Method and device for determining a pressure coefficient

Abstract

The application discloses a pressure coefficient determination method and device. The method comprises the following steps: determining the relationship between the effective stress and the P-wave velocity and the shale content of a target area based on drilling data and logging data; determining the P-wave inversion velocity, the S-wave inversion velocity and the lithology probability volume of the target area through pre-stack deterministic inversion and pre-stack geostatistics inversion based on seismic data, drilling data and logging data; determining the overburden pressure and the hydrostatic pressure of the target area by constructing a full formation density volume model based on the seismic data, the P-wave inversion velocity, the S-wave inversion velocity and the lithology probability volume of the target area; and determining the pressure coefficient of the target area based on the relationship between the effective stress and the P-wave velocity and the shale content of the target area, the P-wave inversion velocity, the S-wave inversion velocity and the lithology probability volume of the target area, and the overburden pressure and the hydrostatic pressure of the target area. The method can improve the prediction accuracy of the pressure coefficient.

Description

Technical Field

[0001] This application relates to the field of geophysical signal interpretation technology, and in particular to a method and apparatus for determining pressure coefficients. Background Technology

[0002] The pressure coefficient is an important reservoir parameter in geological areas containing oil and gas, reflecting the energy inherent in the oil and gas fluids themselves. A higher pressure coefficient indicates higher oil and gas production and stronger sustainable production capacity in that geological area.

[0003] In related technologies, the P-wave velocity method, which considers lithological variations, is mainly used to predict the pressure coefficient. By considering various factors affecting P-wave velocity variations, a lithological model is constructed to calculate the pressure coefficient. In constructing this lithological model, a clay content indicator obtained by normalizing gamma-ray intensity (GR) values ​​is typically used to characterize the clay content. However, when the clay content varies significantly in the actual area, the constructed lithological model may be inaccurate, leading to inaccurate pressure coefficient predictions. Summary of the Invention

[0004] In view of this, this application provides a method and apparatus for determining the pressure coefficient, which can solve the problem of inaccurate pressure coefficient prediction in the prior art and improve the prediction accuracy of the pressure coefficient.

[0005] Specifically, the following technical solutions are included:

[0006] On one hand, embodiments of this application provide a method for determining a pressure coefficient, the method comprising:

[0007] Obtain drilling, logging, and seismic data from sample wells in the target area within the target formation;

[0008] Based on the drilling data and the logging data, the relationship between the effective stress in the target area and the P-wave velocity and clay content is determined.

[0009] Based on the seismic data, drilling data, and well logging data, the lithological planar distribution characteristics and vertical sand-mud ratio of the target area are determined through pre-stack deterministic inversion.

[0010] Based on the seismic data, the lithological planar distribution characteristics of the target area, and the vertical sand-mud ratio, the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area are determined through pre-stack geostatistical inversion.

[0011] Based on the seismic data, the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area, the overlying strata pressure and hydrostatic pressure of the target area are determined by constructing a full-stratum density volume model.

[0012] Based on the relationship between the effective stress, P-wave velocity, and clay content of the target area, the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area, as well as the overlying strata pressure and hydrostatic pressure of the target area, the pressure coefficient of the target area is determined.

[0013] In some embodiments, determining the relationship between effective stress in the target area and P-wave velocity and clay content based on the drilling data and the logging data includes:

[0014] Based on the drilling data and the logging data, the effective stress, P-wave velocity and clay content of the target formation and the functional relationship to be fitted are obtained.

[0015] Based on the functional relationship to be fitted, a multivariate nonlinear regression fitting is performed on the data of effective stress, P-wave velocity and clay content of the target layer to obtain the functional relationship between effective stress, P-wave velocity and clay content in the target area.

[0016] In some embodiments, the seismic data includes seismic attribute data, the well logging data includes P-wave velocity, S-wave velocity, and geological density data of sample wells, and the drilling data includes stratigraphic data of sample wells; the step of determining the lithological planar distribution characteristics and vertical sand-slurry ratio of the target area through pre-stack deterministic inversion based on the seismic data, the drilling data, and the well logging data includes:

[0017] Pre-stack deterministic inversion is performed on the seismic attribute data, the P-wave velocity, the S-wave velocity, the geological density data of the sample wells, and the stratigraphic data of the sample wells to obtain the pre-stack deterministic inversion results.

[0018] Based on the pre-stack deterministic inversion results and the seismic attribute data, the lithological planar distribution characteristics and vertical sand-mud ratio of the target area are determined.

[0019] In some embodiments, the seismic data includes seismic attribute data; the step of determining the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area based on the seismic data, the lithological planar distribution characteristics of the target area, and the vertical sand-mud ratio, through pre-stack geostatistical inversion, includes:

[0020] Based on geostatistical parameters, pre-stack geostatistical inversion is performed on the seismic attribute data, the lithological planar distribution characteristics, and the vertical sand-mud ratio to determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area.

[0021] In some embodiments, determining the overlying strata pressure and hydrostatic pressure of the target area by constructing a full-stratum density volume model based on the seismic data, the P-wave inversion velocity, the S-wave inversion velocity, and the lithology probability volume of the target area includes:

[0022] The seismic data is subjected to depth migration processing to obtain depth-migrated seismic data;

[0023] Based on the depth-migrated seismic data, a depth-migrated velocity field model is constructed;

[0024] Substituting the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target region into the depth migration velocity field model, we obtain the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume after depth migration.

[0025] Based on the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume after the depth migration, the whole-stratum density volume model is constructed.

