Anisotropic velocity modeling method and device in microseism monitoring scene

Abstract

The invention relates to the technical field of unconventional reservoir ground micro-seismic monitoring data processing, in particular to an anisotropic velocity modeling method and device under a micro-seismic monitoring scenario, and the corresponding method comprises the steps: determining the first arrival of a micro-seismic event in each direction of a fractured well received by a plurality of preset measuring lines, the plurality of measuring lines are radially arranged on the ground, and the fracturing well is located at the center of the radial shape; establishing a horizontal layered medium velocity model according to the acoustic logging curve of the fractured well; and carrying out velocity inversion on the horizontal layered medium velocity model according to the first arrival so as to establish an anisotropic velocity model. The anisotropic velocity modeling method in the micro-seismic monitoring scene, provided by the invention, is oriented to the micro-seismic monitoring scene in a hydraulic fracturing period, can meet the requirements of micro-seismic anisotropic positioning so as to improve the positioning precision, and is simple and efficient in calculation process.

Description

Anisotropic velocity modeling method and device in microseismic monitoring scenarios Technical Field

[0001] This disclosure relates to the field of oil and gas field geological development technology, and particularly to the field of unconventional reservoir surface microseismic monitoring data processing technology, specifically to an anisotropic velocity modeling method, device, equipment, storage medium and computer program in a microseismic monitoring scenario. Background Technology

[0002] Hydraulic fracturing technology is widely used for the efficient development of unconventional reservoirs. The fracturing effect directly affects reservoir production; therefore, a technology is needed to evaluate fracturing effectiveness and guide the design of subsequent fracturing schemes to improve fracturing efficiency and production. Simultaneously, in areas with complex stress, the fracturing process also faces several engineering challenges, such as casing deformation and sand plugging. These engineering problems not only affect the construction progress but may also lead to resource waste due to incomplete fracturing or skipped fracturing stages. To solve fracturing engineering problems and evaluate fracturing effectiveness, geophysicists have developed various types of fracturing monitoring technologies, including microseismic monitoring and wide-area electromagnetic methods, among which microseismic monitoring is the most widely used.

[0003] Existing microseismic monitoring methods primarily rely on the assumption of isotropy for microseismic event location. However, actual geological strata often exhibit weak anisotropy. Using isotropic velocity models for microseismic location often introduces certain errors. Therefore, it is necessary to construct anisotropic velocity models and conduct microseismic location based on these models. Summary of the Invention

[0004] This disclosure provides an anisotropic velocity modeling method, apparatus, equipment, storage medium, and computer program for microseismic monitoring scenarios, effectively solving the technical drawback of calculation errors introduced by the isotropic velocity model used in existing microseismic monitoring technologies.

[0005] Firstly, this disclosure provides an anisotropic velocity modeling method for microseismic monitoring scenarios, including:

[0006] The first arrival of microseismic events at various locations of a fractured well is determined by multiple pre-set survey lines, wherein the multiple survey lines are arranged radially on the ground and the fractured well is located at the center of the radial arrangement.

[0007] A velocity model for horizontal layered media was established based on the sonic logging curves of the fractured well.

[0008] Based on the initial arrival, the velocity model of the horizontal layered medium is inverted to establish an anisotropic velocity model.

[0009] In some embodiments of this disclosure, velocity inversion is performed on the velocity model of the horizontal layered medium based on the first arrival to establish an anisotropic velocity model, including:

[0010] The velocity disturbance range and disturbance interval are determined based on the initial arrival.

[0011] The anisotropic velocity model is established by performing a layer-by-layer velocity scan on the horizontal layered medium velocity model based on the initial arrival, the velocity disturbance range, and the disturbance interval.

[0012] In some embodiments of this disclosure, the horizontal layered medium velocity model is scanned layer by layer according to the initial arrival, the velocity disturbance range, and the disturbance interval to establish the anisotropic velocity model, including:

[0013] Within the velocity disturbance range, determine the difference between the theoretical arrival time and the first arrival time for different disturbance intervals in each orientation;

[0014] The current formation velocity scan rate is determined based on the difference to establish the anisotropic velocity model.

[0015] In some embodiments of this disclosure, determining the initial arrival of microseismic events at various azimuths of the fractured well received by a plurality of preset survey lines includes:

[0016] The seismic records corresponding to the microseismic events are received according to the multiple survey lines;

[0017] The energy of the microseismic events was extracted from the seismic record using both long and short time windows.

[0018] The initial arrival of the microseismic event is determined based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window.

[0019] In some embodiments of this disclosure, determining the initial arrival of a microseismic event based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window includes:

[0020] Determine the energy ratio between the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window;

[0021] When the energy ratio exceeds a first preset threshold, the arrival of the microseismic event is determined based on the current seismic record.

[0022] In some embodiments of this disclosure, a horizontal layered medium velocity model is established based on the sonic logging curves of the fractured well, including:

[0023] A sound wave logging velocity model is established based on the sound wave logging curves.

[0024] The acoustic logging velocity model is smoothed.

[0025] When the change in velocity value in the smoothed sonic logging velocity model exceeds the second preset threshold, the current formation boundary is determined based on the depth corresponding to the current sonic logging curve, so as to establish the velocity model of the horizontal layered medium.

[0026] Secondly, this disclosure provides an anisotropic velocity modeling device for microseismic monitoring scenarios, including:

[0027] The initial arrival determination module is used to determine the initial arrival of microseismic events at various locations of the fractured well received by multiple preset survey lines, wherein the multiple survey lines are arranged radially on the ground and the fractured well is located at the center of the radial arrangement.

