An optimal liquid volume design method for effective volume fracturing

Abstract

The application discloses a kind of optimal liquid amount design methods for realizing effective volume fracturing, comprising: based on the geological parameters of target reservoir, rock mechanics parameters, fluid parameters and historical fracturing construction parameters, construct fracturing design basic database, and based on the multi-field coupling numerical model for simulating crack propagation and reservoir response process is constructed to fracturing design basic database;Numerical simulation is carried out in the core design variable domain, and the effective energy volume and crack complexity index under different base liquid amount and energy-adding liquid amount combination are obtained;Multi-objective optimization solution is carried out to the prediction data, and the Pareto optimal solution set is obtained;The combination of optimal base liquid amount and energy-adding liquid amount for target well test construction is determined;On the basis of original single liquid amount, energy-adding liquid amount adapted to formation condition is additionally arranged, effectively removes the stress applied by overlying rock, makes the elastic expansion of stressed reservoir, promotes the recovery, opening and mutual communication of original tectonic crack and non-tectonic crack, and improves single well recovery.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field fracturing and energy enhancement technology, and in particular to an optimal fluid volume design method for achieving effective volume fracturing. Background Technology

[0002] Current methods for fluid volume design in oil and gas field fracturing operations often employ early fracture propagation simulation software for optimization. Besides geological and well network constraints, the boundary condition for fluid volume design is that the marginal productivity gain (net present value) of fracture extension equals the marginal cost of the fracturing fluid system (injection stops when the fracture extension increase is small). Based on this design principle, problems such as repeated stimulation volume and insufficient stimulation are easily encountered, leading to poor production enhancement effects. Microseismic monitoring on the same platform confirms that some wells experience fewer fracture events after injecting a certain amount of fluid, while fracture events increase significantly after the fluid volume exceeds that of adjacent wells. This phenomenon is not accidental but determined by the reservoir's inherent characteristics. Numerous numerical and physical simulation studies show that sedimentary rocks, during sedimentary formation, are subjected to complex stress states such as torsion, compression, and tension due to sedimentary environment, tectonic movements, and subsequent alteration. This stress state causes the reservoir to exhibit an inherent characteristic of recovering to its original stress state during fracturing injection; this characteristic is an objective prerequisite.

[0003] Traditional fluid volume design only considers the increase in the main fracture and the net present value, without fully considering and activating a large number of primary micro fractures, which are long-term oil and gas production channels and seepage carriers. As a result, the resulting modified volume is difficult to constitute a truly effective modified volume, and the reservoir is difficult to be efficiently and fully modified.

[0004] Existing technologies make it difficult to achieve scientific, precise, and adaptive design of volumetric fracturing fluid volume in tight reservoirs, which is one of the important reasons for the "high investment, low return" in on-site construction and the failure of single-well ultimate recovery rate (EUR) to meet expectations. Summary of the Invention

[0005] (a) Technical issues

[0006] The purpose of this invention is to provide an optimal fluid volume design method for achieving effective volumetric fracturing, which solves the problem that existing technologies do not fully consider and activate a large number of native microfractures as long-term oil and gas production channels and seepage carriers, resulting in the formation of a modified volume that is difficult to constitute a truly effective modified volume, and the reservoir is difficult to be efficiently and fully modified.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] An optimal fluid volume design method for achieving effective volumetric fracturing includes:

[0010] A basic database for fracturing design is constructed based on the geological parameters, rock mechanics parameters, fluid parameters, and historical fracturing operation parameters of the target reservoir. A multi-field coupled numerical model for simulating fracture propagation and reservoir response is then constructed based on the basic database for fracturing design.

[0011] Define the core design variable domain. The core design variable domain is based on the optimal liquid volume calculated by the multi-field coupled numerical model. Based on the uniform discrete condition of interval values, multiple sets of liquid volumes with gradients are generated to output the combination of basic liquid volume and energy-enhancing liquid volume. The basic liquid volume is used to satisfy the crack network initiation and main crack propagation, while the energy-enhancing liquid volume is used to activate network cracks, connect and support network cracks, and maximize the effective modification volume.

