Physical model evaluation method for improving large principal stress difference vertical well fracturing crack bandwidth

Abstract

The invention provides a physical model evaluation method for improving a large principal stress difference vertical well fracturing crack bandwidth. The physical model evaluation method comprises the following steps: step 1, measuring an in-situ triaxial stress difference; 2, pouring an artificial rock sample, wherein the triaxial compression strength is consistent with that under the condition of large principal stress difference on site; 3, carrying out a fracturing physical model experiment under the condition of conventional large principal stress difference; 4, carrying out a large principal stress difference fracturing physical model experiment under the condition of pre-injection of low mucus; step 5, comparing the number of acoustic emission AE events monitored by the verification physical model; 6, fracturing physical model experiments of different pre-injection liquid quantities are carried out; and step 7, forming evaluation of the transformation effect of the pre-injected low mucus on the fracturing fracture bandwidth under the large principal stress difference condition. According to the physical model evaluation method for improving the large principal stress difference vertical well fracturing fracture bandwidth, the possibility of fracture wave and bandwidth and fracturing fracture complexity under the large principal stress difference condition is accurately evaluated, the transformation size and the single well productivity are increased, and ultra-deep compact reserve upgrading and effective regional utilization are achieved.

Description

Technical Field

[0001] This invention relates to the field of oil and gas fracturing and production enhancement technology, and in particular to a physical model evaluation method for improving the fracture bandwidth of vertical wells with large principal stress differences. Background Technology

[0002] With the continuous expansion of oil and gas exploration and development, deep and ultra-deep reservoirs have gradually become important areas for increasing oil and gas reserves and production. The central Junggar Basin has abundant deep high-pressure tight sandstone oil reservoirs, mainly distributed in the Zhengshacun, Yongjin, and Moxizhuang oilfields. Although the target blocks vary greatly in depth, the vertical depth is generally between 6500 and 7800 meters, and the horizontal stress difference can reach 20 to 30 MPa. The reservoirs are characterized by deep burial, poor physical properties, abnormally high pressure, high sensitivity, and low natural productivity. Deep oil and gas reservoir fracturing generally faces the problem of low net fracture pressure and limited pressure window, which makes traditional oil and gas extraction methods unable to meet production needs. There is an urgent need to improve industrial production capacity through new fracturing stimulation methods.

[0003] Due to unfavorable geomechanical factors such as poor reservoir properties, large horizontal stress differences, and strong rock plasticity, monitoring results of fracturing in numerous ultra-deep vertical wells with large principal stress differences show that fracturing operations result in low fracture complexity, difficulty in creating a fracture network, low post-fracturing productivity, and even insignificant production increases. The core issue is that when the horizontal stress difference is large (20MPa–30MPa), hydraulic fractures easily penetrate strongly cemented natural fractures directly under high geostress differences, limiting lateral expansion and resulting in small fracture bandwidth, low complexity, and difficulty in achieving the expected stimulation volume.

[0004] Current research primarily focuses on predicting parameters such as fracture length and bandwidth, rather than improving these parameters. There is no direct method to quantify the impact of low-viscosity pre-fracturing fluid on fracture redirection under large principal stress differences, nor can the correlation between pre-fracturing fluid volume and fracture bandwidth be determined. Low-viscosity pre-fracturing fluid can enhance fracture redirection. During fracturing, pore pressure alters the effective stress state of the rock, thus affecting the deformation and fracturing of the rock's solid framework. Besides the decrease in reservoir compressive strength and elastic modulus with increasing pore pressure, according to the effective stress principle, higher pore pressure makes it easier for the reservoir's effective stress to reach shear and tensile strength. In other words, pore water pressure reduces effective stress, making fracturing more likely, especially in cases of well-developed natural fractures. Higher pore pressure makes it easier for disturbance stress to induce shear failure in natural fractures when hydraulic fractures approach them, thus increasing both the bandwidth and complexity of hydraulic fractures. Under conditions of large horizontal stress difference, the fracture bandwidth is small and the complexity is low. Reducing the stress difference through new fracturing methods is of great significance for improving the production capacity of deep sandstone oil and gas resources.

[0005] CN202010490089.X discloses a method and apparatus for predicting effective fracture zones, characterized by the following steps: Step 1: Identifying effective fractures and classifying them into types to determine the development range of effective fracture zones in a single well; Step 2: Establishing a cross-sectional map of rock physical properties for different types of effective fractures, and selecting physical properties used to distinguish different fracture zones based on the cross-sectional map; Step 3: Using Bayesian discriminant analysis, establishing a discriminant formula for effective fracture zones based on the distinguishing physical properties; Step 4: Obtaining a three-dimensional data volume of the physical properties of the formation to be tested, and predicting the effective fracture zones using the discriminant formula to obtain the spatial distribution of the effective fracture zones. This patent only identifies effective fractures and predicts fracture zones. However, it does not optimize or quantify fracture zones that do not meet the requirements for sand addition under large principal stress differences or have small bandwidths.

