A method for evaluating the complexity of hydraulic fracture networks based on microseismicity

Abstract

The present invention discloses a method for evaluating the complexity of hydraulic fracture networks based on microseismicity, belonging to the technical field of oil and gas reservoir development. The method includes the following steps: collecting a number of microseismic event points in a target fractured well through a microseismic monitoring method and obtaining the monitoring data of the microseismic event points; drawing a scatter plot of the magnitudes of the event points based on the set of microseismic event points and determining the critical magnitude; based on the critical magnitude, dividing the microseismic event points into stress relaxation event points and microfracture network event points; obtaining the total standardized energy value of the stress relaxation event points and the total standardized energy value of the microseismic event points; calculating the complexity of the hydraulic fracture network of the target fractured well; The present application takes into account the influence of stress relaxation phenomena in natural fractures on the complexity of hydraulic fracture networks, can effectively reflect the relative strength of stress relaxation phenomena generated in the evaluation object during fracturing, and reflects the complexity of the artificial fracture network.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas reservoir development, and more specifically, to a method for evaluating the complexity of hydraulic fracture networks based on microseismic. Background Art

[0002] For shale gas, tight gas, etc., it is usually necessary to drill horizontal wells and combine hydraulic fracturing to artificially create reservoirs in the reservoir for industrial exploitation; the microseismic monitoring technology is a technical means for monitoring the morphology of hydraulic fracture networks after hydraulic fracturing, and can real-time monitor the spatial morphology of the fracture network generated during fracturing; when fractures are generated due to formation rupture, elastic waves will be released; by deploying an observation system near the reservoir, collecting elastic wave signals, and using geophysical methods, the formation rupture position can be effectively located, and further analyze the reservoir characteristics after fracturing.

[0003] A complex hydraulic fracture network can significantly improve the permeability around the wellbore and in the far-well zone, which helps to increase the single-well production; therefore, quantitatively evaluating the complexity of the hydraulic fracture network is of great significance for evaluating the reservoir stimulation effect of shale gas and tight gas.

[0004] The influence of natural fractures in horizontal wells on the fracturing effect mainly exists in two aspects; on the one hand, natural fractures are an important guarantee for the enrichment and high production of shale gas. Natural fractures can provide migration channels and accumulation spaces for natural gas and formation water, and are conducive to increasing the total gas content of the shale gas reservoir; on the other hand, stress relaxation often occurs in areas with developed natural fractures. The artificial fractures formed by fracturing transition to natural fractures through the stress relaxation zone. After the stress relaxation zone absorbs the fracturing energy, it is prone to elastic deformation, which will affect the formation of a complex fracture network. Therefore, natural fractures have both positive and negative effects on the fracturing effect. Natural fractures densely distributed on a smaller scale are conducive to increasing the complexity of the hydraulic fracture network; while strip-shaped, larger-scale or large-scale developed natural fractures absorb the fracturing energy during fracturing, resulting in poor stimulation effects.

[0005] The invention patent with the application number CN202210757370.4 discloses a method for evaluating the fracturing effect of shale oil wells based on collaborative training, which can evaluate the fracturing effect through block production data acquisition and prediction models; the invention patent with the application number CN202010189682.0 discloses a method for predicting the complexity of the fracture network formed by shale fracturing, which mainly predicts the complexity of the fracture network by analyzing the brittle mineral content and the number of natural fractures; currently, the evaluation methods for the fracturing stimulation effect of horizontal wells in related technologies lack consideration of the relationship between the stress relaxation factor in natural fractures and the artificial fracture network formed by fracturing, and cannot effectively quantitatively evaluate the complexity of the fracture network generated by fracturing. Summary of the Invention

[0006] The object of the present invention is to solve the technical problem that the complexity of the fracture network generated by fracturing cannot be effectively and quantitatively evaluated in the related fracture network evaluation methods, and a method for evaluating the complexity of a fracture network based on microseismic is proposed.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] A method for evaluating the complexity of a fracture network based on microseismic, the method comprising the following steps:

[0009] S1: Collect a number of microseismic event points in the target fracturing well by microseismic monitoring method, obtain the monitoring data of the microseismic event points, and establish a microseismic event point set;

[0010] S2: Draw a scatter plot of the magnitudes of the event points according to the microseismic event point set, and determine the critical magnitude Mc according to the scatter distribution characteristics of the scatter plot of the magnitudes of the event points;

[0011] S3: Based on the critical magnitude Mc, divide the microseismic event points in the microseismic event point set into stress relaxation event points and microfracture network event points;

[0012] S4: Calculate the energy value q corresponding to the magnitude of each microseismic event point according to the energy relationship calculation formula;

[0013] S5: Standardize the energy value q by using the standardization calculation formula, and calculate the standardized energy value s of each microseismic event point;

[0014] S6: Calculate the total standardized energy value Sr of the stress relaxation event points and the total standardized energy value S of the microseismic event points;

[0015] S7: Calculate the complexity Φ of the fracture network of the target fracturing well by using the artificial fracture complexity evaluation calculation formula.

