WO2020140803A1 - 高角度裂缝预测方法、计算机设备及计算机可读存储介质 - Google Patents
高角度裂缝预测方法、计算机设备及计算机可读存储介质 Download PDFInfo
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- G—PHYSICS
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N3/24—Investigating strength properties of solid materials by application of mechanical stress by applying steady shearing forces
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/282—Application of seismic models, synthetic seismograms
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/10—Aspects of acoustic signal generation or detection
- G01V2210/16—Survey configurations
- G01V2210/165—Wide azimuth
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
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- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/64—Geostructures, e.g. in 3D data cubes
- G01V2210/642—Faults
Definitions
- the invention relates to the field of oil and gas exploration technology, in particular to a high-angle fracture prediction method, computer equipment and computer-readable storage medium.
- the result of azimuth amplitude variation with offset (AVAz) prediction is to reflect interface information, and is not suitable for prediction of fracture information within the reservoir.
- Analysis (VVAz) is based on the velocity difference information of wide-azimuth seismic processing, which belongs to the formation interval information, and its result resolution is too low, which can only control the distribution law of fractures better; the methods that are more suitable for fracture prediction in the reservoir are various Anisotropic inversion, the fracture prediction results of this method reflect the information of fractures in the reservoir interval, which is suitable for quantitative research of fractures in the internal interval of the reservoir, but this method inverts fracture prediction in azimuthal anisotropy In the process, the use of isotropic low-frequency model is unreasonable, and the source of low-frequency information is limited. It is easy to cause the regularity of fracture prediction results to be weak, and the anisotropic information of azimuth seismic data is suppressed.
- Embodiments of the present invention provide a high-angle fracture prediction method, computer equipment, and computer-readable storage medium.
- the anisotropy difference information of the longitudinal wave speed and the slow speed is fused into a low-frequency model to obtain formation anisotropy information, thereby predicting
- the requested crack information solves the technical problem that the existing method cannot provide a reasonable low-frequency model in the crack prediction process of anisotropic inversion.
- An embodiment of the present invention provides a high-angle crack prediction method.
- the method includes:
- the first azimuthal inversion of the wide-azimuth seismic data in the target area is performed to obtain the first anisotropic intensity
- the low frequency model of the azimuthal longitudinal wave anisotropy is established;
- the second anisotropic strength and the second anisotropic direction are analyzed to obtain crack prediction results.
- An embodiment of the present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor.
- the processor implements the computer program when the processor executes the computer program:
- the first azimuthal inversion of the wide-azimuth seismic data in the target area is performed to obtain the first anisotropic intensity
- the low frequency model of the azimuthal longitudinal wave anisotropy is established;
- the second anisotropic strength and the second anisotropic direction are analyzed to obtain crack prediction results.
- An embodiment of the present invention also provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program is used to execute:
- the first azimuthal inversion of the wide-azimuth seismic data in the target area is performed to obtain the first anisotropic intensity
- the low frequency model of the azimuthal longitudinal wave anisotropy is established;
- the second anisotropic strength and the second anisotropic direction are analyzed to obtain crack prediction results.
- the first azimuth anisotropy inversion is performed on the wide-azimuth seismic data of the target area to obtain the first anisotropic intensity, and then the wide area of the target area
- the azimuth seismic data is analyzed for the anisotropy of P-wave velocity and velocity, to obtain the anisotropy of P-wave velocity and velocity difference and the direction of P-wave velocity, and to fit the anisotropy of the first anisotropy intensity and the P-wave velocity velocity difference to obtain the
- the anisotropy intensity of the difference between the speed and the slow speed is based on the anisotropy intensity based on the difference between the speed of the longitudinal wave and the direction of the speed of the longitudinal wave.
- the low frequency model of the azimuthal longitudinal wave anisotropy is established to achieve the fusion of the anisotropic analysis results of the longitudinal wave velocity to the azimuthal anisotropy In the process of establishing the anisotropic low frequency, this solves the technical problem that the existing method does not provide a reasonable low frequency model in the crack prediction process of anisotropic inversion.
