for vertical horizontal wells.

[0127] Step 3: Based on the calculated reservoir rock physical and geomechanical parameters, establish a reservoir fracturing geological model using integrated geological engineering software, build an unconventional oil and gas fracturing fracture propagation model, and conduct vertical fracture height propagation simulation on the preliminarily selected sub-layers.

[0128] The reservoir fracturing geological model includes attributes such as reservoir fluid pressure, porosity, permeability, saturation, Young's modulus, Poisson's ratio, rock tensile strength, compressive strength, and triaxial stress distribution field. First, wellhead data, well inclination data, layer data, and logging data are converted and imported using integrated geological engineering software. The wellhead data mainly includes wellhead coordinates and core elevation; the well inclination data mainly includes measurement depth, azimuth, and inclination angle; the layer data mainly includes sublayer numbers and top and bottom depth data; and the logging data includes the rock physical properties and geomechanical parameters described in step two. Then, the target reservoir geological model is meshed, and the three-dimensional attribute model results are obtained through interpolation calculations. Based on this, an unconventional oil and gas fracture propagation model is further established. The three-dimensional attribute geological modeling results of the target reservoir are attached. Figure 3 As shown.

[0129] The unconventional oil and gas fracturing fracture propagation model is innovative. Based on the boundary element method, it considers the influence of lamination and natural fractures on hydraulic fracture propagation. The unconventional oil and gas fracturing fracture propagation model comprises four modules: a basic parameter input module, a fluid-structure interaction equation calculation module, a lamination / natural fracture weak surface failure criterion, and a fracture propagation module.

[0130] The basic parameter input module includes the results of the aforementioned three-dimensional geological property model, as well as well completion parameters and pumping parameters for on-site fracturing operations. Well completion parameters include horizontal section length, fracturing section length, and perforation parameters. Pumping parameters include fracturing fluid flow rate, fluid viscosity, proppant concentration, and injection fluid volume. After inputting the basic parameters, a fracture propagation model mesh is generated. The mesh generation results are shown in the attached figure. Figure 4 As shown.

[0131] The fluid-structure interaction equations include equations for fluid flow within the fracture and equations for rock solid deformation. The fluid flow equation within the fracture is calculated using the mass conservation equation for incompressible fluids within a parallel plate:

[0132]

[0133] In the formula, w is the crack width in meters (m); t is the time in minutes (min); u f C is the fluid viscosity, mPa·s; P is the pressure, MPa; C is the fluid viscosity. L Fluid filtration coefficient, m·s -0.5 t0 is the activation time of the mesh cells, in minutes; Q is the fluid injection rate, in meters. 3 / min; δ is the Kronecker symbol, dimensionless; the rock solid deformation equation is calculated using the three-dimensional displacement discontinuity method, specifically by discretizing the crack surface into N rectangular elements, where each activated crack element induces stress on other elements:

[0134]

[0135] In the formula, x, y, z represent the global coordinate system, σ represents the induced tensile stress, τ represents the induced shear stress, and C represents the induced tensile stress. r The constants related to the Young's modulus and Poisson's ratio of the rock, where v is the Poisson's ratio and D is the constant. x For the crack opening displacement, D y Let I be the crack shear displacement, and I' be the partial derivative of the function I.

[0136] I is the integral kernel function of the crack mesh element surface:

[0137]

[0138] In the formula, ξ and η are local coordinate systems.

[0139] According to the superposition principle, the induced stress on any active cell is equal to the sum of the induced stresses on all other active cells. Based on the stress equilibrium condition, i.e., the fluid pressure inside the fracture is equal to the sum of the induced stress on the fracture cell grid and the formation closure stress, the discrete equation describing the pressure and width inside the fracture is obtained as follows:

[0140]

[0141] Where: N is the total number of units; P is the fluid pressure inside the gap, MPa; σ h is the formation closure stress, equal to the minimum horizontal principal stress of the formation, MPa; C is the three-dimensional plane fracture kernel function, MPa / m, calculated from the right-hand side of equation (16); w is the fracture width, m. Substituting the pressure expression (18) of rock deformation into the fluid flow equation (15) within the fracture, we obtain the coupling equation of fluid flow and solid deformation, and establish the equilibrium equation between the fracture solid deformation width and the fluid pressure.