[0016] Further, in the step S1, the monitoring data of the microseismic event points at least includes: the fracturing stage to which the microseismic event point belongs, and magnitude information.

[0017] Further, in the step S4, the analysis and processing of the monitoring data of the microseismic event points includes:

[0018] S401: Calculate the energy value q corresponding to the magnitude of each microseismic event point according to the energy relationship calculation formula;

[0019] S402: Standardize the energy value q by using the standardization calculation formula, and calculate the standardized energy value s of each microseismic event point.

[0020] Further, in the step S401, the energy relation calculation formula is as follows: q = 10 （1.5M+4.8） ;

[0021] where q is the response energy of the microseismic event point, with the unit of joule; M is the magnitude in the original microseismic data.

[0022] Further, in the step S402, the normalization calculation formula is as follows: s = [(q - μ) / σ] + 1;

[0023] where μ is the average value of the energy value q of the microseismic event points of each fracturing well; σ is the standard deviation of the energy value q of the microseismic event points of each fracturing well.

[0024] Further, in the step S5, the evaluation calculation formula for the complexity of the artificial fracture is as follows: the complexity of the artificial fracture Φ = [1 - (Sr / S)] × {[(P / P0) + (F / F0) + (C / C0)] / 3} × 100%;

[0025] where P is the average sand addition intensity of the target fracturing well; P0 is the highest average sand addition intensity of the wells in the well area where the target fracturing well is located, F is the average fluid consumption intensity of the target fracturing well, F0 is the highest average fluid consumption intensity of the wells in the well area where the target fracturing well is located, C is the average proportion of ceramsite in the target fracturing well, and C0 is the highest average proportion of ceramsite in the well area where the target fracturing well is located.

[0026] Further, according to the complexity Φ of the fracture network, the evaluation results for evaluating the complexity of the artificial fracture and the fracturing effect are obtained, including:

[0027] When the complexity Φ of the fracture network is less than the first threshold, it is determined that the evaluation result of the complexity of the artificial fracture of the target fracturing well is extremely simple, and the evaluation result of the fracturing effect is extremely poor;

[0028] When the complexity Φ of the fracture network is greater than or equal to the first threshold and less than the second threshold, it is determined that the evaluation result of the complexity of the artificial fracture of the target fracturing well is relatively simple, and the evaluation result of the fracturing effect is poor;

[0029] When the complexity Φ of the fracture network is greater than or equal to the second threshold and less than the third threshold, it is determined that the evaluation result of the complexity of the artificial fracture of the target fracturing well is general, and the evaluation result of the fracturing effect is general;

[0030] When the complexity Φ of the fracture network is greater than or equal to the third threshold and less than the fourth threshold, it is determined that the evaluation result of the complexity of the artificial fracture of the target fracturing well is relatively complex, and the evaluation result of the fracturing effect is relatively good;

[0031] When the complexity Φ of the hydraulic fracture network is greater than or equal to the fourth threshold, it is determined that the evaluation result of the complexity of the artificial hydraulic fractures in the target fractured well is complex, and the evaluation result of the fracturing effect is good.

[0032] The beneficial effects of the present invention are as follows:

[0033] The method for evaluating the complexity of a hydraulic fracture network based on microseismicity provided by the present application can effectively, intuitively, and accurately reflect the relative strength of the stress relaxation phenomenon generated during fracturing of the evaluation object by considering the influence of the stress relaxation phenomenon in natural fractures on the complexity of the hydraulic fracture network, and calculate the proportion of the total normalized energy value of stress relaxation event points in the total normalized energy value of all microseismic event points, thereby reflecting the complexity of the artificial fracture network. Description of the Drawings

[0034] Figure 1 It is a schematic flow chart of a method for evaluating the complexity of a hydraulic fracture network based on microseismicity provided by an embodiment of the present invention;

[0035] Figure 2 It is a scatter plot of the magnitudes of event points of Well Z1 in Embodiment 1 of the present invention;

[0036] Figure 3 It is a comparison chart of the sum of the normalized energy values corresponding to the stress relaxation event points of each fracturing stage of Well Z1 and the sum of the normalized energy values of the microseismic event points in Embodiment 1 of the present invention;

[0037] Figure 4 It is a bar chart of the calculation results of the complexity of the artificial fractures of each fracturing stage of Well Z1 in Embodiment 1 of the present invention;

[0038] Figure 5 It is a scatter plot of the magnitudes of event points of Well Z2 in Embodiment 2 of the present invention. Detailed Embodiments

[0039] In the field of oil and gas fields, the permeability of unconventional oil and gas reservoir formations is extremely low, and the natural production capacity is extremely low or there is no natural production capacity. Only by large-scale volume fracturing can production be increased. The complexity of the hydraulic fracture network directly affects the production capacity of the oil and gas field. Because the complexity of the fracture network determines the path and efficiency of the flow of oil and gas from the reservoir to the wellbore; a complex and effective fracture network can increase the fluid flow channels in the reservoir, thereby improving the fluidity of oil and gas and significantly increasing the oil and gas recovery rate. The purpose of evaluating the complexity of the hydraulic fracture network is to evaluate the fracturing effect and provide a reference for optimizing the technical policies for oil and gas field development.