[0028] The horizontal layered model establishment module is used to establish a horizontal layered medium velocity model based on the sonic logging curves of the fractured well.

[0029] An anisotropic velocity model establishment module is used to perform velocity inversion on the velocity model of the horizontal layered medium based on the initial arrival, so as to establish an anisotropic velocity model.

[0030] In some embodiments of this disclosure, the anisotropic velocity model establishment module includes:

[0031] A velocity disturbance determination unit is used to determine the velocity disturbance range and disturbance interval based on the initial arrival.

[0032] An anisotropic velocity model establishment unit is used to perform layer-by-layer velocity scanning on the horizontal layered medium velocity model based on the initial arrival, the velocity disturbance range, and the disturbance interval, so as to establish the anisotropic velocity model.

[0033] In some embodiments of this disclosure, the anisotropic velocity model building unit includes:

[0034] The difference determination unit is used to determine the difference between the theoretical arrival time and the first arrival time for different disturbance intervals in each direction under the velocity disturbance range.

[0035] The current formation scanning velocity determination unit is used to determine the current formation velocity scanning velocity based on the difference, so as to establish the anisotropic velocity model.

[0036] In some embodiments of this disclosure, the initial arrival determination module includes:

[0037] The seismic record receiving unit is used to receive seismic records corresponding to the microseismic events based on the multiple survey lines;

[0038] An energy extraction unit is used to extract the energy of the microseismic events from the seismic record according to long and short time windows, respectively.

[0039] The initial arrival determination unit is used to determine the initial arrival of the microseismic event based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window.

[0040] In some embodiments of this disclosure, the initial arrival determination unit includes:

[0041] An energy ratio determination unit is used to determine the energy ratio between the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window;

[0042] The initial arrival determination subunit is used to determine the initial arrival of the microseismic event based on the current seismic record when the energy ratio exceeds a first preset threshold.

[0043] In some embodiments of this disclosure, the horizontal layered model building module includes:

[0044] The acoustic logging velocity model establishment unit is used to establish an acoustic logging velocity model based on the acoustic logging curve.

[0045] A sonic logging velocity model smoothing unit is used to smooth the sonic logging velocity model.

[0046] The current formation boundary determination unit is used to determine the current formation boundary based on the depth corresponding to the current sonic logging curve when the change in velocity value in the smoothed sonic logging velocity model exceeds a second preset threshold, so as to establish the horizontal layered medium velocity model.

[0047] Thirdly, this disclosure provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the foregoing aspects.

[0048] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the methods described in the above aspects.

[0049] Fifthly, this disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the methods described in the above aspects.

[0050] This disclosure provides an anisotropic velocity modeling method, apparatus, equipment, storage medium, and computer program for microseismic monitoring scenarios.

[0051] The corresponding anisotropic velocity modeling method for microseismic monitoring scenarios includes: First, determining the first arrival of microseismic events at various azimuths of the fractured well received by multiple pre-set logging lines, wherein the multiple logging lines are radially arranged on the ground, and the fractured well is located at the center of the radial arrangement; Next, establishing a velocity model of the horizontal layered medium based on the sonic logging curves of the fractured well; Finally, performing velocity inversion on the velocity model of the horizontal layered medium based on the first arrival to establish an anisotropic velocity model.

[0052] The corresponding anisotropic velocity modeling device for microseismic monitoring scenarios includes: an initial arrival determination module, used to determine the initial arrival of microseismic events at various azimuths of the fractured well received by multiple preset logging lines, wherein the multiple logging lines are radially arranged on the ground, and the fractured well is located at the center of the radial arrangement; a horizontal layered model establishment module, used to establish a horizontal layered medium velocity model based on the sonic logging curves of the fractured well; and an anisotropic velocity model establishment module, used to perform velocity inversion on the horizontal layered medium velocity model based on the initial arrival to establish an anisotropic velocity model.

[0053] In summary, the anisotropic velocity modeling method for microseismic monitoring scenarios provided in this disclosure is designed for microseismic monitoring scenarios during hydraulic fracturing. This method can meet the requirements of anisotropic microseismic positioning to improve positioning accuracy, and the calculation process of this method is simple and efficient. Attached Figure Description

[0054] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0055] Figure 1 is a flowchart illustrating an anisotropic velocity modeling method in a microseismic monitoring scenario provided by an embodiment of this disclosure.

[0056] Figure 2 is a flowchart illustrating step 300 provided in an embodiment of this disclosure.

[0057] Figure 3 is a flowchart illustrating step 302 provided in an embodiment of this disclosure.

[0058] Figure 4 is a flowchart illustrating step 100 provided in an embodiment of this disclosure.

[0059] Figure 5 is a flowchart illustrating step 103 provided in an embodiment of this disclosure.

[0060] Figure 6 is a flowchart illustrating step 200 provided in an embodiment of this disclosure.

[0061] Figure 7 is a flowchart illustrating an anisotropic velocity modeling method in a microseismic monitoring scenario provided by the application example of this disclosure.

[0062] Figure 8 is a schematic diagram of the ground radial survey lines (top view) and the spatial distribution in four directions provided by the application example of this disclosure.

[0063] Figure 9 is a schematic diagram of the initial velocity model determined by the sonic logging curve provided in the application example of this disclosure.

[0064] Figure 10 is a schematic diagram of the initial arrival pickup result of the perforation signal provided in the application example of this disclosure.

