Method for predicting three-dimensional pore pressure of sand shale stratum

Abstract

The invention discloses a sand shale stratum three-dimensional pore pressure prediction method, and relates to the technical field of oil and gas seismic exploration and drilling engineering, and the method comprises the following steps: S1, collecting and sorting well logging data of a drilled well in a three-dimensional work area; s2, establishing a compaction trend line of each well; s3, carrying out work area seismic data processing and interpretation work to obtain an elastic parameter body; s4, obtaining a similarity influence factor of each well on the channel; s5, the distance between the seismic data of the channel and each well and the distance influence factor of each well on the channel are obtained, and parameters in the distance influence factors are determined; s6, obtaining the influence weight of each well on the seismic trace; s7, obtaining a compaction trend line relation of the seismic channel; s8, the formation pore pressure of the channel is obtained; and S9, repeating the steps S4-S8, and obtaining the formation pore pressure data body in the three-dimensional work area, the method can obtain the accurate compaction trend line of the area outside the drilling point, and a new method is provided for pore pressure pre-drilling prediction.

Description

Technical Field

[0001] This invention relates to the field of oil and gas seismic exploration and drilling engineering technology, specifically to a method for predicting three-dimensional pore pressure in sandstone and mudstone formations. Background Technology

[0002] Formation pore pressure and its formation mechanism. Formation pore pressure is the pressure exerted by fluids (oil, gas, water) in the pores and fractures of a formation. In normal geological environments, when the formation is normally compacted, the formation pore pressure equals the hydrostatic pressure at that location; this is called normal formation pore pressure. The magnitude of normal formation pore pressure is related to the properties of the underground fluids. In special geological environments, when the formation pore pressure is higher or lower than the hydrostatic pressure, it is called abnormal formation pore pressure. Formation pore pressure higher than the hydrostatic pressure is called abnormally high pressure or overpressure. Formation pore pressure lower than the hydrostatic pressure is called abnormally low pressure or underpressure. Abnormal formation pore pressure is widely distributed, appearing in metamorphic rocks of the Precambrian to sedimentary rocks of the Cenozoic. Oil and gas exploration practice shows that during drilling, normal formation pore pressure, abnormally high pressure, and abnormally low pressure can all be encountered, but abnormally high pressure occurs more frequently and is more significant for the petroleum industry.

[0003] The causes of abnormal high pressure are diverse, and the phenomenon may be due to a combination of factors, including geological, physical, chemical, and dynamic factors. In 1994, scholar Ward, from the perspective of stress-strain relationship during sedimentary compaction, classified the formation mechanism of abnormal high pressure into three categories: The first category conforms to the original loading curve, i.e., unbalanced compaction. Unbalanced compaction occurs when, as the deposition and burial depth of overlying sediments increase, the pore drainage capacity weakens or stops, and the load of the continuing to increase overlying sediments is partially or entirely borne by pore fluids. The effective load (vertical effective stress) required for further compaction of sediments decreases or remains unchanged, resulting in under-compacted strata and abnormally high-pressure strata. The second category conforms to the unloading curve, mainly including abnormal high pressure formed by pore fluid expansion (hydrothermal pressurization, hydrocarbon generation, montmorillonite dehydration, hydrocarbon cracking, etc.) and abnormal high pressure formed by strata uplift and erosion caused by tectonic movements. The third category is caused by tectonic compressive stress, fluid density differences, etc., without changes in porosity. In actual drilling operations, unbalanced compaction is the most common mechanism for generating abnormal high pressure, and tectonic compression is also an important pressure-increasing mechanism in basins with intense tectonic activity.

[0004] Significance of Formation Pore Pressure Prediction. Formation pore pressure is crucial for drilling engineering. It serves as fundamental data for calculating in-situ stress, formation collapse pressure, and fracture pressure; it is an important basis for determining casing layers and casing depth; and it is key to rationally designing drilling fluid density and implementing near-balanced, underbalanced, and controlled pressure drilling. Therefore, the accurate determination of formation pore pressure has significant economic value for safe, rapid, and low-cost drilling, as well as preventing and avoiding complex drilling accidents. In petroleum geology, formation pore pressure, or the fluid potential converted from pressure, is one of the main controlling factors in the formation and distribution of oil and gas reservoirs, and serves as the basis for the study of oil and gas reservoir hydrodynamics.