[0040] s Embodiment 1: Refer to Figure 1As shown in the figure, the present invention provides a method for evaluating the complexity of the fracture network based on microseismicity. In practical applications, this method is used to evaluate the fracturing effect and the complexity of the fracture network of different fracturing sections in the same fracturing well, so as to reflect the improvement effect of the fracturing technology on the single-well production. The method mainly includes the following steps:

[0041] S1: Collect a number of microseismic event points in the target fracturing well through the microseismic monitoring method, obtain the monitoring data of the microseismic event points, and establish a set of microseismic event points.

[0042] In step S1, after the horizontal well is hydraulically fractured to form a fracture network, elastic wave data generated by rock fracture is collected through the microseismic monitoring method; a number of elastic waves in the elastic wave data are respectively located, so as to obtain a number of microseismic event points in the target fracturing well and the monitoring data of each microseismic event point, and establish a set of microseismic event points of the target fracturing well;

[0043] Among them, the monitoring data of the microseismic event points at least includes: the fracturing section to which the microseismic event point belongs, and magnitude information.

[0044] S2: Draw a scatter plot of the magnitudes of the event points according to the set of microseismic event points, and determine the critical magnitude Mc according to the scatter distribution characteristics of the scatter plot of the magnitudes of the event points;

[0045] In step S2, the vertical axis of the scatter plot of the magnitudes of the event points is the magnitude, and the magnitude of each microseismic event point corresponds to the magnitude on the vertical axis of the scatter plot of the magnitudes of the event points, and each microseismic event point is randomly arranged in the horizontal axis direction; the purpose of adopting this technical solution is to weaken the association between the fracturing section attribute and the magnitude attribute of the microseismic event points in the single well in the scatter plot of the magnitudes of the event points, highlight the distribution characteristics of all microseismic event points in the single well in different magnitude intervals, and avoid the distribution of microseismic event points on the scatter plot of the magnitudes being too dense or scattered, making it difficult to identify their distribution characteristics;

[0046] Based on the three-segment distribution characteristics of the scatter points in the scatter plot of the magnitudes of the event points, the scatter plot of the magnitudes of the event points can be divided into three major sections from large to small magnitudes. The three major sections are: the large-scale natural fracture response section, the relatively large-scale natural fracture response section, and the fine natural fracture + artificial fracture section; and the demarcation magnitude between the fine natural fracture + artificial fracture section and the relatively large natural fracture section is used as the critical magnitude Mc. It should be noted that when technicians in the field delimit the critical magnitude Mc according to the scatter distribution characteristics of the scatter plot of the magnitudes of the event points, the difference between the critical magnitudes Mc obtained by different technicians should not exceed 0.1 magnitude.

[0047] S3: Based on the critical magnitude Mc, divide the microseismic event points in the set of microseismic event points into stress relaxation event points and microfracture network event points;

[0048] It should be noted that due to the stress relaxation phenomenon often existing in the fracturing of large-scale natural fractures and relatively large-scale natural fractures, the above natural fractures provide a larger energy release space for microseismic events, resulting in more intense microseismic events monitored in the area where natural fractures develop; while the microfracture network is mainly composed of artificial fractures in the fracturing, including a small number of micro natural fractures, which are mainly caused by artificial fracturing, and the microseismic events monitored in its area are more gentle; therefore, it is possible to judge whether stress relaxation occurs in the fractures where the microseismic event points are located and whether a microfracture network is formed based on the magnitude of the microseismic event points, and then judge the complexity of the artificial fracture network in the target fracturing well;

[0049] In step S3, the microseismic event points within the response sections of large-scale natural fractures and relatively large-scale natural fractures (magnitude ≥ critical magnitude Mc) are classified as stress relaxation event points, and the microseismic event points within the section of micro natural fractures + artificial fracturing fractures (magnitude < critical magnitude Mc) are classified as microfracture network event points.

