Seismic wave absorption attenuation model determination method and device, equipment and storage medium

Abstract

The invention discloses a seismic wave absorption attenuation model determination method and device, equipment and a storage medium, and belongs to the technical field of seismic exploration. According to the method provided by the invention, the relationship between the speed of the measurement point of each layer in each well and the actual Q value is determined according to the micro-logging interpretation result data of each well, and the reliable points and the abnormal points are divided according to the relationship. And for the abnormal point, re-determining the Q value of the abnormal point according to the relationship, and then constructing a seismic wave absorption attenuation model according to the re-determined Q value of the abnormal point. According to the method, the seismic wave absorption attenuation model is constructed according to the re-determined Q value of the abnormal point, so that the influence of the abnormal point can be eliminated, errors are reduced, and the reliability of the model is improved.

Description

Technical Field

[0001] This application relates to the field of seismic exploration technology, and in particular to a method, apparatus, equipment and storage medium for determining a seismic wave absorption attenuation model. Background Technology

[0002] Under normal circumstances, subsurface strata are not perfectly elastic media but viscous media; therefore, absorption and attenuation of seismic waves by subsurface media are widespread. Compared to subsurface rock strata, incompletely consolidated near-surface strata have a stronger absorption effect on seismic waves. The quality factor Q is an important parameter used to describe the absorption and attenuation of seismic waves, reflecting the strength of the absorption and attenuation by the subsurface medium, and is the basis for quantitative evaluation of the absorption and attenuation characteristics of seismic waves. Therefore, considering the above situation, an absorption and attenuation model, namely the Q-value model, can be established to eliminate the influence of near-surface absorption and attenuation on seismic data, thereby improving the resolution and imaging accuracy of seismic data.

[0003] In related technologies, the thickness of each layer, the velocity of each measurement point, and the initial Q value are first obtained from field micrologging data. Then, a Q-value model is constructed directly based on the thickness of each layer, the velocity of each measurement point, and the initial Q value.

[0004] However, due to the influence of measurement factors and other factors, the initial Q values ​​of these measurement points may be abnormal. In this case, the Q value model constructed based on the initial Q values ​​of abnormal points is not accurate and has a large error, resulting in poor reliability of the Q value model. Summary of the Invention

[0005] This application provides a method, apparatus, device, and storage medium for determining a seismic wave absorption attenuation model, which can improve the reliability of the Q-value model. The technical solution is as follows:

[0006] On the one hand, a method for determining a seismic wave absorption attenuation model is provided, the method comprising:

[0007] Acquire the micrologging interpretation data corresponding to multiple wells in the target area. The micrologging interpretation data of each well includes the thickness of multiple layers, the velocity of multiple measurement points in each layer, and the initial quality factor Q value.

[0008] For each layer of each well, based on the velocity and initial Q value of multiple measurement points in the layer, first relational data is determined, which is used to represent the relationship between the velocity of the measurement points and the actual Q value.

[0009] Based on the first relationship data, reliable points and abnormal points are determined from the plurality of measurement points, wherein the abnormal points are points where the initial Q value is abnormal;

[0010] Based on the first relationship data, determine the actual Q value of the outlier;

[0011] Based on the initial Q-values ​​of reliable points, the actual Q-values ​​of anomaly points, and the thickness of the layers in each of the multiple wells, a seismic wave absorption attenuation model is determined.

[0012] In one possible implementation, determining the first relationship data based on the velocity and initial Q value of multiple measurement points in the layer includes:

[0013] Construct an exponential function to represent the relationship between the velocity at the measurement point and the actual Q value;

[0014] Taking the logarithm of both sides of the exponential function yields a linear function.

[0015] Based on the velocity and initial Q value of the multiple measurement points, the linear function is linearly fitted to obtain the first relationship data.

[0016] In another possible implementation, determining reliable points and outliers from the plurality of measurement points includes:

[0017] Based on the first relationship data, a fitted straight line is plotted in a rectangular coordinate system, wherein the logarithm of the actual Q value is used as the vertical axis and the logarithm of the velocity is used as the horizontal axis.

[0018] Based on the velocity and initial Q value of the plurality of measurement points, the positions of the plurality of measurement points are determined in the Cartesian coordinate system;

[0019] Determine the deviation between the position of each measurement point and the fitted straight line;

[0020] Measurement points with a deviation greater than a preset deviation are identified as abnormal points, and measurement points with a deviation not greater than the preset deviation are identified as reliable points.