[0006] CN202111295274.4 discloses a method for predicting fracture length in multi-stage fracturing horizontal wells of shale gas reservoirs based on elastic yield. The method includes: Step 1, calculating the elastic yield of the shale gas well; Step 2, plotting the relationship curves between elastic yield and fracturing fluid volume, and obtaining the fracturing stimulation coefficient; Step 3, establishing a numerical simulation model of a single-well calibration well, fitting the production dynamics of the calibration well, and determining the fracture length of the calibration well as the calibration fracture length; Step 4, establishing the correlation between the fracturing stimulation volume and the fracture length, fracture bandwidth, and fracture height; Step 5, calculating the fracture length of any shale gas well with the same geological conditions. While this patent constructs a numerical model of a single-well calibration well to predict fracture length, it is only applicable to shale reservoirs with the same geological conditions. Furthermore, it does not provide further analysis and quantification of fracture length, fracture bandwidth, and complexity under conditions of large principal stress differences.

[0007] CN105239984A discloses a method for controlling the propagation of hydraulic fracturing fractures in coal mines. The method includes: Step 1, drilling fracturing boreholes and several pressure-maintaining water injection boreholes, with the positions of the pressure-maintaining water injection boreholes arranged according to a pre-set hydraulic fracture propagation direction; Step 2, grouting and sealing the fracturing boreholes and pressure-maintaining water injection boreholes; Step 3, maintaining pressure and injecting water into the pressure-maintaining water injection boreholes according to the calculated water injection pressure and single-hole pressure-maintaining water injection time; Step 4, performing hydraulic fracturing on the fracturing boreholes. This patented method creates a high pore pressure region around the fracturing borehole, which can induce hydraulic fractures to propagate along the high pore pressure region, increasing the effective fracturing range. However, its application in fracturing non-coal rock under conditions of great burial depth and large principal stress differences is limited, and it cannot fundamentally improve the geostress environment, increase fracture bandwidth, or enhance the fracturing effect.

[0008] The patent disclosures above indicate that current research on predicting fracture parameters such as fracture width and length in hydraulic fracturing primarily focuses on theoretical models and numerical simulations. Even though numerous methods for predicting fracture parameters exist, research on improving and optimizing fracture width under complex geological conditions, such as large principal stress differences, is limited. Furthermore, there is a lack of experimental research on stress environment modification, fracture width improvement, and quantification under large principal stress differences.

[0009] The existing technologies described above are significantly different from the present invention and have failed to solve the technical problem we want to address. Therefore, we have invented a new physical model evaluation method to improve the fracture bandwidth of vertical wells with large principal stress differences. Summary of the Invention

[0010] The purpose of this invention is to provide a physical model evaluation method for improving the fracture bandwidth of vertical wells with large principal stress differences under conditions of large principal stress difference, thereby increasing the volume of the fracturing and the production capacity of a single well, and realizing the upgrading of ultra-deep tight reserves and effective regional utilization.

[0011] The objective of this invention can be achieved through the following technical measures: a physical model evaluation method for improving the fracture bandwidth in vertical wells with large principal stress differences, the physical model evaluation method for improving the fracture bandwidth in vertical wells with large principal stress differences includes:

[0012] Step 1: Measure the in-situ triaxial stress difference;

[0013] Step 2: Cast artificial rock samples, ensuring the triaxial compressive strength matches the on-site principal stress difference condition;

[0014] Step 3: Conduct fracturing model experiments under conventional large principal stress difference conditions;

[0015] Step 4: Conduct fracturing model experiments under pre-injected low-viscosity fluid conditions with large principal stress difference;

[0016] Step 5: Compare and verify the number of acoustic emission (AE) events monitored by the calibration model;

[0017] Step 6: Conduct fracturing model experiments with different pre-injection fluid volumes;

[0018] Step 7: Evaluation of the effect of pre-injected low-viscosity fluid on the bandwidth modification of fracturing fractures under conditions of large principal stress difference.

[0019] The objective of this invention can also be achieved through the following technical measures:

[0020] In step 1, the physical and mechanical parameters of the rock in the fractured section are compiled, including in-situ vertical stress, horizontal stress difference, XRD (X-ray diffraction), to obtain the content of tested minerals and determine the sand, mud, and lime content of the layer; triaxial tests are performed to obtain stress and strain curves and to obtain the triaxial compressive strength of the rock under in-situ loading conditions.

