Method and system for predicting formation pressure based on rock physics analysis data

Abstract

The present invention provides a method and system for predicting formation pressure based on rock physical analysis data, which extracts and analyzes various rock physical parameters corresponding to different depths of the target formation, sets measured points according to a set strategy, and constructs an initial abnormal pressure fitting model using the rock physical parameters and formation pressure data obtained according to the set scheme, and comprehensively sets various rock physical parameters of the measured points and measured pressure data and hydrostatic pressure data to optimize and train the constructed initial abnormal pressure fitting model to obtain a final abnormal pressure fitting model, and then inputs the depth parameters and rock physical parameters of the target formation, obtains the pressure anomaly data of the target formation, and then calculates the formation pressure. The above scheme can break through the limitations of traditional prediction technology for predicting formations, and has better applicability. In addition, this scheme uses detailed rock physical parameters as the data basis for formation pressure prediction, ensuring the high accuracy of the prediction results.

Description

Technical Field

[0001] The present invention relates to the technical field of formation exploration and interpretation, and in particular to a method and system for predicting formation pressure based on rock physics analysis data. Background Art

[0002] In the exploration of oil and gas fields, the formation pressure of oil and gas wells is the driving force for the flow of oil and gas and is an important parameter of oil and gas energy. Therefore, whether in the exploration and development of oil or natural gas, it is of great significance to study the pressure of the formation related to oil and gas exploration. Studying the distribution of oil and gas layer pressure can not only ensure safe and fast drilling, correctly design the medium specific gravity and engineering casing procedures, but also assist in selecting the type of drilling equipment and effective and safe completion plans. Secondly, in the process of oil and gas field development, accurate pressure prediction and pressure distribution research are of great significance for understanding the energy of underground oil and gas layers, controlling the changes in oil and gas layer pressure, and rationally utilizing the energy of oil and gas layers to maximize the extraction of underground oil and gas.

[0003] The existing technology mostly adopts a pressure prediction method based on compaction theory or a method for predicting formation pressure based on the relationship between formation pressure and the longitudinal wave velocity and transverse wave velocity of prestack elastic parameters. However, the applicability of the above two methods is greatly limited. They can only be applied to simple and shallow ordinary oil and gas field formations. When they are applied to complex oil and gas formations, such as fault zone formations or carbonate reservoirs, there are large errors in the accuracy of pressure prediction, which cannot meet the requirements of modern oil and gas exploration projects. Summary of the invention

[0004] To solve the above problems, the present invention provides a method for predicting formation pressure based on rock physical analysis data. In one embodiment, the method comprises:

[0005] A hydrostatic pressure calculation step, calculating hydrostatic pressure data corresponding to different depths of the target formation based on the formation water density of the target formation;

[0006] Rock physical analysis steps, extracting various rock physical parameters corresponding to different depths of the target stratum, and analyzing and classifying them to form a physical parameter data body;

[0007] The pressure model optimization step is to set the measured point set according to the set strategy, and optimize the built initial abnormal pressure fitting model based on the various rock physical parameters of each measured point in the first measured point set and the corresponding measured pressure data and hydrostatic pressure data to obtain the target abnormal pressure fitting model that best matches the target formation;

[0008] A pressure prediction step, using the depth parameter and rock physical property parameter of the target formation as inputs of the target abnormal pressure fitting model, obtaining the pressure abnormality data corresponding to the target formation, and calculating the formation pressure in combination with the hydrostatic pressure data;

[0009] The initial abnormal pressure fitting model is constructed based on the phase-controlled inversion result parameters and rock physical property parameters of each measured point in the second measured point set.

[0010] Preferably, in one embodiment, the method further comprises:

[0011] The phase-controlled model construction steps are to establish the corresponding phase-controlled model by taking the control effect of the structural characterization results of the fault-controlled reservoir of the test formation on the reservoir parameters as the geological constraint conditions.

[0012] Specifically, the pressure model optimization step includes:

[0013] According to the rock physical property parameters and formation pressure data of each measured point in the second measured point set, the phase-controlled model is used to invert and obtain the wave impedance data, velocity data and density data of the corresponding fault-controlled reservoir.

