A pressure prediction method based on diagenesis correction

Abstract

The invention discloses a pressure prediction method based on diagenesis correction. Firstly, geological data, logging data and seismic data in a study area need to be collected, especially formation pressure test data including cable test data and drill pipe test data, etc.; abnormal response of the logging data can determine the abnormal pressure layer; secondly, using the Eaton method, the Eaton index corresponding to the measured pressure point is inverted by comprehensively measuring the measured formation pressure and the logging response; the relationship between the burial depth and the Eaton index is analyzed, and a suitable analytical expression is selected to establish a mapping relationship between the two to achieve n=f(H); wherein H is the burial depth and n is the Eaton index; finally, the predicted value and the measured value of the formation pressure before and after correction are compared to determine whether the improved accuracy meets the exploration and development requirements; the formation pressure prediction work of a three-dimensional work area is completed by combining the corrected pressure prediction method with the logging data and the seismic data.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas field exploration, and in particular to a pressure prediction method based on diagenesis correction. Background Art

[0002] The formation pressure state is a key factor affecting the flow of fluids in oil and gas basins. It is closely related to reservoir properties, oil and gas generation, migration and accumulation. In drilling engineering, formation pressure not only determines the density of drilling fluid and wellbore structure design, but also directly affects whether the drilling operation can be carried out safely, quickly and economically. Therefore, accurate prediction of formation pressure is an important part of oil and gas exploration and development.

[0003] There are various methods for predicting formation pressure in oil and gas basins with different sedimentary backgrounds, reflecting the technological progress and diversified needs in this field. At present, the methods for determining formation pressure are mainly divided into two categories: actual measurement method and pressure prediction method. Although the actual measurement method can provide accurate data, it is limited by cost and technical conditions. These data are often discrete point data and cannot fully reflect the pressure state of the entire formation. In addition, the actual measurement method is expensive and complex to implement, which limits its application in large-scale exploration and development.

[0004] In contrast, the pressure prediction method is more universal and practical, and it can be carried out through various methods such as well logging, seismic method and numerical simulation. The well logging method is based on detailed well logging data downhole, and can predict continuous formation pressure, providing a basis for drilling and completion. On the basis of the well logging method, the seismic method uses seismic data to reflect the formation pressure between wells, and can provide a three-dimensional continuous distribution of formation pressure bodies, providing more comprehensive information for the development of the entire oil and gas field.

[0005] Numerical simulation is a method that has developed rapidly in recent years. It simulates the generation and distribution of formation pressure by establishing a mathematical model. This method can comprehensively consider factors such as geological structure, fluid properties, temperature, stress state, etc. to make a more accurate prediction of formation pressure. However, numerical simulation has high requirements on the quality of input data and the accuracy of the model. Once the model setting or data input is wrong, the deviation of the prediction result may be large.

[0006] Although the existing pressure prediction technology has achieved certain results, its own limitations cannot be ignored. For example, although the well logging method can provide continuous formation pressure data, its prediction accuracy may be affected under certain complex geological conditions, such as overpressure formations and areas near faults. Although the seismic method can provide a three-dimensional pressure field, the uncertainty in the interpretation and processing of seismic data may also lead to deviations in the prediction results. Therefore, how to correct the pressure prediction method based on the sedimentary background of the study area and improve the prediction accuracy has become an important topic in the field of exploration and development.

[0007] In order to improve the prediction accuracy, researchers have tried to improve and optimize the method from multiple angles. First, strengthening the study of sedimentary background and understanding the characteristics and laws of formation pressure under different sedimentary environments will help improve the applicability and accuracy of the prediction method. Secondly, through multidisciplinary cooperation, integrating knowledge and technology from geology, geophysics, engineering technology, etc., we can have a more comprehensive understanding of the formation mechanism of formation pressure. Furthermore, using advanced data processing and analysis technologies, such as artificial intelligence and machine learning, to conduct in-depth analysis of formation pressure data can discover new laws and connections, thereby optimizing the prediction model.

[0008] In short, the development of formation pressure prediction technology is a process of continuous progress and improvement. Through continuous technological innovation and method optimization, the accuracy of formation pressure prediction can be effectively improved, providing strong technical support for the safe and efficient development of oil and gas fields.

