Fluid change indicator extraction method, apparatus, electronic device, and storage medium

Abstract

The embodiment of the application provides a fluid change indicating factor extraction method, device, electronic equipment and storage medium, the method, device, electronic equipment and storage medium are aimed at the four-dimensional seismic difference response of thin oil reservoir, through forward simulation and theoretical derivation, a four-dimensional seismic fluid change indicating factor indicating the fluid change caused by different development modes is defined.The extraction process of the indicating factor is based on 90 degree phase conversion processing and four-dimensional seismic fluid change indicating factor automatic judgment and identification.The indicating factor can automatically distinguish and identify the water drive range and the gas drive range in the thin oil reservoir, and then three-dimensional distribution information of reservoir fluid change is obtained.

Description

Technical Field

[0001] This application relates to the field of petroleum exploration and development, and specifically to a method, apparatus, electronic device, and storage medium for extracting fluid change indicator factors. Background Technology

[0002] 4D seismic analysis is a crucial technology for dynamic monitoring of oil reservoir development. This technology can directly image reservoir fluid changes at different development stages, thereby aiding in the optimization and adjustment of reservoir development plans. Extracting differential attributes from 4D seismic analysis is a vital technique for characterizing fluid changes. Traditional 4D seismic attributes are derived from 3D seismic attributes, but extraction strategies fall into two categories: extracting attributes based on differential seismic attributes and extracting seismic attributes first and then differentiating them. In practical 4D seismic monitoring, interpreting fluid changes in thin layers is a significant challenge. Thin layers in seismic interpretation typically refer to strata with a thickness less than the seismic resolution. Different fluid changes can cause different differential waveforms. Traditional 4D seismic differential amplitude attributes represent the intensity information of amplitude changes caused by fluid changes, but they are insufficient to distinguish and identify different fluid changes occurring during development. While differential waveform information provides some indication of different fluid changes, the judgment of positive and negative waveforms is highly subjective and prone to multiple interpretations, making it difficult to accurately identify fluid changes and accurately describe the spatial range of fluid variations. Chinese patent CN102508294B discloses a method for differential amplitude-dependent velocity (AVO) analysis using four-dimensional seismic exploration data. It utilizes the sensitivity of AVO class attributes to fluid changes to determine the fluid distribution before and after development, and then calculates the difference to obtain the fluid change. This patent analyzes the rock physical meaning represented by differential amplitude AVO, but it cannot provide a direct interpretation of fluid changes. Therefore, there is an urgent need to provide a four-dimensional seismic fluid change indicator that can indicate fluid changes caused by different development methods (such as oil reservoirs simultaneously employing water-drive and gas-drive development methods). Summary of the Invention

[0003] In view of this, this application provides a method, apparatus, electronic device and storage medium for extracting fluid change indicator factors, so as to solve the problem that the prior art cannot accurately identify fluid changes and cannot accurately describe the range of fluid spatial changes.

[0004] In a first aspect, embodiments of this application provide a method for extracting fluid change indicator factors, the method comprising:

[0005] Collect well logging curve interpretation results, including wave impedance curves, porosity curves, and fluid saturation curves of all wells in the target reservoir section;

[0006] Cross-plot analysis of wave impedance curves and fluid saturation curves within a small porosity range yields statistical information on well logging curves.

[0007] An initial reservoir geological model is established, assuming that its pores are saturated with oil. Based on the statistical information of the well logging curves, the geological model is assigned wave impedance parameters to form a rock physical model.

[0008] The water saturation and gas saturation in the initial reservoir geological model were changed respectively to simulate the water-driven reservoir geological model and the gas-driven reservoir geological model.

[0009] The seismic responses of the initial reservoir geological model, the water-drive reservoir geological model, and the gas-drive reservoir geological model were simulated using forward modeling technology, and the seismic responses of the initial model, the water-drive reservoir, and the gas-drive reservoir were obtained.

[0010] By subtracting the initial model seismic response from the seismic response of water-driven reservoirs and gas-driven reservoirs respectively, the differential seismic responses of water-driven and gas-driven reservoirs were obtained.