[0021] In another possible implementation, the micrologging interpretation data for each well also includes the velocity of missing points in each layer, where the missing points are measurement points lacking initial Q values;

[0022] The seismic wave absorption and attenuation model is determined based on the initial Q-values ​​of reliable points, the actual Q-values ​​of anomaly points, and the thickness of the layers in each of the multiple wells, including:

[0023] For each layer, the velocity of the missing point is substituted into the first relational data to obtain the actual Q value of the missing point;

[0024] The seismic wave absorption attenuation model is determined based on the initial Q value of the reliable point, the actual Q value of the anomaly point, the actual Q value of the missing point, and the thickness of the layer in each layer of the multiple wells.

[0025] In another possible implementation, determining the seismic wave absorption attenuation model based on the actual Q-values ​​of reliable points, anomaly points, missing points, and the thickness of the layers in each layer of the multiple wells includes:

[0026] Based on the actual Q-values ​​of the reliable points, the anomaly points, the missing points, and the thickness of the layers in each layer of the multiple wells, the seismic wave absorption and attenuation model is constructed using layer modeling and interpolation methods.

[0027] In another possible implementation, determining the actual Q-value of the outlier based on the first relational data includes:

[0028] Substituting the velocity of the outlier into the first relational data, the actual Q value of the outlier is obtained.

[0029] On the other hand, a device for determining a seismic wave absorption attenuation model is provided, the device comprising:

[0030] The acquisition module is used to acquire the micrologging interpretation data corresponding to multiple wells in the target area. The micrologging interpretation data of each well includes the thickness of multiple layers, the velocity of multiple measurement points in each layer, and the initial quality factor Q value.

[0031] The first determining module is used to determine first relationship data for each layer of each well, based on the velocity and initial Q value of multiple measurement points in the layer. The first relationship data is used to represent the relationship between the velocity of the measurement points and the actual Q value.

[0032] The second determining module is used to determine reliable points and abnormal points from the plurality of measurement points based on the first relationship data, wherein the abnormal points are points where the initial Q value is abnormal;

[0033] The third determining module is used to determine the actual Q value of the outlier based on the first relationship data;

[0034] The fourth determination module is used to determine the seismic wave absorption attenuation model based on the initial Q value of reliable points, the actual Q value of anomaly points, and the thickness of the layers in each layer of the multiple wells.

[0035] In one possible implementation, the first determining module is used to construct an exponential function, which represents the relationship between the velocity of the measurement point and the actual Q value; take the logarithm of both sides of the exponential function to obtain a linear function; and perform linear fitting on the linear function based on the velocity and initial Q value of the plurality of measurement points to obtain the first relationship data.

[0036] In another possible implementation, the second determining module is used to draw a fitted straight line in a rectangular coordinate system based on the first relationship data, wherein the rectangular coordinate system has the logarithm of the actual Q value as the ordinate and the logarithm of the velocity as the abscissa; determine the positions of the plurality of measurement points in the rectangular coordinate system based on the velocities and initial Q values ​​of the plurality of measurement points; determine the deviation between the position of each measurement point and the fitted straight line; determine the measurement points with deviations greater than a preset deviation as the abnormal points, and determine the measurement points with deviations not greater than the preset deviation as the reliable points.

[0037] In another possible implementation, the micrologging interpretation data for each well also includes the velocity of missing points in each layer, where the missing points are measurement points lacking initial Q values;

[0038] The fourth determining module is used to, for each layer, substitute the velocity of the missing point into the first relational data to obtain the actual Q value of the missing point; and determine the seismic wave absorption attenuation model based on the initial Q value of the reliable point, the actual Q value of the anomaly point, the actual Q value of the missing point, and the thickness of the layer in each layer of the multiple wells.

[0039] In another possible implementation, the fourth determining module is used to construct the seismic wave absorption attenuation model based on the actual Q-values ​​of the reliable points, the anomaly points, the missing points, and the thickness of the layers in each layer of the multiple wells, using layer modeling and interpolation methods.

[0040] In another possible implementation, the third determining module is used to substitute the velocity of the anomaly point into the first relational data to obtain the actual Q value of the anomaly point.

[0041] On the other hand, an electronic device is provided, comprising a processor and a memory, wherein the memory stores at least one line of program code, which is loaded and executed by the processor to implement the seismic wave absorption attenuation model determination method described in any of the preceding claims.

[0042] On the other hand, a computer-readable storage medium is provided, wherein at least one piece of program code is stored in the computer-readable storage medium, the at least one piece of program code being loaded and executed by a processor to implement the method for determining the seismic wave absorption attenuation model as described in any of the preceding claims.