[0012] Multiple sets of numerical simulations were conducted within the core design variable domain to obtain predicted data on the effective energy-enhancing volume and crack complexity index under different combinations of basic fluid volume and energy-enhancing fluid volume.

[0013] With maximizing both the effective energy-enhancing volume and the crack complexity index as dual optimization objectives, a multi-objective optimization solution was performed on the predicted data to obtain the Pareto optimal solution set; and

[0014] The optimal combination of base fluid and energy-enhancing fluid for target well testing is determined based on the Pareto optimal solution set.

[0015] Furthermore, based on the Pareto optimal solution set, the optimal combination of base fluid volume and energy-enhancing fluid volume for target well test construction is determined, including:

[0016] The target well is subjected to on-site fracturing based on the optimal combination of basic fluid volume and energy-enhancing fluid volume.

[0017] Calculation of actual effective energy enhancement volume and actual fracture complexity index based on microseismic monitoring fracture network morphology;

[0018] Obtain daily production comparison data between the target well and adjacent wells during the trial construction phase;

[0019] Based on the comparison between actual data and predicted data, if the deviation exceeds the preset index, the parameters and coefficients in the input multi-field coupled numerical model are corrected, and the core design variable domain is redefined; if the deviation does not exceed the preset index, the current combination of basic liquid volume and energy-enhancing liquid volume is determined as the final result.

[0020] Furthermore, the preset indicators include: the deviation between the actual effective energy increase volume and the predicted effective energy increase volume is ≤5%, the deviation between the actual fracture complexity index and the predicted fracture complexity index is ≤15%, and the daily production of the target well during the trial construction stage is ≥200% higher than that of the adjacent well.

[0021] Furthermore, a multi-field coupled numerical model for simulating fracture propagation and reservoir response processes is constructed based on the fracturing design database, including:

[0022] A geological field model characterizing reservoir heterogeneity was constructed based on geological and well logging data;

[0023] A geostress field model describing the initial stress state and construction-induced stress changes was constructed based on rock mechanics parameters and geostress data.

[0024] A seepage field model was constructed based on fluid seepage laws to describe the flow of fracturing fluid within fractures and its filtration into the matrix; and

[0025] A crack propagation field model simulating crack initiation, propagation, and interaction is constructed based on fracture mechanics criteria.

[0026] The geological field model, geostress field model, seepage field model, and fracture propagation field model are jointly solved through coupled iteration to output the combination of basic fluid volume and energy-enhancing fluid volume.

[0027] Furthermore, the seepage field model uses Darcy's law coupled with the filtration control equation to calculate the filtration loss corresponding to the base fluid volume and the energy-enhancing fluid volume; the crack propagation field model is constructed using the displacement discontinuity method combined with crack initiation and propagation criteria to determine the minimum threshold of the base fluid volume and the reasonable energy-enhancing range of the energy-enhancing fluid volume; the geostress field model is solved using the elasticity equation to provide stress parameters for the calculation of the base fluid volume and the energy-enhancing fluid volume.

[0028] Furthermore, when constructing the basic database for fracturing design, geological parameters, rock mechanics parameters, fluid parameters, and historical fracturing construction parameters are standardized and outliers are removed.

[0029] Furthermore, the geological parameters include porosity φ, permeability k, thickness h, and oil saturation. ;

[0030] The rock mechanical parameters include Young's modulus E, Poisson's ratio μ, geostress σ, tectonic stress difference ∆σ, cohesion c, and internal friction angle α;

[0031] The fluid parameters include crude oil viscosity. Density ρ, fracturing fluid filtration coefficient C;

[0032] Historical fracturing operation parameters include displacement q, sand ratio R, and operation pressure p.

[0033] Furthermore, scientific computing software is used to implement multi-field coupled numerical models, multiple sets of numerical simulations, and multi-objective optimization solutions for prediction data.

[0034] The algorithm used to solve the multi-objective optimization problem for the prediction data is the non-dominated sorting genetic algorithm NSGA-II from scientific computing software.

