Design method of multidirectional shallow well microseism observation system

Abstract

The invention provides a design method of a multidirectional shallow well microseism observation system. The design method of the multidirectional shallow well microseism observation system comprises the following steps: step 1, collecting ground noise records in a target work area range; 2, establishing an initial speed model of a target work area; 3, setting parameters such as the number of observation wells, the number of detectors, the interstage spacing and the sampling rate; 4, simulating the type and strength of possibly generated microseismic signals according to the target fracturing area, and analyzing the detectable distance of the induced microseismic signals; and step 5, aiming at the target fracturing area, analyzing a seismic source positioning error of the detectable signal. According to the design method of the multidirectional shallow well microseism observation system, potential detectable signal intensity and microseism signal positioning errors of the observation system can be well described, and a basis is provided for subsequent actual data processing and interpretation.

Description

Technical Field

[0001] The present invention relates to the technical field of microseismic monitoring for unconventional reservoir fracturing, and particularly to a design method for a multi-directional shallow well microseismic observation system. Background Technique

[0002] The construction mode of the "well factory" for fracturing unconventional oil and gas reservoirs is characterized by large fracturing scale, long continuous construction time, wide underground coverage, etc. Fracturing monitoring faces the requirements of low cost, repeatability, and long-term. During the reservoir transformation process, the expansion of fracturing cracks will cause rock fractures and induce weak seismic signals. Microseismic monitoring technology understands the development of underground fracturing cracks by observing and analyzing these weak seismic events, aiming to monitor and evaluate the reservoir transformation effect in real time, and it has played an important role in improving the fracturing stimulation effect of low-permeability oil and gas wells and improving the productivity of oil and gas wells.

[0003] The wave field characteristics, data quality, and positioning accuracy of microseismic events are closely related to the microseismic observation system. The optimization of the microseismic observation system involves various factors such as the source generation mechanism, signal reception method, and fracturing construction environment. To ensure the quality of microseismic monitoring records, usually before the fracturing construction, it is necessary to design reasonable microseismic monitoring methods, acquisition parameters, monitoring distances, etc. based on data such as the geological characteristics, formation physical property parameters, fracturing construction parameters, and geophone sensitivity of the study area, combined with the microseismic magnitude sensitivity and source positioning accuracy. Borehole observation (including downhole monitoring and shallow well monitoring) is a common microseismic monitoring method. Compared with surface monitoring methods, the borehole observation system is closer to the fracturing target layer in depth and can detect more and higher-quality microseismic events. Deep downhole monitoring depends on the availability of suitable monitoring wells near the work area. The shallow well observation method arranges multi-level three-component geophones in several shallow wells with a depth of about 100m for monitoring, which can reduce the absorption and attenuation of microseismic signals by the surface low-velocity zone and also has better operability than downhole monitoring. However, in actual fracturing monitoring projects, there is often a lack of quantitative analysis for the design of shallow well observation systems.

[0004] In the Chinese patent application with the application number: CN201811170023.1, it involves a design of a mine microseismic observation system and a method for extracting surface wave velocity. For the field of mine safety microseismic monitoring, a four-line staggered grid circular microseismic monitoring array observation system is designed in a restricted observation space, and information is collected in a strong noise environment such as microseismic events and mining engineering. Since the microseismic signals and environmental noise are random processes with complex spatio-temporal characteristics, the spatial correlation method is used to effectively extract the surface waves generated by microseismic events and mining vibrations from the signal records, and the dispersion characteristic curve of the surface wave phase velocity is calculated. Further, the wavelength is calculated based on the surface wave frequency and phase velocity, and half of the wavelength corresponding to the frequency is taken as the detection distance to establish an initial formation velocity model. Through repeated iterative processing, the velocity structure characteristics of the formation are obtained. Since the surface wave is not affected by the shielding effect of the high-velocity layer and has a strong resolution ability for low-velocity layers such as coal seams, it can reflect the velocity structure of the working face, thereby improving the utilization effect of microseismic monitoring data.

[0005] In the Chinese patent application with the application number: CN201510373414.3, it involves a method for determining the positions of geophones in a surface microseismic observation system, including: (a) obtaining the existing data in the work area and establishing a geological model; (b) performing a fracturing simulation according to the geological model, the depth of the target layer, and the fracturing construction scale to obtain the lateral range affected by the fracturing cracks in the reservoir; (c) determining the layout range of the geophones according to the lateral range affected by the fracturing cracks in the reservoir, the depth of the target layer, and the microseismic signal wavelength; (d) determining the trace interval according to the microseismic signal wavelength; (e) determining the layout coordinates of each geophone according to the wellhead coordinates, the layout range of the geophones, and the trace interval. According to the exemplary embodiments of the present invention, by integrating the parameter of the fracturing construction scale, the geological characteristics of the target layer and other relevant monitoring task information, the surface microseismic observation system can be designed, and high-quality fracturing rupture microseismic signals can be obtained economically and effectively, which is economical and practical.