[0050] S4: Analyze and process the monitoring data of the microseismic event points to obtain the total standardized energy value Sr of the stress relaxation event points in the target fracturing section and the total standardized energy value S of the microseismic event points in the target fracturing section;

[0051] In order to quantitatively evaluate the complexity of the fracture network numerically rather than making a judgment on the complexity of the fracture network based on the number of stress relaxation event points vaguely, in step S4, the analysis and processing of the monitoring data of the microseismic event points include: S401: Calculate the energy value q corresponding to the magnitude of the microseismic event points in the target fracturing section by using the energy relationship calculation formula;

[0052] In this step, the energy relationship calculation formula can adopt the Richter magnitude-energy relationship calculation formula, and the energy relationship calculation formula is as follows: q = 10 （1.5M+4.8） ;

[0053] where q is the response energy of the microseismic event point, with the unit of joule; M is the magnitude in the original microseismic data, generally distributed from -3 to 3, dimensionless;

[0054] S402: Standardize the energy value q by using the standardization calculation formula to calculate the standardized energy value s of the microseismic event points in the target fracturing section;

[0055] S403: Add up the normalized energy values s of the microseismic event points classified as stress relaxation event points within the target fracturing stage to obtain the total normalized energy value Sr of the stress relaxation event points within the target fracturing stage; add up the normalized energy values s of all microseismic event points within the target fracturing stage to obtain the total normalized energy value S of the microseismic event points within the target fracturing stage.

[0056] Since the energy values q corresponding to the microseismic event points have a large difference in magnitude, it is difficult to reflect the characteristics of the microseismic event points corresponding to the magnitude. Therefore, the energy value q is normalized to obtain the normalized energy value s of each microseismic event point, which can more intuitively reflect the energy of the event point and is also convenient for further processing.

[0057] In this step, the normalization calculation formula is as follows: s = [(q - μ) / σ] + 1;

[0058] where μ is the average value of the energy values q of the microseismic event points of each fracturing well; σ is the standard deviation of the energy values q of the microseismic event points of each fracturing well.

[0059] S5: Use the evaluation calculation formula for the complexity of the artificial fracture to calculate and obtain the complexity Φ of the fracture network of the target fracturing stage;

[0060] In step S5: The evaluation calculation formula for the complexity of the artificial fracture is as follows: the complexity of the artificial fracture Φ = [1 - (Sr / S)] × {[(P / P0) + (F / F0) + (C / C0)] / 3} × 100%;

[0061] where P is the average sand addition intensity of the target fracturing well during fracturing; P0 is the highest average sand addition intensity of the wells in the well area where the target fracturing well is located, F is the average liquid usage intensity of the target fracturing well during fracturing, F0 is the highest average liquid usage intensity of the wells in the well area where the target fracturing well is located, C is the average proportion of ceramsite in the target fracturing well during fracturing, and C0 is the highest average proportion of ceramsite in the wells in the well area where the target fracturing well is located.

[0062] As an implementation manner of the present application, when there is no suitable highest average sand addition intensity of the well in the well area where the target fracturing well is located for reference (for example: there is only a single well group of the target fracturing well in the well area where the target fracturing well is located, at this time, the value of "P / P0" in the formula is always 1), P0 in the formula can be determined as the highest sand addition intensity of the wells in the adjacent area.

[0063] According to the complexity Φ of the fracture network obtained in step S5, obtain the evaluation result for evaluating the complexity of the artificial fracture and the fracturing effect of the fracturing, including:

[0064] When the complexity Φ of the fracture network is less than the first threshold, it is determined that the evaluation result of the complexity of the artificial fracture of the target fracturing well is extremely simple, and the evaluation result of the fracturing effect is extremely poor;

[0065] When the complexity Φ of the fracture network is greater than or equal to the first threshold and less than the second threshold, it is determined that the evaluation result of the complexity of the artificial fracture in the target fractured well is relatively simple, and the evaluation result of the fracturing effect is poor;

[0066] When the complexity Φ of the fracture network is greater than or equal to the second threshold and less than the third threshold, it is determined that the evaluation result of the complexity of the artificial fracture in the target fractured well is average, and the evaluation result of the fracturing effect is average;

[0067] When the complexity Φ of the fracture network is greater than or equal to the third threshold and less than the fourth threshold, it is determined that the evaluation result of the complexity of the artificial fracture in the target fractured well is relatively complex, and the evaluation result of the fracturing effect is relatively good;

[0068] When the complexity Φ of the fracture network is greater than or equal to the fourth threshold, it is determined that the evaluation result of the complexity of the artificial fracture in the target fractured well is complex, and the evaluation result of the fracturing effect is good.

[0069] The present application provides a method for evaluating the complexity of a fracture network based on microseismicity. By calculating the proportion of the total normalized energy value of stress relaxation event points in the total normalized energy value of all microseismic event points, this proportion can effectively, intuitively, and accurately reflect the relative strength of the stress relaxation phenomenon generated by the evaluation object during fracturing, thereby reflecting the complexity of the artificial fracture network. The stronger the stress relaxation phenomenon generated, the weaker the complexity of the fracturing artificial fracture network, and vice versa, the stronger the complexity of the fracturing artificial fracture network, and the better the fracturing effect.