[0021] In step 2, based on the experimental results, a large-sized rock sample containing a vertical well shaft was cast. The pre-embedded sealing device was used for one-time casting. Large particles of sand were screened out using an 80-mesh sieve. The ratio of cement, sand and water in 32.5R composite silicate cement was adjusted to be consistent with the sand and mud content and triaxial compressive strength in step 1.

[0022] In step 2, mix the ingredients thoroughly according to a mass ratio of 1:2:0.5, and use a 300×300×300mm container. 3 The model is cast in a rigid plastic mold and cured for 28 days after demolding. Simulated well shafts are pre-embedded, and the size of the well shafts can be selected as long as they meet the similarity criteria. The well shafts are vertical, and the perforation positions are in the middle. The number of models is at least 6.

[0023] In step 3, experiments were conducted on at least three models. The fracturing fluid used was clean water, without pre-injection of low-viscosity fluid (i.e., slickwater). Direct fracturing was performed with a fixed horizontal stress difference of 20 MPa. The flow rates were calculated on-site to be 20, 40, 60, and 80 ml / min. The impact of the fracturing flow rate on the complexity of the fracture was tested. The fracturing curve and acoustic emission (AE) location event points were recorded.

[0024] In step 4, experiments were conducted on at least three models. To investigate the effect of pre-injection of low-viscosity fluid on fracture formation, the calculated flow rates of 20, 40, 60, and 80 ml / min were used. However, before fracturing, each sample was pre-injected with clean water at an ultra-low flow rate of 5 ml / min for 4 minutes, equivalent to an actual pre-injection of 105 m³ in the field. 3 Ensure there are no acoustic emission signals during the pre-low viscosity injection stage; continue fracturing and record the fracturing curve and acoustic emission (AE) location event points.

[0025] In step 5, compare the number of acoustic emission (AE) events monitored by the calibration model. Only if the number of AE events under the pre-injection low-viscosity condition is greater than the number of AE events under conventional fracturing, proceed to the next step; otherwise, verify the experimental conditions and repeat steps 3 and 4.

[0026] In step 6, keeping other parameters of the fracturing model constant, fracturing model experiments were conducted with different pre-injection volumes. Three samples were pre-injected with clean water for 1 min, 4 min, and 7 min, respectively, using an ultra-low flow rate of 5 ml / min, equivalent to an actual on-site pre-injection volume of 35 m³. 3 105m 3 and 210m 3The fluid volume was adjusted to ensure that there was no acoustic emission signal from the pre-injected low-viscosity fluid; then fracturing was continued at a fixed flow rate of 60 ml / min and a normalized fracture bandwidth of Fw.

[0027] In step 7, an evaluation of the effect of pre-injection of low-viscosity fluid on the bandwidth of fracturing under large principal stress difference conditions is formed, and a formula chart of fluid volume and normalized fracture bandwidth Fw is obtained, providing a basis for on-site discharge and pre-injection of low-viscosity fluid to solve the bandwidth control of fracturing under large principal stress difference conditions.

[0028] The objective of this invention can also be achieved through the following technical measures: a physical model evaluation system for improving the fracture bandwidth of vertical wells with large principal stress differences. This physical model evaluation system for improving the fracture bandwidth of vertical wells with large principal stress differences adopts a physical model evaluation method for improving the fracture bandwidth of vertical wells with large principal stress differences to form an evaluation of the modification effect of pre-injection of low viscosity fluid on the fracture bandwidth under conditions of large principal stress differences.

[0029] This invention presents a physical model evaluation method for enhancing fracture bandwidth in vertical wells with large principal stress differences. This method involves testing the rock's physical and mechanical parameters in the fracturing section to obtain the triaxial compressive strength of the rock under in-situ loading conditions. Large-size rock samples containing a vertical wellbore are prepared and cast. Physical model experiments are conducted under conventional and pre-injected low-viscosity fluid conditions with large principal stress differences. The effects of drilling displacement and fluid volume on fracture complexity are tested, and fracturing curves and acoustic emission (AE) location event points are recorded. An evaluation of the effect of pre-injected low-viscosity fluid on fracture bandwidth enhancement under large principal stress difference conditions is then established. This physical model evaluation method accurately assesses the potential for fracture sweep bandwidth and fracture complexity under large principal stress difference conditions, increasing the enhanced volume and single-well productivity. It enables the upgrading of ultra-deep tight reserves and effective regional utilization, providing a basis for controlling fracture bandwidth under large principal stress difference conditions through on-site drilling displacement and pre-injected low-viscosity fluid.

