A fluid detection method, system and readable medium based on AVO attribute volume constraint

Abstract

The present application belongs to the technical field of oil and gas exploration and development, and relates to a fluid detection method and system based on AVO attribute volume constraint and a readable medium, comprising: calculating AVO attributes according to pre-stack common reflection point gathers; constructing an AVO interpretation volume according to typical reservoirs of target zones of drilled wells; calibrating and correcting the AVO interpretation volume through actual data of key wells; determining the range of AVO attributes in the corrected AVO interpretation volume according to the porosity range of effective reservoirs in the target zone, obtaining the intercept and gradient data volume after the AVO interpretation volume is constrained; demarcating the oil-gas and water boundary according to the effective water saturation, and rotating the intersection graph of the boundary and the constrained intercept and gradient data volume to obtain the fluid detection result of the target zone. The AVO interpretation volume is calibrated and corrected in combination with the actual drilled well seismic data, so that it is most consistent with the geological and geophysical conditions of the target zone, thereby improving the fluid detection accuracy.

Description

Technical Field

[0001] This invention relates to a fluid detection method, system, and readable medium based on AVO attribute quantization constraints, belonging to the field of oil and gas exploration and development technology. Background Technology

[0002] Seismic fluid detection in the oil exploration and development field has formed a core technical system based on various attributes derived from pre-stack seismic data. Among these, AVO technology and its derivative methods are the core support for current fluid identification. This technology accurately describes the differences in seismic responses of different fluids by analyzing the variation characteristics of seismic wave amplitude with offset, combined with parameters such as P-wave impedance, P-wave / S-wave velocity ratio, and Poisson impedance. It has mature applications in conventional oil and gas reservoir exploration. Meanwhile, rock physics theory based on the Gassmann equation continues to develop and integrates with pre-stack seismic technology, forming a multi-parameter joint fluid detection technology system based on rock physics. This system has been widely applied in conventional oil and gas reservoirs, as well as tight gas and shallow gas reservoirs, significantly improving the success rate of oil exploration and development.

[0003] However, current seismic fluid detection technology still faces multiple challenges due to complex geological conditions. The core issue lies in the problem of ambiguity, as numerous factors influence the characteristics of pre-stack seismic gathers, including lithology, porosity, cementation, compaction, saturation, fluid type, and sedimentary environment. In summary, these factors mainly involve diagenesis, sedimentary environment, geological age, lithology, physical properties, and fluid characteristics. The combined effect of these factors significantly impacts the accuracy of fluid detection. The heterogeneity, anisotropy, and pore structure differences of underground rocks lead to mutual influence of the seismic response characteristics of different fluids (oil, gas, and water). AVO technology is susceptible to geological interference; the differences in AVO characteristics may be reduced under different fluid filling conditions. Sometimes, both oil-bearing and water-bearing sandstones may exhibit AVO anomalies, resulting in severe ambiguity in AVO oil and gas detection. Summary of the Invention

[0004] To address the aforementioned issues, the present invention aims to provide a fluid detection method, system, and readable medium based on AVO attribute gauge constraints. This method combines actual drilled wellside seismic data to calibrate and correct the AVO interpretation gauge, ensuring that the gauge conforms to the geological and geophysical conditions of the target area to the greatest extent possible, thereby improving the accuracy of fluid detection.

[0005] To achieve the above objectives, the present invention proposes the following technical solution: a fluid detection method based on AVO attribute template constraints, comprising the following steps: calculating AVO attributes based on pre-stack common reflection point gathers to obtain intercept P data volume and gradient G data volume; constructing an AVO interpretation template based on typical reservoirs of the drilled target layer within the target area; calibrating and correcting the AVO interpretation template using AVO attribute intercept P and gradient G calculated from seismic gathers near key well points; determining the range of the previously calculated AVO attribute intercept P and gradient G data volume in the corrected AVO interpretation template based on the porosity range of the effective reservoir within the target area to obtain the intercept and gradient data volume constrained by the AVO interpretation template; delineating the boundary between oil / gas and water based on the effective water saturation, and rotating the intersection diagram of the boundary line and the constrained intercept and gradient data volume to obtain the fluid detection results of the target layer within the target area.