[0035] (III) Beneficial Effects

[0036] A basic database for fracturing design was constructed by combining the geological parameters, rock mechanics parameters, fluid parameters, and historical fracturing operation parameters of the target reservoir. A multi-field coupled numerical model was also constructed to simulate the fracture propagation and reservoir response process. By adding energy-enhancing fluid to the basic fluid volume, the predicted data of the combination of basic fluid volume and energy-enhancing fluid volume were simulated under the conditions of maximizing the effective energy-enhancing volume and maximizing the fracture complexity index. At the same time, the optimal combination of basic fluid volume and energy-enhancing fluid volume for the target well test operation was obtained through multi-objective optimization to improve the energy enhancement effect of volumetric fracturing in tight reservoirs.

[0037] Therefore, by combining the optimal base fluid volume and the energy-enhancing fluid volume, the stress exerted by the overlying strata can be effectively relieved, causing the pressurized reservoir to elastically expand, prompting a large number of original structural fractures and non-structural fractures to recover, open and connect with each other, thereby improving the final recovery rate of a single well. Attached Figure Description

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

[0039] Figure 2 This is a schematic diagram of the relationships in the multi-field coupled numerical model of this invention;

[0040] Figure 3 This is a diagram of the three-dimensional hydraulic fracturing numerical simulation model in this invention;

[0041] Figure 4 This is a schematic diagram simulating the application of the energy-enhancing liquid volume in this invention. Detailed Implementation

[0042] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0043] See Figure 1 The diagram shows a schematic flow chart of the design method of the present invention. An embodiment of the present invention proposes an optimal fluid volume design method for achieving effective volume fracturing, specifically including the following steps:

[0044] S1. Construct a basic database for fracturing design based on the geological parameters, rock mechanics parameters, fluid parameters, and historical fracturing operation parameters of the target reservoir.

[0045] Geological parameters, rock mechanics parameters, fluid parameters, and historical fracturing operation parameters of the target reservoir were collected. Geological parameters included porosity φ, permeability k, thickness h, and oil saturation. Rock mechanics parameters include Young's modulus E, Poisson's ratio μ, geostress σ, and tectonic stress difference. Cohesion c, Angle of internal friction Fluid parameters include crude oil viscosity. Density ρ, fracturing fluid filtration coefficient C; historical fracturing operation parameters include displacement q, sand ratio R, and operation pressure p.

[0046] After collecting the above parameters, outlier values ​​need to be removed. Specifically, the collected parameters are standardized and outliers are removed using the 3σ criterion, which means removing data that exceeds the mean ± 3 times the standard deviation. Based on the removed data, a fracturing design database is constructed to provide input data for basic fluid volume, energy-enhancing fluid volume, and numerical models.

[0047] The outlier removal formula is as follows:

[0048] ;

[0049] in, For single parameter data, This is the average value of the parameters. The standard deviation of the parameter is used. Data that meets this condition are judged as outliers and are removed. The geological parameters, rock mechanics parameters, fluid parameters, and historical fracturing construction parameters mentioned above are all processed using this outlier removal formula.

[0050] S2. Based on the fracturing design database, construct a multi-field coupled numerical model to simulate fracture propagation and reservoir response processes. (See...) Figure 2 The diagram shows the relationship of a multi-field coupled numerical model.

[0051] Based on the fracturing design database established in step S1, a multi-field coupled numerical model is built, which integrates the geological field, geostress field, seepage field, and fracture propagation field; that is, a three-dimensional fracturing numerical model. (See [link to relevant documentation]). Figure 3 This is a diagram of the three-dimensional hydraulic fracturing numerical simulation model in this invention. Each field model is solved independently and correlated through coupling conditions. It is used to accurately calculate the minimum threshold of the basic fluid volume and the reasonable energy-enhancing fluid volume. The specific multi-field coupled numerical model and formulas are as follows:

[0052] S21. Construct a geological field model to represent reservoir heterogeneity.