[0065] Figure 11 is a schematic diagram of the velocity scan time residual curve of the fourth layer medium in orientation 1 provided in the application example of this disclosure.

[0066] Figure 12 is a schematic diagram of the velocity scan time residual curves in four directions of the fourth layer medium provided in the application example of this disclosure.

[0067] Figure 13 is a schematic diagram of the omnidirectional velocity inversion results of the fourth layer medium provided in the application example of this disclosure.

[0068] Figure 14 is a block diagram of an anisotropic velocity modeling device in a microseismic monitoring scenario provided by an embodiment of this disclosure.

[0069] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0070] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0071] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0072] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0073] Example 1

[0074] Velocity modeling is a crucial technique in 3D seismic exploration. This technique primarily constructs velocities through imaging, enabling the creation of velocity models even in complex geological conditions. However, this method is cumbersome, computationally intensive, and requires high illumination of the subsurface along the ground survey lines. In contrast, ground-based microseismic monitoring offers significantly lower illumination compared to 3D seismic exploration, failing to meet the requirements for constructing complex velocity models. Therefore, the velocity modeling methods used in 3D seismic exploration cannot be applied to construct anisotropic velocity models in microseismic exploration.

[0075] Based on this, this disclosure provides an anisotropic velocity modeling method for microseismic monitoring scenarios. Figure 1 is a flowchart illustrating an anisotropic velocity modeling method for microseismic monitoring scenarios provided in this disclosure. As shown in Figure 1, an anisotropic velocity modeling method for microseismic monitoring scenarios includes:

[0076] Step 100: Determine the initial arrival of microseismic events at various locations of the fractured well, which are received by multiple preset survey lines, wherein the multiple survey lines are arranged radially on the ground and the fractured well is located at the center of the radial arrangement;

[0077] Step 200: Establish a velocity model for the horizontal layered medium based on the sonic logging curves of the fractured well;

[0078] Step 300: Perform velocity inversion on the velocity model of the horizontal layered medium based on the initial arrival to establish an anisotropic velocity model.

[0079] This disclosure provides an anisotropic velocity modeling method for microseismic monitoring scenarios, comprising: first, determining the first arrival of microseismic events at various azimuths of a fractured well received by multiple pre-set logging lines, wherein the multiple logging lines are radially arranged on the ground, and the fractured well is located at the center of the radial arrangement; next, establishing a horizontal layered medium velocity model based on the sonic logging curves of the fractured well; and finally, performing velocity inversion on the horizontal layered medium velocity model based on the first arrival to establish an anisotropic velocity model.

[0080] In summary, the anisotropic velocity modeling method for microseismic monitoring scenarios provided in this disclosure is designed for microseismic monitoring scenarios during hydraulic fracturing. This method can meet the requirements of anisotropic microseismic positioning to improve positioning accuracy, and the calculation process of this method is simple and efficient.

[0081] Example 2

[0082] Preferably, the microseismic event is selected from the perforation signal with strong energy in the fractured well. Correspondingly, the first arrival of the perforation signal refers to the earliest seismic wave signal detected by the ground survey line when the seismic wave propagates from the perforation point to the ground survey line, which is generally a P-wave.

[0083] The implementation scenario of step 100 is as follows: The observation system is a radial survey line on the ground, and the center of the radial survey line is the wellhead position of the fractured well. It can be understood that by setting up such an observation system, the velocity in various directions of the fractured well can be obtained, thereby establishing an anisotropic velocity model.

[0084] For step 200, sonic logging is a technique used in geophysical logging that obtains various properties of subsurface rock formations and fluids by measuring the propagation speed of sound waves in the formation. Sonic logging mainly includes two basic parameters: sonic transit time (Δt) and sonic velocity (Vp).

[0085] Acoustic transit time (Δt): This refers to the time difference between when a sound wave is emitted from the transmitter and when it is received by the receiver, measured in microseconds per foot (μs / ft) or microseconds per meter (μs / m). The larger the acoustic transit time, the slower the sound wave travels through the strata, and vice versa.

[0086] Sound velocity (Vp): Sound velocity is the speed at which sound waves propagate through geological formations, measured in meters per second (m / s). Sound velocity can be calculated from known sound travel time and propagation distance. Sonic logging curves have the following applications:

[0087] Lithology identification: Different types of rocks (such as sandstone, limestone, shale, etc.) have different acoustic velocities, and different lithologies can be distinguished by acoustic logging curves.

[0088] Porosity evaluation: Sonic velocity is closely related to the density and porosity of rocks. Sonic logging can indirectly estimate the porosity of rocks, thereby assessing the oil storage potential of reservoirs.

[0089] Formation pressure and stress: Sonic velocity data can be used to analyze formation pressure and stress conditions, helping to predict wellbore stability and prevent accidents such as blowouts.

[0090] Seismic correction: Sonic logging data can be used for velocity model correction in seismic exploration, improving the accuracy of seismic data interpretation.

[0091] In step 200, the formation boundary is set at the place where the velocity values ​​of the sonic logging curves are significantly different, in order to determine the depth boundary of different formations and thus establish a horizontal layered medium velocity model. However, it should be noted that the horizontal layered medium velocity model only simulates part of the formation around the wall of the fractured well and is only a velocity model in one direction of the fractured well, and does not have anisotropic characteristics.

[0092] For step 300, firstly, the azimuth interval is set according to the first arrival, and the receiving channels at different azimuths are determined. Finally, based on the high-energy perforation signal, tomographic imaging is performed on the survey lines at different azimuths according to the first arrival and the velocity model of the horizontal layered medium to invert the velocity field at different azimuths.