- the second azimuthal inversion of the wide-azimuth seismic data in the target area is performed to obtain the second anisotropic intensity and the second anisotropic direction, and the second anisotropic intensity Analyze with the second anisotropy direction to obtain fracture prediction results and achieve quantitative prediction of cracks, which can not only have the overall rationality of crack distribution, but also ensure the accuracy of crack prediction.
- FIG. 1 is a flowchart of a high-angle crack prediction method provided by an embodiment of the present invention
- FIG. 2 is a processing flowchart of a specific high-angle crack prediction method provided by an embodiment of the present invention
- FIG. 3 is a schematic diagram of an optimized logging interpretation result provided by an embodiment of the present invention.
- FIG. 4 is a schematic diagram of a seismic rock physics interpretation template for a fractured reservoir provided by an embodiment of the present invention
- FIG. 5 is a schematic diagram of a cross section of an isotropic low-frequency model provided by an embodiment of the present invention.
- FIG. 6 is a schematic diagram of a fast longitudinal wave velocity profile (represented by a) and a slow longitudinal wave velocity profile (represented by b) provided by an embodiment of the present invention
- FIG. 7 is a schematic diagram of crack azimuth statistical analysis obtained by a fast and slow longitudinal wave velocity analysis provided by an embodiment of the present invention, and considers that this direction is perpendicular to the anisotropic direction;
- FIG. 8 is a schematic diagram of a fitting relationship between the anisotropy of the longitudinal wave speed difference and the first anisotropic strength provided by an embodiment of the present invention
- FIG. 9 is a schematic diagram of an anisotropic intensity comparison profile provided by an embodiment of the present invention
- a is the above figure: anisotropic (J) profile obtained by fast and slow longitudinal wave velocity analysis
- b is J and the first anisotropic intensity (b 1 ) Fitting, the anisotropic intensity (b 1v ) profile obtained after correction based on the difference of the longitudinal wave speed and slow speed;
- FIG. 10 is a schematic diagram of an azimuthal anisotropic low-frequency model provided by an embodiment of the present invention.
- FIG. 11 is an anisotropic intensity profile provided by an embodiment of the present invention (upper graph: first anisotropic intensity obtained by the first anisotropic inversion (b 1 ); middle graph: fast and slow longitudinal wave velocity Analyze the anisotropic intensity obtained after correction (b 1v ); the following figure: the second anisotropic intensity obtained by the second anisotropic inversion (b 12 ));
- FIG. 12 is a plan view of a comprehensive analysis of cracks provided by an embodiment of the present invention (figure a: crack density and direction obtained by the first anisotropic inversion; figure b: crack density and direction obtained after fast and slow longitudinal wave velocity analysis and correction; Figure c: Crack density and direction obtained by the second anisotropic inversion);
- FIG. 13 is a schematic diagram of a statistical analysis of fracture azimuth angle provided by an embodiment of the present invention (a: histogram of statistical analysis of fracture azimuth angle obtained by the first anisotropic inversion; b: statistics of fracture azimuth angle obtained by fast and slow longitudinal wave velocity analysis Analyze the histogram; c: the statistical analysis histogram of fracture azimuth obtained by the second anisotropic inversion);
- FIG. 14 is a schematic block diagram of a system configuration of a computer device provided by an embodiment of the present invention.
- a high-angle crack prediction method is provided. As shown in FIG. 1, the method includes:
- Step 101 Based on the constructed isotropic low-frequency model, perform the first azimuthal inversion of wide-azimuth seismic data in the target area to obtain the first anisotropic intensity;
- Step 102 Perform anisotropy analysis of the longitudinal wave speed and slow speed on the wide-azimuth seismic data of the target area to obtain the anisotropy of the longitudinal wave speed and slow speed difference and the direction of the fast longitudinal wave speed;
- Step 103 Fit the first anisotropy intensity to the anisotropy of the difference between the longitudinal wave speed and the slow speed to obtain the anisotropic intensity based on the longitudinal wave speed difference;
- Step 104 Establish an azimuth longitudinal wave anisotropic low-frequency model based on the anisotropic intensity based on the difference between the longitudinal wave speed and the slow wave speed and the direction of the fast longitudinal wave speed;
- Step 105 Based on the azimuth longitudinal wave anisotropic low-frequency model, perform a second azimuthal inversion of the wide-azimuth seismic data of the target area to obtain a second anisotropic intensity and a second anisotropic direction;
- Step 106 Analyze the second anisotropic strength and the second anisotropic direction to obtain a crack prediction result.