[0014] In one embodiment, the process of constructing the initial abnormal pressure fitting model includes:

[0015] A number of measured points are set for strata with different physical property parameters at different depths, and the first measured point set and the second measured point set are obtained based on the principle that each measured point set covers strata of all depth categories and all types of physical property parameters;

[0016] The depth, wave impedance, velocity and density data of the fault-controlled reservoir in the second measured point concentration are retrieved, the hydrostatic pressure data and the measured value of the formation pressure of the fault-controlled reservoir at the measured point are introduced, and the initial abnormal pressure fitting model corresponding to different rock physical property parameter distribution types is constructed.

[0017] Furthermore, in one embodiment, based on the characterization of the fault-controlled reservoir structure, a matching initial wave impedance is filled in for the formations corresponding to the distribution of different physical parameters, and low-frequency trend data of the formation is added to construct a phase-controlled model of the fault-controlled reservoir.

[0018] In one embodiment, in the hydrostatic pressure calculation step, the hydrostatic pressure value P of the target formation is obtained by the following formula: w :

[0019] P w =ρ w gH=1.09*9.8*H / 1000

[0020] Where ρ wis the formation water density of the target study area, and H is the depth of the target study reservoir.

[0021] Based on the method described in any one or more of the above embodiments, the present invention further provides a storage medium storing program codes that can implement the method described in any one or more of the above embodiments.

[0022] Based on other aspects of the method described in any one or more of the above embodiments, the present invention further provides a system for predicting formation pressure based on rock physical analysis data, the system comprising:

[0023] A hydrostatic pressure calculation module, configured to calculate hydrostatic pressure data corresponding to different depths of the target formation based on formation water density of the target formation;

[0024] A rock physics analysis module, which is configured to extract various rock physical property parameters corresponding to different depths of the target stratum, and analyze and classify them into a physical property parameter data body;

[0025] The pressure model optimization module is configured to set the measured point set according to the set strategy, optimize and train the built initial abnormal pressure fitting model based on various rock physical parameters of the measured points in the first measured point set and in combination with the corresponding measured pressure data and hydrostatic pressure data, so as to obtain the target abnormal pressure fitting model that best matches the target formation;

[0026] A pressure prediction module is configured to use the depth parameter and rock property parameter of the target formation as inputs of the target abnormal pressure fitting model, obtain pressure abnormality data corresponding to the target formation, and calculate the formation pressure in combination with the hydrostatic pressure data;

[0027] The initial abnormal pressure fitting model is constructed based on the phase-controlled inversion result parameters and rock physical property parameters of the test formation.

[0028] Furthermore, in a preferred embodiment, the system further comprises:

[0029] The phase-controlled model building module is configured to establish a corresponding phase-controlled model by taking the control effect of the structural characterization results of the test formation fault-controlled reservoir on the reservoir parameters as a geological constraint condition.

[0030] Compared with the closest prior art, the present invention also has the following beneficial effects:

[0031] The method and system for predicting formation pressure based on rock physics analysis data provided by the present invention successfully extend the new rock physics method to three-dimensional geological parameter analysis through the construction of a detailed formation pressure model, thereby establishing a formation pressure prediction technology system suitable for ultra-deep strike-slip fault zones and fault-controlled reservoirs in carbonate reservoirs, broadening the research field of pressure prediction of fault-controlled reservoirs in carbonate reservoirs, overcoming the defect of the incomplete application scope of existing prediction methods, and improving the accuracy of pressure prediction. It can guide the evaluation and deployment of fault zones and carbonate fault-controlled reservoirs, provide support for the optimization of well site selection and well trajectory design for exploration and development, give priority to drilling of large-scale fault-controlled reservoirs, thereby improving the success rate of drilling and enhancing the economic benefits of exploration and development.