[0093] Example 3

[0094] Based on the above embodiments, referring to Figure 2, step 300 of an anisotropic velocity modeling method in a microseismic monitoring scenario includes:

[0095] Step 301: Determine the velocity disturbance range and disturbance interval based on the initial arrival;

[0096] Determine the appropriate velocity disturbance range and disturbance interval for that azimuth based on the first arrival at the corresponding azimuth.

[0097] Step 302: Perform layer-by-layer velocity scanning on the horizontal layered medium velocity model based on the initial arrival, the velocity disturbance range, and the disturbance interval to establish the anisotropic velocity model.

[0098] A velocity perturbation sequence is generated based on the velocity perturbation range and perturbation interval. Specifically, the depth range and initial velocity of each layer in the horizontal layered medium velocity model are determined. Then, a velocity perturbation sequence is generated based on the initial velocity, perturbation range, and perturbation interval. For example, if the initial velocity is 2000 m / s, the perturbation range is ±10%, and the perturbation interval is 1%, then [1800, 1820, ..., 2180, 2200] m / s is generated.

[0099] Next, for each disturbance velocity value, a forward modeling simulation of seismic waves is performed (preferably, the finite element method or ray tracing method is used to simulate the propagation of seismic waves).

[0100] The simulation results are compared with actual observation data, and the error is determined by calculating the root mean square error (RMSE). The velocity with the smallest error is selected as the update velocity for that layer. After completing the velocity scan and selecting the optimal velocity for each layer, the entire velocity model is updated.

[0101] Based on the above embodiments, referring to Figure 3, step 302 of an anisotropic velocity modeling method in a microseismic monitoring scenario includes:

[0102] Step 3021: Under the velocity disturbance range, determine the difference between the theoretical arrival time and the first arrival time for different disturbance intervals in each orientation;

[0103] Step 3022: Determine the current formation velocity scan rate based on the difference to establish the anisotropic velocity model.

[0104] In steps 3021 and 2022, based on the initial velocity model (horizontal layered medium velocity model), the velocity perturbation range and interval are set, and velocity scanning is performed layer by layer to invert the velocity field. The receiver channel with the azimuth at the i-th azimuth is selected. Based on the scanned velocity values, the travel time from the perforation point to each receiver channel within that azimuth is calculated using ray tracing. The difference between the calculated travel time and the actual travel time is calculated. According to the velocity-time difference curve, the velocity field corresponding to the value with the smallest time difference is selected as the current inverted velocity value. It should be noted that, each time the velocities of other strata are fixed, only one layer's velocity is perturbed and scanned to obtain the optimal velocity. This process is repeated to obtain the velocity values ​​of all layers within the i-th azimuth.

[0105] Using the same method, the velocity field in all directions can be obtained. This completes the modeling of anisotropic velocities in all directions.

[0106] Example 4

[0107] Based on the above embodiments, referring to Figure 4, step 100 of an anisotropic velocity modeling method in a microseismic monitoring scenario includes:

[0108] Step 101: Receive the seismic records corresponding to the microseismic events according to the multiple survey lines;

[0109] Understandably, the earthquake records in step 101 are from multiple directions.

[0110] Step 102: Extract the energy of the microseismic events from the seismic record according to both long and short time windows;

[0111] Short time window (STA): preferably 3 seconds, used to capture the instantaneous energy changes when seismic waves arrive.

[0112] Long Term Window (LTA): Preferably 35 seconds to 2.5 minutes, used to estimate the average energy level of background noise.

[0113] Step 103: Determine the initial arrival of the microseismic event based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window.

[0114] In steps 102 and 103, a perforation signal with relatively strong energy is selected, and its arrival time is captured. Specifically, the energy variation of the seismic signal is reflected by calculating the energy ratio of the long-term window (LTA) and the short-term window (STA) for a test point on the seismic record. The calculation method for the long and short time windows is as follows:

[0115]

[0116] Based on the above embodiments, referring to Figure 5, step 103 of an anisotropic velocity modeling method in a microseismic monitoring scenario includes:

[0117] Step 1031: Determine the energy ratio between the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window;

[0118] Step 1032: When the energy ratio exceeds the first preset threshold, determine the initial arrival of the microseismic event based on the current seismic record.

[0119] In steps 1031 and 1032, when a valid seismic event arrives, the STA / LTA ratio will suddenly increase sharply. If this ratio is greater than a predetermined threshold (2 to 4), it is considered that the initial movement of a valid microseismic event has been detected at this moment.

[0120] Once the energy ratio of the long time window (LTA) to the short time window (STA) exceeds a threshold, the start time of the event is recorded. Alternatively, false alarms can be reduced by setting a duration requirement (e.g., the energy ratio of the long time window (LTA) to the short time window (STA) must be greater than a threshold for a continuous number of seconds).

[0121] Based on the above embodiments, referring to Figure 6, step 200 of an anisotropic velocity modeling method in a microseismic monitoring scenario includes:

[0122] Step 201: Establish an acoustic logging velocity model based on the acoustic logging curves;

[0123] Step 202: Smooth the acoustic logging velocity model;

[0124] Step 203: When the change in velocity value in the smoothed sonic logging velocity model exceeds the second preset threshold, determine the current formation boundary line according to the depth corresponding to the current sonic logging curve, so as to establish the velocity model of the horizontal layered medium.

