Single well passing profile simulation method and device, computer equipment and storage medium

Abstract

The invention provides a single well passing profile simulation method and device, computer equipment and a storage medium. The method comprises the steps that an actual single well passing profile is obtained; the fracture characteristics of the actual single well passing section are measured; performing structural description on a fracture system of the actual single-well cross-section by utilizing fracture characteristics of the actual single-well cross-section, and constructing a geologic model; acquiring actual logging information, and analyzing the actual logging information to obtain physical parameters; based on the geologic model, constructing an initial single well forward modeling model; assigning a value to the preliminary single well forward model by using the physical parameters to obtain a corrected single well forward model; performing convolution forward modeling on the corrected single well forward modeling model to obtain a single well forward modeling model after convolution forward modeling; and performing single well forward modeling by using the single well forward modeling model after convolution forward modeling to obtain a simulated single well passing section. According to the method, the accuracy of simulating the single well passing profile can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic data interpretation, and in particular to a single well cross-well profile simulation method, device, computer equipment and storage medium. Background Art

[0002] Carbonate reservoirs are a common type of oil and gas reservoirs, among which fracture-cavity reservoirs are the best. This is because fracture-cavity reservoirs have large storage spaces and the cracks provide good permeation channels, allowing oil and gas to accumulate and be mined. In other words, carbonate fracture-cavity reservoirs are high-yield well reservoirs.

[0003] Compared with other types of reservoirs, the structure of carbonate fracture-cavity reservoirs is more complex, which is due to the diversity of carbonate rock composition and structure, as well as the complex distribution and morphology of fractures and caves in fracture-cavity reservoirs.

[0004] These characteristics make the storage and permeability properties of fracture-vuggy reservoirs very unstable, which brings great difficulties to the extraction of oil and natural gas.

[0005] The identification and evaluation of high-yield well reservoirs is an important petroleum geological and geophysical technology, which mainly involves the detailed description and prediction of underground reservoirs to determine the location and reserves of high-yield wells. Therefore, the identification and evaluation of high-yield well reservoirs is one of the important means to study carbonate fracture-cavity reservoirs.

[0006] When identifying and evaluating reservoirs in high-yield wells, the single-well forward modeling method can be used as a tool to help understand and study the characteristics of reservoirs.

[0007] The process of studying carbonate fracture-vuggy reservoirs using the single-well forward modeling method usually includes the following steps:

[0008] 1. Collect data: First, it is necessary to collect relevant data on carbonate fracture-vuggy reservoirs, including geological, geophysical, drilling and production history data.

[0009] 2. Establish a mathematical model: Based on the collected data, a mathematical model of carbonate fracture-cavity reservoirs is established using single-well forward simulation. This model should be able to simulate the physical processes and seismic wave propagation in the formation in order to predict the seismic profile and geophysical response in the formation.

[0010] 3. Simulate seismic profile: The established mathematical model can be used to simulate the propagation of seismic waves in the strata, thereby generating seismic profiles. The seismic profiles need to be able to reflect the characteristics and distribution of carbonate fracture-cavity reservoirs.

[0011] 4. Simplify the geological model: Based on the single well cross-well profile generated by simulation, simplify the geological model, that is, optimize the geological model to improve the knowledge and understanding of reservoir characteristics and distribution.

[0012] 5. Parameter assignment and model establishment: Based on the simplified geological model, observe the general characteristics of the single well cross-section by naked eye, and establish a single well forward model based on empirical parameter assignment. This single well forward model needs to be able to reflect the actual situation of carbonate fracture-vuggy reservoirs and can be used for capacity prediction and development plan design.

[0013] From step 5 of the above research process, it can be seen that the process of studying carbonate fracture-vuggy reservoirs using single-well forward modeling has the following problems:

[0014] The general characteristics of the seismic profile are obtained through visual observation and are assigned according to empirical parameters. The human interference factor is strong, which makes the accuracy of the single-well forward model low. The single-well forward model can obtain the single-well cross-well profile through single-well forward simulation. Due to the low accuracy of the single-well forward model itself, the accuracy of the simulated single-well cross-well profile is also low. In other words, it is very difficult to achieve accurate simulation of the single-well cross-well profile. Summary of the invention

[0015] Based on this, it is necessary to provide a single well cross-well profile simulation method, device, computer equipment and storage medium to address the above technical problems.

[0016] A single well cross-well profile simulation method, comprising:

[0017] Obtain the actual single well cross-well profile;

[0018] Measuring the fracture characteristics of the actual single well cross-well profile;

[0019] Using the fracture characteristics of the actual single well cross-section, structurally characterize the fracture system of the actual single well cross-section and construct a geological model;

[0020] Acquiring actual well logging data, and analyzing the actual well logging data to obtain physical parameters;

[0021] Based on the geological model, a preliminary single-well forward model is constructed;

[0022] Assigning values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model;

[0023] Performing convolution forward modeling on the modified single-well forward model to obtain a single-well forward model after convolution forward modeling;

[0024] The single well forward model after the convolution forward modeling is used to perform single well forward simulation to obtain a simulated single well cross-well profile.

[0025] In one embodiment, after the step of performing single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile, the method includes:

[0026] The actual single well crossing profile is used to iteratively optimize the simulated single well crossing profile to obtain an optimized simulated single well crossing profile.

[0027] In one embodiment, the step of performing convolution forward modeling on the modified single well forward model to obtain the single well forward model after convolution forward modeling comprises:

[0028] In the process of performing self-excitation and self-collection convolution forward modeling on the modified single-well forward model, the actual single-well cross-well profile is used to optimize the modified single-well forward model to obtain the single-well forward model after the convolution forward modeling.