[0026] Based on the full-formation density volume model, the overlying formation pressure and hydrostatic pressure of the target area are determined.

[0027] In some embodiments, determining the overlying formation pressure and hydrostatic pressure of the target area based on the full-formation density volume model includes:

[0028] The overlying formation pressure of the target area is obtained by performing depth integration on the entire formation density volume.

[0029] Substituting the density of water into the whole-formation density volume model yields a whole-formation density volume that includes the density of water.

[0030] The hydrostatic pressure of the target area is obtained by performing depth integration on the whole-stratum density volume including the density of water.

[0031] In some embodiments, determining the pressure coefficient of the target area based on the relationship between the effective stress and P-wave velocity and clay content of the target area, the P-wave inversion velocity, the S-wave inversion velocity and the lithological probability volume of the target area, the overlying formation pressure and hydrostatic pressure of the target area includes:

[0032] Based on the relationship between the effective stress and P-wave velocity and clay content of the target area, the P-wave inversion velocity and lithological probability volume of the target area are obtained, and the effective stress and effective stress coefficient of the target area are obtained.

[0033] The pressure coefficient of the target area is determined based on the overlying formation pressure and hydrostatic pressure of the target area, as well as the effective stress and effective stress coefficient of the target area.

[0034] In some embodiments, the effective stress coefficient is calculated according to the following formula:

[0035]

[0036]

[0037] Where γ represents Poisson's ratio, α represents the effective stress coefficient, and v p This represents the longitudinal wave inversion velocity, v. s This represents the transverse wave inversion velocity.

[0038] In some embodiments, the pressure coefficient is calculated according to the following formula:

[0039] p P =S v -αp e

[0040] p f =p p / (ρ w gh)

[0041] Where, p P This represents the formation pore pressure, p e This represents the effective stress, α represents the effective stress coefficient, and S... v This represents the pressure of the overlying strata, p. f This represents the pressure coefficient, ρ. w gh represents hydrostatic pressure, ρ w ρ represents the density of water, h represents the burial depth of the target layer, and g represents the gravitational acceleration.

[0042] On the other hand, embodiments of this application provide a pressure coefficient determination device, the device comprising:

[0043] The data acquisition module is used to acquire drilling data, logging data, and seismic data of sample wells in the target area within the target formation.

[0044] The relationship determination module is used to determine the relationship between the effective stress and the P-wave velocity and the clay content in the target area based on the drilling data and the logging data.

[0045] The deterministic inversion module is used to determine the lithological planar distribution characteristics and vertical sand-mud ratio of the target area through pre-stack deterministic inversion based on the seismic data, the drilling data, and the well logging data.

[0046] The geostatistical inversion module is used to determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area based on the seismic data, the lithological planar distribution characteristics of the target area, and the vertical sand-mud ratio, through pre-stack geostatistical inversion.

[0047] The pressure determination module is used to determine the overlying strata pressure and hydrostatic pressure of the target area by constructing a full-stratum density volume model based on the seismic data, the P-wave inversion velocity, the S-wave inversion velocity and the lithology probability volume of the target area.

[0048] The pressure coefficient determination module is used to determine the pressure coefficient of the target area based on the relationship between the effective stress and P-wave velocity and clay content of the target area, the P-wave inversion velocity, the S-wave inversion velocity and the lithological probability volume of the target area, the overlying strata pressure and hydrostatic pressure of the target area.

[0049] The method for determining the pressure coefficient provided in this application involves using drilling and logging data from sample wells in the target area to obtain the relationship between the effective stress, P-wave velocity, and clay content in the target area. Using seismic, drilling, and logging data from sample wells in the target area, and through pre-stack deterministic and pre-stack geostatistical inversion, the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area can be obtained. Based on the seismic data, P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume, the overlying formation pressure and hydrostatic pressure can be obtained using a constructed full-formation density volume model. Based on the obtained relationship between the effective stress, P-wave velocity, and clay content in the target area, as well as the P-wave inversion velocity, S-wave inversion velocity, lithological probability volume, overlying formation pressure, and hydrostatic pressure, the pressure coefficient of the target area can be determined. In this method, pre-stack geostatistical inversion is performed using seismic data and lithological planar distribution characteristics and vertical sand-mud ratio obtained from pre-stack deterministic inversion to determine P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume. This is combined with the relationship between effective stress, P-wave velocity, and clay content. The lithological probability volume is used to characterize clay content, which can better constrain clay content in both the longitudinal and transverse directions, allowing for accurate characterization of clay content and improving the prediction accuracy of pressure coefficient. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1A flowchart illustrating a method for determining a pressure coefficient as provided in an embodiment of this application;

[0052] Figure 2 A fitting diagram showing the relationship between effective stress in the target area and longitudinal wave velocity and clay content in a method for determining the pressure coefficient provided in this application embodiment;

[0053] Figure 3(a) is a diagram showing the effect of determining the longitudinal wave inversion velocity of the target area in a pressure coefficient determination method provided in an embodiment of this application.

[0054] Figure 3(b) is a diagram showing the effect of the shear wave inversion velocity in the target area determined by a method for determining the pressure coefficient provided in an embodiment of this application.

[0055] Figure 3(c) is an effect diagram of the lithological probability body of the target area determined in a method for determining the pressure coefficient provided in an embodiment of this application;

[0056] Figure 4 The flowchart illustrates a method for determining the pressure coefficient in an embodiment of this application, which uses seismic data, P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area to construct a full-stratum density volume model to determine the overlying strata pressure and hydrostatic pressure of the target area.