[0125] In steps 201 to 203, firstly, the acoustic logging data of the work area is read, and the acoustic logging velocity model V is obtained using the acoustic time difference δt.

[0126] V = 1 / δt

[0127] Next, the sonic logging velocity model is smoothed. Specifically, the velocity curve in the sonic logging data is converted to the frequency domain by Fourier transform to remove high-frequency noise, and then the smoothed velocity curve is obtained by inverse Fourier transform back to the time domain.

[0128] Finally, based on the smoothed velocity model, areas where velocity values ​​differ significantly are designated as stratigraphic boundaries. Thus, a velocity model for horizontally layered media can be obtained.

[0129] This disclosure provides an anisotropic velocity modeling method for microseismic monitoring scenarios, comprising: first, determining the first arrival of microseismic events at various azimuths of a fractured well received by multiple pre-set logging lines, wherein the multiple logging lines are radially arranged on the ground, and the fractured well is located at the center of the radial arrangement; next, establishing a horizontal layered medium velocity model based on the sonic logging curves of the fractured well; and finally, performing velocity inversion on the horizontal layered medium velocity model based on the first arrival to establish an anisotropic velocity model.

[0130] In summary, the anisotropic velocity modeling method for microseismic monitoring scenarios provided in this disclosure is geared towards microseismic monitoring during hydraulic fracturing. Compared to existing sonic logging velocity models in microseismic monitoring, this method considers the characteristics of azimuth anisotropy and the advantages of surface radial logging for microseismic monitoring, improving the location accuracy of microseismic events in weakly anisotropic formations. Compared to existing 3D seismic anisotropic velocity modeling techniques, it eliminates the need for 3D seismic imaging. Furthermore, this method is simple to operate and meets the requirements of microseismic monitoring in anisotropic media.

[0131] Example 5

[0132] To further illustrate the solution, based on the above embodiments, this embodiment takes the acquisition of perforation signals from fractured well A as an example to provide an application example, in order to further explain an anisotropic velocity modeling method in a microseismic monitoring scenario. See Figure 7. This method includes the following:

[0133] This disclosure pertains to the field of surface microseismic monitoring data processing for unconventional reservoirs. Specifically, it targets surface radial seismic monitoring, employing azimuth-based tomographic imaging to invert velocity fields at different azimuths and establish a velocity model with anisotropic characteristics.

[0134] Specifically, in order to meet the needs of microseismic monitoring in anisotropic media, this disclosure proposes an anisotropic velocity modeling method in microseismic monitoring scenarios, based on ground radial survey line microseismic monitoring and with tomographic imaging algorithm as the core.

[0135] Step S1: Determine the azimuth of each ground receiving channel based on the ground radial survey line observation system.

[0136] Read the ground radial survey line observation system (see Figure 8) to obtain the spatial coordinates (x, y) of each receiving channel. i y i , z i Using the center point of the observation system as the center (x0, y0, z0), calculate the azimuth angle of each receiving channel. The calculation method is as follows:

[0137]

[0138] For receiving points located in the second and third quadrants, find their symmetrical points about the center point (x0, y0, z0) of the observation system. The method is as follows:

[0139] (x i ,y i )→(x0-x i ,y0-y i )

[0140] The azimuth of the converted points is then calculated. Through this calculation, the azimuth angle of each receiving channel can be obtained.

[0141] S2: Arrival time of the perforation signal.

[0142] A high-energy perforation signal is selected, and the arrival time of the perforation signal is picked up using the long-term / short-term window energy ratio method. This method reflects the energy variation of the seismic signal by calculating the energy ratio of the long-term window (LTA) and the short-term window (STA) for a test point on the seismic record. The calculation method for the long-term and short-term windows is as follows:

[0143]

[0144] When a valid seismic event arrives, the STA / LTA ratio will suddenly increase sharply. If this ratio is greater than a predetermined threshold, it is considered that a valid microseismic event has been detected at this moment.

[0145] S3: Establish the initial velocity model.

[0146] Read the acoustic logging data of the work area and use the acoustic time difference δt to obtain the acoustic logging velocity model V.

[0147] V = 1 / δt

[0148] The sonic logging velocity model is smoothed, and based on the smoothed velocity model, areas where velocity values ​​differ significantly are designated as formation boundaries. Therefore, a velocity model for the horizontally layered medium can be obtained (initial velocity model, see Figure 9).

[0149] S4: Perform tomographic imaging on the received records in each direction to obtain the velocity field in each direction.

[0150] Specifically, taking true north as zero degrees, rotating clockwise, true east is 90° and true south is 180°. The space from 0° to 180° is divided into N directions, where the angle range of the i-th direction is [(i-1)*180 / N, i*180 / N], where i = 1, 2, ..., N.

[0151] Based on the initial velocity model, the velocity perturbation range and interval are set, and velocity scanning is performed layer by layer to invert the velocity field. The receiver channel at the i-th azimuth is selected. Based on the scanned velocity values, ray tracing is used to calculate the travel time from the perforation point to each receiver channel within that azimuth. The calculated travel time is then differed from the actual travel time. According to the velocity-time difference curve, the velocity field corresponding to the minimum time difference is selected as the current inverted velocity value. It is worth noting that, each time the velocities of other formations are fixed, only one layer's velocity is perturbed and scanned to obtain the optimal velocity. This process is repeated to obtain the velocity values ​​of all layers within the i-th azimuth.

[0152] Using the same method, the velocity field in all directions can be obtained. This completes the modeling of anisotropic velocities in all directions.