[0006] Furthermore, the method for obtaining the intercept P data volume and the gradient G data volume is as follows: acquire the pre-stack common reflection point gather and the migrated seismic velocity volume within the target area; use the migrated seismic velocity volume to determine the incident angle range based on the minimum and maximum offset distances and the quality of the pre-stack common reflection point gather; convert the pre-stack common reflection point gather into an angle set based on the angle range; calculate the AVO attribute using the Zoeppritz equation to obtain the intercept P data volume and the gradient G data volume.

[0007] Furthermore, the method for constructing the AVO interpretation template is as follows: select a typical reservoir of the drilled target layer within the target area and collect drilling and logging data; determine the value range and interval of porosity and fluid saturation; select a seismic wavelet similar to the seismic frequency band, and based on the drilling and logging data, use the Zoeppritz equation or elastic wave equation to perform an AVO forward modeling simulation; based on the AVO forward modeling simulation, form the AVO interpretation template.

[0008] Furthermore, the method for forming an AVO interpretation scale based on the AVO forward modeling model is as follows: based on the AVO forward modeling model, and combined with the value range and interval of porosity and fluid saturation, calculate AVO model gathers for different porosities and different fluid saturations; based on the AVO model gathers, extract the AVO attributes of the top interface of the typical reservoir; plot the AVO attributes of the top interface of the typical reservoir in a rectangular coordinate system, with the intercept P as the abscissa and the gradient G as the ordinate, to form an AVO interpretation scale showing the variation of AVO attributes with porosity and fluid saturation.

[0009] Furthermore, the drilling logging data includes P-wave velocity, S-wave velocity, density, and formation thickness; the key well is a well in the target area with complete formation drilling, high-quality logging curves, and clear fluid interpretation results.

[0010] Furthermore, the method for calibrating and correcting the AVO interpretation scale using actual data from key wells is as follows: Select the pre-stack seismic gather corresponding to the target layer of the key well, and calculate the AVO attributes based on the pre-stack seismic gather; locate the corresponding theoretical PG data points in the AVO interpretation scale based on the measured reservoir parameters of the key well; compare the coordinates of the PG data points calculated from the well gather with the theoretical points, and calculate the deviation value between the two; adjust the order of magnitude of the AVO interpretation scale based on the deviation value to make it comparable to the AVO attributes generated by the actual seismic gather.

[0011] Furthermore, wells within the target area that were not calibrated were selected as verification wells. Their actual AVO attributes were extracted and compared with the corrected AVO interpretation scale to verify the universality and reliability of the AVO interpretation scale. If the actual data of the verification wells accurately fall into the reservoir-fluid category region corresponding to the AVO interpretation scale, it indicates that the calibration correction is effective. If there are still deviations, the AVO interpretation scale needs to be fine-tuned until it matches the AVO attributes of the target layer that has been drilled in the target area.

[0012] Furthermore, the method for constraining the intercept P and gradient G data range based on the AVO attribute quantization is as follows: according to the porosity range of the effective reservoir in the target area, the range of the AVO attribute intercept P and gradient G data volume is determined in the modified AVO interpretation quantization, and the intercept and gradient data volume constrained by the AVO interpretation quantization are obtained.

[0013] Furthermore, the method for delineating the boundary between oil and gas and water based on effective water saturation is as follows: Under the same porosity conditions, the boundary between oil and gas and water is delineated on the AVO interpretation scale according to the effective water saturation interpreted from the target area logging. Linear fitting is then performed on the AVO attribute points of fluid boundaries at different porosities to obtain the formula G=a Pb, where P is the intercept, G is the gradient, and a and b are constants.

[0014] Furthermore, the fluid detection method based on AVO attribute volume constraints is as follows: the constrained intercept and gradient data volume are processed using the aforementioned oil-gas-water boundary formula F=a PbG and F are fluid factors. The fluid detection data of the target layer in the target area are obtained. The larger the fluid factor F value, the more the AVO attribute deviates from the AVO background trend line, and the higher the probability of the reservoir containing oil and gas.