[0011] The water-drive and gas-drive differential seismic responses were subjected to 90° phase transformation. For each seismic trace of the differential seismic response within the reservoir area, a fluid change indicator factor (f) was extracted. The extraction expression is as follows:

[0012] abs(f) = max(abs(s(t)) dif ))(2)

[0013] Where s(t)dif is the seismic trace of differential seismic response. When calculating f, find and record the sample point with the maximum absolute value of s(t)dif. Then, this point is the position of the main lobe peak of the differential amplitude. The polarity of f is consistent with the sample point with the maximum absolute value.

[0014] This paper summarizes the polarity and numerical range of the fluid change indicator factor f under reservoir geological models under different development methods.

[0015] In one possible implementation, the fluid saturation curve includes a water saturation curve, an oil saturation curve, and a gas saturation curve.

[0016] In one possible implementation, the forward modeling technique employs a convolution algorithm.

[0017] Secondly, embodiments of this application provide a method for four-dimensional seismic interpretation of fluid change indicator factors extracted according to the method described in the first aspect, the method comprising:

[0018] The basic seismic data and the monitoring seismic data were subjected to mutual equalization and consistency processing.

[0019] The differences between the base seismic data and the monitoring seismic data after mutual equalization and consistency processing are calculated to obtain the differential 3D seismic data volume.

[0020] Perform a 90° phase transformation on the differential 3D seismic data volume;

[0021] The fluid change indicator factor is extracted from the target layer, and the polarity and numerical range of the fluid change indicator factor f under the reservoir geological model under different development methods are used to determine the fluid change mode in the target layer.

[0022] In one possible implementation, the mutual equalization consistency processing includes consistency processing of frequency, phase, and denoising stages.

[0023] In one possible implementation, the basic seismic data is seismic data acquired before development, and the monitoring seismic data is seismic data acquired after development.

[0024] Thirdly, embodiments of this application provide a fluid change indicator extraction device, the extraction device comprising the following modules:

[0025] The data collection module is used to collect logging curve interpretation results, including wave impedance curves, porosity curves, and fluid saturation curves of all wells in the target reservoir section;

[0026] The logging curve statistical information calculation module is used to perform cross-analysis of wave impedance curves and fluid saturation curves within a small porosity range to obtain logging curve statistical information.

[0027] The reservoir geological model simulation module is used to establish an initial reservoir geological model and to change the water saturation and gas saturation in the initial reservoir geological model to simulate water-driven reservoir geological models and gas-driven reservoir geological models, respectively.

[0028] The differential seismic response calculation module is used to perform forward modeling of the initial reservoir geological model, water-drive reservoir geological model and gas-drive reservoir geological model to obtain the initial model seismic response, water-drive reservoir seismic response and gas-drive reservoir seismic response, and then calculate the water-drive differential seismic response and gas-drive differential seismic response.

[0029] Phase conversion module is used to perform 90° phase conversion processing on the water-driven differential seismic response and the gas-driven differential seismic response respectively;

[0030] The fluid change indicator extraction module is used to extract fluid change indicator factors for each seismic trace of the differential seismic response within the reservoir area, and to summarize the polarity and numerical range of fluid change indicator factors under different development methods in the reservoir geological model.

[0031] Fourthly, embodiments of this application provide a four-dimensional seismic interpretation device, which includes the fluid change indicator extraction device described in the third aspect, and further includes the following modules:

[0032] The mutual averaging and consistency processing module is used to perform mutual averaging and consistency processing on basic seismic data and monitoring seismic data;

[0033] The differential 3D seismic data volume acquisition module is used to calculate the differences between the basic seismic data and the monitored seismic data after mutual equalization and consistency processing, obtain the differential 3D seismic data volume, and perform a 90° phase transformation on the differential 3D seismic data volume.

[0034] The interpretation module is used to extract the fluid change indicator factors in the target layer, and to determine the fluid change mode in the target layer by using the polarity and numerical range of the fluid change indicator factors in the reservoir geological model under different development modes summarized by the fluid change indicator factor extraction module.