- step 101 is specifically implemented as follows:
- Obtain logging data in the target area including: longitudinal, transverse wave curve, density curve, longitudinal and longitudinal wave impedance, longitudinal and longitudinal wave velocity ratio and rock mineral composition curve, porosity curve, water saturation curve, drilling stratification And other data, as shown in Figure 3.
- the logging evaluation and analysis of fractured reservoirs are completed.
- the fractures in the reservoir will lead to anisotropy of the formation. Therefore, it is necessary to establish fracture-based rock physical modeling to determine the directions caused by the fracture.
- Sensitive elastic parameters of heterogeneous reservoirs This process selects the longitudinal and lateral wave velocity ratios as the sensitive elastic parameters of fractures in this type of reservoir.
- the wide-azimuth seismic data in the target area is obtained.
- the quality of the wide-azimuth seismic data is directly related to the subsequent inversion effect. Therefore, the quality of the wide-azimuth seismic data needs to be evaluated, and the focus is on the orientation of the wide-azimuth seismic data.
- the most favorable azimuth and offset division principles are formulated. Specifically, the wide-azimuth seismic data of the target area is divided and superimposed in a manner of first dividing the azimuth angle and then dividing the offset, to form multi-azimuth sub-superimposed data;
- multi-azimuth prestack anisotropic inversion is performed on the multi-azimuth sub-stack data, and a pre-stack inversion is performed for each azimuth to obtain the sensitivity of the azimuth crack Elastic parameter data (longitudinal wave velocity ratio data);
- the first anisotropic strength is determined according to the following formula:
- V p represents the longitudinal wave velocity
- V s represents the shear wave velocity
- b 1 represents the first anisotropic intensity
- ⁇ represents the azimuth angle of the seismic data, that is, the azimuth angle of the survey network
- ⁇ represents the first anisotropic direction
- b 0 Represents the isotropic background
- b 2 represents the anisotropy of the influence of higher-order noise in the first azimuthal inversion
- It represents the ratio of the P- and S-wave velocities obtained after the first azimuthal inversion of the isotropic low-frequency model.
- step 102 is specifically implemented as follows:
- J represents the anisotropy of the difference between the longitudinal and fast speeds
- Vp NMO fast represents the fast longitudinal wave speed
- Vp NMO slow represents the slow longitudinal wave speed
- step 103 is specifically implemented as follows:
- the anisotropy (J) is converted into an anisotropy intensity (b 1v ) based on the difference between the velocity of the longitudinal wave and the velocity with the same range characteristic as the first anisotropy intensity (b 1 ), as shown in FIG. 8.
- Figure 9 a shows the anisotropy caused by the difference between the fast and slow longitudinal wave velocities (J)
- Figure b shows the correction of the anisotropy caused by the difference between the fast and slow longitudinal wave velocities to the first anisotropic intensity (b 1 )
- a schematic diagram of the cross- sectional comparative analysis of the anisotropic intensity (b 1v ) based on the difference between the speed of the longitudinal wave and the velocity formed after the correction.
- the fitting formula is as follows:
- step 104 is specifically implemented as follows:
- the anisotropy intensity (b 1v ) based on the difference between the speed of P-wave and the speed of P-wave and the direction of P-wave velocity are fused into the constructed azimuthal isotropic low-frequency model.