[0032] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0034] Figure 1 is a flow chart of a method for predicting formation pressure based on rock physics analysis data in one embodiment of the present invention;

[0035] Figure 2 It is a list of pressure parameters of measured points in Shunbei area of ​​Tarim Basin using the present invention to predict formation pressure provided by an embodiment of the present invention;

[0036] Figure 3 It is a schematic diagram of a phase-controlled model of a fault-controlled reservoir constructed in a method for predicting formation pressure provided in an embodiment of the present invention;

[0037] Figure 4 It is a fitting analysis example of the velocity parameters of the interruption-controlling reservoir in the method for predicting formation pressure provided by an embodiment of the present invention;

[0038] Figure 5 is a fitting analysis diagram of residual impedance parameters in the method for predicting formation pressure provided in an embodiment of the present invention;

[0039] Figure 6 is a fitting analysis diagram of wave impedance parameters in the method for predicting formation pressure provided by an embodiment of the present invention;

[0040] Figure 7is a schematic diagram of a formation pressure analysis cross section of a method for predicting formation pressure based on rock physical analysis data in an embodiment of the present invention;

[0041] Figure 8 is a comparison chart of the formation pressure prediction result using the method of the embodiment of the present invention and the pressure coefficient prediction result using the Bowers technique;

[0042] Fig. 9 It is a schematic diagram of the structure of a system for predicting formation pressure based on rock physical analysis data in another embodiment of the present invention. DETAILED DESCRIPTION

[0043] The following will describe the implementation methods of the present invention in detail in conjunction with the accompanying drawings and embodiments, so that the implementers of the present invention can fully understand how the present invention applies technical means to solve technical problems and achieve the implementation process of technical effects and implement the present invention specifically according to the above implementation process. It should be noted that as long as there is no conflict, the various embodiments and various features of the embodiments in the present invention can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0044] Although the flowcharts describe the operations as sequential processes, many of the operations may be performed in parallel, concurrently, or simultaneously. The order of the operations may be rearranged. A process may be terminated when its operations are completed, but may also have additional steps not included in the accompanying drawings. A process may correspond to a method, function, procedure, subroutine, subprogram, etc.

[0045] Computer devices include user devices and network devices. Among them, user devices or clients include but are not limited to computers, smart phones, PDAs, etc.; network devices include but are not limited to a single network server, a server group consisting of multiple network servers, or a cloud composed of a large number of computers or network servers based on cloud computing. Computer devices can be operated alone to implement the present invention, or they can be connected to the network and implement the present invention through interactive operations with other computer devices in the network. The network where the computer device is located includes but is not limited to the Internet, wide area network, metropolitan area network, local area network, VPN network, etc.

[0046] The terms "first", "second", etc. may be used herein to describe various units, but these units should not be limited by these terms, and these terms are used only to distinguish one unit from another unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items. When a unit is referred to as being "connected" or "coupled" to another unit, it can be directly connected or coupled to the other unit, or there can be intermediate units.

[0047] The terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms "one", "one" and "item" used herein are also intended to include plural numbers. It should also be understood that the terms "include" and / or "comprise" used herein specify the existence of stated features, integers, steps, operations, units and / or components, without excluding the existence or addition of one or more other features, integers, steps, operations, units, components and / or combinations thereof.

[0048] In recent years, many experts have studied and discussed the theories and methods of formation pressure prediction for carbonate rock formations and other complex geological conditions and special rock properties. For carbonate rock formations in the target area, various pressure prediction methods based on compaction theory are not applicable. Currently, there are the following problems in the prediction of fault-controlled reservoir pressure in carbonate rock areas:

[0049] ① The abnormal pressure characteristics of carbonate formations are unclear, the cause mechanism is unclear, and the abnormal pressure poses a great challenge to drilling and well control safety;

[0050] ② The carbonate fault-controlled reservoir has complex reservoir characteristics and is difficult to analyze in terms of rock physics;

[0051] ③It is difficult to predict the carbonate formation pressure. It is difficult to accurately predict the carbonate formation pressure using the conventional undercompaction pressure prediction model;

[0052] ④ The abnormally high pressure in carbonate formations varies greatly in the lateral direction. It is difficult to predict the lateral distribution law, and the accuracy of the formation pressure prediction results cannot be guaranteed.

[0053] In view of the current complex geological conditions in the exploration and development of new oilfield areas, avoiding the previous method of attributing abnormal formation pressure to formation pressure prediction, making its application scope wider, is the future direction of the development of complex formation and special lithology formation pressure prediction. At the same time, with the application of artificial neural network, gray prediction theory and fuzzy mathematics in the processing of seismic data and well logging data, data processing methods are more extensive, and the accuracy of formation pressure prediction will be further improved.

