Geological model generation method and device based on fractured-vuggy reservoir

Abstract

The invention provides a geological model generation method and device based on a fractured-vuggy reservoir, and the method comprises the steps: generating a first stratum model of a target work area according to the logging data and seismic data of the target work area, and the reservoir type of the target work area is a fractured-vuggy reservoir; according to the seismic data, determining lithology characterization parameters of stratums except the fracture-cavity type reservoir in the target work area, and adding the lithology characterization parameters to the first stratum model to generate a second stratum model; a pre-generated random function is added to the second stratum model to generate a geologic model of the target work area, and the random function is used for representing the space and lithology of the fracture-vug type reservoir. Compared with an existing geologic body modeling method, the structure description precision and the lithology description precision of the fracture-vug type reservoir are improved, and therefore the description precision and the prediction precision of the fracture-vug type reservoir are improved.

Description

Technical Field

[0001] This application belongs to the technical field of oil and gas exploration, especially the technical field of seismic data processing for oil and gas exploration. Specifically, it relates to a method and device for generating a geological model based on a fracture-vug reservoir. Background Art

[0002] In recent years, obvious achievements have been obtained in the exploration and development of fracture-vug carbonate reservoirs in many areas. However, since the burial depth of fracture-vug carbonate reservoirs generally exceeds 6,000 meters, and the scales of fracture-vug reservoirs are variable, the connection relationship between caves is not clear, and it is difficult to image the reservoirs, it is very difficult to accurately depict the scale of the reservoirs. Aiming at the problem of difficult reservoir modeling, the modeling methods in the prior art describe the fracture-vug reservoirs relatively simply, and do not comprehensively describe the petrophysical properties inside the reservoirs, and cannot have an accurate amplitude and phase response in the seismic records obtained by forward modeling. Therefore, the modeling method for the reservoirs is not accurate. Summary of the Invention

[0003] This invention belongs to the technical field of seismic data processing. An object of this invention is to provide a method and device for generating a geological model based on a fracture-vug reservoir, which can not only fully consider the influence of the scale of fractures and vugs themselves on seismic records, but also consider the petrophysical properties inside the fracture-vug reservoir under actual geological structures. Compared with the existing geological body modeling methods, this method is beneficial to improving the structure description accuracy and lithology description accuracy of the fracture-vug reservoir, and improving the depiction accuracy and prediction accuracy of the fracture-vug reservoir.

[0004] Another object of this invention is to provide a device for generating a geological model based on a fracture-vug reservoir. Still another object of this invention is to provide an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned method for generating a geological model based on a fracture-vug reservoir are implemented. Still another object of this invention is to provide a readable medium, on which a computer program is stored, and when the computer program is executed by the processor, the steps of the above-mentioned method for generating a geological model based on a fracture-vug reservoir are implemented.

[0005] To solve the technical problems in the background art of this application, this invention provides the following technical solutions:

[0006] In the first aspect, this invention provides a method for generating a geological model based on a fracture-vug reservoir, including:

[0007] Generating a first stratigraphic model of the target work area according to the logging data and seismic data of the target work area, where the reservoir type of the target work area is a fracture-vug reservoir;

[0008] Determine the lithology characterization parameters of the formations in the target work area except for the fracture-vuggy reservoir based on the seismic data, and add them to the first formation model to generate a second formation model;

[0009] Add a pre-generated random function to the second formation model to generate the geological model of the target work area, where the random function is used to characterize the space and lithology of the fracture-vuggy reservoir.

[0010] In an embodiment of the present invention, the generating the first formation model of the target work area based on the logging data and seismic data of the target work area includes:

[0011] Determine the reflection interface and seismic facies of the target work area based on the seismic data;

[0012] Perform a primary division of the formations in the target work area based on the reflection interface and the seismic facies to generate a primary division result;

[0013] Perform a secondary division of the primary division result based on the lithology logging curves of the target work area to generate the first formation model.

[0014] In an embodiment of the present invention, the lithology logging curves include a borehole diameter logging curve, a spontaneous potential logging curve, and a natural gamma logging curve.

[0015] In an embodiment of the present invention, the steps of generating the random function include:

[0016] Establish the spatial characterization parameters of the fracture-vuggy reservoir based on the burial depth of the fracture-vuggy reservoir, the number of fracture-vuggy bodies, the distance between multiple fracture-vuggy bodies, and the spatial scale parameters of the fracture-vuggy reservoir;

[0017] Establish the lithology characterization parameters of the fracture-vuggy reservoir based on the lithology parameters of the fracture-vuggy bodies;

[0018] Generate the random function based on the spatial characterization parameters, the lithology characterization parameters, and the initial function of the random function.

[0019] In an embodiment of the present invention, the spatial scale parameters include a longitudinal scale parameter and a transverse scale parameter;

[0020] The lithology parameters of the fracture-vuggy bodies include longitudinal wave velocity, transverse wave velocity, and density.

[0021] In an embodiment of the present invention, the initial function is a normal distribution random function.

[0022] In an embodiment of the present invention, the lithology characterization parameters of the formations in the target work area except for the fracture-vuggy reservoir include longitudinal wave velocity, transverse wave velocity, and density;

[0023] The lithological parameters of the fracture-vug body further include porosity and permeability.

[0024] In a second aspect, the present invention provides a geological model generation device based on a fracture-vug reservoir, and the device includes:

[0025] A first formation model generation module, configured to generate a first formation model of the target work area according to well logging data and seismic data of the target work area, and the reservoir type of the target work area is a fracture-vug reservoir;

[0026] A second formation model generation module, configured to determine lithological characterization parameters of formations other than the fracture-vug reservoir in the target work area according to the seismic data, and add them to the first formation model to generate a second formation model;

[0027] A geological model generation module, configured to add a pre-generated random function to the second formation model to generate a geological model of the target work area, wherein the random function is used to characterize the space and lithology of the fracture-vug reservoir.

[0028] In an embodiment of the present invention, the first formation model generation module includes:

[0029] A reflection interface determination unit, configured to determine a reflection interface and a seismic facies of the target work area according to the seismic data;

[0030] A primary division result generation unit, configured to perform a primary division on the formations of the target work area according to the reflection interface and the seismic facies to generate a primary division result;

[0031] A first formation model generation unit, configured to perform a secondary division on the primary division result according to a lithological well logging curve of the target work area to generate a first formation model.