[0057] Figure 5 The flowchart illustrates a method for determining the pressure coefficient in an embodiment of this application, which uses the relationship between the effective stress of the target area and the P-wave velocity and clay content, the P-wave inversion velocity and S-wave inversion velocity of the target area, the lithological probability volume, the overlying formation pressure and hydrostatic pressure of the target area to determine the pressure coefficient of the target area.

[0058] Figure 6 This is a schematic diagram of a pressure coefficient determination device provided in an embodiment of this application. Detailed Implementation

[0059] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0060] For oil and gas-bearing geological areas, the pressure coefficient of formation pores is an important reservoir parameter that reflects the energy inherent in the oil and gas fluids, thus providing data support for oil and gas exploration. The pressure coefficient is directly related to oil and gas production; a higher pressure coefficient indicates higher oil and gas production and stronger sustainable production capacity in the geological area.

[0061] Currently, there are three main methods for determining the pressure coefficient:

[0062] The first method is the inter-well interpolation method. This method involves substituting the formation pore pressure obtained from well logging data into a seismic tectonic model for interpolation to obtain the formation pore pressure, and then using the formation pore pressure to calculate the pressure coefficient. The disadvantage of this method is that it cannot control the spatial variation trend of formation pore pressure between wells, and it is only applicable to geological areas where the pressure coefficient is significantly correlated with oil and gas depth and the lithology is stable.

[0063] The second method is the P-wave velocity method, such as the Phillipsphone method. This method determines the formation pore pressure based on the relationship between inversion velocities, layer velocities, and other velocity volumes, and then uses the formation pore pressure to calculate the pressure coefficient. The disadvantage of this method is that it is only suitable for determining the pressure coefficient of large geological areas, and the prediction accuracy of the pressure coefficient for small areas is relatively low.

[0064] The third method is the P-wave velocity method considering lithological variations. Since P-wave velocity is influenced by multiple factors, including formation pore pressure, clay content, tectonic movement, and lithological changes, an increase in clay content leads to a decrease in P-wave velocity. If lithology is not considered, the predicted pressure coefficient will be overestimated. Furthermore, erosion can also lead to an overestimation of the predicted pressure coefficient. The P-wave velocity method considering lithological variations predicts the pressure coefficient by constructing a lithological model, taking into account the various factors affecting P-wave velocity changes. In constructing the lithological model, a clay content indicator obtained by normalizing the GR values ​​from well logging data is often used to characterize the clay content. The drawback of this method is that it is only applicable to geological areas where clay content changes slowly. When the actual area experiences large variations in clay content, the constructed lithological model may be inaccurate, leading to inaccurate pressure coefficient predictions.

[0065] To address the problem of inaccurate pressure coefficient prediction in existing technologies, this application provides a method for determining the pressure coefficient.

[0066] Figure 1 A flowchart illustrating a method for determining a pressure coefficient as provided in an embodiment of this application. See also... Figure 1 The method includes:

[0067] Step 101: Obtain drilling data, logging data, and seismic data of the sample wells in the target area within the target formation.

[0068] The target area may include multiple sample wells.

[0069] In this embodiment of the application, the drilling data, logging data and seismic data obtained in this step refer to the drilling data, logging data and seismic data of each sample well in the target area at the target layer.

[0070] It should be noted that the target stratigraphic segment is the segment that requires seismic exploration, and this segment is likely to contain oil and gas reservoirs. By combining drilling data, logging data, and seismic data of this segment, the pressure coefficient of the area can be investigated, which can better reflect the energy of oil and gas reservoirs in the region.

[0071] It is understandable that drilling operations can be performed on sample wells to obtain drilling data; logging operations can be performed on sample wells to obtain logging data; and seismic exploration operations can be performed on sample wells to obtain seismic data.

[0072] Step 102: Based on drilling and logging data, determine the relationship between effective stress in the target area and P-wave velocity and mud content.

[0073] By using drilling and logging data, the relationship between the effective stress in the target area and the P-wave velocity and mud content is determined, which facilitates the subsequent calculation of the effective stress in the target area and thus the pressure coefficient of the target area.

[0074] In some embodiments, this step includes the following sub-steps:

[0075] Step 1021: Based on drilling and logging data, obtain data on effective stress, P-wave velocity, and clay content of the target formation, as well as the functional relationship to be fitted.

[0076] The drilling and logging data include data on the effective stress, P-wave velocity, and clay content of the target formation. Selecting the function to be fitted facilitates the subsequent fitting of the effective stress, P-wave velocity, and clay content data of the target formation.

[0077] In some embodiments, the functional relationship to be fitted has the following four types:

[0078]

[0079]

[0080] p e =A ln v p +BL i

[0081]

[0082] In the formula, p e This represents the effective stress, v pThis represents the longitudinal wave velocity, L. i The value represents the mud content, and A, B, and C represent the fitting coefficients.

[0083] Step 1022: Based on the functional relationship to be fitted, perform multivariate nonlinear regression fitting on the data of effective stress, P-wave velocity and clay content of the target layer to obtain the functional relationship between effective stress, P-wave velocity and clay content of the target area.

[0084] By fitting multiple nonlinear regression, the coefficients in the function to be fitted can be determined, thereby determining the functional relationship between the effective stress in the target area and the longitudinal wave velocity and mud content.

[0085] It is understandable that the relationship between the effective stress of the target area and the P-wave velocity and clay content can be characterized by using the functional relationship between the effective stress of the target area and the P-wave velocity and clay content.