[0053] The spatial distribution functions of porosity and permeability are used to describe reservoir heterogeneity. A three-dimensional geological model is constructed based on the Kriging interpolation method. The core formula is:

[0054] ;

[0055] ;

[0056] in:

[0057] Porosity at any point (x, y, z) in the reservoir, dimensionless;

[0058] : Average reservoir porosity, dimensionless;

[0059] Kriging interpolation weighting coefficients, satisfying ;

[0060] : Permeability at any point (x, y, z) in the reservoir, in mD;

[0061] : Permeability corresponding to average porosity, mD;

[0062] a: Fit coefficient, determined by reservoir experimental data, dimensionless.

[0063] S22. Construct a geostress field model to achieve elasticity mechanics solution.

[0064] Based on the equilibrium equations of elasticity, considering reservoir self-weight and tectonic stress, the distribution of the in-situ stress field is solved to provide stress parameters for calculating the fracturing threshold of the basic fluid volume. The core formula is:

[0065] ;

[0066] Stress calculation of overlying strata:

[0067] ;

[0068] Minimum ground stress:

[0069] ;

[0070] Maximum ground stress:

[0071] ;

[0072] Calculation of reservoir compression, i.e., fracture height:

[0073] ;

[0074] ;

[0075] in:

[0076] Minimum ground stress, MPa;

[0077] Maximum ground stress, MPa;

[0078] : Reservoir rock density, kg / m³;

[0079] g: acceleration due to gravity, m / s²;

[0080] H: Burial depth, m;

[0081] : Structural stress difference, MPa;

[0082] E: Young's modulus, GPa;

[0083] μ: Poisson's ratio, dimensionless;

[0084] F n Force, N;

[0085] S: Cross-sectional area under axial force, m 2 ;

[0086] : Compression amount of fracture height and reservoir thickness, m;

[0087] h: reservoir thickness, m.

[0088] Boundary condition: The stress at the top surface of the reservoir is equal to the stress of the overlying strata. The sides are structural stress boundaries, and the bottom is a fixed constraint.

[0089] S23. Construct a seepage field model to calculate the fracturing fluid loss and flow rate corresponding to the base fluid volume and the energy-enhancing fluid volume.

[0090] The flow of fracturing fluid within the fracture and its loss to the reservoir are coupled using Darcy's law and the loss control equation. This is employed to calculate the loss corresponding to the base fluid volume and the energy-enhancing fluid volume, ensuring that the fluid volume meets the fracture propagation requirements. The core formula is as follows:

[0091] (1) Equation of fracturing fluid flow in fractures (Poiseuille's law):

[0092] ;

[0093] (2) Equation for fluid loss due to fracturing in the reservoir (fluid loss coefficient method):

[0094] ;

[0095] (3) Seepage continuity equation:

[0096] ;

[0097] (4) Construction pressure within the fracture: The first two terms are the fracture initiation pressure (Mohr-Coulomb criterion), and the third term is the frictional pressure of the fracturing fluid along the fracture (Poiseuille's law).

[0098] ;

[0099] in:

[0100] : Volumetric flow rate of fracturing fluid within the fracture, m³ / s;

[0101] Dynamic crack width, in meters;

[0102] Pressure gradient within the crack, MPa / m;

[0103] Construction pressure within the crack, MPa;

[0104] Minimum ground stress, MPa;

[0105] : Viscosity of fracturing fluid, mPa·s;

[0106] q: Construction displacement, m³ / s;

[0107] Crack half-length, m;

[0108] : Fracturing fluid loss rate, m / s;

[0109] C: Fracturing fluid loss coefficient, m / min;

[0110] t: Filtration time, in minutes;

[0111] Fracturing fluid density, kg / m³;

[0112] Crack porosity, dimensionless; typically much smaller than matrix porosity.

[0113] : Crack filtration area, m²;

[0114] c: Rock cohesion, MPa, represents the shear strength of the material under zero normal stress, providing basic strength;

[0115] : Internal friction angle of rock, °, reflects the frictional resistance between material particles.

[0116] S24. Construct a crack propagation field model to determine the minimum threshold of the base fluid volume and the reasonable energy enhancement of the energy-enhancing fluid volume.