[0153] Results demonstration: The observation system used for fracturing is shown in Figure 8, which has 14 measuring lines and calculates the azimuth of each receiving point. The space is divided into 4 azimuths: (0°-45°), (45°-90°), (90°-135°), and (135°-180°).

[0154] Based on the azimuth calculation results and the azimuth sub-situation, the receiving channels in different directions can be obtained, as shown in Figure 8. Different colors represent different azimuth channels.

[0155] Next, the initial velocity model obtained using sonic logging is shown in Figure 9. The blue line represents the sonic logging curve, and the red line represents the smoothed logging curve. The formation is divided into 9 layers, and the velocity curve for each layer is shown as the black line in Figure 10. The first arrival of the perforation signal is automatically calculated, as shown by the red dots in Figure 10. Based on the calculation results in Figure 8, the first arrival time of the receiving seismic trace corresponding to the first azimuth (0°-45°) receiver is selected. The scanning range of the fourth layer velocity in the velocity model is set to 3000m / s-6000m / s, with a velocity scanning interval of 20m / s, while the velocity values ​​of other layers remain unchanged. The time difference between the theoretical arrival time and the actual arrival time at different velocities is determined by ray tracing, and the calculation results are shown in Figure 11. As can be seen from Figure 11, there exists a velocity (shown as red *) that minimizes the time difference between the theoretical and actual arrival times. The velocity corresponding to the minimum time residual is then used as the inverted velocity value.

[0156] Using the same method, the velocities in the four directions of the fourth layer were scanned to obtain the time residuals in each direction, as shown in Figure 12. Figure 12 shows that the optimal velocity can be retrieved for each direction. Based on the optimal velocities in the four directions, the azimuth velocity inversion results for the fourth layer are now complete, as shown in Figure 13. Using the same method, the inversion of azimuth anisotropic velocities for all layers can be achieved.

[0157] This disclosure provides an anisotropic velocity modeling method for microseismic monitoring scenarios, comprising: first, determining the first arrival of microseismic events at various azimuths of a fractured well received by multiple pre-set logging lines, wherein the multiple logging lines are radially arranged on the ground, and the fractured well is located at the center of the radial arrangement; next, establishing a horizontal layered medium velocity model based on the sonic logging curves of the fractured well; and finally, performing velocity inversion on the horizontal layered medium velocity model based on the first arrival to establish an anisotropic velocity model.

[0158] Specifically, firstly, the azimuth of the surface logging lines is calculated based on the location of the radial logging lines and the center of the fractured well. Then, the arrival time of the first arrival wave is picked up based on the strong perforation signal. Secondly, the acoustic logging curves are smoothed to form an initial horizontal layered medium velocity model. Then, azimuth intervals are set to determine the receiving channels at different azimuths. Finally, based on the perforation signal, tomographic imaging is performed on the logging lines at different azimuths to invert the velocity field at each azimuth.

[0159] In summary, the anisotropic velocity modeling method for microseismic monitoring scenarios provided in this disclosure conducts velocity scanning based on different orientations to form a weakly anisotropic velocity model construction method for ground microseismic monitoring, so as to locate microseismic events in weakly anisotropic media.

[0160] Example 6

[0161] Based on the same inventive concept, this application also provides an anisotropic velocity modeling device for microseismic monitoring scenarios, which can be used to implement the methods described in the above embodiments, as shown in the following embodiments. Since the principle of the anisotropic velocity modeling device for microseismic monitoring scenarios is similar to that of the anisotropic velocity modeling method for microseismic monitoring scenarios, the implementation of the anisotropic velocity modeling device for microseismic monitoring scenarios can refer to the implementation of the anisotropic velocity modeling method for microseismic monitoring scenarios, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0162] The embodiments of this disclosure provide a specific implementation of an anisotropic velocity modeling device for microseismic monitoring scenarios, capable of realizing anisotropic velocity modeling methods in microseismic monitoring scenarios. Referring to Figure 14, an anisotropic velocity modeling device for microseismic monitoring scenarios includes:

[0163] The initial arrival determination module 10 is used to determine the initial arrival of microseismic events at various locations of the fractured well received by multiple preset survey lines, wherein the multiple survey lines are arranged radially on the ground and the fractured well is located at the center of the radial arrangement.

[0164] The horizontal layered model establishment module 20 is used to establish a horizontal layered medium velocity model based on the sonic logging curve of the fractured well.

[0165] An anisotropic velocity model establishment module 30 is used to perform velocity inversion on the horizontal layered medium velocity model based on the initial arrival to establish an anisotropic velocity model.

[0166] In some embodiments of this disclosure, the anisotropic velocity model establishment module includes:

[0167] A velocity disturbance determination unit is used to determine the velocity disturbance range and disturbance interval based on the initial arrival.

[0168] An anisotropic velocity model establishment unit is used to perform layer-by-layer velocity scanning on the horizontal layered medium velocity model based on the initial arrival, the velocity disturbance range, and the disturbance interval, so as to establish the anisotropic velocity model.

[0169] In some embodiments of this disclosure, the anisotropic velocity model building unit includes:

[0170] The difference determination unit is used to determine the difference between the theoretical arrival time and the first arrival time for different disturbance intervals in each direction under the velocity disturbance range.

[0171] The current formation scanning velocity determination unit is used to determine the current formation velocity scanning velocity based on the difference, so as to establish the anisotropic velocity model.