[0086] In some embodiments, the multivariate nonlinear regression fitting uses the effective stress, P-wave velocity, and clay content of the target layer as variables. Based on the functional relationship to be fitted, multivariate nonlinear regression fitting is performed on the effective stress, P-wave velocity, and clay content of the target layer. On the basis that the correlation coefficient is greater than a preset threshold, the undetermined coefficients in the functional relationship to be fitted are determined, and the functional relationship between the effective stress, P-wave velocity, and clay content of the target area is obtained.

[0087] It should be noted that, based on the fitted correlation coefficient R, the functional relationship between effective stress, P-wave velocity, and clay content can be determined. The closer the correlation coefficient R is to 1, the better the fit.

[0088] For example, for the terrestrial shale region of the Sichuan Basin, the multivariate nonlinear regression fitting table can be shown in Table 1 below. Table 1 contains the variables that need to be fitted by multivariate linear regression for the target layer, namely effective stress, P-wave velocity, and clay content.

[0089] Table 1. Multivariate Nonlinear Regression Fitting Table

[0090]

[0091] By performing multivariate nonlinear regression fitting on the above four types of functional relationships to be fitted, the fitted functional relationships with inclusion coefficients and correlation coefficients were obtained. After comparing the correlation coefficients, the functional relationship between the effective stress of the target area and the P-wave velocity and clay content can be obtained as follows: Figure 2 A fitting diagram showing the relationship between effective stress in the target region and longitudinal wave velocity and clay content in a method for determining the pressure coefficient provided in this application embodiment. See also... Figure 2As can be seen, the correlation coefficient R is 0.8023, which is relatively large and indicates a good fit.

[0092] Step 103: Based on seismic data, drilling data, and well logging data, determine the lithological planar distribution characteristics and vertical sand-mud ratio of the target area through pre-stack deterministic inversion.

[0093] By obtaining the lithological planar distribution characteristics and vertical sand-mud ratio of the target area, a basis for subsequent pre-stack geostatistical inversion is provided.

[0094] In some embodiments, seismic data includes seismic attribute data, which includes amplitude attribute data and frequency attribute data; well logging data includes P-wave velocity, S-wave velocity, and geological density data of sample wells; and drilling data includes stratigraphic data of sample wells.

[0095] In some embodiments, this step includes the following sub-steps:

[0096] Step 1031: Perform pre-stack deterministic inversion on the seismic attribute data, P-wave velocity, S-wave velocity, geological density data of the sample wells, and stratigraphic data of the sample wells to obtain the pre-stack deterministic inversion results.

[0097] The pre-stack deterministic inversion results can quantitatively reflect the planar distribution characteristics of lithology and the vertical sand-mud ratio.

[0098] Step 1032: Based on the pre-stack deterministic inversion results and seismic attribute data, determine the lithological planar distribution characteristics and vertical sand-mud ratio of the target area.

[0099] Since seismic attribute data can qualitatively reflect the planar distribution characteristics of lithology, when combined with pre-stack deterministic inversion results, the planar distribution characteristics of lithology qualitatively reflected by seismic attribute data can be compared with the pre-stack deterministic inversion results, thereby better determining the planar distribution characteristics of lithology and the vertical sand-mud ratio of the target area.

[0100] Step 104: Based on seismic data, the lithological planar distribution characteristics and vertical sand-mud ratio of the target area, determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area through pre-stack geostatistical inversion.

[0101] Among them, the lithological probability volume obtained by pre-stack geostatistical inversion can be used to characterize the clay content, so as to more accurately reflect the clay content of the target area. The obtained P-wave inversion velocity, S-wave inversion velocity and lithological probability volume of the target area are convenient for subsequent construction of the whole stratigraphic density volume model, which in turn facilitates the calculation of the overlying strata pressure and hydrostatic pressure of the target area.

[0102] It should be noted that geostatistical inversion integrates available prior information and actual measurement data using Bayesian discriminant analysis to obtain the probability density function and variogram function in geostatistics that characterize the reservoir conditions of the target area. These probability density function and variogram function are then used to calculate the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume for the target area. In this step, the lithological planar distribution characteristics and vertical sand-mud ratio of the target area are prior information obtained from pre-stack deterministic inversion and seismic attribute data, while the seismic data are actual measurement data. Therefore, the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume obtained through pre-stack geostatistical inversion are more consistent with geological patterns, and the lithological probability volume can more accurately reflect the clay content of the target area compared to the GR value in related techniques.

[0103] In some embodiments, blind wells in the same target area were used to fully validate the results of pre-stack geostatistical inversion, ensuring the reliability of P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume.

[0104] It should be noted that logging operations are performed on blind wells in the same target area to obtain logging data. The P-wave velocity, S-wave velocity, and lithological information of the blind well area are analyzed from the logging data and the drilling data obtained from the drilling operation. When the error between the P-wave velocity, S-wave velocity, and lithological information of the blind well area and the obtained P-wave inversion velocity, S-wave inversion velocity, and lithological probability of the target area is less than the preset error, it indicates that the obtained P-wave inversion velocity, S-wave inversion velocity, and lithological probability of the target area can reflect the P-wave velocity, S-wave velocity, and lithological information of the target area, thereby ensuring the reliability of the obtained P-wave inversion velocity, S-wave inversion velocity, and lithological probability body.

[0105] For example, Figure 3(a) is a diagram showing the effect of P-wave inversion velocity in a target area determined by a method for determining pressure coefficient provided in an embodiment of this application; Figure 3(b) is a diagram showing the effect of shear wave inversion velocity in a target area determined by a method for determining pressure coefficient provided in an embodiment of this application; Figure 3(c) is a diagram showing the effect of lithological probability volume in a target area determined by a method for determining pressure coefficient provided in an embodiment of this application. See also Figures 3(a) to 3(c) It can be seen that the changes in the P-wave inversion profile, S-wave inversion profile, and lithological probability volume generated by the P-wave inversion velocity and S-wave inversion velocity are different.

