Processing method and device for tomographic inversion velocity

Abstract

This application discloses a method and apparatus for processing tomographic inversion velocities, belonging to the field of geophysical exploration technology. The method includes: obtaining micrologging data based on data from the area to be studied; for any micrologging well, establishing a tomographic inversion velocity model based on the seismic data of the micrologging well, and obtaining multiple tomographic inversion velocities of the micrologging well based on the tomographic inversion velocity model and the near-surface medium velocity data of the micrologging well, wherein each tomographic inversion velocity corresponds one-to-one with a velocity layer and is located at the same position as the near-surface medium velocity in each velocity layer; determining the relationship between the tomographic inversion velocity and the near-surface medium velocity based on the number of micrologging wells, the multiple near-surface medium velocities of each micrologging well, and the multiple tomographic inversion velocities of each micrologging well. This method can process the tomographic inversion velocity to reduce the error between the tomographic inversion velocity and the near-surface medium velocity.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration technology, and in particular to a method and apparatus for processing tomographic inversion velocities. Background Technology

[0002] Currently, in seismic exploration, there are various tomographic velocity inversion methods based on ray theory and wave theory to extract velocity parameters. These methods can retrieve tomographic inversion velocities. Since actual near-surface medium velocities are difficult to measure, tomographic inversion velocities are typically used as a substitute for near-surface medium velocities in pre-stack depth migration inversion modeling.

[0003] However, due to interference from external factors or the influence of different grid definition values, the inverted tomographic inversion velocity may differ from the actual near-surface medium velocity, resulting in significant errors in pre-stack depth migration inversion modeling and affecting the quality of seismic tomography. Therefore, it is necessary to process the tomographic inversion velocity. Summary of the Invention

[0004] This application provides a method and apparatus for processing tomographic inversion velocities, which can process tomographic inversion velocities to reduce the error between tomographic inversion velocities and near-surface medium velocities.

[0005] Specifically, the following technical solutions are included:

[0006] On one hand, embodiments of this application provide a method for processing tomographic inversion speed, the method comprising:

[0007] Based on the data of the area to be studied, micrologging data is obtained. The micrologging data includes the number of micrologging wells, the seismic data of each micrologging well, and the near-surface medium velocity data of each micrologging well. For any micrologging well, the micrologging well includes multiple velocity layers. The velocity layer refers to the stratum used to characterize the medium velocity. The near-surface medium velocity data includes multiple near-surface medium velocities of the micrologging well, and the near-surface medium velocity corresponds one-to-one with the velocity layer.

[0008] For any microlog, a tomographic inversion velocity model is established based on the seismic data of the microlog, and multiple tomographic inversion velocities of the microlog are obtained based on the tomographic inversion velocity model and the near-surface medium velocity data of the microlog. The tomographic inversion velocities correspond one-to-one with the velocity layers and are in the same position as the near-surface medium velocity in each velocity layer.

[0009] Based on the number of micrologs, the multiple near-surface medium velocities of each microlog, and the multiple tomographic inversion velocities of each microlog, the relationship between the tomographic inversion velocity and the near-surface medium velocity is determined.

[0010] In some embodiments, determining the relationship between the tomographic inversion velocity and the near-surface medium velocity based on the number of micrologging wells, multiple near-surface medium velocities of each micrologging well, and multiple tomographic inversion velocities of each micrologging well includes:

[0011] Based on the number of micrologs, the multiple near-surface medium velocities of each microlog and the multiple tomographic inversion velocities of each microlog, a set of near-surface medium velocities and a set of tomographic inversion velocities are obtained.

[0012] Polynomial fitting is performed on the near-surface medium velocity set and the tomographic inversion velocity set to obtain the relationship curve and fitting formula between the tomographic inversion velocity and the near-surface medium velocity.

[0013] The fitting formula is expressed as follows:

[0014]

[0015] In the formula: V c This represents the corrected near-surface medium velocity, V. tom This represents the tomographic inversion rate, a i Let i be the coefficient of the polynomial, 0 ≤ i ≤ n, and n be the degree of the polynomial.