[0005] Current methods for predicting formation pore pressure and their limitations. Pore pressure prediction methods are categorized based on data sources, including measured formation pore pressure methods, drilling data prediction methods, well logging data prediction methods, and seismic data prediction methods. According to their sequence with the drilling process, they can be divided into pre-drilling prediction methods, monitoring while drilling methods, and post-drilling detection methods. Pre-drilling prediction methods process and interpret existing seismic data for the region, combining it with geological data and analysis of adjacent well drilling data to determine the distribution of underground formation pressure in the target area and predict the formations, depths, and magnitudes of abnormally high pressure. Prediction accuracy depends primarily on the quality of the seismic data, the rationality of the prediction model, and the understanding of geological stratification and lithology. Since unbalanced compaction is the most common mechanism for the formation of abnormally high pressure, widely present in sandstone and mudstone formations, commonly used methods include the equivalent depth method, the Eaton method, and the Bowers method. The Eaton method, based on a normal compaction trend line, has become one of the most widely used methods for predicting formation pore pressure using well logging data since its introduction in 1972, offering high accuracy. However, this method is based on post-drilling pore pressure prediction using existing wells. For undrilled areas, well logging data is unavailable, making it impossible to obtain normal compaction trend lines and thus preventing the use of the Eaton method for pore pressure prediction. Currently, the commonly used pre-drilling prediction method is based on empirical models, but this method is highly susceptible to formation velocities and requires setting different rock skeleton velocities and fluid velocities, leading to significant errors in actual calculations. Summary of the Invention

[0006] The purpose of this invention is to solve / improve the above-mentioned problems by providing a three-dimensional pore pressure prediction method for sandstone and mudstone formations. This method combines well logging data and seismic data, extending the Eaton method to pre-drilling formation pore pressure prediction. First, single-well compaction trend lines are established using known well data within the area. Then, compaction trend lines are established for each point within the area using these single-well compaction trend lines. Finally, the Eaton method is used to predict the three-dimensional formation pore pressure within the area. This method can obtain relatively accurate compaction trend lines outside the drilling point, extending post-drilling formation pore pressure prediction technology to the pre-drilling area, and providing a new method for pre-drilling pore pressure prediction.

[0007] More specifically, the present invention is achieved through the following technical solution:

[0008] A method for predicting three-dimensional pore pressure in sandstone and mudstone formations includes the following steps:

[0009] S1: Collect and organize well logging data of drilled wells within a three-dimensional work area;

[0010] S2: By analyzing the logging data of each well in the work area, the mudstone strata of each well are obtained, and the compaction trend line of each well is established based on the logging data of the mudstone strata.

[0011] S3: Carry out seismic data processing and interpretation work in the work area, interpret the range of sandstone and mudstone strata in the seismic data, and carry out well-seismic joint inversion in combination with well logging data in the work area to obtain elastic parameter volume;

[0012] S4: For a certain seismic trace data to be calculated, extract the P-wave velocity data retrieved from the trace within the sandstone and mudstone strata, convert it into sonic transit time, obtain the similarity between the sonic transit time of the trace and the sonic transit time of each well in the work area, and obtain the similarity influence factor of each well on the trace.

[0013] S5: Obtain the distance between the seismic data and each well, obtain the distance influence factor of each well to the seismic data, and determine the parameters in the distance influence factor by combining the seismic phase data;

[0014] S6: Combine the similarity influence factor and distance influence factor obtained from S4 and S5 to obtain the influence weight of each well on the seismic trace;

[0015] S7: Combining the influence weight of each well on the seismic trace with the compaction trend line formula of the well, the compaction trend line relationship of the seismic trace is obtained;

[0016] S8: Based on the compaction trend line relationship of the seismic trace, the normal compaction rate of each depth of the sandstone and mudstone section is obtained, and the formation pore pressure of the trace is obtained using the Eaton formula.

[0017] S9: Repeat S4 to S8 to obtain the formation pore pressure for each seismic trace and obtain the formation pore pressure data volume in the three-dimensional work area.

[0018] Furthermore, in step S1, the logging data includes sonic transit time data, clay content data, gamma data, and well diameter data. When collecting and organizing the logging data, outliers are removed.

[0019] Furthermore, in step S2, the mudstone section of each well is obtained as the target section for the study. The selection of the mudstone section must refer to the logging data and well diameter data. The selected target section does not have any cases of narrowing or widening.

[0020] Furthermore, in step S2, sonic transit time data within the mudstone strata of each well are extracted, and the compaction trend line relationship (1) for each well is obtained.

[0021] Depth t =a t ln(AC t )+b t (1),

[0022] In the formula, t is the well number, t = 1, 2, 3, ... r;

[0023] The logarithm of the acoustic transit time in well t is fitted with a linear relationship with depth, a t b is the fitted slope t The intercept is the fitting angle.