[0043] On the other hand, a computer program product is provided, wherein at least one piece of program code is stored in the computer program product, and the at least one piece of program code is loaded and executed by a processor to implement the method for determining the seismic wave absorption attenuation model as described in any of the above claims.

[0044] This application provides a method for determining a seismic wave absorption attenuation model. The method first determines the relationship between the velocity and actual Q-value at each measurement point in each layer of each well based on the micrologging interpretation data. Based on this relationship, reliable points and anomalous points are identified. For anomalous points, their Q-values ​​are redefined according to the relationship, and then a seismic wave absorption attenuation model is constructed based on these redefined Q-values. Because this method constructs the seismic wave absorption attenuation model based on the redefined Q-values ​​of the anomalous points, it can eliminate the influence of anomalous points, reduce errors, and thus improve the reliability of the model.

[0045] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this disclosure. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the implementation environment of a method for determining a seismic wave absorption attenuation model provided in an embodiment of this application;

[0047] Figure 2 This is a flowchart of a method for determining a seismic wave absorption attenuation model provided in an embodiment of this application;

[0048] Figure 3 This is a schematic diagram illustrating the determination of anomalies provided in an embodiment of this application;

[0049] Figure 4 This is a schematic diagram of a Q-value model profile provided in an embodiment of this application;

[0050] Figure 5 This is a schematic diagram of a Q-value model profile provided by related technologies;

[0051] Figure 6 This is a schematic diagram of the structure of a seismic wave absorption attenuation model determination device provided in an embodiment of this application;

[0052] Figure 7 This is a structural block diagram of a terminal provided in an embodiment of this application;

[0053] Figure 8 This is a structural block diagram of a server provided in an embodiment of this application. Detailed Implementation

[0054] To make the technical solution and advantages of this application clearer, the embodiments of this application will be described in further detail below.

[0055] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. 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 includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0056] It should be noted that all information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in this application have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the micro-logging interpretation results data involved in this application were obtained with full authorization.

[0057] Figure 1 This is a schematic diagram illustrating the implementation environment of a method for determining a seismic wave absorption attenuation model provided in this application embodiment. Figure 1 The implementation environment includes an electronic device, which can be provided as terminal 101, or as a combination of terminal 101 and server 102. If the electronic device is provided as terminal 101 and server 102, terminal 101 and server 102 can be connected via a wireless or wired network. In this embodiment, the electronic device is not specifically limited.

[0058] If the electronic device is provided as terminal 101, then the seismic wave absorption attenuation model is determined by terminal 101.

[0059] If the electronic devices are provided as terminal 101 and server 102, terminal 101 sends the micrologging interpretation data corresponding to each of the multiple wells in the target area to server 102. Server 102 determines the seismic wave absorption attenuation model based on the micrologging interpretation data corresponding to each of the multiple wells in the target area, and then returns the seismic wave absorption attenuation model to terminal 101. A target application is installed on terminal 101, which is used to determine the seismic wave absorption attenuation model. Server 102 is the backend server for the target application, used to provide backend services for the target application.

[0060] The terminal 101 can be at least one of the following: mobile phone, tablet computer, PC (Personal Computer) device, intelligent voice interaction device, and vehicle terminal. The server 102 can be at least one of the following: a single server, a server cluster consisting of multiple servers, a cloud server, a cloud computing platform, and a virtualization center.

[0061] Figure 2 This is a flowchart of a method for determining a seismic wave absorption attenuation model provided in an embodiment of this application, executed by an electronic device. See also... Figure 2 The method includes:

[0062] Step 201: The electronic device acquires the micrologging interpretation data corresponding to each of the multiple wells in the target area.

[0063] The target area is a seismic research area. Electronic devices can acquire micrologging interpretation data from multiple wells sent by other devices, or they can acquire micrologging interpretation data from multiple wells input by the user; there are no specific limitations on this. For example, there are 51 wells in the target area, and each well has 3 interpretation horizons.

[0064] For each well, the micrologging interpretation data is derived from the interpretation of micrologging data. This data includes the thickness of multiple layers, the velocity at multiple measurement points within each layer, and the initial Q value. For each measurement point, the velocity refers to the propagation speed of the seismic wave corresponding to that point.

[0065] The initial Q value of each measurement point can be obtained by the spectral ratio method, the matching pursuit algorithm or other methods. In this embodiment of the application, the method for obtaining the initial Q value of each measurement point is not specifically limited.

[0066] Step 202: For each layer of each well, the electronic equipment determines the first relationship data based on the velocity and initial Q value of multiple measurement points in that layer.

[0067] This step can be achieved through the following steps (1) to (3), including:

[0068] (1) Electronic devices construct exponential functions.