[0016] In some embodiments, establishing a tomographic inversion velocity model based on the seismic data from the micrologging well includes:

[0017] An initial model was established based on the seismic data from the micro-logging wells.

[0018] Based on the first arrival data, the initial model, and the second offset, the tomographic inversion velocity model is established, wherein the first arrival data is obtained by picking the first arrival time of each shot by setting a first offset, and the second offset is not greater than the first offset.

[0019] In some embodiments, the seismic data from the micrologging includes surface initiation velocity and velocity gradient, and the establishment of an initial model based on the seismic data from the micrologging includes:

[0020] The initial model is established based on the surface initiation velocity and velocity gradient obtained from the micrologging.

[0021] In some embodiments, the area to be studied is the region where the same lithological body is located.

[0022] On the other hand, embodiments of this application also provide a processing apparatus for tomographic inversion speed, the apparatus comprising:

[0023] The data acquisition module is used to obtain microlog data based on the data of the area to be studied. The microlog data includes the number of micrologs, the seismic data of each microlog, and the near-surface medium velocity data of each microlog. For any microlog, the microlog includes multiple velocity layers, which refer to the formation used to characterize the medium velocity. The near-surface medium velocity data includes multiple near-surface medium velocities of the microlog, and the near-surface medium velocities correspond one-to-one with the velocity layers.

[0024] The model building module is used to establish a tomographic inversion velocity model for any micrologging well based on the seismic data of the micrologging well, and to obtain multiple tomographic inversion velocities of the micrologging well based on the tomographic inversion velocity model and the near-surface medium velocity data of the micrologging well. The tomographic inversion velocities correspond one-to-one with the velocity layers and are at the same position as the near-surface medium velocity in each velocity layer.

[0025] The relationship determination module is used to determine the relationship between the tomographic inversion velocity and the near-surface medium velocity based on the number of micrologs, multiple near-surface medium velocities of each microlog, and multiple tomographic inversion velocities of each microlog.

[0026] In some embodiments, the relationship determination module includes:

[0027] The velocity set acquisition unit is used to obtain a near-surface medium velocity set and a tomographic inversion velocity set based on the number of micrologs, multiple near-surface medium velocities of each microlog and multiple tomographic inversion velocities of each microlog;

[0028] The fitting unit is used to perform polynomial fitting on the near-surface medium velocity set and the tomographic inversion velocity set to obtain the relationship curve and fitting formula between the tomographic inversion velocity and the near-surface medium velocity.

[0029] The fitting formula is expressed as follows:

[0030]

[0031] In the formula: V c This represents the corrected near-surface medium velocity, V. tom This represents the tomographic inversion rate, a i Let i be the coefficient of the polynomial, 0 ≤ i ≤ n, and n be the degree of the polynomial.

[0032] In some embodiments, the model building module includes:

[0033] The first model building unit is used to build an initial model based on the seismic data from the micro-logging well.

[0034] The second model building unit is used to build the tomographic inversion velocity model based on the first arrival data, the initial model, and the second offset, wherein the first arrival data is obtained by picking the first arrival time of each shot by setting a first offset, and the second offset is not greater than the first offset.

[0035] In some embodiments, the seismic data from the micrologging includes surface initiation velocity and velocity gradient, and the first model building unit includes:

[0036] The initial model is established based on the surface initiation velocity and velocity gradient obtained from the micrologging.

[0037] In some embodiments, the area to be studied is the region where the same lithological body is located.

[0038] The tomographic inversion velocity processing method provided in this application involves obtaining microlog data based on data from the area under study. For any microlog, a tomographic inversion velocity model can be constructed using the seismic data of that well. Then, based on this model and near-surface medium velocity data, multiple tomographic inversion velocities from the microlog are obtained. Finally, based on the number of micrologs, the tomographic inversion velocity of each microlog, and the near-surface medium velocity of each microlog, the relationship between the tomographic inversion velocity and the near-surface medium velocity is determined. Since this relationship characterizes the relationship and trend between the tomographic inversion velocity and the near-surface medium velocity, it can be used to correct the tomographic inversion velocity, reducing the error between the tomographic inversion velocity and the near-surface medium velocity. This avoids large errors in pre-stack depth migration inversion modeling and ensures the imaging quality of pre-stack depth migration. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 A flowchart illustrating a method for processing tomographic inversion velocity provided in an embodiment of this application;