[0024] Furthermore, step S3 includes the following steps for processing and interpreting seismic data in the work area:

[0025] Interpret the stratigraphic information of the sandstone and mudstone sections in this region;

[0026] Based on existing well logging data in the work area, a high-precision three-dimensional elastic data volume is obtained by using a well-seismic joint inversion method. The elastic data volume includes three data volumes: P-wave velocity volume, S-wave velocity volume, and density volume.

[0027] Furthermore, in step S4, the acoustic time difference satisfies the following relationship (2).

[0028]

[0029] In equation (2), AC ij The time difference for sound waves is expressed in µs / ft; vp ij The longitudinal wave velocity obtained from the inversion is expressed in m / s.

[0030] Simultaneously, the acoustic transit time curves between layers T1 and T2 in each well of r wells were extracted;

[0031] Because the sampling rates of well logging data and seismic data differ, and well logging data has a denser sampling density than seismic data, considering computational efficiency, the AC sonic transit time data from well logging... 测 Extraction of seismic traces AC ij Points at the same depth form a new logging sonic transit time data, denoted as AC'. 测 , where AC' 测 The number of data points and seismic traces AC ij The number of data points is consistent, and the logging sonic transit time AC' of each well is obtained. 测 With earthquake track AC ij The similarity between them is used to obtain the similarity influence factor of each well to the passage. The similarity influence factor satisfies the following relationship (3).

[0032]

[0033] In equation (3), Simi t For the drilled well t and the seismic trace s to be calculated ij The similarity influence factor between them ranges from 0 to 1. The closer the value is to 1, the more similar the acoustic transit time curve of the well logging data is to the acoustic transit time curve of the seismic trace data.

[0034] Furthermore, in step S5, the seismic trace s to be calculated ij The geographic coordinates are (x ij ,y ij Let the geographical coordinates of the drilled wells be (x...). i ' j ,y i ' j The distance D between the seismic trace to be calculated and the drilled well t satisfies the following equation (4), and the distance influence factor between the seismic trace of each well and the drilled well t satisfies the relationship (5).

[0035]

[0036]

[0037] In the above formula, Dist t For the tth well already drilled and the seismic traces to be calculated s ij The distance influence factor between them, t = 1, 2, 3, 4....r;

[0038] p is an important parameter in the distance influence factor. If the seismic trace to be calculated and the drilled well are within the same seismic facies range, the p value is 2; if the seismic trace to be calculated and the drilled well are not within the same seismic facies range, the p value is 1.

[0039] Furthermore, in step S6, each well is to be calculated as a seismic trace s ijThe influence weight is a combination of the similarity influence factor and the distance influence factor. The seismic trace s is obtained by calculating the influence weight of the two influence factors. ij The final influence weight satisfies the following equation (6):

[0040]

[0041] Among them, w t For the drilled well t to the seismic trace s ij The influence weight.

[0042] Furthermore, in step S7, the compaction trend line has two parameters: slope and intercept. The seismic trace s to be calculated is obtained for each parameter. ij The slope of the compaction trend line is:

[0043]

[0044] In equation (7), a ij For earthquake traces s ij The slope of the compaction trend line in the sandstone and mudstone strata; w t For the drilled well t to the seismic trace s ij Influence weight, a t The slope of the compaction trend line fitted to the t-logging curve of the drilled well;

[0045] Calculate seismic traces s ij The intercept of the compaction trend line is:

[0046]

[0047] In equation (8), b ij For earthquake traces s ij Intercept of the compaction trend line in the sandstone and mudstone section, b t The intercept of the compaction trend line fitted to the t-logging curve of the drilled well;

[0048] Obtain earthquake traces s ij The compaction trend line satisfies relation (9).

[0049] Depth ij =a ij ln(AC ij )+b ij (9).

[0050] Furthermore, in step S8, the normal compaction acoustic time difference AC is obtained according to step S7. ij Subsequently, seismic traces were obtained using the Eaton method. ij The formation pore pressure satisfies the following relationship (10).

[0051]

[0052] in, For earthquake traces s ij Formation pore pressure;

[0053] For earthquake traces s ij The pressure of the overlying strata;

[0054] For earthquake traces s ij The hydrostatic pressure;

[0055] For earthquake traces s ij The longitudinal wave velocity obtained from the inversion, and the corresponding acoustic time difference;

[0056] AC ij The normal compaction acoustic time difference is calculated using the normal compaction trend line;

[0057] N is the Eaton index, a dimensionless adjustment parameter that varies with region and geological age.