[0054] In order to solve the shortcomings of existing formation pressure prediction methods, the researchers of this invention studied the fault-controlled reservoir pressure prediction method, which truly reflects the distribution characteristics of fault-controlled reservoirs, helps to recognize and discover new oil and gas layers, understand the energy of underground oil and gas layers, control the changes in oil and gas layer pressure, and rationally utilize the energy of oil and gas layers to maximize the extraction of underground oil and gas. This method is highly targeted and effective for carbonate reservoirs in a certain block, and has certain applicability and promotion as an empirical model derived from experiments or actual data.

[0055] Next, the detailed process of the method according to the embodiment of the present invention is described in detail based on the accompanying drawings. The steps shown in the flowchart of the accompanying drawings can be executed in a computer system including a set of computer executable instructions. Although the logical order of each step is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0056] Embodiment 1

[0057] In an embodiment of the present invention, a method for predicting the body pressure of a fault-controlled reservoir is studied. The method is a new method for stratum prediction based on rock physics and is applicable to strata in ultra-deep strike-slip fault zones and carbonate reservoirs.

[0058] Specifically, the researchers of the present invention considered that since the rock physics-based method has no restrictions on the lithology of the applied area and the mechanism of abnormal formation pressure, it is not necessary to establish a normal compaction trend line of the formation, and the principle of the fault-controlled reservoir pressure prediction method is suitable for carbonate formation pressure prediction, and designed the following technical concepts to predict the formation pressure of the target formation:

[0059] (1) Calculate the hydrostatic pressure at the same depth;

[0060] (2) Characterization of the structure of fault-controlled reservoirs and phase-controlled inversion to find the distribution law of abnormal formation pressure and obtain the relevant data body that ultimately characterizes the development characteristics of fault-controlled reservoirs;

[0061] (3) Through detailed rock physics analysis, a new rock physics model is developed to characterize the abnormal values ​​of formation pressure that deviate from the hydrostatic pressure;

[0062] (4) Extract various rock physical quantities in the target area, conduct detailed statistical analysis on the measured pressure data points, obtain the fitting results of pressure anomaly parameters, and determine the final model of the rock physical method for predicting formation pressure of fault-controlled reservoirs;

[0063] (5) Predict the formation pressure in the target area according to the final fitting relationship.

[0064] The embodiment of the present invention uses rock physics analysis to conclude that the fault-controlled reservoir collective impedance data body is most closely related to the overpressure anomaly of the formation pressure deviating from the hydrostatic pressure. Therefore, based on the relationship between the hydrostatic pressure of the formation in the target area and the formation pressure to be measured, the present invention uses the model obtained by optimizing the training according to the set scheme to predict the corresponding formation pressure data. Next, the specific implementation process is described in conjunction with the accompanying drawings.

[0065] Figure 1 A schematic diagram of a method for predicting formation pressure based on rock physical analysis data in Embodiment 1 of the present invention is shown, referring to Figure 1 It can be seen that the method includes the following steps.

[0066] The hydrostatic pressure calculation step calculates the hydrostatic pressure data corresponding to different depths of the target formation based on the formation water density of the target formation.

[0067] In practical applications, the hydrostatic pressure value P at a certain depth of the target formation w can be obtained by the following formula: w :

[0068] P w =ρ w gH=1.09*9.8*H / 1000

[0069] In the formula, ρ w is the formation water density of the target research area w, and H is the depth of the target research reservoir. After investigation, taking a 3D work area in Shunbei area of ​​Tarim Basin (hereinafter referred to as S3D) as an example, the formation water density value in this area is about 1.09 g / cm 3 .

[0070] Atashbari et al. mentioned in the SPE article published in 2012 that pore pressure (i.e., formation pressure) is essentially the sum of hydrostatic pressure and pressure anomaly (high pressure or low pressure) of the fault-controlled reservoir at the same depth. Therefore, it is further necessary to find the distribution law of abnormal formation pressure data. The embodiment of the present invention finds the distribution law of abnormal formation pressure through fault-controlled reservoir structure characterization and phase-controlled inversion, and then obtains the relevant data that finally characterizes the development characteristics of the fault-controlled reservoir. Based on this, the embodiment of the present invention first adopts the following steps to obtain the rock physical parameters of the target formation: rock physical analysis step, extracting various rock physical parameters corresponding to different depths of the target formation, and analyzing and classifying the formation of physical parameter data body;

[0071] Furthermore, the method also includes: a phase-controlled model construction step, using the control effect of the structural characterization results of the test formation fault-controlled reservoir on the reservoir parameters as a geological constraint condition to establish a corresponding phase-controlled model.