[0117] Specifically, the Discontinuity Discontinuity Method (DDM) combined with the Mohr-Coulomb criterion is used to determine crack initiation and propagation, and a crack propagation field model is constructed to determine the minimum threshold of the base fluid volume (to satisfy crack initiation and base extension) and the reasonable energy enhancement of the energy-enhancing fluid volume (to satisfy crack network propagation and support). The core formula is as follows:

[0118] (1) Relationship between displacement discontinuity and stress:

[0119] ;

[0120] in, The influence coefficient matrix is ​​determined by crack geometry parameters and rock mechanics parameters. The displacement discontinuity vector (normal + tangential) of the crack surface. This represents the stress vector on the crack surface.

[0121] (2) Crack initiation criterion (Mohr-Coulomb criterion):

[0122] ;

[0123] When the stress at the crack tip satisfies At that time, the crack expanded;

[0124] (3) Crack propagation direction (direction of maximum principal stress):

[0125] ;

[0126] (4) Crack initiation length (fracture mechanics standard):

[0127] ;

[0128] (5) Design length of foundation cracks:

[0129] ;

[0130] in:

[0131] Shear stress at the crack surface, MPa;

[0132] Normal stress on the crack surface, MPa;

[0133] Friction term: As normal stress increases, the material's resistance to shear increases;

[0134] : Crack propagation direction angle, °;

[0135] Shear stress component, MPa;

[0136] , Principal stresses in the x and y directions, MPa;

[0137] : Crack initiation length, m;

[0138] Fracture toughness;

[0139] Average penetration rate, mD.

[0140] S25. The coupling conditions of the multi-field coupled numerical model, and the specific coupling operations are performed in scientific computing software (MATLAB software is used in this embodiment, and the same scientific computing software is described below. Other software such as Mathematica can also perform some calculation functions, but MATLAB software is preferred in this embodiment).

[0141] 1. Coupling of geological field model and geostress field model: The distribution of reservoir porosity and permeability affects the transfer of geostress. By associating the rock mechanics parameters in the elasticity equation, a basic geological-stress boundary is provided for the calculation of fracture initiation pressure and fracture initiation length.

[0142] 2. Coupling of the geostress field and the fracture propagation field: The geostress distribution determines the fracture initiation pressure and propagation direction. Fracture propagation reacts to the geostress field (induced stress interference). The formula for induced stress is: ;

[0143] The strain generated by crack propagation;

[0144] 3. Coupling of seepage field model and fracture propagation field model: The pressure distribution within the fracture determines the fracture width, fracture length and propagation speed. Dynamic fracture propagation significantly increases the seepage and filtration area, changes the flow and filtration characteristics of fracturing fluid, and thus affects the demand for base fluid and energy-enhancing fluid.

[0145] 4. Model solution process:

[0146] A fully coupled iterative algorithm is used to first solve the geological field model and the geostress field model to obtain the initial stress distribution;

[0147] Then input the fracturing fluid parameters to solve the seepage field model and obtain the pressure distribution inside the fracture;

[0148] Finally, the crack propagation field model is solved based on the pressure distribution and crack initiation criteria, and the crack morphology is updated. The iteration is repeated until the crack propagation is stable, that is, when the propagation rate is ≤0.01m / min, the basic data for calculating the basic fluid volume and the energy-enhancing fluid volume are output simultaneously.

[0149] S3. Define the core design variable domain

[0150] The optimal liquid volume is determined by the combination of the base liquid volume and the energy-enhancing liquid volume, thus constructing the core design variable domain. The core formula is as follows:

[0151] 1. Core Definition:

[0152] Optimal liquid volume ;

[0153] Basic fluid volume The minimum liquid volume required to meet crack initiation and foundation extension to the minimum design length must overcome ground stress and filtration loss.

[0154] Energizing fluid volume The additional fluid volume required to maximize the effective energy enhancement volume, construct a complex fracture network, and improve the fracture conductivity, based on the basic fluid volume.

[0155] 2. Formula for calculating basic fluid volume:

[0156] ;

[0157] in:

[0158] Cracking fluid volume ;

[0159] d is the diameter of the wellbore, in meters; Let be the crack initiation length, m, obtained from the crack initiation criterion. Calculate the actual pore volume of liquid that the crack itself can contain.

