A method for adjusting and controlling fracture EOR coupled reservoir fracture network flooding

Abstract

The application discloses a kind of fractured EOR coupling's reservoir network drive production regulation and control method, based on reservoir parameter establishment embedded discrete fracture model, to fracture conductivity, injection rate, chemical agent concentration and slug size design orthogonal scheme, obtain drive production dynamic data;Define network advantage index and slug intensity coefficient, coupling is network drive production regulation and control coefficient, and establish its quantitative relationship with recovery ratio increment, see agent time;Determine optimal regulation interval: positive regulation is required by measured network advantage inversion slug parameter;Reverse regulation is required by injection allocation capacity network reconstruction target;According to reservoir status, select scheme, implement injection or repeated fracturing, and real-time monitoring water cut, chemical agent concentration and tracer, when measured see agent time and prediction deviation threshold value is updated quantitative relationship and slug parameter;The application realizes network and injection two-way collaborative regulation and control, overcomes the drawbacks of trial and error, inhibits chemical agent channeling, improves sweep efficiency and recovery.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas field development technology, and in particular relates to a reservoir fracture network drive and production control method with hydraulic fracturing and EOR coupling. Background Technology

[0002] Low-permeability, tight oil reservoirs have extremely low matrix permeability, and natural energy recovery rates are typically less than 10%. Industrial oil flows can only be obtained by creating complex fracture networks through volumetric fracturing. After fracturing, the reservoir exhibits a dual "matrix-fracture" media characteristic, leading to the widespread application of EOR technologies such as polymer flooding and surfactant flooding to utilize remaining oil. In practice, the fracture network structure controls the chemical agent migration channels, and injection parameters determine the degree of fracture network utilization; a proper match between these two factors is crucial for achieving ideal oil recovery results.

[0003] Existing technologies typically employ reservoir numerical simulation methods to establish a dual-medium model with equivalent parameters for the fracture network. Through single-factor or orthogonal simulations, they compare recovery rates under different slug sizes, injection rates, chemical concentrations, and injection timings to select the relatively optimal injection combination. In the field, an initial plan is set based on experience, and adjustments are made in stages using data such as tracer monitoring and production dynamics. Remedial measures such as rate reduction, well shut-in, or repeated fracturing are implemented when fluid breakthroughs or production declines occur.

[0004] However, existing technologies have the following obvious drawbacks: First, the design of fracturing parameters and the design of injection regime are independent of each other, lacking a unified coupling characterization method, and cannot accurately optimize injection parameters based on the fracture network morphology; second, they mainly rely on experience-based trial and error adjustments, lacking two-way quantitative control methods, and cannot determine injection based on the fracture network, nor can they inversely derive the fracture network modification requirements from the recovery target, resulting in serious chemical agent cross-flow, low utilization rate, and difficulty in effectively utilizing the inter-fracture matrix and residual oil in the affected blind zone, thus limiting the increase in recovery rate. Summary of the Invention

[0005] Purpose of the Invention: The purpose of this invention is to provide a reservoir fracture network flooding and production control method coupled with EOR (Enhanced Oil Recovery) in fracturing. By uniformly coupling the fracture network structure parameters and EOR injection parameters into control coefficients and establishing a quantitative relationship chart, a two-way control method of "determining injection based on the fracture network and inverting fracture network modification based on the flooding and production target" is achieved. This overcomes the shortcomings of existing technologies, such as severe chemical agent cross-flow, low utilization rate, and difficulty in utilizing remaining oil in the fracture network blind zone caused by independent parameter design and reliance on experience trial and error. It effectively improves the utilization rate of chemical agents and the degree of utilization of remaining oil, and significantly enhances the recovery rate.

[0006] Technical solution: The reservoir fracture network flooding and production control method with hydraulic fracturing and EOR coupling described in this invention includes the following steps:

[0007] Obtain the reservoir basic parameters, fracturing operation parameters and EOR injection parameters of the target reservoir, and establish a conceptual numerical model of fracturing EOR coupled production using an embedded discrete fracture model to explicitly characterize the main fracture and secondary fracture network.

[0008] An orthogonal scheme was designed with fracture conductivity, injection rate, chemical agent concentration and chemical agent slug size as influencing factors, and batch simulations were conducted to obtain a dynamic data set of flooding and production, including production well water cut, time to chemical agent exposure, chemical flooding recovery rate and water flooding recovery rate under the same fracture network parameters.

[0009] The fracture network dominance index is determined based on the fracture conductivity, matrix permeability, and injection-production well spacing. The slug strength coefficient is determined based on the chemical agent concentration, chemical agent slug size, chemical agent baseline concentration, and fracture network sweep pore volume. The fracture network dominance index and the slug strength coefficient are coupled to form the fracture network drive-production control coefficient. The quantitative relationship between the fracture network drive-production control coefficient and the recovery rate increase and normalized time to agent exposure is established using the drive-production dynamic data set.