[0030] This invention provides a physical model optimization method for improving the fracture bandwidth in vertical wells with large principal stress differences. It evaluates the effect of pre-injection of low-viscosity fluid on the fracture bandwidth under conditions of large principal stress differences and derives a formula chart for fluid volume and normalized fracture bandwidth Fw. This provides a basis for controlling fracture bandwidth under large principal stress differences by adjusting the discharge rate and pre-injection of low-viscosity fluid in the field. Attached Figure Description

[0031] Figure 1 This is a flowchart illustrating a specific embodiment of the present invention: a physical model optimization method for improving the fracture bandwidth in vertical well fracturing with large principal stress differences.

[0032] Figure 2 This is a diagram showing the arrangement of the physical model sample and wellbore in a specific embodiment of the present invention;

[0033] Figure 3 This is a graph showing the total number of acoustic emission events under different displacements in a specific embodiment of the present invention, with and without pre-injection of low-viscosity fluid.

[0034] Figure 4 This is a schematic diagram of the bandwidth obtained from the acoustic emission event distribution in a fracturing model experiment with different pre-injection fluid volumes, as shown in a specific embodiment of the present invention.

[0035] Figure 5 This is a graph showing the relationship between different pre-injection fluid volumes and the normalized fracture bandwidth Fw in a specific embodiment of the present invention. Detailed Implementation

[0036] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0037] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0038] To address the development conditions of ultra-deep fracturing with large principal stress differences, based on fracturing models in vertical wells, a model optimization method for improving fracture bandwidth in vertical wells with large principal stress differences is developed, such as... Figure 1 As shown, Figure 1 This is a flowchart of the physical model evaluation method for improving the fracture bandwidth in vertical well fracturing with large principal stress differences, as per the present invention. The physical model optimization method for improving the fracture bandwidth in vertical well fracturing with large principal stress differences includes the following steps:

[0039] Step 101: Compile the physical and mechanical parameters of the rock in the fractured section, including in-situ vertical stress, horizontal stress difference, XRD (X-ray diffraction) to obtain the content of tested minerals, and determine the sand, mud, and lime content of the layer. Perform triaxial testing to obtain stress-strain curves and determine the triaxial compressive strength of the rock under in-situ loading conditions.

[0040] Step 102: Based on the experimental results, cast large-sized rock samples containing a vertical well casing. The samples are prepared according to... Figure 2 As shown, a one-time casting method with a pre-embedded sealing device is adopted. Large particles of sand are removed using an 80-mesh sieve. The ratio of cement, sand, and water in the 32.5R composite silicate cement is adjusted to match the sand and mud content and triaxial compressive strength of step 1. Here, the mixture is stirred evenly at a mass ratio of 1:2:0.5. A 300×300×300mm... 3The model is cast in a rigid plastic mold and cured for 28 days after demolding. A simulated well shaft is pre-embedded, and the size of the well shaft can be selected as long as it meets the similarity criteria. The well shaft is a vertical well, and the perforation position is in the middle. The number of models must be at least 6.

[0041] Step 103: Conduct fracturing model experiments under conventional large principal stress difference conditions. To eliminate data dispersion, at least three models should be tested. Use clean water as the fracturing fluid, without pre-injection of low-viscosity fluid (slippery water), and perform direct fracturing. Maintain a fixed horizontal stress difference of 20 MPa. Use field-calculated flow rates of 20, 40, 60, and 80 ml / min to test the impact of the fracturing flow rate on fracture complexity. Record the fracturing curves and acoustic emission (AE) location event points.

[0042] Step 104: Conduct fracturing model experiments under pre-injection of low-viscosity fluid and large principal stress difference. To eliminate data dispersion, at least three models should be tested. To investigate the effect of pre-injection of low-viscosity fluid on fracture creation, the same field-calculated flow rates of 20, 40, 60, and 80 ml / min are used. However, before fracturing, each sample is pre-injected with clean water at an ultra-low flow rate of 5 ml / min for 4 minutes, equivalent to an actual field pre-injection of 105 m³. 3 Ensure there are no acoustic emission signals during the pre-low viscosity injection stage. Continue fracturing and record the fracturing curves and acoustic emission (AE) location event points.

[0043] Step 105: Compare the number of acoustic emission (AE) events monitored by the calibration model. Only proceed to the next step if the number of AE events under pre-injection low-viscosity conditions is greater than the number of AE events under conventional fracturing. Otherwise, verify the experimental conditions and repeat steps 3 and 4. The number of AE events is as follows: Figure 3 As shown.