[0009] To this end, we propose a pressure prediction method based on diagenesis correction. Summary of the invention

[0010] The object of the present invention is to provide a pressure prediction method based on diagenesis correction to solve the problems raised in the above background technology.

[0011] To achieve the above object, the present invention provides the following technical solution: a pressure prediction method based on diagenesis correction, comprising the following steps:

[0012] Obtain basic geological, well logging and seismic data of the study area;

[0013] Analyze the seismic response characteristics of normally compacted and overpressured formations through seismic data;

[0014] Using the logging data, a logging response characteristic is obtained, and the overpressure development layer section is determined by using the logging response characteristic, and the logging response characteristic value of the abnormal pressure formation is determined;

[0015] In combination with the logging response characteristic value of the abnormal pressure formation, a normal compaction trend of the acoustic wave time difference is established;

[0016] Determine the formation water density in the study area based on the geological data obtained, and then calculate the hydrostatic pressure;

[0017] Combined with the acquired logging response characteristics, the overlying rock pressure is calculated;

[0018] Inverting the Eaton index in combination with the formation test data;

[0019] Combine the burial depth and Eaton index in the basic geology to establish a mapping relationship between the burial depth and Eaton index;

[0020] The mapping relationship is brought into the Eaton method formation pressure calculation formula to calculate the predicted formation pressure;

[0021] Analyze the accuracy and stability of pressure prediction based on the basic geological, logging and seismic data of the study area and the data obtained by calculating and predicting formation pressure;

[0022] The three-dimensional formation pressure field is predicted by combining the data obtained based on the basic geological, logging and seismic data of the study area and the calculated predicted formation pressure.

[0023] As a preferred technical solution of the present invention, the basic geological, logging and seismic data of the study area are obtained as follows: geological data include regional sedimentary background, formation test data, sedimentary phase type and physical property characteristics of the reservoir; logging data include logging lithology information and conventional logging data, conventional logging data include natural gamma, acoustic wave time difference, neutron and density data; seismic data include post-stack seismic data and three-dimensional velocity field data.

[0024] As a preferred technical solution of the present invention, the normal compaction trend of the acoustic time difference is established in combination with the logging response characteristic value of the abnormal pressure formation, specifically including calculating ACn as the normal compaction trend of the acoustic time difference, which is related to the burial depth H, wherein AC0 is the acoustic time difference of the near-surface formation, H is the burial depth, a and b are constants, and the formula is:

[0025] ACn=a*AC0 / e b*H .

[0026] As a preferred technical solution of the present invention, the hydrostatic pressure calculation formula is:

[0027] P w =ρ w HkDJ

[0028] where ρ w is the density of formation water, g is the acceleration due to gravity, and H is the burial depth.

[0029] As a preferred technical solution of the present invention, the calculation formula for the overlying rock pressure is:

[0030]

[0031] Where S V is the overlying rock pressure, ρ b is the volume density of rock, g is the acceleration of gravity, and H is the burial depth.

[0032] As a preferred technical solution of the present invention, the inversion of the Eaton index is to derive the Eaton index corresponding to the burial depth by combining the Eaton method formation pressure calculation formula with the measured pressure. The formula is:

[0033]

[0034] Among them, P f is the formation pressure; P w is the hydrostatic pressure; S V is the overlying rock pressure; ACn and AC are the acoustic time difference of normal formation and measured formation respectively; C is the Eaton index, also known as the compaction correction coefficient.

[0035] The formation test data obtained from S1 can determine the measured pressure, that is, P f As a known quantity, the Eaton index can be derived by combining the formation pressure calculation formula of the Eaton method, namely:

[0036]

[0037] From this, the Eaton index corresponding to the burial depth of the measured pressure can be calculated.

[0038] As a preferred technical solution of the present invention, the mapping relationship is established by combining the burial depth and Eaton index in the basic geology, intersecting the two to further analyze their relationship, and fitting the burial depth and Eaton index with constant function, power function, exponential function, logarithmic function, trigonometric function and inverse trigonometric function respectively, and optimizing the mapping relationship with the best correlation, and obtaining: C=f(H), so as to achieve the goal of correcting the Eaton index with burial depth.