[0106] In some embodiments, this step may specifically include: performing pre-stack geostatistical inversion on seismic attribute data, lithological planar distribution characteristics, and vertical sand-mud ratio based on geostatistical parameters to determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area.

[0107] In some embodiments, geostatistical parameters are the parameters required for pre-stack geostatistical inversion. Pre-stack geostatistical inversion is an inversion framework based on Bayes' theorem. It involves analyzing seismic attribute data, lithological planar distribution characteristics, and vertical sand-mud ratios of the target area to construct probability density functions and variograms. These constructed probability density functions and variograms are used to characterize the geostatistical parameters. Based on the geostatistical parameters, pre-stack geostatistical inversion is performed on the seismic attribute data, lithological planar distribution characteristics, and vertical sand-mud ratios to determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area.

[0108] In some embodiments, JASON geostatistical inversion software is used to perform pre-stack geostatistical inversion.

[0109] Step 105: Based on seismic data, P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area, determine the overlying strata pressure and hydrostatic pressure of the target area by constructing a full-stratum density volume model.

[0110] Overburden pressure refers to the pressure generated by the sum of the mass of the overburden matrix and the mass of fluids (oil, gas, water) in the pores of the overburden. Hydrostatic pressure refers to the pressure generated by water. Determining the overburden pressure and hydrostatic pressure of the target area facilitates the calculation of formation pore pressure and pressure coefficient.

[0111] Figure 4 The flowchart illustrates a method for determining the pressure coefficient provided in this application. Based on seismic data, P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area, a full-stratum density volume model is constructed to determine the overlying strata pressure and hydrostatic pressure of the target area. See also... Figure 4 This step can specifically include the following sub-steps:

[0112] Step 1051: Perform depth migration processing on the seismic data to obtain depth-migrated seismic data.

[0113] Depth migration can obtain seismic data in the depth domain, thus enriching the seismic data.

[0114] Step 1052: Construct a depth-migrated velocity field model based on the seismic data after depth migration.

[0115] By constructing a depth migration velocity field model, data can be converted between the time domain and the depth domain.

[0116] Step 1053: Substitute the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area into the depth migration velocity field model to obtain the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume after depth migration.

[0117] The obtained depth-migrated P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume are depth-domain data, which can enrich the data of P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume.

[0118] Step 1054: Based on the P-wave inversion velocity, S-wave inversion velocity, and lithology probability volume after depth migration, construct a full-stratum density volume model.

[0119] By constructing a full-formation density volume model, it is easier to calculate the overlying formation pressure and hydrostatic pressure in subsequent operations.

[0120] In some embodiments, the following three methods can be used to construct a full-stratum density volume model:

[0121] The first method is the density average method. This method uses the average shallow density of the target area to construct a full-layer density volume model.

[0122] The second method is density curve interpolation. This involves using the average shallow density of the target area to determine the density curve, then performing interpolation to construct a density volume model of the entire formation.

[0123] The third method is the velocity method. Based on the depth migration velocity field model, the acoustic-density conversion formula is used to obtain the whole-stratum density volume model.

[0124] Step 1055: Based on the full formation density volume model, determine the overlying formation pressure and hydrostatic pressure of the target area.

[0125] The overlying formation pressure and hydrostatic pressure of the target area are obtained to prepare for the subsequent calculation of the pressure coefficient.

[0126] Based on the whole-formation density volume model, the overlying formation pressure and hydrostatic pressure of the target area can be determined as follows: perform depth integration on the whole-formation density volume to obtain the overlying formation pressure of the target area; substitute the density of water into the whole-formation density volume model to obtain the whole-formation density volume containing the density of water; perform depth integration on the whole-formation density volume containing the density of water to obtain the hydrostatic pressure of the target area.

[0127] Overburden pressure refers to the pressure generated by the sum of the mass of the overburden matrix and the mass of fluids (oil, gas, water) in the pores of the overburden. Therefore, the overburden pressure of the target area can be obtained by depth integration of the entire formation density volume. Hydrostatic pressure refers to the pressure generated by water. Therefore, the hydrostatic pressure of the target area can be obtained by depth integration of the entire formation density volume containing water.

[0128] Step 106: Based on the relationship between effective stress and P-wave velocity and clay content in the target area, the P-wave inversion velocity, S-wave inversion velocity and lithological probability volume in the target area, and the overlying strata pressure and hydrostatic pressure in the target area, determine the pressure coefficient of the target area.

[0129] By using lithological probabilistic volume to characterize clay content, the P-wave inversion velocity, S-wave inversion velocity, and lithological probabilistic volume of the target area are substituted into the relationship between the effective stress of the target area and the P-wave velocity and clay content. Then, by constraining the overlying formation pressure and hydrostatic pressure, the pressure coefficient of the target area can be calculated.

[0130] Figure 5 The flowchart illustrates a method for determining the pressure coefficient in an embodiment of this application, based on the relationship between effective stress and P-wave velocity and clay content in the target area, P-wave inversion velocity, S-wave inversion velocity, lithological probability volume, overlying formation pressure, and hydrostatic pressure in the target area. See also... Figure 5 This step specifically includes the following sub-steps:

[0131] Step 1061: Based on the relationship between the effective stress and P-wave velocity and clay content in the target area, the P-wave inversion velocity and lithological probability volume of the target area are obtained, and the effective stress and effective stress coefficient of the target area are obtained.