[0072] In one embodiment, based on the characterization of the fault-controlled reservoir structure, a matching initial wave impedance is filled in for the formation corresponding to the distribution of different physical parameters, and the low-frequency trend data of the formation is added to build a phase-controlled model of the fault-controlled reservoir. In practical applications, before building the phase-controlled model, the difference between the relative wave impedance of the stable formation and the actual relative wave impedance is usually obtained through the virtual well residual impedance technology as the residual impedance parameter of the corresponding fault-controlled reservoir, providing auxiliary support for accurately characterizing the porous and fractured reservoirs in the process of characterizing the fault-controlled reservoir structure.

[0073] Taking a 3D work area in Shunbei area of ​​Tarim Basin (hereinafter referred to as S3D) as an example, based on its Figure 2The measured point pressure parameter table is shown in FIG. 1 , and the schematic diagram of the phase control model of the fault-controlled reservoir constructed by the scheme in the above embodiment is shown in FIG. Figure 3 As shown in the figure, due to the structure of the fault-controlled reservoir as a constraint, the inversion result will be more consistent with the reservoir characteristics of the fault-controlled reservoir. Based on the phase-controlled model, wave impedance inversion is carried out to obtain the wave impedance data of the fault-controlled reservoir. At the same time, using the various parameters of wave impedance inversion, the velocity and density data of the fault-controlled reservoir can also be obtained as the basic data for predicting the formation pressure distribution.

[0074] The researchers of the present invention considered that through detailed rock physics analysis, a new rock physics model that can be used to characterize the abnormal values ​​of formation pressure deviating from hydrostatic pressure can be explored. According to the structural characterization of the fault-controlled reservoir and the phase-controlled inversion, the final data bodies such as residual impedance, wave impedance, velocity, density, etc. that characterize the development characteristics of the fault-controlled reservoir were obtained. Then, through detailed rock physics analysis, we can explore a new set of rock physics models that can be used to characterize the abnormal values ​​of formation pressure deviating from hydrostatic pressure.

[0075] Therefore, further, an embodiment of the present invention includes the following steps: a pressure model optimization step, setting a measured point set according to a set strategy, optimizing and training the established initial abnormal pressure fitting model based on various rock property parameters of each measured point in the first measured point set, and combining corresponding measured pressure data and hydrostatic pressure data to obtain a target abnormal pressure fitting model that best matches the target formation; wherein the initial abnormal pressure fitting model is constructed based on the phase-controlled inversion result parameters and rock physical property parameters of the test formation.

[0076] In this step, the data required in the pressure model optimization step is first obtained through the constructed phase-controlled model. The specific execution process is as follows:

[0077] According to the rock physical parameters and formation pressure data of each measured point in the second measured point set, the corresponding fault-controlled reservoir body impedance data, velocity data and density data are obtained by inversion using the phase control model. Taking the target formation in Shunbei area as an example, the statistical table of rock physical parameters of measured pressure data is shown in the following table:

[0078]

[0079] Among them, the fitting analysis diagram of the velocity parameters of the fault-controlled reservoir is as follows: Figure 4 As shown in the figure, the vertical axis parameter is the low-frequency inversion velocity data obtained by inverting the established phase-controlled model, and the horizontal axis parameter is the pressure coefficient associated with the fault-controlled reservoir velocity, which represents the ratio of the formation pore pressure to the hydrostatic pressure at the same depth, and is used to describe the amplitude of the abnormal formation pressure, which is a dimensionless parameter; the fitting analysis diagram of the residual impedance parameter is as follows Figure 5As shown in the figure, the residual impedance parameter is the value obtained by subtracting the actual relative impedance from the relative impedance of the stable formation obtained by the virtual well residual impedance technology; the fitting analysis diagram of the impedance parameter is as follows: Figure 6 As shown, Figure 6 The wave impedance data in is the low-frequency inversion impedance data obtained by inverting the established phase-controlled model.