[0039] As a preferred technical solution of the present invention, the calculation and prediction of formation pressure is specifically to substitute the correction relationship obtained in S8 into the Eaton method formation pressure calculation formula:

[0040]

[0041] The Eaton method can be corrected to overcome the deficiency that the conventional Eaton method often takes the regional empirical constant for the Eaton index.

[0042] As a preferred technical solution of the present invention, the accuracy and stability of the analysis pressure prediction are specifically: combining S1 and S9 to compare and analyze the measured pressure and the predicted pressure, evaluating the degree of deviation of the predicted pressure through the intersection diagram of the measured pressure and the predicted pressure, and further calculating the relative error to quantify the accuracy and stability of the pressure prediction method.

[0043] As a preferred technical solution of the present invention, the three-dimensional formation pressure field is predicted by combining the three-dimensional velocity field and substituting it into the corrected formation pressure prediction formula to obtain the three-dimensional formation pressure.

[0044] Beneficial effects:

[0045] The present invention corrects the Eaton method on the basis of the method, inheriting the advantages of the Eaton method while avoiding the uncertainty of pressure prediction caused by the conventional Eaton method taking the regional constant of the Eaton index. Taking into account the diagenesis of rocks, the Eaton index is corrected using the burial depth, which improves the stability and accuracy of formation pressure prediction. The present invention has been successfully applied to the overpressure prediction of a reservoir section in a basin. The prediction accuracy of the corrected formation pressure prediction method is improved by about 10% compared with the conventional Eaton method. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of pressure prediction based on diagenesis correction of the present invention;

[0047] Figure 2 It is the overpressure logging response characteristic diagram of a well in a basin;

[0048] Figure 3 It is the rock density-velocity intersection diagram under different overpressure genesis types;

[0049] Figure 4 It is the formation pressure diagram predicted by different pressure prediction methods for a certain well;

[0050] Figure 5 This is a comparison chart of relative errors of different pressure prediction methods for a certain well;

[0051] Figure 6 This is a comparison chart between the formation pressure predicted by different pressure prediction methods and the measured pressure of a certain well. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] The present invention provides a pressure prediction method based on diagenesis correction ( Figure 1 ) is used to overcome the shortcomings of the conventional Eaton method in taking regional constants for the Eaton index, improve the accuracy and stability of sandstone and mudstone formation pressure prediction, and lay the foundation for safe and effective production and development of oil and gas fields. The specific method steps include the following:

[0054] 1. Obtain basic geological, logging and seismic data in the study area. Geological data should include regional sedimentary background, formation test data such as cable test data (FRT) and drill stem test (DST) data, reservoir sedimentary phase type and physical properties. Logging data should include logging lithology information and conventional logging data such as natural gamma, acoustic time difference, neutron and density. Seismic data should include post-stack seismic data and three-dimensional velocity field data.

[0055] By providing more comprehensive geological data analysis, including lithology information and structural characteristics of the formation, the pressure environment of the formation can be more accurately assessed, thereby providing higher security and reduced risk for oil and gas exploration and development. Detailed lithology and structural data help predict and manage potential geological risks, such as formation slip and pressure anomalies.

[0056] 2. Seismic response characteristics. When the formation is under normal compaction, the compaction effect gradually increases with the increase of burial depth, resulting in a gradual decrease in porosity, so the speed of seismic waves propagating in the formation becomes faster and faster with the burial depth. When the formation is under-compacted, because the compaction degree of the rock is low, the rock porosity will be higher than that of the normal pressure formation, resulting in abnormal propagation of seismic waves in the formation, that is, the speed decreases. Therefore, the magnitude of formation pressure can be reflected by the magnitude of seismic wave velocity. The precise formation physical data provided by laboratory tests make the pressure prediction model more reliable. These data help calibrate numerical models, reduce prediction errors, and ensure the safety of drilling and production activities.

[0057] Through the joint analysis of seismic data and well logging data, overpressure formations and normal compaction formations can be more effectively identified, thereby optimizing drilling plans and improving drilling efficiency. The comprehensive analysis of the three-dimensional velocity field provided by seismic data and the physical response characteristics in well logging data makes pressure prediction more accurate and reduces uncertainty in exploration and development.

