Fault determination method and device, computer device and storage medium

Abstract

The application provides a fault determination method and device, computer equipment and a storage medium, and belongs to the technical field of geophysical exploration. The method comprises the following steps: obtaining original seismic data of a target area to be studied, wherein the original seismic data comprises waveform data of a plurality of seismic traces; for each seismic trace, determining an inclination parameter of the seismic trace based on the waveform data of the seismic trace, wherein the seismic trace comprises a plurality of sampling points, and the inclination parameter of the seismic trace comprises an inclination angle of each sampling point; performing difference processing on the inclination angle of each sampling point to obtain a peak value parameter of the seismic trace; generating a peak value stereogram of the target area based on the peak value parameters of the plurality of seismic traces; and determining a fault in the target area based on the peak value stereogram. The method improves the accuracy of determining the fault.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration technology, and in particular to a method, apparatus, computer equipment, and storage medium for determining faults. Background Technology

[0002] A fault is a geological phenomenon in which rock strata or rock masses shift along a fracture surface. Different faults extend to different distances along their fracture direction, and the displacement along the fault varies. During the adjustment phase of oilfield development, identifying faults within the oilfield area is crucial for guiding reservoir potential tapping in that region.

[0003] In related technologies, faults are generally determined by methods such as pre-stack fracture prediction technology and post-stack seismic attribute technology. However, the accuracy of fault determination by these methods is limited. They can only determine large faults with large fault displacement and long extension distance, but it is difficult to determine small faults with small fault displacement and short extension distance, which leads to low accuracy of fault determination. Summary of the Invention

[0004] This application provides a method, apparatus, computer device, and storage medium for determining faults, which can improve the accuracy of fault determination. The technical solution is as follows:

[0005] On the one hand, a method for determining faults is provided, the method comprising:

[0006] Obtain raw seismic data of the target area to be studied, wherein the raw seismic data includes waveform data from multiple seismic traces;

[0007] For each seismic trace, the dip angle parameter of the seismic trace is determined based on the waveform data of the seismic trace. The seismic trace includes multiple sampling points, and the dip angle parameter of the seismic trace includes the tilt angle of each sampling point.

[0008] The peak parameters of the seismic trace are obtained by performing differential processing on the tilt angle of each sampling point.

[0009] Based on the peak parameters of the multiple seismic traces, a peak 3D map of the target area is generated;

[0010] Based on the peak stereoscopic image, faults in the target region are determined.

[0011] In one possible implementation, determining the dip parameter of the seismic trace based on its waveform data includes:

[0012] For each sampling point included in the seismic trace, the slope of the sampling point is determined based on the first waveform data of the sampling point and the second waveform data of the next sampling point;

[0013] The slope of the sampling point is processed by arctangent to obtain the tilt angle of the sampling point.

[0014] In one possible implementation, the waveform data for each sampling point includes the sampling time of the sampling point and the amplitude value of the seismic trace at the sampling point. Determining the slope of the sampling point based on the first waveform data of the sampling point and the second waveform data of the next sampling point includes:

[0015] Determine the time difference between the sampling time of the next sampling point and the sampling time of the sampling point, and the amplitude difference between the amplitude value of the next sampling point and the amplitude value of the sampling point;

[0016] The slope of the sampling point is obtained by determining the quotient of the amplitude difference and the time difference.

[0017] In one possible implementation, the step of interpolating the tilt angle of each sampling point to obtain the peak parameters of the seismic trace includes:

[0018] Determine the difference between the tilt angle of the previous sampling point and the tilt angle of the current sampling point;

[0019] The difference is taken as the difference angle of the sampling points.

[0020] In one possible implementation, the peak parameters of the seismic trace include the difference angle at each sampling point of the seismic trace, and determining the fault in the target region based on the peak stereogram includes:

[0021] The peak stereogram is divided into multiple seismic profiles;

[0022] For each seismic profile, a target stratum is determined from the seismic profile. The target stratum is a stratum where the difference angle exhibits a preset discontinuity characteristic.

[0023] Identify faults on each target stratum;

[0024] Faults on multiple target strata are combined to form the faults of the target area.

[0025] In one possible implementation, determining the fault on each target stratum includes:

[0026] For each target formation, coherent attributes are extracted from the target formation to obtain a coherent attribute map of the target formation;

[0027] Identify the faults on the coherence property map;

[0028] The faults on the coherence attribute map are taken as faults on the target stratum.