[0041] Figure 2 A flowchart of another method for processing tomographic inversion velocity provided in an embodiment of this application;

[0042] Figure 3 A flowchart illustrating the process of establishing a tomographic inversion velocity model in the tomographic inversion velocity processing method provided in the embodiments of this application;

[0043] Figure 4 A schematic diagram illustrating the relationship between tomographic inversion velocity and near-surface medium velocity, provided for an embodiment of this application;

[0044] Figure 5 A structural block diagram of a tomographic inversion velocity processing device provided in an embodiment of this application;

[0045] Figure 6 A structural block diagram of the relation determination module in a tomographic inversion velocity processing device provided in an embodiment of this application;

[0046] Figure 7 This is a structural block diagram of the model building module in a tomographic inversion velocity processing device provided in an embodiment of this application. Detailed Implementation

[0047] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0048] Unless otherwise defined, all technical terms used in the embodiments of this application have the same meaning as commonly understood by those skilled in the art. Some technical terms appearing in the embodiments of this application are described below.

[0049] In the embodiments of this application, the "tomographic inversion velocity" generally refers to the velocity parameters obtained in the field of lithological seismic exploration through various tomographic inversion methods based on ray theory and wave theory.

[0050] The "near-surface medium velocity" mentioned generally refers to the propagation speed of seismic waves in various media layers as measured by micrologging.

[0051] The “pre-stack depth migration inversion modeling” generally refers to a model establishment method that uses tomographic inversion velocity to update the depth domain velocity. This method can use migration imaging data to calculate the residual error curve and stratigraphic dip information, iteratively update the position and morphology of the reflector layer, and finally obtain an accurate velocity model. The accuracy of its depth domain velocity model can determine the imaging quality of pre-stack depth migration.

[0052] The "seismic tomography" involved is a seismic data processing method for stratigraphic reconstruction and velocity inversion. It refers to the use of first-arrival tomography to construct a near-surface velocity field, which can essentially eliminate near-surface time distortion.

[0053] Currently, tomographic inversion methods are widely used in seismic exploration to obtain near-surface medium velocities. In order to address the problem that the tomographic inversion velocities obtained by related technologies differ significantly from the actual near-surface medium velocities, which affects the quality of seismic tomographic imaging when applied to pre-stack depth migration, this application provides a method for processing tomographic inversion velocities.

[0054] Figure 1 A flowchart illustrating a method for processing tomographic inversion velocity according to an embodiment of this application. See also... Figure 1 The method includes:

[0055] 101. Based on the data of the area to be studied, the data of micrologging is obtained. The data of micrologging includes the number of micrologging wells, the seismic data of each micrologging well, and the near-surface medium velocity data of each micrologging well. For any micrologging well, the micrologging well includes multiple velocity layers. The velocity layer refers to the stratum used to characterize the medium velocity. The near-surface medium velocity data includes multiple near-surface medium velocities of the micrologging well. The near-surface medium velocity corresponds one-to-one with the velocity layer.

[0056] 102. For any microlog, a tomographic inversion velocity model is established based on the seismic data of the microlog. Based on the tomographic inversion velocity model and the near-surface medium velocity data of the microlog, multiple tomographic inversion velocities of the microlog are obtained. The tomographic inversion velocities correspond one-to-one with the velocity layers and are located in the same position as the near-surface medium velocity in each velocity layer.

[0057] 103. Based on the number of micrologging wells, multiple near-surface medium velocities of each micrologging well, and multiple tomographic inversion velocities of each micrologging well, the relationship between tomographic inversion velocity and near-surface medium velocity is determined.