[0069] The exponential function is used to represent the relationship between the velocity at the measurement point and the actual Q value.

[0070] In this step, the exponential function can be expressed as Q = a × V b Q represents the actual Q value, V represents the velocity, and a and b are coefficients.

[0071] (2) The electronic device takes the logarithm of both sides of the exponential function to obtain a linear function.

[0072] Electronic devices can take the logarithm of both sides of an exponential function with any number greater than 1 as the base. For example, they can take the logarithm with the natural logarithm e as the base, the common logarithm 10 as the base, or other numbers as the base. In this embodiment, we will only use the natural logarithm e as the base as an example for illustration.

[0073] With the natural logarithm e as the base, for Q = a × V b Taking the logarithm, the resulting linear function can be expressed as ln Q = ln a + b ln V.

[0074] (3) The electronic device performs linear fitting on the linear function based on the speed and initial Q value of multiple measurement points to obtain the first relationship data.

[0075] For each measurement point, the electronic device determines the logarithm of the velocity at that measurement point and the logarithm of the initial Q value. Then, based on the logarithm of the velocity at each measurement point and the logarithm of the initial Q value, it performs a linear fit on the linear function using the least squares method to obtain the first relationship data.

[0076] For example, a = 1.378 * 10 -6 If b = 2.177, then Q = 1.378 * 10 -6 *V 2.177 .

[0077] Step 203: The electronic device determines reliable points and abnormal points from multiple measurement points based on the first relationship data.

[0078] The electronic device plots a fitted straight line in a Cartesian coordinate system based on the first relational data; it then determines the positions of multiple measurement points in the Cartesian coordinate system based on the velocities and initial Q values ​​of multiple measurement points; it determines the deviation between the position of each measurement point and the fitted straight line; measurement points with deviations greater than a preset deviation are identified as outliers, while those with deviations no greater than the preset deviation are identified as reliable points. The Cartesian coordinate system uses the logarithm of the actual Q value as the ordinate and the logarithm of the velocity as the abscissa.

[0079] In this implementation, the electronic device draws the fitted straight line corresponding to the first relational data in a Cartesian coordinate system, determines the logarithm of the velocity of multiple measurement points and the logarithm of the initial Q value, and finds the position of multiple measurement points in the Cartesian coordinate system.

[0080] In one possible implementation, the electronic device determines the vertical distance between the position of each measurement point and the fitted line, and defines this vertical distance as the deviation. If the vertical distance is greater than a preset vertical distance, the measurement point is determined to be an outlier because the deviation between the measurement point and the fitted line is greater than the preset deviation. If the vertical distance is not greater than the preset vertical distance, the measurement point is determined to be a reliable point because the deviation between the measurement point and the fitted line is not greater than the preset deviation.

[0081] In another possible implementation, the electronic device determines the horizontal distance between the position of each measurement point and the fitted line, and defines this horizontal distance as the deviation. If the horizontal distance is greater than a preset horizontal distance, the measurement point is determined to be an outlier because the deviation between the measurement point and the fitted line is greater than the preset deviation. If the horizontal distance is not greater than the preset horizontal distance, the measurement point is determined to be a reliable point because the deviation between the measurement point and the fitted line is not greater than the preset deviation.

[0082] In the embodiments of this application, the electronic device may also determine the deviation between the position of each measurement point and the fitted straight line in other ways, without specific limitations.

[0083] See Figure 3 ,from Figure 3 As can be seen, there are 6 measurement points with large vertical or horizontal distances from the fitted line. Therefore, these 6 measurement points are identified as outliers. The majority of the remaining measurement points are on the fitted line and are therefore identified as reliable points.

[0084] Step 204: The electronic device determines the actual Q value of the outlier based on the first relational data.

[0085] The electronic device substitutes the velocity of the outlier into the first relational data to obtain the actual Q value of the outlier.

[0086] For example, the first relational data is Q = 1.378 * 10 -6 *V 2.177 The velocity of the missing point is V i Then the electronic device will V i Substituting into the first relational data, we get Q. i Where i ranges from 1 to n, and n is the total number of outliers.

[0087] For each layer in each well, the electronic equipment determines the actual Q value of the anomaly point in that layer through steps 202 to 204.

[0088] For example, if each well has three interpretation horizons, the electronic equipment can first determine the actual Q-values ​​of anomalies in the first horizon, then the second horizon, and finally the third horizon. Alternatively, the electronic equipment can first determine the actual Q-values ​​of anomalies in the third horizon, then the second horizon, and finally the first horizon; the order is not specifically limited.