[0132] By substituting the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area into the relationship between the effective stress of the target area and the P-wave velocity and clay content, the effective stress can be calculated, and thus the effective stress coefficient can be obtained.

[0133] In some embodiments, the effective stress coefficient of the target region is obtained according to the following formula:

[0134]

[0135]

[0136] Where γ represents Poisson's ratio, α represents the effective stress coefficient, and v p This represents the longitudinal wave inversion velocity, v s This represents the transverse wave inversion velocity.

[0137] Step 1062: Determine the pressure coefficient of the target area based on the overlying formation pressure and hydrostatic pressure, as well as the effective stress and effective stress coefficient of the target area.

[0138] Based on the formation pore pressure formula and pressure coefficient formula, the pressure coefficient is calculated by constraining the overlying formation pressure, hydrostatic pressure, effective stress, and effective stress coefficient.

[0139] In some embodiments, the pressure coefficient is obtained according to the following formula:

[0140] p P =S v -αp e

[0141] p f =p p / (ρ w gh)

[0142] Where, p P This represents the formation pore pressure, p e This represents the effective stress, α represents the effective stress coefficient, and S... v This represents the overlying strata pressure, p f This represents the pressure coefficient, ρ. w gh represents hydrostatic pressure, ρ w ρ represents the density of water, h represents the burial depth of the target layer, i.e., the depth from the ground to the target layer, and g represents the acceleration due to gravity.

[0143] In some embodiments, the calculated formation pore pressure is compared with the maximum and minimum principal stresses of the target area to ensure that the formation pore pressure is less than or equal to the minimum principal stress.

[0144] For example, in the case of the terrestrial shale region of the Sichuan Basin, based on the actual measured pressure coefficient of the target area in this application, the pressure coefficient determined using the pressure coefficient method provided in this application embodiment is compared with the pressure coefficient obtained by the P-wave velocity method considering lithological variations. The results show that the pressure coefficient determined by the P-wave velocity method considering lithological variations is 1.7, the pressure coefficient determined by the pressure coefficient method provided in this application embodiment is 1.4, and the actual measured pressure coefficient is 1.3. From the above pressure coefficient values, it can be seen that the pressure coefficient method provided in this application embodiment reduces the prediction error of the pressure coefficient of the target area from 23% to 7%, indicating that the prediction accuracy of the pressure coefficient method provided in this application embodiment is high.

[0145] It should be noted that this method can solve the problem in most areas with relatively abundant logging and drilling data. If logging and drilling data are scarce, or if pressure coefficients are unavailable, detailed analysis using data from adjacent areas is required. The approximate pressure coefficient can be obtained based on the compaction trend, and then empirically corrected using lithological probability data. It should also be noted that the relationship between P-wave velocity, clay content, and effective stress may differ from region to region. If rock physics experiments have been conducted in the area, calculations can be performed directly based on the relationships obtained from those experiments. If rock physics experiments have not been conducted in the area, the relationship between P-wave velocity, clay content, and effective stress can be determined using the method provided in this application.

[0146] It should be noted that this method is more accurate in predicting the pressure coefficient for geological regions with the following characteristics: thin shale, rapid changes in the sand-mud ratio within the shale, and relatively stable geological density, such as the terrestrial shale region of the Sichuan Basin.

[0147] The method for determining the pressure coefficient provided in this application uses seismic data and lithological planar distribution characteristics and vertical sand-mud ratio obtained from pre-stack deterministic inversion to perform pre-stack geostatistical inversion, thereby determining the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume. This is combined with the relationship between effective stress, P-wave velocity, and clay content. The lithological probability volume is used to characterize the clay content. Substituting the lithological probability volume into the relationship between effective stress, P-wave velocity, and clay content can better constrain the clay content in both the longitudinal and transverse directions, improving the prediction accuracy of the pressure coefficient and providing data support for oil and gas exploration.

[0148] Figure 6 A schematic diagram of a pressure coefficient determination device provided in an embodiment of this application. See also... Figure 6 The device includes:

[0149] The data acquisition module 601 is used to acquire drilling data, logging data and seismic data of sample wells in the target area within the target stratum;

[0150] The relationship determination module 602 is used to determine the relationship between the effective stress and the P-wave velocity and clay content of the target area based on drilling data and logging data.

[0151] The deterministic inversion module 603 is used to determine the lithological planar distribution characteristics and vertical sand-mud ratio of the target area through pre-stack deterministic inversion based on seismic data, drilling data, and well logging data.

[0152] The geostatistical inversion module 604 is used to determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area based on seismic data, lithological planar distribution characteristics, and vertical sand-mud ratio of the target area through pre-stack geostatistical inversion.

[0153] The pressure determination module 605 is used to determine the overlying strata pressure and hydrostatic pressure of the target area based on seismic data, P-wave inversion velocity, S-wave inversion velocity and lithological probability volume of the target area by constructing a full-stratum density volume model.

[0154] The pressure coefficient determination module 606 is used to determine the pressure coefficient of the target area based on the relationship between the effective stress of the target area and the P-wave velocity and clay content, the P-wave inversion velocity and S-wave inversion velocity of the target area, the lithological probability volume, the overlying strata pressure and hydrostatic pressure of the target area.

[0155] In some embodiments, the relationship determination module 602 includes:

[0156] The acquisition unit is used to acquire data on effective stress, P-wave velocity, and clay content of the target formation, as well as the functional relationship to be fitted, based on drilling and logging data.