[0029] On the other hand, a fault-determining device is provided, the device comprising:

[0030] The acquisition module is used to acquire raw seismic data of the target area to be studied, wherein the raw seismic data includes waveform data of multiple seismic traces;

[0031] The first determining module is used to determine the dip angle parameter of each seismic trace based on the waveform data of the seismic trace. The seismic trace includes multiple sampling points, and the dip angle parameter of the seismic trace includes the tilt angle of each sampling point.

[0032] The processing module is used to perform differential processing on the tilt angle of each sampling point to obtain the peak parameters of the seismic trace;

[0033] A generation module is used to generate a peak stereo map of the target area based on the peak parameters of the multiple seismic traces;

[0034] The second determining module is used to determine the fault in the target region based on the peak stereoscopic image.

[0035] In one possible implementation, the first determining module includes:

[0036] The first determining unit is configured to determine the slope of each sampling point included in the seismic trace based on the first waveform data of the sampling point and the second waveform data of the next sampling point.

[0037] The first processing unit is used to perform arctangent processing on the slope of the sampling point to obtain the tilt angle of the sampling point.

[0038] In one possible implementation, the waveform data for each sampling point includes the sampling time of the sampling point and the amplitude value of the seismic trace at the sampling point. The first determining unit is configured to:

[0039] Determine the time difference between the sampling time of the next sampling point and the sampling time of the sampling point, and the amplitude difference between the amplitude value of the next sampling point and the amplitude value of the sampling point;

[0040] The slope of the sampling point is obtained by determining the quotient of the amplitude difference and the time difference.

[0041] In one possible implementation, the processing module is configured to:

[0042] Determine the difference between the tilt angle of the previous sampling point and the tilt angle of the current sampling point;

[0043] The difference is taken as the difference angle of the sampling points.

[0044] In one possible implementation, the peak parameter of the seismic trace includes the difference angle of each sampling point of the seismic trace, and the second determining module includes:

[0045] A dividing unit is used to divide the peak stereoscopic image into multiple seismic profiles;

[0046] The first determining unit is used to determine the target stratum from the seismic profile for each seismic profile, wherein the target stratum is a stratum in which the difference angle exhibits a preset discontinuity feature;

[0047] The second determining unit is used to determine the faults on each target stratum;

[0048] The constituent unit is used to form the faults of the target area by combining multiple faults on the target strata.

[0049] In one possible implementation, the second determining unit is configured to:

[0050] For each target formation, coherent attributes are extracted from the target formation to obtain a coherent attribute map of the target formation;

[0051] Identify the faults on the coherence property map;

[0052] The faults on the coherence attribute map are taken as faults on the target stratum.

[0053] On the other hand, a computer device is provided, the computer device including one or more processors and one or more memories, the one or more memories storing at least one instruction, the at least one instruction being loaded and executed by the one or more processors to perform the operations performed by the tomography determination method described in any of the above implementations.

[0054] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction is stored in the computer-readable storage medium, the at least one instruction being loaded and executed by a processor to perform the operations performed by the tomography determination method described in any of the above implementations.

[0055] On the other hand, a computer program product or computer program is provided, the computer program product or computer program including computer program code stored in a computer-readable storage medium. A processor of a computer device reads the computer program code from the computer-readable storage medium, and the processor executes the computer program code, causing the computer device to perform the operations performed by the aforementioned tomography determination method.

[0056] The beneficial effects of the technical solutions provided in this application include at least the following:

[0057] This application provides a method for determining faults. This method obtains the peak parameters of the seismic trace by performing differential processing on the tilt angle of each sampling point in the seismic trace. In this way, the peak parameters can highlight the peak characteristics of the waveform data of the seismic trace and achieve a fine characterization of the changing trend of the waveform data. Furthermore, based on the changing trend of the peak parameters in the peak stereoscopic image, the fault in the target area can be accurately determined, thereby improving the accuracy of fault determination. Attached Figure Description

[0058] 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.

[0059] Figure 1 This is a flowchart of a method for determining a fault according to an embodiment of this application;

[0060] Figure 2 This is a seismic waveform diagram of a seismic trace provided in an embodiment of this application;

[0061] Figure 3 This is an angle value curve provided in an embodiment of this application;

[0062] Figure 4 This is a difference curve provided in an embodiment of this application;

[0063] Figure 5 This is a seismic profile provided in an embodiment of this application;

[0064] Figure 6 This is an original seismic profile provided in an embodiment of this application;

[0065] Figure 7 This is a coherent attribute map provided in an embodiment of this application;

[0066] Figure 8 This is a coherent attribute map provided in an embodiment of this application;

[0067] Figure 9 This is a block diagram of a tomography device provided in an embodiment of this application;

[0068] Figure 10 This is a block diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0070] 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.