[0089] In this embodiment, the velocity of the measurement point can be obtained through measurement, which is relatively accurate. Therefore, the velocity of the measurement point is substituted into the first relational data, and the Q value of the outlier is recalculated through the first relational data, thereby improving the accuracy of the Q value of the outlier.

[0090] Step 205: The electronic device determines the seismic wave absorption attenuation model based on the initial Q value of the reliable point, the actual Q value of the anomaly point, and the thickness of the layer in each layer of the multiple wells.

[0091] In step 201, after the electronic device acquires the micrologging interpretation data of each well, it can determine whether there are missing points in the micrologging interpretation data of each well. The missing points are measurement points that lack the initial Q value.

[0092] If there are no missing points, after determining the actual Q value of the anomaly point in each layer of each well, the electronic equipment can directly construct a seismic wave absorption attenuation model based on the initial Q value of the reliable point in each layer of each well, the actual Q value of the anomaly point, and the thickness of each layer, using layer modeling and interpolation methods.

[0093] If missing points exist, after determining the first relational data, the electronic device can substitute the velocity of the missing points into the first relational data to obtain the actual Q value of the missing points. After determining the actual Q value of the anomaly points in each layer of each well, based on the initial Q value of the reliable points in each layer of each well, the actual Q value of the anomaly points, the actual Q value of the missing points, and the thickness of each layer, a seismic wave absorption attenuation model is constructed using layer modeling and interpolation methods.

[0094] For example, the first relational data is Q = 1.378 * 10 -6 *V 2.177 The velocity of the missing point is V j Then the electronic device will V j Substituting into the first relational data, we get Q. j Where j ranges from 1 to m, and m is the total number of missing points. For example, if the total number of missing points is 3, then m is 3.

[0095] In this case, after determining the first relational data, the electronic device can either first determine the actual Q value of the outlier and then determine the actual Q value of the missing point, or it can first determine the actual Q value of the missing point and then determine the actual Q value of the outlier. There is no specific restriction on this order.

[0096] In addition, the interpolation method can be set and changed as needed, such as the Kriging interpolation method or other interpolation methods, without specific limitations.

[0097] In this embodiment, the velocity and initial Q-value of the measurement points in the field micrologging interpretation data are utilized. By fitting the relationship between velocity and Q-value, outliers are identified. The Q-values ​​of the outliers are recalculated using the relationship between velocity and Q-value, and the Q-values ​​of missing points are supplemented. Finally, a robust and high-precision near-surface Q-value model is obtained through interpolation. The Q-value model is a three-dimensional cube model. This method significantly improves the reliability and stability of near-surface Q-values, effectively eliminates the influence of near-surface absorption attenuation on seismic data, and further improves the resolution and imaging accuracy of seismic data.

[0098] See Figure 4 and Figure 5 , Figure 4 This is a cross-sectional view of the seismic wave absorption and attenuation model, i.e., the Q-value model, generated using the method provided in this application. Figure 5 This is a profile of a Q-value model generated by directly using micrologging data to interpret layer thickness, velocity at multiple measurement points within each layer, and initial Q-values, following methods found in relevant technologies. Figure 4 and Figure 5 As can be seen, the Q-value distribution in the Q-value model generated by the method provided in this application is more reasonable, and no local Q-value abrupt changes occur, which is a significant improvement over the methods in related technologies.

[0099] This application provides a method for determining a seismic wave absorption attenuation model. The method first determines the relationship between the velocity and actual Q-value at each measurement point in each layer of each well based on the micrologging interpretation data. Based on this relationship, reliable points and anomalous points are identified. For anomalous points, their Q-values ​​are redefined according to the relationship, and then a seismic wave absorption attenuation model is constructed based on these redefined Q-values. Because this method constructs the seismic wave absorption attenuation model based on the redefined Q-values ​​of the anomalous points, it can eliminate the influence of anomalous points, reduce errors, and thus improve the reliability of the model.

[0100] Figure 6 This is a schematic diagram of a seismic wave absorption attenuation model determination device provided in an embodiment of this application. See also... Figure 6 The device includes:

[0101] The acquisition module 601 is used to acquire the micrologging interpretation results data corresponding to multiple wells in the target area. The micrologging interpretation results data of each well include the thickness of multiple layers, the velocity of multiple measurement points in each layer, and the initial quality factor Q value.

[0102] The first determining module 602 is used to determine first relational data for each layer of each well, based on the velocity and initial Q value of multiple measurement points in the layer. The first relational data is used to represent the relationship between the velocity of the measurement points and the actual Q value.