[0035] Fifthly, embodiments of this application provide an electronic device, including:

[0036] processor;

[0037] Memory;

[0038] And a computer program, wherein the computer program is stored in the memory, the computer program including instructions that, when executed by the processor, cause the electronic device to perform the method described in either the first aspect or the second aspect.

[0039] In a sixth aspect, embodiments of this application provide a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the method described in either the first or second aspect.

[0040] This invention addresses the shortcomings of traditional four-dimensional seismic attributes and the differential response characteristics of four-dimensional seismic data in thin oil reservoirs. Through forward modeling and theoretical derivation, it defines a four-dimensional seismic fluid change indicator factor that can indicate fluid changes caused by different development methods (such as reservoirs simultaneously employing water-drive and gas-drive development methods). The overall process includes 90° phase transformation processing and extraction of the four-dimensional seismic fluid change indicator factor. Using this fluid change indicator factor, not only can the water-drive and gas-drive ranges in thin oil reservoirs be distinguished and identified, but quantitative information on the three-dimensional distribution range of reservoir fluid changes can also be obtained.

[0041] This invention proposes a novel four-dimensional seismic differential attribute—the fluid change indicator factor—to distinguish between water-drive and gas-drive zones in thin reservoirs, thereby obtaining three-dimensional distribution information on reservoir fluid changes. Compared to traditional four-dimensional seismic differential attributes, this method offers stronger interpretability; compared to interpretation methods such as four-dimensional seismic inversion, it boasts faster computation speed, reduces the interpretation cycle, and increases the timeliness of technology application. This method is applicable to the four-dimensional seismic interpretation stage in the development of various types of deep-water reservoirs, such as deep-water turbidite sandstone reservoirs or pre-salt carbonate reservoirs. Compared with traditional differential seismic attributes, this invention has the following beneficial effects:

[0042] (1) Applicable to four-dimensional seismic dynamic monitoring and analysis of fluid changes in thin oil reservoirs;

[0043] (2) It can effectively distinguish the fluid transport path and range of change under different development methods;

[0044] (3) It can achieve a quantitative description of the range of fluid variation. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 A flow chart of a method for extracting fluid change indicator factors provided in this application embodiment;

[0047] Figure 2 A four-dimensional seismic interpretation process is provided for embodiments of this application;

[0048] Figure 3 A structural block diagram of a fluid change indicator extraction device provided in this application embodiment;

[0049] Figure 4 A structural block diagram of a four-dimensional seismic interpretation device provided in an embodiment of this application;

[0050] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0051] Figure 6 The initial geological model and post-development geological model of the thin oil reservoir provided in the embodiments of this application;

[0052] Figure 7 Examples of this application Figure 6 The image shows a comparison of seismic response profiles before and after the development of the geological model.

[0053] Figure 8 Examples of this application Figure 6 The geological model shows the differential seismic response profile;

[0054] Figure 9 Examples of this application Figure 6 The geological model shown is a 90° phase-transform profile of differential seismic response.

[0055] Figure 10 Examples of this application Figure 6 The geological model shown exhibits characteristics of fluid change indicators under different development methods;

[0056] Figure 11 This is a schematic diagram of the planar distribution of the P oilfield fluid change indicator factor provided in the embodiments of this application. Detailed Implementation

[0057] To better understand the technical solution of this application, the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0058] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0059] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0060] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0061] Changes in underground fluids can cause variations in reservoir elastic parameters such as velocity, density, and wave impedance, leading to changes in the reflection coefficient and resulting in differential seismic reflection responses. Rock physics analysis indicates that different fluid displacement processes induce different changes in reservoir elastic parameters: gas displacement of oil reduces reservoir wave impedance, while water displacement of light oil increases it.

[0062] This embodiment uses four-dimensional seismic fluid substitution rock physics analysis to determine the reservoir acoustic impedance changes under different fluid variations, and uses seismic forward modeling to determine the differential reflection characteristics under different acoustic impedance changes, providing a seismic attribute factor that can indicate different fluid changes and distinguish different fluid displacement effects. Combined with... Figure 1 A method for extracting indicators of fluid change, the specific steps of which are as follows:

[0063] Step 1.1: Collect logging curve interpretation results, including wave impedance curves (I), porosity curves (φ), and fluid saturation curves for all wells in the target reservoir section.