[0029] In one embodiment, the step of performing single well forward simulation using the single well forward model after convolution forward modeling to obtain a simulated single well cross-well profile comprises:

[0030] Using the single well forward model after the convolution forward modeling, shot gather data and velocity volume data are obtained;

[0031] The velocity volume data and the shot gather data are used to perform migration imaging, and a simulated single well cross-well profile is obtained through migration imaging.

[0032] In one embodiment, the step of obtaining shot gather data and velocity volume data using the single well forward model after convolution forward modeling comprises:

[0033] Obtain observation data;

[0034] Get the wave equation;

[0035] Based on the single well forward model after the convolution forward modeling and the wave equation, the shot gather data is obtained by using the observation data;

[0036] The velocity volume data is derived using the single well forward model after the convolution forward modeling.

[0037] In one embodiment, the wave equation is calculated as follows:

[0038]

[0039]

[0040]

[0041] Among them, U=U(x, z, t), U is the sound pressure, V is the propagation speed of sound waves in the medium, ρ is the density, and s(x, z, t) is the source function.

[0042] A single well cross-well profile simulation device, comprising:

[0043] A profile acquisition module is used to obtain the actual single well cross-well profile;

[0044] A fracture feature measurement module, used to measure the fracture features of the actual single well cross-well profile;

[0045] A geological model building module is used to structurally characterize the fracture system of the actual single well cross-section by utilizing the fracture characteristics of the actual single well cross-section and to build a geological model;

[0046] A physical parameter acquisition module is used to acquire actual well logging data and analyze the actual well logging data to obtain physical parameters;

[0047] A preliminary single-well forward model building module is used to build a preliminary single-well forward model based on the geological model;

[0048] An assignment module, used for assigning values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model;

[0049] A convolution forward modeling module is used to perform convolution forward modeling on the modified single well forward model to obtain a single well forward model after convolution forward modeling;

[0050] The profile simulation module is used to perform single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile.

[0051] In one embodiment, the single well cross-well profile simulation device further comprises:

[0052] The simulation profile optimization module is used to iteratively optimize the simulated single well cross-well profile using the actual single well cross-well profile to obtain an optimized simulated single well cross-well profile.

[0053] In one embodiment, the convolution forward modeling module includes:

[0054] The self-excited and self-collected convolution forward modeling unit is used to optimize the modified single-well forward model using the actual single-well cross-well profile during the process of performing self-excited and self-collected convolution forward modeling on the modified single-well forward model to obtain the single-well forward model after the convolution forward modeling.

[0055] In one embodiment, the profile simulation module includes:

[0056] A data acquisition unit, used for obtaining shot gather data and velocity volume data by using the single well forward model after the convolution forward modeling;

[0057] The profile simulation unit is used to perform migration imaging using the velocity volume data and the shot gather data, and obtain a simulated single well cross-well profile through migration imaging.

[0058] In one embodiment, the data acquisition unit includes:

[0059] An observation data acquisition subunit, used for acquiring observation data;

[0060] A wave equation acquisition subunit is used to acquire the wave equation;

[0061] A shot gather operation subunit, for obtaining the shot gather data by using the observation data based on the single well forward model after the convolution forward modeling and the wave equation;

[0062] The velocity volume data export subunit is used to export the velocity volume data using the single well forward model after the convolution forward modeling.

[0063] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the following steps when executing the computer program:

[0064] Obtain the actual single well cross-well profile;

[0065] Measuring the fracture characteristics of the actual single well cross-well profile;

[0066] Using the fracture characteristics of the actual single well cross-section, structurally characterize the fracture system of the actual single well cross-section and construct a geological model;

[0067] Acquiring actual well logging data, and analyzing the actual well logging data to obtain physical parameters;

[0068] Based on the geological model, a preliminary single-well forward model is constructed;

[0069] Assigning values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model;

[0070] Performing convolution forward modeling on the modified single-well forward model to obtain a single-well forward model after convolution forward modeling;

[0071] The single well forward model after the convolution forward modeling is used to perform single well forward simulation to obtain a simulated single well cross-well profile.

[0072] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0073] Obtain the actual single well cross-well profile;

[0074] Measuring the fracture characteristics of the actual single well cross-well profile;

[0075] Using the fracture characteristics of the actual single well cross-section, structurally characterize the fracture system of the actual single well cross-section and construct a geological model;

[0076] Acquiring actual well logging data, and analyzing the actual well logging data to obtain physical parameters;

[0077] Based on the geological model, a preliminary single-well forward model is constructed;

[0078] Assigning values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model;

[0079] Performing convolution forward modeling on the modified single-well forward model to obtain a single-well forward model after convolution forward modeling;

[0080] The single well forward model after the convolution forward modeling is used to perform single well forward simulation to obtain a simulated single well cross-well profile.

[0081] In the above-mentioned single-well cross-well profile simulation method, the fracture characteristics of the actual single-well cross-well profile are measured, that is, the fracture characteristics of the actual single-well cross-well profile are obtained based on objective data, so that the accuracy of the geological model is improved. Similarly, the physical parameters are obtained based on actual logging data, that is, the physical parameters are also obtained based on objective data. It not only avoids the traditional method of using the naked eye to observe the general characteristics of the seismic profile, which makes the human interference factor strong and causes the subsequent single-well forward model to have low accuracy, but also avoids the traditional method of using empirical parameter assignment, which makes the human interference factor strong and causes the subsequent single-well forward model to have low accuracy. The accuracy of the modified single-well forward model obtained after the physical parameter assignment is improved, and the convolution forward modeling optimizes the modified single-well forward model, so that the accuracy of the single-well forward model after the convolution forward modeling is improved.