[0058] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0059] I. This invention proposes a three-dimensional pore pressure prediction method for sandstone and mudstone formations based on drilling and logging data and seismic data. This method utilizes the compaction trend line formula of drilled wells within the work area, combined with seismic geological data, to obtain the compaction trend line for each seismic trace, extending the single-well pore pressure prediction method to three-dimensional seismic data volumes. Compared to the traditional approach of directly interpolating single-well pore pressure curves or directly using the compaction trend line of a single drilled well to replace the compaction trend lines of all seismic traces within the work area, the method proposed in this invention comprehensively considers factors such as distance, seismic facies, and waveform similarity, calculates the weighted influence of each drilled well on the seismic trace to be calculated, accurately calculates the compaction trend line of each seismic trace, and thus obtains a more accurate formation pore pressure.

[0060] Second, this invention can obtain relatively accurate compaction trend lines in areas outside the drilling point, extending post-drilling formation pore pressure prediction technology to the pre-drilling area and providing a new method for pre-drilling pore pressure prediction. It has also achieved good application results in practical applications, representing a significant technical improvement over traditional methods. Attached Figure Description

[0061] Figure 1 This is a flowchart of the present invention.

[0062] Figure 2 This is a diagram of the well logging data from Example 1.

[0063] Figure 3This is a fitted diagram of the single-well compaction trend line in Example 1.

[0064] Figure 4 This is a three-dimensional seismic data map from Example 1.

[0065] Figure 5 This is the three-dimensional seismic inversion diagram from Example 1.

[0066] Figure 6 This is a diagram of the formation pore pressure data in Example 1. Detailed Implementation

[0067] The present invention will be further described in detail below with reference to embodiments, but the implementation of the present invention is not limited thereto.

[0068] Example 1

[0069] A method for predicting three-dimensional pore pressure in sandstone and mudstone formations, relating to the fields of oil and gas seismic exploration and drilling engineering technology, includes the following steps:

[0070] Step 1: Collect and organize the logging data of the drilled wells within a three-dimensional work area.

[0071] In this step, for a three-dimensional research area, assuming r wells have been drilled, each well has complete logging data, including sonic transit time data, clay content data, gamma ray data, and well diameter data. Each type of logging data can be represented by a two-dimensional image, with the horizontal axis representing the data value (e.g., clay content value, gamma ray value) and the vertical axis representing the depth. The logging data is collected and processed, and outliers are removed. Methods for removing outliers from logging data are relatively mature and will not be discussed in detail here.

[0072] Step 2: Analyze the logging data of each well in the work area to obtain the mudstone strata for each well. Establish a compaction trend line for each well based on the logging data of the mudstone strata.

[0073] In this step, by screening logging data from each well in the work area, the mudstone interval of each well is obtained as the target interval for study, and the compaction trend line is calculated using this target interval. Since mudstone compaction is significant, the preferred target interval is a large, pure mudstone interval. The selection of the mudstone interval must refer to logging data, such as mud content and gamma ray, and also needs to consider well diameter data; the selected target interval must not exhibit any reduction or enlargement in diameter.

[0074] After selecting the mudstone strata, sonic transit time data for each well within that strata were extracted. Since the mudstone strata selected for each well are different, the size and range of the extracted sonic transit time data are also different. Each sonic transit time data point corresponds to a depth value. A two-dimensional scatter plot was created using the logarithm of the sonic transit time of the target strata as the abscissa and the depth value as the ordinate. The compaction trend line formula for each well was obtained by linearly fitting this two-dimensional scatter plot. Let the well to be calculated be t, then the compaction trend line of this well satisfies the relationship in equation (1):

[0075] Depth t =a t ln(AC t )+b t (1),

[0076] The above formula represents the linear relationship between the logarithm of the acoustic transit time (t) and the depth, where t = 1, 2, 3, ..., r. Where a t b is the fitted slope t The intercept is the fitting angle.

[0077] Step 3: Conduct seismic data processing and interpretation in the work area, interpreting the extent of sandstone and mudstone strata from the seismic data. Combine well logging data within the work area to perform well-seismic joint inversion and obtain elastic parameter volumes.