[0044] Step 106: Keeping other parameters of the fracturing model constant, conduct fracturing model experiments with different pre-injection volumes. Three samples are pre-injected with clean water for 1 min, 4 min, and 7 min respectively, using an ultra-low flow rate of 5 ml / min, equivalent to an actual on-site pre-injection volume of 35 m³. 3 105m 3 and 210m 3 The fluid volume was adjusted to ensure no acoustic emission signal was detected during the pre-injection of low-viscosity fluid. Fracturing was then continued at a fixed flow rate of 60 ml / min. The AE event distribution is as follows: Figure 4 As shown, the normalized bandwidth of the crack is Fw.

[0045] Step 107: Evaluate the effect of pre-injection of low-viscosity fluid on the bandwidth modification of fracturing under large principal stress difference conditions, and derive a formula chart for fluid volume and normalized fracture bandwidth Fw, providing a basis for on-site displacement and pre-injection of low-viscosity fluid to control fracture bandwidth under large principal stress difference conditions. For example... Figure 5 As shown.

[0046] The physical model evaluation method for improving fracture bandwidth in vertical wells with large principal stress differences, as proposed in this invention, is a physical model optimization method for improving fracture bandwidth in vertical wells with large principal stress differences. It is capable of quantitatively evaluating the influence of pre-filled low-viscosity fluid on fracture turning ability under large principal stress difference conditions, determining the correspondence between pre-filled fluid volume and fracture bandwidth, and is of great significance for increasing the complexity of fracturing fractures and the volume of fracturing.

[0047] The following are several specific embodiments of the application of the present invention.

[0048] Example 1:

[0049] In a specific embodiment 1 of the present invention, a physical model optimization method for improving the fracture bandwidth of a vertical well with a large principal stress difference includes:

[0050] Step 1: Compile the physical and mechanical parameters of the rock in the fractured section, including in-situ vertical stress, horizontal stress difference, and XRD (X-ray diffraction) to determine the content of tested minerals and the content of sand, mud, and lime in the layer. Perform triaxial testing to obtain stress-strain curves and determine the triaxial compressive strength of the rock under in-situ loading conditions of 20 MPa horizontal stress difference, which is 25 MPa.

[0051] Step 2: Based on the experimental results, cast large-sized rock samples containing a vertical well casing. The samples are prepared according to... Figure 2 As shown, a simulated well shaft is pre-embedded. The size of the well shaft can be selected as long as it meets the similarity criteria. A one-time casting method is adopted. The sand is screened with an 80-mesh sieve to remove large particles. The ratio of cement, sand, and water in the 32.5R composite silicate cement is adjusted to match the sand and mud ash content and triaxial compressive strength in step 1. Here, the mixture is stirred evenly at a mass ratio of 1:1.5:0.5. A 300×300×300mm... 3 It is cast in a rigid plastic mold and then demolded and cured for 28 days.

[0052] Step 3: Conduct fracturing model experiments under conventional large principal stress difference conditions. To eliminate data dispersion, at least three models should be tested. Use clean water as the fracturing fluid, without pre-injection of low-viscosity fluid (slippery water), and perform direct fracturing. Maintain a fixed horizontal stress difference of 20 MPa. Use field-calculated flow rates of 20, 40, 60, and 80 ml / min to test the impact of the fracturing flow rate on fracture complexity. Record the fracturing curves and acoustic emission (AE) location event points.

[0053] Step 4: Conduct fracturing model experiments under pre-injection of low-viscosity fluid and large principal stress difference. To eliminate data dispersion, at least three models should be tested. To investigate the effect of pre-injection of low-viscosity fluid on fracture creation, the same field-calculated flow rates of 20, 40, 60, and 80 ml / min are used. However, before fracturing, each sample is pre-injected with clean water at an ultra-low flow rate of 5 ml / min for 4 minutes, equivalent to an actual field pre-injection of 105 m³.3 Ensure there are no acoustic emission signals during the pre-low viscosity injection stage. Continue fracturing and record the fracturing curves and acoustic emission (AE) location event points.

[0054] Step 5: Compare the number of acoustic emission (AE) events monitored by the calibration model. Only if the number of AE events under the pre-injection low-viscosity condition is greater than the number of AE events under conventional fracturing, proceed to the next step. Otherwise, verify the experimental conditions and repeat steps 3 and 4.

[0055] Step 6: Keeping other parameters of the fracturing model constant, conduct fracturing model experiments with different pre-injection volumes. Three samples are pre-injected with clean water for 1 min, 4 min, and 7 min respectively, using an ultra-low flow rate of 5 ml / min, equivalent to an actual on-site pre-injection volume of 35 m³. 3 105m 3 and 210m 3 The fluid volume was adjusted to ensure no acoustic emission signal was detected during the pre-injection of low-viscosity fluid. Fracturing was then continued at a fixed flow rate of 60 ml / min. The AE event distribution is as follows: Figure 4 As shown, the normalized bandwidth of the crack is Fw.