[0082] Since the accuracy of the single well forward model after convolution forward modeling is improved, the accuracy of the simulated single well cross-well profile simulated by the single well forward model after convolution forward modeling is improved, that is, the accurate simulation of the actual single well cross-well profile is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 A schematic diagram of a flow chart of a single well cross-well profile simulation method according to an embodiment;

[0084] Figure 2 A schematic flow chart of a single-well forward modeling method for carbonate fracture-cavity reservoirs based on a palisade structure according to another embodiment;

[0085] Figure 3 for Figure 2 The geological model constructed by the single-well forward modeling method of carbonate fracture-cavity reservoir based on palisade structure is shown;

[0086] Figure 4 for Figure 2 The preliminary single-well forward model is constructed by the single-well forward modeling method of carbonate fracture-cavity reservoir based on palisade structure;

[0087] Figure 5 for Figure 2 The simulated single well cross-well profile simulated by the single well forward modeling method of carbonate fracture-cavity reservoir based on palisade structure is shown;

[0088] Figure 6 for Figure 2 A schematic flow chart of innovative forward modeling steps in a single-well forward modeling method for carbonate fracture-vuggy reservoirs based on a palisade structure is shown;

[0089] Figure 7 It is the actual single well cross-well profile;

[0090] Figure 8 for Figure 2 The simulated single well cross-well profile after multiple iterations of the single well forward modeling method for carbonate fracture-cavity reservoirs based on the palisade structure is shown;

[0091] Fig. 9 It is a structural block diagram of a single well cross-well profile simulation device according to an embodiment;

[0092] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0093] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0094] Embodiment 1

[0095] In this embodiment, Figure 1 As shown, a single well cross-well profile simulation method is provided, which includes:

[0096] Step 100, obtaining an actual single well cross-well profile.

[0097] In this embodiment, the actual single well cross-well profile is constructed through the characteristics and parameters of the formation structure. In this embodiment, the formation structure includes but is not limited to carbonate fracture-cavity reservoirs, sandstone reservoirs, limestone reservoirs, volcanic rock reservoirs, reef reservoirs and tight sandstone reservoirs. In this embodiment, the structure of carbonate fracture-cavity reservoirs includes but is not limited to palisade structures, mass structures and composite structures.

[0098] Step 200, measuring the fracture characteristics of the actual single well cross-well profile.

[0099] In this embodiment, the fracture characteristics of the actual single well cross-well profile are obtained through measurement, that is, the fracture characteristics of the actual single well cross-well profile are objective data obtained by measurement, avoiding the problem of serious interference from human factors caused by the traditional practice of obtaining the approximate characteristics of the actual single well cross-well profile through naked eye observation.

[0100] Step 300, using the fracture characteristics of the actual single well cross-section, structurally characterize the fracture system of the actual single well cross-section and construct a geological model.

[0101] In this way, the fracture characteristics of the actual single well cross-section can be used to construct a geological model that conforms to the actual single well cross-section. The fracture characteristics of the actual single well cross-section are obtained by measurement in step 200, which avoids the problem of serious interference from human factors caused by the traditional practice of obtaining the approximate characteristics of the actual single well cross-section by naked eye observation, thereby improving the accuracy of the geological model constructed using the fracture characteristics of the actual single well cross-section. In this embodiment, when the single well cross-section simulation method is applied to a carbonate fracture-cavity reservoir with a palisade structure, a model that conforms to the geological conditions is established based on the palisade structure characteristics of the carbonate fracture-cavity reservoir.

[0102] Step 400, obtaining actual well logging data, and analyzing the actual well logging data to obtain physical parameters.

[0103] In this embodiment, the physical parameters are obtained by analyzing the actual logging data, that is, the physical parameters are obtained based on objective data, which avoids the problem that the traditional practice of using empirical parameter assignment causes strong human interference factors and causes low accuracy of the subsequent single well forward model, so that the accuracy of the modified single well forward model obtained after the physical parameter assignment is improved. In this embodiment, the actual logging data includes actual acoustic time difference logging data and actual density logging curves.

[0104] Step 500: construct a preliminary single-well forward model based on the geological model.

[0105] In this embodiment, since the geological model is obtained by structurally characterizing the fracture system of the actual single well cross-section using the fracture characteristics of the actual single well cross-section in step 300, that is, the geological model is obtained based on objective data, the accuracy of the preliminary single well forward model constructed by the geological model is improved.

[0106] Step 600, using the physical parameters to assign values ​​to the preliminary single-well forward model to obtain a revised single-well forward model.

[0107] In this embodiment, the actual logging data gives the preliminary single-well forward model accurate physical parameters, which effectively improves the accuracy of the preliminary single-well forward model, that is, improves the accuracy of the obtained revised single-well forward model.

[0108] Step 700, performing convolution forward modeling on the modified single-well forward model to obtain a single-well forward model after convolution forward modeling.

[0109] In this embodiment, the modified single-well forward model is subjected to convolution forward modeling to obtain the single-well forward model after convolution forward modeling. Convolution forward modeling is a quality control process for the modified single-well forward model. The quality control process is advanced to avoid simple errors caused by the low accuracy of the modified single-well forward model, which leads to inaccurate results of the subsequent simulated single-well cross-well profile. Not only the accuracy of the simulated single-well cross-well profile is improved, but also the process is simplified by reducing the optimization steps returned to the modified single-well forward model. In this embodiment, the modified single-well forward model can be corrected after convolution forward modeling, that is, the accuracy of the single-well forward model after convolution forward modeling is improved. In this embodiment, the modified single-well forward model is modified by the advance quality control of the self-excited and self-collected convolution forward modeling.