[0070] The evaluation method of the present application also provides a calculation formula for the complexity of the fracture network. Combining the sand addition intensity, liquid usage intensity, and ceramsite proportion of the evaluation object, the complexity of the fracture network of each evaluation object can be calculated to quantitatively evaluate the complexity of the fracture network.

[0071] Based on the above calculation formula for the complexity of the fracture network, this evaluation method also provides an evaluation standard for the complexity of the fracture network, which divides the complexity of the fracture network into several levels, can intuitively evaluate the complexity of the fracture network of each fracturing stage of the same horizontal well, and can also achieve inter-well comparison of the complexity of the fracture network of different wells.

[0072] In this embodiment, taking the microseismic monitoring data of each fracturing stage of Well Z1 as the analysis object, the fracturing stage (Stage) and the corresponding magnitude of all event points of Well Z1 are sorted out, and a microseismic event point set of Well Z1 is established, as shown in Table 1 below (Original analysis data table for comparing the complexity evaluation of the fracture network of different fracturing stages of Well Z1);

[0073] ,

[0074] Table 1

[0075] Please refer to Figure 2 , according to the monitoring data of all microseismic event points in the microseismic event point set of the Z1 fracturing well, draw a scatter plot of the magnitudes of the event points, as Figure 2 shown in (Scatter plot of the magnitudes of the microseismic event points in the Z1 fracturing well). Among them, the magnitude of the microseismic event points in the Z1 fracturing well corresponds to the magnitude on the vertical axis of the scatter plot of magnitudes, and each microseismic event point in the Z1 fracturing well is randomly arranged in the horizontal axis direction;

[0076] According to the scatter distribution characteristics of the scatter plot of the magnitudes of the microseismic event points in the Z1 fracturing well, the fractures reflected by the microseismic event points are divided into large-scale natural fracture response segments, relatively large-scale natural fracture response segments, and fine natural fracture + fracturing artificial fracture segments, and the demarcation magnitude between the fine natural fracture + fracturing artificial fracture segment and the relatively large natural fracture segment is used as the critical magnitude Mc; in this example, the critical magnitude Mc of the Z1 fracturing well is -1.0.

[0077] All microseismic event points in each fracturing stage of the Z1 fracturing well are divided into stress relaxation event points (magnitude ≥ critical magnitude Mc) and fine fracture network event points (magnitude < critical magnitude Mc) based on the critical magnitude Mc, and the sorting results are shown in Table 2 (Classification table of microseismic event points in different fracturing stages of the Z1 fracturing well) as follows;

[0078] ,

[0079] Table 2

[0080] According to the energy relationship calculation formula: q = 10 （1.5M+4.8） Calculate and sort out the energy values q corresponding to the magnitudes of all microseismic event points in each fracturing stage of the Z1 fracturing well, and the sorting results are shown in Table 3 (Calculation table of energy values of microseismic event points in each fracturing stage of the Z1 fracturing well) as follows;

[0081] ,

[0082] Table 3

[0083] Perform standardization processing on the energy values q corresponding to the magnitudes of the microseismic event points in each fracturing stage of the Z1 fracturing well, and use the formula: s = [(q - μ) / σ] + 1 to calculate the standardized energy values s of all microseismic event points in each fracturing stage, and the calculation results are shown in Table 4 (Calculation table of standardized energy values of microseismic event points in each fracturing stage of the Z1 fracturing well) as follows;

[0084] Where: μ is the average value of the energy value q corresponding to the magnitudes of all microseismic event points in each fracturing stage (in this example, μ = 11388359); σ is the standard deviation of the energy value q corresponding to the magnitudes of all microseismic event points in each fracturing stage (in this example, σ = 25158557);

[0085] ,

[0086] Table 4

[0087] Please refer to Figure 3 , and according to the standardized energy value s of all microseismic event points in each fracturing stage in the Z1 fracturing well, calculate the total sum Sr of the standardized energy values corresponding to the stress relaxation event points (magnitude ≥ critical magnitude Mc) in each fracturing stage of the Z1 fracturing well and the total sum S of the standardized energy values of the microseismic event points; the sorted results are as Figure 3 shown in (Comparison chart of the total sum of the standardized energy values corresponding to the stress relaxation event points and the total sum of the standardized energy values of the microseismic event points in each fracturing stage of the Z1 fracturing well);