[0080] Further, in one embodiment, the initial abnormal pressure fitting model is constructed based on the data obtained by the reverse inversion according to the following operations:

[0081] A number of measured points are set for strata with different physical property parameters at different depths, and the first measured point set and the second measured point set are obtained based on the principle that each measured point set covers strata of all depth categories and all types of physical property parameters;

[0082] The depth, residual impedance, wave impedance, velocity and density data of the fault-controlled reservoir at each measured point in the second measured point set are retrieved, and the hydrostatic pressure data and measured values ​​of the formation pressure of the fault-controlled reservoir at the measured point are introduced to construct the initial abnormal pressure fitting model corresponding to different rock physical property parameter distribution types.

[0083] Based on this, various rock physical parameters of the target area are extracted, and detailed statistical analysis is carried out in combination with the pressure data of each measured point in the first measured point set. Fitting training is carried out to finally determine the target abnormal pressure fitting model that matches the target formation.

[0084] Then, the formation pressure of the target area is predicted by the final model of the rock physics method for predicting the formation pressure of the fault-controlled reservoir, so there is a pressure prediction step, the depth parameter and rock physical property parameter of the target formation are used as the input of the target abnormal pressure fitting model, the pressure abnormality data corresponding to the target formation is obtained, and the formation pressure is calculated in combination with the hydrostatic pressure data. Figure 7 A schematic diagram of a formation pressure analysis cross section of a method for predicting formation pressure based on rock physical analysis data in an embodiment of the present invention is shown. In addition, Figure 8 A comparison chart of the effect of using the scheme of the present invention to predict formation pressure and the prediction result of the pressure coefficient using the Bowers technique is provided in Figure 7 and Figure 8 It can be seen from the information in that, compared with the existing technology, the method provided by the embodiment of the present invention can effectively achieve a wider prediction range and a higher prediction result accuracy.

[0085] The present invention broadens the research field of pressure prediction of fault-controlled reservoirs in carbonate reservoirs by using the fault-controlled reservoir pressure prediction method, improves the accuracy of pressure prediction, and uses the impedance inversion method under phase control to characterize the distribution of fault-controlled reservoirs in the study area. On this basis, a new method of pressure prediction based on rock physics is explored. Among them, through the construction of a detailed formation pressure model, the new rock physics method is successfully extended to three-dimensional geological parameter analysis, thereby establishing a formation pressure prediction technology system suitable for ultra-deep strike-slip fault zones and fault-controlled reservoirs in carbonate reservoirs. Based on the existing data, this solution has good applicability and promotion, and the research ideas and technical methods are highly feasible. It guides the evaluation and deployment of fault zones and carbonate fault-controlled reservoirs, provides support for the optimization of exploration and development well site selection and well trajectory design, and gives priority to drilling large-scale fault-controlled reservoirs, thereby improving the drilling success rate and enhancing the economic benefits of exploration and development.

[0086] In addition, it should be noted that, based on the method in any one or more of the above-mentioned embodiments of the present invention, the present invention also provides a storage medium, which stores program code that can implement the method as described in any one or more of the above-mentioned embodiments, and when the code is executed by the operating system, it can implement the method of predicting formation pressure based on rock physical analysis data as described above.

[0087] Embodiment 2

[0088] Based on other aspects of the method described in any one or more of the above embodiments, the present invention also provides a system for predicting formation pressure based on rock physical analysis data, and its structural schematic diagram is shown in FIG. Fig. 9 As shown, combined Fig. 9 According to the information disclosed in the system, the system includes:

[0089] A hydrostatic pressure calculation module, configured to calculate hydrostatic pressure data corresponding to different depths of the target formation based on formation water density of the target formation;

[0090] A rock physics analysis module, which is configured to extract various rock physical property parameters corresponding to different depths of the target stratum, and analyze and classify them into a physical property parameter data body;

[0091] The pressure model optimization module is configured to set the measured point set according to the set strategy, optimize and train the built initial abnormal pressure fitting model based on the various rock physical parameters of each measured point in the first measured point set and the corresponding measured pressure data and hydrostatic pressure data, and obtain the target abnormal pressure fitting model that best matches the target formation;

[0092] A pressure prediction module is configured to use the depth parameter and rock property parameter of the target formation as inputs of the target abnormal pressure fitting model, obtain pressure abnormality data corresponding to the target formation, and calculate the formation pressure in combination with the hydrostatic pressure data;

[0093] The initial abnormal pressure fitting model is constructed based on the phase-controlled inversion result parameters and rock physical property parameters of the test formation.