- an azimuth longitudinal wave anisotropic low-frequency model is established, as shown in Figure 10;
- V p represents the longitudinal wave velocity
- V s represents the shear wave velocity
- b 1v represents the anisotropic intensity based on the difference between the velocity of the longitudinal wave and the velocity
- ⁇ represents the azimuth of the seismic data
- ⁇ v represents the direction perpendicular to the velocity of the longitudinal wave
- An azimuthal longitudinal wave anisotropic low-frequency model Represents each isotropic low-frequency model.
- step 105 is specifically implemented as follows:
- the second azimuthal inversion of the wide-azimuth seismic data in the target area is performed according to the following formula to obtain the second anisotropic intensity and the second anisotropic direction:
- V p represents the longitudinal wave velocity
- V s represents the shear wave velocity
- b 0 represents the isotropic background
- b 12 represents the second anisotropic intensity
- ⁇ represents the azimuth of the seismic data
- ⁇ 2 represents the second anisotropic direction
- b 22 represents the anisotropy of the influence of high-order noise in the second azimuthal anisotropic inversion
- It represents the ratio of the vertical and horizontal wave velocities obtained after the second azimuthal anisotropic inversion.
- step 106 is specifically implemented as follows:
- the anisotropic strength reflects the density of the fracture to a certain extent, and the anisotropic direction and the direction of the fracture are azimuth It is approximately vertical, so the crack density and crack direction are obtained.
- FIG. 11 is an anisotropic intensity profile provided by an embodiment of the present invention (upper graph: first anisotropic intensity obtained by the first anisotropic inversion (b 1 ); middle graph: fast and slow longitudinal wave velocity Analyze the anisotropic intensity obtained after correction (b 1v ); the following figure: the second anisotropic intensity obtained by the second anisotropic inversion (b 12 ));
- FIG 12 is a plan view of a comprehensive analysis of cracks provided by an embodiment of the present invention (figure a: crack density and direction obtained by the first anisotropic inversion; figure b: crack density and direction obtained after fast and slow longitudinal wave velocity analysis and correction; Figure c: Crack density and direction obtained from the second anisotropic inversion); from Figure 12, it can be seen that the crack directions obtained after the first anisotropic inversion are relatively scattered, and the regularity of the predicted crack is not strong; based on the longitudinal wave After the anisotropy correction caused by the speed, the crack direction obtained only reflects the general regularity, but the resolution is low; the fracture orientation regularity obtained after the second anisotropic inversion is relatively strong, and the resolution of the crack is predicted Has improved.
- FIG. 13 is a schematic diagram of a statistical analysis of fracture azimuth angle provided by an embodiment of the present invention (a: histogram of statistical analysis of fracture azimuth angle obtained by the first anisotropic inversion; b: statistics of fracture azimuth angle obtained by fast and slow longitudinal wave velocity analysis Analyze the histogram; c: the statistical analysis of the fracture azimuth obtained by the second anisotropic inversion histogram); as can be seen from Figure 13, the fracture directions obtained after the first anisotropic inversion are relatively scattered, based on the speed of the longitudinal wave After the correction of the induced anisotropy, the obtained fracture direction only reflects the general regularity; the fracture orientation regularity obtained after the second anisotropic inversion is relatively strong.
- the present invention also provides a computer device, which may be a desktop computer, a tablet computer, a mobile terminal, etc. This embodiment is not limited thereto. In this embodiment, the computer device can complete the implementation of the high-angle crack prediction method.
- FIG. 14 is a schematic block diagram of a system configuration of a computer device 500 according to an embodiment of the present invention.
- the computer device 500 may include a processor 100 and a memory 140; the memory 140 is coupled to the processor 100. It is worth noting that the figure is exemplary; other types of structures can also be used to supplement or replace the structure to achieve telecommunications functions or other functions.
- a computer program that implements a high-angle crack prediction function may be integrated into the processor 100.
- the processor 100 may be configured to perform the following control:
- the first azimuthal inversion of the wide-azimuth seismic data in the target area is performed to obtain the first anisotropic intensity
- the low frequency model of the azimuthal longitudinal wave anisotropy is established;
- the second anisotropic strength and the second anisotropic direction are analyzed to obtain crack prediction results.