[0142] The failure criteria module for lamination / natural fracture weak surfaces includes failure criteria for parallel lamination surfaces and failure criteria for vertically distributed natural fracture surfaces, both of which are based on the Mohr-Coulomb criterion.

[0143] When a bedding plane fails due to instability, the shear slip stress on the bedding plane needs to overcome the frictional force on the bedding plane. That is, the bedding plane fails when the shear stress equals the maximum static frictional force on the bedding plane.

[0144] τ s -λ s (σ n -P b )=0 (19)

[0145] In the formula: τ s σ represents the induced shear stress at the bedding tip of the hydraulic fracture, in MPa; n λ represents the induced normal stress at the bedding plane due to hydraulic fractures, in MPa; s P is the friction coefficient of the bedding plane, which is dimensionless; b Let be the fluid pressure within the bedding plane, in MPa. The shear stress and normal stress at the tip of the bedding plane can be calculated using equation (16). For natural fracture surfaces to fail due to instability, the shear slip of the natural fracture surface needs to overcome the sum of the cohesion and friction on the natural fracture surface. That is, when the hydraulically induced shear stress exceeds the sum of the maximum static friction and cohesion, the natural fracture fails.

[0146] τ nf =τ0+λ f (σ nf -P b (20)

[0147] In the formula: τ nf σ represents the induced shear stress at the bedding tip of the hydraulic fracture, in MPa; nf τ0 is the induced normal stress of the hydraulic fracture at the bedding plane, MPa; τ0 is the cohesion of the natural fracture surface, MPa; λ f is the friction coefficient of the natural crack surface, which is dimensionless;

[0148] The fracture propagation module includes calculation of the comprehensive stress intensity factor at the fracture front and tracking of the fracture propagation front. Fracture propagation is a dynamic process within a given injection time; that is, during the numerical simulation, as fracturing fluid is continuously injected, the fracture front continuously expands, and the fracture coverage area increases. The criteria for fracture propagation are calculated based on the comprehensive stress intensity factor.

[0149]

[0150] In the formula, K I The stress intensity factor for type I cracks is MPa·m.0.5 ;K II The stress intensity factor for type II cracks is MPa·m. 0.5 ;K eq The equivalent stress intensity factor is MPa·m. 0.5 θ0 is the fracture propagation angle, °; r is the half-length of the fracture grid cell, m. The stress intensity factors of Type I and Type II fractures are calculated using the width of the leading edge grid cells. Then, the fracture propagation direction is determined, and the equivalent stress intensity factor of the leading edge grid is calculated. This is then compared with the fracture toughness of the reservoir itself. If the equivalent stress intensity factor is greater than the fracture toughness, the fracture propagates along the θ0 angle direction; otherwise, it does not.

[0151] The crack propagation angle is determined by the maximum circumferential stress criterion. By identifying and determining the number and location of active mesh elements at each simulation time, the crack propagation morphology corresponding to each simulation time can be obtained.

[0152] Based on the four modules of the unconventional oil and gas fracturing fracture propagation model described above, the process involves: first, inputting basic parameters; calculating the fluid-structure interaction equations; determining whether the hydraulic fracture activates laminae / weak surfaces of natural fractures using failure criteria; then, iterating through fracture propagation and tracking the fracture morphology, repeating the above process iteratively to complete the hydraulic fracture propagation simulation for a given pumping program; and finally, outputting the fracture propagation morphology and fracture coverage area results. The simulated hydraulic fracture propagation morphology is shown in the attached figure. Figure 5 As shown. The preferred vertical arrangement of horizontal wells is in the 2nd, 4th, and 6th sub-layers.

[0153] Using the preliminarily selected sub-layers based on the overall reservoir quality as landing points for horizontal wells, fracture height propagation simulations were conducted for each sub-layer to obtain the fracture propagation morphology and reservoir stimulation area. The degree of overlap between adjacent sub-layers was evaluated using the fracture morphology distribution results. The degree of overlap between adjacent sub-layers refers to the mutual area coverage of fractures originating from different wells in adjacent sub-layers. When the mutual area coverage of fractures is greater than 30%, the number of vertical well layers should be reduced. Furthermore, when there is a reservoir thickness of more than 30m between two adjacent sub-layers that is not covered by fractures, the number of vertical well layers should be increased between the adjacent sub-layers. The specific criteria for determining whether to reduce or increase the number of vertical well layers are appropriately modified according to different reservoir geological conditions or oilfield development goals. After determining the final vertical well placement positions based on the fracture height propagation morphology, the lateral well density of the corresponding well placement positions is further calculated.