[0032] In an embodiment of the present invention, the lithological well logging curve includes a caliper well logging curve, a spontaneous potential well logging curve, and a natural gamma well logging curve.

[0033] In an embodiment of the present invention, a geological model generation device based on a fracture-vug reservoir further includes:

[0034] A random function generation module, configured to generate the random function, and the random function generation module includes:

[0035] A spatial characterization parameter establishment unit, configured to establish spatial characterization parameters of the fracture-vug reservoir according to the burial depth of the fracture-vug reservoir, the number of fracture-vug bodies, the distance between multiple fracture-vug bodies, and the spatial scale parameters of the fracture-vug reservoir;

[0036] A lithology characterization parameter establishing unit, configured to establish lithology characterization parameters of the fracture-vug reservoir according to the lithology parameters of the fracture-vug bodies;

[0037] A random function generating unit, configured to generate the random function according to the spatial characterization parameters, the lithology characterization parameters, and an initial function of the random function.

[0038] In an embodiment of the present invention, the spatial scale parameters include a longitudinal scale parameter and a transverse scale parameter;

[0039] The lithology parameters of the fracture-vug bodies include a longitudinal wave velocity, a transverse wave velocity, and a density.

[0040] In an embodiment of the present invention, the initial function is a normal distribution random function.

[0041] In an embodiment of the present invention, the lithology characterization parameters of the formations in the target work area other than the fracture-vug reservoir include a longitudinal wave velocity, a transverse wave velocity, and a density;

[0042] The lithology parameters of the fracture-vug bodies further include a porosity and a permeability.

[0043] In a third aspect, the present invention provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of a method for generating a geological model based on a fracture-vug reservoir.

[0044] In a fourth aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor, when executing the program, implements the steps of a method for generating a geological model based on a fracture-vug reservoir.

[0045] In a fifth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of a method for generating a geological model based on a fracture-vug reservoir.

[0046] As can be seen from the above description, an embodiment of the present invention provides a method and apparatus for generating a geological model based on a fracture-vug reservoir. The corresponding method for generating a geological model based on a fracture-vug reservoir includes: first, generating a first formation model of a target work area according to well logging data and seismic data of the target work area, where the reservoir type of the target work area is a fracture-vug reservoir; then, determining lithology characterization parameters of the formations in the target work area other than the fracture-vug reservoir according to the seismic data, and adding them to the first formation model to generate a second formation model; finally, adding a pre-generated random function to the second formation model to generate a geological model of the target work area, where the random function is used to characterize the space and lithology of the fracture-vug reservoir.

[0047] The corresponding geological model generation device for fractured-vuggy reservoirs includes: a first formation model generation module, configured to generate a first formation model of the target work area according to the logging data and seismic data of the target work area, where the reservoir type of the target work area is a fractured-vuggy reservoir; a second formation model generation module, configured to determine the lithology characterization parameters of the formations other than the fractured-vuggy reservoir in the target work area according to the seismic data, and add them to the first formation model to generate a second formation model; a geological model generation module, configured to add a pre-generated random function to the second formation model to generate a geological model of the target work area, where the random function is used to characterize the space and lithology of the fractured-vuggy reservoir.

[0048] The geological model generation method for fractured-vuggy reservoirs proposed by this method can not only fully consider the influence of the scale of fractures and vugs themselves on seismic records, but also take into account the petrophysical properties inside the fractured-vuggy reservoir under actual geological structures. Compared with the existing geological body modeling methods, the present invention improves the structural description accuracy and lithology description accuracy of fractured-vuggy reservoirs, thereby improving the characterization accuracy and prediction accuracy of fractured-vuggy reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0050] Figure 1 It is a schematic flowchart of a method for generating a geological model based on a fractured-vuggy reservoir in an embodiment of the present invention;

[0051] Figure 2 It is a schematic flowchart of step 100 of the method for generating a geological model based on a fractured-vuggy reservoir in an embodiment of the present invention;

[0052] Figure 3 It is another schematic flowchart of the method for generating a geological model based on a fractured-vuggy reservoir in an embodiment of the present invention;

[0053] Figure 4 It is a schematic flowchart of step 400 of the method for generating a geological model based on a fractured-vuggy reservoir in an embodiment of the present invention;

[0054] Figure 5 It is a schematic flowchart of the method for generating a geological model based on a fractured-vuggy reservoir in the specific embodiment of the present invention;

[0055] Figure 6 It is a mind map of the method for generating a geological model based on a fractured-vuggy reservoir in the specific embodiment of the present invention;

[0056] Figure 7 Schematic diagram of the background geological model for establishing the formation framework in the specific embodiment of the present invention;

[0057] Figure 8 The first schematic diagram of the fracture-vuggy reservoir geological model at a certain depth with different scales in the specific embodiment of the present invention;

[0058] Figure 9 The second schematic diagram of the fracture-vuggy reservoir geological model at a certain depth with different scales in the specific embodiment of the present invention;

[0059] Figure 10 The third schematic diagram of the fracture-vuggy reservoir geological model at a certain depth with different scales in the specific embodiment of the present invention;

[0060] Figure 11 The fourth schematic diagram of the fracture-vuggy reservoir geological model at a certain depth with different scales in the specific embodiment of the present invention;

[0061] Figure 12 Schematic diagram of the geological modeling results of the fracture-vuggy reservoir simulating different scales and rock physical properties in the specific embodiment of the present invention;

[0062] Figure 13 Block diagram of the geological model generation device based on the fracture-vuggy reservoir in the specific embodiment of the present invention;

[0063] Figure 14 Schematic diagram of the structure of the electronic device in the embodiment of the present invention. Specific embodiment

[0064] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0065] Those skilled in the art should understand that the embodiments of the present invention may be provided as a method, a system, or a computer program product. Therefore, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0066] It should be noted that the terms "including" and "having" in the description, claims and above-mentioned drawings of this application, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices. Without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will detail this application with reference to the drawings and in combination with embodiments.

[0067] In the technical solution of this application, the acquisition, storage, use, processing, etc. of data all comply with the relevant regulations of laws and regulations.