[0015] This invention also discloses a fluid detection system based on AVO attribute scale constraints, comprising: an AVO attribute calculation module for calculating AVO attributes based on pre-stack common reflection point gathers to obtain intercept P data volume and gradient G data volume; an AVO interpretation scale construction module for constructing an AVO interpretation scale based on typical reservoirs of the drilled target layer within the target area; a calibration correction module for calibrating and correcting the AVO interpretation scale using actual data from key wells; an AVO attribute constraint module for determining the range of AVO attributes in the corrected AVO interpretation scale based on the porosity range of the effective reservoir within the target area; and a fluid detection result output module for delineating the boundary between oil / gas and water based on the effective water saturation, rotating the intersection diagram of the boundary and AVO attributes to obtain the fluid detection results of the target layer within the target area.

[0016] The present invention also discloses a computer-readable storage medium storing a computer program that is executed by a processor to implement the fluid detection method based on AVO attribute quantization constraints as described in any of the preceding claims.

[0017] The technical solution of this invention has at least the following technical effects or advantages: Since rock physics models are usually based on the assumption of homogeneity and isotropy, while actual reservoirs are highly heterogeneous and have complex pore structures, the calculated elastic parameters after fluid replacement deviate from reality, leading to a discrepancy between the theoretical AVO interpretation scale and the actual response. This invention combines actual drilled well-side seismic data to calibrate and correct the AVO interpretation scale, ensuring that the scale conforms to the geological and geophysical conditions of the target area to the greatest extent possible, thereby improving the accuracy of fluid detection.

[0018] Using the effective water saturation cutoff value interpreted from drilled wells within the target area as the fluid boundary between oil and gas and water is more objective and applicable to the target area situation. Using the effective reservoir porosity cutoff value within the target area as the threshold for delineating the effective reservoir AVO attribute range can remove the influence of dry layers and obtain economically viable fluid anomaly prediction results. Combining geological and sedimentary understanding to determine the maximum porosity of the reservoir can minimize the ambiguity in fluid detection caused by special lithologies such as limestone and volcanic rocks and thin interbedded layers.

[0019] Therefore, fluid detection technology constrained by AVO interpretation scale eliminates interference from non-fluid factors to the greatest extent, significantly improving the accuracy of fluid detection. Attached Figure Description

[0020] Figure 1 This is a flowchart of a fluid detection method based on AVO attribute quantization constraints in one embodiment of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention is described in detail through specific embodiments. However, it should be understood that the specific embodiments are provided only for a better understanding of the present invention and should not be construed as limiting the present invention. In the description of the present invention, it should be understood that the terminology used is for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0022] To address the problems in existing technologies, such as discrepancies between calculated elastic parameters after fluid replacement and actual responses due to the fact that rock physics models are typically based on the assumption of homogeneity and isotropy, while actual reservoirs are highly heterogeneous and have complex pore structures, leading to inconsistencies between theoretical AVO interpretation scales and actual responses, this invention discloses a fluid detection method, system, and readable medium based on AVO attribute scale constraints. The method includes the following steps: calculating AVO attributes based on pre-stack common reflection point gathers to obtain intercept P data volumes and gradient G data volumes; constructing an AVO interpretation scale based on typical reservoirs of the drilled target layer within the target area; calibrating and correcting the AVO interpretation scale using actual data from key wells; determining the range of AVO attributes in the corrected AVO interpretation scale based on the porosity range of the effective reservoir within the target area; delineating the oil-gas and water boundary line based on the effective water saturation, and rotating the intersection diagram of the boundary line and AVO attributes to obtain the fluid detection results of the target layer within the target area. This invention effectively reduces the discrepancy between the theoretical AVO interpretation and the actual response, and fully utilizes regional geological findings, greatly improving the accuracy of seismic fluid detection. The invention will now be described in detail with reference to the accompanying drawings.

[0023] Example 1

[0024] This embodiment discloses a fluid detection method based on AVO attribute quantization constraints, such as... Figure 1 As shown, it includes the following steps: S1 calculates the AVO attribute based on the pre-stack common reflection point gather, and obtains the intercept P data volume and gradient G data volume.