[0064] Furthermore, the fluid saturation curve includes a water saturation curve (S... w ), oil saturation curve (S) o ) and gas saturation curve (S g ).

[0065] Step 1.2: The basic components of an oil reservoir are rock and fluid. It can be assumed that the main influencing factors of wave impedance are porosity and fluid composition. Cross-plot analysis is performed on the wave impedance curve and the fluid saturation curve within a small porosity range to obtain logging curve statistical information. This logging curve statistical information represents the law of wave impedance variation with different fluid saturation levels.

[0066] For example, in a certain oil field, when the cross-analysis of wave impedance and oil saturation in oil-bearing and water-bearing reservoirs within the 23%-25% porosity range is performed, a linearly decreasing fitting curve is obtained, which can be considered as wave impedance decreasing with increasing oil saturation.

[0067] Step 1.3: Establish an initial reservoir geological model, assuming that its pores are saturated with oil. Assign wave impedance parameters to the geological model based on the statistical information of the well logging curves to form a rock physics model.

[0068] Step 1.4: Change the water saturation and gas saturation in the initial reservoir geological model respectively to simulate the water-driven reservoir geological model and the gas-driven reservoir geological model.

[0069] Specifically, based on the rock physics analysis results (i.e., well logging curve statistics) in step 1.2, the rock physics model parameters corresponding to the geological model are adjusted.

[0070] Step 1.5: Use forward modeling technology to simulate the seismic response of the initial reservoir geological model, the water-drive reservoir geological model, and the gas-drive reservoir geological model, respectively, to obtain the initial model seismic response, the water-drive reservoir seismic response, and the gas-drive reservoir seismic response.

[0071] Preferably, the forward modeling technique can employ a convolution algorithm:

[0072] s(t)=w(t)*r(t) (1)

[0073] Where s(t), w(t), and r(t) are the synthetic seismic record, wavelet, and reflection coefficient, respectively.

[0074] Step 1.6: Subtract the initial model seismic response from the seismic response of the water-drive reservoir and the gas-drive reservoir, respectively, to obtain the differential seismic response of the water-drive reservoir and the differential seismic response of the gas-drive reservoir.

[0075] Step 1.7: Perform 90° phase transformation processing on the water-driven and gas-driven differential seismic responses respectively, and summarize the reflection characteristics of the two types of differential seismic responses. The polarity and value of the main lobe in the differential seismic reflection responses corresponding to different fluid changes are significantly different. Extract the fluid change indicator factor (f) for each seismic trace of the differential seismic response within the reservoir area. The extraction expression is as follows:

[0076] abs(f) = max(abs(s(t)) dif (2)

[0077] Where, s(t) dif These are differential seismic response traces. When calculating f, find and record s(t). dif The sample point with the maximum absolute value is considered to be the peak position of the main lobe of the differential amplitude, and the polarity of f needs to be consistent with that of the sample point with the maximum absolute value.

[0078] Step 1.8: Summarize the polarity and numerical range of the fluid change indicator factor f under different development methods in reservoir geological models.

[0079] Combination Figure 2 Based on the above embodiments, this embodiment further discloses a process for four-dimensional seismic interpretation using fluid change indicator factors extracted by the above method, the specific steps of which are as follows:

[0080] Step 2.1: Perform mutual equalization and consistency processing on the actual reservoir's four-dimensional seismic multi-phase data, including consistency processing of frequency, phase, and denoising.

[0081] Furthermore, the seismic data includes basic seismic data (i.e., seismic data acquired before development) and monitoring seismic data (i.e., seismic data acquired after development).

[0082] Step 2.2: Calculate the differences between the basic seismic data and the monitoring seismic data to obtain the differential 3D seismic data volume.

[0083] s(t) dif =s(t) base -s(t) mon (3)

[0084] Where, s(t) dif s(t) base s(t) mon These are differential earthquake data, basic earthquake data, and monitored earthquake data;

[0085] Step 2.3: Perform a 90° phase transformation on the differential 3D seismic data volume.