[0160] Basic filtrate loss ;

[0161] The filtration area of ​​the basic crack, in m². ; The basic crack propagation time, in minutes;

[0162] Basic extension volume ;

[0163] The design length of the basic fracture is given in meters (m); h is the reservoir thickness in meters (m).

[0164] 3. Formula for calculating the volume of boosting fluid:

[0165] ;

[0166] in:

[0167] This refers to the compression amount based on the fracture height and reservoir thickness. Cluster spacing, For half the length of the crack, ( As section chief, (Number of clusters per segment), see [link / reference] Figure 4 This is a schematic diagram simulating the application of the energy-enhancing liquid volume of the present invention.

[0168] 4. Design variables:

[0169] Automatic sampling of liquid volume gradient conditions to achieve optimal liquid volume Based on the baseline, upper and lower floating ranges are set, and 10 to 20 sets of construction fluid volumes are generated based on the condition of uniform discrete values ​​within the range. At the same time, auxiliary parameters are fixed to ensure single-variable control and eliminate parameter coupling interference.

[0170] This enables the construction of the core design variable domain, outputting the combination of basic fluid volume and energy-enhancing fluid volume.

[0171] S4. Perform multiple sets of numerical simulations within the core design variable domain to obtain predicted data on the effective energy-enhancing volume and crack complexity index under different combinations of basic fluid volume and energy-enhancing fluid volume; with maximizing the effective energy-enhancing volume and maximizing the crack complexity index as dual optimization objectives, perform multi-objective optimization on the predicted data to obtain the Pareto optimal solution set.

[0172] S41, Target Calculation

[0173] ①Effective energy-enhancing volume:

[0174] ;

[0175] Quantitative determination of the effectiveness coefficient of energy enhancement: ;

[0176] Where m, k, and p are the number of 3D reservoir grids, and Δx, Δy, and Δz are the side lengths of the grid cells. Let d be the porosity of the reservoir cell, and d be the distance from the reservoir cell to the fracture, in meters. The crack half-length is in meters. The energy enhancement effectiveness coefficient is 1 for crack penetration, 0.5~0.9 for crack-affected zone, and 0 for no effect.

[0177] ② Crack complexity index:

[0178] ;

[0179] in, For the total area of ​​all activated branch cracks, m 2 ; The total area of ​​the hydraulic main fracture is m. 2 ,when >1. The mesh stitching is complex, but the modification effect is good. The larger the size, the better the effect.

[0180] S42. Orthogonal numerical simulation:

[0181] Using scientific computing software, the core design variable domain was divided into multiple orthogonal experimental schemes (≥50 groups). Each scheme was input into a multi-field coupled numerical model, and the effective energy-enhancing volume was obtained by solving the model. Crack complexity index The analysis focuses on the synergistic effect of base fluid volume and energy-enhancing fluid volume on the energy-enhancing effect, using indicators such as these.

[0182] S42. Multi-objective optimization:

[0183] Using the NSGA-Ⅱ algorithm built into MATLAB, with the objectives of maximizing the effective energy-enhancing volume and the crack complexity index, an objective function is constructed to solve for the optimal combination of basic fluid volume and energy-enhancing fluid volume, thus obtaining the Pareto optimal solution set.

[0184] Objective function:

[0185] ;

[0186] Since the NSGA-II algorithm only supports minimization problems, we transform the maximization objective by taking a negative value, and optimize the algorithm steps as follows:

[0187] S421. Initialize the population: Set the algorithm parameters (population size N≥50, number of iterations G≥100), and randomly generate the initial population;

[0188] S422, Fitness Calculation: Extract the population (basal liquid volume and energy-boosting liquid volume combination, and other variables) and input it into the numerical model to obtain... , , as the fitness value;

[0189] S423. Non-dominated sorting: Perform non-dominated sorting on the population, divide the front layer, calculate the crowding degree, and select the optimal non-dominated individuals;

[0190] S424, Iterative Update: Employing an elite retention strategy, a new population is generated through selection, crossover, and mutation, and S422-S423 are executed iteratively. The iteration is set with dual termination conditions: a preset maximum number of iterations is used as the basic termination condition; simultaneously, a hypervolume index (HV) is introduced to quantify the Pareto front convergence characteristics. When the HV fluctuation amplitude is less than a threshold for several consecutive generations, the algorithm is considered to have converged, and the iteration stops.