[0071] This application provides a method for determining a fault, see [link to relevant documentation] Figure 1 The methods include:

[0072] Step 101: The computer equipment acquires the raw seismic data of the target area to be studied. The raw seismic data includes waveform data from multiple seismic traces.

[0073] The target area is an unconventional oil and gas exploration area where horizontal wells are to be laid out, and this target area includes multiple strata.

[0074] It should be noted that the raw seismic data for the target area can be directly obtained from the existing seismic data for the region. Each seismic trace includes multiple sampling points, and the waveform data for each sampling point includes the sampling time and the amplitude value of the seismic trace at that sampling point.

[0075] See Figure 2 , Figure 2 The image shows the seismic waveform of a specific seismic trace. It can be seen that the waveform data in this embodiment is transverse wave data, and the seismic waveform reflects the transverse changes in the waveform of the seismic trace. The seismic waveform includes multiple sampling points, with the vertical axis representing the sampling time and the horizontal axis representing the amplitude value. As can be seen from the image, the amplitude values ​​at multiple sampling points vary relatively little, making it difficult to determine the trend of amplitude changes at multiple sampling points based on this seismic waveform.

[0076] Step 102: For each seismic trace, the computer equipment determines the dip angle parameters of the seismic trace based on the waveform data of the seismic trace.

[0077] It should be noted that the seismic trace includes multiple sampling points, and the dip parameter of the seismic trace includes the tilt angle of each sampling point.

[0078] This step can be achieved through the following steps (1)-(2):

[0079] (1) For each sampling point included in the seismic trace, the computer equipment determines the slope of the sampling point based on the first waveform data of the sampling point and the second waveform data of the next sampling point.

[0080] The waveform data for each sampling point includes the sampling time at that sampling point and the amplitude value of the seismic trace at that sampling point. The waveform data for that sampling point can be represented as (t... i , z i The waveform data of the next sampling point can be represented as (t) i+1 , z i+1 ), where t is the sampling time and z is the amplitude value.

[0081] This step is achieved through the following steps A1-A2:

[0082] A1: The computer equipment determines the time difference between the sampling time of the next sampling point and the sampling time of the current sampling point, as well as the amplitude difference between the amplitude value of the next sampling point and the amplitude value of the current sampling point.

[0083] The time difference between the sampling time of the next sampling point and the sampling time of the current sampling point is expressed as (t). i+1 -t i The amplitude difference between the amplitude value of the next sampling point and the amplitude value of the current sampling point is expressed as (z). i+1 -z i ).

[0084] A2: The computer equipment determines the quotient of the amplitude difference and the time difference, and obtains the slope of the sampling point.

[0085] The slope of the sampling point can be obtained using the following formula.

[0086] Formula 1: k = (z i+1 -z i ) / (t i+1 -t i )

[0087] Where k is the slope, (z i+1 -z i ) represents the amplitude difference, (t) i+1 -t i () represents the time difference.

[0088] It should be noted that since the last sampling point has no corresponding next sampling point, the slope of the last sampling point is not determined.

[0089] In this embodiment, the slope of each sampling point was determined one by one using the two-point method, thereby determining the amplitude value change trend of multiple sampling points.

[0090] (2) The computer equipment performs arctangent processing on the slope of the sampling point to obtain the tilt angle of the sampling point.

[0091] In this embodiment, the computer device performs an arctangent operation on the slope of the sampling point using the arctangent function in the inverse trigonometric functions to obtain the arctangent function value, which is used as the tilt angle of the sampling point. It should be noted that the range of the arctangent function value is (-π / 2, π / 2), that is, the range of the tilt angle is (-π / 2, π / 2).

[0092] Arctangent function: θ = arctank

[0093] Where θ is the tilt angle of the sampling point, and k is the slope of the sampling point.

[0094] It should be noted that for the last sampling point, there is no next sampling point; the computer device performs arctangent processing on the amplitude value of the last sampling point, and the obtained arctangent function value is used as the tilt angle of the last sampling point, thereby realizing the determination of the tilt angle of all sampling points.