[0110] Step 800, performing single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile.

[0111] In this embodiment, since the accuracy of the single-well forward model after the convolution forward modeling obtained in step 700 is improved, the accuracy of the simulated single-well cross-well profile obtained by simulating the single-well forward model after the convolution forward modeling is improved, that is to say, the simulated single-well cross-well profile is accurately simulated to the actual single-well cross-well profile.

[0112] In the above-mentioned single-well cross-well profile simulation method, the fracture characteristics of the actual single-well cross-well profile are measured, that is, the fracture characteristics of the actual single-well cross-well profile are obtained based on objective data, so that the accuracy of the geological model is improved. Similarly, the physical parameters are obtained based on actual logging data, that is, the physical parameters are also obtained based on objective data. It not only avoids the traditional method of using the naked eye to observe the general characteristics of the seismic profile, which makes the human interference factor strong and causes the subsequent single-well forward model to have low accuracy, but also avoids the traditional method of using empirical parameter assignment, which makes the human interference factor strong and causes the subsequent single-well forward model to have low accuracy. The accuracy of the modified single-well forward model obtained after the physical parameter assignment is improved, and the convolution forward modeling optimizes the modified single-well forward model, so that the accuracy of the single-well forward model after the convolution forward modeling is improved.

[0113] Since the accuracy of the single well forward model after convolution forward modeling is improved, the accuracy of the simulated single well cross-well profile simulated by the single well forward model after convolution forward modeling is improved, that is, the accurate simulation of the actual single well cross-well profile is achieved.

[0114] In one embodiment, after the step of performing single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile, the method includes:

[0115] The actual single well crossing profile is used to iteratively optimize the simulated single well crossing profile to obtain an optimized simulated single well crossing profile.

[0116] In this embodiment, the imaging effect of the simulated single well cross-section is quality controlled by using the characteristics of the actual single well cross-section. The basis is the imaging effect of the simulated single well cross-section, that is, the similarity between the simulated single well cross-section and the actual single well cross-section. If the imaging effect of the simulated single well cross-section does not meet expectations, return to step 700 and iterate to this step again until a simulated single well cross-section that accurately simulates the actual single well cross-section is obtained. In this embodiment, the forward modeling results are quality controlled, and multiple iterations are performed to obtain ideal forward modeling results with high similarity. In this embodiment, the optimized simulated single well cross-section is the simulated single well cross-section after multiple iterations.

[0117] In one embodiment, the step of performing convolution forward modeling on the modified single well forward model to obtain the single well forward model after convolution forward modeling comprises:

[0118] In the process of performing self-excitation and self-collection convolution forward modeling on the modified single-well forward model, the actual single-well cross-well profile is used to optimize the modified single-well forward model to obtain the single-well forward model after the convolution forward modeling.

[0119] In this embodiment, self-excited and self-collected convolution forward modeling is adopted. Compared with conventional convolution forward modeling, the advantage of self-excited and self-collected convolution forward modeling is that it can automatically generate seismic wave signals, avoiding the tedious process of manually designing seismic wave signals, and at the same time can better simulate the actual seismic wave propagation situation. In addition, self-excited and self-collected convolution forward modeling can perform single-well forward modeling simulation without using actual seismic data, that is, generating a single well cross-well profile and seismic response, and has a higher degree of automation. In addition, self-excited and self-collected convolution forward modeling can also improve the accuracy and reliability of the modified single-well forward model through multiple iterations and optimizations, so that the accuracy of the single-well forward model after the convolution forward modeling is improved.

[0120] In one embodiment, the step of performing single well forward simulation using the single well forward model after convolution forward modeling to obtain a simulated single well cross-well profile comprises:

[0121] Using the single well forward model after the convolution forward modeling, shot gather data and velocity volume data are obtained;

[0122] The velocity volume data and the shot gather data are used to perform migration imaging, and a simulated single well cross-well profile is obtained through migration imaging.

[0123] In this embodiment, since the accuracy of the single well forward model after convolution forward modeling obtained in step 700 is improved, the accuracy of the shot data and velocity volume data obtained from the single well forward model after convolution forward modeling is improved, and the accuracy of the single well cross-well profile simulated by offset imaging using the velocity volume data and the shot data is improved. In the process of performing single well forward simulation using the single well forward model after convolution forward modeling to obtain a simulated single well cross-well profile, the simulated single well cross-well profile is offset imaged by the velocity volume data and the shot data to iteratively optimize the single well forward model after convolution forward modeling to obtain an optimized single well forward model and the simulated single well cross-well profile simulated based on the optimized single well forward modeling. The simulated single well cross-well profile is made close to the actual single well cross-well profile by offset imaging of the simulated single well cross-well profile by the velocity volume data and the shot data, and the single well forward model after convolution forward modeling is optimized accordingly.

[0124] In one embodiment, the steps of performing migration imaging using the velocity volume data and the shot gather data and obtaining a simulated single well cross-well profile through migration imaging include:

[0125] Get Paradigm;

[0126] Get Kirchhoff;

[0127] Paradigm is used to perform Kirchhoff migration imaging on the shot gather data and velocity volume data to iteratively optimize the single well forward model after the convolution forward modeling to obtain an optimized single well forward model and the simulated single well cross-well profile simulated based on the optimized single well forward model.