[0191] S425, Solution Selection:

[0192] From the Pareto optimal solution set (balanced optimality), combined with the construction cost formula ;

[0193] For the unit cost of fracturing fluid, The unit cost of the proppant.

[0194] The optimal combination of base fluid volume and energy-enhancing fluid volume, which balances effectiveness and economy, is selected, i.e., the optimal fluid volume scheme.

[0195] S5. Determine the optimal combination of base fluid volume and energy-enhancing fluid volume for target well testing based on the Pareto optimal solution set.

[0196] Target wells were selected, and on-site fracturing operations were performed. The optimal combination of base fluid and energy-enhancing fluid was employed, with the base fluid injected first to ensure fracture initiation and base extension, and the energy-enhancing fluid injected later to achieve fracture network expansion. The fracture network morphology was monitored via microseismic monitoring, and the effective energy-enhancing volume was calculated. Crack complexity index Combined with production capacity To verify the effectiveness of the solution.

[0197] Comparing the three indicators of the target well and adjacent wells, if the effective energy-enhancing volume, fracture complexity index, and production capacity of the target well are significantly greater than those of the adjacent wells, then the scheme is effective, and the optimal combination of base fluid volume and energy-enhancing fluid volume is determined. Specifically, after on-site fracturing construction of the target well based on the optimal combination of base fluid volume and energy-enhancing fluid volume, the actual effective energy-enhancing volume and actual fracture complexity index are calculated based on the fracture network morphology monitored by microseismic monitoring, and the daily production comparison data of the target well and adjacent wells during the trial construction phase are obtained. The deviation between the actual data and the predicted data is compared, and the parameters and coefficients are judged to determine whether they need to be adjusted in conjunction with the preset indicators. If the preset indicators are exceeded, the parameters and coefficients in the multi-field coupled numerical model are corrected to redefine the core design variable domain; if the preset indicators are not exceeded, the current combination of base fluid volume and energy-enhancing fluid volume is determined as the final result.

[0198] The preset indicators include a deviation of ≤5% between the actual effective energy-enhancing volume and the predicted effective energy-enhancing volume, a deviation of ≤15% between the actual fracture complexity index and the predicted fracture complexity index, and a daily production increase of ≥200% compared to adjacent wells during the target well's trial construction phase.

[0199] Right now:

[0200] ;

[0201] ;

[0202] .

[0203] By combining the optimal base fluid volume with the energy-enhancing fluid volume, stress is applied to the overlying strata, causing the pressurized reservoir to elastically expand, prompting a large number of original structural fractures and non-structural fractures to recover, open, and connect with each other, thereby improving the final recovery rate of a single well.

[0204] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0205] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. In addition, the terms "first," "second," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0206] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. An optimal fluid volume design method for achieving effective volumetric fracturing, characterized in that, include: A basic database for fracturing design is constructed based on the geological parameters, rock mechanics parameters, fluid parameters, and historical fracturing operation parameters of the target reservoir. A multi-field coupled numerical model is then constructed based on the basic database for fracturing design to simulate the fracture propagation and reservoir response process. Define the core design variable domain. The core design variable domain is based on the optimal liquid volume calculated by the multi-field coupled numerical model. Based on the uniform discrete condition of interval values, multiple sets of liquid volumes with gradients are generated to output the combination of basic liquid volume and energy-enhancing liquid volume. The basic liquid volume is used to satisfy the crack network initiation and main crack propagation, while the energy-enhancing liquid volume is used to activate network cracks, connect and support network cracks, and maximize the effective modification volume. Multiple sets of numerical simulations were conducted within the core design variable domain to obtain predicted data on the effective energy-enhancing volume and crack complexity index under different combinations of basic fluid volume and energy-enhancing fluid volume. With maximizing both the effective energy-enhancing volume and the crack complexity index as dual optimization objectives, a multi-objective optimization solution was performed on the predicted data to obtain the Pareto optimal solution set; and The optimal combination of base fluid and energy-enhancing fluid for target well testing is determined based on the Pareto optimal solution set.