[0006] In the Chinese patent application with the application number: CN201710942919.6, it involves a method and system for determining the location of a ground shallow well microseismic monitoring observation station. The method may include: obtaining the work area data of the fracturing block and analyzing the influencing factors for setting up the monitoring observation station; establishing a three-dimensional geological model based on the geological data and surface exploration data of the fracturing block; performing forward modeling of shallow surface waves on the three-dimensional geological model to obtain the surface wave attenuation curve with depth, and determining the burial depth; analyzing the distribution of the fracturing block and the depth of the target layer, performing simulation of the distribution of hydraulic fracturing microseismic sources, and determining the maximum lateral layout range; determining the layout method of the monitoring observation station according to the influencing factors, and determining the number of monitoring observation stations; determining the layout coordinates according to the burial depth, maximum lateral layout range, layout method and number of the monitoring observation stations. The invention can reduce the acquisition cost, reduce the amount of seismic record data, and improve the calculation efficiency, and has certain advantages in long-term multi-well monitoring and the development zone stage.

[0007] In the Chinese patent application with the application number: CN201610087061.5, it involves a method for designing the distribution of ground microseismic monitoring stations, mainly solving the problem that there is a lack of basis for the design of station distribution in the existing ground microseismic monitoring technology. The present invention establishes a three-dimensional fine geological model based on the existing three-dimensional seismic data and drilling data in the work area, statistically obtains the theoretical microseismic signal waveform from the microseismic signals monitored in the previous wells in the area, calculates the energy distribution of the theoretical microseismic signal propagating to the surface through forward modeling of the three-dimensional wave equation, and designs the distribution range and location of the stations based on the energy distribution in combination with the actual surface conditions of the work area, so that the stations are distributed as much as possible at the locations with larger energy values. This technology reduces the blindness of station layout in ground microseismic monitoring, enhances the ability to monitor ground microseismic signals, and can be used in the industrial production of hydraulic fracturing ground microseismic monitoring.

[0008] The above existing technologies are all quite different from the present invention and fail to solve the technical problems we want to solve. Therefore, we have invented a new method for designing a multi-directional shallow well microseismic observation system. Summary of the Invention

[0009] The purpose of the present invention is to provide a method for designing a multi-directional shallow well microseismic observation system for the lack of an effective and quantitative microseismic monitoring and observation system design for the target geology in the current fracturing monitoring project.

[0010] The purpose of the present invention can be achieved by the following technical measures: A method for designing a multi-directional shallow well microseismic observation system, and this method for designing a multi-directional shallow well microseismic observation system includes:

[0011] Step 1, collecting ground noise records within the range of the target work area;

[0012] Step 2, establishing an initial velocity model for the target work area;

[0013] Step 3, set parameters such as the number of observation wells, the number of geophones, the level spacing, and the sampling rate;

[0014] Step 4, for the target fracturing area, simulate the types and intensities of possible microseismic signals, and analyze the detectable distance of the induced microseismic signals;

[0015] Step 5, for the target fracturing area, analyze the source location error of the detectable signals.

[0016] The object of the present invention can also be achieved by the following technical measures:

[0017] In Step 1, collect background noise records at different azimuths and times in the target work area; analyze the background noise signals to identify potential noise sources and the noise intensity within the work area.

[0018] In Step 1, the potential noise sources include operation infrastructure and roads.

[0019] In Step 2, establish an initial velocity model of the target work area based on the well logging data and seismic data of the existing wells in the work area.

[0020] In Step 2, the well logging data includes the acoustic logging and GR logging curves of the fracturing wells and observation wells, and the seismic data is the 3D seismic profile of the work area. The formation is divided through the seismic profile and GR logging curve, and the longitudinal and transverse wave velocities of the formation are obtained using the acoustic logging curve.

[0021] In Step 3, calculate the relative monitoring distance, event observation aperture, and geophone observation aperture between the observation well and the fracturing section through the position of the observation system.

[0022] In Step 3, the calculation formula for the relative monitoring distance is

[0023]

[0024] where s m (x,y,z) represents the spatial coordinates of the m-th potential seismic source near the fracturing section, and r n (x,y,z) are the spatial coordinates of the n-th level geophone;

[0025] The event observation aperture is the angle between the seismic source event and the line connecting any two geophones, and its calculation formula is as follows

[0026]

[0027] where n1 and n2 are the numbers of any two levels of geophones, and m is the event number;

[0028] The observation aperture of the geophone is the angle between the geophone and the line connecting any two events, and its calculation formula is as follows

[0029]

[0030] Among them, m1 and m2 are any two source event numbers, and n is the detector number;

[0031] The maximum value, minimum value and average value of the relative monitoring distance, event observation aperture and detector observation aperture of the observation system can be obtained from the relative monitoring distance, event observation aperture and detector observation aperture calculated according to the above formula.