[0056] Step 7: Evaluate the effect of pre-injection of low-viscosity fluid on fracture bandwidth modification under large principal stress difference conditions, and derive a formula chart for fluid volume versus normalized fracture bandwidth Fw. This provides a basis for on-site displacement and pre-injection of low-viscosity fluid to control fracture bandwidth under large principal stress difference conditions. Finally, a pre-injection depth of 105m is selected. 3 16m 3 / min, with a bandwidth of 80m.

[0057] Example 2:

[0058] In a specific embodiment 1 of the present invention, a physical model optimization method for improving the fracture bandwidth of a vertical well with a large principal stress difference includes:

[0059] Step 1: Compile the physical and mechanical parameters of the rock in the fractured section, including in-situ vertical stress, horizontal stress difference, and XRD (X-ray diffraction) to determine the content of tested minerals and the content of sand, mud, and lime in the layer. Perform triaxial testing to obtain stress-strain curves, and determine the triaxial compressive strength of the rock under in-situ loading conditions of 15 MPa horizontal stress difference as 23 MPa.

[0060] Step 2: Based on the experimental results, cast large-sized rock samples containing a vertical well casing. The samples are prepared according to... Figure 2As shown, a pre-embedded simulated well shaft is used. The size of the well shaft can be selected as long as it meets the similarity criteria. A one-time casting method is adopted. The sand is screened with an 80-mesh sieve to remove large particles. The ratio of cement, sand, and water in the 32.5R composite silicate cement is adjusted to match the sand and mud ash content and triaxial compressive strength in step 1. Here, the mixture is stirred evenly at a mass ratio of 1:2:0.5. A 300×300×300mm... 3 It is cast in a rigid plastic mold and then demolded and cured for 28 days.

[0061] Step 3: Conduct fracturing model experiments under conventional large principal stress difference conditions. To eliminate data dispersion, at least three models should be tested. Use clean water as the fracturing fluid, without pre-injection of low-viscosity fluid (slippery water), and perform direct fracturing. Maintain a fixed horizontal stress difference of 15 MPa. Use field-calculated flow rates of 20, 40, 60, and 80 ml / min to test the impact of the fracturing flow rate on fracture complexity. Record the fracturing curves and acoustic emission (AE) location event points.

[0062] Step 4: Conduct fracturing model experiments under pre-injection of low-viscosity fluid and large principal stress difference. To eliminate data dispersion, at least three models should be tested. To investigate the effect of pre-injection of low-viscosity fluid on fracture creation, the same field-calculated flow rates of 20, 40, 60, and 80 ml / min are used. However, before fracturing, each sample is pre-injected with clean water at an ultra-low flow rate of 5 ml / min for 4 minutes, equivalent to an actual field pre-injection of 105 m³. 3 Ensure there are no acoustic emission signals during the pre-low viscosity injection stage. Continue fracturing and record the fracturing curves and acoustic emission (AE) location event points.

[0063] Step 5: Compare the number of acoustic emission (AE) events monitored by the calibration model. Only if the number of AE events under the pre-injection low-viscosity condition is greater than the number of AE events under conventional fracturing, proceed to the next step. Otherwise, verify the experimental conditions and repeat steps 3 and 4.

[0064] Step 6: Keeping other parameters of the fracturing model constant, conduct fracturing model experiments with different pre-injection volumes. Three samples are pre-injected with clean water for 1 min, 4 min, and 7 min respectively, using an ultra-low flow rate of 5 ml / min, equivalent to an actual on-site pre-injection volume of 35 m³. 3 105m 3 and 210m 3 The fluid volume was adjusted to ensure no acoustic emission signal was detected during the pre-injection of low-viscosity fluid. Fracturing was then continued at a fixed flow rate of 40 ml / min. The AE event distribution is as follows: Figure 4 As shown, the normalized bandwidth of the crack is Fw.

[0065] Step 7: Evaluate the effect of pre-injection of low-viscosity fluid on fracture bandwidth modification under large principal stress difference conditions, and derive a formula chart for fluid volume versus normalized fracture bandwidth Fw. This provides a basis for on-site displacement and pre-injection of low-viscosity fluid to control fracture bandwidth under large principal stress difference conditions. Finally, a pre-injection depth of 35m is selected. 3 11m 3 / min, with a bandwidth of 85m.

[0066] Example 3:

[0067] In a specific embodiment 1 of the present invention, a physical model optimization method for improving the fracture bandwidth of a vertical well with a large principal stress difference includes:

[0068] Step 1: Compile the physical and mechanical parameters of the rock in the fractured section, including in-situ vertical stress, horizontal stress difference, and XRD (X-ray diffraction) to determine the content of tested minerals and the content of sand, mud, and lime in the layer. Perform triaxial testing to obtain stress-strain curves and determine the triaxial compressive strength of the rock under in-situ loading conditions of 30 MPa with a horizontal stress difference of 25 MPa.

