Seismic phase calculation method, device, electronic equipment and medium taking into account crack characterization

Abstract

This application discloses a method, device, electronic device, and medium for calculating seismic facies that takes into account fracture characterization. The method may include: calculating multiple seismic fracture attribute data volumes for an original seismic data volume; using the seismic fracture attribute data volume with the best fracture characterization as baseline data; and fusing the baseline data with the original seismic data volume to calculate a fused seismic facies. The present invention fully considers the impact of fractures on sedimentation and incorporates optimized seismic fracture data volumes into seismic facies calculations, resulting in seismic facies results that are more consistent with geological laws and take fracture facies into account.

Description

Technical Field

[0001] The present invention relates to the field of oil and gas geophysics technology, and more specifically, to a seismic phase calculation method, device, electronic equipment and medium that take fracture characterization into consideration. Background Art

[0002] Seismic facies is the sum of the manifestations of sedimentary facies on the seismic profile. It is a seismic feature formed by the sedimentary environment (such as marine or terrestrial). It refers to a seismic reflection unit within a certain area. The seismic attribute parameters within this unit are different from those of the adjacent units. It represents the lithologic combination, bedding and sedimentary characteristics of the sediments that produce its reflection. In the exploration and development of underground sedimentary minerals such as oil and coal, sedimentary facies research is of great significance. The amplitude, consistency and other attributes of three-dimensional seismic data will change with the changes in lithology and fluid. Reservoir modeling and underground geological analysis will be carried out based on these attributes, so these attributes play an important role in seismic analysis. In general, attributes are used to generate seismic facies, and seismic facies can reflect the difference in amplitude between different seismic waves. Therefore, seismic facies can reflect the structure of the underground. Seismic facies analysis is used to extract and analyze useful information of seismic reflection parameters (consistency, continuity, etc.). At present, the main features of waveform classification technology are: (1) Multidisciplinary cross-disciplinary features, including geography, computing, biomimetics and other disciplines. Make full use of seismic data information to divide and identify seismic phases, reduce the impact of human intervention, and provide a more reliable analysis basis for oil and gas reservoir prediction and geological structure analysis of rock formations; (2) Human participation is becoming less and less, mainly using computer processing to improve the efficiency of seismic phase division, reduce the impact of human factors on the results, and reduce the labor cost in seismic phase division and identification.

[0003] The main methods used in seismic phase technology include discriminant factor analysis, artificial neural networks, texture model regression, and statistical models. In 1962, Widrow et al. proposed a continuously variable weight adaptive theory; Minskey and Papert subsequently published the book "Perceptrons" in 1969; Finnish scientist Kohonen proposed the self-organizing map neural network theory in 1972; Fukushima proposed the cognitive machine principle of neural networks in 1975; and Grossberg proposed the adaptive resonance mechanism of artificial neural networks in 1976. Hopfield proposed the HNN model in 1982, incorporating energy function theory and developing methods for determining the stability of artificial neural networks and implementing them in electronic circuits. This model significantly advanced the theory of artificial neural networks. Hinton proposed the Boltzmann machine model in 1984, drawing on simulated annealing techniques from statistical physics to ensure global convergence of the artificial neural network learning process. In the period that followed, waveform classification methods based on artificial neural networks developed rapidly and were applied in many fields. In domestic seismic research, Duan Yushun et al. proposed an automatic seismic phase identification method and its application in 2004, which can automatically identify seismic phases. Chen Fanghong et al. proposed visualization-based three-dimensional seismic phase analysis in 2005 and applied it to sedimentary phase identification. Deng Chuanwei et al. proposed the application of waveform classification technology to reservoir microfacies prediction in 2008, using a waveform classification algorithm to identify microseismic phases. In 2009, Iván Dimitri Marroquín et al. proposed waveform classification based on visualization data mining and compared the results with traditional supervised waveform classification methods, demonstrating that visualization data mining methods can also effectively classify seismic signal waveforms. In 2010, Zhang Linke et al. proposed a seismic image analysis approach based on seismic attributes. Liu Qingmin et al. proposed a seismic phase analysis technique based on empirical mode decomposition in 2010, introducing empirical mode decomposition into seismic phase analysis. Atish Roy Norman et al. analyzed the distribution of seismic phases in latent space in 2013.