[0103] The second determining module 603 is used to determine reliable points and abnormal points from multiple measurement points based on the first relationship data. Abnormal points are points where the initial Q value is abnormal.

[0104] The third determining module 604 is used to determine the actual Q value of the outlier based on the first relational data;

[0105] The fourth determination module 605 is used to determine the seismic wave absorption attenuation model based on the initial Q value of reliable points, the actual Q value of anomaly points and the thickness of the layers in each layer of multiple wells.

[0106] In one possible implementation, the first determining module 602 is used to construct an exponential function, which represents the relationship between the velocity of the measurement point and the actual Q value; take the logarithm of both sides of the exponential function to obtain a linear function; and perform linear fitting on the linear function based on the velocity of multiple measurement points and the initial Q value to obtain the first relationship data.

[0107] In another possible implementation, the second determining module 603 is used to draw a fitted straight line in a rectangular coordinate system based on the first relational data, with the logarithm of the actual Q value as the ordinate and the logarithm of the velocity as the abscissa; determine the positions of multiple measurement points in the rectangular coordinate system based on the velocities and initial Q values ​​of multiple measurement points; determine the deviation between the position of each measurement point and the fitted straight line; determine measurement points with deviations greater than a preset deviation as outliers, and determine measurement points with deviations not greater than the preset deviation as reliable points.

[0108] In another possible implementation, the micrologging interpretation data for each well also includes the velocity of missing points in each layer, where the missing points are measurement points lacking initial Q values;

[0109] The fourth determination module 605 is used to substitute the velocity of the missing point into the first relational data for each layer to obtain the actual Q value of the missing point; and to determine the seismic wave absorption attenuation model based on the initial Q value of the reliable point, the actual Q value of the anomaly point, the actual Q value of the missing point, and the thickness of the layer in each layer of multiple wells.

[0110] In another possible implementation, the fourth determining module 605 is used to construct a seismic wave absorption attenuation model based on the actual Q-values ​​of reliable points, anomaly points, missing points, and layer thickness in each layer of multiple wells, using a layer modeling and interpolation device.

[0111] In another possible implementation, the third determining module 604 is used to substitute the velocity of the outlier into the first relational data to obtain the actual Q value of the outlier.

[0112] This application provides a device for determining a seismic wave absorption attenuation model. The device first determines the relationship between the velocity and the actual Q-value at each measurement point in each layer of each well based on the micrologging interpretation data. Based on this relationship, reliable points and anomalous points are identified. For anomalous points, their Q-values ​​are re-determined according to the relationship, and then a seismic wave absorption attenuation model is constructed based on these re-determined Q-values. Because this device constructs the seismic wave absorption attenuation model based on the re-determined Q-values ​​of the anomalous points, the influence of anomalous points can be eliminated, errors reduced, and thus the reliability of the model improved.

[0113] In some embodiments, the electronic device is provided as a terminal. (See reference) Figure 7 , Figure 7 This illustration shows a structural block diagram of a terminal 700 provided in an exemplary embodiment of this application. The terminal 700 can be a portable mobile terminal, such as a smartphone, tablet computer, MP3 player (Moving Picture Experts Group Audio Layer III), MP4 player (Moving Picture Experts Group Audio Layer IV), laptop computer, or desktop computer. The terminal 700 may also be referred to as a user device, portable terminal, laptop terminal, desktop terminal, or other names.

[0114] Typically, terminal 700 includes a processor 701 and a memory 702.

[0115] Processor 701 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 701 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 701 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 701 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 701 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0116] The memory 702 may include one or more computer-readable storage media, which may be non-transitory. The memory 702 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 702 is used to store at least one line of program code, which is executed by the processor 701 to implement the seismic wave absorption attenuation model determination method provided in the method embodiments of this application.

[0117] In some embodiments, the terminal 700 may also optionally include a peripheral device interface 703 and at least one peripheral device. The processor 701, memory 702, and peripheral device interface 703 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 703 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of the following: a radio frequency circuit 704, a display screen 705, a camera assembly 706, an audio circuit 707, and a power supply 708.

[0118] Peripheral device interface 703 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 701 and memory 702. In some embodiments, processor 701, memory 702 and peripheral device interface 703 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 701, memory 702 and peripheral device interface 703 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0119] The radio frequency (RF) circuit 704 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 704 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 704 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 704 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The RF circuit 704 can communicate with other terminals through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 704 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0120] Display screen 705 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 705 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 701 for processing. In this case, display screen 705 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 705, disposed on the front panel of terminal 700; in other embodiments, there may be at least two display screens 705, disposed on different surfaces of terminal 700 or in a folded design; in other embodiments, display screen 705 may be a flexible display screen, disposed on a curved or folded surface of terminal 700. Furthermore, display screen 705 may be configured as a non-rectangular irregular shape, i.e., a non-rectangular screen. Display screen 705 may be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0121] The camera assembly 706 is used to acquire images or videos. Optionally, the camera assembly 706 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the terminal, and the rear-facing camera is located on the back of the terminal. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, VR (Virtual Reality) shooting, or other fusion shooting functions. In some embodiments, the camera assembly 706 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm-light flash and a cool-light flash, which can be used for light compensation at different color temperatures.