[0010] The optimal control range is determined based on the quantitative relationship, and the target control coefficient is selected within the optimal control range. The required slug strength coefficient and chemical agent slug size are inverted based on the measured slug dominance index to form a positive control scheme. The required slug dominance index and effective fracture conductivity are inverted based on the maximum slug strength coefficient under the limitation of on-site injection capacity to form a negative control scheme.

[0011] Based on the current state of the fracture network and injection capacity of the target reservoir, the forward control scheme or the reverse control scheme is selected. EOR chemical slug injection is implemented according to the selected control scheme. When the reverse control scheme is selected, the effective fracture conductivity is adjusted by repeated fracturing or temporary plugging to make the fracture network drive-production control coefficient in the optimal control range.

[0012] During implementation, the water cut of the production well, the concentration of the chemical agent in the produced fluid, and the tracer monitoring data are tracked. The measured time to see the agent is compared with the predicted time to see the agent obtained according to the quantitative relationship. When the deviation between the two exceeds the set threshold, the quantitative relationship and subsequent chemical agent slug parameters are updated according to the measured data.

[0013] Preferably, the reservoir basic parameters include reservoir porosity φ, matrix permeability km, crude oil viscosity μo, reservoir temperature T, injection-production well spacing L, oil saturation So, water saturation Sw, rock compressibility coefficient cf, crude oil compressibility coefficient co, and formation water compressibility coefficient cw. The fracturing construction parameters include fracture half-length xf, fracture permeability kf, fracture width wf, fracture network density nf, and fracture network stimulation volume SRV. The reservoir comprehensive compressibility coefficient ct is calculated according to... Calculations are performed where ct, cf, co, and cw are all in units of 1. φ, So, and Sw are all decimals.

[0014] Preferably, the fracture conductivity FCD is determined according to... The calculation is performed, where FCD represents the fracture conductivity, measured in units of... kf is the fracture permeability, in units of wf is the fracture width in cm; the injection well in the conceptual numerical model is completed in a segmented and clustered manner according to volumetric fracturing; the EOR chemical agent is a polymer, surfactant or a composite system thereof; the viscosity-enhancing parameter, interfacial tension reduction parameter, adsorption retention parameter and inaccessible pore volume parameter of the EOR chemical agent are determined by laboratory experiments, and the injection volume and production volume are kept in balance under reservoir conditions.

[0015] Preferably, under the condition that other parameters remain unchanged, multiple levels are set for fracture conductivity (FCD), injection rate (q), chemical agent concentration (C), and chemical agent slug size (Vsl) to form the orthogonal scheme; after simulation of each orthogonal scheme, the production well water cut (fw), time to reach chemical agent (tb), and chemical flooding recovery rate (ER) are output, and the water flooding recovery rate (ERw) under the same fracture network parameters is used as the benchmark, according to... Calculate the increase in recovery rate ,in, The units for ER and ERw are all percentages.

[0016] Preferably, the mesh dominance index Nf is determined according to... Calculations were performed using FCD, km, L, kf, and wf, all converted to SI units, with Nf being a dimensionless number; the slug strength coefficient Is was calculated according to... Calculate, where C is the concentration of the chemical agent, in units of... Vsl is the volume of the chemical slug, in units of Cs is the baseline concentration of the chemical reagent determined in the laboratory experiment, in units of... Vp represents the swept pore volume of the seam mesh, in units of... Is is a dimensionless number.

[0017] Preferably, the stitching mesh drive control coefficient F is according to... Calculate, where, and The fitting index is determined by regression based on the aforementioned dynamic data set of oil recovery, with an initial value of 1 for all values, and F is a dimensionless number; F is plotted as the x-axis, representing the increase in oil recovery rate. The ordinate is obtained by fitting it in a semi-logarithmic coordinate system. Plotting F as the x-axis and normalizing the time to administration. The ordinate is obtained by fitting it to a double logarithmic coordinate system. Where tb0 is the time to see the agent under the baseline seam parameters and baseline injection regime, in days, and a, b, c and d are the fitting coefficients determined by regression based on the dynamic data set of the drive and extraction.

[0018] Preferably, based on the increase in recovery rate The curve of the control coefficient F of the sewing mesh driving method changed from a rapid increase to a flattening position, and this was combined with the normalized inoculation time. The optimal control range is determined by the relationship between F and the flow rate. When F is lower than the lower limit of the optimal control range, it is determined that the flow rate advantage of the suture mesh is insufficient or the chemical injection intensity is too low. When F is higher than the upper limit of the optimal control range, it is determined that the flow of chemical agent along the dominant suture channel is intensified and the time of drug exposure is advanced.

[0019] Preferred, in and When both are 1, the positive control scheme is according to and It is confirmed that, among them, The target control coefficient is denoted as Nf, and the measured dominance index of the seam mesh is denoted as Nf. The target slug strength coefficient, Let Cs be the target chemical slug volume, Vp be the fracture mesh sweep pore volume, and C be the chemical concentration to be implemented. By adjusting at least one of the chemical slug volume and the chemical concentration, the fracture mesh drive control coefficient F is made to reach [value missing]. .