[0058] The tomographic inversion velocity processing method provided in this application involves obtaining microlog data based on data from the area under study. For any microlog, a tomographic inversion velocity model can be constructed using the seismic data of that well. Then, based on this model and near-surface medium velocity data, multiple tomographic inversion velocities from the microlog are obtained. Finally, based on the number of micrologs, the tomographic inversion velocity of each microlog, and the near-surface medium velocity of each microlog, the relationship between the tomographic inversion velocity and the near-surface medium velocity is determined. Since this relationship characterizes the relationship and trend between the tomographic inversion velocity and the near-surface medium velocity, it can be used to correct the tomographic inversion velocity, reducing the error between the tomographic inversion velocity and the near-surface medium velocity. This avoids large errors in pre-stack depth migration inversion modeling and ensures the imaging quality of pre-stack depth migration.

[0059] In some embodiments, the relationship between the tomographic inversion velocity and the near-surface medium velocity is determined based on the number of micrologging wells, multiple near-surface medium velocities of each micrologging well, and multiple tomographic inversion velocities of each micrologging well, including:

[0060] Based on the number of micrologs, multiple near-surface medium velocities from each microlog and multiple tomographic inversion velocities from each microlog, a set of near-surface medium velocities and a set of tomographic inversion velocities are obtained.

[0061] Polynomial fitting was performed on the near-surface medium velocity set and the tomographic inversion velocity set to obtain the relationship curve and fitting formula between the tomographic inversion velocity and the near-surface medium velocity.

[0062] The fitting formula is expressed as:

[0063]

[0064] In the formula: V c This represents the corrected near-surface medium velocity, V. tom This represents the tomographic inversion rate, a i Let i be the coefficient of the polynomial, 0 ≤ i ≤ n, and n be the degree of the polynomial.

[0065] In some embodiments, establishing a tomographic inversion velocity model based on micrologging seismic data includes:

[0066] An initial model was established based on seismic data from micrologging.

[0067] Based on the first arrival data, the initial model, and the second offset, a tomographic inversion velocity model is established. The first arrival data is obtained by picking the first arrival time of each shot by setting a first offset, and the second offset is no greater than the first offset.

[0068] In some embodiments, the seismic data from the micrologging includes surface initiation velocity and velocity gradient. Based on the seismic data from the micrologging, establishing an initial model includes:

[0069] An initial model is established based on the surface initiation velocity and velocity gradient obtained from micrologging.

[0070] In some embodiments, the area to be studied is the region where the same lithological body is located.

[0071] Figure 2 A flowchart illustrating another method for processing tomographic inversion velocity provided in an embodiment of this application. See also... Figure 2 The method includes:

[0072] 201. Based on the data of the area to be studied, the data of micro-logging is obtained.

[0073] The data from micrologging includes the number of micrologging wells, the seismic data of each micrologging well, and the near-surface medium velocity data of each micrologging well. For any given micrologging well, the micrologging well includes multiple velocity layers, which refer to the formations used to characterize the medium velocity. The near-surface medium velocity data includes multiple near-surface medium velocities from the micrologging well, and the near-surface medium velocity corresponds one-to-one with the velocity layer.

[0074] By using data from micrologging wells, the number of micrologging wells in the area under study can be determined. It is understandable that a larger number of micrologging wells yields more data samples, which is more beneficial to the accuracy of subsequent fitting results. By acquiring seismic data and near-surface medium velocity data from each micrologging well, data preparation is provided for determining the relationship between tomographic inversion velocity and near-surface medium velocity.

[0075] It is understood that the number of micrologging wells in the area to be studied can be one or more. When there are multiple micrologging wells in the area to be studied, the number of micrologging wells can be two, three, or four, etc. The specific number of micrologging wells in the area to be studied is not specifically limited in the embodiments of this application.

[0076] Understandably, micro-logging generally refers to wells that are tens or hundreds of meters deep.

[0077] For any velocity layer, the near-surface medium velocity can be expressed as the medium velocity detected at a predetermined point within that velocity layer. The near-surface medium velocity corresponds to an elevation position. Specifically, within the j-th velocity layer out of n velocity layers, the elevation position corresponding to the near-surface medium velocity can be calculated using the following formula:

[0078]

[0079] In the formula: D j Let j be the elevation position of the preset point within the velocity layer, j be the number of the velocity layer (1≤j≤n), E be the ground elevation of the preset point, and h be the elevation of the preset point. i Let be the thickness of the i-th velocity layer, where i is the number of velocity layers, 1≤i≤n.