[0032] In step 4, for the target fracturing area, simulate the possible types and intensities of microseismic signals. In the simulation, the magnitude and frequency of microseismic events satisfy the magnitude-frequency empirical formula, that is, the G-R relationship, as follows

[0033] lgN(M) = a - bM (4)

[0034] Among them, N(M) is the number of earthquakes occurring within a certain period in a small interval (M±ΔM) centered on the magnitude M; a and b are constants, a represents the seismic activity level within the statistical events and regions, and the b value represents the proportional relationship between the number of large and small earthquakes;

[0035] The spatial distribution of the simulated K microseismic events is set within a cube with a spatial coordinate point (x0, y0, z0) as the center, an angle θ in the positive direction of the clockwise direction from due north, and the length, width and height are L, W, and D respectively.

[0036] In step 4, the minimum magnitude of microseismic events that can be monitored by the multi-azimuth shallow well array is related to the spatial distribution of the array, the background noise intensity, the main frequency of microseismic events, and the formation properties including the velocity model, quality factor and density. Combine the background noise and the seismic magnitude and seismic wave propagation attenuation law to analyze the detectability of microseismic signals; the intensity of microseismic events can be described by the moment magnitude, and the seismic moment M0 of a homogeneous isotropic medium can be estimated according to the following formula

[0037]

[0038] In the above formula, v is the wave velocity, r is the distance from the source to the detector, ρ is the formation density, W0 is the low-frequency cut-off value of the amplitude spectrum, and U is the amplitude radiation characteristic; the low-frequency cut-off value W0 of the amplitude spectrum can be estimated by the following formula

[0039]

[0040] In the above formula, f0 is the main frequency of microseismic events, and A0 is the amplitude of the source effective signal at f0:

[0041]

[0042] In the above formula, Q p is the quality factor of the longitudinal wave, t0 is the travel time from the seismic source to the geophone, and A w is the amplitude of the effective signal of the geophone at f0:

[0043]

[0044] In the above formula, SNR is the estimated minimum signal-to-noise ratio, and A n is the background noise amplitude of the monitoring area; since the amplitude of the longitudinal wave is generally weaker than that of the transverse wave, the longitudinal wave moment magnitude of the monitoring area is usually used to represent the sensitivity of a given geophone in this area;

[0045] Based on the simulated microseismic magnitude and the magnitude sensitivity of the geophone, at a certain noise level, if the microseismic magnitude that the geophone can detect is greater than the simulated microseismic magnitude, it is considered that the corresponding magnitude event cannot be detected.

[0046] In step 4, calculate the signal-to-noise ratio of the detectable events, and the calculation formula is

[0047]

[0048] In step 5, for the target fracturing area, analyze the source location error of the detectable signals. Considering that the spatial uncertainty of the source location increases with the event magnitude energy from strong to weak, that is, the error of the simulated source position is affected by the signal-to-noise ratio of the event signal; according to the signal-to-noise ratio of the detectable events calculated in step 4, give the first arrival error and azimuth error under different signal-to-noise ratios.

[0049] In step 5, for the characteristics of the multi-azimuth shallow well microseismic observation system, construct a source location objective function by combining the first arrival times of P waves and S waves and the P wave polarization angle; the double-phase arrival time difference objective function f ps and the P-phase arrival time difference objective function f p as well as the S-phase arrival time difference objective function f s can be calculated by the following formula

[0050]

[0051] In the formula, tp obs , ts obs are the observed first arrivals of P waves and S waves, and tp cal , ts cal are the theoretically calculated first arrivals of P waves and S waves, and N is the number of geophones;

[0052] According to the P wave polarization angle, an azimuth objective function can be constructed, and the calculation formula is as follows

[0053]

[0054] In the formula are the azimuth angle information recorded by each level of geophones and obtained through theoretical calculation respectively, and N is the number of geophones;

[0055] The calculation formula of the final objective function for seismic source location is as follows

[0056]

[0057] In the above formula, ω1 and ω2 are weighting coefficients; the position corresponding to the minimum of the objective function obtained by using the grid search or nonlinear search method is the seismic source location coordinate.

[0058] The object of the present invention can also be achieved by the following technical measures: a multi - azimuth shallow - well micro - seismic observation system design system, which uses the multi - azimuth shallow - well micro - seismic observation system design method to simulate micro - seismic events and analyze the detectable number of micro - seismic events and the positioning error of the seismic source location under a potential observation system, and then selects the most suitable geophone layout scheme.