[0122] The audio circuit 707 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, converting the sound waves into electrical signals that are input to the processor 701 for processing, or input to the radio frequency circuit 704 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each located at a different part of the terminal 700. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert the electrical signals from the processor 701 or the radio frequency circuit 704 into sound waves. The speaker may be a conventional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 707 may also include a headphone jack.

[0123] Power supply 708 is used to power the various components in terminal 700. Power supply 708 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 708 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, while a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0124] In some embodiments, the terminal 700 further includes one or more sensors 709. The one or more sensors 709 include, but are not limited to: an accelerometer 710, a gyroscope 711, a pressure sensor 712, an optical sensor 713, and a proximity sensor 714.

[0125] Accelerometer 710 can detect the magnitude of acceleration along the three coordinate axes of a coordinate system established by terminal 700. For example, accelerometer 710 can be used to detect the components of gravitational acceleration along the three coordinate axes. Processor 701 can control display screen 705 to display the user interface in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 710. Accelerometer 710 can also be used for games or for acquiring user motion data.

[0126] The gyroscope sensor 711 can detect the orientation and rotation angle of the terminal 700. The gyroscope sensor 711, in conjunction with the accelerometer sensor 710, can collect 3D motion data from the user on the terminal 700. Based on the data collected by the gyroscope sensor 711, the processor 701 can perform the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0127] The pressure sensor 712 can be disposed on the side bezel of the terminal 700 and / or on the lower layer of the display screen 705. When the pressure sensor 712 is disposed on the side bezel of the terminal 700, it can detect the user's grip signal on the terminal 700, and the processor 701 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 712. When the pressure sensor 712 is disposed on the lower layer of the display screen 705, the processor 701 can control the operable controls on the UI interface based on the user's pressure operation on the display screen 705. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0128] An optical sensor 713 is used to collect ambient light intensity. In one embodiment, the processor 701 can control the display brightness of the display screen 705 based on the ambient light intensity collected by the optical sensor 713. Specifically, when the ambient light intensity is high, the display brightness of the display screen 705 is increased; when the ambient light intensity is low, the display brightness of the display screen 705 is decreased. In another embodiment, the processor 701 can also dynamically adjust the shooting parameters of the camera assembly 706 based on the ambient light intensity collected by the optical sensor 713.

[0129] The proximity sensor 714, also known as a distance sensor, is typically located on the front panel of the terminal 700. The proximity sensor 714 is used to detect the distance between the user and the front of the terminal 700. In one embodiment, when the proximity sensor 714 detects that the distance between the user and the front of the terminal 700 is gradually decreasing, the processor 701 controls the display screen 705 to switch from a screen-on state to a screen-off state; when the proximity sensor 714 detects that the distance between the user and the front of the terminal 700 is gradually increasing, the processor 701 controls the display screen 705 to switch from a screen-off state to a screen-on state.

[0130] Those skilled in the art will understand that Figure 7 The structure shown does not constitute a limitation on terminal 700, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0131] In some embodiments, the electronic device is provided as a server. A structural block diagram of the server can be found... Figure 8The server 800 can vary considerably depending on its configuration or performance. It may include a Central Processing Unit (CPU) 801 and a memory 802. The memory 802 stores at least one line of program code, which is loaded and executed by the processor 801 to implement the aforementioned method for determining the seismic wave absorption attenuation model. Of course, the server 800 may also have wired or wireless network interfaces, a keyboard, and input / output interfaces for input and output. The server 800 may also include other components for implementing device functions, which will not be elaborated upon here.

[0132] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one line of program code that is loaded and executed by a processor to implement the method for determining the seismic wave absorption attenuation model in the above embodiments.

[0133] In an exemplary embodiment, a computer program product is also provided, which stores at least one line of program code that is loaded and executed by a processor to implement the method for determining the seismic wave absorption attenuation model in the above embodiments.