[0094] Furthermore, in one embodiment, the system further comprises:

[0095] The phase-controlled model building module is configured to establish a corresponding phase-controlled model by taking the control effect of the structural characterization results of the test formation fault-controlled reservoir on the reservoir parameters as a geological constraint condition.

[0096] In one embodiment, the pressure model optimization module is configured to: obtain corresponding fault-controlled reservoir body impedance data, velocity data and density data by inversion using the phase-controlled model according to the rock physical parameters and formation pressure data of each measured point in the second measured point set;

[0097] Specifically, in one embodiment, the pressure model optimization module is configured as follows: based on the characterization of the fault-controlled reservoir structure, a matching initial wave impedance is filled in for the formations corresponding to different physical property parameter distributions, and low-frequency trend data of the formation is added to construct a phase-controlled model of the fault-controlled reservoir.

[0098] Furthermore, in one embodiment, the pressure model optimization module is configured to perform the following operations to construct the initial abnormal pressure fitting model:

[0099] A number of measured points are set for strata with different physical property parameters at different depths, and the first measured point set and the second measured point set are obtained based on the principle that each measured point set covers strata of all depth categories and all types of physical property parameters;

[0100] The depth, residual impedance, wave impedance, velocity and density data of the fault-controlled reservoir at each measured point in the second measured point set are retrieved, the hydrostatic pressure data and the measured value of the formation pressure of the fault-controlled reservoir at the measured point are introduced, and the initial abnormal pressure fitting model corresponding to different rock physical property parameter distribution types is constructed.

[0101] In one embodiment, the hydrostatic pressure calculation module obtains the hydrostatic pressure value of the target formation w by the following formula:

[0102] P w =ρ w gH=1.09*9.8*H / 1000

[0103] In the formula, ρ wis the formation water density of the target study area, and H is the depth of the target study reservoir.

[0104] In the system for predicting formation pressure based on rock physical analysis data in the embodiment of the present invention, each module or unit structure can operate independently or in combination according to actual analysis or prediction requirements to achieve corresponding technical effects.

[0105] It should be understood that the embodiments disclosed in the present invention are not limited to the specific structures, processing steps or materials disclosed herein, but should be extended to equivalent substitutions of these features understood by ordinary technicians in the relevant field. It should also be understood that the terms used herein are only used for the purpose of describing specific embodiments and are not meant to be limiting.

[0106] The "one embodiment" mentioned in the specification means that a particular feature, structure or characteristic described in conjunction with the embodiment is included in at least one embodiment of the present invention. Therefore, the phrase "one embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0107] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A method for predicting formation pressure based on rock physical analysis data, characterized in that: The method comprises: A hydrostatic pressure calculation step, calculating hydrostatic pressure data corresponding to different depths of the target formation based on the formation water density of the target formation; Rock physical analysis steps: extracting various rock physical parameters corresponding to different depths of the target stratum, and analyzing and classifying them to form a physical parameter data body; Phase-controlled model construction steps: using the control effect of the structural characterization results of the fault-controlled reservoir of the test formation on the reservoir parameters as geological constraints to establish the corresponding phase-controlled model; The pressure model optimization step is to set the measured point set according to the set strategy, and optimize the established initial abnormal pressure fitting model based on the various rock physical parameters of each measured point in the first measured point set in combination with the corresponding measured pressure data and hydrostatic pressure data to obtain the target abnormal pressure fitting model that best matches the target formation; wherein the initial abnormal pressure fitting model is constructed based on the phase control inversion result parameters and rock physical parameters of each measured point in the second measured point set; A pressure prediction step, using the depth parameter and rock physical property parameter of the target formation as inputs of the target abnormal pressure fitting model, obtaining the pressure abnormality data corresponding to the target formation, and calculating the formation pressure in combination with the hydrostatic pressure data; In the pressure model optimization step, the process of constructing the initial abnormal pressure fitting model includes: A number of measured points are set for strata with different physical property parameters at different depths, and the first measured point set and the second measured point set are obtained based on the principle that each measured point set covers strata of all depth categories and all types of physical property parameters; According to the rock physical property parameters and formation pressure data of each measured point in the second measured point set, wave impedance data, velocity data and density data of the corresponding fault-controlled reservoir are obtained by inversion using the phase-controlled model; The depth, wave impedance, velocity and density data of the fault-controlled reservoir in the second measured point concentration are retrieved, the hydrostatic pressure data and the measured value of the formation pressure of the fault-controlled reservoir at the measured point are introduced, and the initial abnormal pressure fitting model corresponding to different rock physical property parameter distribution types is constructed.