[0059] The multi - azimuth shallow - well micro - seismic observation system design method in the present invention, aiming at the problems existing in the prior art, by considering various factors such as the generation mechanism of fracturing - induced seismic sources, signal reception methods, and fracturing construction environments, and according to data such as geological characteristics, physical property parameters, and geophone sensitivities, analyzes the positioning error of the simulated micro - seismic source location under a potential micro - seismic monitoring method, acquisition parameters, monitoring distance, and observation system, providing a basis for actual fracturing fracture description and quality control. This multi - azimuth shallow - well micro - seismic observation system design method analyzes the positioning error of the simulated micro - seismic source location under a potential micro - seismic monitoring method, acquisition parameters, monitoring distance, and observation system by considering various factors such as the generation mechanism of fracturing - induced seismic sources, signal reception methods, and fracturing construction environments, and according to data such as geological characteristics, formation physical property parameters, and geophone sensitivities, providing a basis for actual fracturing fracture description and quality control. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 is a flowchart of a specific embodiment of the multi - azimuth shallow - well micro - seismic observation system design method of the present invention;

[0061] Figure 2 is a schematic diagram of the well trajectory of the horizontal fracturing well in the work area and the established velocity model in a specific embodiment of the present invention;

[0062] Figure 3 is a schematic diagram of the crack model composed of micro - seismic sources and the relative position relationship of the observation wells in specific embodiments 1 and 2 of the present invention;

[0063] Figure 4Schematic diagram of detectable events and positioning under the observation conditions and acquisition parameters in a specific embodiment 1 of the present invention;

[0064] Figure 5 Schematic diagram of detectable events and positioning under the observation conditions and acquisition parameters in a specific embodiment 2 of the present invention;

[0065] Figure 6 Schematic diagram of the fracture model composed of microseismic sources simulated by multiple fracturing sections of horizontal wells and the relative position relationship of observation wells in a specific embodiment 3 of the present invention;

[0066] Figure 7 Schematic diagram of detectable events and positioning under the observation conditions and acquisition parameters in a specific embodiment 3 of the present invention. Detailed implementation manners

[0067] It should be noted that the following detailed description is exemplary and is intended to provide further illustration of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0068] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they specify the presence of features, steps, operations, and / or combinations thereof.

[0069] The design method of the multi - azimuth shallow - well microseismic observation system of the present invention includes first collecting ground noise records within the target work area, identifying potential noise sources and analyzing the noise intensity distribution within the work area. Establishing an initial velocity model of the target work area and setting formation physical property parameters, and combining the type of geophones and sensitivity parameters to simulate and analyze the magnitude and quantity of microseismic signals from the underground fracturing area that can be detected by the potential observation system. Setting acquisition parameters such as the number of multi - azimuth shallow wells, the number of geophones, the level interval, and the sampling rate, calculating the source location error for microseismic signals with different signal - to - noise ratios in the target fracturing area, and analyzing the uncertainty of fracture interpretation.

[0070] The method of the present invention specifically includes the following steps:

[0071] Step 1, collect background noise records at different azimuths and times within the target work area; analyze the background noise signals to identify potential noise sources (such as operation infrastructure and roads, etc.) and the noise intensity within the work area.

[0072] Step 2: Establish an initial velocity model based on the logging data and seismic data of the existing wells in the work area; the logging data includes the acoustic logging and GR logging curves of the fracturing wells and observation wells, and the seismic data is the 3D seismic profile of the work area. The stratigraphic division is realized through the seismic profile and GR logging curve, and the longitudinal and transverse wave velocities of the strata are obtained by using the acoustic logging curve.

[0073] Step 3: Set parameters such as the number of observation wells, the number of geophones, the level spacing, and the sampling rate;

[0074] Calculate the relative monitoring distance, event observation aperture, and geophone observation aperture between the observation well and the fracturing section through the position of the observation system.

[0075] The calculation formula for the relative monitoring distance is

[0076]

[0077] where s m (x, y, z) represents the spatial coordinates of the m-th potential seismic source near the fracturing section, and r n (x, y, z) is the spatial coordinates of the n-th level geophone;

[0078] The event observation aperture is the angle between the seismic source event and the line connecting any two geophones, and its calculation formula is as follows

[0079]

[0080] where n1 and n2 are the numbers of any two levels of geophones, and m is the event number;

[0081] The observation aperture of the geophone is the angle between the geophone and the line connecting any two events, and its calculation formula is as follows

[0082]

[0083] where m1 and m2 are the numbers of any two seismic source events, and n is the geophone number;

[0084] The maximum, minimum, and average values of the relative monitoring distance, event observation aperture, and geophone observation aperture of the observation system can be obtained based on the relative monitoring distance, event observation aperture, and geophone observation aperture calculated according to the above formulas.

[0085] Step 4: For the target fracturing area, simulate the types and intensities of possible microseismic signals, and analyze the detectable distance of the induced microseismic signals;

[0086] For the target fracturing area, simulate the types and intensities of possible microseismic signals. In the simulation, the magnitude and frequency of microseismic events satisfy the magnitude-frequency empirical formula, i.e., the G-R relationship, as follows

[0087] lg N(M) = a - bM (4)

[0088] where N(M) is the number of earthquakes occurring within a small magnitude interval (M ± ΔM) centered on magnitude M over a certain period; a and b are constants, a represents the seismic activity level within the statistical event and region, and the value of b represents the proportional relationship between the number of large and small earthquakes;

[0089] The spatial distribution of the simulated K microseismic events is set within a cube with length L, width W, and height D, centered on a spatial coordinate point (x0, y0, z0), with an included angle θ in the clockwise direction from due north as the positive direction.