2. The optimal fluid volume design method for achieving effective volumetric fracturing according to claim 1, characterized in that, The optimal combination of base fluid and energy-enhancing fluid for target well testing is determined based on the Pareto optimal solution set, including: The target well is subjected to on-site fracturing based on the optimal combination of basic fluid volume and energy-enhancing fluid volume. Calculation of actual effective energy enhancement volume and actual fracture complexity index based on microseismic monitoring fracture network morphology; Obtain daily production comparison data between the target well and adjacent wells during the trial construction phase; Based on the comparison between actual data and predicted data, if the deviation exceeds the preset index, the parameters and coefficients in the input multi-field coupled numerical model are corrected and the core design variable domain is redefined; if the deviation does not exceed the preset index, the current combination of basic liquid volume and energy-enhancing liquid volume is determined as the final result.

3. The optimal fluid volume design method for achieving effective volume fracturing according to claim 2, characterized in that, The preset indicators include: the deviation between the actual effective energy increase volume and the predicted effective energy increase volume is ≤5%, the deviation between the actual fracture complexity index and the predicted fracture complexity index is ≤15%, and the daily production of the target well during the trial construction stage is ≥200% higher than that of the adjacent well.

4. The optimal fluid volume design method for achieving effective volume fracturing according to claim 1, characterized in that, A multi-field coupled numerical model for simulating fracture propagation and reservoir response processes was constructed based on a fracturing design database, including: A geological field model characterizing reservoir heterogeneity was constructed based on geological and well logging data; A geostress field model describing the initial stress state and construction-induced stress changes was constructed based on rock mechanics parameters and geostress data. A seepage field model was constructed based on fluid seepage laws to describe the flow of fracturing fluid within fractures and its filtration into the matrix; and A crack propagation field model simulating crack initiation, propagation, and interaction is constructed based on fracture mechanics criteria. The geological field model, geostress field model, seepage field model, and fracture propagation field model are jointly solved through coupled iteration to output the combination of basic fluid volume and energy-enhancing fluid volume.

5. The optimal fluid volume design method for achieving effective volume fracturing according to claim 4, characterized in that, The seepage field model uses Darcy's law coupled with the filtration control equation to calculate the filtration loss corresponding to the base fluid volume and the energy-enhancing fluid volume; the crack propagation field model is constructed using the displacement discontinuity method combined with crack initiation and propagation criteria to determine the minimum threshold of the base fluid volume and the reasonable energy-enhancing range of the energy-enhancing fluid volume. The geostress field model is solved using the equations of elasticity, providing stress parameters for the calculation of the base fluid volume and the energy-enhancing fluid volume.

6. The optimal fluid volume design method for achieving effective volumetric fracturing according to claim 1, characterized in that, When constructing the basic database for fracturing design, geological parameters, rock mechanics parameters, fluid parameters, and historical fracturing construction parameters are standardized and outliers are removed.

7. The optimal fluid volume design method for achieving effective volumetric fracturing according to claim 6, characterized in that, The geological parameters include porosity φ, permeability k, thickness h, and oil saturation. ; The rock mechanical parameters include Young's modulus E, Poisson's ratio μ, geostress σ, and tectonic stress difference. Cohesion c, Angle of internal friction ; The fluid parameters include crude oil viscosity. Density ρ, fracturing fluid filtration coefficient C; Historical fracturing operation parameters include displacement q, sand ratio R, and operation pressure p.

8. The optimal fluid volume design method for achieving effective volumetric fracturing according to claim 1, characterized in that, Scientific computing software is used to implement multi-field coupled numerical models, multiple sets of numerical simulations, and multi-objective optimization solutions for prediction data. The algorithm used to solve the multi-objective optimization problem for the prediction data is the non-dominated sorting genetic algorithm NSGA-II from scientific computing software.

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