[0154] Step four: Based on the final established vertical drilling layer layout results, simulations of fracture propagation morphology under different well density conditions are carried out for each layer. The fracture propagation morphology is then imported into the reservoir numerical model to evaluate production capacity, and the single-well production capacity under different well density conditions for each sub-layer is obtained. The optimal lateral well density for each sub-layer is determined by the single-well production capacity.

[0155] For the finally determined vertical well placement layers, and using the unconventional oil and gas fracture propagation numerical model established in step three, fracture propagation simulations were carried out sequentially from bottom to top for different vertical well placement layers. The fracture propagation simulation for different vertical well placement layers involved selecting a specific vertical layer, then placing multiple adjacent horizontal wells at the same depth within that layer, and then conducting a multi-horizontal well zipper fracturing fracture propagation simulation to obtain fracture morphology results. The fracture propagation morphology simulation results were imported into an integrated geological engineering simulation platform, and its reservoir numerical simulation module was used to calculate the daily and cumulative oil production of each horizontal well. Based on the production prediction data obtained from the reservoir numerical model simulation, and after correcting the accuracy of the reservoir numerical model by combining it with existing field production data, further production capacity simulations were conducted. The simulated fracture propagation morphology of the multiple horizontal wells and the reservoir numerical simulation results are attached. Figure 6 As shown.

[0156] Different well density refers to the spacing between multiple horizontal wells in a certain formation. Since the reservoir area is fixed, the larger the lateral spacing between adjacent horizontal wells, the smaller the well density and the fewer wells drilled. The total cumulative oil production over 10 years is compared under different well density conditions, and then normalized to calculate the cumulative oil production per 100m horizontal section of each well, which is the normalized cumulative oil production. Using the normalized production when only one horizontal well is drilled as a reference, the normalized production per 100m horizontal section of a single well gradually decreases as the number of horizontal wells increases. The optimal number of horizontal wells is selected based on a 5% reduction in normalized production per 100m horizontal section of a single well. In other words, the optimal number of horizontal wells should be the maximum number of wells that cannot reduce normalized production by more than 5%. The 5% reduction standard for normalized production per 100m horizontal section of a single well is adjusted according to the oilfield's production targets.

[0157] The simulation results of the cumulative oil production and normalized production loss of all wells over 10 years are as follows: Figure 7 As shown, the optimal lateral well density for each sub-layer is 6 wells for the 2nd sub-layer, 5 wells for the 4th sub-layer, and 7 wells for the 6th sub-layer. A schematic diagram of the three-dimensional well network layout is attached. Figure 8 As shown. Following the method described above, the lateral well pattern density optimization for each target layer in the vertical direction is completed sequentially.

[0158] Step 5: The optimization analysis of the three-dimensional well network fracturing well layout parameters for the thick shale oil reservoir has been completed, and the three-dimensional well network layout results are output, including the comprehensive reservoir quality evaluation results, the optimal vertical well placement results, the corresponding horizontal well network density results, and the single well productivity prediction results.

[0159] The three-dimensional well network layout optimization process is innovative, including: initially selecting vertical landing layers based on overall quality; further selecting vertical horizontal well landing layers based on fracture height propagation morphology; and optimizing the lateral well network density of each sub-layer based on fracturing fracture propagation morphology and production performance. The unconventional oil and gas fracturing fracture propagation model is innovative, as it considers the influence of bedding and natural fractures on hydraulic fracture propagation compared to traditional fracturing models.

[0160] The method for optimizing fracturing parameters in a three-dimensional well network for extremely thick shale oil reservoirs provided in this application calculates reservoir rock properties and geomechanical parameters by inputting the logging curve interpretation results of pilot test wells of the target reservoir. It evaluates reservoir quality, completion quality, and overall quality, classifying the overall quality into four categories, and using the first-category quality reservoir as the initial preferred landing layer for vertical horizontal wells. The reservoir rock properties and geomechanical parameters are then imported into an integrated geological engineering software platform to establish a three-dimensional geological model of the target reservoir. Based on this model, an unconventional oil and gas fracturing fracture propagation model is then established.