[0004] In the past decade, however, the primary focus of seismic facies research has been on applied fields. To characterize the seismic sedimentary characteristics of different regions and strata within various oilfield blocks, various methods have been developed specifically for the application of seismic facies, tailored to the specific stratigraphic characteristics of their respective regions. Zhang Shuai (2013) applied seismic facies to phreatic lake sandbodies, Tang Huafeng (2007) to volcanic rocks in the Songliao Basin, She Gang (2012) to thin sandstone reservoirs in northern Hubei, Wang Jincheng (2011) to the Kong 3 sedimentary system in the Huanghua Depression, and Sun Jing (2013) to the Cretaceous Qingshuihe Formation on the northwestern margin of the Junggar Basin. These methods have all been applied to the Qingshuihe Formation in the Cretaceous on the northwestern margin of the Junggar Basin.

[0005] However, in many applied studies of seismic phases, there are few research methods that take crack factors into consideration.

[0006] Fracture research is a crucial element in determining reservoir targets, both during the exploration and development phases. As effective reservoir spaces and primary flow pathways for oil and gas within a reservoir, fractures control their occurrence and production capacity. Favorable fracture zones often indicate the presence of high-yield zones. In tight sandstone and volcanic reservoirs, there's even a saying that "no fractures, no reservoirs." This demonstrates the crucial role fracture systems play in the accumulation and formation of oil and gas. Furthermore, among the many research hotspots regarding fractures, effectively evaluating their impact on production capacity directly impacts both final oil and gas production and the substantial, often millions or even tens of millions, of actual single-well drilling costs.

[0007] As early as the 1970s, foreign countries began using seismic methods to detect fractured oil and gas reservoirs. This technology has evolved through several stages, including shear wave exploration, multi-wave and multi-component exploration, and compressional wave fracture detection. Remarkable progress has been made in compressional wave seismic fracture detection. The development of fracture prediction often builds on the research of equivalent rock physics models. Currently, rock physics models for anisotropic, two-phase, and two-phase anisotropic media have been developed abroad. In recent years, with the discovery and development of numerous fractured oil and gas reservoirs both domestically and internationally, researchers have conducted extensive research on the core issue of reservoir fracture characterization, achieving significant progress. These include geological methods for field outcrop characterization, laboratory core analysis, well logging, and seismic exploration. While drilling, logging, and core data provide relatively detailed and accurate fracture descriptions, their scope is limited to the well point, resulting in a limited understanding. Seismic exploration, with its relatively wide coverage and relatively low cost, plays a crucial role in fracture system identification, fracture reservoir prediction, and detailed characterization. Currently, commonly used fractured reservoir prediction and identification technologies include seismic attribute technology and coherence technology based on seismic anisotropy. Seismic attribute technologies such as amplitude attributes, coherence volume technology, and curvature volume technology, with their relative simplicity and practicality, have played a vital role in well placement in the early stages of fractured reservoir exploration.

[0008] Therefore, both seismic facies and fractures are crucial for oil and gas exploration. When characterizing seismic facies, it's crucial to consider fractures for greater accuracy, especially when describing fractured reservoirs. Huang Handong (2015) combined seismic and well logging to characterize volcanic fractures, but this combination failed to fully integrate seismic facies layers with fractures.

[0009] Therefore, it is necessary to develop a seismic phase calculation method, device, electronic equipment and medium that take into account fracture characterization.