[0058] 3. Logging response characteristics. Overpressure is widely distributed in oil and gas basins, such as the Gulf Coast Basin, the North Sea Basin, the Malay Basin, and the Bohai Bay Basin. Determining the overpressure development interval based on logging response characteristics is one of the most commonly used and most reliable methods ( Figure 2 ). Generally, a single type of logging curve can only reflect the specific physical properties of the target formation. Therefore, it is strongly recommended to combine different types of logging data to indicate the overall composition, structure and organic matter content of the formation to determine the local overpressure development layer. Usually, when the acoustic wave, resistivity, neutron and density logging have obvious deviation trends, it indicates that the formation has abnormal pressure. Different causes of overpressure have different logging response characteristics due to different mechanical mechanisms ( Figure 3 ).

[0059] The analysis of historical data can provide a basis for the validation of prediction models and ensure the effectiveness of new models in practical applications. By learning from past cases, it is possible to identify which factors play a decisive role in pressure prediction and which methods are more effective in specific geological settings. The accumulation of this methodology greatly improves the success rate of future projects and reduces economic losses caused by prediction errors.

[0060] As the depth of the normal pressure formation increases, the porosity will gradually decrease, and the formation velocity, density and resistivity will gradually increase. For the overpressure formation caused by undercompaction, the porosity will be larger than that of the normal pressure formation, the formation velocity, density and water layer resistivity will decrease, and the resistivity of the oil and gas layer will increase. The formation with tectonic compression overpressure is further compacted, the porosity decreases, the formation velocity, density and water layer resistivity will increase, and the resistivity of the oil and gas layer will decrease. Because the clay mineral conversion overpressure involves the physical and chemical reactions between clay minerals and formation water, the logging response characteristics of the rock will be more complicated. It is generally believed that the clay mineral conversion overpressure will have a slight increase in porosity compared with the normal pressure formation, the density may increase slightly, the velocity change is not obvious, and the resistivity may decrease. Fluid expansion overpressure Because the expansion of the fluid will reopen the pores connected to the rock, the porosity and density are not much different from those of the normal pressure formation, while the velocity and resistivity may decrease.

[0061] 4. Establish a normal compaction trend. Combined with the logging response characteristics of the abnormal pressure formation in step 3, divide the abnormal pressure development layer and the normal pressure formation section on the well. Generally, the shallow layer is mostly normal sedimentary formation, so the normal compaction trend can be determined based on the shallow logging data. The present invention is based on the optimization of the Eaton method. In order to smoothly carry out the following steps, it is only necessary to establish the normal compaction trend of the acoustic time difference: ACn = a*AC0 / e b*H Where ACn is the normal compaction trend of acoustic transit time, which is generally related to the burial depth H, AC0 is the acoustic transit time of the near-surface stratum, H is the burial depth, and a and b are constants.

[0062] Advanced numerical simulation techniques can process and analyze large amounts of geological and physical data to provide more accurate and comprehensive predictions of formation pressure. The application of these technologies is not limited to pressure prediction, but can also be used to simulate the development process of oil and gas reservoirs and optimize production strategies. In addition, the introduction of machine learning algorithms can automatically learn and identify patterns from historical data, thereby providing dynamic prediction adjustments under changing geological conditions.

[0063] 5. Calculate the hydrostatic pressure. After the formation water density of the study area is determined based on geological data, the hydrostatic pressure is calculated by the following formula: P w =ρ w gH. w is the density of formation water, g is the acceleration due to gravity, and H is the burial depth.

[0064] 6. Calculate overburden pressure. Overburden pressure is the basis for the analysis of wellbore, sedimentary structure and basin formation pressure. If the change of bulk density with depth is known, then the overburden pressure can be obtained by simply integrating the bulk density from the surface to the target depth:

[0065]

[0066] Where S V is the overlying rock pressure, ρ b is the volume density of rock, g is the acceleration of gravity, and H is the burial depth.

[0067] Accurate calculation of hydrostatic pressure and overburden rock pressure provides the basis for the assessment of formation pressure. This precise calculation method can effectively guide the safe drilling and development of oil and gas wells and avoid formation collapse and other related risks caused by inaccurate pressure assessment.