[0068] Embodiment 1:

[0069] An embodiment of the present invention provides a specific implementation manner of a geological model generation method based on a fracture-vuggy reservoir. Refer to Figure 1 , and specifically includes the following content:

[0070] Step 100: Generate a first formation model of the target work area according to the logging data and seismic data of the target work area, and the reservoir type of the target work area is a fracture-vuggy reservoir;

[0071] Step 200: Determine the lithology characterization parameters of the formations other than the fracture-vuggy reservoir in the target work area according to the seismic data, and add them to the first formation model to generate a second formation model;

[0072] Step 300: Add a pre-generated random function to the second formation model to generate the geological model of the target work area, where the random function is used to characterize the space and lithology of the fracture-vuggy reservoir.

[0073] As can be seen from the above description, an embodiment of the present invention provides a geological model generation method based on a fracture-vuggy reservoir, including: first, generate a first formation model of the target work area according to the logging data and seismic data of the target work area, and the reservoir type of the target work area is a fracture-vuggy reservoir; then, determine the lithology characterization parameters of the formations other than the fracture-vuggy reservoir in the target work area according to the seismic data, and add them to the first formation model to generate a second formation model; finally, add a pre-generated random function to the second formation model to generate the geological model of the target work area, where the random function is used to characterize the space and lithology of the fracture-vuggy reservoir.

[0074] The geological model generation method for fractured-vuggy reservoirs proposed by this method can not only fully consider the influence of the scale of fractures and vugs themselves on seismic records, but also take into account the petrophysical properties inside the fractured-vuggy reservoir under actual geological structures. Compared with the existing geological body modeling methods, the present invention improves the structural description accuracy and lithology description accuracy of fractured-vuggy reservoirs, thereby improving the characterization accuracy and prediction accuracy of fractured-vuggy reservoirs.

[0075] Example Two:

[0076] It can be understood that the fractured-vuggy reservoir in Step 100 is a special type of oil and gas reservoir, whose characteristic is that the reservoir space is mainly composed of rock fractures and caves. This type of reservoir is commonly found under some special geological conditions, such as carbonate rock formations, karst landforms, etc.

[0077] The rock fractures and caves in fractured-vuggy reservoirs can provide a relatively large reservoir space, which is conducive to the storage and migration of oil and gas. The characteristics of this type of reservoir are relatively high porosity and large permeability, resulting in good reservoir capacity and fluidity. When exploring and developing fractured-vuggy reservoirs, it is necessary to accurately judge the distribution and characteristics of the reservoir through means such as geological exploration, seismic exploration, and well exploration. At the same time, appropriate development methods, such as horizontal wells, acidification, fracturing, etc., need to be adopted to effectively develop and produce oil and gas resources. The exploration and development of fractured-vuggy reservoirs have certain technical difficulties, but due to their relatively strong reservoir capacity and large development potential, they have received extensive attention and research.

[0078] In addition, the logging data in Step 100 refers to the data on the properties of underground rocks, water, oil and gas, etc. obtained by logging instruments during the drilling process. Logging data can provide information on the physical properties, lithology, porosity, permeability, etc. of underground reservoirs, and is of great significance for the exploration and development of oil and gas resources. Preferably, the logging data in Step 100 includes:

[0079] Electric logging (SP, GR, LLD, RT): By measuring the electrical properties of underground rocks, information such as lithology, porosity, and water saturation can be obtained.

[0080] Natural gamma logging (GR): By measuring the radioactive intensity of underground rocks, the type and mineral composition of rocks can be judged.

[0081] Acoustic logging (DT, Sonic): By measuring the propagation speed of sound waves in underground rocks, information such as the density and Poisson's ratio of rocks can be judged.

[0082] Nuclear magnetic resonance logging (NMR): By measuring the nuclear magnetic resonance phenomenon in underground rocks, information such as pore structure and water saturation can be obtained.

[0083] Modular Dynamics Tester (MDT): By measuring the pressure changes in the underground reservoir, the properties and pressure distribution of the oil and gas reservoir can be determined.

[0084] It can be understood that the purpose of step 100 is to establish a framework within which the work done in the subsequent steps is carried out.

[0085] For step 200, based on step 100, lithology characterization parameters of a conventional reservoir (non-fractured-vuggy reservoir) are established according to seismic data. Preferably, lithology characterization parameters can be established through P-wave velocity, S-wave velocity, and density. Specifically:

[0086] P-wave / S-wave velocity ratio (Vp / Vs): Calculate the ratio of P-wave velocity to S-wave velocity to determine the type of rock. Generally speaking, the Vp / Vs ratio of carbonate rocks is relatively low, while that of sandstones and shales is relatively high.

[0087] Density-acoustic velocity relationship (density-velocity pair): Through the relationship between density and acoustic velocity, a density-velocity pair diagram can be established, and the type of rock can be determined according to the position of the rock in the diagram. For example, carbonate rocks and sandstones can exhibit different clustering characteristics in the density-velocity pair diagram.

[0088] In addition, by inputting parameters such as P-wave velocity, S-wave velocity, and density into a rock physics parameter model, physical properties such as porosity and permeability of the rock can be calculated.

[0089] In a more preferred manner, by performing optimized calculations on P-wave velocity, S-wave velocity, and density to generate a new parameter (i.e., lithology characterization parameter), this parameter is extremely sensitive to the lithology of the target work area and can better characterize the formation lithology.

[0090] Regarding step 300, it can be understood that the regularity of fractured-vuggy reservoirs is extremely poor and has a very large randomness. It is difficult to use existing methods to characterize their spatial and lithology changes. The values generated by random functions in a certain range are random, with the characteristics of unpredictability and uniformity, which happen to be similar to those of fractured-vuggy reservoirs. Therefore, the method of random functions can be used to predict the lithology and space of fractured-vuggy reservoirs.

[0091] In some embodiments of the present invention, referring to Figure 2 , step 100 includes:

[0092] Step 101: Determine the reflection interface and seismic facies of the target work area according to the seismic data;

[0093] A reflection interface refers to the interface between two media with different properties within the Earth's internal medium, which can reflect seismic waves. The process of searching for reflection interfaces is an important task in seismic exploration. Different types of reflection interfaces can be obtained according to different methods of seismic exploration data processing. Seismic facies refer to the fluctuation conditions caused by sudden changes in wave impedance due to changes in the medium during the propagation of seismic waves. By recording and analyzing seismic waves, different types of seismic facies can be determined.