[0010] The information disclosed in the background technology section of the present invention is only intended to deepen the understanding of the general background technology of the present invention, and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to those skilled in the art. Summary of the Invention

[0011] The present invention proposes a seismic phase calculation method, device, electronic equipment and medium that take into account crack characterization. On the basis of conventional seismic phase characterization technology, it takes crack factors into account and more accurately characterizes seismic phases, providing a data basis for the representative significance, evolution law and boundary demarcation of seismic phase belts.

[0012] In a first aspect, an embodiment of the present disclosure provides a seismic phase calculation method that takes fracture characterization into consideration, including:

[0013] Calculate multiple seismic fracture attribute data volumes for the original seismic data volume;

[0014] The earthquake crack attribute data volume with the best crack characterization effect is used as the basic data;

[0015] The basic data is fused with the original seismic data volume to calculate the fused seismic phase.

[0016] Preferably, the earthquake crack attribute data body with the best crack characterization effect as the basic data includes:

[0017] respectively calculating the seismic phases corresponding to the seismic crack attribute data volumes;

[0018] The earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect is used as the basic data.

[0019] Preferably, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0020] When the geological target is a large-scale fracture, the seismic fracture attribute data volume calculated by the coherence method or the AFE method is used as the basic data.

[0021] Preferably, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0022] When the geological target is a small-scale fracture, the seismic fracture attribute data volume calculated by the pre-stack AVAZ method or the VVAZ method is used as the basic data.

[0023] Preferably, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0024] When the geological target is to take into account fractures of different scale levels, the seismic fracture attribute data volume calculated by the likelihood method or the curvature method is used as the basic data.

[0025] Preferably, fusing the basic data with the original seismic data volume to calculate the fused seismic phase comprises:

[0026] performing normalization processing on the basic data and the original seismic data volume;

[0027] Calculate the fused data volume;

[0028] The fused seismic phase is calculated from the fused data volume.

[0029] Preferably, the fused data volume is calculated by formula (1):

[0030] N=D2+C*M' (1)

[0031] Among them, N is the fusion data volume, D2 is the normalized basic data, M' is the normalized original seismic data volume, and C is the fusion parameter.

[0032] As a specific implementation of the embodiment of the present disclosure,

[0033] In a second aspect, the embodiments of the present disclosure further provide a seismic phase calculation device that takes fracture characterization into consideration, including:

[0034] A calculation module calculates multiple earthquake fracture attribute data volumes based on the original earthquake data volume;

[0035] The basic data determination module uses the earthquake crack attribute data volume with the best crack characterization effect as the basic data;

[0036] A fusion module is used to fuse the basic data with the original seismic data volume and calculate the fused seismic phase.

[0037] Preferably, the earthquake crack attribute data body with the best crack characterization effect as the basic data includes:

[0038] respectively calculating the seismic phases corresponding to the seismic crack attribute data volumes;

[0039] The earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect is used as the basic data.

[0040] Preferably, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0041] When the geological target is a large-scale fracture, the seismic fracture attribute data volume calculated by the coherence method or the AFE method is used as the basic data.

[0042] Preferably, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0043] When the geological target is a small-scale fracture, the seismic fracture attribute data volume calculated by the pre-stack AVAZ method or the VVAZ method is used as the basic data.

[0044] Preferably, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0045] When the geological target is to take into account fractures of different scale levels, the seismic fracture attribute data volume calculated by the likelihood method or the curvature method is used as the basic data.

[0046] Preferably, fusing the basic data with the original seismic data volume to calculate the fused seismic phase comprises:

[0047] performing normalization processing on the basic data and the original seismic data volume;

[0048] Calculate the fused data volume;

[0049] The fused seismic phase is calculated from the fused data volume.

[0050] Preferably, the fused data volume is calculated by formula (1):

[0051] N=D2+C*M' (1)

[0052] Among them, N is the fusion data volume, D2 is the normalized basic data, M' is the normalized original seismic data volume, and C is the fusion parameter.

[0053] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0054] a memory storing executable instructions;

[0055] A processor runs the executable instructions in the memory to implement the seismic phase calculation method taking fracture characterization into consideration.