[0068] 7. Invert the Eaton index. The Eaton method calculates formation pressure in the form of:

[0069]

[0070] Among them, P f is the formation pressure; P w is the hydrostatic pressure; S V is the overlying rock pressure; ACn and AC are the acoustic time difference of normal formation and the acoustic time difference of measured formation respectively; C is the Eaton index, also known as the compaction correction coefficient. In addition, ACn has been calculated by step 4.

[0071] The formation test data obtained from step 1 can determine the measured pressure, that is, P f is a known quantity. Combined with the formation pressure calculation formula of Eaton method, the Eaton index can be derived, namely:

[0072]

[0073] From this, the Eaton index corresponding to the burial depth of the measured pressure can be calculated.

[0074] The improved Eaton index calculation method can more accurately evaluate and predict the actual pressure state of the formation, especially under complex geological conditions. The optimized Eaton index helps to improve the adaptability and accuracy of the prediction model, especially in unconventional oil and gas reservoirs and complex formation structures.

[0075] 8. Establish a mapping relationship. Combining steps 1 and 7, we can obtain the burial depth and Eaton index. We can further analyze their relationship by intersecting the two. Use constant function, power function, exponential function, logarithmic function, trigonometric function and inverse trigonometric function to fit the burial depth and Eaton index respectively, and select the mapping relationship with the best correlation to obtain: C = f(H). This can achieve the goal of using burial depth to correct the Eaton index.

[0076] By establishing a mapping relationship between burial depth and Eaton index and applying it to the prediction and correction of formation pressure, the prediction accuracy of Eaton method can be significantly improved. The establishment of this correction relationship helps to overcome the limitations of regional empirical constants commonly used in traditional methods, making the formation pressure prediction more consistent with actual geological conditions and improving the stability and accuracy of the prediction.

[0077] 9. Calculate and predict formation pressure. Substitute the correction relationship obtained in step 8 into the Eaton method formation pressure calculation formula:

[0078]

[0079] The Eaton method can be corrected to overcome the shortcomings of the conventional Eaton method, which often uses regional empirical constants for the Eaton index. The formation pressure calculated by the Eaton method before and after correction is shown in Figure 4 .

[0080] 10. Analyze the accuracy and stability of pressure prediction. Combine steps 1 and 9 to compare and analyze the measured pressure and the predicted pressure. Generally, the deviation of the predicted pressure can be evaluated by the intersection diagram of the measured pressure and the predicted pressure, and the accuracy and stability of the pressure prediction method can be further quantified by calculating the relative error ( Figure 5 and Figure 6 ). The combined use of formation pressure prediction and risk assessment tools can systematically identify and manage risks in geological exploration and development. By identifying high-risk areas of formation pressure, corresponding preventive measures can be taken, such as selecting appropriate wellbore stabilization technology and optimizing drilling fluid parameters. The implementation of risk management strategies helps prevent environmental accidents, protect the safety of operators, and ensure the continuity and efficiency of oil and gas production.

[0081] 11. Predict the three-dimensional formation pressure field. Combine the three-dimensional velocity field and substitute it into the corrected formation pressure prediction formula to obtain the three-dimensional formation pressure.