[0094] When implementing Step 101, first, preprocess the seismic data, including operations such as denoising and balancing, to clearly display the seismic signals. Then, observe the seismic waveforms and find the places where the waveform changes significantly. This may be the seismic signal generated by the reflection interface, but it is necessary to combine geological conditions to determine whether it is a real reflection interface. Track the reflection interface, search for the same-shaped reflection waveforms at different detection points, and determine the depth positions of the reflection interface at each detection point. Judge whether the reflection interface is an upper reflection interface or a lower reflection interface according to the phase change of the reflection waveform. The same phase change represents the same reflection interface. Analyze the frequency components of the reflection waveform. Higher frequencies represent near layers, and lower frequencies represent far layers. This can help identify multiple reflections. Connect the depths of the reflection interfaces at multiple adjacent detection points to reconstruct the variation law of the reflection interface in the horizontal direction. Combine the geological structure and the variation law of geological lithology to give a geological interpretation of the reflection interface and determine the specific formation or structural interface it represents. Compare the synchronous or subsequent seismic exploration data to further verify and correct the accuracy of the reflection interface identification results.

[0095] Step 102: Perform a primary division on the strata of the target work area according to the reflection interface and the seismic facies to generate a primary division result;

[0096] Specifically, generate the overall framework of the first stratum model, that is, the primary division result, according to the reflection interface and seismic facies identified in Step 101. It can be understood that, relatively speaking, the result of this stratum division is relatively rough compared to Step 103.

[0097] Step 103: Perform a secondary division on the primary division result according to the lithology logging curve of the target work area to generate the first stratum model.

[0098] It is understandable that well logging data has the following advantages over seismic data: Well logging instruments are in direct contact with underground rocks and can provide higher resolution. In contrast, seismic data is the result of the interference of underground reflected waves received by surface seismic sources and receivers, and has relatively low resolution. Well logging data can provide physical property parameters of rocks, such as density, porosity, saturation, etc., and quantitative analysis can be carried out. Seismic data is more inclined to provide information on the position and shape of underground structures and reflection interfaces. Well logging data can be obtained in real time during field exploration, making the decision-making process more rapid and flexible. Seismic data requires data acquisition and processing to obtain usable results, which takes a longer time. Well logging data can provide continuous sampling of the underground profile in the vertical direction and can more accurately depict the changes in strata. Relatively speaking, the resolution of seismic data in the vertical direction is relatively poor. Therefore, in step 103, based on the result of the first division, fine formation division is carried out by lithology well logging curves.

[0099] In summary, through step 102 and step 103, seismic data can provide a larger range of underground structures, while well logging data can provide more detailed physical property parameters of rocks. Well logging data and seismic data can complement each other and jointly provide a more comprehensive first formation model with more information.

[0100] In some embodiments of the present invention, the lithology well logging curves include caliper log curves, spontaneous potential log curves, and natural gamma ray log curves.

[0101] Caliper Log is used to measure the change in the diameter of the wellbore, usually in millimeters or inches. This curve can reflect the formation lithology and provide information on the wellbore shape, including the diameter of the wellbore, the situation of expansion or contraction, and possible problems such as wellbore collapse or caving.

[0102] Spontaneous Potential Log (SP) measures the change in the spontaneous potential difference of the formation and can be used for formation lithology identification. The spontaneous potential is caused by the distribution of underground current and charge and can reflect the electrical and salinity characteristics in the formation. The spontaneous potential log curve is used to identify groundwater layers such as aquifers and saline water-bearing layers.

[0103] Natural Gamma Ray Log (GR) measures the change in the intensity of natural gamma rays in the formation and can be used for formation lithology identification. Natural gamma rays are natural radiations widely present on the earth's surface and in underground rocks, and their intensity is related to the content of radioactive elements in the formation.

[0104] In some embodiments of the present invention, see Figure 3 , a method for generating a geological model based on a fracture-cavity type reservoir, further includes:

[0105] Step 400: Generate the random function. Refer to Figure 4 , and step 400 includes:

[0106] Step 401: Establish the spatial characterization parameters of the fractured-vuggy reservoir according to the burial depth of the fractured-vuggy reservoir, the number of vug bodies, the distance between multiple vug bodies, and the spatial scale parameters of the fractured-vuggy reservoir;

[0107] Step 402: Establish the lithology characterization parameters of the fractured-vuggy reservoir according to the lithology parameters of the vug bodies;

[0108] Step 403: Generate the random function according to the spatial characterization parameters, the lithology characterization parameters, and the initial function of the random function.

[0109] Specifically, in steps 401 to 403, first, set the burial depth H of the fractured-vuggy reservoir, the number D of vug bodies, the distance L between vug bodies, and the spatial scale of the fractured-vuggy reservoir itself, including the longitudinal scale h cav and the transverse scale d cav ; then, set the lithology parameters inside the vugs, including the longitudinal wave velocity V p , the shear wave velocity V s , the density ρ, the porosity φ, and the permeability κ parameters, and their expression is: Cav(H,L,D)={V p (i),V s (i),ρ(i),φ(i),κ(i)}, i≤D;

[0110] Finally, generate the random function, and its expression is {rand (x,y,z) , Cav(H,L,D)}, where rand (x,y,z) is the spatial coordinate of the fractured-vuggy reservoir.

[0111] In some embodiments of the present invention, the spatial scale parameters include longitudinal scale parameters and transverse scale parameters;

[0112] The lithology parameters of the vug bodies include longitudinal wave velocity, shear wave velocity, and density.

[0113] The longitudinal wave velocity (P-wave velocity / Vp) is an elastic wave that generates compression and expansion along the propagation direction, also known as a compression wave or longitudinal wave. The longitudinal wave velocity is the velocity at which the longitudinal wave propagates in the rock. It is related to factors such as the elastic modulus of the rock, the density of the rock, and the fractures and porosity in the rock. The higher the longitudinal wave velocity, usually the higher the density and strength of the rock, so the longitudinal wave velocity can be used as a lithology parameter.