[0134] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0135] The above description is only for the purpose of enabling those skilled in the art to understand the technical solution of this application, and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method of determining a seismic wave absorption attenuation model, characterized by, The method comprises: acquiring microlog interpretation result data corresponding to each well in a target area, the microlog interpretation result data of each well comprising thicknesses of multiple horizons, velocities and initial quality factor Q values of multiple measuring points in each horizon; for each horizon of each well, determining first relationship data based on the velocities and initial Q values of the multiple measuring points in the horizon, the first relationship data being used to represent a relationship between the velocities and actual Q values of the measuring points; determining reliable points and abnormal points from the multiple measuring points based on the first relationship data, the abnormal points being points with abnormal initial Q values; determining actual Q values of the abnormal points based on the first relationship data; determining a seismic wave absorption attenuation model based on the initial Q values of the reliable points, the actual Q values of the abnormal points and the thicknesses of the horizons in each well.

2. The method of claim 1, wherein, The determining of the first relationship data based on the velocities and initial Q values of the multiple measuring points in the horizon comprises: constructing an exponential function used to represent a relationship between the velocities and actual Q values of the measuring points; taking logarithms of both sides of the exponential function to obtain a linear function; performing linear fitting on the linear function based on the velocities and initial Q values of the multiple measuring points to obtain the first relationship data.

3. The method of claim 1, wherein, The determining of the reliable points and abnormal points from the multiple measuring points comprises: plotting a fitting straight line in a rectangular coordinate system based on the first relationship data, the rectangular coordinate system taking a logarithm of the actual Q value as a vertical coordinate and a logarithm of the velocity as a horizontal coordinate; determining positions of the multiple measuring points in the rectangular coordinate system based on the velocities and initial Q values of the multiple measuring points; determining a deviation degree between the position of each measuring point and the fitting straight line; determining a measuring point with a deviation degree greater than a preset deviation degree as the abnormal point and a measuring point with a deviation degree not greater than the preset deviation degree as the reliable point.

4. The method of claim 1, wherein, The microlog interpretation result data of each well further comprises a velocity of a missing point in each horizon, the missing point being a measuring point lacking an initial Q value; The determining of the seismic wave absorption attenuation model based on the initial Q values of the reliable points, the actual Q values of the abnormal points and the thicknesses of the horizons in each well comprises: for each horizon, substituting the velocity of the missing point into the first relationship data to obtain an actual Q value of the missing point; determining the seismic wave absorption attenuation model based on the initial Q values of the reliable points, the actual Q values of the abnormal points, the actual Q value of the missing point and the thicknesses of the horizons in each well.

5. The method of claim 4, wherein, The determining of the seismic wave absorption attenuation model based on the actual Q values of the reliable points, the actual Q values of the abnormal points, the actual Q value of the missing point and the thicknesses of the horizons in each well comprises: adopting a horizon modeling and interpolation method to construct the seismic wave absorption attenuation model based on the actual Q values of the reliable points, the actual Q values of the abnormal points, the actual Q value of the missing point and the thicknesses of the horizons in each well.

6. The method of claim 1, wherein, The determining of the actual Q values of the abnormal points based on the first relationship data comprises: The velocity of the abnormal point is substituted into the first relationship data to obtain an actual Q value of the abnormal point.

7. A seismic wave absorption attenuation model determination apparatus characterized by comprising: The device comprises: An acquisition module is configured to acquire microlog interpretation result data corresponding to each well in a target area, wherein the microlog interpretation result data of each well comprises thicknesses of multiple layers, velocities of multiple measuring points in each layer, and initial quality factors Q of the measuring points; A first determination module is configured to determine, for each layer of each well, first relationship data based on the velocities and the initial Q values of the measuring points in the layer, wherein the first relationship data is used to represent a relationship between the velocities and actual Q values of the measuring points; A second determination module is configured to determine, based on the first relationship data, reliable points and abnormal points from the multiple measuring points, wherein the abnormal points are points with abnormal initial Q values; A third determination module is configured to determine, based on the first relationship data, an actual Q value of the abnormal point; A fourth determination module is configured to determine, based on the initial Q values of the reliable points, the actual Q value of the abnormal point, and the thickness of the layer, a seismic wave absorption attenuation model.

8. An electronic device, comprising: The electronic device comprises a processor and a memory, and the memory stores at least one program code, which is loaded and executed by the processor to implement the method for determining a seismic wave absorption attenuation model according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one program code, which is loaded and executed by the processor to implement the method for determining a seismic wave absorption attenuation model according to any one of claims 1 to 6.

10. A computer program product, characterised in that, The computer program product stores at least one program code, which is loaded and executed by the processor to implement the method for determining a seismic wave absorption attenuation model according to any one of claims 1 to 6.

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