[0088] Please refer to Figure 4 , and based on the total sum Sr of the standardized energy values of the stress relaxation event points in each fracturing stage and the total sum S of the standardized energy values of the microseismic event points in each fracturing stage, use the artificial fracture complexity Φ = [1 - (Sr / S)] × {[(P / P0) + (F / F0) + (C / C0)] / 3} × 100% to calculate the artificial fracture complexity Φ of each fracturing stage of the Z1 fracturing well; in this example: the highest average sand addition intensity P0 in the well area where the Z1 fracturing well is located is 4.5 t / m, the highest average liquid usage intensity F0 is 45 m 3 / m, the highest average ceramsite proportion C0 is 55%, the average sand addition intensity P of the Z1 fracturing well z1 is 3.92 t / m, the average liquid usage intensity F Z1 is 43.4 m3 / m, the average ceramsite proportion C Z1 is 48.2%; finally, the results of the artificial fracture complexity Φ of each fracturing stage of the Z1 well are sorted as Figure 4 shown in (Bar chart of the calculation results of the artificial fracture complexity Φ of each fracturing stage of the Z1 fracturing well);

[0089] Compare the calculated artificial fracture complexity Φ of each fracturing stage of the Z1 fracturing well with the empirical classification standard table of the artificial fracture complexity (shown in Table 5 below) to obtain the fracturing effects between different fracturing stages in the Z1 fracturing well and evaluate the complexity of the artificial fractures in the Z1 fracturing well; among them: the overall artificial fracture complexity of the Z1 fracturing well is low and the fracturing effect is poor. The artificial fracture complexity of the 3rd fracturing stage is relatively the highest and the fracturing effect is relatively the best. The artificial fracture complexity of the 14th fracturing stage is relatively the lowest and the fracturing effect is relatively the worst;

[0090] ,

[0091] Table 5

[0092] It can be understood that the complexity of the artificial fracture network = 30% corresponds to the first threshold in the above technical solution; the complexity of the artificial fracture network = 40% corresponds to the second threshold in the above technical solution; the complexity of the artificial fracture network = 40% corresponds to the second threshold in the above technical solution; the complexity of the artificial fracture network = 60% corresponds to the third threshold in the above technical solution; the complexity of the artificial fracture network = 80% corresponds to the fourth threshold in the above technical solution.

[0093] Embodiment 2: On the basis of Embodiment 1, the present invention further provides another implementation manner. In practical applications, this method is used to evaluate the fracturing effect and fracture network complexity between different fracturing well groups; the evaluation method provided in this embodiment further includes steps on the basis of steps S1 to S3 of Embodiment 1:

[0094] S'4: Analyze and process the monitoring data of the microseismic event points to obtain the total standardized energy value Sr of all stress relaxation event points and the total standardized energy value S of all microseismic event points in the target fracturing well;

[0095] In step S'4, analyzing and processing the monitoring data of the microseismic event points includes: S'401: Calculate the energy value q corresponding to each microseismic event point under the corresponding magnitude according to the energy relationship calculation formula;

[0096] In this step, the energy relationship calculation formula can adopt the Richter magnitude energy relationship formula, and the energy relationship calculation formula is as follows: q = 10 （1.5M+4.8） ;

[0097] where q is the response energy of the microseismic event point, with the unit of joule; M is the magnitude in the microseismic original data, generally distributed between -3 and 3, dimensionless;

[0098] S'402: Standardize the energy value q using the standardization calculation formula to calculate the standardized energy value s of each microseismic event point;

[0099] S'403: Add up the standardized energy values s of the microseismic event points classified as stress relaxation event points in the target fracturing well to obtain the total standardized energy value Sr of all stress relaxation event points in the target fracturing well; add up the standardized energy values s of all microseismic event points in the target fracturing well to obtain the total standardized energy value S of all microseismic event points in the target fracturing well;

[0100] In this step, the standardization calculation formula is as follows: s = [(q - μ) / σ] + 1;

[0101] Among them, μ is the average value of the energy value q corresponding to the magnitudes of all microseismic event points in each fracturing well; σ is the standard deviation of the energy value q corresponding to the magnitudes of all microseismic event points in each fracturing well.

[0102] S’5: Using the evaluation calculation formula for the complexity of artificial fractures, calculate the complexity Φ of the fracture network of the target fracturing well.

[0103] In step S5: The evaluation calculation formula for the complexity of artificial fractures is as follows: The complexity of artificial fractures Φ = [1 - (Sr / S)] × {[(P / P0) + (F / F0) + (C / C0)] / 3} × 100%;

[0104] In the formula: P is the average proppant addition intensity of the target fracturing well, P0 is the highest average proppant addition intensity of the wells in the well area where the target fracturing well is located, F is the average fluid consumption intensity of the target fracturing well, F0 is the highest average fluid consumption intensity of the wells in the well area where the target fracturing well is located, C is the average proportion of ceramsite in the target fracturing well, and C0 is the highest average proportion of ceramsite in the wells in the well area where the target fracturing well is located.