[0080] In this embodiment of the application, the description will be based on the example of two micrologging wells (micrologging well A and micrologging well B) in the area to be studied. Since there are two micrologging wells, namely micrologging well A and micrologging well B, in this step, the acquisition of seismic data and near-surface medium velocity data of the micrologging wells includes acquiring the seismic data and near-surface medium velocity data of micrologging well A and acquiring the seismic data and near-surface medium velocity data of micrologging well B.

[0081] Alternatively, two micrologging wells, namely micrologging well A and micrologging well B, can be drilled at the shot point or receiver point location within the area to be studied. The well depth should penetrate 20 meters below the high-velocity layer. Measurements should be performed as required to obtain data such as the near-surface medium velocity and thickness of each velocity layer in each micrologging well. A three-dimensional data file for each micrologging well can be established, which may include receiver point file, shot point file, and relational file.

[0082] 202. For any microlog, establish a tomographic inversion velocity model based on the seismic data from the microlog.

[0083] For any micrologging well, a tomographic inversion velocity model can be established using the seismic data from the micrologging well, and then the tomographic inversion velocity can be obtained based on this model.

[0084] like Figure 3 As shown, this step can specifically include:

[0085] In 2021, an initial model was established based on seismic data from micrologging.

[0086] The purpose of establishing the initial model here is to subsequently build a tomographic inversion velocity model based on this model.

[0087] Specifically, the seismic data from micrologging includes surface initiation velocity and velocity gradient, and this step can be specifically described as follows:

[0088] An initial model is established based on the surface initiation velocity and velocity gradient obtained from micrologging.

[0089] In 2022, a tomographic inversion velocity model was established based on initial arrival data, an initial model, and a second offset.

[0090] The first arrival data is obtained by picking the first arrival time of each shot by setting a first offset distance, and the second offset distance is not greater than the first offset distance.

[0091] Understandably, the first offset refers to the horizontal distance between the excitation point and the detector in a vertical seismic profile, determined based on the depth of the microlog. The second offset refers to the distance determined based on the initial model of the microlog, and its value is no greater than the value of the first offset.

[0092] In this embodiment of the application, by determining the grid, initial models of micrologging A and micrologging B can be established respectively based on the surface initiation velocity and velocity gradient of micrologging A and micrologging B.

[0093] In this embodiment of the application, based on the initial arrival data, initial model and second offset of microlog A and microlog B, the minimum travel time ray tracing method is used to perform tomographic inversion to obtain the tomographic inversion velocity models of microlog A and microlog B.

[0094] 203. For any micrologging well, based on the tomographic inversion velocity model and near-surface medium velocity data, multiple tomographic inversion velocities of the micrologging well are obtained. The tomographic inversion velocities correspond one-to-one with the velocity layers and are located in the same position as the near-surface medium velocity in each velocity layer.

[0095] It is understandable that the same position of the tomographic inversion velocity and the near-surface medium velocity in each velocity layer refers to the same elevation position.

[0096] This step is used to obtain the tomographic inversion velocity at the same elevation position as the near-surface medium velocity, based on the tomographic inversion velocity model and near-surface medium velocity data.

[0097] In this embodiment of the application, the velocity data of microlog A in the area to be studied can be shown in Table 1 below, and the velocity data of microlog B can be shown in Table 2 below.

[0098] Table 1. Velocity data from micro-logging A.

[0099] 1 864.94 387 682 2 840.58 606 759 3 816.15 742 977 4 771.89 903 1469 5 744.83 1102 1870

[0100] Table 2. Velocity data from micro-logging B.

[0101] 1 884.79 437 595 2 851.16 588 807 3 838.13 820 905 4 791.27 874 1335 5 762.99 1054 1747

[0102] 204. Based on the number of micrologging wells, multiple near-surface medium velocities of each micrologging well, and multiple tomographic inversion velocities of each micrologging well, the relationship between tomographic inversion velocity and near-surface medium velocity is determined.

[0103] By determining the relationship between the tomographic inversion velocity and the near-surface medium velocity, the tomographic inversion velocity can be processed, i.e., the error between the tomographic inversion velocity and the near-surface medium velocity can be reduced.