[0161] Unconventional oil and gas fracturing fracture propagation models are used to simulate fracture propagation morphology and stimulation area of ​​horizontal wells at different vertical landing points. Based on the degree of fracture area coverage or undercoverage between adjacent layers, landing layers for vertical horizontal wells are further selected, or additional infill wells are added. Once the landing layer for the vertical horizontal wells is determined, the fracture propagation numerical model is used to simulate the fracture propagation morphology of multi-well lateral fracturing at different landing layers sequentially from bottom to top. The fracture propagation morphology results are imported into the reservoir numerical simulation module of the integrated geological engineering software to simulate and analyze the normalized production capacity of different lateral well network densities. The optimal lateral well network density for each sub-layer is determined based on the normalized production loss rate. After the optimization of the three-dimensional well network layout parameters, the corresponding results are output, including comprehensive reservoir quality evaluation results, optimized vertical well network layout results, corresponding lateral well network density results, and single-well production capacity prediction results.

[0162] The model and optimization method can quickly and efficiently optimize the well layout parameters for fracturing in thick shale oil reservoirs, and can provide guidance for the layout of three-dimensional well networks at the fracturing site.

[0163] Example 2

[0164] A method for optimizing well placement parameters in a three-dimensional well network for ultra-thick shale oil reservoirs, comprising:

[0165] Firstly, based on the interpretation results of the logging curves from the pilot test well, the vertical clay content, porosity, permeability, and saturation of the reservoir are calculated, and a reservoir quality evaluation model is established. Secondly, based on the logging curve interpretation results, the rock mechanical strength, rock comprehensive brittleness index, triaxial geostress distribution, and the degree of development of natural fractures and bedding are evaluated, and a reservoir completion quality evaluation model is established. Thirdly, through parameter normalization and parameter weight analysis, the reservoir quality and completion quality evaluation models are integrated to establish a comprehensive quality evaluation model. The results of the change of the target reservoir's vertical comprehensive quality with depth are analyzed, and several vertical horizontal well landing layers are preliminarily selected.

[0166] Secondly, based on the vertical rock physical properties and geomechanical results of the target reservoir, a geological model of the super-thick shale oil reservoir was established. An unconventional oil and gas fracturing fracture propagation numerical model was imported, and longitudinal fracture propagation simulation analysis was conducted using commonly used fracturing parameters to evaluate the vertical reservoir stimulation volume and the degree of inter-fracture interference. With the common goal of maximizing stimulation volume and avoiding inter-fracture interference, based on the preliminary selection of horizontal well landing sites according to comprehensive quality, the optimal vertical well location layout for the three-dimensional well network was further determined.

[0167] Thirdly, after establishing the landing strata for vertical horizontal wells, the lateral well density of each landing stratum is optimized. Considering different lateral well densities (where lateral well density refers to the number of horizontal wells within a given range), multiple horizontal wells are used to simulate fracture propagation based on geological models of thick shale oil reservoirs and unconventional oil and gas fracture propagation numerical models. The simulation results are then imported into the reservoir numerical model to analyze production performance under different lateral well density conditions, thereby determining the optimal lateral well density within each sub-layer.

[0168] The method for optimizing fracturing layout parameters in a three-dimensional well network for super-thick shale oil reservoirs provided in this application uses the logging curves from pilot test wells to interpret the results, thereby conducting a comprehensive quality evaluation of super-thick shale oil reservoirs and initially selecting vertical landing layers. This method includes optimizing the vertical landing layers of horizontal wells and the density of the horizontal well network. Based on the rock physical properties and geomechanical parameters of the super-thick shale oil reservoir, a geomechanical model of the shale oil reservoir is established. This geological model includes porosity, permeability, saturation, rock elastic mechanical parameters, and a three-dimensional stress distribution field. Based on the vertical landing layers selected from the comprehensive reservoir quality evaluation results, an unconventional oil and gas fracturing fracture propagation numerical model is used to simulate the high fracture propagation of horizontal wells at different landing points. This fracture propagation simulation includes the area of ​​fractures initiated from different wells, the interference and overlap of fractures between adjacent wells, and other factors. With the goal of maximizing reservoir utilization, which refers to the maximum vertical fracture expansion area and minimal fracture overlap between adjacent wells, the landing sites for vertical horizontal wells are further optimized. This optimization includes screening landing sites initially determined based on overall reservoir quality or further supplementing and infiltrating horizontal wells. After determining the landing sites, the density of the horizontal well network in each landing site is optimized sequentially from bottom to top. Different horizontal well densities are used to conduct fracture expansion and reservoir numerical simulations. The horizontal well network density refers to the number of wells in the same area. As the well network density increases, the number of wells increases, and the single-well productivity in the same production cycle gradually decreases. The optimal horizontal well network density within each sub-layer is determined based on a 5% reduction in single-well productivity. Through the above-mentioned comprehensive reservoir quality evaluation, vertical landing site optimization, and horizontal well network density calculation, the optimization of fracturing well layout parameters for three-dimensional well networks in thick shale oil reservoirs can be achieved quickly and economically, meeting the needs of efficient shale oil reservoir development.