2. The method according to claim 1, characterized in that The process of establishing a phase-controlled model includes: On the basis of the characterization of the fault-controlled reservoir structure, a matching initial wave impedance is filled in for the formations corresponding to the distribution of different physical parameters, and the low-frequency trend data of the formation is added to construct a phase-controlled model of the fault-controlled reservoir.

3. The method according to claim 1 or 2, characterized in that: Before establishing the phase-controlled model, the difference between the relative wave impedance of the stable formation and the actual relative wave impedance is obtained by the virtual well residual impedance technology as the residual impedance parameter of the corresponding fault-controlled reservoir, and the structural characterization of the fault-controlled reservoir is achieved based on the residual impedance parameter.

4. The method according to claim 1, characterized in that: In the hydrostatic pressure calculation step, the hydrostatic pressure value P of the target formation is obtained by the following formula: w : P w =ρ w gH=1.09*9.8*H / 1000 Where ρ w is the formation water density of the target study area, and H is the depth of the target study reservoir.

5. A storage medium, characterized in that: The storage medium stores program codes that can implement the method as claimed in any one of claims 1 to 4.

6. A system for predicting formation pressure based on rock physical analysis data, characterized in that: The system comprises: A hydrostatic pressure calculation module, configured to calculate hydrostatic pressure data corresponding to different depths of the target formation based on formation water density of the target formation; A rock physics analysis module, which is configured to extract various rock physical property parameters corresponding to different depths of the target stratum, and analyze and classify them into a physical property parameter data body; A phase-controlled model building module is configured to establish a corresponding phase-controlled model by taking the control effect of the structural characterization results of the fault-controlled reservoir of the test formation on the reservoir parameters as a geological constraint condition; A pressure model optimization module is configured to set a measured point set according to a set strategy, optimize and train the established initial abnormal pressure fitting model based on various rock physical parameters of the measured points in the first measured point set in combination with the corresponding measured pressure data and hydrostatic pressure data, and obtain a target abnormal pressure fitting model that best matches the target formation; wherein the initial abnormal pressure fitting model is constructed based on the phase control inversion result parameters and rock physical parameters of each measured point in the second measured point set of the test formation; A pressure prediction module is configured to use the depth parameter and rock property parameter of the target formation as inputs of the target abnormal pressure fitting model, obtain pressure abnormality data corresponding to the target formation, and calculate the formation pressure in combination with the hydrostatic pressure data; The pressure model optimization module is configured to perform the following operations to construct the initial abnormal pressure fitting model: A number of measured points are set for strata with different physical property parameters at different depths, and the first measured point set and the second measured point set are obtained based on the principle that each measured point set covers strata of all depth categories and all types of physical property parameters; According to the rock physical property parameters and formation pressure data of each measured point in the second measured point set, wave impedance data, velocity data and density data of the corresponding fault-controlled reservoir are obtained by inversion using the phase-controlled model; The depth, wave impedance, velocity and density data of the fault-controlled reservoir in the second measured point concentration are retrieved, the hydrostatic pressure data and the measured value of the formation pressure of the fault-controlled reservoir at the measured point are introduced, and the initial abnormal pressure fitting model corresponding to different rock physical property parameter distribution types is constructed.

7. The system according to claim 6, characterized in that The phase-controlled model building module is configured as follows: On the basis of the characterization of the fault-controlled reservoir structure, a matching initial wave impedance is filled in for the formations corresponding to the distribution of different physical parameters, and the low-frequency trend data of the formation is added to construct a phase-controlled model of the fault-controlled reservoir.

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