[0128] In this embodiment, Paradigm is software with a migration imaging function. In this embodiment, Kirchhoff is an equation. Kirchhoff migration imaging is a seismic data processing method based on the Helmholtz-Hodge principle. It uses the propagation path of seismic waves underground and the location information of reflection points to redistribute the coherent energy in the seismic record to its true position, thereby realizing the imaging of underground structures. This method synthesizes the data of each receiving point in the seismic record to obtain the seismic record at each position, thereby better reflecting the situation of the underground structure.

[0129] In one embodiment, before the step of obtaining shot gather data and velocity volume data using the single well forward model after the convolution forward modeling, the step includes:

[0130] Get the Unified Grid program;

[0131] The shot gather data and the velocity volume data are assigned grids of the same size through a unified grid procedure.

[0132] In this embodiment, by assigning the calculated shot gather and the derived velocity volume data to a grid of the same size, a more accurate seismic wave field simulation and seismic response calculation can be performed. The shot gather data and velocity volume data grids are unified, and the forward modeling result is obtained by migration imaging. The forward modeling result is a simulated single well cross-well profile. In this embodiment, the unified grid program includes Omega.

[0133] In one embodiment, the step of obtaining shot gather data and velocity volume data using the single well forward model after convolution forward modeling comprises:

[0134] Obtain observation data;

[0135] Get the wave equation;

[0136] Based on the single well forward model after the convolution forward modeling and the wave equation, the shot gather data is obtained by using the observation data;

[0137] The velocity volume data is derived using the single well forward model after the convolution forward modeling.

[0138] In this embodiment, the shot gather data is obtained by shot gather calculation based on the wave equation, that is, the shot gather data is obtained based on objective conditions, which avoids the problem of inaccurate shot gather data caused by interference from human factors, ensures the accuracy of the shot gather data, and then improves the accuracy of the simulated single well cross-well profile obtained by subsequent simulation using the shot gather data. In this embodiment, the observation data is the actual engineering construction parameters, and the observation system is constructed based on the actual engineering construction parameters. The observation system includes a geophysical exploration system, a geochemical exploration system, a geological remote sensing system, and underground engineering and drilling engineering, wherein the geophysical exploration system studies the geological structure by studying the physical properties of the rock layer, such as magnetism, conductivity, density, etc., the geochemical exploration system studies the geological structure by studying the distribution and migration laws of elements in the crust, the geological remote sensing system uses satellite or aerial remote sensing technology to obtain geological information, such as remote sensing images, digital elevation models, etc., to assist geological surveys and mineral resource exploration, and the underground engineering and drilling engineering obtains underground rock samples through underground engineering or drilling engineering to study the geological structure and mineral distribution in the crust. In other words, the observation system is constructed based on accurate actual engineering construction parameters, which improves the accuracy of the shot gather data obtained using the observation system, and improves the accuracy of the simulated single well cross-well profile obtained by subsequent offset imaging using the shot gather data and velocity volume data.

[0139] In one embodiment, based on the single well forward model after the convolution forward modeling and the wave equation, the step of obtaining the shot gather data using the observation data includes:

[0140] Obtaining seismic wave field characteristics through the wave equation;

[0141] Get the graphics processing program;

[0142] The shot gather data is obtained by performing calculations on the seismic wave field characteristics using the observation data and the graphics processing program.

[0143] In this embodiment, the operation is a shot gather operation. In this embodiment, the graphics processing program is set on a graphics processor, and the graphics processor is a GPU, and the GPU is used to accelerate the operation of the shot gather operation. In this embodiment, the innovative forward modeling process based on GPU accelerated operation is used to obtain the shot gather data, that is, the efficiency of the shot gather operation is improved by the GPU. In this embodiment, the observation system is constructed using the observation data, and the observation system is used to perform operations on the seismic wave field characteristics to obtain the shot gather data.

[0144] In one embodiment, the wave equation is calculated as follows:

[0145]

[0146]

[0147]

[0148] Among them, U=U(x, z, t), U is the sound pressure, V is the propagation speed of sound waves in the medium, ρ is the density, and s(x, z, t) is the source function.

[0149] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0150] Embodiment 2

[0151] In this embodiment, a single well forward modeling method for carbonate fracture-vuggy reservoir based on a palisade structure is provided, which includes:

[0152] Select the depth domain seismic data through-well profile of the target to be studied, that is, the actual single well through-well profile, and establish a geological model that conforms to the geological characteristics based on the grid structure; calculate the physical parameters of each geological body based on the actual logging data and assign values ​​to the geological model; design the seismic acquisition observation system based on the actual acquisition parameters, and the actual acquisition parameters described in this embodiment are the observation data in the above embodiment; use the geological model and the observation data to obtain a preliminary single well forward model, and obtain preliminary results through the self-excited and self-collected convolution forward modeling to perform quality control on the preliminary single well forward model in advance; establish a unified grid through Omega for the shot data and velocity body data obtained based on GPU accelerated computing, and use Paradigm to use the Kirchhoff equation to perform prestack depth migration. The migration imaging in the above embodiment includes the prestack depth migration described in this embodiment to obtain imaging results, and the imaging results described in this embodiment are the simulated single well through-well profile in the above embodiment. Perform quality control on the imaging results, and obtain the final forward simulation results through multiple iterations. The final forward simulation results described in this embodiment are the simulated single well through-well profile in the above embodiment. After multiple iterations, the optimized single-well forward model is obtained.