[0020] Preferred, in and When both are 1, the reverse control scheme is according to and It is confirmed that, among them, This represents the maximum slug strength coefficient under the limitation of on-site dispensing capacity. The target sewing mesh advantage index that the sewing mesh modification should achieve is... The target effective fracture conductivity should be achieved by fracture mesh modification, where km is the matrix permeability and L is the injection-production well spacing; when the effective fracture conductivity is lower than... At that time, the effective fracture conductivity is improved by repeated fracturing or increasing the proppant size. When the measured fracture network dominance index makes F continuously higher than the upper limit of the optimal control range, a temporary plugging and diversion is implemented after injecting a pre-plug with 0.1 times the fracture network pore volume to reduce the effective fracture conductivity; and according to Predict the onset time tb under the target control coefficient.

[0021] Preferably, during on-site implementation, the water cut of the production well and the concentration of the chemical agent in the produced fluid are tracked according to the preset injection volume interval, and the actual time to see the agent is determined using the tracer monitoring data; when the deviation of the actual time to see the agent from the predicted time to see the agent is set to a threshold, a, b, c and d are refitted according to the actual data, the fracture network drive production control coefficient is corrected, and the subsequent chemical agent slug parameters are continuously optimized.

[0022] Beneficial Effects: Compared with the prior art, the present invention has the following significant advantages: 1. By coupling the fracture network structure parameters and EOR injection parameters into a single control coefficient and establishing a quantitative relationship chart, the present invention achieves bidirectional control of "injection determined by the fracture network and fracture network modification derived from the target of oil recovery," alleviating the problems of severe chemical agent cross-flow, low utilization rate, and difficulty in utilizing residual oil in the fracture network-affected blind zone caused by independent parameter design and reliance on experience trial and error in the prior art, thus providing a new approach to improve chemical agent utilization efficiency and recovery rate; 2. The present invention establishes a bidirectional control mechanism of forward and reverse directions, which can quickly determine the EOR injection regime based on measured fracture network parameters and derive the required fracture network modification based on the target of oil recovery. The invention provides a quantitative basis for determining the timing and intensity of repeated fracturing and temporary plugging diversion measures, based on the requirements for fracturing and effective fracture conductivity. Furthermore, relying on a technical approach of "numerical simulation batch schemes + statistical regression charts," this invention elevates the traditional experience-based trial-and-error control method to a quantifiable and predictable general quantitative method, offering valuable insights for other reservoir engineering problems involving the coupling of reservoir structure parameters and development parameters. Finally, the invention introduces a rolling correction mechanism driven by measured data during field implementation. By comparing the deviation between measured and predicted fracturing times in real time and updating the quantitative relationship, the dynamic adaptability of the control scheme under complex reservoir conditions is ensured, reducing the risk of long-term implementation effects deviating from the expected goals. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0024] Figure 2 This is a schematic diagram of the conceptual numerical model of the present invention;

[0025] Figure 3 To increase the recovery rate of the present invention Intersection chart with the control coefficient F of the mesh drive;

[0026] Figure 4 This is a cross-plot of the normalized time to see the agent tb / tb0 and the control coefficient F of the mesh drive in this invention. Detailed Implementation

[0027] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0028] This invention discloses a reservoir fracture network flooding and production control method based on fracturing and EOR coupling, comprising the following steps:

[0029] Step 1: Collect basic parameters of the target reservoir and fracturing operation parameters.

[0030] Basic reservoir parameters include reservoir porosity The parameters include matrix permeability (km), crude oil viscosity (μo), reservoir temperature (T), injection-production well spacing (L), oil saturation (So), water saturation (Sw), rock compressibility coefficient (cf), crude oil compressibility coefficient (co), and formation water compressibility coefficient (cw); fracturing parameters include fracture half-length (xf), fracture permeability (kf), fracture width (wf), fracture network density (nf), and fracture network stimulation volume (SRV). The overall reservoir compressibility coefficient (ct) is calculated using the following formula:

[0031] (1)

[0032] In the formula, ct is the reservoir's overall compressibility coefficient, in units of... cf is the rock compressibility coefficient, in units of ; Reservoir porosity, expressed as a decimal; So and Sw are oil saturation and water saturation, respectively, both expressed as decimals; co and cw are crude oil compressibility and formation water compressibility, respectively, both in units of... .

[0033] Fracture conductivity (FCD) calculated from fracturing parameters:

[0034] (2)

[0035] In the formula, FCD represents the fracture conductivity, and the unit is _____. kf represents crack permeability, in units of... wf represents the crack width in cm.

[0036] Step 2: Establish a conceptual numerical model of fracturing EOR coupling and fracture network-driven mining.