[0025] The method for obtaining the intercept P data volume and gradient G data volume is as follows: acquire the drilled logging data, logging interpretation results, pre-stack common reflection point gathers, migrated seismic velocity volumes, and seismic horizon interpretation results within the target area; use the migrated seismic velocity volume to determine the incident angle range based on the minimum and maximum offset distances during seismic acquisition and the quality of the pre-stack common reflection point gathers; convert the pre-stack common reflection point gathers into angle gathers based on the angle range; calculate the AVO properties using the simplified Aki-Richards formula of the Zoeppritz equation to obtain the intercept P data volume and gradient G data volume.

[0026] In this embodiment, the drilling logging data includes P-wave velocity, S-wave velocity, and density, and the logging interpretation results include lithological interpretation curves, porosity, saturation, and effective reservoir porosity and saturation cutoff values.

[0027] S2 constructs an AVO interpretation scale based on typical reservoirs of the drilled target formations within the target area.

[0028] The method for constructing the AVO interpretation model is as follows: Typical reservoirs of the drilled target formation within the target area are selected, and drilling and logging data are collected. Based on the geological and sedimentary understanding of the area, the range and interval of porosity and fluid saturation values ​​are determined. Through well-seismic calibration, seismic wavelets of the target formation are extracted, and seismic wavelets with frequencies close to the seismic band are selected to ensure comparability between the AVO forward model and the well-side seismic gathers. Based on drilling and logging data, such as P-wave velocity, S-wave velocity, density, and formation thickness, the Zoeppritz equation or elastic wave equation is used. Cheng established an AVO forward simulation model; based on the AVO forward simulation model, and combined with the value range and interval of porosity and fluid saturation, calculated AVO model gathers for different porosities and fluid saturations; based on the AVO model gathers, extracted the AVO attributes of the top interface of typical reservoirs, such as intercept P and gradient G; plotted the AVO attributes of the top interface of typical reservoirs on a rectangular coordinate system, with intercept P as the abscissa and gradient G as the ordinate, to form an AVO interpretation scale showing the variation of AVO attributes with porosity and fluid saturation.

[0029] S3 calibrates and corrects the AVO interpretation scale using actual data from key wells.

[0030] Key wells are those with complete formation encounters within the target area, high-quality logging curves, and clear fluid interpretation results, ensuring that the data accurately reflects the true lithology and fluid characteristics of the reservoir.

[0031] The method for calibrating and correcting the AVO interpretation scale using actual data from key wells is as follows: Select the pre-stack seismic gathers corresponding to the target layer of the key well, and calculate the AVO attributes based on the pre-stack seismic gathers; locate the corresponding theoretical PG data points in the AVO interpretation scale based on the measured reservoir parameters of the key well, such as lithology, porosity, and fluid type; compare the PG data points calculated from the well gathers with the theoretical points on both the horizontal and vertical axes, and calculate the deviation value; adjust the order of magnitude of the AVO interpretation scale based on the deviation value to make it comparable to the AVO attributes generated by the actual seismic gathers. Select wells in the target area that were not calibrated as verification wells, extract their actual AVO attributes, and compare them with the corrected AVO interpretation scale to verify the universality and reliability of the AVO interpretation scale; if the actual data of the verification wells can accurately fall into the reservoir-fluid category region corresponding to the AVO interpretation scale, it indicates that the calibration correction is effective; if there is still a deviation, the AVO interpretation scale needs to be fine-tuned until the AVO interpretation scale matches the AVO attributes of the target layer that has been drilled in the target area.

[0032] Based on the lithology, physical properties, and fluid characteristics of the drilled target layer within the target area, and the geological and sedimentary understanding, S4 determines the distribution range of the minimum and maximum porosity of the effective reservoir within the target area, as well as the main lithological composition and fluid properties. The range of AVO attributes is then determined in the corrected AVO interpretation scale. The intercept P and gradient G calculated by S1 outside the determined AVO attribute range are set to 0, resulting in the intercept and gradient data volume constrained by the AVO interpretation scale. This minimizes the ambiguity in fluid detection caused by special lithologies such as carbonates and volcanic rocks, thin interbedded layers, and sidelobe AVO anomalies due to pre-stack gather far-channel frequency attenuation.

[0033] S5 defines the boundary between oil and gas and water based on the effective water saturation on the AVO interpretation scale. It then uses the boundary to calculate the constrained intercept and gradient data volume to obtain the target layer fluid detection results.