[0078] This step involves processing and interpreting the seismic data within the work area. A crucial aspect of this interpretation is interpreting the stratigraphic information of the sandstone and mudstone sections based on known geological data and well logging data for the region. The starting stratigraphic position of the sandstone and mudstone section is designated as T1, and the ending stratigraphic position as T2. The seismic data between T1 and T2 constitutes the target section for calculation. Combining existing well logging data within the work area, a high-precision three-dimensional elastic data volume is obtained using a well-seismic joint inversion method. The elastic data volume comprises three data volumes: P-wave velocity volume, S-wave velocity volume, and density volume. The elastic data volume obtained from the well-seismic joint inversion is the fundamental data for pore pressure prediction, especially the accuracy of the P-wave velocity volume inversion, which directly affects the final pore pressure prediction accuracy. Well-seismic joint inversion techniques are relatively mature and will not be elaborated upon here.

[0079] Step 4: For a certain seismic trace data to be calculated, extract the P-wave velocity data inverted from the trace within the sandstone and mudstone strata, convert it into sonic transit time, calculate the similarity between the sonic transit time of the trace and the sonic transit time of each well in the work area, and obtain the similarity influence factor of each well on the trace.

[0080] In this step, the seismic data volume is a three-dimensional volume. The vertical coordinates represent depth or time, and the horizontal coordinates are the line number and trace number, respectively. Each location in the vertical direction represents a seismic trace. The calculation starts from the initial line number and proceeds sequentially according to the trace numbers from smallest to largest, traversing one line before moving on to the next. Assume the seismic data line numbers are l1, l2, l3, ... l m The seismic data trace numbers are x1, x2, x3, ... x n Therefore, there are m*n seismic traces to be calculated. Let each seismic trace to be calculated be s. ij Where i is 1, 2, 3, ..., m, and j is 1, 2, 3, ..., n. The number of sample points is consistent for each seismic trace along the vertical axis. Assuming each trace has w points, each point in the seismic trace to be calculated can be represented as a point. ijk , where i is 1, 2, 3, ..., m, j is 1, 2, 3, ..., n, and k is 1, 2, 3, ..., w.

[0081] Let the seismic data line number be i and the trace number be j. Extract s from the P-wave velocity data volume obtained in step 3. ij The channel data is converted from P-wave velocity to acoustic transit time data. The specific conversion method is expressed by the following formula:

[0082]

[0083] In the above formula, AC ij The time difference of sound waves is expressed in µs / ft, vp. ij The value represents the longitudinal wave velocity obtained from the inversion, expressed in m / s. Simultaneously, the sonic transit time curves between layers T1 and T2 in each of the r wells are extracted.

[0084] Because the sampling rates of well logging data and seismic data differ, and well logging data has a denser sampling density than seismic data, considering computational efficiency, the sampling rate of well logging sonic transit time data (denoted as AC) is used. 测 Extracting from seismic traces AC ij Points at the same depth form new logging sonic transit time data, denoted as AC'. 测 , where AC' 测 The number of data points and seismic traces AC ij The number of data points is consistent. At this point, the logging sonic transit time AC' for each well is calculated. 测 With earthquake track AC ij The similarity between wells is used to obtain the similarity influence factor of each well on the passage. The similarity influence factor satisfies the following relationship (3):

[0085]

[0086] Simi t For the drilled well t and the seismic trace s to be calculated ij The similarity influence factor between the two is calculated. The value of the similarity influence factor ranges from 0 to 1. The closer the value is to 1, the more similar the acoustic transit time curve of the well logging data is to the acoustic transit time curve of the seismic trace data. The similarity influence factor between the seismic trace to be calculated and each well is calculated using formula (3).

[0087] Step 5: Calculate the distance between the seismic data and each well. Based on the principle that the greater the distance, the smaller the impact, and the closer the distance, the greater the impact, calculate the distance influence factor of each well to the seismic data. Then, combine this with seismic facies data to determine the parameters in the distance influence factor.

[0088] In this step, the seismic trace s to be calculated ij The geographic coordinates are (x ij ,y ij Let the geographical coordinates of the drilled wells be (x...). i ' j ,y i ' j If the distance D between the seismic trace to be calculated and the drilled well t is:

[0089]

[0090] The distance influence factor between the calculated seismic trace and the drilled well t satisfies the following relationship (5):

[0091]

[0092] In the above formula, Dist t For the tth well already drilled and the seismic trace s to be calculated ij The distance influence factor is t = 1, 2, 3, 4...r; p is an important parameter in the distance influence factor.

[0093] The formula shows that the larger the p-value, the greater the impact of distance differences on the distance factor, and the greater the difference in distance influence factors between different wells. The specific value of p depends on whether the seismic trace to be calculated and the drilled well are located in the same seismic facies. If the seismic trace to be calculated and the drilled well are within the same seismic facies range, the p-value is 2; if they are not within the same seismic facies range, the p-value is 1. The p-parameter further strengthens the distance weight of wells within the same seismic facies and weakens the distance weight of wells in different seismic facies.