[0069] Step 2: Based on the experimental results, cast large-sized rock samples containing a vertical well casing. The samples are prepared according to... Figure 2 As shown, a simulated well shaft is pre-embedded. The size of the well shaft can be selected as long as it meets the similarity criteria. A one-time casting method is adopted. The sand is screened with an 80-mesh sieve to remove large particles. The ratio of cement, sand, and water in 32.5R composite silicate cement is adjusted to match the sand and mud ash content and triaxial compressive strength in step 1. Here, the mixture is stirred evenly at a mass ratio of 1:1:0.5. A 300×300×300mm... 3 It is cast in a rigid plastic mold and then demolded and cured for 28 days.

[0070] Step 3: Conduct fracturing model experiments under conventional large principal stress difference conditions. To eliminate data dispersion, at least three models should be tested. Use clean water as the fracturing fluid, without pre-injection of low-viscosity fluid (slippery water), and perform direct fracturing. Maintain a fixed horizontal stress difference of 25 MPa. Use field-calculated flow rates of 20, 40, 60, and 80 ml / min to test the impact of the fracturing flow rate on fracture complexity. Record the fracturing curves and acoustic emission (AE) location event points.

[0071] Step 4: Conduct fracturing model experiments under pre-injection of low-viscosity fluid and large principal stress difference. To eliminate data dispersion, at least three models should be tested. To investigate the effect of pre-injection of low-viscosity fluid on fracture creation, the same field-calculated flow rates of 20, 40, 60, and 80 ml / min are used. However, before fracturing, each sample is pre-injected with clean water at an ultra-low flow rate of 5 ml / min for 4 minutes, equivalent to an actual field pre-injection of 105 m³. 3Ensure there are no acoustic emission signals during the pre-low viscosity injection stage. Continue fracturing and record the fracturing curves and acoustic emission (AE) location event points.

[0072] Step 5: Compare the number of acoustic emission (AE) events monitored by the calibration model. Only proceed to the next step if the number of AE events under pre-injection low-viscosity conditions is greater than the number of AE events under conventional fracturing. Otherwise, verify the experimental conditions and repeat steps 3 and 4. The number of AE events is as follows: Figure 3 As shown.

[0073] Step 6: Keeping other parameters of the fracturing model constant, conduct fracturing model experiments with different pre-injection volumes. Three samples are pre-injected with clean water for 1 min, 4 min, and 7 min respectively, using an ultra-low flow rate of 5 ml / min, equivalent to an actual on-site pre-injection volume of 35 m³. 3 105m 3 and 210m 3 The fluid volume was adjusted to ensure no acoustic emission signal was detected during the pre-injection of low-viscosity fluid. Fracturing was then continued at a fixed flow rate of 80 ml / min. The AE event distribution is as follows: Figure 4 As shown, the normalized bandwidth of the crack is Fw.

[0074] Step 7: Evaluate the effect of pre-injection of low-viscosity fluid on fracture bandwidth modification under large principal stress difference conditions, and derive a formula chart for fluid volume versus normalized fracture bandwidth Fw. This provides a basis for on-site displacement and pre-injection of low-viscosity fluid to control fracture bandwidth under large principal stress difference conditions. Finally, a pre-injection depth of 210m is selected. 3 20m 3 / min, with a bandwidth of 78m.

[0075] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0076] Except for the technical features described in the specification, all other technologies are known to those skilled in the art.

Claims

1. A physical model evaluation method for improving fracture bandwidth in vertical wells with large principal stress differences, characterized in that, The physical model evaluation method for improving the fracture bandwidth in vertical well fracturing with large principal stress difference includes: Step 1: Measure the in-situ triaxial stress difference; Step 2: Cast artificial rock samples, ensuring the triaxial compressive strength matches the on-site principal stress difference condition; Step 3: Conduct fracturing model experiments under conventional large principal stress difference conditions; Step 4: Conduct fracturing model experiments under pre-injected low-viscosity fluid conditions with large principal stress difference; Step 5: Compare and verify the number of acoustic emission (AE) events monitored by the calibration model; Step 6: Conduct fracturing model experiments with different pre-injection fluid volumes; Step 7: Evaluation of the effect of pre-injected low-viscosity fluid on the bandwidth modification of fracturing fractures under conditions of large principal stress difference.