[0034] The method for delineating the boundary between oil / gas and water based on effective water saturation is as follows: Under the same porosity conditions, oil / gas layers are farther from the background trend of AVO attributes than water layers, and coordinate rotation can effectively distinguish the two. On the AVO interpretation scale, the boundary between oil / gas and water is delineated according to the effective water saturation interpreted from the target area logging. Linear fitting is performed on the AVO attribute points at the fluid boundary for different porosities to obtain the formula G=a Pb, where P is the intercept, G is the gradient, and a and b are constants. The constrained intercept and gradient data volume is then expressed using the formula F=a PbG and F are fluid factors. The fluid detection data of the target layer in the target area are obtained. The larger the fluid factor F value, the more the AVO attribute deviates from the AVO background trend line, and the higher the probability of the reservoir containing oil and gas.

[0035] This invention is highly feasible for exploration, development, and production, and can be applied without complex additional procedures. Its core innovation lies in breaking through the limitations of traditional seismic fluid detection by deeply integrating regional geological sedimentary understanding into the geophysical fluid detection process. This enables geophysical fluid detection based on geological understanding, significantly improving the accuracy and reliability of fluid detection results and providing more scientific technical support for exploration and development decisions.

[0036] Example 2 Based on the same inventive concept, this embodiment discloses a fluid detection system based on AVO property scale constraints, comprising: The AVO attribute calculation module is used to calculate the AVO attribute based on the pre-stack common reflection point gather, and obtain the intercept P data volume and gradient G data volume.

[0037] The AVO interpretation template construction module is used to construct AVO interpretation templates based on typical reservoirs of the drilled target formations within the target area.

[0038] The calibration correction module is used to calibrate and correct the AVO interpretation scale using actual data from key wells.

[0039] The AVO attribute constraint module is used to determine the range of AVO attributes in the corrected AVO interpretation scale based on the porosity range of the effective reservoir within the target area.

[0040] The fluid detection result output module is used to delineate the boundary between oil and gas and water based on the effective water saturation, rotate the intersection diagram of the boundary line and the AVO attribute, and obtain the fluid detection result of the target layer in the target area.

[0041] Example 3 Based on the same inventive concept, this embodiment discloses a computer-readable storage medium storing a computer program, which is executed by a processor to implement the fluid detection method based on AVO attribute quantization constraints as described above.

[0042] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0043] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0044] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0045] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific embodiments of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention. The above content is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims

1. A fluid detection method based on AVO attribute quantization constraints, characterized in that, Includes the following steps: Calculate AVO attributes based on the pre-stack common reflection point gather; Based on the typical reservoirs of the target formations that have been drilled in the target area, construct an AVO interpretation scale; The AVO interpretation scale was calibrated and corrected using actual data from key wells. Based on the porosity range of the effective reservoir within the target area, the range of AVO attributes obtained from the pre-stack common reflection point gather is determined in the corrected AVO interpretation scale, and the intercept and gradient data volume constrained by the AVO interpretation scale are obtained. The boundary between oil and gas and water is delineated based on the effective water saturation. The intersection diagram of the boundary line and the constrained intercept and gradient data volume is rotated to obtain the target layer fluid detection results.

2. The fluid detection method based on AVO attribute quantization constraints as described in claim 1, characterized in that, The method for calculating the AVO attribute is as follows: Obtain pre-stack common reflection point gathers and migrated seismic velocity volumes within the target area; Using the aforementioned offset seismic velocity volume, the range of incident angles is determined based on the minimum and maximum offset distances and the quality of the pre-stack common reflection point gathers. Based on the aforementioned angle range, the pre-stack common reflection point gather is converted into an angle set; The AVO properties are calculated using the Zoeppritz equation to obtain the intercept P data volume and the gradient G data volume.

3. The fluid detection method based on AVO attribute quantization constraints as described in claim 1, characterized in that, The method for constructing the AVO interpreter version is as follows: Select typical reservoirs of the target layer that have been drilled within the target area and collect drilling and logging data; Determine the range and interval of porosity and fluid saturation values; A seismic wavelet with a frequency band close to that of the earthquake was selected, and an AVO forward model was established based on well logging data using the Zoeppritz equation or the elastic wave equation. Based on the AVO forward simulation model, an AVO explanatory scale is generated.