- the processor realizes when the computer program is executed:
- the first anisotropic intensity is determined according to the ratio of the vertical and horizontal wave velocities at the sub-azimuth.
- the processor realizes when the computer program is executed:
- the anisotropy of the difference between the fast and slow velocity of the longitudinal wave is determined according to the fast and slow longitudinal velocity.
- b 1v represents the anisotropy intensity based on the difference of the longitudinal wave speed and slow speed
- J represents the anisotropy of the longitudinal wave speed and slow speed difference.
- the processor realizes when the computer program is executed:
- the azimuth longitudinal wave anisotropic low-frequency model is established according to the following formula
- V p represents the longitudinal wave velocity
- V s represents the shear wave velocity
- b 1v represents the anisotropic intensity based on the difference between the velocity of the longitudinal wave and the velocity
- ⁇ represents the azimuth of the seismic data
- ⁇ v represents the direction perpendicular to the velocity of the longitudinal wave
- An azimuthal longitudinal wave anisotropic low-frequency model Represents each isotropic low-frequency model.
- the function of high-angle crack prediction can be configured separately from the processor 100, for example, the function of high-angle crack prediction can be configured on a chip connected to the processor 100, and the high angle can be achieved through the control of the processor The function of crack prediction.
- the computer device 500 may further include: an input unit 120, a display 160, and a power supply 170. It is worth noting that the computer device 500 does not necessarily include all the components shown in FIG. 14; in addition, the computer device 500 may also include components not shown in FIG. 14, and reference may be made to the prior art.
- the processor 100 is sometimes referred to as a controller or operation control, and may include a microprocessor or other processor devices and/or logic devices.
- the processor 100 receives input and controls operations of various components of the computer device 500.
- the input unit 120 provides input to the processor 100.
- the input unit 120 is, for example, a key or a touch input device.
- the memory 140 may be, for example, one or more of a buffer, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices.
- a program for executing relevant information may be stored, and the processor 100 may execute the program stored in the memory 140 to implement information storage or processing, and the like.
- the memory 140 may be a solid-state memory, for example, a read only memory (ROM), a random access memory (RAM), a SIM card, or the like. It may also be a memory that retains information even when the power is turned off, can be selectively erased, and is provided with more data, and an example of this memory is sometimes called EPROM or the like.
- the memory 140 may also be some other type of device.
- the memory 140 includes a buffer memory 141 (sometimes referred to as a buffer).
- the memory 140 may include an application/function storage part 142 for storing application programs and function programs or a flow for performing operations of the electronic device through the processor 100.
- the memory 140 may further include a data storage part 143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by the electronic device.
- the driver storage portion 144 of the memory 140 may include various drivers for the electronic device for communication functions and/or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).
- the display 160 is used to display display objects such as images and characters.
- the display may be, for example, an LCD display, but it is not limited thereto.
- the power supply 170 is used to provide power to the computer device 500.
- An embodiment of the present invention further provides a computer-readable storage medium that stores a computer program, and the computer program is used to execute any of the computer programs of the high-angle crack prediction method described above.
- the computer-readable storage medium may include a physical device for storing information, and the information may be digitized and then stored in a medium using electrical, magnetic, or optical methods.
- the computer-readable storage medium described in this embodiment may include: devices that use electrical energy to store information, such as various types of memory, such as RAM, ROM, etc.; devices that use magnetic energy to store information, such as hard disks, floppy disks, magnetic tapes, and magnetic cores Memory, bubble memory, U disk; devices that use optical means to store information such as CD or DVD.
- devices that use electrical energy to store information such as various types of memory, such as RAM, ROM, etc.
- devices that use magnetic energy to store information such as hard disks, floppy disks, magnetic tapes, and magnetic cores Memory, bubble memory, U disk
- devices that use optical means to store information such as CD or DVD.
- quantum memory graphene memory, and so on.