[0090] The minimum magnitude of microseismic events that can be detected by multi - azimuth shallow - well arrays is related to the spatial distribution of the array, the background noise intensity, the dominant frequency of microseismic events, and formation properties including the velocity model, quality factor, and density. By combining the background noise and the attenuation law of seismic magnitude with seismic wave propagation, the detectability of microseismic signals is analyzed; the intensity of microseismic events can be described by the moment magnitude, and the seismic moment M0 of a homogeneous isotropic medium can be estimated according to the following formula

[0091]

[0092] In the above formula, v is the wave velocity, r is the distance from the seismic source to the geophone, ρ is the formation density, W0 is the low - frequency cut - off value of the amplitude spectrum, and U is the amplitude radiation characteristic; the low - frequency cut - off value W0 of the amplitude spectrum can be estimated by the following formula

[0093]

[0094] In the above formula, f0 is the dominant frequency of the microseismic event, and A0 is the amplitude of the effective signal at the seismic source at f0:

[0095]

[0096] In the above formula, Q p is the quality factor of the P - wave, t0 is the travel time from the seismic source to the geophone, and A w is the amplitude of the effective signal at the geophone at f0:

[0097]

[0098] In the above formula, SNR is the estimated minimum signal - to - noise ratio, and A n is the background noise amplitude of the monitoring area; since the amplitude of the P - wave is generally weaker than that of the S - wave, the P - wave moment magnitude of the monitoring area is usually used to represent the sensitivity of a given geophone in this area;

[0099] Based on the simulated microseismic magnitude and the magnitude sensitivity of the geophones, at a certain noise level, if the microseismic magnitude that the geophones can detect is greater than the simulated microseismic magnitude, it is considered that the corresponding magnitude event cannot be detected.

[0100] Calculate the signal-to-noise ratio of detectable events, and the calculation formula is

[0101]

[0102] Step 5: Analyze the source location error of detectable signals for the target fracturing area.

[0103] For the target fracturing area, analyze the source location error of detectable signals. Considering that the spatial uncertainty of source location increases with the decreasing event magnitude energy from strong to weak, that is, the error of the simulated source location is affected by the signal-to-noise ratio of the event signal; according to the signal-to-noise ratio of detectable events calculated in Step 4, give the first arrival error and azimuth error under different signal-to-noise ratio conditions.

[0104] For the characteristics of the multi-azimuth shallow well microseismic observation system, jointly construct a source location objective function using the first arrival times of P-wave and S-wave and the P-wave polarization angle; the double-phase arrival time difference objective function f ps and the P-phase arrival time difference objective function f p and the S-phase arrival time difference objective function f s can be calculated by the following formula

[0105]

[0106] In the formula, tp obs , ts obs are the observed first arrivals of P-wave and S-wave, and tp cal , ts cal are the theoretically calculated first arrivals of P-wave and S-wave, and N is the number of geophones;

[0107] According to the P-wave polarization angle, an azimuth objective function can be constructed, and the calculation formula is as follows

[0108]

[0109] In the formula are the azimuth angle information recorded by each level of geophones and the azimuth angle information obtained by theoretical calculation respectively, and N is the number of geophones;

[0110] The calculation formula of the final source location objective function is as follows

[0111]

[0112] In the above formula, ω1 and ω2 are weighting coefficients; the position corresponding to the minimum of the objective function obtained by using the grid search or the non-linear search method is the seismic source location coordinate.

[0113] The following are several specific embodiments of applying the present invention

[0114] Embodiment 1

[0115] In a specific Embodiment 1 of applying the present invention, as Figure 1 shown, the design method of the multi-directional shallow well microseismic observation system includes the following steps:

[0116] In step 101, background noise records at different azimuths and different times in the target work area are collected by seismic acquisition equipment; the background noise signals are analyzed to identify potential noise sources (such as operation infrastructure and roads, etc.) and the noise intensity at each potential measurement position within the work area. The process proceeds to step 102.

[0117] In step 102, an initial velocity model is established based on the well logging data and seismic data of the existing wells in the work area. Figure 2 (a) shows a horizontal well in a work area and the designed fracturing section, Figure 2 (b) is a layered velocity model established according to the well logging curve of the fracturing well in this work area. The process proceeds to step 103.