[0105] Based on the complexity Φ of the fracture network of the target fracturing well obtained in step S’5, compare it with the empirical classification standard table of the complexity of artificial fractures (Table 5) to obtain the evaluation result for evaluating the complexity of the artificial fractures and the fracturing effect of the target fracturing well. It can be understood that by adopting the above scheme, the evaluation results of the complexity of the artificial fractures and the fracturing effect of any single well can be obtained; further compare the fracturing effects and the complexities of the artificial fractures between different well groups.

[0106] In this embodiment, taking the microseismic event point monitoring data of Z1 and Z2 fracturing wells as the analysis object, sort out the fracturing sections and magnitudes to which each event point of Z1 and Z2 fracturing wells belongs, and establish a microseismic event point set of Z1 and Z2 fracturing wells, as shown in Table 6 below;

[0107] ,

[0108] Table 6

[0109] Please refer to Figure 2 and Figure 5 , according to the monitoring data of all microseismic event points in the microseismic event point set of Z1 and Z2 fracturing wells, respectively draw the scatter plot of the event point magnitudes; and determine the critical magnitude Mc of each well group; in this embodiment, the critical magnitude Mc1 of Z1 fracturing well is -1.0, and the critical magnitude Mc2 of Z2 fracturing well is -0.8.

[0110] The microseismic event points of the Z1 and Z2 fracturing wells are respectively divided into stress relaxation event points (magnitude ≥ critical magnitude Mc) and microfracture network event points (magnitude < critical magnitude Mc) based on the critical magnitude Mc, and the sorting results are shown in Table 7 (Classification Table of Event Points of Z1 and Z2 Fracturing Wells) as follows;

[0111] ,

[0112] Table 7

[0113] According to the energy relationship calculation formula: q = 10 （1.5M+4.8） Calculate and sort the energy values q corresponding to the magnitudes of the microseismic event points in the Z1 and Z2 fracturing wells respectively, and the sorting results are shown in Table 8 (Calculation Table of Monitoring Energy Values of Microseismic Event Points of Z1 and Z2 Fracturing Wells) as follows;

[0114] ,

[0115] Table 8

[0116] Standardize the energy values q of the microseismic event points in the Z1 and Z2 fracturing wells respectively, and use the formula: s = [(q - μ) / σ] + 1 to calculate the standardized energy values s of all microseismic event points. The calculation results are shown in Table 9 (Calculation Table of Monitoring Standardized Energy Values of Microseismic Event Points of Z1 and Z2 Fracturing Wells) as follows;

[0117] In the formula: μ is the average value of the energy values q corresponding to the magnitudes of all microseismic event points in each fracturing well; σ is the standard deviation of the energy values q corresponding to the magnitudes of all microseismic event points in each fracturing well;

[0118] In this example: the average value μ1 of the Z1 fracturing well is 11388359 joules, the standard deviation σ1 is 25158557 joules, the average value μ2 of the Z2 fracturing well is 324364 joules, and the standard deviation σ2 is 4290962 joules;

[0119] ,

[0120] Table 9

[0121] According to the standardized energy values s of the microseismic event points of the Z1 and Z2 fracturing wells respectively; and calculate the sum Sr of the standardized energy values corresponding to the stress relaxation event points (magnitude ≥ Mc) of the Z1 and Z2 fracturing wells respectively and the total standardized energy S of all microseismic event points;

[0122] Among them: the total standard energy S1 of the stress relaxation event points in the Z1 fracturing well is 951 joules, and the total standardized energy S of the microseismic event points 总1 is 1606 joules. The total standard energy S2 of the stress relaxation event points in the Z2 fracturing well is 486 joules, and the total standardized energy S of the microseismic event points总2 is 3593 joules;

[0123] Based on the above-obtained calculation data, using the artificial fracture complexity Φ = [1 - (Sr / S)] × {[(P / P0) + (F / F0) + (C / C0)] / 3} × 100%, the artificial fracture complexities Φ of the Z1 and Z2 fracturing wells are calculated respectively;

[0124] In the formula: P is the average sand addition intensity of the target fracturing well, P0 is the highest average sand addition intensity of the wells in the well area where the target fracturing well is located, F is the average fluid consumption intensity of the target fracturing well, F0 is the highest average fluid consumption intensity of the wells in the well area where the target fracturing well is located, C is the average proportion of ceramsite in the target fracturing well, and C0 is the highest average proportion of ceramsite in the wells in the well area where the target fracturing well is located.