[0037] Using reservoir numerical simulation software, the embedded discrete fracture model EDFM was employed to explicitly characterize the primary fractures and secondary fracture networks formed by hydraulic fracturing, establishing a conceptual numerical model for simulating hydraulic fracturing coupled with oil recovery and recovery (EOR) production. In the model, injection wells were completed using a segmented and clustered volumetric fracturing approach; EOR chemicals consisted of polymers, surfactants, or composite systems thereof, with parameters such as viscosity enhancement, interfacial tension reduction, adsorption retention, and inaccessible pore volume input based on laboratory experimental measurements; the injection and production rates were maintained in equilibrium under reservoir conditions.

[0038] Step 3: Perform batch simulations of orthogonal schemes to obtain a dynamic data set of drive and mining data.

[0039] With other parameters remaining constant, multiple levels of influencing factors were set, and orthogonal schemes were designed, including fracture conductivity (FCD), injection velocity (q), chemical concentration (C), and chemical slug size (Vsl). The chemical slug size (Vsl) represents the chemical slug volume and can be... It can also be expressed as a multiple of the pore volume affected by the fractured mesh, PV. After each scheme is run, the water cut of the production well, fw, the time to reach the chemical flooding agent, tb, and the final chemical flooding recovery rate, ER, are output. Using the water flooding recovery rate ERw under the same fractured mesh parameters as a benchmark, the recovery rate increase is calculated according to the following formula:

[0040] (3)

[0041] In the formula, % represents the increase in recovery rate of chemical flooding relative to water flooding; ER represents the recovery rate of chemical flooding; ERw represents the recovery rate of water flooding; This forms a dynamic data set of flooding and production that covers the coupling relationship between different fracture network parameters and injection parameters.

[0042] Step 4: Define the control coefficient F of the mesh drive, draw the intersection chart and determine the quantitative relationship.

[0043] First, we define the fracture network dominance index Nf. Under the same pressure differential, according to Darcy's law, the ratio of the fluid's transport capacity along the fracture channel to the matrix's supply capacity to the fracture determines the distribution relationship between the injected fluid's inrush along the fracture network and its sweep to the matrix; the larger this ratio, the more pronounced the fracture network's conductivity advantage. Based on this, we define a dimensionless fracture network dominance index:

[0044] (4)

[0045] In the formula, km is the matrix permeability; L is the injection-production well spacing; FCD, km, L, kf and wf are converted to SI units before being used in the calculation; and Nf is a dimensionless number.

[0046] Next, the slug strength coefficient Is is defined. The effective action of the chemical agent depends on the chemical dosage injected per unit sweep pore volume. Using the reference chemical agent concentration Cs, determined experimentally and used as a normalized baseline, and the reference slug, as benchmarks, the reference chemical agent concentration Cs is preferably the optimal concentration determined experimentally. The slug strength coefficient is calculated according to the following formula:

[0047] (5)

[0048] In the formula, C is the chemical concentration, in mg / L; Vsl is the chemical slug volume, in mg / L. Cs represents the standard concentration of the chemical reagent, in units of... Vp represents the swept-sweep pore volume of the seam mesh, in units of... Is is a dimensionless number.

[0049] The slug dominance determines the transport pathway conditions for the chemical agent, while the slug strength determines the effective dosage of the chemical agent. Coupled, the slug-based flooding control coefficient is defined as follows:

[0050] (6)

[0051] In the formula, F is the dimensionless mesh drive control coefficient; α and β are the fitting indices, both initially set to 1, and corrected by regression based on the dynamic data set of the drive.

[0052] Using the fractured mesh recovery control coefficient F as the horizontal axis and the recovery rate increase as the vertical axis... Plot a cross-plot on the ordinate and perform linear fitting on a semi-logarithmic scale to obtain a quantitative relationship:

[0053] (7)

[0054] Using the sewing mesh drive control coefficient F as the abscissa and the normalized time to see the agent as the normalized time to see the agent. Plot a cross-section on the ordinate and perform linear fitting on a log-log scale to obtain a quantitative relationship:

[0055] (8)

[0056] In the formula, tb0 represents the time to see the agent under the reference suture mesh parameters and the reference injection regime, in days; is the normalized time to see the agent; a, b, c, and d are fitting coefficients, determined by regression analysis of the dynamic data set of the drive and extraction process.

[0057] Step 5: Determine the optimal control range and inversely determine the control scheme.

[0058] Based on the characteristics of the recovery rate increase with the control coefficient F of the fracture-net drive shown in Equation (7), and combined with the characteristics of the normalized time to reach the target chemical agent shown in Equation (8), the position where the recovery rate increase curve changes from rapid rise to slowing down and the risk of chemical agent crossflow are determined, and then the optimal control range Fopt is determined. When F is lower than the lower limit of this range, it indicates that the fracture-net conduction advantage is insufficient or the chemical agent injection intensity is low, and the fracture-net coverage is limited; when F is higher than the upper limit of this range, the crossflow of chemical agent along the dominant fracture channel intensifies, the recovery rate increase tends to saturate and the time to reach the target chemical agent is advanced. The target control coefficient is selected within the optimal control range. When a given target recovery rate increase At the same time, the corresponding increase in the target recovery rate can also be determined according to equation (7). And verify the corresponding predicted time of administration according to formula (8).