[0114] The shear wave velocity (S-wave velocity / Vs) is an elastic wave that vibrates perpendicular to the propagation direction, also known as a shear wave or a transverse wave. The shear wave velocity is the velocity at which the shear wave propagates in the rock. It is related to factors such as the shear modulus of the rock, the density of the rock, and the fractures and porosity in the rock. The shear wave velocity is usually lower than the compressional wave velocity, and its propagation velocity is affected by the strength and toughness of the rock. Therefore, the shear wave velocity can be used as a lithology parameter.

[0115] Density is a physical parameter that describes the mass distribution of the rock, representing the mass of the rock per unit volume. Density is usually expressed in grams per cubic centimeter (g / cm 3 ) or kilograms per cubic meter (kg / m 3 ). The density of the rock is related to factors such as the composition of the rock, porosity, and saturation. By measuring the density of the subsurface rock, the type of rock, saturation, porosity, and physical properties of the rock can be inferred. Therefore, the shear wave velocity can be used as a lithology parameter.

[0116] In some embodiments of the present invention, the initial function is a normal distribution random function.

[0117] A normal distribution random function is a function that generates random numbers that follow a normal distribution (also known as a Gaussian distribution) and has the characteristics of a bell-shaped curve. The characteristics of the normal distribution are as follows:

[0118] Symmetry: The normal distribution is symmetric about the mean, with the mean located at the center of the distribution and the tails on both sides gradually decaying.

[0119] Kurtosis: The normal distribution has zero kurtosis, that is, its kurtosis coefficient is 0. This means that its tails are relatively light and there is no obvious skewness.

[0120] Parametrization: The normal distribution is completely determined by two parameters, the mean and the standard deviation. The mean determines the position of the distribution, and the standard deviation determines the degree of dispersion of the distribution.

[0121] Specifically, the Box-Muller transformation or the Marsaglia polar coordinate method can be used to generate the initial function of the random function. It can be understood that a large amount of production data shows that although the space of the fracture-vug reservoir is irregular, it generally conforms to the normal distribution as a whole. Therefore, the normal distribution random function can be used to characterize the space of the fracture-vug body and the trend of lithology change.

[0122] In some embodiments of the present invention, the lithology characterization parameters of the formations in the target work area other than the fracture-vug reservoir include the compressional wave velocity, the shear wave velocity, and the density;

[0123] The lithology parameters of the fracture-vug body also include porosity and permeability.

[0124] Porosity refers to the proportion of pore space within a rock. It represents the ratio of the volume of pores in the rock to the total volume of the rock. Porosity can be used to describe the reservoir properties of a rock.

[0125] Permeability refers to the ability of fluids to flow through the pores in a rock. It represents the velocity of fluid flow through the rock pores under a unit pressure per unit time. Permeability is an important parameter for describing the seepage properties of a rock and affects the development of oil and gas fields and the extraction of water resources.

[0126] It should be noted that porosity and permeability are interrelated, but not always directly proportional. A high porosity in a rock does not necessarily mean a high permeability, as it is also affected by factors such as the connectivity of the rock pores, pore morphology, and pore size distribution.

[0127] From the above description, embodiments of the present invention provide a method for generating a geological model based on a fracture-vuggy reservoir, including: first, generating a first formation model of a target work area according to well logging data and seismic data of the target work area, where the reservoir type of the target work area is a fracture-vuggy reservoir; then, determining the lithological characterization parameters of the formations other than the fracture-vuggy reservoir in the target work area according to the seismic data and adding them to the first formation model to generate a second formation model; finally, adding a pre-generated random function to the second formation model to generate a geological model of the target work area, where the random function is used to characterize the space and lithology of the fracture-vuggy reservoir.

[0128] Since the distribution of fracture-vug reservoirs in the vertical and horizontal directions is controlled by geological factors such as sedimentation, fluids, and tectonics, but there are significant differences in the influence of the main controlling factors under different geological backgrounds. Therefore, different modeling methods for fracture-vug reservoirs need to be established for different geological bodies. The stochastic modeling method using well logging data, seismic data, and lithological parameters proposed in the present invention can model fracture-vug reservoirs of different scales, effectively improving the modeling accuracy of fracture-vuggy reservoirs and the characterization accuracy of fracture-vug reservoirs.

[0129] Example Three:

[0130] In a specific implementation manner, the present invention also takes a deep carbonate rock reservoir as an example to provide a specific implementation manner of a method for generating a geological model based on a fracture-vuggy reservoir. Refer to Figure 5 and Figure 6 , which specifically includes the following steps.

[0131] The main reservoir spaces of carbonate fracture-vuggy reservoirs are fractures, vugs, and pores. Carbonate rock is a sedimentary rock composed of carbonate minerals (such as calcite, dolomite, etc.) and has high dissolution and solubility. In carbonate rocks, there are various types of fractures, vugs, and pores, including the following:

[0132] Flow-through fractures and caves: Due to dissolution or fissure development, a connected fracture-cave system is formed, which has good fluid and gas mobility.

[0133] Cave: Dissolution in carbonate rocks can form large caves, which are important reservoir spaces. Caves can have high porosity and permeability and are suitable for storage and fluid migration.

[0134] Fine pores: There are also some microscopic pores in carbonate rocks, such as interparticle pores, microfractures, and intercrystalline pores. Although individual pores are very small, due to their large number, they can provide storage and fluid migration space to a certain extent.

[0135] The characteristics of carbonate fracture-cave reservoirs include: large spatial heterogeneity of porosity and permeability, and there may be significant differences in storage capacity and fluidity at different geological locations. The connectivity of fractures and caves is crucial for the effectiveness of the reservoir, and a well-connected fracture-cave system is conducive to the accumulation and flow of oil and gas. There are very complex fracture-cave and pore development patterns in the reservoir, and multiple data such as logging, core analysis, and seismic data need to be comprehensively used for interpretation and evaluation.

[0136] S1: Establish a formation model framework based on actual logging data and seismic data.

[0137] Based on actual logging data {Well 1 ,Well 2 ,...,Well n} and seismic data Cube seis , establish a formation model framework {Strat 1 ,Strat 2 ,...,Strat m}.