- the high-angle crack prediction method, computer equipment and computer-readable storage medium proposed by the present invention have the following beneficial effects:
- the first azimuth anisotropy inversion is performed on the wide-azimuth seismic data in the target area to obtain the first anisotropic intensity, and then the longitudinal wave velocity of the wide-azimuth seismic data in the target area Anisotropy analysis, to obtain the anisotropy of the longitudinal wave speed and slow speed difference and fast longitudinal wave speed direction, fitting the first anisotropic intensity to the anisotropy of the longitudinal wave speed and slow speed difference, to obtain the anisotropy based on the longitudinal wave speed and slow speed difference
- the azimuth longitudinal wave anisotropic low-frequency model is established based on the anisotropy intensity based on the difference between the longitudinal wave speed and the slow wave velocity direction, which achieves the fusion of the anisotropic analysis results of the longitudinal wave velocity difference to the azimuth anisotropic low frequency establishment process It solves the technical problem that the existing low-frequency model cannot be provided in the process of anisotropic inversion crack prediction.
- the second azimuth anisotropic inversion of the wide-azimuth seismic data in the target area is performed to obtain the second anisotropic intensity and the second anisotropic direction
- the second anisotropic intensity Analyze with the second anisotropy direction to obtain fracture prediction results and achieve quantitative prediction of cracks, which can not only have the overall rationality of crack distribution, but also ensure the accuracy of crack prediction.
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Abstract
Description
Claims (15)
- 一种高角度裂缝预测方法,其特征在于,包括:基于已构建的各向同性低频模型,对目标区域的宽方位地震数据进行第一次方位各向异性反演,获得第一各向异性强度;对所述目标区域的宽方位地震数据进行纵波快慢速度各向异性分析,获得纵波快慢速度差异的各向异性和快纵波速度方向;将所述第一各向异性强度与所述纵波快慢速度差异的各向异性进行拟合,获得基于纵波快慢速度差异的各向异性强度;根据基于纵波快慢速度差异的各向异性强度和快纵波速度方向,建立方位纵波各向异性低频模型;基于所述方位纵波各向异性低频模型,对所述目标区域的宽方位地震数据进行第二次方位各向异性反演,获得第二各向异性强度和第二各向异性方向;对所述第二各向异性强度和所述第二各向异性方向进行分析,获得裂缝预测结果。