[0086] Step 2.4: Extract the fluid change indicator factor in the target layer, and use the polarity and numerical range of the fluid change indicator factor f under the reservoir geological model under different development methods summarized in Step 1.8 to determine the fluid change mode in the target layer.

[0087] Corresponding to the above embodiments, this application also provides a fluid change indicator extraction device, combined with Figure 3 It mainly includes the following modules:

[0088] The data collection module 301 is used to collect logging curve interpretation results, including wave impedance curves (I), porosity curves (φ), and fluid saturation curves of all wells in the target reservoir section;

[0089] The logging curve statistical information calculation module 302 is used to perform cross-analysis of wave impedance curve and fluid saturation curve within a small porosity range to obtain logging curve statistical information.

[0090] The reservoir geological model simulation module 303 is used to establish an initial reservoir geological model and change the water saturation and gas saturation in the initial reservoir geological model respectively to simulate the water-driven reservoir geological model and the gas-driven reservoir geological model.

[0091] The differential seismic response calculation module 304 is used to perform forward modeling of the initial reservoir geological model, water-drive reservoir geological model and gas-drive reservoir geological model to obtain the initial model seismic response, water-drive reservoir seismic response and gas-drive reservoir seismic response, and then calculate the water-drive differential seismic response and gas-drive differential seismic response.

[0092] Phase conversion module 305 is used to perform 90° phase conversion processing on the water-driven differential seismic response and the gas-driven differential seismic response respectively;

[0093] The fluid change indicator extraction module 306 is used to extract fluid change indicator factors for each seismic trace of the differential seismic response within the reservoir area, and to summarize the polarity and numerical range of the fluid change indicator factor f under different development methods in the reservoir geological model.

[0094] Corresponding to the above embodiments, based on the fluid change indicator extraction device, this embodiment further proposes a four-dimensional seismic interpretation device, combined with... Figure 4 In addition to the fluid change indicator extraction device, it also includes the following modules:

[0095] The mutual averaging and consistency processing module 401 is used to perform mutual averaging and consistency processing on multi-phase four-dimensional seismic data of actual oil reservoirs, wherein the seismic data includes basic seismic data and monitoring seismic data.

[0096] The differential 3D seismic data volume acquisition module 402 calculates the differences between basic seismic data and monitoring seismic data to obtain differential 3D seismic data volume, and performs a 90° phase transformation on the differential 3D seismic data volume.

[0097] The interpretation module 403 extracts the fluid change indicator factor in the target layer and uses the polarity and numerical range of the fluid change indicator factor f under different development methods in the reservoir geological model summarized by the fluid change indicator factor extraction module 306 to determine the fluid change mode in the target layer.

[0098] It should be noted that the specific content involved in the embodiments of this application can be found in the description of the above method embodiments, and will not be repeated here for the sake of brevity.

[0099] Corresponding to the above embodiments, this application also provides an electronic device.

[0100] See Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 500 may include a processor 501, a memory 502, and a communication unit 503. These components communicate through one or more buses. Those skilled in the art will understand that the electronic device structure shown in the figure does not constitute a limitation on the embodiment of this application. It may be a bus-shaped structure or a star-shaped structure, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0101] The communication unit 503 is used to establish a communication channel, thereby enabling the electronic device to communicate with other devices.

[0102] Processor 501 serves as the control center of the electronic device, connecting various parts of the device via various interfaces and lines. It executes software programs and / or modules stored in memory 502, and calls data stored in memory to perform various functions and / or process data. The processor may be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs with the same or different functions connected together. For example, processor 501 may consist only of a central processing unit (CPU). In this embodiment, the CPU may have a single processing core or include multiple processing cores.

[0103] Memory 502 is used to store the execution instructions of processor 501. Memory 502 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0104] When the execution instructions in memory 502 are executed by processor 501, the electronic device 500 is able to perform some or all of the steps in the above method embodiments.

[0105] Corresponding to the above embodiments, this application also provides a computer-readable storage medium, wherein the computer-readable storage medium may store a program, wherein when the program runs, it can control the device where the computer-readable storage medium is located to execute some or all of the steps in the above method embodiments. In specific implementation, the computer-readable storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0106] Corresponding to the above embodiments, this application also provides a computer program product containing executable instructions that, when executed on a computer, cause the computer to perform some or all of the steps in the above method embodiments.