[0056] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the seismic phase calculation method taking fracture characterization into consideration.

[0057] Its beneficial effects are:

[0058] In order to improve the seismic facies characterization of fractured reservoirs and fully consider the impact of fracture factors on sedimentation, the seismic fracture data volume that has undergone optimized analysis is introduced when doing seismic facies, and the seismic facies results that are more in line with geological laws and take fracture facies into consideration are calculated.

[0059] The methods and apparatus of the present invention have other features and advantages that will be apparent from or will be described in detail in the accompanying drawings and subsequent detailed descriptions incorporated herein, which together serve to explain the specific principles of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.

[0061] Figure 1 A flow chart showing steps of a method for calculating seismic phases taking fracture characterization into consideration according to an embodiment of the present invention.

[0062] Figure 2 A schematic diagram of a seismic data plane map slice of a target layer according to an embodiment of the present invention is shown.

[0063] Figure 3 A schematic diagram showing conventional seismic phase characterization results according to an embodiment of the present invention is shown.

[0064] Figure 4a 、 Figure 4b and Figure 4c Schematic diagrams respectively show curvature crack attributes, coherence crack attributes, and likelyhood crack attributes according to an embodiment of the present invention.

[0065] Figure 5a 、 Figure 5b 、 Figure 5c and Figure 5d Schematic diagrams respectively show the seismic phase corresponding to the coherence attribute, the seismic phase corresponding to the curvature attribute, the seismic phase corresponding to the likelyhood attribute, and the seismic phase corresponding to the fusion of the coherence and curvature attributes according to an embodiment of the present invention.

[0066] Figure 6 A schematic diagram showing seismic phase results taking fracture characterization into consideration according to an embodiment of the present invention is shown.

[0067] Figure 7 A block diagram of a seismic phase calculation device taking fracture characterization into consideration according to an embodiment of the present invention is shown.

[0068] Description of reference numerals:

[0069] 201. Calculation module; 202. Basic data determination module; 203. Fusion module. DETAILED DESCRIPTION

[0070] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0071] The present invention provides a seismic phase calculation method taking fracture characterization into consideration, comprising:

[0072] For the original seismic data volume, multiple seismic fracture attribute data volumes are calculated.

[0073] Specifically, for the original seismic data volume M, the seismic crack attribute data volume B is calculated using different calculation principles. i (i=1, 2, 3...), for example, the earthquake crack attribute data body characterized by the curvature method is B1, the earthquake crack attribute data body characterized by the coherence method is B2, the earthquake crack attribute data body characterized by the likelihood method is B3, the earthquake crack attribute data body characterized by the AFE method is B4, etc.

[0074] The earthquake crack attribute data volume with the best crack characterization effect is used as the basic data. In one example, the earthquake crack attribute data volume with the best crack characterization effect as the basic data includes:

[0075] Calculate the seismic phases corresponding to the earthquake crack attribute data volume respectively;

[0076] The earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect is used as the basic data.

[0077] In one example, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0078] When the geological target is a large-scale fracture, the seismic fracture attribute data volume calculated by the coherence method or the AFE method is used as the basic data.

[0079] In one example, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0080] When the geological target is a small-scale fracture, the seismic fracture attribute data volume calculated by the prestack AVAZ method or VVAZ method is used as the basic data.

[0081] In one example, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0082] When the geological target is to take into account fractures of different scale levels, the seismic fracture attribute data volume calculated by the likelihood method or curvature method is used as the basic data.