4. The fluid detection method based on AVO attribute quantization constraints as described in claim 3, characterized in that, The method for generating the AVO explanatory scale based on the AVO forward simulation model is as follows: Based on the AVO forward model, and considering the range and interval of porosity and fluid saturation values, AVO model gathers with different porosities and fluid saturations are calculated. Based on the AVO model gather, extract the AVO attributes of the top interface of the typical reservoir; The AVO properties of the top interface of the typical reservoir are plotted in a rectangular coordinate system, with the intercept P as the abscissa and the gradient G as the ordinate, forming an AVO interpretation scale that shows the variation of AVO properties with porosity and fluid saturation.

5. The fluid detection method based on AVO attribute quantization constraints as described in claim 3, characterized in that, The drilling logging data includes P-wave velocity, S-wave velocity, density, and formation thickness; the key well is a well in the target area with complete formation encounters, high-quality logging curves, and clear fluid interpretation results.

6. The fluid detection method based on AVO attribute quantization constraints as described in claim 5, characterized in that, The method for calibrating and correcting the AVO interpretation scale using actual data from key wells is as follows: Select the pre-stack seismic gathers near the target layer of the key well, and calculate the AVO attribute based on the pre-stack seismic gathers near the well. Based on the measured reservoir parameters of the key wells, locate the corresponding theoretical PG data points in the AVO interpretation scale; The coordinates of the PG data points calculated by the wellside gathering are compared with the theoretical points, and the deviation between the two is calculated. The magnitude of the AVO interpretation scale is adjusted based on the deviation value to make it comparable to the AVO attributes generated from actual seismic gathers.

7. The fluid detection method based on AVO attribute quantization constraints as described in claim 6, characterized in that, Wells within the target area that were not calibrated were selected as verification wells. Their actual AVO attributes were extracted and compared with the corrected AVO interpretation scale to verify the universality and reliability of the AVO interpretation scale. If the actual data of the verification wells can accurately fall into the reservoir-fluid category region corresponding to the AVO interpretation scale, it indicates that the calibration correction is effective. If discrepancies still exist, the AVO interpretation scale needs to be fine-tuned until it matches the AVO properties of the target layer that has been drilled in the target area.

8. The fluid detection method based on AVO attribute quantization constraints as described in any one of claims 1-7, characterized in that, The method for delineating the boundary between oil and gas and water based on effective water saturation is as follows: Under the same porosity conditions, the boundary between oil and gas and water is delineated on the AVO interpretation scale according to the effective water saturation interpreted from the target area logging. Linear fitting is then performed on the AVO attribute points of the fluid boundary at different porosities to obtain the formula G=a Pb, where P is the intercept, G is the gradient, and a and b are constants. The constrained intercept and gradient data volume is then expressed using the formula F=a PbG and F are fluid factors. The fluid detection data of the target layer in the target area are obtained. The larger the fluid factor F value, the more the AVO attribute deviates from the AVO background trend line, and the higher the probability of the reservoir containing oil and gas.

9. A fluid detection system based on AVO attribute plate constraints, characterized in that, Includes the following steps: The AVO attribute calculation module is used to calculate the AVO attribute based on the pre-stack common reflection point gather, and obtain the intercept P data volume and gradient G data volume. The AVO interpretation template construction module is used to construct an AVO interpretation template based on the typical reservoirs of the drilled target formation within the target area. The calibration correction module is used to calibrate and correct the AVO interpretation scale using actual data from key wells. The AVO attribute constraint module is used to determine the range of AVO attributes obtained from the pre-stack common reflection point gather in the corrected AVO interpretation scale based on the porosity range of the effective reservoir in the target area, so as to obtain the intercept and gradient data volume after AVO interpretation scale constraint. The fluid detection result output module is used to delineate the boundary line between oil and gas and water based on the effective water saturation, and rotate the intersection diagram of the boundary line and the AVO attribute to obtain the fluid detection result of the target layer in the target area.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the fluid detection method based on AVO attribute quantization constraints as described in any one of claims 1-8.

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