[0138] Figure 7 It shows the establishment of a background geological model based on the formation framework. According to seismic data and logging data, the burial depth and shape of different geological bodies are established, and according to logging data, the P-wave velocity, S-wave velocity, and density parameters are filled into the framework.

[0139] S2: Establish parameters such as P-wave velocity, S-wave velocity, and density in the formation model framework, and establish a lithology expression for a certain formation.

[0140] Establish the P-wave velocity V p , the S-wave velocity V s , and density parameter ρ in the formation model framework. For a certain formation, its lithology expression is Strat k (1≤k≤m) = {V p (k),V s (k),ρ(k)}.

[0141] S3: Construct the expression of the lithology parameters inside the fracture-vug bodies of the fracture-vug reservoir.

[0142] First, set the burial depth H of the fracture-vug reservoir, the number D of the fracture-vug bodies, the distance L between the fracture-vug bodies, and the spatial scale of the fracture-vug reservoir itself, including the vertical scale h cav and the horizontal scale d cav ; Then, set the lithology parameters inside the fractures and vugs, including the P-wave velocity V p , the S-wave velocity V s , the density ρ, the porosity φ, and the permeability κ parameters, and their expression is: Cav(H,L,D) = {V p (i),V s (i),ρ(i),φ(i),κ(i)}, i ≤ D;

[0143] Figures 8 to 11 shows the geological models of the fracture-vug reservoirs with different scales at a certain depth. Through the burial depth H, the number D of the fracture-vug bodies, the distance L between the fracture-vug bodies, and the spatial scale of the fracture-vug reservoir itself, including the vertical scale h cav and the horizontal scale d cav , by setting different combinations of fractures and vugs, the quantitative characterization of the fracture-vug reservoir and the relationship between the fractures and vugs can be found.

[0144] S4: Construct a random function.

[0145] Set a random function in space, and its expression is {rand (x,y,z) , Cav(H,L,D)}, where rand (x,y,z) is the spatial coordinate of the fracture-vug reservoir.

[0146] S5: Generate the geological model of the fracture-vug reservoir according to the random function.

[0147] Figure 12 shows the simulation results of the geological modeling of the fracture-vug reservoirs with different scales. Through the process established above, a model of the fracture-vug reservoir that conforms to the actual working area is established. This model contains different lithology parameters, different scales, and different burial depths.

[0148] S6: Characterize the morphology of the reservoir bodies and the petrophysical properties of the reservoir bodies of the fracture-vug reservoir according to the geological model.

[0149] By using the method of modeling the fracture-vug reservoir bodies, through the comparison between the geological model, the obtained seismic records and the actual seismic records, the morphology of the underground reservoir bodies and the petrophysical properties of the reservoir bodies can be effectively described, and the corresponding relationship between the model and the actual underground situation can be established.

[0150] As can be seen from the above description, the specific implementation manner of the present invention provides a method for generating a geological model based on a fractured-vuggy reservoir, including: first, generating a first formation model of a target work area according to well logging data and seismic data of the target work area, where the reservoir type of the target work area is a fractured-vuggy reservoir; then, determining lithology characterization parameters of formations other than the fractured-vuggy reservoir in the target work area according to the seismic data, and adding them to the first formation model to generate a second formation model; finally, adding a pre-generated random function to the second formation model to generate a geological model of the target work area, where the random function is used to characterize the space and lithology of the fractured-vuggy reservoir.

[0151] The method for generating a geological model based on a fractured-vuggy reservoir provided by the present invention includes: constructing a background formation model framework, constructing formation rock physical parameters, constructing the buried depth, scale, and quantity of fractures and vugs, and constructing the rock physical parameters of fractures and vugs. The modeling method proposed by the present invention can perform modeling on fractured-vuggy reservoirs of different scales, effectively improving the modeling accuracy of fractured-vuggy reservoirs and the characterization accuracy of fractured-vuggy reservoirs.

[0152] Example 4:

[0153] Based on the same inventive concept, the embodiments of the present application also provide a device for generating a geological model based on a fractured-vuggy reservoir, which can be used to implement the method described in the above embodiments, as shown in the following embodiments. Since the principle of the device for generating a geological model based on a fractured-vuggy reservoir to solve problems is similar to that of the method for generating a geological model based on a fractured-vuggy reservoir, the implementation of the device for generating a geological model based on a fractured-vuggy reservoir can refer to the implementation of the method for generating a geological model based on a fractured-vuggy reservoir, and the repeated parts will not be described again. As used below, the term "unit" or "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the systems described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0154] The embodiments of the present invention provide a specific implementation manner of a device for generating a geological model based on a fractured-vuggy reservoir that can implement the method for generating a geological model based on a fractured-vuggy reservoir. Refer to Figure 13 , a device for generating a geological model based on a fractured-vuggy reservoir includes:

[0155] A first formation model generation module 10, configured to generate the first formation model of the target work area according to well logging data and seismic data of the target work area, where the reservoir type of the target work area is a fractured-vuggy reservoir;

[0156] A second formation model generation module 20, configured to determine lithology characterization parameters of formations other than the fractured-vuggy reservoir in the target work area according to the seismic data, and add them to the first formation model to generate a second formation model;

[0157] The geological model generation module 30 is configured to add a pre-generated random function to the second formation model to generate a geological model of the target work area, wherein the random function is used to characterize the space and lithology of the fracture-vuggy reservoir.

[0158] In an embodiment of the present invention, the first formation model generation module includes:

[0159] A reflection interface determination unit, configured to determine a reflection interface and seismic facies of the target work area according to the seismic data;

[0160] A primary division result generation unit, configured to perform a primary division on the formation of the target work area according to the reflection interface and the seismic facies to generate a primary division result;

[0161] A first formation model generation unit, configured to perform a secondary division on the primary division result according to the lithology logging curve of the target work area to generate a first formation model.

[0162] In an embodiment of the present invention, the lithology logging curve includes a well diameter logging curve, a spontaneous potential logging curve, and a natural gamma logging curve.