[0104] This step may include: obtaining a set of near-surface medium velocities and a set of tomographic inversion velocities based on the number of micrologging wells, multiple near-surface medium velocities from each micrologging well, and multiple tomographic inversion velocities from each micrologging well; performing polynomial fitting on the set of near-surface medium velocities and the set of tomographic inversion velocities to obtain the relationship curve and fitting formula between the tomographic inversion velocities and the near-surface medium velocities.

[0105] The fitting formula is expressed as:

[0106]

[0107] In the formula: V c V represents the velocity of the near-surface medium. tom This represents the tomographic inversion rate, a i Let i be the coefficient of the polynomial, 0 ≤ i ≤ n, and n be the degree of the polynomial.

[0108] Understandably, the relationship between tomographic inversion velocity and near-surface medium velocity can be characterized by a relationship curve and a fitting formula.

[0109] Here, when there is only one micrologging well, the near-surface medium velocity set refers to the multiple near-surface medium velocities of that micrologging well, and the tomographic inversion velocity set refers to the multiple near-surface medium velocities of that micrologging well; when there are multiple micrologging wells, the near-surface medium velocity set refers to all surface medium velocities contained in the multiple micrologging wells, and the tomographic inversion velocity set refers to all tomographic inversion velocities contained in the multiple micrologging wells.

[0110] In this embodiment of the application, the velocity data of microlog A and microlog B obtained in step 203 can be organized into velocity data of the area to be studied according to the increasing velocity order of the tomographic inversion, as shown in Table 3 below.

[0111] Table 3. Velocity data for the area under study.

[0112] 1 595 437 2 628 387 3 759 606 4 807 588 5 905 820 6 977 742 7 1335 874 8 1469 903 9 1747 1054 10 1870 1102

[0113] By performing a cubic polynomial fit on the data in Table 3, the relationship curve between the tomographic inversion velocity and the near-surface medium velocity can be obtained, as shown in the attached figure. Figure 4 As shown, the fitting formula is as follows:

[0114]

[0115] In the formula: V c V represents the corrected near-surface medium velocity. tom This represents the tomographic inversion speed.

[0116] The tomographic inversion velocity processing method provided in this application involves obtaining microlog data based on data from the area under study. For any microlog, a tomographic inversion velocity model can be constructed using the seismic data of that well. Then, based on this model and near-surface medium velocity data, multiple tomographic inversion velocities from the microlog are obtained. Finally, based on the number of micrologs, the tomographic inversion velocity of each microlog, and the near-surface medium velocity of each microlog, the relationship between the tomographic inversion velocity and the near-surface medium velocity is determined. Since this relationship characterizes the relationship and trend between the tomographic inversion velocity and the near-surface medium velocity, it can be used to correct the tomographic inversion velocity, reducing the error between the tomographic inversion velocity and the near-surface medium velocity. This avoids large errors in pre-stack depth migration inversion modeling and ensures the imaging quality of pre-stack depth migration.

[0117] Figure 5This is a structural block diagram of a tomographic inversion velocity processing apparatus provided in an embodiment of this application. See also... Figure 5 The device includes:

[0118] The data acquisition module 501 is used to obtain microlog data based on the data of the area to be studied. The microlog data includes the number of micrologs, the seismic data of each microlog, and the near-surface medium velocity data of each microlog. For any microlog, the microlog includes multiple velocity layers, which refer to the strata used to characterize the medium velocity. The near-surface medium velocity data includes multiple near-surface medium velocities of the microlog, and the near-surface medium velocity corresponds one-to-one with the velocity layer.

[0119] The model building module 502 is used to build a tomographic inversion velocity model for any micrologging well based on the seismic data of the micrologging well, and to obtain multiple tomographic inversion velocities of the micrologging well based on the tomographic inversion velocity model and the near-surface medium velocity data of the micrologging well. The tomographic inversion velocities correspond one-to-one with the velocity layers and are in the same position as the near-surface medium velocity in each velocity layer.