[0153] In this embodiment, the single well forward modeling method is applied to the construction of an optimized single well forward model and the construction of a simulated single well cross-well profile. This method establishes a set of reasonable and standardized single well forward modeling methods, which has good application prospects.

[0154] Embodiment 3

[0155] In this embodiment, another embodiment of a single well forward simulation method for carbonate fracture-vuggy reservoir based on a palisade structure is provided, which includes:

[0156] 1) Establish a geological model that conforms to the geological conditions based on the palisade structure characteristics of carbonate fracture-vuggy reservoirs;

[0157] 2) Using actual well logging data and engineering parameters to assign accurate physical parameters to the geological model and establish an observation system. The engineering parameters described in this embodiment are the observation data in the above embodiment;

[0158] 3) Based on the above steps, a preliminary single-well forward model of a palisade structure is established. The preliminary single-well forward model of a palisade structure described in this embodiment is the preliminary single-well forward model in the above embodiment;

[0159] 4) Through the self-excitation and self-collection convolution forward modeling advance quality control, the preliminary single-well forward model of the grid structure is modified to obtain a revised single-well forward model;

[0160] 5) Use an innovative forward modeling process based on GPU accelerated computing to obtain shot gather data;

[0161] 6) Unifying the shot gather data and velocity volume data grids, and performing migration imaging to obtain forward modeling results. The forward modeling results described in this embodiment are the simulated single well cross-well profile in the above embodiment;

[0162] 7) Performing quality control on the forward modeling results, and obtaining an ideal forward modeling result with high similarity through multiple iterations. The ideal forward modeling result described in this embodiment is the optimized single well cross-well profile described in the above embodiment.

[0163] The innovation of the present invention is that the grid structure is used for the single well model forward modeling for the first time. The single well model forward modeling described in this embodiment is the single well forward modeling simulation in the above embodiment, which lays the foundation for subsequent research. In order to solve the problems of low consistency between the single well forward modeling simulation results and the actual single well cross-well profile in actual production, and complex and lengthy forward modeling processes, the present invention improves the accuracy and work efficiency of the single well model forward modeling by using the grid structure for the establishment of the single well forward model, early quality control of the convolution forward modeling, and efficient calculation of the shot collection based on GPU acceleration, etc., laying the foundation for the detailed study of the reservoir.

[0164] A single-well forward model was established using a grid structure to conduct single-well forward simulation of high-yield single wells. A standardized and efficient workflow for single-well forward simulation was proposed, which improved the accuracy and work efficiency of single-well forward simulation results.

[0165] Embodiment 4

[0166] In this embodiment, Figure 2 As shown, a single well forward modeling method for carbonate fracture-vuggy reservoir based on a palisade structure is provided in another embodiment, which includes:

[0167] In a certain exploration area in Northwest China, the seismic response characteristics of carbonate reservoirs and the detailed study of reservoir structure were carried out.

[0168] like Figure 7 As shown in Figure 1, we first selected the depth domain profile of a high-yield well in the well direction, which is also the actual single well cross-well profile. According to the fracture characteristics and fault fence structure mode of the actual single well cross-well profile, as shown in Figure 1, Figure 3 As shown, a 1:1 restored geological model is established. An observation system is established according to actual engineering construction parameters. The actual engineering construction parameters in this embodiment are the observation data in the above embodiment. The geological model is given accurate physical parameters of each layer velocity and density according to the acoustic time difference and density curve of the actual logging data. The acoustic time difference and density curve of the actual logging data described in this embodiment are the actual acoustic time difference logging data and actual density logging data in the above embodiment. The actual physical parameters used are sub-wave frequency of 22Hz, calculation grid of 5m, shot distance of 50m, track distance of 50m, and arrangement length of 8000m. Figure 4 As shown, a preliminary single-well forward model is obtained. Secondly, the convolution forward simulation is carried out by self-excitation and self-collection, and the results are compared with the actual single-well cross-well profile to perform quality control in advance. The model described in this embodiment is the preliminary single-well forward model in the above embodiment. The preliminary single-well forward model is modified in a targeted manner to solve the problems in the model, such as incorrect relationship between the strength of the phase axis, inaccurate formation morphology, unclear fracture characteristics, etc., so as to prevent inaccurate results caused by simple errors in the later stage. Then, according to the following example, Figure 6 The innovative forward modeling workflow shown in the figure is the innovative forward modeling simulation step. The shot gather data and the derived velocity volume data obtained by GPU acceleration calculation are used to establish a unified grid through Omega, and the Kirchhoff equation is used to perform prestack depth migration using Paradigm, such as Figure 5 As shown, the imaging result is obtained. The imaging result described in this embodiment is the simulated single well cross-well profile in the above embodiment. The imaging result is then iterated multiple times, such as Figure 8 As shown, the final forward simulation result is obtained. The final forward simulation result described in this embodiment is the simulated single well cross-well profile after multiple iterations in the above embodiment.

[0169] The actual seismic profile described in this embodiment is the actual single well cross-well profile in the above embodiment. The final forward simulation result is subjected to quality control analysis and compared with the actual seismic profile. Figure 7 and Figure 8 As shown in the figure, the actual single well cross-well profile and the simulated single well cross-well profile after multiple iterations have a good match effect, and the actual single well cross-well profile and the model forward modeling result have a high consistency, which verifies the reliability and applicability of the method. The model forward modeling result described in this embodiment is the optimized simulated single well cross-well profile in the above embodiment.