[0163] In an embodiment of the present invention, a geological model generation device based on a fracture-vuggy reservoir further includes:

[0164] A random function generation module, configured to generate the random function, and the random function generation module includes:

[0165] A space characterization parameter establishment unit, configured to establish space characterization parameters of the fracture-vuggy reservoir according to the burial depth of the fracture-vuggy reservoir, the number of fracture-vuggy bodies, the distance between multiple fracture-vuggy bodies, and the space scale parameters of the fracture-vuggy reservoir;

[0166] A lithology characterization parameter establishment unit, configured to establish lithology characterization parameters of the fracture-vuggy reservoir according to the lithology parameters of the fracture-vuggy body;

[0167] A random function generation unit, configured to generate the random function according to the space characterization parameters, the lithology characterization parameters, and the initial function of the random function.

[0168] In an embodiment of the present invention, the space scale parameters include a longitudinal scale parameter and a transverse scale parameter;

[0169] The lithology parameters of the fracture-vuggy body include longitudinal wave velocity, transverse wave velocity, and density.

[0170] In an embodiment of the present invention, the initial function is a normal distribution random function.

[0171] In an embodiment of the present invention, the lithology characterization parameters of the formation in the target work area except for the fracture-vuggy reservoir include P-wave velocity, S-wave velocity, and density;

[0172] The lithology parameters of the fracture-vug body further include porosity and permeability.

[0173] As can be seen from the above description, an embodiment of the present invention provides a geological model generation device based on a fracture-vuggy reservoir, including: a first formation model generation module, configured to generate a first formation model of the target work area according to the logging data and seismic data of the target work area, where the reservoir type of the target work area is a fracture-vuggy reservoir; a second formation model generation module, configured to determine the lithology characterization parameters of the formation in the target work area except for the fracture-vuggy reservoir according to the seismic data, and add them to the first formation model to generate a second formation model; a geological model generation module, configured to add a pre-generated random function to the second formation model to generate a geological model of the target work area, where the random function is used to characterize the space and lithology of the fracture-vuggy reservoir.

[0174] Due to the variable scale of the fracture-vug reservoir body, the connection relationship between holes is unclear, and it is difficult to image the reservoir body, making it difficult to accurately depict the scale of the reservoir body. The present invention uses the method of fracture-vug reservoir body modeling. By comparing the obtained seismic records with the actual seismic records, it can effectively describe the morphology of the underground reservoir body and the petrophysical properties of the reservoir body, and establish the corresponding relationship between the model and the actual underground situation. Aiming at the problem of difficult modeling of the fracture-vug reservoir body, the geological modeling method proposed by the present invention can model fracture-vug reservoir bodies of different scales, effectively improving the modeling accuracy of the fracture-vuggy reservoir and the characterization accuracy of the fracture-vug reservoir body.

[0175] Embodiment Five:

[0176] An embodiment of the present application also provides a specific implementation manner of an electronic device capable of implementing all steps in the above-mentioned geological model generation method based on a fracture-vuggy reservoir. Refer to Figure 14 ., the electronic device specifically includes the following content:

[0177] A processor 1201, a memory 1202, a communication interface 1203, and a bus 1204;

[0178] Among them, the processor 1201, the memory 1202, and the communication interface 1203 complete mutual communication through the bus 1204; the communication interface 1203 is used to implement information transmission between related devices such as server-side devices and client-side devices;

[0179] The processor 1201 is used to call the computer program in the memory 1202. When the processor executes the computer program, all steps in the geological model generation method based on the fractured-vuggy reservoir in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0180] Generate a first formation model of the target work area according to the logging data and seismic data of the target work area, where the reservoir type of the target work area is a fractured-vuggy reservoir;

[0181] Determine the lithology characterization parameters of the formations other than the fractured-vuggy reservoir in the target work area according to the seismic data, and add them to the first formation model to generate a second formation model;

[0182] Add a pre-generated random function to the second formation model to generate the geological model of the target work area, where the random function is used to characterize the space and lithology of the fractured-vuggy reservoir.

[0183] In one embodiment, the generating the first formation model of the target work area according to the logging data and seismic data of the target work area includes:

[0184] Determine the reflection interface and seismic facies of the target work area according to the seismic data;

[0185] Perform a first division on the formations of the target work area according to the reflection interface and the seismic facies to generate a first division result;

[0186] Perform a second division on the first division result according to the lithology logging curve of the target work area to generate a first formation model.

[0187] In one embodiment, the lithology logging curve includes a caliper logging curve, a spontaneous potential logging curve, and a natural gamma logging curve.

[0188] In one embodiment, the steps of generating the random function include:

[0189] Establish the spatial characterization parameters of the fractured-vuggy reservoir according to the burial depth of the fractured-vuggy reservoir, the number of vuggy bodies, the distance between multiple vuggy bodies, and the spatial scale parameters of the fractured-vuggy reservoir;

[0190] Establish the lithology characterization parameters of the fractured-vuggy reservoir according to the lithology parameters of the vuggy bodies;

[0191] Generate the random function according to the spatial characterization parameters, the lithology characterization parameters, and the initial function of the random function.

[0192] In one embodiment, the spatial scale parameters include a longitudinal scale parameter and a transverse scale parameter;

[0193] The lithology parameters of the fracture-vug body include P-wave velocity, S-wave velocity, and density.

[0194] In one embodiment, the initial function is a normal distribution random function.

[0195] In one embodiment, the lithology characterization parameters of the formations in the target work area except the fracture-vug reservoir include P-wave velocity, S-wave velocity, and density;

[0196] The lithology parameters of the fracture-vug body further include porosity and permeability.

[0197] Embodiment Six:

[0198] An embodiment of the present application further provides a computer-readable storage medium capable of implementing all steps in the above-mentioned geological model generation method based on a fracture-vug reservoir. A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, all steps of the above-mentioned geological model generation method based on a fracture-vug reservoir are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0199] Generate a first formation model of the target work area according to the logging data and seismic data of the target work area, where the reservoir type of the target work area is a fracture-vug reservoir;

[0200] Determine the lithology characterization parameters of the formations in the target work area except the fracture-vug reservoir according to the seismic data, and add them to the first formation model to generate a second formation model;

[0201] Add a pre-generated random function to the second formation model to generate the geological model of the target work area, where the random function is used to characterize the space and lithology of the fracture-vug reservoir.