[0083] Specifically, calculate the earthquake crack attribute data volume B i Corresponding seismic phase C i , analyze and select C with better crack characterization effect i , corresponding to B i The data volume is used as the basic data D1. The standard for good fracture characterization effect is that when the geological target is a large-scale fracture, the B iAs D1; ​​when the geological target is a small-scale fracture, the B obtained by the prestack AVAZ method or VVAZ method can be used. i As D1; ​​when the geological target is to take into account the fractures of different scales, the B calculated by the likelihood method or curvature method can be used. i As D1. Among them, large cracks refer to cracks or fractures with a size larger than one seismic wavelength, medium-scale cracks refer to cracks with a size ranging from one seismic wavelength to one-quarter of the wavelength, and small-scale cracks refer to cracks with a size smaller than one-quarter of the wavelength of the seismic wave.

[0084] The basic data is integrated with the original seismic data volume to calculate the integrated seismic phase. In one example, the basic data is integrated with the original seismic data volume to calculate the integrated seismic phase, including:

[0085] Normalize the basic data and original seismic data volume;

[0086] Calculate the fused data volume;

[0087] Calculate fused seismic phases by fusing data volumes.

[0088] In one example, the fused data volume is calculated by formula (1):

[0089] N=D2+C*M' (1)

[0090] Among them, N is the fusion data volume, D2 is the normalized basic data, M' is the normalized original seismic data volume, and C is the fusion parameter.

[0091] Specifically, the basic data D1 and the original seismic data volume M are normalized, that is, the numerical ranges of the two are unified to the same dimensional level, and the numerical ranges of D1 and M can be unified to between 0 and 1. The fused data volume is calculated by formula (1), and the numerical range of the fusion coefficient C is controlled between (0.1-10). The selection standard of C is to make the crack traces clearly visible in the layer slice attributes in the fused data volume N as much as possible.

[0092] Finally, the fused seismic phase is calculated by fusing the data volume, that is, the seismic phase that takes the cracks into account is obtained.

[0093] The present invention also provides a seismic phase calculation device that takes fracture characterization into consideration, comprising:

[0094] The calculation module calculates multiple earthquake crack attribute data volumes based on the original earthquake data volume.

[0095] Specifically, for the original seismic data volume M, the seismic crack attribute data volume B is calculated using different calculation principles. i(i=1, 2, 3...), for example, the earthquake crack attribute data body characterized by the curvature method is B1, the earthquake crack attribute data body characterized by the coherence method is B2, the earthquake crack attribute data body characterized by the likelihood method is B3, the earthquake crack attribute data body characterized by the AFE method is B4, etc.

[0096] The basic data determination module uses the earthquake crack attribute data volume with the best crack characterization effect as the basic data. In one example, the earthquake crack attribute data volume with the best crack characterization effect as the basic data includes:

[0097] Calculate the seismic phases corresponding to the earthquake crack attribute data volume respectively;

[0098] The earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect is used as the basic data.

[0099] In one example, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0100] When the geological target is a large-scale fracture, the seismic fracture attribute data volume calculated by the coherence method or the AFE method is used as the basic data.

[0101] In one example, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0102] When the geological target is a small-scale fracture, the seismic fracture attribute data volume calculated by the prestack AVAZ method or VVAZ method is used as the basic data.

[0103] In one example, the earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect as basic data includes:

[0104] When the geological target is to take into account fractures of different scale levels, the seismic fracture attribute data volume calculated by the likelihood method or curvature method is used as the basic data.

[0105] Specifically, calculate the earthquake crack attribute data volume B i Corresponding seismic phase C i , analyze and select C with better crack characterization effect i , corresponding to B i The data volume is used as the basic data D1. The standard for good fracture characterization effect is that when the geological target is a large-scale fracture, the B i As D1; ​​when the geological target is a small-scale fracture, the B obtained by the prestack AVAZ method or VVAZ method can be used. iAs D1; ​​when the geological target is to take into account the fractures of different scales, the B calculated by the likelihood method or curvature method can be used. i As D1. Among them, large cracks refer to cracks or fractures with a size larger than one seismic wavelength, medium-scale cracks refer to cracks with a size ranging from one seismic wavelength to one-quarter of the wavelength, and small-scale cracks refer to cracks with a size smaller than one-quarter of the wavelength of the seismic wave.