[0172] In some embodiments of this disclosure, the initial arrival determination module includes:

[0173] The seismic record receiving unit is used to receive seismic records corresponding to the microseismic events based on the multiple survey lines;

[0174] An energy extraction unit is used to extract the energy of the microseismic events from the seismic record according to long and short time windows, respectively.

[0175] The initial arrival determination unit is used to determine the initial arrival of the microseismic event based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window.

[0176] In some embodiments of this disclosure, the initial arrival determination unit includes:

[0177] An energy ratio determination unit is used to determine the energy ratio between the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window;

[0178] The initial arrival determination subunit is used to determine the initial arrival of the microseismic event based on the current seismic record when the energy ratio exceeds a first preset threshold.

[0179] In some embodiments of this disclosure, the horizontal layered model building module includes:

[0180] The acoustic logging velocity model establishment unit is used to establish an acoustic logging velocity model based on the acoustic logging curve.

[0181] A sonic logging velocity model smoothing unit is used to smooth the sonic logging velocity model.

[0182] The current formation boundary determination unit is used to determine the current formation boundary based on the depth corresponding to the current sonic logging curve when the change in velocity value in the smoothed sonic logging velocity model exceeds a second preset threshold, so as to establish the horizontal layered medium velocity model.

[0183] An anisotropic velocity modeling device for microseismic monitoring scenarios provided in this embodiment includes: an initial arrival determination module, used to determine the initial arrival of microseismic events at various locations of a fractured well received by multiple preset logging lines, wherein the multiple logging lines are radially arranged on the ground, and the fractured well is located at the center of the radial arrangement; a horizontal layered model establishment module, used to establish a horizontal layered medium velocity model based on the sonic logging curves of the fractured well; and an anisotropic velocity model establishment module, used to perform velocity inversion on the horizontal layered medium velocity model based on the initial arrival to establish an anisotropic velocity model.

[0184] In summary, the anisotropic velocity modeling method for microseismic monitoring scenarios provided in this disclosure, which is designed for microseismic monitoring during hydraulic fracturing, can meet the requirements for anisotropic microseismic positioning, thereby improving positioning accuracy. Furthermore, the implementation process of this device is simple and efficient.

[0185] Example 7

[0186] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0187] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the steps of the method described in the above embodiments, specifically including the following:

[0188] The first arrival of microseismic events at various locations of a fractured well is determined by multiple pre-set survey lines, wherein the multiple survey lines are arranged radially on the ground and the fractured well is located at the center of the radial arrangement.

[0189] A velocity model for horizontal layered media was established based on the sonic logging curves of the fractured well.

[0190] Based on the initial arrival, the velocity model of the horizontal layered medium is inverted to establish an anisotropic velocity model.

[0191] In some embodiments of this disclosure, velocity inversion is performed on the velocity model of the horizontal layered medium based on the first arrival to establish an anisotropic velocity model, including:

[0192] The velocity disturbance range and disturbance interval are determined based on the initial arrival.

[0193] The anisotropic velocity model is established by performing a layer-by-layer velocity scan on the horizontal layered medium velocity model based on the initial arrival, the velocity disturbance range, and the disturbance interval.

[0194] In some embodiments of this disclosure, the horizontal layered medium velocity model is scanned layer by layer according to the initial arrival, the velocity disturbance range, and the disturbance interval to establish the anisotropic velocity model, including:

[0195] Within the velocity disturbance range, determine the difference between the theoretical arrival time and the first arrival time for different disturbance intervals in each orientation;

[0196] The current formation velocity scan rate is determined based on the difference to establish the anisotropic velocity model.

[0197] In some embodiments of this disclosure, determining the initial arrival of microseismic events at various azimuths of the fractured well received by a plurality of preset survey lines includes:

[0198] The seismic records corresponding to the microseismic events are received according to the multiple survey lines;

[0199] The energy of the microseismic events was extracted from the seismic record using both long and short time windows.

[0200] The initial arrival of the microseismic event is determined based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window.

[0201] In some embodiments of this disclosure, determining the initial arrival of a microseismic event based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window includes:

[0202] Determine the energy ratio between the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window;

[0203] When the energy ratio exceeds a first preset threshold, the arrival of the microseismic event is determined based on the current seismic record.

[0204] In some embodiments of this disclosure, a horizontal layered medium velocity model is established based on the sonic logging curves of the fractured well, including:

[0205] A sound wave logging velocity model is established based on the sound wave logging curves.

[0206] The acoustic logging velocity model is smoothed.

[0207] When the change in velocity value in the smoothed sonic logging velocity model exceeds the second preset threshold, the current formation boundary is determined based on the depth corresponding to the current sonic logging curve, so as to establish the velocity model of the horizontal layered medium.

[0208] In some embodiments of this example, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described in the above embodiments, specifically including the following:

[0209] The first arrival of microseismic events at various locations of a fractured well is determined by multiple pre-set survey lines, wherein the multiple survey lines are arranged radially on the ground and the fractured well is located at the center of the radial arrangement.

[0210] A velocity model for horizontal layered media was established based on the sonic logging curves of the fractured well.

[0211] Based on the initial arrival, the velocity model of the horizontal layered medium is inverted to establish an anisotropic velocity model.

[0212] In some embodiments of this disclosure, velocity inversion is performed on the velocity model of the horizontal layered medium based on the first arrival to establish an anisotropic velocity model, including:

[0213] The velocity disturbance range and disturbance interval are determined based on the initial arrival.

[0214] The anisotropic velocity model is established by performing a layer-by-layer velocity scan on the horizontal layered medium velocity model based on the initial arrival, the velocity disturbance range, and the disturbance interval.