[0095] join Figure 3 , Figure 3 To and Figure 2 The graph shows the angle value curve of the dip parameter for a specific seismic trace. This curve includes multiple sampling points, with the vertical axis representing the sampling time and the horizontal axis representing the dip angle. The graph shows significant differences in the dip angles among the sampling points; some adjacent sampling points have the same dip angle, while others show a gradual increase or decrease in dip angle. The angle value curve exhibits a clear inflection point, and the trend of amplitude changes among the sampling points can be observed based on this curve.

[0096] Step 103: The computer equipment performs differential processing on the tilt angle of each sampling point to obtain the peak parameters of the seismic trace.

[0097] The peak parameters of the seismic trace include the difference angle at each sampling point of the seismic trace.

[0098] This step can be achieved through the following steps (1)-(2):

[0099] (1) The computer equipment determines the difference between the tilt angle of the previous sampling point and the tilt angle of the current sampling point.

[0100] (2) The computer equipment uses the difference as the difference angle of the sampling point.

[0101] It should be noted that since the first sampling point has no corresponding previous sampling point, the difference angle of the first sampling point is assigned to zero.

[0102] See Figure 4 , Figure 4 To and Figure 3 The graph shows the difference curve of the peak parameters for a specific seismic trace. This curve includes multiple sampling points, with the vertical axis representing the sampling time and the horizontal axis representing the difference angle. As can be seen from the graph, there are significant differences in the difference angles among the various sampling points; some sampling points have a difference angle of zero, while others reach their maximum and minimum values ​​within a certain range, highlighting the peak characteristics of the wave and clearly depicting the horizontal trend of the seismic trace's waveform data.

[0103] Step 104: The computer equipment generates a peak stereo map of the target area based on the peak parameters of multiple seismic traces.

[0104] See also Figure 4 Computer equipment will be like Figure 4 The difference curves of multiple seismic traces shown are combined sequentially according to the arrangement of the seismic traces to obtain a peak three-dimensional map of the target area.

[0105] In another possible implementation, the computer device inputs the peak parameters of multiple seismic traces into the plotting module to directly generate a peak stereo map.

[0106] It should be noted that the peak value stereogram is a three-dimensional image, including both horizontal and vertical seismic profiles. See also... Figure 5 , Figure 5 This is a seismic profile at a specific lateral angle, which includes difference curves from multiple seismic traces. See also... Figure 6 , Figure 6 To and Figure 5 The original seismic profile generated from waveform data of multiple corresponding seismic traces shows that the seismic waveforms at the strata corresponding to the dashed lines in the original seismic profile are relatively stable laterally, without fault response characteristics, meaning no fault has been identified. In contrast... Figure 5 In the strata corresponding to the position of the dashed line, it can be seen that the difference angle shows a clear discontinuity at the position indicated by the circle, that is, the response characteristics of a fault appear. From the above comparison, it can be seen that the peak value stereogram determined by the embodiments of this application can effectively highlight the characteristics of the fault and can identify faults that cannot be identified by the original seismic profile. In other words, the method provided by the embodiments of this application has higher accuracy in determining faults.

[0107] Step 105: The computer equipment determines the faults in the target area based on the peak stereoscopic image.

[0108] This step can be achieved through the following steps (1)-(4):

[0109] (1) The computer equipment divides the peak stereo map into multiple seismic profiles.

[0110] See also Figure 5 The computer equipment divides the peak stereogram into such... Figure 5 The multiple seismic profiles shown.

[0111] (2) For each seismic profile, the computer equipment determines the target stratum from the seismic profile. The target stratum is the stratum where the difference angle shows a preset discontinuity feature.

[0112] See also Figure 5 If any stratum exhibits a discontinuity in the angle difference at the location indicated by the circle in the figure, then that stratum is designated as the target stratum. It should be noted that if the stratum is continuous and without faults, the angle difference should be continuous and uninterrupted. If the angle difference is discontinuous at any point, it indicates that a fault has occurred in that stratum.

[0113] (3) Computer equipment identifies faults on each target stratum.

[0114] This step can be achieved through the following steps A1-A3:

[0115] A1: For each target formation, the computer equipment extracts coherent attributes to obtain a coherent attribute map of the target formation.

[0116] Among them, coherence attribute is a seismic attribute that highlights and emphasizes the lack of correlation in seismic data. This attribute is used to determine faults through the analysis of discontinuous strata. In the embodiments of this application, the computer device extracts the coherence attribute of the target strata based on the difference angle of the target strata, and obtains the coherence attribute map of the target strata. The coherence attribute map is a planar distribution map of the target strata.