[0170] Finally, according to the model structure and fault storage space characteristics obtained by forward modeling, the foundation can be laid for further carrying out the seismic response characteristics of carbonate reservoirs in high-yield wells and detailed reservoir analysis. The model structure described in this embodiment is the optimized single-well forward model in the above embodiment, and the fault storage space characteristics are obtained by optimizing the simulated single-well cross-well profile.

[0171] Good results were achieved by using the single-well forward modeling process of carbonate fracture-vuggy reservoirs based on the palisade structure.

[0172] In the application of a certain exploration area in the northwest, the process designed by the present invention can calculate relatively accurate single well forward modeling results, providing valuable research ideas and results for the fine description of the fracture-cavity body of the oil field. The single well forward modeling results described in this embodiment are the optimized simulated single well cross-well profile in the above embodiment.

[0173] In this embodiment, a single well forward model with high accuracy is established for carbonate fracture-cavity reservoirs with palisade structures, and the single well forward model is used to accurately simulate the single well cross-well profile to obtain an optimized simulated single well cross-well profile. The single well forward model described in this embodiment is the optimized single well forward model in the above embodiment.

[0174] Embodiment 5

[0175] In this embodiment, Fig. 9 As shown, a single well cross-well profile simulation device is provided, comprising:

[0176] The profile acquisition module 910 is used to acquire the actual single well cross-well profile;

[0177] A fracture feature measurement module 920 is used to measure the fracture features of the actual single well cross-well profile;

[0178] A geological model building module 930 is used to structurally characterize the fracture system of the actual single well cross-section by using the fracture characteristics of the actual single well cross-section to build a geological model;

[0179] A physical parameter acquisition module 940 is used to acquire actual well logging data and analyze the actual well logging data to obtain physical parameters;

[0180] A preliminary single well forward model building module 950 is used to build a preliminary single well forward model based on the geological model;

[0181] An assignment module 960 is used to assign values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model;

[0182] A convolution forward modeling module 970 is used to perform convolution forward modeling on the modified single well forward model to obtain a single well forward model after convolution forward modeling;

[0183] The profile simulation module 980 is used to perform single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile.

[0184] In one embodiment, the single well cross-well profile simulation device further comprises:

[0185] The simulation profile optimization module is used to iteratively optimize the simulated single well cross-well profile using the actual single well cross-well profile to obtain an optimized simulated single well cross-well profile.

[0186] In one embodiment, the convolution forward modeling module includes:

[0187] The self-excited and self-collected convolution forward modeling unit is used to optimize the modified single-well forward model using the actual single-well cross-well profile during the process of performing self-excited and self-collected convolution forward modeling on the modified single-well forward model to obtain the single-well forward model after the convolution forward modeling.

[0188] In one embodiment, the profile simulation module includes:

[0189] A data acquisition unit, used for obtaining shot gather data and velocity volume data by using the single well forward model after the convolution forward modeling;

[0190] The profile simulation unit is used to perform migration imaging using the velocity volume data and the shot gather data, and obtain a simulated single well cross-well profile through migration imaging.

[0191] In one embodiment, the data acquisition unit includes:

[0192] An observation data acquisition subunit, used for acquiring observation data;

[0193] A wave equation acquisition subunit is used to acquire the wave equation;

[0194] A shot gather operation subunit, for obtaining the shot gather data by using the observation data based on the single well forward model after the convolution forward modeling and the wave equation;

[0195] The velocity volume data export subunit is used to export the velocity volume data using the single well forward model after the convolution forward modeling.

[0196] The specific definition of the single-well cross-well profile simulation device can be found in the definition of the single-well cross-well profile simulation method mentioned above, which will not be repeated here. Each unit in the above-mentioned single-well cross-well profile simulation device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned units can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned units.

[0197] Embodiment 6

[0198] In this embodiment, a computer device is provided. Its internal structure diagram can be shown as follows: Fig.10 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database, which is used to store actual single well cross-well profiles, shot collection data and velocity body data. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used to communicate with other computer devices deployed with application software. When the computer program is executed by the processor, a single well cross-well profile simulation method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0199] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0200] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0201] Step 100, obtaining an actual single well cross-well profile;

[0202] Step 200, measuring the fracture characteristics of the actual single well cross-well profile;

[0203] Step 300, using the fracture characteristics of the actual single well cross-section, structurally characterize the fracture system of the actual single well cross-section and construct a geological model;

[0204] Step 400, obtaining actual well logging data, and analyzing the actual well logging data to obtain physical parameters;

[0205] Step 500, constructing a preliminary single well forward model based on the geological model;

[0206] Step 600, assigning values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model;

[0207] Step 700, performing convolution forward modeling on the modified single well forward model to obtain a single well forward model after convolution forward modeling;

[0208] Step 800, performing single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile.

[0209] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0210] The actual single well crossing profile is used to iteratively optimize the simulated single well crossing profile to obtain an optimized simulated single well crossing profile.

[0211] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0212] In the process of performing self-excitation and self-collection convolution forward modeling on the modified single-well forward model, the actual single-well cross-well profile is used to optimize the modified single-well forward model to obtain the single-well forward model after the convolution forward modeling.

[0213] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0214] Using the single well forward model after the convolution forward modeling, shot gather data and velocity volume data are obtained;

[0215] The velocity volume data and the shot gather data are used to perform migration imaging, and a simulated single well cross-well profile is obtained through migration imaging.

[0216] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0217] Obtain observation data;

[0218] Get the wave equation;

[0219] Based on the single well forward model after the convolution forward modeling and the wave equation, the shot gather data is obtained by using the observation data;

[0220] The velocity volume data is derived using the single well forward model after the convolution forward modeling.