[0215] In some embodiments of this disclosure, the horizontal layered medium velocity model is scanned layer by layer according to the initial arrival, the velocity disturbance range, and the disturbance interval to establish the anisotropic velocity model, including:

[0216] Within the velocity disturbance range, determine the difference between the theoretical arrival time and the first arrival time for different disturbance intervals in each orientation;

[0217] The current formation velocity scan rate is determined based on the difference to establish the anisotropic velocity model.

[0218] In some embodiments of this disclosure, determining the initial arrival of microseismic events at various azimuths of the fractured well received by a plurality of preset survey lines includes:

[0219] The seismic records corresponding to the microseismic events are received according to the multiple survey lines;

[0220] The energy of the microseismic events was extracted from the seismic record using both long and short time windows.

[0221] The initial arrival of the microseismic event is determined based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window.

[0222] In some embodiments of this disclosure, determining the initial arrival of a microseismic event based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window includes:

[0223] Determine the energy ratio between the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window;

[0224] When the energy ratio exceeds a first preset threshold, the arrival of the microseismic event is determined based on the current seismic record.

[0225] In some embodiments of this disclosure, a horizontal layered medium velocity model is established based on the sonic logging curves of the fractured well, including:

[0226] A sound wave logging velocity model is established based on the sound wave logging curves.

[0227] The acoustic logging velocity model is smoothed.

[0228] When the change in velocity value in the smoothed sonic logging velocity model exceeds the second preset threshold, the current formation boundary is determined based on the depth corresponding to the current sonic logging curve, so as to establish the velocity model of the horizontal layered medium.

[0229] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods in the above embodiments.

[0230] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0231] Computer-readable storage media may also store at least one computer-executable program, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0232] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0233] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0234] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0235] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0236] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0237] While the embodiments disclosed herein are as described above, the foregoing content is merely for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Any person skilled in the art to which this disclosure pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope of this disclosure; however, the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.

Claims

1. A method for modeling anisotropic velocity in a microseismic monitoring scenario, characterized in that, include: The first arrival of microseismic events at various locations of the fractured well, received by multiple pre-set survey lines, is determined. The multiple survey lines are arranged radially on the ground, and the fractured well is located at the center of the radial arrangement. A horizontal layered medium velocity model is established based on the sonic logging curves of the fractured well. Based on the first arrival, the velocity model of the horizontal layered medium is inverted to establish an anisotropic velocity model.

2. The anisotropic velocity modeling method according to claim 1, characterized in that, Based on the first arrival, a velocity inversion is performed on the velocity model of the horizontal layered medium to establish an anisotropic velocity model, including: determining the velocity perturbation range and perturbation interval based on the first arrival; and performing a layer-by-layer velocity scan on the velocity model of the horizontal layered medium based on the first arrival, the velocity perturbation range, and the perturbation interval to establish the anisotropic velocity model.

3. The anisotropic velocity modeling method according to claim 2, characterized in that, The anisotropic velocity model is established by performing a layer-by-layer velocity scan on the horizontal layered medium velocity model based on the first arrival, the velocity disturbance range, and the disturbance interval. This includes: determining the difference between the theoretical arrival time of different disturbance intervals in each orientation and the first arrival within the velocity disturbance range; and determining the current formation velocity scan speed based on the difference to establish the anisotropic velocity model.

4. The anisotropic velocity modeling method according to claim 1, characterized in that, The determination of the initial arrival of microseismic events at various locations of the fractured well, received by multiple preset survey lines, includes: receiving seismic records corresponding to the microseismic events from the multiple survey lines; extracting the energy of the microseismic events from the seismic records according to long and short time windows respectively; and determining the initial arrival of the microseismic events based on the energy of the microseismic events under the long time window and the energy of the microseismic events under the short time window.

5. The anisotropic velocity modeling method according to claim 4, characterized in that, Determining the initial arrival of a microseismic event based on the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window includes: determining the energy ratio between the energy of the microseismic event under the long time window and the energy of the microseismic event under the short time window; and when the energy ratio exceeds a first preset threshold, determining the initial arrival of the microseismic event based on the current seismic record.

6. The anisotropic velocity modeling method according to any one of claims 1 to 5, characterized in that, Establishing a horizontal layered medium velocity model based on the sonic logging curve of the fractured well includes: establishing a sonic logging velocity model based on the sonic logging curve; smoothing the sonic logging velocity model; when the change in velocity value in the smoothed sonic logging velocity model exceeds a second preset threshold, determining the current formation boundary based on the depth corresponding to the current sonic logging curve, so as to establish the horizontal layered medium velocity model.

7. An anisotropic velocity modeling device for microseismic monitoring scenarios, characterized in that, include: The initial arrival determination module is used to determine the initial arrival of microseismic events at various locations of the fractured well received by multiple preset survey lines, wherein the multiple survey lines are arranged radially on the ground and the fractured well is located at the center of the radial arrangement. The horizontal layered model establishment module is used to establish a horizontal layered medium velocity model based on the sonic logging curve of the fractured well; the anisotropic velocity model establishment module is used to perform velocity inversion on the horizontal layered medium velocity model based on the first arrival to establish an anisotropic velocity model.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the anisotropic velocity modeling method in the microseismic monitoring scenario according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the anisotropic velocity modeling method for microseismic monitoring scenarios as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the anisotropic velocity modeling method for microseismic monitoring scenarios as described in any one of claims 1 to 6.

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