[0117] In this embodiment of the application, by extracting coherent attributes from the target strata, the generated coherent attribute map can highlight and emphasize the incoherence of the difference angles. See also Figure 7 , Figure 7 for Figure 5 The coherence property map of the target strata at the circled area clearly shows that there are obvious discontinuities in some dark areas, indicating that the difference angles in these areas are incoherent and are discontinuous faults. The occurrence of faults causes discontinuities in the difference angles of each coherent path.

[0118] A2: Computer equipment determines faults on the coherence attribute map.

[0119] See also Figure 7The dark areas in the figure represent areas where the difference angles are discontinuous. These areas are identified as faults on the coherence attribute map. The coherence attribute map of the target stratum includes at least one fault.

[0120] See Figure 8 , Figure 8 for Figure 6 The coherence property diagram of the strata corresponding to the dashed lines in the diagram. Figure 8 This is a coherent attribute map of the formation obtained by extracting coherent attributes based on the formation's amplitude values. (Comparison) Figure 7 and Figure 8 It can be seen that, Figure 8 Only faults with obvious intermediate breaks in the strata were identified, while Figure 7 The study not only identified faults with obvious discontinuities in the target strata, but also faults with less obvious discontinuities. Figure 8 The absence of identified faults indicates that extracting coherence attributes through the difference angles of the target strata yields a more accurate coherence attribute map. Among these, Figure 7 The obvious discontinuities in the fault map are large faults with large displacement and long extension distance, while the indistinct faults are small faults with small displacement and short extension distance. This shows that the coherence attribute map extracted through the embodiments of this application can not only identify large faults with large displacement and long extension distance, but also identify small faults with small displacement and short extension distance, thus making the fault identification highly accurate.

[0121] A3: The computer equipment uses the faults on the coherent attribute map as faults on the target stratum.

[0122] It should be noted that since the coherence attribute map is obtained by extracting coherence attributes based on the difference angle of the target stratum, the faults on the coherence attribute map represent the faults on the target stratum. Therefore, the faults on the coherence attribute map are taken as the faults on the target stratum.

[0123] In this embodiment of the application, the computer device determines the faults on the target stratum, realizes the characterization of the faults in the plane distribution, and thus can effectively determine the faults on the target stratum.

[0124] (4) The computer equipment will combine the faults on multiple target strata into the faults of the target area.

[0125] Each target stratum includes at least one fault, and the computer equipment combines the multiple faults included in the multiple target strata into a fault in the target area.

[0126] It should be noted that the method provided by the embodiments of this application can improve the accuracy of determining faults in the target area. Even small faults with small displacement and short extension distance can be accurately determined, thereby providing reliable technical support for the fine structural interpretation of the target area, adjustment of development plan, and unconventional oil and gas exploration. In other words, it provides reliable technical support for early warning of horizontal well drilling in the target area, thereby improving the efficiency of horizontal well drilling.

[0127] This application provides a method for determining faults. This method obtains the peak parameters of the seismic trace by performing differential processing on the tilt angle of each sampling point in the seismic trace. In this way, the peak parameters can highlight the peak characteristics of the waveform data of the seismic trace and achieve a fine characterization of the changing trend of the waveform data. Furthermore, based on the changing trend of the peak parameters in the peak stereoscopic image, the fault in the target area can be accurately determined, thereby improving the accuracy of fault determination.

[0128] This application also provides a device for determining a fault, see [link to relevant documentation]. Figure 9 The device includes:

[0129] The acquisition module 901 is used to acquire the raw seismic data of the target area to be studied. The raw seismic data includes waveform data from multiple seismic traces.

[0130] The first determining module 902 is used to determine the dip angle parameter of each seismic trace based on the waveform data of the seismic trace. The seismic trace includes multiple sampling points, and the dip angle parameter of the seismic trace includes the tilt angle of each sampling point.

[0131] The processing module 903 is used to perform differential processing on the tilt angle of each sampling point to obtain the peak parameters of the seismic trace;

[0132] The generation module 904 is used to generate a peak stereo map of the target area based on the peak parameters of multiple seismic traces.

[0133] The second determining module 905 is used to determine faults in the target area based on the peak stereoscopic image.

[0134] In one possible implementation, the first determining module 902 includes:

[0135] The first determining unit is used to determine the slope of each sampling point included in the seismic trace based on the first waveform data of the sampling point and the second waveform data of the next sampling point.

[0136] The first processing unit is used to perform arctangent processing on the slope of the sampling point to obtain the tilt angle of the sampling point.