[0118] In step 103, parameters such as the number of observation wells, the number of geophones, the level spacing, and the sampling rate are set. The relative distance between the observation well and the fracturing section is calculated through the position of the observation system. In the embodiment, the observation system parameters are set. The observation system includes 3 observation wells, the number of geophones in each observation well is 8 levels, the level spacing is 10 m, the depth range is 100 m to 170 m, and the sampling rate is 1000 Hz. The observation system is as Figure 3 shown, and the black triangles are the positions of the geophones. The process proceeds to step 104.

[0119] In step 104, for the target fracturing area, the types and intensities of possible microseismic signals are simulated, and the detectability of microseismic signals is analyzed in combination with the background noise and the seismic wave propagation attenuation law. As Figure 3 (a) shows, the gray circles in the figure are 200 microseismic events simulated with the perforation as the center. The spatial distribution of the events satisfies 30° north by west in azimuth, the crack is 200 m long, 80 m wide, and 50 m high in space. The microseismic magnitude of the simulated events and the event frequency satisfy the G-R relationship, the b value is 1.8, and the microseismic magnitude distribution range is -3.0 to 1.0. Figure 3 (b) is the planar distribution of the simulated microseismic sources.

[0120] The monitoring distance of an event can be calculated based on the relationship between the seismic source and the geophone positions. The background noise amplitudes of three wells are all set to 6 nm / s, the main frequency f0 is 20 Hz, the P-wave quality factor QP is 100, and the signal-to-noise ratio SNR is 3 dB. The minimum moment magnitude that can be reliably monitored by the acquisition scheme composed of these 3 shallow wells can be obtained, which is approximately -1.6. Based on the relationship between the microseismic magnitude, the number of detectable events, and the monitoring distance (i.e., the greater the monitoring distance, the greater the magnitude requirement for detectable events, and the fewer the number of detectable events), when the intensity of the microseismic signal with added noise is lower than the detection limit, it is considered that the events of the corresponding magnitude cannot be detected.

[0121] In step 105, for the target fracturing area, analyze the source location error of the detectable signals. Considering that the spatial uncertainty of the seismic source becomes larger as the event energy decreases from strong to weak, that is, the error of the simulated seismic source position is affected by the signal-to-noise ratio of the event signal. For the characteristics of the multi-azimuth shallow well microseismic observation system, construct a source location objective function by combining the P-wave and S-wave first arrival times of the detectable events and the P-wave polarization angle, and use the grid search method to obtain the position corresponding to the minimum of the objective function as the source location coordinates. Figure 4 (a) and Figure 4 (b) are the stereogram and plan view of the location results of the simulated detectable events; the process ends.

[0122] Example 2

[0123] In a specific Example 2 of applying the present invention, for the 200 microseismic events in Example 1, the parameters of the fractures, the microseismic source positions, and the intensities remain unchanged. Four observation wells are set, with 6 geophones in each well, the interval between levels is 20 m, the depth range is 200 m to 300 m, and the sampling rate is 1000 Hz. The observation system is as Figure 5 shown, and the black triangles are the geophone positions.

[0124] The monitoring distance of an event can be calculated based on the relationship between the seismic source and the geophone positions. The background noise amplitudes of the four wells are set to 5 nm / s, 10 nm / s, 15 nm / s, and 20 nm / s respectively, the main frequency f0 is 30 Hz, the P-wave quality factor QP is 100, and the signal-to-noise ratio SNR is 2 dB. The minimum moment magnitude that can be reliably monitored by the acquisition scheme composed of these 4 shallow wells can be obtained, which is approximately -2.1. Based on the relationship between the microseismic magnitude, the number of detectable events, and the monitoring distance (i.e., the greater the monitoring distance, the greater the magnitude requirement for detectable events, and the fewer the number of detectable events), when the intensity of the microseismic signal with added noise is lower than the detection limit, it is considered that the events of the corresponding magnitude cannot be detected.

[0125] For the target fracturing area, analyze the source location error of detectable signals under the given observation conditions and acquisition parameters. Considering that the spatial uncertainty of the source increases as the event energy decreases from strong to weak, that is, the error of the simulated source position is affected by the signal-to-noise ratio of the event signal. According to the characteristics of the multi-azimuth shallow well microseismic observation system, a source location objective function is constructed by combining the P-wave and S-wave first arrival times and the P-wave polarization angle of detectable events, and the grid search method is used to obtain the position corresponding to the minimum of the objective function as the source location coordinates. Figure 5 (a) and Figure 5 (b) are the stereogram and plan view of the location results of simulated detectable events. By simulating and comparing the identification and location results of potential microseismic events in the same work area under different observation systems, the microseismic detectability and location error under different observation systems and acquisition conditions can be obtained.