- 如权利要求1所述的高角度裂缝预测方法,其特征在于,基于已构建的各向同性低频模型,对目标区域的宽方位地震数据进行第一次方位各向异性反演,获得第一各向异性强度,包括:对所述目标区域的宽方位地震数据按照先分方位角再分偏移距的方式进行分叠加,形成多方位分叠加数据;基于已构建的各向同性低频模型,对所述多方位分叠加数据进行方位各向异性反演,获得分方位的纵横波速度比;根据分方位的纵横波速度比,确定第一各向异性强度。
- 如权利要求1所述的高角度裂缝预测方法,其特征在于对所述目标区域的宽方位地震数据进行纵波快慢速度各向异性分析,获得纵波快慢速度差异的各向异性和快纵波速度方向,包括:对所述目标区域的宽方位地震数据进行处理,获得快纵波速度、慢纵波速度和快纵波速度方向;根据所述快纵波速度和慢纵波速度确定纵波快慢速度差异的各向异性。
- 如权利要求3所述的高角度裂缝预测方法,其特征在于,按照如下公式将所述第一各向异性强度与所述纵波快慢速度差异的各向异性进行拟合,获得基于纵波快慢速度差异的各向异性强度:b 1v=-0.23×J-0.005;其中,b 1v表示基于纵波快慢速度差异的各向异性强度;J表示纵波快慢速度差异的各向异性。
- 一种计算机设备,包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序,其特征在于,所述处理器执行所述计算机程序时实现:基于已构建的各向同性低频模型,对目标区域的宽方位地震数据进行第一次方位各向异性反演,获得第一各向异性强度;对所述目标区域的宽方位地震数据进行纵波快慢速度各向异性分析,获得纵波快慢速度差异的各向异性和快纵波速度方向;将所述第一各向异性强度与所述纵波快慢速度差异的各向异性进行拟合,获得基于纵波快慢速度差异的各向异性强度;根据基于纵波快慢速度差异的各向异性强度和快纵波速度方向,建立方位纵波各向异性低频模型;基于所述方位纵波各向异性低频模型,对所述目标区域的宽方位地震数据进行第二次方位各向异性反演,获得第二各向异性强度和第二各向异性方向;对所述第二各向异性强度和所述第二各向异性方向进行分析,获得裂缝预测结果。
- 如权利要求6所述的计算机设备,其特征在于,所述处理器执行所述计算机程序时实现:对所述目标区域的宽方位地震数据按照先分方位角再分偏移距的方式进行分叠加, 形成多方位分叠加数据;基于已构建的各向同性低频模型,对所述多方位分叠加数据进行方位各向异性反演,获得分方位的纵横波速度比;根据分方位的纵横波速度比,确定第一各向异性强度。
- 如权利要求6所述的计算机设备,其特征在于,所述处理器执行所述计算机程序时实现:对所述目标区域的宽方位地震数据进行处理,获得快纵波速度、慢纵波速度和快纵波速度方向;根据所述快纵波速度和慢纵波速度确定纵波快慢速度差异的各向异性。
- 如权利要求8所述的计算机设备,其特征在于,所述处理器执行所述计算机程序时实现:按照如下公式将所述第一各向异性强度与所述纵波快慢速度差异的各向异性进行拟合,获得基于纵波快慢速度差异的各向异性强度:b 1v=-0.23×J-0.005;其中,b 1v表示基于纵波快慢速度差异的各向异性强度;J表示纵波快慢速度差异的各向异性。
- 一种计算机可读存储介质,其特征在于,所述计算机可读存储介质存储有计算机程序,所述计算机程序用于执行:基于已构建的各向同性低频模型,对目标区域的宽方位地震数据进行第一次方位各 向异性反演,获得第一各向异性强度;根据第一各向异性方向,对所述目标区域的宽方位地震数据进行纵波快慢速度各向异性分析,获得纵波快慢速度差异的各向异性和快纵波速度方向;将所述第一各向异性强度与所述纵波快慢速度差异的各向异性进行拟合,获得基于纵波快慢速度差异的各向异性强度;根据基于纵波快慢速度差异的各向异性强度和快纵波速度方向,建立方位纵波各向异性低频模型;基于所述方位纵波各向异性低频模型,对所述目标区域的宽方位地震数据进行第二次方位各向异性反演,获得第二各向异性强度和第二各向异性方向;对所述第二各向异性强度和所述第二各向异性方向进行分析,获得裂缝预测结果。
- 如权利要求11所述的计算机可读存储介质,其特征在于,所述计算机程序用于执行:对所述目标区域的宽方位地震数据按照先分方位角再分偏移距的方式进行分叠加,形成多方位分叠加数据;基于已构建的各向同性低频模型,对所述多方位分叠加数据进行方位各向异性反演,获得分方位的纵横波速度比;根据分方位的纵横波速度比,确定第一各向异性强度。
- 如权利要求11所述的计算机可读存储介质,其特征在于,所述计算机程序用于执行:对所述目标区域的宽方位地震数据进行处理,获得快纵波速度、慢纵波速度和快纵波速度方向;根据所述快纵波速度和慢纵波速度确定纵波快慢速度差异的各向异性。
- 如权利要求13所述的计算机可读存储介质,其特征在于,所述计算机程序用于执行:按照如下公式将所述第一各向异性强度与所述纵波快慢速度差异的各向异性进行拟合,获得基于纵波快慢速度差异的各向异性强度:b 1v=-0.23×J-0.005;其中,b 1v表示基于纵波快慢速度差异的各向异性强度;J表示纵波快慢速度差异的各向异性。
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CN113391350B (zh) * | 2021-04-30 | 2023-10-13 | 成都北方石油勘探开发技术有限公司 | 一种半定量叠后地震裂缝预测方法 |
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