[0137] In one possible implementation, the waveform data for each sampling point includes the sampling time of the sampling point and the amplitude value of the seismic trace at the sampling point. A first determining unit is used for:

[0138] Determine the time difference between the sampling time of the next sampling point and the sampling time of the sampling point, as well as the amplitude difference between the amplitude value of the next sampling point and the amplitude value of the sampling point;

[0139] The slope of the sampling point is obtained by determining the quotient of the amplitude difference and the time difference.

[0140] In one possible implementation, processing module 903 is used for:

[0141] Determine the difference between the tilt angle of the previous sampling point and the tilt angle of the current sampling point;

[0142] The difference is used as the angle of difference between the sampling points.

[0143] In one possible implementation, the peak parameters of the seismic trace include the difference angle at each sampling point of the seismic trace, and the second determining module 905 includes:

[0144] Divide the data into units, which are used to divide the peak stereo map into multiple seismic profiles;

[0145] The first determining unit is used to determine the target stratum from each seismic profile. The target stratum is the stratum where the difference angle exhibits a preset discontinuity characteristic.

[0146] The second determining unit is used to determine the faults on each target stratum;

[0147] Compositional units are used to combine faults on multiple target strata into faults in the target area.

[0148] In one possible implementation, the second determining unit is used for:

[0149] For each target formation, coherent attributes are extracted to obtain a coherent attribute map of the target formation.

[0150] Identify faults on the coherence property map;

[0151] Faults on the coherence attribute map are used as faults on the target strata.

[0152] Figure 10This illustration shows a structural block diagram of a computer device 1000 provided in an exemplary embodiment of this application. The computer device 1000 may be a portable mobile computer device, 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 computer device 1000 may also be referred to as a user device, portable computer device, laptop computer device, desktop computer device, or other names.

[0153] Typically, computer device 1000 includes a processor 1001 and a memory 1002.

[0154] Processor 1001 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 1001 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 1001 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 1001 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the screen. In some embodiments, processor 1001 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0155] The memory 1002 may include one or more computer-readable storage media, which may be non-transitory. The memory 1002 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 1002 are used to store at least one instruction, which is executed by the processor 1001 to implement the tomography determination method provided in the method embodiments of this application.

[0156] In some embodiments, the computer device 1000 may optionally include a peripheral device interface 1003 and at least one peripheral device. The processor 1001, memory 1002, and peripheral device interface 1003 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 1003 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of the following: a radio frequency circuit 1004, a display screen 1005, a camera assembly 1006, an audio circuit 1007, a positioning assembly 1008, and a power supply 1009.

[0157] Peripheral device interface 1003 can be used to connect at least one I / O (Input / Output) related peripheral device to processor 1001 and memory 1002. In some embodiments, processor 1001, memory 1002 and peripheral device interface 1003 are integrated on the same chip or circuit board; in some other embodiments, any one or two of processor 1001, memory 1002 and peripheral device interface 1003 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0158] The radio frequency (RF) circuit 1004 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 1004 communicates with communication networks and other communication devices via electromagnetic signals. The RF circuit 1004 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 1004 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 1004 can communicate with other computer devices via 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 1004 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0159] Display screen 1005 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 1005 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 1001 for processing. In this case, display screen 1005 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, display screen 1005 may be a single screen disposed on the front panel of computer device 1000; in other embodiments, display screen 1005 may be at least two screens, disposed on different surfaces of computer device 1000 or in a folded design; in still other embodiments, display screen 1005 may be a flexible display screen disposed on a curved or folded surface of computer device 1000. Furthermore, display screen 1005 may also be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. The display screen 1005 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0160] The camera assembly 1006 is used to acquire images or videos. Optionally, the camera assembly 1006 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the computer device, and the rear-facing camera is located on the back of the computer device. 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 1006 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.

[0161] The audio circuit 1007 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 1001 for processing, or input to the radio frequency circuit 1004 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each located in a different part of the computer device 1000. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from the processor 1001 or the radio frequency circuit 1004 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 1007 may also include a headphone jack.

[0162] The positioning component 1008 is used to locate the current geographical location of the computer device 1000 in order to enable navigation or LBS (Location Based Service). The positioning component 1008 can be a positioning component based on the US GPS (Global Positioning System), China's BeiDou system, or Russia's Galileo system.

[0163] Power supply 1009 is used to supply power to the various components in computer device 1000. Power supply 1009 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 1009 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, and 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.