[0169] Beneficial effects: This invention has a more comprehensive and complete design and calculation in terms of basic model, well pattern and fracture pattern synergistic optimization, and economic evaluation.

[0170] The basic model incorporates parameters from multiple disciplines, including geology, engineering, and reservoirs, making it more comprehensive and richer.

[0171] In terms of well network and fracture network collaborative optimization, it is not limited to single wells, but also includes the location of well groups and the artificial fracture system of single wells and well groups. Evaluation and analysis of the entire well network and the entire artificial fracture system can be carried out.

[0172] The evaluation results include comprehensive reservoir quality evaluation results, overall well network fracturing fracture system evaluation results, and production capacity of single wells, sub-layers, and well areas, which can meet the geological and engineering needs of the demonstration process in shale oil development.

[0173] Application Scenarios: 1. Development of fracturing and layout schemes for three-dimensional well networks in different types of shale oil blocks. 2. Design of three-dimensional fracturing and layout networks for well groups. 3. This method also provides a basis for developing three-dimensional fracturing and layout schemes for other complex oil and gas reservoirs.

[0174] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing well layout parameters in a three-dimensional well network for fracturing in extremely thick shale oil reservoirs, characterized in that, The parameter optimization method includes: Step S1: Input the interpretation results of the pilot test well logging curves, and calculate the physical and geomechanical parameters of the target reservoir rock; Step S2: Calculate reservoir quality, well completion quality, and overall quality based on physical and geomechanical parameters, and preliminarily select the vertical landing site for horizontal wells; Step S3: Based on the physical and geomechanical parameters, establish a reservoir fracturing geological model, build an unconventional oil and gas fracturing fracture propagation model, and conduct vertical fracture height propagation simulation for the initially selected horizontal well vertical landing site. Step S4: Based on the final established vertical drilling layout results, determine the optimal lateral well density for each sub-layer by single-well productivity; Step S5: Obtain the optimization parameters for fracturing and well placement of the three-dimensional well network in the thick shale oil reservoir, and output the three-dimensional well network layout results.

2. The method for optimizing fracturing well layout parameters in a three-dimensional well network for extremely thick shale oil reservoirs according to claim 1, characterized in that, The results of the three-dimensional well network layout specifically include the comprehensive reservoir quality evaluation results, the results of the optimal vertical well placement, and the corresponding horizontal well network density results and single-well productivity prediction results.

3. The method for optimizing fracturing well layout parameters in a three-dimensional well network for extremely thick shale oil reservoirs according to claim 1, characterized in that, Step S4: Based on the final established vertical drilling layer layout results, determining the optimal lateral well network density for each sub-layer through single-well productivity specifically includes: Based on the final established vertical drilling layout, simulations of fracture propagation morphology were conducted for each layer under different well density conditions. The fracture propagation morphology is imported into the reservoir numerical model to evaluate production capacity, and the production capacity of single wells under different well density conditions in each sub-layer is obtained. The optimal lateral well density of each sub-layer is determined by the production capacity of single wells.

4. The method for optimizing fracturing well layout parameters in a three-dimensional well network for extremely thick shale oil reservoirs according to claim 1, characterized in that, The establishment of a reservoir fracturing geological model based on physical property parameters and geomechanical parameters specifically includes: establishing a reservoir fracturing geological model using integrated geological engineering software based on physical property parameters and geomechanical parameters.