[0059] With both α and β set to 1, the forward control uses the measured joint network dominance index Nf as a known quantity to invert the target slug strength coefficient. and target chemical slug volume :

[0060] (9)

[0061] (10)

[0062] In the formula, The target control coefficient; The target slug strength coefficient; The target chemical slug volume is defined. F is achieved by adjusting at least one of the chemical slug volume and chemical concentration. The injection rate q can be selected from the rate levels already evaluated in the orthogonal scheme, taking into account the on-site injection capacity.

[0063] With both α and β set to 1, the reverse control method uses the maximum slug strength coefficient Is,max under the limitation of on-site injection capacity as a known quantity to invert the target slug dominance index that the slug modification should satisfy. And the target effective fracture conductivity (FCD*) to be achieved after repeated fracturing or temporary plugging is calculated using equations (2) and (4):

[0064] (11)

[0065] In the formula, Is,max is the maximum slug strength coefficient under the limitation of on-site injection capacity; The target sewing mesh advantage index that should be achieved in the sewing mesh renovation; The target effective fracture conductivity should be achieved through fracture mesh modification. Effective fracture conductivity can be improved by repeated fracturing or increasing the proppant volume; when measured Nf causes F to consistently exceed the upper limit of the optimal control range, the effective fracture conductivity can be adjusted by temporarily blocking and redirecting the proppant. The predicted proppant ingress time under the target control coefficient is... It serves as a benchmark for on-site monitoring and comparison.

[0066] Step 6: Conduct on-site implementation and dynamic feedback correction.

[0067] The control scheme determined in step 5 is implemented on-site. During the implementation process, the water cut of the production well and the concentration of the chemical agent in the produced fluid are tracked according to the preset injection volume interval, and the actual time of agent initiation is determined by combining the tracer monitoring data. The actual time of agent initiation is compared with the predicted time of agent initiation obtained by equation (8). When the deviation between the two exceeds the preset deviation threshold, the fitting coefficients a, b, c, and d in equations (7) and (8) are refitted according to the measured data, the fracture network drive production control coefficient is corrected, and the subsequent chemical agent slug parameters are continuously optimized, thereby realizing the dynamic control of the full displacement process. The preset injection volume interval and the preset deviation threshold can be determined according to the frequency of on-site monitoring and the control accuracy. The specific values ​​can be set according to the embodiment.

[0068] The following example uses a tight sandstone reservoir, combined with... Figures 1 to 4 The present invention will be further described below. The following embodiments are used to illustrate the technical solution of the present invention, and the specific parameter values ​​are used to demonstrate the control process and do not affect the applicability of the aforementioned general steps and parameter relationships.

[0069] like Figure 1 As shown, the entire control process includes the following steps: collecting reservoir basic parameters and fracturing operation parameters; establishing a conceptual numerical model of fracturing EOR coupled with fracture network drive and production using EDFM; conducting batch simulations of orthogonal schemes and obtaining a dynamic data set of drive and production; defining the fracture network drive and production control coefficient F and drawing a cross plot; determining the optimal control interval Fopt and inverting the control scheme; and implementing the control in the field and correcting the control coefficient based on dynamic data feedback. Figure 1 The feedback correction arrow on the right indicates that the actual measured data is returned to the stage of determining the control coefficient and cross plot, which is used to refit the quantitative relationship and continuously optimize subsequent schemes.

[0070] Step 1: Determine the basic parameters of the reservoir and calculate the comprehensive compressibility coefficient and fracture conductivity.

[0071] Reservoir porosity in this embodiment Matrix permeability Crude oil viscosity reservoir temperature The well spacing between injection and production is L=300m, the half-length of the fracturing fracture is xf=120m, the initial oil saturation Soi=65%, and the corresponding initial water saturation is 35%; the rock compressibility coefficient... Crude oil compression coefficient Formation water compressibility coefficient The baseline injection regime is: injection speed The polymer baseline concentration Cs = 1500 mg / L, and the baseline slug size is 0.3 PV, where 0.3 PV means that the volume of the chemical agent slug is 0.3 times the volume of the corresponding slit network wave and pores.

[0072] The overall reservoir compressibility coefficient is calculated according to equation (1):

[0073] (1-1)

[0074] Step 2: Establish a conceptual numerical model for fracturing EOR coupled fracture network mining.

[0075] A conceptual numerical model was established using the GEM component simulator in CMG numerical simulation software. The model employs a single injection-production well group with a planar grid size of 10m × 10m, and the matrix is ​​vertically divided into 5 layers. The embedded discrete fracture model (EDFM) is used to explicitly characterize the fracture network, with a main fracture half-length of 120m and secondary fractures arranged in an orthogonal fracture network with a specific fracture network density. Viscosity-concentration relationship and adsorption retention of polymer solutions. Both the inaccessible pore volume of 0.15 and the value of inaccessible pore volume were determined by indoor experiments.