[0164] In some embodiments, the computer device 1000 further includes one or more sensors 1010. The one or more sensors 1010 include, but are not limited to: an accelerometer 1011, a gyroscope 1012, a pressure sensor 1013, a fingerprint sensor 1014, an optical sensor 1015, and a proximity sensor 1016.

[0165] Accelerometer 1011 can detect the magnitude of acceleration along the three coordinate axes of a coordinate system established by computer device 1000. For example, accelerometer 1011 can be used to detect the components of gravitational acceleration along the three coordinate axes. Processor 1001 can control display screen 1005 to display the user interface in either a landscape or portrait view based on the gravitational acceleration signal acquired by accelerometer 1011. Accelerometer 1011 can also be used for games or for acquiring user motion data.

[0166] The gyroscope sensor 1012 can detect the orientation and rotation angle of the computer device 1000. The gyroscope sensor 1012 can work in conjunction with the accelerometer sensor 1011 to acquire the user's 3D movements on the computer device 1000. Based on the data acquired by the gyroscope sensor 1012, the processor 1001 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.

[0167] The pressure sensor 1013 can be disposed on the side bezel of the computer device 1000 and / or on the lower layer of the display screen 1005. When the pressure sensor 1013 is disposed on the side bezel of the computer device 1000, it can detect the user's grip signal on the computer device 1000, and the processor 1001 can perform left / right hand recognition or quick operation based on the grip signal collected by the pressure sensor 1013. When the pressure sensor 1013 is disposed on the lower layer of the display screen 1005, the processor 1001 can control the operable controls on the UI interface based on the user's pressure operation on the display screen 1005. The operable controls include at least one of button controls, scroll bar controls, icon controls, and menu controls.

[0168] The fingerprint sensor 1014 is used to collect a user's fingerprint. The processor 1001 identifies the user based on the fingerprint collected by the fingerprint sensor 1014, or vice versa. When the user's identity is identified as trusted, the processor 1001 authorizes the user to perform relevant sensitive operations, including unlocking the screen, viewing encrypted information, downloading software, making payments, and changing settings. The fingerprint sensor 1014 can be located on the front, back, or side of the computer device 1000. When the computer device 1000 has physical buttons or a manufacturer's logo, the fingerprint sensor 1014 can be integrated with the physical buttons or the manufacturer's logo.

[0169] An optical sensor 1015 is used to collect ambient light intensity. In one embodiment, the processor 1001 can control the display brightness of the display screen 1005 based on the ambient light intensity collected by the optical sensor 1015. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1005 is increased; when the ambient light intensity is low, the display brightness of the display screen 1005 is decreased. In another embodiment, the processor 1001 can also dynamically adjust the shooting parameters of the camera assembly 1006 based on the ambient light intensity collected by the optical sensor 1015.

[0170] The proximity sensor 1016, also known as a distance sensor, is typically installed on the front panel of the computer device 1000. The proximity sensor 1016 is used to detect the distance between the user and the front of the computer device 1000. In one embodiment, when the proximity sensor 1016 detects that the distance between the user and the front of the computer device 1000 is gradually decreasing, the processor 1001 controls the display screen 1005 to switch from a screen-on state to a screen-off state; when the proximity sensor 1016 detects that the distance between the user and the front of the computer device 1000 is gradually increasing, the processor 1001 controls the display screen 1005 to switch from a screen-off state to a screen-on state.

[0171] Those skilled in the art will understand that Figure 10 The structure shown does not constitute a limitation on the computer device 1000, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0172] This application also provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to perform the operation of the tomography determination method in any of the above implementations.

[0173] This application also provides a computer program product or computer program, which includes computer program code stored in a computer-readable storage medium. The processor of a computer device reads the computer program code from the computer-readable storage medium and executes the computer program code, causing the computer device to perform the operations described above in the tomography determination method.

[0174] In some embodiments, the computer program involved in the present application embodiments may be deployed and executed on a computer device, or executed on multiple computer devices located in one location, or executed on multiple computer devices distributed in multiple locations and interconnected through a communication network. Multiple computer devices distributed in multiple locations and interconnected through a communication network may constitute a blockchain system.

[0175] This application provides a method for determining faults. This method obtains the peak parameters of the seismic trace by performing differential processing on the tilt angle of each sampling point in the seismic trace. In this way, the peak parameters can highlight the peak characteristics of the waveform data of the seismic trace and achieve a fine characterization of the changing trend of the waveform data. Furthermore, based on the changing trend of the peak parameters in the peak stereoscopic image, the fault in the target area can be accurately determined, thereby improving the accuracy of fault determination.