5. The method for optimizing well layout parameters in a three-dimensional well network for ultra-thick shale oil reservoirs according to claim 1, characterized in that, Step S1: Inputting the logging curve interpretation results of the pilot test well and calculating the physical and geomechanical parameters of the target reservoir rock specifically includes: The interpretation results of pilot test well logging curves refer to the results of gamma logging, natural point logging, density logging, resistivity logging, and sonic transit time logging. Calculate the reservoir clay content V based on gamma logging data. sh : In the formula, ΔGR is the standardized natural gamma and spontaneous potential logging curve value; GR and SP are the natural gamma and spontaneous potential curve values; GR min GR max and SP min SP max These are the minimum and maximum values ​​of the natural gamma and natural potential curves, respectively; Calculate the effective porosity of the reservoir based on sonic transit time logging data: In the formula, Porosity, %; DT is the acoustic transit time of the target layer, μs / m; Δt mp The time difference of acoustic waves in the rock skeleton is expressed in μs / m; T f V represents the acoustic transit time of formation fluids, in μs / m. sh T is the clay content index, a decimal; sh Sonic transit time in mud, μs / m; Since there is a correlation between permeability and porosity, based on the permeability results, we obtain the following permeability results: lgK=D1-2.622ΔGR+7.11lgφ (3) In the formula, K is the permeability (mD); D1 is the formation empirical coefficient; lg is the logarithmic sign; Calculate oil saturation based on resistivity logging results: In the formula, S o Oil saturation, %; R w R is the resistivity of formation water, in Ω·m; t denoted as resistivity of the oil and gas-bearing rock, in Ω·m; a is a lithology coefficient related to rock properties, taken as 0.5–1.5; b is a lithology-related coefficient, taken as 2; m is the cementation index, related to porosity and structure; n is the saturation index, taken as 2. Key parameters that determine reservoir quality include: clay content, porosity, permeability, and oil saturation. Key parameters that determine well completion quality are calculated based on well logging data, including Young's modulus, Poisson's ratio, rock tensile strength, triaxial stress distribution, and rock brittleness index. Calculate the Young's modulus and Poisson's ratio of the reservoir based on acoustic transit time data: In the formula, E is Young's modulus, GPa; v is Poisson's ratio, dimensionless; ρ b The actual density value from the well logging curve is in g / cm³. 3 β is the conversion factor, with a value of 10. 6 ;Δt s Transverse wave time difference, μs / m; Δt p The longitudinal wave time difference is expressed in μs / m. Calculate the tensile strength of the rock based on Young's modulus and clay content: In the formula, σ t The tensile strength is expressed in MPa. The triaxial in-situ stress of the reservoir includes vertical stress, maximum horizontal principal stress, and minimum horizontal principal stress. The vertical stress is calculated using an integral formula over the formation density. In the formula, σ v For vertical stress, MPa; ρ b The density of the formation is kg / m³. 3 H is the target layer depth, in meters; g is the scaling factor, 9.8 N / kg. Calculate the horizontal principal stresses based on the transversely isotropic model: In the formula, σ h The minimum horizontal principal stress is given in MPa; σ H ρ is the maximum horizontal principal stress, MPa; α is the pore pressure coefficient; p p ε represents the pore pressure at the target layer depth, in MPa; h ε is the minimum horizontal principal stress coefficient; H E is the maximum horizontal principal stress coefficient. horz v is the horizontal Young's modulus; horz E is the horizontal Poisson's ratio. vert For vertical Young's modulus; v vert This represents the vertical Poisson's ratio. The overall rock brittleness index is calculated based on the proportion of brittle minerals in the reservoir. In the formula, BI is the rock brittleness index, V is the mass percentage of mineral components, a is the weighting factor of mineral components, qua is quartz, fel is feldspar, pyr is pyrite, car is calcite, cly is clay, and TOC is the total organic matter content.

6. The method for optimizing fracturing well layout parameters in a three-dimensional well network for extremely thick shale oil reservoirs according to claim 1, characterized in that, Step S2: Calculating reservoir quality, well completion quality, and overall quality based on physical and geomechanical parameters specifically includes: The reservoir quality includes clay content, porosity, permeability, and oil saturation. Reservoir quality, which characterizes reservoir properties, is obtained by weighted combination: In the formula, Q RQ G is the reservoir quality index. Ii Let be the normalized parameter value of the i-th reservoir quality evaluation index; 'a' is the weight of the i-th index; L = 4; Well completion quality includes Young's modulus, Poisson's ratio, rock tensile strength, triaxial stress distribution, and rock brittleness index. Reservoir quality, which characterizes reservoir properties, is obtained by weighted combination: In the formula, Q CQ F represents the well completion quality index, dimensionless. Ii Let α be the normalized parameter value of the i-th well completion quality evaluation index. i Let L be the weight of the i-th indicator of well completion quality, which is dimensionless; L = 5. Calculation of the reservoir's comprehensive quality index (CQI): Q CQI =W1Q RQ +W2Q CQ (14) In the formula, Q CQI The reservoir's overall quality index is dimensionless; W1 and W2 are Q... RQ and Q CQ The weight values ​​are dimensionless.