[0202] In one embodiment, the generating a first formation model of the target work area according to the logging data and seismic data of the target work area includes:

[0203] Determine the reflection interface and seismic facies of the target work area according to the seismic data;

[0204] Perform a primary division of the formations in the target work area according to the reflection interface and the seismic facies to generate a primary division result;

[0205] Perform a secondary division of the primary division result according to the lithology logging curves of the target work area to generate a first formation model.

[0206] In one embodiment, the lithology logging curves include a caliper logging curve, a spontaneous potential logging curve, and a natural gamma logging curve.

[0207] In one embodiment, the steps of generating the random function include:

[0208] Establishing the spatial characterization parameters of the fracture-vug reservoir according to the burial depth of the fracture-vug reservoir, the number of fracture-vug bodies, the distance between multiple fracture-vug bodies, and the spatial scale parameters of the fracture-vug reservoir;

[0209] Establishing the lithological characterization parameters of the fracture-vug reservoir according to the lithological parameters of the fracture-vug bodies;

[0210] Generating the random function according to the spatial characterization parameters, the lithological characterization parameters, and the initial function of the random function.

[0211] In one embodiment, the spatial scale parameters include a longitudinal scale parameter and a transverse scale parameter;

[0212] The lithological parameters of the fracture-vug bodies include the longitudinal wave velocity, the transverse wave velocity, and the density.

[0213] In one embodiment, the initial function is a normal distribution random function.

[0214] In one embodiment, the lithological characterization parameters of the formations other than the fracture-vug reservoir in the target work area include the longitudinal wave velocity, the transverse wave velocity, and the density;

[0215] The lithological parameters of the fracture-vug bodies further include the porosity and the permeability.

[0216] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the hardware + program type embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0217] The specific embodiments of this specification are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0218] Although the present application provides method operation steps such as in the embodiments or flowcharts, more or fewer operation steps may be included based on routine or non-creative labor. The order of steps listed in the embodiments is only one way among the execution orders of numerous steps and does not represent the only execution order. When the actual device or client product is executed, it may be executed in the order of the method shown in the embodiments or the drawings or executed in parallel (e.g., in an environment of parallel processors or multi-threaded processing).

[0219] For convenience of description, when describing the above device, it is divided into various modules according to functions and described separately. Of course, when implementing the embodiments of this specification, the functions of each module can be implemented in the same or multiple software and / or hardware, or the modules implementing the same function can be realized by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms.

[0220] Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, the method steps can be logically programmed to enable the controller to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. to achieve the same function. Therefore, such a controller can be regarded as a hardware component, and the devices included therein for implementing various functions can also be regarded as the structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and the structures within the hardware component.

[0221] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0222] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0223] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and reference can be made to the corresponding parts of the method embodiments for relevant details. In the description of this specification, the description of reference terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of this specification. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0224] The above description is only for the embodiments of this specification and does not limit the embodiments of this specification. For those skilled in the art, various changes and modifications can be made to the embodiments of this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of this specification shall be included within the scope of the claims of the embodiments of this specification.

Claims

1. A method for generating a geological model based on a fractured-vuggy reservoir, characterized in that, it includes: generating a first stratigraphic model of the target work area according to the logging data and seismic data of the target work area, where the reservoir type of the target work area is a fractured-vuggy reservoir; determining the lithology characterization parameters of the strata in the target work area except the fractured-vuggy reservoir according to the seismic data, and adding them to the first stratigraphic model to generate a second stratigraphic model; adding a pre-generated random function to the second stratigraphic model to generate the geological model of the target work area, where the random function is used to characterize the space and lithology of the fractured-vuggy reservoir.

2. The geological model generation method according to claim 1, characterized in that, the generating the first stratigraphic model of the target work area according to the logging data and seismic data of the target work area includes: determining the reflection interface and seismic facies of the target work area according to the seismic data; performing a primary division on the strata of the target work area according to the reflection interface and the seismic facies to generate a primary division result; performing a secondary division on the primary division result according to the lithology logging curve of the target work area to generate a first stratigraphic model.

3. The geological model generation method according to claim 2, characterized in that, the lithology logging curve includes a borehole diameter logging curve, a spontaneous potential logging curve, and a natural gamma logging curve.

4. The geological model generation method according to any one of claims 1 to 3, characterized in that, the steps of generating the random function include: establishing the spatial characterization parameters of the fractured-vuggy reservoir according to the burial depth of the fractured-vuggy reservoir, the number of fracture-vug bodies, the distance between multiple fracture-vug bodies, and the spatial scale parameters of the fractured-vuggy reservoir; establishing the lithology characterization parameters of the fractured-vuggy reservoir according to the lithology parameters of the fracture-vug body; generating the random function according to the spatial characterization parameters, the lithology characterization parameters, and the initial function of the random function.

5. The geological model generation method according to claim 4, characterized in that, the spatial scale parameters include a longitudinal scale parameter and a transverse scale parameter; the lithology parameters of the fracture-vug body include longitudinal wave velocity, transverse wave velocity, and density.

6. The geological model generation method according to claim 5, characterized in that, the initial function is a normal distribution random function.

7. The geological model generation method according to claim 5, characterized in that, the lithology characterization parameters of the strata in the target work area except the fractured-vuggy reservoir include longitudinal wave velocity, transverse wave velocity, and density; the lithology parameters of the fracture-vug body further include porosity and permeability.

8. A device for generating a geological model based on a fractured-vuggy reservoir, characterized in that, it includes: a first stratigraphic model generation module for generating the first stratigraphic model of the target work area according to the logging data and seismic data of the target work area, where the reservoir type of the target work area is a fractured-vuggy reservoir; The second formation model generation module is configured to determine the lithology characterization parameters of the formations in the target work area except for the fracture-vuggy reservoir based on the seismic data, and add them to the first formation model to generate a second formation model; The geological model generation module is configured to add a pre-generated random function to the second formation model to generate the geological model of the target work area, wherein the random function is used to characterize the space and lithology of the fracture-vuggy reservoir.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, when the processor executes the program, the steps of a method for generating a geological model based on a fracture-vuggy reservoir according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, on which a computer program is stored, wherein, when the computer program is executed by a processor, the steps of a method for generating a geological model based on a fracture-vuggy reservoir according to any one of claims 1 to 7 are implemented.

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