2. The physical model evaluation method for improving the fracture bandwidth of vertical well fracturing with large principal stress difference according to claim 1, characterized in that, In step 1, the rock physical and mechanical parameters of the fractured section are sorted out, including in-situ vertical stress, horizontal stress difference, XRD (X-ray diffraction), to obtain the test mineral content and determine the sand, mud and lime content of the layer. Triaxial tests were conducted to obtain stress-strain curves and determine the triaxial compressive strength of the rock under in-situ loading conditions.

3. The physical model evaluation method for improving the fracture bandwidth of vertical well fracturing with large principal stress difference according to claim 1, characterized in that, In step 2, based on the experimental results, a large-sized rock sample containing a vertical well shaft was cast. The pre-embedded sealing device was used for one-time casting. Large particles of sand were screened out using an 80-mesh sieve. The ratio of cement, sand and water in 32.5R composite silicate cement was adjusted to be consistent with the sand and mud content and triaxial compressive strength in step 1.

4. The physical model evaluation method for improving the fracture bandwidth of vertical well fracturing with large principal stress difference according to claim 3, characterized in that, In step 2, mix the ingredients thoroughly according to a mass ratio of 1:2:0.5, and use a 300×300×300mm container. 3 The model is cast in a rigid plastic mold and cured for 28 days after demolding. A simulated well shaft is pre-embedded, and the size of the well shaft can be selected as long as it meets the similarity criteria. The well shaft is a straight well, and the perforation position is in the middle. The number of models is at least 6.

5. The physical model evaluation method for improving the fracture bandwidth of vertical well fracturing with large principal stress difference according to claim 1, characterized in that, In step 3, experiments were conducted on at least three models. The fracturing fluid used was clean water, without pre-injection of low-viscosity fluid (i.e., slickwater). Direct fracturing was performed with a fixed horizontal stress difference of 20 MPa. The flow rates were calculated on-site to be 20, 40, 60, and 80 ml / min. The impact of the fracturing flow rate on the complexity of the fracture was tested. The fracturing curve and acoustic emission (AE) location event points were recorded.

6. The physical model evaluation method for improving the fracture bandwidth of vertical well fracturing with large principal stress difference according to claim 1, characterized in that, In step 4, experiments were conducted on at least three models. To investigate the effect of pre-injection of low-viscosity fluid on fracture formation, the calculated flow rates of 20, 40, 60, and 80 ml / min were used. However, before fracturing, each sample was pre-injected with clean water at an ultra-low flow rate of 5 ml / min for 4 minutes, equivalent to an actual pre-injection of 105 m³ in the field. 3 Ensure there are no acoustic emission signals during the pre-low viscosity injection stage; continue fracturing and record the fracturing curve and acoustic emission (AE) location event points.

7. The physical model evaluation method for improving the fracture bandwidth of vertical well fracturing with large principal stress difference according to claim 1, characterized in that, In step 5, compare the number of acoustic emission (AE) events monitored by the calibration model. Only if the number of AE events under the pre-injection low-viscosity condition is greater than the number of AE events under conventional fracturing, proceed to the next step; otherwise, verify the experimental conditions and repeat steps 3 and 4.

8. The physical model evaluation method for improving the fracture bandwidth of vertical well fracturing with large principal stress difference according to claim 1, characterized in that, In step 6, keeping other parameters of the fracturing model constant, fracturing model experiments were conducted with different pre-injection volumes. Three samples were pre-injected with clean water for 1 min, 4 min, and 7 min, respectively, using an ultra-low flow rate of 5 ml / min, equivalent to an actual on-site pre-injection volume of 35 m³. 3 105m 3 and 210m 3 The fluid volume was adjusted to ensure that there was no acoustic emission signal from the pre-injected low-viscosity fluid; then fracturing was continued at a fixed flow rate of 60 ml / min and a normalized fracture bandwidth of Fw.

9. The physical model evaluation method for improving the fracture bandwidth of vertical well fracturing with large principal stress difference according to claim 1, characterized in that, In step 7, an evaluation of the effect of pre-injection of low-viscosity fluid on the bandwidth of fracturing under large principal stress difference conditions is formed, and a formula chart of fluid volume and normalized fracture bandwidth Fw is obtained, providing a basis for on-site discharge and pre-injection of low-viscosity fluid to solve the bandwidth control of fracturing under large principal stress difference conditions.

10. A physical model evaluation system for improving fracture bandwidth in vertical wells with large principal stress differences, characterized in that: The physical model evaluation system for improving the fracture bandwidth of vertical wells with large principal stress difference adopts the physical model evaluation method for improving the fracture bandwidth of vertical wells with large principal stress difference as described in any one of claims 1-9 to evaluate the effect of pre-injection of low viscosity fluid on the fracture bandwidth of fracturing under large principal stress difference conditions.

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