[0106] The fusion module fuses the basic data with the original seismic data volume and calculates the fused seismic phase. In one example, the fusion of the basic data with the original seismic data volume and the calculation of the fused seismic phase include:

[0107] Normalize the basic data and original seismic data volume;

[0108] Calculate the fused data volume;

[0109] Calculate fused seismic phases by fusing data volumes.

[0110] In one example, the fused data volume is calculated by formula (1):

[0111] N=D2+C*M' (1)

[0112] Among them, N is the fusion data volume, D2 is the normalized basic data, M' is the normalized original seismic data volume, and C is the fusion parameter.

[0113] Specifically, the basic data D1 and the original seismic data volume M are normalized, that is, the numerical ranges of the two are unified to the same dimensional level, and the numerical ranges of D1 and M can be unified to between 0 and 1. The fused data volume is calculated by formula (1), and the numerical range of the fusion coefficient C is controlled between (0.1-10). The selection standard of C is to make the crack traces clearly visible in the layer slice attributes in the fused data volume N as much as possible.

[0114] Finally, the fused seismic phase is calculated by fusing the data volume, that is, the seismic phase that takes the cracks into account is obtained.

[0115] The present invention also provides an electronic device, comprising: a memory storing executable instructions; and a processor running the executable instructions in the memory to implement the above-mentioned seismic phase calculation method taking fracture characterization into consideration.

[0116] The present invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the computer program implements the above-mentioned seismic phase calculation method taking fracture characterization into consideration.

[0117] To facilitate understanding of the solutions and effects of the embodiments of the present invention, four specific application examples are given below. Those skilled in the art should understand that these examples are only for facilitating understanding of the present invention, and any specific details thereof are not intended to limit the present invention in any way.

[0118] Example 1

[0119] Figure 1 A flow chart showing steps of a method for calculating seismic phases taking fracture characterization into consideration according to an embodiment of the present invention.

[0120] like Figure 1 As shown, the seismic phase calculation method taking into account crack characterization includes: step 101, calculating multiple seismic crack attribute data volumes for the original seismic data volume; step 102, using the seismic crack attribute data volume with the best crack characterization effect as basic data; step 103, fusing the basic data with the original seismic data volume to calculate the fused seismic phase.

[0121] A seismic facies characterization, taking fractures into account, was conducted for a target horizon in a specific oilfield area. This area is a tight sandstone oil and gas exploration research area. In such areas, fractures play a crucial role in oil and gas accumulation.

[0122] Figure 2 A schematic diagram of a seismic data plane map slice of a target layer according to an embodiment of the present invention is shown.

[0123] Figure 3 A schematic diagram showing conventional seismic phase characterization results according to an embodiment of the present invention is shown.

[0124] Figure 2 and Figure 3 To a certain extent, it reveals the sedimentary characteristics of this layer. Figure 2 The amplitude slice shows that there are large cracks in this layer, but Figure 3 In the seismic phase table, the cracks that should have been very obvious were represented very vaguely.

[0125] Figure 4a 、 Figure 4b and Figure 4c Schematic diagrams respectively show curvature crack attributes, coherence crack attributes, and likelyhood crack attributes according to an embodiment of the present invention.

[0126] There are many properties that can characterize cracks, which are roughly Figure 4a-4c The other attributes are not described in detail in this example. Each data volume representing a crack has its own unique characteristics and can specifically characterize cracks of different levels, directions, and scales. The Likelyhood attribute can also characterize cracks in a hierarchical manner.

[0127] Figure 5a 、 Figure 5b 、 Figure 5c and Figure 5d Schematic diagrams respectively show the seismic phase corresponding to the coherence attribute, the seismic phase corresponding to the curvature attribute, the seismic phase corresponding to the likelyhood attribute, and the seismic phase corresponding to the fusion of the coherence and curvature attributes according to an embodiment of the present invention.