[0094] Regarding the acquisition of seismic facies, methods such as waveform classification and attribute analysis can be used to conduct seismic facies analysis on seismic data to obtain the seismic facies classification of sandstone and mudstone strata. Seismic facies are the representation of geological sedimentary facies in seismic data; sedimentary characteristics within the same seismic facies are similar. Analysis of seismic facies can help determine the lateral distribution characteristics of sandstone and mudstone. Suppose there are g seismic facies in the work area, labeled f1, f2, f3, ... f... g In the specific calculation process, it is necessary to compare the seismic phase f of the seismic trace to be calculated. ij Seismic activity at the drilling site t Whether they are consistent or not, if they are consistent, the p-value is 2; if they are inconsistent, the p-value is 1.

[0095] Step 6: Combine the similarity influence factor and distance influence factor calculated in Steps 4 and 5 to calculate the influence weight of each well on the seismic trace.

[0096] In this step, each well is to be calculated as a seismic trace s ij The influence weight is a combination of the similarity influence factor and the distance influence factor. The seismic trace s is obtained by calculating the influence weight of the two influence factors. ij The final impact weight is:

[0097]

[0098] Among them, w t For the drilled well t to the seismic trace s ij The influence weights are calculated sequentially for each well within the work area that influences the seismic trace.

[0099] Step 7: Combine the influence weight of each well on the seismic trace with the compaction trend line formula of the well to calculate the compaction trend line formula of the seismic trace;

[0100] In this step, the seismic trace s is calculated based on the compaction trend line of each well obtained in step 2 and the influence weight of each well on the seismic trace to be calculated. ij The compaction trend line is obtained. Since the compaction trend line has two parameters, slope and intercept, the seismic trace s to be calculated is obtained by calculating each parameter separately. ij The slope of the compaction trend line is:

[0101]

[0102] In the above formula, a ij For earthquake traces s ij The slope of the compaction trend line in the sandstone and mudstone section, w t For the drilled well t to the seismic trace s ij Influence weight, a t This represents the slope of the compaction trend line fitted to the t-logging curve of the drilled well. Similarly, the slope of the seismic trace s is calculated.ij The intercept of the compaction trend line is:

[0103]

[0104] In the above formula, b ij For earthquake traces s ij Intercept of the compaction trend line in the sandstone and mudstone section, b t This is the intercept of the compaction trend line fitted to the t-logging curve of the drilled well. Therefore, the seismic trace s to be calculated... ij The formula for the compaction trend line is:

[0105] Depth ij =a ij ln(AC ij )+b ij (9).

[0106] Step 8: Calculate the normal compaction rate of the sandstone and mudstone layer at each depth based on the compaction trend line formula of the seismic trace, and obtain the formation pore pressure of the trace using the Eaton formula.

[0107] In this step, the normal compaction sonic transit time at each depth of the sandstone and mudstone strata is calculated based on the formula for the compaction trend line of the seismic trace. The method for calculating the normal compaction sonic transit time is to input a depth value and use the relationship (9) to calculate an AC value. ij This value is the normal compaction sonic transit time. Knowing the normal compaction sonic transit time at each point, the seismic trace s is calculated using the Eaton method formula. ij The formation pore pressure. The specific formula for the Eaton method is as follows:

[0108]

[0109] In the above formula, For earthquake traces s ij Formation pore pressure;

[0110] For earthquake traces s ij The pressure of the overlying strata;

[0111] For earthquake traces s ij The hydrostatic pressure;

[0112] For earthquake traces s ij The longitudinal wave velocity obtained from the inversion and the acoustic time difference obtained by conversion are described in step 4.

[0113] AC ij The normal compaction acoustic time difference is calculated using the normal compaction trend line;

[0114] N is the Eaton index, an adjustment parameter that varies with region and geological age. It is dimensionless and can be calculated by back-calculating from measured pore pressure points in the formation.

[0115] If there are no measured pore pressure points in the area, the value can be determined based on experience within the block; the empirical value is generally in the range of 2 to 4. Overlying strata pressure and hydrostatic pressure The calculation method is quite mature, so it will not be discussed in detail here.

[0116] Step 9: Repeat steps 4 to 8 to calculate the formation pore pressure for each seismic trace and obtain the formation pore pressure data volume in the three-dimensional work area.