[0076] Figure 2 In the diagram, the blue vertical line on the left represents the injector well, and the red vertical line on the right represents the producer well, with a well spacing L of 300m. The tan area represents the reservoir matrix. The blue dashed box near the injector well represents the fractured reservoir volume (SRV) formed by fracturing. The black horizontal line within the dashed box represents the primary fracture, and the intersecting or diagonal lines represent the secondary fracture network. The green arrows indicate the migration of EOR chemical displacement front from the fracture network into the matrix and continuing towards the producer well. This figure also shows that the primary fracture and secondary fracture network provide dominant migration channels for the chemical agent, while the extent of matrix sweep outside the fracture network is jointly controlled by the conductivity of the fracture network and the injection regime.

[0077] Step 3: Design an orthogonal scheme and obtain dynamic data of the mining process.

[0078] To maintain a balance between injection and production rates under reservoir conditions, the following orthogonal scheme is adopted: The fracture conductivity (FCD) is set to 5, 10, 20, 40, and 80. There are 5 levels in total; the chemical concentration C is set at 1000, 1500, and 2000 mg / L, for a total of 3 levels; the chemical slug size Vsl is set at 0.1, 0.3, and 0.5 PV, for a total of 3 levels; the injection rate q is fixed. The dominance index of the seam mesh is calculated based on equations (2) and (4), for example... At that time, after unifying all parameters to SI units, Each scheme was run until the water cut of the production well reached 98%, and the recovery rate increase was calculated according to formula (3). Representative schemes and results are shown in Table 1.

[0079] Table 1. Orthogonal scheme and dynamic results of mining drive

[0080] 1 5 0.167 1.00 0.167 5.2 4.09 2 10 0.33 1.00 0.33 8.7 2.68 3 20 0.67 1.00 0.67 12.3 1.73 4 40 1.33 1.00 1.33 15.8 1.13 5 80 2.67 1.00 2.67 19.4 0.73 6 40 1.33 1.50 2.00 17.9 0.88 7 80 2.67 1.50 4.00 21.5 0.57 8 80 2.67 2.22 5.93 23.6 0.44 9 20 0.67 0.50 0.335 8.8 2.65

[0081] Step 4: Fit quantitative relationships and draw cross plots.

[0082] Pick Using the fractured mesh recovery control coefficient F as the abscissa and the recovery rate increase as the ordinate. Plot a cross-plot for the ordinate. Under semi-logarithmic coordinates, the numerical simulation results show a good linear relationship with F. Equation (7) in this embodiment takes the following form:

[0083] , (7-1)

[0084] Figure 3 The horizontal axis represents the dimensionless fractured mesh recovery control coefficient F, measured on a logarithmic scale, and the vertical axis represents the recovery rate increase. Red dots represent the results of numerical simulation schemes, and blue lines represent... The fitting results, correlation coefficient The yellow shaded area represents the optimal control range determined in this embodiment. As shown in the figure, the increase in recovery rate increases with the increase of F, but after entering and exceeding the optimal control range, the contribution of further increasing F to the increase in recovery rate gradually slows down.

[0085] A cross-plot was plotted with F as the abscissa and the normalized time to administration tb / tb0 as the ordinate. Under the logarithmic coordinate system, the numerical simulation results showed a good linear relationship with F. Equation (8) in this embodiment is as follows:

[0086] , (8-1)

[0087] In this embodiment, tb0 is the baseline scheme. , The time to administration of the drug under the conditions of C=1500mg / L and Vsl=0.3PV was tb0=286d.

[0088] Figure 4 The horizontal axis represents the dimensionless mesh-driven control coefficient F, measured on a logarithmic scale; the vertical axis represents the normalized time to dredge (tb / tb0), also measured on a logarithmic scale. Red dots represent the results of the numerical simulation scheme, and blue lines represent... The fitting results, correlation coefficient The yellow shaded area indicates As shown in the figure, the normalized inoculation time decreases as F increases, indicating that the inoculation time is advanced and the risk of chemical agent leakage along the dominant suture channel is increased.

[0089] Step 5: Determine the optimal control range and perform a two-way inversion.

[0090] according to Figure 3 When F exceeds 2.0, the recovery rate increase curve tends to flatten, and further increasing F has limited contribution to the recovery rate; according to Figure 4 When F is greater than 2.0, tb / tb0 is less than 0.9, indicating premature agent introduction and a significantly increased risk of chemical cross-contamination. The optimal control range for this embodiment was determined based on comprehensive analysis. And take the target control coefficient .

[0091] During positive control, the effective fracture conductivity formed by the actual fracturing operation in this reservoir is: Nf = 2.0 is obtained by calculation using equation (4). The result is obtained by inversion using equation (9). Then, using equation (10), the chemical slug size is adjusted from 0.3PV to 0.225PV; while keeping the slug volume constant, the polymer concentration can also be equivalently adjusted to 1125mg / L. After implementing this system, the time to see the chemical agent in the production well was delayed from 172 days in the empirical scheme to 251 days, which is consistent with the prediction made by equation (8). At the same control level, the deviation is mainly caused by the heterogeneity of the well group and is less than the deviation threshold set in this embodiment; the recovery rate increases by 17.2%, which is 4.9 percentage points higher than the empirical scheme, and the amount of chemical agent used is reduced by 25%.