[0120] The relationship determination module 503 is used to determine the relationship between the tomographic inversion velocity and the near-surface medium velocity based on the number of micrologs, multiple near-surface medium velocities of each microlog, and multiple tomographic inversion velocities of each microlog.

[0121] In some embodiments, such as Figure 6 As shown, the relationship determination module 503 includes:

[0122] The velocity set acquisition unit 5031 is used to obtain the near-surface medium velocity set and the tomographic inversion velocity set based on the number of micro-logging wells, multiple near-surface medium velocities of each micro-logging well, and multiple tomographic inversion velocities of each micro-logging well.

[0123] The fitting unit 5032 is used to perform polynomial fitting on the near-surface medium velocity set and the tomographic inversion velocity set to obtain the relationship curve and fitting formula between the tomographic inversion velocity and the near-surface medium velocity.

[0124] The fitting formula is expressed as:

[0125]

[0126] In the formula: V c This represents the corrected near-surface medium velocity, V. tom This represents the tomographic inversion rate, a i Let i be the coefficient of the polynomial, 0 ≤ i ≤ n, and n be the degree of the polynomial.

[0127] In some embodiments, such as Figure 7 As shown, the model building module 502 includes:

[0128] The first model building unit 5021 is used to build an initial model based on seismic data from micro-logging.

[0129] The second model building unit 5022 is used to build a tomographic inversion velocity model based on the first arrival data, the initial model, and the second offset. The first arrival data is obtained by picking the first arrival time of each shot by setting a first offset, and the second offset is not greater than the first offset.

[0130] In some embodiments, the seismic data from the micrologging includes surface initiation velocity and velocity gradient, and the first model building unit 5021 includes:

[0131] An initial model is established based on the surface initiation velocity and velocity gradient obtained from micrologging.

[0132] In some embodiments, the area to be studied is the region where the same lithological body is located.

[0133] It should be noted that the tomographic inversion speed processing device provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the tomographic inversion speed processing device and the tomographic inversion speed processing method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0134] The tomographic inversion velocity processing apparatus provided in this application obtains microlog data based on data from the area under study. For any microlog, a tomographic inversion velocity model can be constructed using the seismic data of that well. Then, based on this tomographic inversion velocity model and near-surface medium velocity data, multiple tomographic inversion velocities of the microlog are obtained. Finally, based on the number of micrologs, the tomographic inversion velocity of each microlog, and the near-surface medium velocity of each microlog, the relationship between the tomographic inversion velocity and the near-surface medium velocity is determined. Since this relationship can characterize the relationship and trend between the tomographic inversion velocity and the near-surface medium velocity, it can be used to correct the tomographic inversion velocity to be processed, thereby reducing the error between the tomographic inversion velocity and the near-surface medium velocity. This avoids large errors in pre-stack depth migration inversion modeling and ensures the imaging quality of pre-stack depth migration.

[0135] In this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The term "multiple" refers to two or more unless otherwise expressly defined.

[0136] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only.

[0137] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for processing tomographic inversion velocity, characterized in that, The method includes: Based on the data of the area to be studied, micrologging data is obtained. The micrologging data includes the number of micrologging wells, the seismic data of each micrologging well, and the near-surface medium velocity data of each micrologging well. For any micrologging well, the micrologging well includes multiple velocity layers. The velocity layer refers to the stratum used to characterize the medium velocity. The near-surface medium velocity data includes multiple near-surface medium velocities of the micrologging well, and the near-surface medium velocity corresponds one-to-one with the velocity layer. For any microlog, a tomographic inversion velocity model is established based on the seismic data of the microlog, and multiple tomographic inversion velocities of the microlog are obtained based on the tomographic inversion velocity model and the near-surface medium velocity data of the microlog. The tomographic inversion velocities correspond one-to-one with the velocity layers and are in the same position as the near-surface medium velocity in each velocity layer. Based on the number of micrologs, the multiple near-surface medium velocities of each microlog, and the multiple tomographic inversion velocities of each microlog, the relationship between the tomographic inversion velocity and the near-surface medium velocity is determined. The determination of the relationship between the tomographic inversion velocity and the near-surface medium velocity includes: Based on the number of micrologs, the multiple near-surface medium velocities of each microlog and the multiple tomographic inversion velocities of each microlog, a set of near-surface medium velocities and a set of tomographic inversion velocities are obtained. Polynomial fitting is performed on the near-surface medium velocity set and the tomographic inversion velocity set to obtain the relationship curve and fitting formula between the tomographic inversion velocity and the near-surface medium velocity. The fitting formula is expressed as follows: = + +…+ + In the formula: This represents the corrected near-surface medium velocity. This represents the tomographic inversion rate. Let i be the coefficient of the polynomial, 0 ≤ i ≤ n, and n be the degree of the polynomial.