7. The method for optimizing well layout parameters in a three-dimensional well network for ultra-thick shale oil reservoirs according to claim 6, characterized in that, The preliminary preferred horizontal well vertical landing layer sites specifically include: Based on the normalized reservoir comprehensive quality, four categories were divided with 1, 0.45, 0.25, 0.1 and 0 as the boundaries, which are classified as Category I, Category II, Category III and Category IV from best to worst; the small layer with the comprehensive reservoir quality of Category I was selected as the preliminary preferred landing layer for vertical horizontal wells.

8. The method for optimizing fracturing well layout parameters in a three-dimensional well network for extremely thick shale oil reservoirs according to claim 1, characterized in that, Step S3: Based on the physical and geomechanical parameters, establish a reservoir fracturing geological model, build an unconventional oil and gas fracturing fracture propagation model, and conduct vertical fracture height propagation simulation for the preliminarily selected horizontal well vertical landing site. Specifically, this includes: The reservoir fracturing geological model includes reservoir fluid pressure, porosity, permeability, saturation, Young's modulus, Poisson's ratio, rock tensile strength, compressive strength, and triaxial geostress distribution field properties. Convert and import wellhead data, well inclination data, stratification data, and logging data using integrated geological engineering software; The geological model of the target reservoir is divided into grids, and the three-dimensional attribute model results are obtained by interpolation calculation. Based on this, an unconventional oil and gas fracture propagation model is further established. The unconventional oil and gas fracturing fracture propagation model includes a basic parameter input module, a fluid-structure interaction equation calculation module, a laminar / natural fracture weak surface failure criterion, and a fracture propagation module. The basic parameter input module includes the results of the three-dimensional geological attribute model, as well as the completion parameters and pumping parameters for on-site fracturing operations. The completion parameters include the horizontal section length, the fracturing section length, and the perforation parameters; the pumping parameters include the fracturing fluid discharge rate, the fluid viscosity, the sand concentration, and the construction fluid volume.

9. The method for optimizing fracturing well layout parameters in a three-dimensional well network for extremely thick shale oil reservoirs according to claim 1, characterized in that, Step S4: Based on the final established vertical drilling layer layout results, determining the optimal lateral well network density for each sub-layer through single-well productivity specifically includes: Based on the determined vertical well placement layers, and using the established unconventional oil and gas fracture propagation numerical model, fracture propagation simulations were carried out sequentially from bottom to top for different vertical well placement layers. The simulation of fracture propagation in different longitudinal well layouts involves selecting a certain longitudinal layer, arranging multiple horizontally adjacent wells at the same depth in the current layer, conducting a multi-well zipper fracturing fracture propagation simulation, and obtaining fracture morphology results. The simulation results of fracture propagation morphology were imported into the integrated geological engineering simulation platform to calculate the daily and cumulative oil production of each horizontal well. Based on the production prediction data obtained from reservoir numerical model simulation, and after correcting the accuracy of the reservoir numerical model by combining it with existing field production data, further production capacity simulation is carried out. The simulation results show the fracture propagation morphology of multiple horizontal wells and the numerical simulation results of the reservoir.

10. The method for optimizing well layout parameters in a three-dimensional well network for ultra-thick shale oil reservoirs according to claim 1, characterized in that, Step S5: Obtaining the optimized parameters for fracturing and well placement of the three-dimensional well network in the thick shale oil reservoir, and outputting the three-dimensional well network layout results, specifically includes: The optimization of the three-dimensional well network layout includes: initially selecting the vertical landing layer based on comprehensive quality; further selecting the vertical horizontal well landing layer based on fracture height expansion pattern; and selecting the horizontal well network density of each sub-layer based on fracturing fracture expansion pattern and production performance.

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