[0082] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0083] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A pressure prediction method based on diagenesis correction, characterized in that: The steps include: S1: Obtain basic geological, logging and seismic data of the study area; S2: Analyze the seismic response characteristics of normally compacted and overpressured formations through seismic data; S3: using the logging data to obtain logging response characteristics, and using the logging response characteristics to determine the overpressure development layer section, and determine the logging response characteristic value of the abnormal pressure formation; S4: establishing a normal compaction trend of the acoustic wave time difference in combination with the logging response characteristic value of the abnormal pressure formation; S5: Determine the formation water density of the study area based on the geological data obtained, and then calculate the hydrostatic pressure; S6: Calculate the overlying rock pressure by combining the acquired logging response characteristics; S7: Inverting the Eaton index based on the formation test data; S8: combining the burial depth and Eaton index in the basic geology, and establishing a mapping relationship between the burial depth and Eaton index; S9: Bringing the mapping relationship into the Eaton method formation pressure calculation formula to calculate the predicted formation pressure; S10: Analyze the accuracy and stability of pressure prediction based on the basic geological, logging and seismic data of the study area and the data obtained by calculating and predicting formation pressure; S11: Predicting the three-dimensional formation pressure field by combining the data obtained from the basic geological, logging and seismic data of the study area and the calculated predicted formation pressure; The mapping relationship is established by combining the burial depth and Eaton index in the basic geology, intersecting the two to further analyze the relationship, respectively fitting the burial depth and Eaton index with a constant function, a power function, an exponential function, a logarithmic function, a trigonometric function and an inverse trigonometric function, and optimizing the mapping relationship with the best correlation, and obtaining: C=f(H), where C is the Eaton index, also known as the compaction correction coefficient, and H is the burial depth, so as to achieve the goal of correcting the Eaton index with the burial depth; The calculation and prediction of the formation pressure is specifically to substitute the correction relationship obtained in S8 into the Eaton method formation pressure calculation formula: Among them, P f is the formation pressure; P w is the hydrostatic pressure; S V is the overlying rock pressure; ACn and AC are the acoustic time difference of normal formation and the acoustic time difference of measured formation respectively; The Eaton method can be corrected to overcome the deficiency that the conventional Eaton method often takes the regional empirical constant for the Eaton index.

2. A pressure prediction method based on diagenesis correction according to claim 1, characterized in that: The basic geological, logging and seismic data obtained in the study area are specifically as follows: geological data include regional sedimentary background, formation test data, sedimentary phase type and physical property characteristics of the reservoir; logging data include logging lithology information and conventional logging data, conventional logging data include natural gamma, sonic time difference, neutron and density data; seismic data include post-stack seismic data and three-dimensional velocity field data.

3. The pressure prediction method based on diagenesis correction according to claim 1, characterized in that: The normal compaction trend of the acoustic time difference is established by combining the logging response characteristic value of the abnormal pressure formation, specifically including calculating ACn as the normal compaction trend of the acoustic time difference, which is related to the burial depth H, wherein AC0 is the acoustic time difference of the near-surface formation, H is the burial depth, a and b are constants, and the formula is: ACn=a*AC0 / e b*H 。 4. The pressure prediction method based on diagenesis correction according to claim 1, characterized in that: The hydrostatic pressure calculation formula is: P w =ρ w gH where ρ w is the density of formation water, g is the acceleration due to gravity, and H is the burial depth.

5. The pressure prediction method based on diagenesis correction according to claim 1, characterized in that: The calculation formula for the overlying rock pressure is: Where S V is the overlying rock pressure, ρ b is the volume density of rock, g is the acceleration of gravity, and H is the burial depth.

6. The pressure prediction method based on diagenesis correction according to claim 1, characterized in that: The inversion of the Eaton index is to derive the Eaton index corresponding to the burial depth by combining the Eaton method formation pressure calculation formula with the measured pressure. The formula is: Among them, P f is the formation pressure; P w is the hydrostatic pressure; S V is the overlying rock pressure; ACn and AC are the acoustic time difference of normal formation and the acoustic time difference of measured formation respectively; C is the Eaton index, also known as the compaction correction coefficient; The formation test data obtained from S1 can determine the measured pressure, that is, P f As a known quantity, the Eaton index can be derived by combining the formation pressure calculation formula of the Eaton method, namely: From this, the Eaton index corresponding to the burial depth of the measured pressure can be calculated.

7. The pressure prediction method based on diagenesis correction according to claim 1, characterized in that: The accuracy and stability of the pressure prediction analysis are specifically as follows: combining S1 and S9 to compare and analyze the measured pressure and the predicted pressure, evaluating the deviation of the predicted pressure through the intersection diagram of the measured pressure and the predicted pressure, and further calculating the relative error to quantify the accuracy and stability of the pressure prediction method.

8. The pressure prediction method based on diagenesis correction according to claim 1, characterized in that: The three-dimensional formation pressure field is predicted by combining the three-dimensional velocity field and substituting it into the corrected formation pressure prediction formula to obtain the three-dimensional formation pressure.

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