A method, device and storage medium for seismic prediction of an oil-water interface

Abstract

The application discloses a kind of oil-water interface seismic prediction method, equipment and storage medium, belong to oil and gas exploration technical field.The method includes the following steps: S1.Based on well logging data, the intersection interpretation template of longitudinal wave impedance and shear wave impedance curve of reservoir actual state and water-saturated state is established;S2.Based on the prestack bayesian inversion of bayesian sparse inversion theory and model soft constraint, the inversion result of longitudinal wave impedance and shear wave impedance in study area is obtained;S3.According to the intersection interpretation template, the inversion result of longitudinal wave impedance and shear wave impedance is predicted for the distribution of water-bearing layer in study area;S4.The time-depth relationship that meets the depth requirement is established, and the time-depth conversion is carried out for the distribution of water-bearing layer in study area, and the shallowest depth position of water-bearing layer is the position of oil-water interface.The application can qualitatively-semi-quantitatively predict oil-water interface, and can estimate oil-water interface according to a small amount of well data in early exploration, to provide technical support for next step exploration of oil field.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas exploration, and relates to an oil-water interface prediction method, in particular to an oil-water interface seismic prediction method, device and storage medium. Background Art

[0002] The determination of the oil-gas-water interface is one of the important links in oil and gas exploration and reservoir evaluation. The position of the oil-water interface in the reservoir is indispensable information for evaluating the reservoir and calculating the oil and gas reserves.

[0003] At present, the research methods used by Chinese and foreign scholars for oil-water interface identification and prediction mainly include direct methods such as core profile analysis, dynamic data method, well logging interpretation method, oil testing method, geochemical determination method, as well as indirect methods such as formation pressure estimation method, capillary pressure prediction method, seismic attribute analysis method, water breakthrough time-liquid production depth intersection method, karst residual hillock landform method, etc.

[0004] In oilfield exploration, the above-mentioned prediction methods primarily determine the location of the oil-water contact based on well logging, well testing, and well testing data. While effective, this method requires extensive data and reliable results from drilling a large number of wells. However, for offshore oilfields or in the early stages of exploration, insufficient data may be obtained due to a small number of wells drilled, or only a single fluid phase may be encountered, making the aforementioned oil-water contact prediction methods unsuitable. Therefore, for these types of oilfields, identifying the oil-water contact is difficult if it has not been encountered, making it difficult to clearly determine the scale of oil and gas reserves. Summary of the Invention

[0005] The purpose of the present invention is to provide a seismic prediction method, device and storage medium for oil-water interface to solve the problem that the oil-water interface is difficult to predict due to a small number of wells or drilling only a single fluid phase.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A method for predicting earthquakes at an oil-water interface comprises the following steps:

[0008] S1. Based on well logging data, establish an intersection interpretation template for the P-wave impedance and S-wave impedance curves of the actual reservoir state and the water-saturated state;

[0009] S2. Conduct pre-stack Bayesian inversion based on Bayesian sparse inversion theory and model soft constraints to obtain inversion results of P-wave impedance and S-wave impedance in the study area;

[0010] S3. Based on the intersection interpretation template, predict the aquifer distribution in the study area based on the inversion results of longitudinal wave impedance and shear wave impedance;

[0011] S4. Establish a time-depth relationship that meets the depth requirements and perform time-depth conversion on the aquifer distribution in the study area. The shallowest depth of the aquifer is the oil-water interface.

[0012] As a limitation, the step S4 of establishing the time-depth relationship that meets the depth requirement specifically includes:

[0013] According to the projection point of the velocity spectrum at the logging position, the deviation between the logging velocity and the velocity spectrum is calculated, the deep deviation is derived, and the time-depth relationship that meets the depth requirements of the data volume is established.

[0014] As another limitation, step S1 specifically includes:

[0015] S11. Based on the well logging curves and interpretation theory, establish an original interpretation template and build an actual formation model;

[0016] S12. Perform fluid replacement on the actual formation model to obtain a water-saturated replacement model, and calculate the P-wave velocity, S-wave velocity, and density of the water-saturated replacement model;

[0017] S13. Establish an intersection interpretation template for the P-wave impedance and S-wave impedance curves of the actual reservoir state and the water-saturated state.

[0018] As a further limitation, the well logging curves include compressional wave velocity, shear wave velocity and density curves.

[0019] The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned oil-water interface earthquake prediction method when executing the computer program.

[0020] The present invention also provides a computer-readable storage medium storing a computer program for executing the above-mentioned oil-water interface earthquake prediction method.

[0021] Due to the adoption of the above technical solution, the present invention has the following technical advancements compared with the prior art:

[0022] The present invention provides a seismic prediction method, device and storage medium for oil-water interface, which can qualitatively and semi-quantitatively predict the oil-water interface. It can make an estimate of the oil-water interface based on a small amount of well data in the early stage of exploration, providing technical support for the next step of oil field exploration. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flowchart of the oil-water interface earthquake prediction method in Example 1;

[0024] Figure 2 The result of fluid replacement in the actual formation model in Example 1;

[0025] Figure 3 It is a template for explaining the intersection of the longitudinal wave impedance and the shear wave impedance curves in Example 1;

[0026] Figure 4 is the inversion result profile of longitudinal wave impedance and shear wave impedance in Example 1, where Figure 4 a is the longitudinal wave impedance profile, Figure 4 b is the shear wave impedance profile;

[0027] Figure 5 is the deviation between the logging velocity and the velocity spectrum in Example 1;

[0028] Figure 6 This is the profile of the depth domain oil-water interface prediction result in Example 1. DETAILED DESCRIPTION

[0029] The present invention will be further described in detail below by way of specific examples. It should be understood that the described examples are only used to illustrate the present invention and are not intended to limit the present invention.