[0221] In one embodiment, the wave equation is calculated as follows:

[0222]

[0223]

[0224]

[0225] Among them, U=U(x, z, t), U is the sound pressure, V is the propagation speed of sound waves in the medium, ρ is the density, and s(x, z, t) is the source function.

[0226] Embodiment 7

[0227] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0228] Step 100, obtaining an actual single well cross-well profile;

[0229] Step 200, measuring the fracture characteristics of the actual single well cross-well profile;

[0230] Step 300, using the fracture characteristics of the actual single well cross-section, structurally characterize the fracture system of the actual single well cross-section and construct a geological model;

[0231] Step 400, obtaining actual well logging data, and analyzing the actual well logging data to obtain physical parameters;

[0232] Step 500, constructing a preliminary single well forward model based on the geological model;

[0233] Step 600, assigning values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model;

[0234] Step 700, performing convolution forward modeling on the modified single well forward model to obtain a single well forward model after convolution forward modeling;

[0235] Step 800, performing single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile.

[0236] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0237] The actual single well crossing profile is used to iteratively optimize the simulated single well crossing profile to obtain an optimized simulated single well crossing profile.

[0238] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0239] In the process of performing self-excitation and self-collection convolution forward modeling on the modified single-well forward model, the actual single-well cross-well profile is used to optimize the modified single-well forward model to obtain the single-well forward model after the convolution forward modeling.

[0240] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0241] Using the single well forward model after the convolution forward modeling, shot gather data and velocity volume data are obtained;

[0242] The velocity volume data and the shot gather data are used to perform migration imaging, and a simulated single well cross-well profile is obtained through migration imaging.

[0243] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0244] Obtain observation data;

[0245] Get the wave equation;

[0246] Based on the single well forward model after the convolution forward modeling and the wave equation, the shot gather data is obtained by using the observation data;

[0247] The velocity volume data is derived using the single well forward model after the convolution forward modeling.

[0248] In one embodiment, the wave equation is calculated as follows:

[0249]

[0250]

[0251]

[0252] Among them, U=U(x, z, t), U is the sound pressure, V is the propagation speed of sound waves in the medium, ρ is the density, and s(x, z, t) is the source function.

[0253] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0254] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0255] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A single well cross-well profile simulation method, characterized in that: include: Obtain the actual single well cross-well profile; Measuring the fracture characteristics of the actual single well cross-well profile; Using the fracture characteristics of the actual single well cross-section, structurally characterize the fracture system of the actual single well cross-section and construct a geological model; Acquiring actual well logging data, and analyzing the actual well logging data to obtain physical parameters; Based on the geological model, a preliminary single-well forward model is constructed; Assigning values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model; Performing convolution forward modeling on the modified single-well forward model to obtain a single-well forward model after convolution forward modeling; The single well forward model after the convolution forward modeling is used to perform single well forward simulation to obtain a simulated single well cross-well profile.

2. The method according to claim 1, characterized in that After the step of performing single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile, the method includes: The actual single well crossing profile is used to iteratively optimize the simulated single well crossing profile to obtain an optimized simulated single well crossing profile.

3. The method according to claim 1, characterized in that The step of performing convolution forward modeling on the modified single well forward model to obtain the single well forward model after convolution forward modeling comprises: In the process of performing self-excitation and self-collection convolution forward modeling on the modified single-well forward model, the actual single-well cross-well profile is used to optimize the modified single-well forward model to obtain the single-well forward model after the convolution forward modeling.

4. The method according to claim 1, characterized in that: The step of performing single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile comprises: Using the single well forward model after the convolution forward modeling, shot gather data and velocity volume data are obtained; The velocity volume data and the shot gather data are used to perform migration imaging, and a simulated single well cross-well profile is obtained through migration imaging.

5. The method according to claim 4, characterized in that The step of obtaining shot gather data and velocity volume data by using the single well forward model after the convolution forward modeling comprises: Obtain observation data; Get the wave equation; Based on the single well forward model after the convolution forward modeling and the wave equation, the shot gather data is obtained by using the observation data; The velocity volume data is derived using the single well forward model after the convolution forward modeling.

6. The method according to claim 5, characterized in that The wave equation is calculated as follows: Among them, U=U(x, z, t), U is the sound pressure, V is the propagation speed of sound waves in the medium, ρ is the density, and s(x, z, t) is the source function.

7. A single well cross-well profile simulation device, characterized in that: include: A profile acquisition module is used to obtain the actual single well cross-well profile; A fracture feature measurement module, used to measure the fracture features of the actual single well cross-well profile; A geological model building module is used to structurally characterize the fracture system of the actual single well cross-section by utilizing the fracture characteristics of the actual single well cross-section and to build a geological model; A physical parameter acquisition module is used to acquire actual well logging data and analyze the actual well logging data to obtain physical parameters; A preliminary single-well forward model building module is used to build a preliminary single-well forward model based on the geological model; An assignment module, used for assigning values ​​to the preliminary single-well forward model using the physical parameters to obtain a revised single-well forward model; A convolution forward modeling module is used to perform convolution forward modeling on the modified single well forward model to obtain a single well forward model after convolution forward modeling; The profile simulation module is used to perform single well forward simulation using the single well forward model after the convolution forward modeling to obtain a simulated single well cross-well profile.

8. The device according to claim 7, characterized in that The single well cross-well profile simulation device also includes: The simulation profile optimization module is used to iteratively optimize the simulated single well cross-well profile using the actual single well cross-well profile to obtain an optimized simulated single well cross-well profile.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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