[0157] The fitting unit is used to perform multivariate nonlinear regression fitting on the effective stress, P-wave velocity, and clay content data of the target layer based on the functional relationship to be fitted, so as to obtain the functional relationship between the effective stress, P-wave velocity, and clay content of the target area.

[0158] In some embodiments, seismic data includes seismic attribute data, well logging data includes P-wave velocity, S-wave velocity and geological density data of sample wells, and drilling data includes stratigraphic data of sample wells.

[0159] In some embodiments, the deterministic inversion module 603 includes:

[0160] The deterministic inversion unit is used to perform pre-stack deterministic inversion on seismic attribute data, P-wave velocity, S-wave velocity, geological density data of sample wells, and stratigraphic data of sample wells to obtain pre-stack deterministic inversion results.

[0161] The feature determination unit is used to determine the lithological planar distribution characteristics and vertical sand-mud ratio of the target area based on pre-stack deterministic inversion results and seismic attribute data.

[0162] In some embodiments, the geostatistical inversion module 604 includes:

[0163] The geostatistical inversion unit is used to perform pre-stack geostatistical inversion on seismic attribute data, lithological planar distribution characteristics, and vertical sand-mud ratio based on geostatistical parameters, in order to determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area.

[0164] In some embodiments, the pressure determination module 605 includes:

[0165] The depth migration unit is used to perform depth migration processing on seismic data to obtain depth-migrated seismic data.

[0166] The first model building unit is used to build a depth migration velocity field model based on the depth-migrated seismic data.

[0167] Substitute the unit to input the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area into the depth migration velocity field model to obtain the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume after depth migration.

[0168] The second model building unit is used to construct a full-stratum density volume model based on the P-wave inversion velocity, S-wave inversion velocity and lithological probability volume after depth migration.

[0169] The pressure determination unit is used to determine the overlying formation pressure and hydrostatic pressure of the target area based on the whole formation density volume model.

[0170] In some embodiments, the pressure determining unit includes:

[0171] The first defined sub-unit is used to obtain the overlying formation pressure of the target area based on the depth integration of the entire formation density volume.

[0172] The density volume calculation unit is used to obtain a full formation density volume that includes the density of water by substituting the density of water into the full formation density volume model.

[0173] The second determining sub-unit is used to perform depth integration on the whole-stratum density volume containing water density to obtain the hydrostatic pressure of the target area.

[0174] In some embodiments, the pressure coefficient determination modulus 606 includes:

[0175] The stress calculation unit is used to obtain the effective stress and effective stress coefficient of the target area based on the relationship between the effective stress of the target area and the P-wave velocity and clay content, the P-wave inversion velocity of the target area and the lithological probability volume of the target area.

[0176] The pressure coefficient determination unit is used to determine the pressure coefficient of the target area based on the overlying formation pressure and hydrostatic pressure, as well as the effective stress and effective stress coefficient of the target area.

[0177] In some embodiments, the effective stress coefficient is calculated according to the following formula:

[0178]

[0179]

[0180] Where γ represents Poisson's ratio, α represents the effective stress coefficient, and v p This represents the longitudinal wave inversion velocity, v s This represents the transverse wave inversion velocity.

[0181] In some embodiments, the pressure coefficient is calculated according to the following formula:

[0182] p P =S v -αp e

[0183] p f =p p / (ρ w gh)

[0184] Where, p P This represents the formation pore pressure, p e This represents the effective stress, α represents the effective stress coefficient, and S... v This represents the overlying strata pressure, p f This represents the pressure coefficient, ρ. w gh represents hydrostatic pressure, ρ w ρ represents the density of water, h represents the burial depth of the target layer, i.e., the depth from the ground to the target layer, and g represents the acceleration due to gravity.

[0185] The pressure coefficient determination device provided in this application uses seismic data and lithological planar distribution characteristics and vertical sand-mud ratio obtained from pre-stack deterministic inversion to perform pre-stack geostatistical inversion, thereby determining the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume. This is combined with the relationship between effective stress, P-wave velocity, and clay content. The lithological probability volume is used to characterize the clay content. Substituting the lithological probability volume into the relationship between effective stress, P-wave velocity, and clay content can better constrain the clay content in both the longitudinal and transverse directions, thus improving the prediction accuracy of the pressure coefficient.

[0186] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only.

[0187] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for determining a pressure coefficient, characterized in that, The method includes: Obtain drilling, logging, and seismic data from sample wells in the target area within the target formation; Based on the drilling data and the logging data, the relationship between the effective stress in the target area and the P-wave velocity and clay content is determined. Based on the seismic data, drilling data, and well logging data, the lithological planar distribution characteristics and vertical sand-mud ratio of the target area are determined through pre-stack deterministic inversion. Based on the seismic data, the lithological planar distribution characteristics of the target area, and the vertical sand-mud ratio, the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area are determined through pre-stack geostatistical inversion. Based on the seismic data, the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area, the overlying strata pressure and hydrostatic pressure of the target area are determined by constructing a full-stratum density volume model. Based on the relationship between the effective stress, P-wave velocity, and clay content of the target area, the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area, as well as the overlying strata pressure and hydrostatic pressure of the target area, the pressure coefficient of the target area is determined.

2. The method for determining the pressure coefficient according to claim 1, characterized in that, The determination of the relationship between effective stress in the target area and P-wave velocity and clay content based on the drilling data and the logging data includes: Based on the drilling data and the logging data, the effective stress, P-wave velocity and clay content of the target formation and the functional relationship to be fitted are obtained. Based on the functional relationship to be fitted, a multivariate nonlinear regression fitting is performed on the data of effective stress, P-wave velocity and clay content of the target layer to obtain the functional relationship between effective stress, P-wave velocity and clay content in the target area.