[0030] Example 1 A method for predicting earthquakes at an oil-water interface

[0031] This embodiment discloses a method for predicting earthquakes at an oil-water interface. The operation flow chart is as follows: Figure 1 As shown in the figure, this method was applied in a study area where only one well was drilled. The actual formation oil saturation was predicted to be 56% based on the well logging interpretation results, and no water layer was encountered. The specific operation included the following steps:

[0032] S1.

[0033] S11. Based on the measured logging curves of P-wave velocity, S-wave velocity, and density during drilling and the interpretation results, establish an original interpretation template and an actual formation model;

[0034] S12. The actual formation model is replaced with Gassmann fluids with different water contents in the reservoir. The results are as follows: Figure 2 As shown, this embodiment mainly obtains a water-saturated replacement model and calculates the longitudinal wave velocity, shear wave velocity and density of the water-saturated replacement model;

[0035] Depend on Figure 2 It can be seen that the dotted lines represent the actual velocity curve and the actual density curve (the actual formation oil saturation is 56%). The predicted P-wave velocity and density curves when the formation oil saturation is 60% are close to the actual curves, indicating that the established formation model is reliable and the fluid replacement results are relatively accurate.

[0036] S13. Establish an intersection interpretation template for the longitudinal wave impedance and shear wave impedance curves of the reservoir's actual fluid state and water-saturated state, such as Figure 3 As shown;

[0037] S2. Apply the measured P-wave velocity, S-wave velocity and density as well as the seismic data volume to perform pre-stack Bayesian inversion and perform soft constraints on the model to obtain the inversion results of P-wave impedance and S-wave impedance of the study area with high accuracy and resolution, such as Figure 4 As shown;

[0038] S3. Based on the intersection interpretation template obtained in step S13, the inversion results of the longitudinal wave impedance and the shear wave impedance obtained in step S2 are used to predict the distribution of the aquifer in the study area;

[0039] S4. Calculate the deviation between the logging velocity and the velocity spectrum based on the projection point of the velocity spectrum at the logging location. The result is as follows: Figure 5 As shown in the figure, the deep deviation difference is derived and the time-depth relationship that meets the depth requirements of the data body is established. On this basis, the time-depth conversion of the aquifer distribution in the study area is carried out. The shallowest depth position of the aquifer is the oil-water interface position. The results are shown in the figure. Figure 6 shown.

[0040] Example 2 A computer device

[0041] This embodiment provides a computer device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, so as to implement the above-mentioned method for seismic prediction of oil-water interface.

[0042] The memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, flash memory, etc.

[0043] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. The processor is configured to execute the computer-readable instructions stored in the memory.

[0044] Those skilled in the art should understand that in order to solve the technical problem of how to obtain a good user experience, this embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the scope of protection of this disclosure.

[0045] For detailed description of this embodiment, please refer to the corresponding description in the aforementioned embodiments, which will not be repeated here.

[0046] Example 3 A computer-readable storage medium

[0047] This embodiment provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for predicting the seismic behavior of an oil-water interface is implemented.

[0048] The computer-readable storage medium stores non-transitory computer-readable instructions, which, when executed by a processor, execute all or part of the steps of the aforementioned methods.

[0049] The above-mentioned computer-readable storage media include, but are not limited to, optical storage media (e.g., CD-ROMs and DVDs), magneto-optical storage media (e.g., MOs), magnetic storage media (e.g., magnetic tapes or mobile hard disks), media with built-in rewritable non-volatile memory (e.g., memory cards), and media with built-in ROM (e.g., ROM cartridges).

Claims

1. A method for predicting earthquakes at an oil-water interface, characterized in that: The following steps are involved: S1. Based on well logging data, establish an intersection interpretation template for the P-wave impedance and S-wave impedance curves of the actual reservoir state and the water-saturated state; S11. Based on the well logging curves and interpretation theory, establish an original interpretation template and build an actual formation model; S12. Perform fluid replacement on the actual formation model to obtain a water-saturated replacement model, and calculate the P-wave velocity, S-wave velocity, and density of the water-saturated replacement model; S13. Establish an intersection interpretation template for the P-wave impedance and S-wave impedance curves of the actual reservoir state and the water-saturated state; S2. Conduct pre-stack Bayesian inversion based on Bayesian sparse inversion theory and model soft constraints to obtain inversion results of P-wave impedance and S-wave impedance in the study area; S3. Based on the intersection interpretation template, predict the aquifer distribution in the study area based on the inversion results of longitudinal wave impedance and shear wave impedance; S4. Based on the projection point of the velocity spectrum at the logging location, calculate the deviation between the logging velocity and the velocity spectrum, deduce the deep-layer deviation, establish a time-depth relationship that meets the depth requirements, and perform time-depth conversion on the aquifer distribution in the study area. The shallowest depth of the aquifer is the oil-water interface.

2. The method for predicting earthquakes at an oil-water interface according to claim 1, wherein: The logging curves include compressional wave velocity, shear wave velocity and density curves.

3. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the oil-water interface earthquake prediction method according to claim 1 or 2 is implemented.

4. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program for executing the oil-water interface earthquake prediction method according to claim 1 or 2.

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