[0126] Example 3

[0127] In a specific Example 3 of applying the present invention, consider the microseismic monitoring situation of multi-stage fracturing in horizontal wells in actual engineering applications. For 1000 microseismic events simulated for multi-stage fracturing in horizontal wells, the length of the simulated fractures in each fracturing stage is 230 - 320 m, the width is 40 - 80 m, the height is 40 - 90 m, and the main direction range of the fractures is 40 - 50 m north by west. The microseismic magnitude of the simulated events and the event frequency satisfy the G-R relationship, with a b value of 1.7, and the microseismic magnitude distribution range is -3.0 to 1.0. In this example, the microseismic event identification ability and location error of the shallow well single-stage observation system are simulated and analyzed. The observation system consists of 24 three-component geophones in random positions in the work area, with a depth of 30 m and a sampling rate of 500 Hz, and is used to simulate the acquisition and analysis of multi-stage fracturing microseismic monitoring data. The observation system is as Figure 6 shown, and the black triangles are the geophone positions.

[0128] According to the relationship between the source and the geophone positions, the monitoring distance of the event can be calculated. The background noise amplitude of the 24 wells is set to gradually increase from east to west, ranging from 5 nm / s to 30 nm / s, the main frequency f0 is 10 Hz, and the longitudinal wave quality factor QP is 100. With a signal-to-noise ratio SNR of 4 db, the lowest moment magnitude that can be reliably monitored by the acquisition scheme composed of these 24 shallow wells is approximately -1.1. Based on the relationship between the microseismic magnitude and the number of detectable events and the monitoring distance (that is, the greater the monitoring distance, the greater the magnitude requirement for detectable events and the fewer the number of detectable events), when the intensity of the microseismic signal with added noise is lower than the detection limit, the corresponding magnitude event is considered undetectable.

[0129] For the target fracturing area, analyze the source location error of detectable signals under the given observation conditions and acquisition parameters. Considering that the spatial uncertainty of the source increases with the decrease of event energy from strong to weak, that is, the error of the simulated source position is affected by the signal-to-noise ratio of the event signal. According to the characteristics of the multi-azimuth shallow well microseismic observation system, a source location objective function is constructed by combining the first arrival times of P-waves and S-waves of detectable events and the P-wave polarization angle, and the position corresponding to the minimum of the objective function is obtained as the source location coordinates by using the grid search method. Figure 7 (a) and Figure 7 (b) are the three-dimensional and planar views of the location results of simulated detectable events. Since the observation system in Example 3 has a larger observation aperture, the positioning error of the microseismic source on the horizontal plane is smaller compared to the observation systems in Examples 1 and 2.

[0130] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are 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 perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

[0131] Except for the technical features described in the specification, the rest are well-known technologies to those skilled in the art.

Claims

1. A design method for a multi-directional shallow well microseismic observation system, characterized in that, The design method of the multi-directional shallow well microseismic observation system includes: Step 1, collect the ground noise records within the target work area; Step 2, establish the initial velocity model of the target work area; Step 3, set parameters such as the number of observation wells, the number of geophones, the level interval, and the sampling rate; Step 4, for the target fracturing area, simulate the possible types and intensities of microseismic signals, and analyze the detectable distance of the induced microseismic signals; Step 5, for the target fracturing area, analyze the source location error of the detectable signals.

2. The design method of the multi-directional shallow well microseismic observation system according to claim 1, characterized in that, In Step 1, collect the background noise records at different azimuths and times within the target work area; Analyze the background noise signals to clarify the potential noise sources and the noise intensity within the work area.

3. The design method of the multi-directional shallow well microseismic observation system according to claim 2, characterized in that, In Step 1, the potential noise sources include operation infrastructure and roads.

4. The design method of the multi-directional shallow well microseismic observation system according to claim 1, characterized in that, In Step 2, establish the initial velocity model of the target work area according to the well logging data and seismic data of the existing wells in the work area.

5. The design method of the multi-directional shallow well microseismic observation system according to claim 4, characterized in that, In Step 2, the well logging data includes the acoustic logging and GR logging curves of the fracturing wells and observation wells, and the seismic data is the 3D seismic profile of the work area. The formation is divided through the seismic profile and the GR logging curve, and the longitudinal and transverse wave velocities of the formation are obtained using the acoustic logging curve.

6. The design method of the multi-directional shallow well microseismic observation system according to claim 1, wherein In Step 3, calculate the relative monitoring distance, the event observation aperture, and the geophone observation aperture between the observation well and the fracturing section through the position of the observation system.

7. The design method of the multi-directional shallow well microseismic observation system according to claim 6, characterized in that, In Step 3, the calculation formula for the relative monitoring distance is Among them, s m (x, y, z) represents the spatial coordinates of the m-th potential seismic source near the fracturing section, and r n (x, y, z) are the spatial coordinates of the n-th level detector; The event observation aperture is the angle between the seismic source event and the line connecting any two geophones, and its calculation formula is as follows where n1 and n2 are the numbers of any two-level geophones, and m is the number of the event; The observation aperture of the geophone is the angle between the geophone and the line connecting any two events, and its calculation formula is as follows where m1 and m2 are the numbers of any two seismic source events, and n is the number of the geophone; The maximum, minimum, and average values of the relative monitoring distance, the event observation aperture, and the geophone observation aperture of the observation system can be obtained according to the relative monitoring distance, the event observation aperture, and the geophone observation aperture calculated by the above formulas.