[0107] Corresponding to the above embodiments, this embodiment further takes the P reservoir of a turbidite sandstone reservoir in the deep water area of ​​West Africa as an example to extract fluid change indicator factors and determine the fluid movement path and change range of the two displacement methods of water drive and gas drive.

[0108] Figure 6 The initial geological model and the post-development geological model of the thin oil reservoir established in this embodiment include the left, middle and right three-stage turbidite channel sandstone oil reservoirs. Figure 6 The image above shows the initial geological model of the oil reservoir, with an oil saturation of 100%. Figure 6 The image below shows a geological model of the developed reservoir. The lower waterway on the left has undergone water injection development, resulting in increased water saturation and higher wave impedance. The higher waterway on the right has undergone gas injection development, resulting in increased gas saturation and lower wave impedance. The middle waterway has not been developed or utilized, and its properties remain unchanged. Figure 7 For this embodiment Figure 6 The diagram shows a comparison of the seismic response before and after the development of the geological model. Figure 7 The image above shows the seismic response before the geological model was developed. Figure 7 The figure below shows the seismic response after the geological model was developed. Figure 8 for Figure 6 The geological model shown is the initial geological model of the reservoir and the differential seismic response profiles after water-drive and gas-drive development. Figure 9 The study demonstrates the initial geological model of the reservoir and the differential seismic response after a 90° phase transition following water-drive and gas-drive development. The strong wavelet side-adjoint influence in the differential response accurately indicates changes in fluid in space.

[0109] Figure 10 The characteristics of fluid change indicator factors under different development methods are demonstrated. In this embodiment, negative anomalies in fluid change indicator factors were generated in the water-drive reservoir, while positive anomalies were generated in the gas-drive reservoir. Furthermore, the intensity of the indicator factors is positively correlated with the differential amplitude energy. Therefore, fluid change indicator factors can indicate the mode and intensity of fluid changes.

[0110] Figure 11 The planar variation of fluid change indicator factors in the P oilfield is shown, clearly characterizing the water drive and gas drive ranges. Comparative matching analysis with the production dynamics of production wells, water injection wells, and gas injection wells reveals (matching analysis results are shown in Table 1) that the fluid change indicator factors perfectly match the reservoir ecological dynamics, demonstrating high reliability in predicting inter-well fluid changes.

[0111] Table 1: Matching Analysis of Fluid Change Indicators and Production Dynamic Response

[0112]

[0113]

[0114] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0115] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0116] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0117] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0118] The above description is merely a specific embodiment of this application. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. The protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for extracting fluid change indicator factors, characterized in that, The method includes: Collect well logging curve interpretation results, including wave impedance curves, porosity curves, and fluid saturation curves of all wells in the target reservoir section; Cross-plot analysis of wave impedance curves and fluid saturation curves within a small porosity range yields statistical information on well logging curves. An initial reservoir geological model is established, assuming that its pores are saturated with oil. Based on the statistical information of the well logging curves, the geological model is assigned wave impedance parameters to form a rock physical model. The water saturation and gas saturation in the initial reservoir geological model were changed respectively to simulate the water-driven reservoir geological model and the gas-driven reservoir geological model. The seismic responses of the initial reservoir geological model, the water-drive reservoir geological model, and the gas-drive reservoir geological model were simulated using forward modeling technology, and the seismic responses of the initial model, the water-drive reservoir, and the gas-drive reservoir were obtained. By subtracting the initial model seismic response from the seismic response of water-driven reservoirs and gas-driven reservoirs, the differential seismic responses of water-driven and gas-driven reservoirs were obtained. The water-drive and gas-drive differential seismic responses were subjected to 90° phase transformation processing, and fluid change indicator factors were extracted for each seismic trace of the differential seismic response within the reservoir area. The extracted expression is: (2) in, These are differential seismic response seismic traces, calculated. At that time, search and record The sample point with the maximum absolute value is the location of the main lobe peak of the difference amplitude. The polarity of the sample points is consistent with the maximum absolute value. Summarize fluid variation indicator factors in reservoir geological models under different development methods The polarity and numerical range of .