[0092] When adjusting in reverse, if the on-site injection capacity limit causes the maximum slug strength coefficient Is,max=0.5, then the result can be obtained by inversion from equation (11). , This means that the effective fracture conductivity needs to be increased to #imgpt118# through repeated fracturing or by increasing the proppant size. Conversely, if the measured Nf=4.0 causes F to remain above the upper limit of the optimal control range, then a temporary plugging and redirection should be implemented after injecting a 0.1PV pre-slug to reduce the effective fracture conductivity and bring F back to the optimal control range.

[0093] Step 6: Conduct on-site monitoring and feedback correction.

[0094] During the on-site implementation, the water cut of the production well and the concentration of the chemical agent in the produced fluid were tracked every 0.05 PV injected. The actual time to reach the target fluid (tb) was calculated using the tracer monitoring data, and the actual time to reach the target fluid was compared with... Figure 4 The predicted values ​​of the intersection charts are compared. When the deviation between the two exceeds 15%, the a, b, c, and d values ​​in equations (7) and (8) are refitted based on the measured data to correct the slit-mesh displacement control coefficient and continuously optimize the subsequent chemical slug parameters, thereby achieving dynamic control of the total displacement process. In this embodiment, 0.05PV is the specific value of the preset injection volume interval, and 15% is the specific value of the preset deviation threshold.

[0095] As can be seen from the above implementation process, this method uses the fracture network dominance index Nf to characterize the degree of dominance of fracture channels relative to matrix supply capacity, uses the slug strength coefficient Is to characterize the effective amount of chemical agent in a unit fracture network sweep pore volume, and couples the two in a unified manner through the fracture network flooding control coefficient F; then, it combines two flooding indicators, namely recovery rate increase and agent exposure time, to determine the control range, so that the hydraulic fracture network modification and EOR injection system can be designed forward, checked backward and dynamically corrected under the same quantitative framework.

Claims

1. A reservoir fracture network flooding and production control method with hydraulic fracturing and EOR coupling, characterized in that, Includes the following steps: Obtain the reservoir basic parameters, fracturing operation parameters and EOR injection parameters of the target reservoir, and establish a conceptual numerical model of fracturing EOR coupled production using an embedded discrete fracture model to explicitly characterize the main fracture and secondary fracture network. An orthogonal scheme was designed with fracture conductivity, injection rate, chemical agent concentration and chemical agent slug size as influencing factors, and batch simulations were conducted to obtain a dynamic data set of flooding and production, including production well water cut, time to chemical agent exposure, chemical flooding recovery rate and water flooding recovery rate under the same fracture network parameters. The fracture network dominance index is determined based on the fracture conductivity, matrix permeability, and injection-production well spacing. The slug strength coefficient is determined based on the chemical agent concentration, chemical agent slug size, chemical agent baseline concentration, and fracture network sweep pore volume. The fracture network dominance index and the slug strength coefficient are coupled to form the fracture network drive-production control coefficient. The quantitative relationship between the fracture network drive-production control coefficient and the recovery rate increase and normalized time to agent exposure is established using the drive-production dynamic data set. The optimal control range is determined based on the quantitative relationship, and the target control coefficient is selected within the optimal control range. The required slug strength coefficient and chemical agent slug size are inverted based on the measured slug dominance index to form a positive control scheme. The required slug dominance index and effective fracture conductivity are inverted based on the maximum slug strength coefficient under the limitation of on-site injection capacity to form a negative control scheme. Based on the current state of the fracture network and injection capacity of the target reservoir, the forward control scheme or the reverse control scheme is selected. EOR chemical slug injection is implemented according to the selected control scheme. When the reverse control scheme is selected, the effective fracture conductivity is adjusted by repeated fracturing or temporary plugging to make the fracture network drive-production control coefficient in the optimal control range. During implementation, the water cut of the production well, the concentration of the chemical agent in the produced fluid, and the tracer monitoring data are tracked. The measured time to see the agent is compared with the predicted time to see the agent obtained according to the quantitative relationship. When the deviation between the two exceeds the set threshold, the quantitative relationship and subsequent chemical agent slug parameters are updated according to the measured data.

2. The method according to claim 1, characterized in that, The reservoir basic parameters include reservoir porosity φ, matrix permeability km, crude oil viscosity μo, reservoir temperature T, injection-production well spacing L, oil saturation So, water saturation Sw, rock compressibility coefficient cf, crude oil compressibility coefficient co, and formation water compressibility coefficient cw. The fracturing operation parameters include fracture half-length xf, fracture permeability kf, fracture width wf, fracture network density nf, and fracture network stimulation volume SRV; the reservoir comprehensive compressibility coefficient ct is calculated according to... Calculations are performed where ct, cf, co, and cw are all in units of 1. φ, So, and Sw are all decimals.