8. The design method of the multi-directional shallow well microseismic observation system according to claim 1, characterized in that, In Step 4, for the target fracturing area, simulate the possible types and intensities of microseismic signals. In the simulation, the magnitude of the microseismic event and the event frequency satisfy the magnitude-frequency empirical formula, that is, the G-R relationship, as follows lgN(M) = a - bM (4) where N(M) is the number of earthquakes occurring within a certain period in a small interval (M ± ΔM) centered on the magnitude M; a and b are constants, a represents the seismic activity level within the statistical event and region, and the b value represents the proportional relationship between the number of large and small earthquakes; The spatial distribution of the simulated K microseismic events is set within a cube with a length, width, and height of L, W, and D, centered on a spatial coordinate point (x0, y0, z0), and with an angle θ in the clockwise direction from due north as the positive direction.

9. The design method of the multi-directional shallow well microseismic observation system according to claim 8, characterized in that, In step 4, the minimum magnitude of microseismic events that can be monitored by the multi-azimuth shallow well array is related to the spatial distribution of the array, the background noise intensity, the dominant frequency of microseismic events, and the formation properties including the velocity model, quality factor, and density. The detectability of microseismic signals is analyzed by combining the background noise and the attenuation law of seismic magnitude and seismic wave propagation. The intensity of microseismic events can be described by the moment magnitude. The seismic moment M0 of a homogeneous isotropic medium can be estimated according to the following formula In the above formula, v is the wave velocity, r is the distance from the source to the geophone, ρ is the formation density, W0 is the low-frequency cutoff value of the amplitude spectrum, and U is the amplitude radiation characteristic. The low-frequency cutoff value W0 of the amplitude spectrum can be estimated by the following formula In the above formula, f0 is the dominant frequency of microseismic events, and A0 is the amplitude of the effective signal at the source at f0 In the above formula, Q p is the quality factor of the P-wave, t0 is the travel time from the source to the geophone, and A w is the amplitude of the effective signal of the geophone at f0: In the above formula, SNR is the estimated minimum signal-to-noise ratio, and A n is the background noise amplitude of the monitoring area; since the amplitude of the P-wave is generally weaker than that of the S-wave, the P-wave moment magnitude of the monitoring area is usually used to represent the sensitivity of a given geophone in this area; Based on the simulated microseismic magnitude and the magnitude sensitivity of the geophone, at a certain noise level, if the microseismic magnitude that the geophone can detect is greater than the simulated microseismic magnitude, it is considered that the corresponding magnitude event cannot be detected 10. The design method of the multi-directional shallow well microseismic observation system according to claim 9, characterized in that, In step 4, calculate the signal-to-noise ratio of detectable events, and the calculation formula is 11. The design method of the multi-directional shallow well microseismic observation system according to claim 1, characterized in that, In step 5, for the target fracturing area, analyze the source location error of detectable signals. Considering that the spatial uncertainty of source location increases with the decrease of event magnitude energy from strong to weak, that is, the error of the simulated source position is affected by the signal-to-noise ratio of the event signal. According to the signal-to-noise ratio of detectable events calculated in step 4, give the first arrival error and azimuth error under different signal-to-noise ratio conditions 12. The design method of the multi-directional shallow well microseismic observation system according to claim 11, characterized in that, In step 5, according to the characteristics of the multi-azimuth shallow well microseismic observation system, a source location objective function is constructed by combining the first arrival times of P-waves and S-waves and the P-wave polarization angle; the double-phase arrival time difference objective function f ps and the P-phase arrival time difference objective function f p and the S-phase arrival time difference objective function f s can be calculated by the following formula $t_p$ in the formula obs , $t_s$ obs are the observed first arrivals of P-wave and S-wave. $t_p$ cal , $t_s$ cal are the theoretically calculated first arrivals of P-wave and S-wave. $N$ is the number of geophones; The azimuth objective function can be constructed according to the P-wave polarization angle, and the calculation formula is as follows In the formula are respectively the azimuth information recorded by detectors at all levels and obtained through theoretical calculation, and N is the number of detectors; The calculation formula of the final source location objective function is as follows In the above formula, ω1 and ω2 are weighting coefficients. The position corresponding to the minimum of the objective function is obtained by using the grid search or nonlinear search method as the source location coordinates 13. Multi-directional shallow well microseismic observation system design system, characterized in that, The multi-azimuth shallow well microseismic observation system design system uses the multi-azimuth shallow well microseismic observation system design method described in any one of claims 1-12 to simulate microseismic events and analyze the number of detectable microseismic events and the location error of the source position under a potential observation system, and then select the most suitable geophone layout scheme

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