2. The method according to claim 1, characterized in that, The fluid saturation curves include water saturation curves, oil saturation curves, and gas saturation curves.

3. The method according to claim 1, characterized in that, The forward modeling technique employs a convolution algorithm.

4. A method for four-dimensional seismic interpretation of fluid change indicator factors extracted according to any one of claims 1-3, characterized in that, The method includes: The basic seismic data and the monitoring seismic data were subjected to mutual equalization and consistency processing. The differences between the base seismic data and the monitoring seismic data after mutual equalization and consistency processing are obtained to obtain the differential 3D seismic data volume. Perform a 90° phase transformation on the differential 3D seismic data volume; The fluid change indicator factors were extracted from the target layer, and the fluid change indicator factors under different development methods in reservoir geological models were summarized. The polarity and numerical range are used to determine the fluid variation pattern in the target layer.

5. The method according to claim 4, characterized in that, The mutual equalization consistency processing includes consistency processing of frequency, phase, and denoising stages.

6. The method according to claim 4, characterized in that, The basic seismic data refers to seismic data collected before development, while the monitoring seismic data refers to seismic data collected after development.

7. A device for extracting fluid change indicator factors, characterized in that, The extraction device includes the following modules: The data collection module is used to collect logging curve interpretation results, including wave impedance curves, porosity curves, and fluid saturation curves of all wells in the target reservoir section; The logging curve statistical information calculation module is used to perform cross-analysis of wave impedance curves and fluid saturation curves within a small porosity range to obtain logging curve statistical information. The reservoir geological model simulation module is used to establish an initial reservoir geological model, assuming that its pores are saturated with oil. Based on the statistical information of the well logging curves, the geological model is assigned wave impedance parameters to form a rock physics model. The water saturation and gas saturation in the initial reservoir geological model are changed respectively to simulate water-driven reservoir geological models and gas-driven reservoir geological models. The differential seismic response calculation module is used to perform forward modeling of the initial reservoir geological model, water-drive reservoir geological model, and gas-drive reservoir geological model to obtain the initial model seismic response, water-drive reservoir seismic response, and gas-drive reservoir seismic response. The water-drive differential seismic response and gas-drive differential seismic response are obtained by subtracting the initial model seismic response from the water-drive reservoir seismic response and the gas-drive reservoir seismic response, respectively. The phase conversion module is used to perform 90° phase conversion processing on the water-driven differential seismic response and the gas-driven differential seismic response respectively; The fluid change indicator extraction module is used to extract fluid change indicator factors from each seismic trace of differential seismic response within the reservoir area. And summarize the fluid change indicator factors under reservoir geological models under different development methods. The polarity and numerical range; the extracted expression is: (2) in, These are differential seismic response seismic traces, calculated. At that time, search and record The sample point with the maximum absolute value is the location of the main lobe peak of the difference amplitude. The polarity of the sample points is consistent with the maximum absolute value.

8. A four-dimensional seismic interpretation device, the interpretation device comprising the fluid change indicator extraction device of claim 7, characterized in that, The four-dimensional seismic interpretation device also includes the following modules: The mutual averaging and consistency processing module is used to perform mutual averaging and consistency processing on basic seismic data and monitoring seismic data; The differential 3D seismic data volume acquisition module is used to calculate the differences between the basic seismic data and the monitored seismic data after mutual equalization and consistency processing, obtain the differential 3D seismic data volume, and perform a 90° phase transformation on the differential 3D seismic data volume. The interpretation module is used to extract the fluid change indicator factors in the target layer, and to determine the fluid change mode in the target layer by using the polarity and numerical range of the fluid change indicator factors in the reservoir geological model under different development modes summarized by the fluid change indicator factor extraction module.

9. An electronic device, characterized in that, include: processor; Memory; And a computer program, wherein the computer program is stored in the memory, the computer program including instructions that, when executed by the processor, cause the electronic device to perform the method of any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 6.

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