[0125] In this embodiment, the Z1 and Z2 fracturing wells are in the same well area. The highest average sand addition intensity P0 of the wells in the well area is 4.5 t / m, the highest average fluid consumption intensity F0 is 45 m 3 / m, the highest average proportion of ceramsite C0 is 55%, and the average sand addition intensities P z1 、P z2 of the target wells are 3.92 t / m and 4.07 t / m respectively, the average fluid consumption intensities F Z1 、F Z2 are 43.4 m 3 / m and 45.0 m 3 / m respectively, and the average proportions of ceramsite C Z1 、C Z2 are 48.2% and 50.4% respectively. Finally, the artificial fracture complexity of the Z1 fracturing well is calculated to be 36.87%, and the artificial fracture complexity of the Z2 fracturing well is 81.31%;

[0126] Compare the calculated artificial fracture complexities of the Z1 and Z2 fracturing wells with the empirical classification standard table of artificial fracture complexity (Table 5) provided in Embodiment 1 respectively, and the fracturing effects between different well groups can be compared to evaluate the artificial fracture complexity of the target well fracturing; among them: the artificial fracture complexity of the Z1 fracturing well is relatively simple and the fracturing effect is poor, while the artificial fracture complexity of the Z2 fracturing well is complex and the fracturing effect is good.

[0127] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A method for evaluating the complexity of a fracture network based on microseismic analysis, characterized in that: The method comprises the following steps: S1: Collect a number of microseismic event points in the target fracturing well through a microseismic monitoring method, obtain monitoring data of the microseismic event points, and establish a microseismic event point set; S2: drawing a scatter plot of event point magnitudes according to the microseismic event point set, and determining a critical magnitude Mc according to the scatter distribution characteristics of the event point magnitude scatter plot; S3: Based on the critical magnitude Mc, the microseismic event points in the microseismic event point set are divided into stress relaxation event points and micro-fracture network event points; S4: Analyze and process the monitoring data of the microseismic event points to obtain the normalized energy value sum Sr of the stress relaxation event points and the normalized energy value sum S of the microseismic event points; Analyze and process the monitoring data of the microseismic event points including: S401: Calculate the energy value q of each microseismic event point at the corresponding magnitude using an energy relationship calculation formula; S402: Standardizing the energy value q using a standardized calculation formula to obtain a standardized energy value s of each microseismic event point; S5: Calculate the fracture network complexity Φ of the target fracture well using the artificial fracture complexity evaluation calculation formula; the artificial fracture complexity evaluation calculation formula is as follows: artificial fracture complexity Φ=[1-(Sr / S)]×{[(P / P0)+(F / F0)+(C / C0)] / 3}×100%; Among them, P is the average sand addition intensity of the target fracturing well; P0 is the highest average sand addition intensity of the wells in the well area where the target fracturing well is located; F is the average fluid intensity of the target fracturing well; F0 is the highest average fluid intensity of the wells in the well area where the target fracturing well is located; C is the average ceramsite ratio of the target fracturing well; and C0 is the highest average ceramsite ratio of the wells in the well area where the target fracturing well is located.

2. The method for evaluating the complexity of a fracture network based on microseismic analysis according to claim 1, characterized in that: In S1, the monitoring data of the microseismic event point at least includes: the fracturing section to which the microseismic event point belongs and magnitude information.

3. The method for evaluating the complexity of a fracture network based on microseismic analysis according to claim 1, characterized in that: In S401, the energy relationship calculation formula is as follows: q=10 （1.5M+4.8） ; Where q is the response energy of the microseismic event point, in joules; M is the magnitude in the original microseismic data.

4. The method for evaluating the complexity of a fracture network based on microseismic analysis according to claim 1, characterized in that: In the S402, the standardized calculation formula is as follows: s=[(q-μ) / σ]+1; Among them, μ is the average value of the energy value q of the microseismic event point of each fracturing well; σ is the standard deviation of the energy value q of the microseismic event point of each fracturing well.

5. The method for evaluating the complexity of a fracture network based on microseismic analysis according to claim 1, characterized in that: According to the fracturing network complexity Φ, an evaluation result for evaluating the complexity of artificial fracturing seams and the fracturing effect is obtained, including: When the fracturing network complexity Φ is less than a first threshold value, it is determined that the evaluation result of the complexity of the artificial fracturing seams of the target fracturing well is extremely simple, and the evaluation result of the fracturing effect is extremely poor; When the hydraulic fracture network complexity Φ is greater than or equal to the first threshold value and less than the second threshold value, it is determined that the evaluation result of the complexity of the artificial fractures of the target hydraulic fracture well is relatively simple, and the evaluation result of the hydraulic fracture effect is poor; When the hydraulic fracture network complexity Φ is greater than or equal to the second threshold value and less than the third threshold value, it is determined that the evaluation result of the complexity of the artificial fractures of the target hydraulic fracture well is average, and the evaluation result of the hydraulic fracture effect is average; When the hydraulic fracture network complexity Φ is greater than or equal to the third threshold value and less than the fourth threshold value, it is determined that the evaluation result of the complexity of the artificial fractures of the target hydraulic fracture well is relatively complex, and the evaluation result of the hydraulic fracture effect is relatively good; When the fracturing network complexity Φ is greater than or equal to the fourth threshold, it is determined that the evaluation result of the complexity of the artificial fracturing seams of the target fracturing well is complex, and the evaluation result of the fracturing effect is good.

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