[0176] The above are merely optional embodiments of this application and are 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 for determining faults, characterized in that, The method includes: Obtain raw seismic data of the target area to be studied, wherein the raw seismic data includes waveform data from multiple seismic traces; For each seismic trace, the dip angle parameter of the seismic trace is determined based on the waveform data of the seismic trace. The seismic trace includes multiple sampling points, and the dip angle parameter of the seismic trace includes the tilt angle of each sampling point. The difference between the tilt angle of the previous sampling point and the tilt angle of the sampling point is determined, and the difference is used as the difference angle of the sampling point. Based on the difference angle of each sampling point, the peak parameter of the seismic trace is obtained. The peak parameter includes the difference angle of each sampling point. The peak parameter is used to characterize the peak characteristics of the seismic trace waveform and the trend of waveform change. Based on the peak parameters of the multiple seismic traces, a peak stereoscopic map of the target area is generated. The peak stereoscopic map is a three-dimensional map, including a horizontal seismic profile and a vertical seismic profile. The peak stereoscopic image is divided into multiple seismic profiles; for each seismic profile, a target stratum is determined from the seismic profile, the target stratum being a stratum with a preset discontinuity characteristic at the difference angle; faults on each target stratum are determined; the faults on multiple target strata are combined to form the faults of the target region.

2. The method for determining faults according to claim 1, characterized in that, Determining the dip parameter of the seismic trace based on its waveform data includes: For each sampling point included in the seismic trace, the slope of the sampling point is determined based on the first waveform data of the sampling point and the second waveform data of the next sampling point; The slope of the sampling point is processed by arctangent to obtain the tilt angle of the sampling point.

3. The method for determining faults according to claim 2, characterized in that, The waveform data for each sampling point includes the sampling time of the sampling point and the amplitude value of the seismic trace at the sampling point. Determining the slope of the sampling point based on the first waveform data of the sampling point and the second waveform data of the next sampling point includes: Determine the time difference between the sampling time of the next sampling point and the sampling time of the sampling point, and the amplitude difference between the amplitude value of the next sampling point and the amplitude value of the sampling point; The slope of the sampling point is obtained by determining the quotient of the amplitude difference and the time difference.

4. The method for determining faults according to claim 1, characterized in that, The determination of faults on each target stratum includes: For each target formation, coherent attributes are extracted from the target formation to obtain a coherent attribute map of the target formation; Identify the faults on the coherence property map; The faults on the coherence attribute map are taken as faults on the target stratum.

5. A device for determining faults, characterized in that, The device includes: The acquisition module is used to acquire raw seismic data of the target area to be studied, wherein the raw seismic data includes waveform data of multiple seismic traces; The first determining module is used to determine the dip angle parameter of each seismic trace based on the waveform data of the seismic trace. The seismic trace includes multiple sampling points, and the dip angle parameter of the seismic trace includes the tilt angle of each sampling point. The processing module is used to determine the difference between the tilt angle of the previous sampling point and the tilt angle of the sampling point, and use the difference as the difference angle of the sampling point. Based on the difference angle of each sampling point, the peak parameters of the seismic trace are obtained. The peak parameters include the difference angle of each sampling point. The peak parameters are used to characterize the peak characteristics of the seismic trace waveform and the trend of waveform change. The generation module is used to generate a peak stereoscopic image of the target area based on the peak parameters of the multiple seismic traces. The peak stereoscopic image is a three-dimensional image, including a horizontal seismic profile and a vertical seismic profile. The second determining module is used to divide the peak stereoscopic image into multiple seismic profiles; for each seismic profile, to determine the target stratum from the seismic profile, the target stratum being a stratum with a preset discontinuity feature at the difference angle; to determine the faults on each target stratum; and to form the faults of the target region by combining the faults on the multiple target strata.

6. The fault determination device according to claim 5, characterized in that, The first determining module includes: The first determining unit is configured to determine the slope of each sampling point included in the seismic trace based on the first waveform data of the sampling point and the second waveform data of the next sampling point. The first processing unit is used to perform arctangent processing on the slope of the sampling point to obtain the tilt angle of the sampling point.

7. A computer device, characterized in that, The computer device includes one or more processors and one or more memories, the one or more memories storing at least one instruction, the at least one instruction being loaded and executed by the one or more processors to perform the operations performed by the method for determining a tomography as described in any one of claims 1 to 4.

8. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, which is loaded and executed by a processor to perform the operation of the tomography determination method as described in any one of claims 1 to 4.

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