2. The method for processing the tomographic inversion rate according to claim 1, characterized in that, The establishment of the tomographic inversion velocity model based on the seismic data from the micro-logging well includes: An initial model was established based on the seismic data from the micro-logging wells. Based on the first arrival data, the initial model, and the second offset, the tomographic inversion velocity model is established, wherein the first arrival data is obtained by picking the first arrival time of each shot by setting a first offset, and the second offset is not greater than the first offset.

3. The method for processing the tomographic inversion rate according to claim 2, characterized in that, The seismic data from the micrologging includes surface initiation velocity and velocity gradient. The initial model established based on the seismic data from the micrologging includes: The initial model is established based on the surface initiation velocity and velocity gradient obtained from the micrologging.

4. The method for processing the tomographic inversion rate according to claim 1, characterized in that, The area to be studied refers to the region where the same lithological body is located.

5. A processing apparatus for measuring the rate of chromatographic inversion, characterized in that, The device includes: The data acquisition module is used to obtain microlog data based on the data of the area to be studied. The microlog data includes the number of micrologs, the seismic data of each microlog, and the near-surface medium velocity data of each microlog. For any microlog, the microlog includes multiple velocity layers, which refer to the formation used to characterize the medium velocity. The near-surface medium velocity data includes multiple near-surface medium velocities of the microlog, and the near-surface medium velocities correspond one-to-one with the velocity layers. The model building module is used to establish a tomographic inversion velocity model for any micrologging well based on the seismic data of the micrologging well, and to obtain multiple tomographic inversion velocities of the micrologging well based on the tomographic inversion velocity model and the near-surface medium velocity data of the micrologging well. The tomographic inversion velocities correspond one-to-one with the velocity layers and are in the same position as the near-surface medium velocity in each velocity layer. The relationship determination module is used to determine the relationship between the tomographic inversion velocity and the near-surface medium velocity based on the number of micrologs, multiple near-surface medium velocities of each microlog, and multiple tomographic inversion velocities of each microlog. The relationship determination module includes: The velocity set acquisition unit is used to obtain a near-surface medium velocity set and a tomographic inversion velocity set based on the number of micrologs, multiple near-surface medium velocities of each microlog and multiple tomographic inversion velocities of each microlog; The fitting unit is used to perform polynomial fitting on the near-surface medium velocity set and the tomographic inversion velocity set to obtain the relationship curve and fitting formula between the tomographic inversion velocity and the near-surface medium velocity. The fitting formula is expressed as follows: = + +…+ + In the formula: This represents the corrected near-surface medium velocity. This represents the tomographic inversion rate. Let i be the coefficient of the polynomial, 0 ≤ i ≤ n, and n be the degree of the polynomial.

6. The apparatus for processing the tomographic inversion rate according to claim 5, characterized in that, The model building module includes: The first model building unit is used to build an initial model based on the seismic data from the micro-logging well. The second model building unit is used to build the tomographic inversion velocity model based on the first arrival data, the initial model, and the second offset, wherein the first arrival data is obtained by picking the first arrival time of each shot by setting a first offset, and the second offset is not greater than the first offset.

7. The apparatus for processing the chromatographic inversion rate according to claim 6, characterized in that, The seismic data from the micro-logging includes surface initiation velocity and velocity gradient, and the first model building unit includes: The initial model is established based on the surface initiation velocity and velocity gradient obtained from the micrologging.

8. The apparatus for processing the tomographic inversion rate according to claim 5, characterized in that, The area to be studied refers to the region where the same lithological body is located.

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