[0117] In this step, steps 4-8 are repeated to calculate the formation pore pressure of each sandstone-mudstone stratum in the seismic trace. Based on step 4, there are m*n seismic traces to be calculated. Each calculated seismic trace is arranged according to its line number and trace number to obtain the formation pore pressure data volume for the sandstone-mudstone strata in the study area.

[0118] To facilitate public understanding of this solution and to make the objectives, technical solutions, and advantages of this invention clearer, the following detailed explanation will be provided using the analysis and research of well logging data and seismic data from a certain work area to achieve three-dimensional formation pore pressure prediction within the work area as an example.

[0119] This plan utilizes well logging and seismic data obtained from a specific work area to predict three-dimensional formation pore pressure within the area. (Reference) Figure 1 The experimental procedure is as follows:

[0120] Step 1: Analyze and organize the logging data from the 6 wells drilled in the work area, check for any abnormal or distorted values ​​in the key logging data, remove any outliers if they are found, and ensure that all values ​​are within a reasonable range to guarantee the accuracy of subsequent calculations.

[0121] Step 2: Analysis of geological and well logging data within the work area reveals that the strata above the Xujiahe Formation are sandstone and mudstone. Therefore, using the Xujiahe bottom as the boundary in the well logging data stratification, well logging data above the Xujiahe bottom is extracted. Through comprehensive analysis of data such as mud content, spontaneous potential, porosity, sonic transit time, and well diameter, pure mudstone intervals are selected, and sonic transit time data for these pure mudstone intervals is obtained. The well logging data is then used as a reference. Figure 2The logging curves for each well are different, and the range of pure mudstone strata obtained from the analysis is different. Therefore, the range of sonic transit time data intercepted also varies. The logarithm of the sonic transit time of the mudstone strata intercepted from a single well is taken as the x-axis value, and the depth corresponding to each sonic transit time point is taken as the y-axis value. Linear fitting is performed using the above formula (1) to obtain the linear relationship between depth y and the logarithm of sonic transit time x, which is the normal compaction trend line of the mudstone strata. As mentioned above, the range of sonic transit time intercepted from each well is different, so the fitted normal compaction trend line differs between different wells. Figure 3 This is a schematic diagram of fitting the compaction trend line of a single well.

[0122] Step 3: Process and interpret the seismic data within the work area. (See 3D seismic data map for reference.) Figure 4 , 5 The work area has line numbers ranging from 9656 to 11212 and trace numbers ranging from 9071 to 9941. Therefore, the work area has a total of 1,353,720 seismic traces to be calculated: (11212-9656)*(9941-9071). There are 4,100 points along the longitudinal direction. The 1,353,720 traces along the lateral direction and the 4,100 points along the longitudinal direction together form a three-dimensional seismic data volume. Seismic interpretation work requires interpreting sandstone and mudstone strata within the seismic data, such as determining the precise location of strata like the Xujiahe Formation. Subsequently, combined with well logging data from six drilled wells within the work area, a well-seismic joint inversion was conducted to obtain the inverted elastic parameter volume, with the key elastic parameter volume being the P-wave velocity data volume. At this point, the vertical axis of the seismic data and the inverted elastic parameter data volume in the work area is time. Since the calculated pore pressure is related to the burial depth of the strata, and the burial depth value is an important parameter in the calculation, it is necessary to convert the seismic data with time as the vertical axis into seismic data with depth as the vertical axis. This method requires the use of the velocity field data established in the work area to convert the seismic data volume and the inverted P-wave velocity volume into depth domain data.

[0123] Step 4: For the first seismic trace data to be calculated (line number: 9656, trace number: 9071), extract the data trace in the sandstone and mudstone strata from the P-wave data volume, and convert it into an acoustic transit time data trace using equation (2). At this time, the acoustic transit time of this trace is a set of data, and each data point includes two pieces of information: depth and acoustic transit time. The acoustic transit time data of each well in the work area is thinned according to the depth to find the acoustic transit time points at the depths corresponding to the seismic data, forming a new set of well logging acoustic transit time data. The similarity between the recombined well logging acoustic transit time data and the seismic trace acoustic transit time data is calculated using equation (3), and the similarity influence factor of each well on the seismic trace is obtained.

[0124] Step 5: For the first seismic trace to be calculated, read its geographical coordinates from the seismic data, and calculate the straight-line distance of each drilled well from the first seismic trace according to formula (4). Based on the known seismic facies classification results in the work area, the seven different seismic facies are digitized spatially into different values, namely 1, 2, 3, 4, 5, 6, and 7. The first seismic trace belongs to seismic facies type 3, of which the six drilled wells belong to seismic facies types 1, 3, 4, 6, 4, and 7 respectively.