[0128] according to Figure 4a-4c The three types of crack attributes are respectively mapped to their corresponding earthquake phases. Figure 5a 、 Figure 5b 、 Figure 5c ; It is also possible to group two or more bodies together to calculate a seismic phase, such as Figure 5d After calculating the seismic phase by waveform classification, only Figure 5a The cracks can be clearly characterized. Therefore, the corresponding coherent crack attribute body is used as the basic data D1.

[0129] Figure 6 A schematic diagram showing the seismic phase results of fracture characterization according to an embodiment of the present invention. Figure 3 compared to, Figure 6 On the one hand, it can highlight the existence of fracture phases. On the other hand, when the fracture factor is taken into account, the distribution of sedimentary phases is more stable and has regional characteristics. Figure 3 This is more consistent with the actual geological understanding, proving that this seismic phase result is more reliable.

[0130] Example 2

[0131] Figure 7 A block diagram of a seismic phase calculation device taking fracture characterization into consideration according to an embodiment of the present invention is shown.

[0132] like Figure 7 As shown, the seismic phase calculation device taking fracture characterization into consideration includes:

[0133] The calculation module 201 calculates multiple earthquake fracture attribute data volumes based on the original earthquake data volume;

[0134] Basic data determination module 202, using the earthquake crack attribute data volume with the best crack characterization effect as basic data;

[0135] The fusion module 203 fuses the basic data with the original seismic data volume and calculates the fused seismic phase.

[0136] As an optional solution, the seismic crack attribute data volume with the best crack characterization effect is used as the basic data, including:

[0137] Calculate the seismic phases corresponding to the earthquake crack attribute data volume respectively;

[0138] The earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect is used as the basic data.

[0139] As an optional solution, the earthquake crack attribute data corresponding to the earthquake with the best crack characterization effect is used as the basic data, including:

[0140] When the geological target is a large-scale fracture, the seismic fracture attribute data volume calculated by the coherence method or the AFE method is used as the basic data.

[0141] As an optional solution, the earthquake crack attribute data corresponding to the earthquake with the best crack characterization effect is used as the basic data, including:

[0142] When the geological target is a small-scale fracture, the seismic fracture attribute data volume calculated by the prestack AVAZ method or VVAZ method is used as the basic data.

[0143] As an optional solution, the earthquake crack attribute data corresponding to the earthquake with the best crack characterization effect is used as the basic data, including:

[0144] When the geological target is to take into account fractures of different scale levels, the seismic fracture attribute data volume calculated by the likelihood method or curvature method is used as the basic data.

[0145] As an optional solution, the basic data is fused with the original seismic data volume to calculate the fused seismic phase including:

[0146] Normalize the basic data and original seismic data volume;

[0147] Calculate the fused data volume;

[0148] Calculate fused seismic phases by fusing data volumes.

[0149] As an alternative, the fused data volume is calculated using formula (1):

[0150] N=D2+C*M' (1)

[0151] Among them, N is the fusion data volume, D2 is the normalized basic data, M' is the normalized original seismic data volume, and C is the fusion parameter.

[0152] Example 3

[0153] The present disclosure provides an electronic device, comprising: a memory storing executable instructions; and a processor running the executable instructions in the memory to implement the above-mentioned seismic phase calculation method taking fracture characterization into consideration.

[0154] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0155] The memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc.

[0156] The processor may be a central processing unit (CPU) or other form of processing unit having data processing capability and / or instruction execution capability, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is used to execute the computer-readable instructions stored in the memory.

[0157] Those skilled in the art should understand that in order to solve the technical problem of how to obtain a good user experience, this embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the scope of protection of this disclosure.

[0158] For detailed description of this embodiment, please refer to the corresponding description in the aforementioned embodiments, which will not be repeated here.

[0159] Example 4

[0160] An embodiment of the present disclosure provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the seismic phase calculation method taking fracture characterization into consideration is implemented.