3. The method according to claim 2, characterized in that, The fracture conductivity FCD is based on The calculation is performed, where FCD represents the fracture conductivity, measured in units of... kf is the fracture permeability, in units of wf is the fracture width in cm; the injection well in the conceptual numerical model is completed in a segmented and clustered manner according to volumetric fracturing; the EOR chemical agent is a polymer, surfactant or a composite system thereof; the viscosity-enhancing parameter, interfacial tension reduction parameter, adsorption retention parameter and inaccessible pore volume parameter of the EOR chemical agent are determined by laboratory experiments, and the injection volume and production volume are kept in balance under reservoir conditions.

4. The method according to claim 1, characterized in that, Under the condition that other parameters remain unchanged, multiple levels are set for fracture conductivity (FCD), injection velocity (q), chemical agent concentration (C), and chemical agent slug size (Vsl) to form the orthogonal scheme; after simulation of each orthogonal scheme, the production well water cut (fw), time to reach chemical agent (tb), and chemical flooding recovery rate (ER) are output, and the water flooding recovery rate (ERw) under the same fracture network parameters is used as the benchmark, according to... Calculate the increase in recovery rate ,in, The units for ER and ERw are all percentages.

5. The method according to claim 4, characterized in that, The mesh dominance index Nf is based on Calculations were performed using FCD, km, L, kf, and wf, all converted to SI units, with Nf being a dimensionless number; the slug strength coefficient Is was calculated according to... Calculate, where C is the concentration of the chemical agent, in units of... Vsl is the volume of the chemical slug, in units of... Cs is the baseline concentration of the chemical reagent determined in the laboratory experiment, in units of... Vp represents the swept pore volume of the seam mesh, in units of... Is is a dimensionless number.

6. The method according to claim 5, characterized in that, The stitch mesh drive control coefficient F is according to Calculate, where, and The initial value of the fitting index is 1, determined by regression based on the aforementioned dynamic data set of oil recovery. F is a dimensionless number. The index is plotted on the x-axis as the increase in oil recovery rate. The ordinate is obtained by fitting it in a semi-logarithmic coordinate system. Plotting F as the x-axis and normalizing the time to administration. The ordinate is obtained by fitting it to a double logarithmic coordinate system. Where tb0 is the time to see the agent under the baseline seam parameters and baseline injection regime, in days, and a, b, c and d are the fitting coefficients determined by regression based on the dynamic data set of the drive and extraction.

7. The method according to claim 6, characterized in that, Based on the increase in recovery rate The curve of the control coefficient F of the sewing mesh driving method changed from a rapid increase to a flattening position, and this was combined with the normalized inoculation time. The optimal control range is determined by the relationship between F and the flow rate. When F is lower than the lower limit of the optimal control range, it is determined that the flow rate advantage of the suture mesh is insufficient or the chemical injection intensity is too low. When F is higher than the upper limit of the optimal control range, it is determined that the flow of chemical agent along the dominant suture channel is intensified and the time of drug exposure is advanced.

8. The method according to claim 6, characterized in that, exist and When both are 1, the positive control scheme is according to and It is confirmed that, among them, The target control coefficient is denoted as Nf, and the measured dominance index of the seam mesh is denoted as Nf. The target slug strength coefficient, Let Cs be the target chemical slug volume, Vp be the fracture mesh sweep pore volume, and C be the chemical concentration to be implemented. By adjusting at least one of the chemical slug volume and the chemical concentration, the fracture mesh drive-through control coefficient F is made to reach [value missing]. .

9. The method according to claim 6, characterized in that, exist and When both are 1, the reverse control scheme is according to and It is confirmed that, among them, This represents the maximum slug strength coefficient under the limitation of on-site dispensing capacity. The target sewing mesh advantage index that the sewing mesh modification should achieve is... The target effective fracture conductivity should be achieved by fracture mesh modification, where km is the matrix permeability and L is the injection-production well spacing; when the effective fracture conductivity is lower than... At that time, the effective fracture conductivity is improved by repeated fracturing or increasing the proppant size. When the measured fracture network dominance index makes F continuously higher than the upper limit of the optimal control range, temporary plugging and diversion are implemented after injecting a pre-slug with 0.1 times the fracture network pore volume to reduce the effective fracture conductivity; and according to Predict the onset time tb under the target control coefficient.

10. The method according to claim 6, characterized in that, During the on-site implementation, the water cut of the production well and the concentration of the chemical agent in the produced fluid were tracked according to the preset injection volume interval, and the actual time to see the agent was determined by using the tracer monitoring data. When the deviation of the actual time to see the agent from the predicted time to see the agent was set to a threshold, a, b, c and d were refitted according to the actual data, the fracture network drive production control coefficient was corrected, and the subsequent chemical agent slug parameters were continuously optimized.

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