3. The method for determining the pressure coefficient according to claim 1, characterized in that, The seismic data includes seismic attribute data, the well logging data includes P-wave velocity, S-wave velocity, and geological density data of sample wells, and the drilling data includes stratigraphic data of sample wells; the determination of the lithological planar distribution characteristics and vertical sand-slurry ratio of the target area through pre-stack deterministic inversion based on the seismic data, the drilling data, and the well logging data includes: Pre-stack deterministic inversion is performed on the seismic attribute data, the P-wave velocity, the S-wave velocity, the geological density data of the sample wells, and the stratigraphic data of the sample wells to obtain the pre-stack deterministic inversion results. Based on the pre-stack deterministic inversion results and the seismic attribute data, the lithological planar distribution characteristics and vertical sand-mud ratio of the target area are determined.

4. The method for determining the pressure coefficient according to claim 1, characterized in that, The seismic data includes seismic attribute data; the determination of the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area based on the seismic data, the lithological planar distribution characteristics of the target area, and the vertical sand-mud ratio, through pre-stack geostatistical inversion, includes: Based on geostatistical parameters, pre-stack geostatistical inversion is performed on the seismic attribute data, the lithological planar distribution characteristics, and the vertical sand-mud ratio to determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area.

5. The method for determining the pressure coefficient according to claim 1, characterized in that, Based on the seismic data, the P-wave inversion velocity, S-wave inversion velocity, and lithology probability volume of the target area, the overlying strata pressure and hydrostatic pressure of the target area are determined by constructing a full-stratum density volume model, including: The seismic data is subjected to depth migration processing to obtain depth-migrated seismic data; Based on the depth-migrated seismic data, a depth-migrated velocity field model is constructed; Substituting the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target region into the depth migration velocity field model, we obtain the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume after depth migration. Based on the P-wave inversion velocity, S-wave inversion velocity, and lithology probability volume after the depth migration, the whole-stratum density volume model is constructed. Based on the full-formation density volume model, the overlying formation pressure and hydrostatic pressure of the target area are determined.

6. The method for determining the pressure coefficient according to claim 5, characterized in that, The determination of the overlying formation pressure and hydrostatic pressure in the target area based on the full-formation density volume model includes: The overlying formation pressure of the target area is obtained by performing depth integration on the entire formation density volume. Substituting the density of water into the whole-formation density volume model yields a whole-formation density volume that includes the density of water. The hydrostatic pressure of the target area is obtained by performing depth integration on the whole-stratum density volume containing the density of water.

7. The method for determining the pressure coefficient according to claim 1, characterized in that, The pressure coefficient of the target area is determined based on the relationship between effective stress and P-wave velocity and clay content, the P-wave inversion velocity, S-wave inversion velocity and lithological probability volume of the target area, and the overlying formation pressure and hydrostatic pressure of the target area, including: Based on the relationship between the effective stress and P-wave velocity and clay content of the target area, the P-wave inversion velocity and lithological probability volume of the target area are obtained, and the effective stress and effective stress coefficient of the target area are obtained. The pressure coefficient of the target area is determined based on the overlying formation pressure and hydrostatic pressure of the target area, as well as the effective stress and effective stress coefficient of the target area.

8. The method for determining the pressure coefficient according to claim 7, characterized in that, The effective stress coefficient is calculated using the following formula: Where γ represents Poisson's ratio, α represents the effective stress coefficient, and v p This represents the longitudinal wave inversion velocity, v. s This represents the transverse wave inversion velocity.

9. The method for determining the pressure coefficient according to claim 7, characterized in that, The pressure coefficient is calculated using the following formula: p P =S v -αp e p f =p p / (ρ w gh) Where, p P This represents the formation pore pressure, p e This represents the effective stress, α represents the effective stress coefficient, and S... v This represents the pressure of the overlying strata, p. f This represents the pressure coefficient, ρ. w gh represents hydrostatic pressure, ρ w ρ represents the density of water, h represents the burial depth of the target layer, and g represents the gravitational acceleration.

10. A device for determining a pressure coefficient, characterized in that, The device includes: The data acquisition module is used to acquire drilling data, logging data, and seismic data of sample wells in the target area within the target formation. The relationship determination module is used to determine the relationship between the effective stress and the P-wave velocity and the clay content in the target area based on the drilling data and the logging data. The deterministic inversion module is used to determine the lithological planar distribution characteristics and vertical sand-mud ratio of the target area through pre-stack deterministic inversion based on the seismic data, the drilling data, and the well logging data. The geostatistical inversion module is used to determine the P-wave inversion velocity, S-wave inversion velocity, and lithological probability volume of the target area based on the seismic data, the lithological planar distribution characteristics of the target area, and the vertical sand-mud ratio, through pre-stack geostatistical inversion. The pressure determination module is used to determine the overlying strata pressure and hydrostatic pressure of the target area by constructing a full-stratum density volume model based on the seismic data, the P-wave inversion velocity, the S-wave inversion velocity and the lithology probability volume of the target area. The pressure coefficient determination module is used to determine the pressure coefficient of the target area based on the relationship between the effective stress and P-wave velocity and clay content of the target area, the P-wave inversion velocity, the S-wave inversion velocity and the lithological probability volume of the target area, the overlying strata pressure and hydrostatic pressure of the target area.

Images