[0161] According to an embodiment of the present disclosure, a computer-readable storage medium stores non-transitory computer-readable instructions, which, when executed by a processor, execute all or part of the steps of the aforementioned methods of the embodiments of the present disclosure.

[0162] The above-mentioned computer-readable storage media include, but are not limited to, optical storage media (e.g., CD-ROMs and DVDs), magneto-optical storage media (e.g., MOs), magnetic storage media (e.g., magnetic tapes or mobile hard disks), media with built-in rewritable non-volatile memory (e.g., memory cards), and media with built-in ROM (e.g., ROM cartridges).

[0163] Those skilled in the art should understand that the above description of the embodiments of the present invention is only for the purpose of illustrative purposes only to illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.

[0164] While various embodiments of the present invention have been described above, the above description is intended to be illustrative, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A seismic phase calculation method taking into account fracture characterization, characterized in that: include: Calculate multiple seismic fracture attribute data volumes for the original seismic data volume; The earthquake crack attribute data volume with the best crack characterization effect is used as the basic data; Fusing the basic data with the original seismic data volume to calculate the fused seismic phase; Among them, the earthquake crack attribute data with the best crack characterization effect as the basic data includes: respectively calculating the seismic phases corresponding to the seismic crack attribute data volumes; The earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect is used as the basic data; The step of fusing the basic data with the original seismic data volume to calculate the fused seismic phase includes: performing normalization processing on the basic data and the original seismic data volume; Calculate the fused data volume; The fused seismic phase is calculated from the fused data volume.

2. The seismic phase calculation method taking fracture characterization into consideration according to claim 1, wherein: The earthquake crack attribute data corresponding to the earthquake with the best crack characterization effect is used as the basic data, including: When the geological target is a large-scale fracture, the seismic fracture attribute data volume calculated by the coherence method or the AFE method is used as the basic data.

3. The seismic phase calculation method taking fracture characterization into consideration according to claim 1, wherein: The earthquake crack attribute data corresponding to the earthquake with the best crack characterization effect is used as the basic data, including: When the geological target is a small-scale fracture, the seismic fracture attribute data volume calculated by the pre-stack AVAZ method or the VVAZ method is used as the basic data.

4. The seismic phase calculation method taking fracture characterization into consideration according to claim 1, wherein: The earthquake crack attribute data corresponding to the earthquake with the best crack characterization effect is used as the basic data, including: When the geological target is to take into account fractures of different scale levels, the seismic fracture attribute data volume calculated by the likelihood method or the curvature method is used as the basic data.

5. The seismic phase calculation method taking fracture characterization into consideration according to claim 1, wherein: The fused data volume is calculated by formula (1): N=D2+C*M' (1) Among them, N is the fusion data volume, D2 is the normalized basic data, M' is the normalized original seismic data volume, and C is the fusion parameter.

6. A seismic phase calculation device taking into account fracture characterization, characterized in that: include: A calculation module calculates multiple earthquake fracture attribute data volumes based on the original earthquake data volume; The basic data determination module uses the earthquake crack attribute data volume with the best crack characterization effect as the basic data; A fusion module, fusing the basic data with the original seismic data volume to calculate the fused seismic phase; Among them, the earthquake crack attribute data with the best crack characterization effect as the basic data includes: respectively calculating the seismic phases corresponding to the seismic crack attribute data volumes; The earthquake crack attribute data volume corresponding to the earthquake with the best crack characterization effect is used as the basic data; The step of fusing the basic data with the original seismic data volume to calculate the fused seismic phase includes: performing normalization processing on the basic data and the original seismic data volume; Calculate the fused data volume; The fused seismic phase is calculated from the fused data volume.

7. An electronic device, characterized in that: The electronic device comprises: a memory storing executable instructions; A processor runs the executable instructions in the memory to implement the seismic phase calculation method taking fracture characterization into consideration according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the seismic phase calculation method taking fracture characterization into consideration according to any one of claims 1 to 5 is implemented.

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