[0125] At this point, the distance influence factor of each well to be calculated is calculated using relation (5). For the parameter p in relation (5), the first, third, fourth, fifth and sixth wells are all assigned a constant value of 1. Since the second well is in the same seismic phase category as the first seismic trace, p is taken as a constant value of 2 when calculating the distance influence factor of the second well.

[0126] Step 6: For the first seismic trace to be calculated, combine the similarity influence factor and the distance influence factor, and use formula (6) to calculate the final influence weight of each well on the seismic trace. Within the study area, each seismic trace to be calculated must have 6 influence weight values ​​calculated.

[0127] Step 7: Combining the compaction trend line of each well and the influence weight of each well on the seismic trace to be calculated, calculate the slope and intercept of the compaction trend line of the first seismic trace to be calculated according to equations (7) and (8). Obtain the formula for the compaction trend line of the first seismic trace to be calculated according to equation (9).

[0128] Step 8: For the first seismic trace to be calculated, calculate the normal compaction sonic transit time at each depth in the sandstone and mudstone section according to the relation (9), and use the Eaton method to calculate the formation pore pressure data of the sandstone and mudstone section of the seismic trace according to the relation (10).

[0129] Step 9: Calculate the pore pressure values ​​of seismic data from traces 2 to 1,353,720 sequentially to form the pore pressure data volume of the formation in the study area. When calculating each seismic data trace, the calculation order is from smallest to largest line number, and within the same line number, the trace number is calculated sequentially from smallest to largest. In this study area, seismic traces with line number 9656 and trace number 9071 are extracted first for calculation, followed by traces with line number 9656 and trace number 9072. The line number remains unchanged during each calculation, while the trace number increases sequentially until the trace number reaches 9941. At this point, the line number increases by 1, and the calculation is performed on seismic traces with line number 9656 and trace number 9071, and so on, until all seismic traces in the study area have been calculated. The final formation pore pressure data volume is referenced. Figure 6 As shown.

[0130] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications or equivalent changes made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for predicting three-dimensional pore pressure in sandstone and mudstone formations, characterized in that, Includes the following steps: S1: Collect and organize well logging data of drilled wells within a three-dimensional work area; S2: By analyzing the logging data of each well in the work area, the mudstone strata of each well are obtained, and the compaction trend line of each well is established based on the logging data of the mudstone strata. S3: Carry out seismic data processing and interpretation work in the work area, interpret the range of sandstone and mudstone strata in the seismic data, and carry out well-seismic joint inversion in combination with well logging data in the work area to obtain elastic parameter volume; S4: For a certain seismic trace data to be calculated, extract the P-wave velocity data retrieved from the trace within the sandstone and mudstone strata, convert it into sonic transit time, obtain the similarity between the sonic transit time of the trace and the sonic transit time of each well in the work area, and obtain the similarity influence factor of each well on the trace. S5: Obtain the distance between the seismic data and each well, obtain the distance influence factor of each well to the seismic data, and determine the parameters in the distance influence factor by combining the seismic phase data; S6: Combine the similarity influence factor and distance influence factor obtained from S4 and S5 to obtain the influence weight of each well on the seismic trace; S7: Combining the influence weight of each well on the seismic trace with the compaction trend line formula of the well, the compaction trend line relationship of the seismic trace is obtained; S8: Based on the compaction trend line relationship of the seismic trace, the normal compaction rate of each depth of the sandstone and mudstone section is obtained, and the formation pore pressure of the trace is obtained using the Eaton formula. S9: Repeat S4 to S8 to obtain the formation pore pressure for each seismic trace and obtain the formation pore pressure data volume in the three-dimensional work area.

2. The method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 1, characterized in that, In step S1, the logging data includes sonic transit time data, clay content data, gamma data, and well diameter data. When collecting and organizing the logging data, outliers are removed.

3. The method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 1, characterized in that, In step S2, the mudstone section of each well is obtained as the target section for the study. The selection of the mudstone section must refer to the logging data and well diameter data. The selected target section does not have any cases of narrowing or widening.

4. The method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 3, characterized in that, In step S2, sonic transit time data within the mudstone strata of each well are extracted, and the compaction trend line relationship (1) for each well is obtained. Depth t =a t ln(AC t )+b t (1), In the formula, t is the well number, t = 1, 2, 3, ... r; The logarithm of the acoustic transit time in well t is fitted with a linear relationship with depth, a t b is the fitted slope t This is the fitting intercept.

5. The method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 1, characterized in that, Step S3 includes the following steps for processing and interpreting seismic data in the work area: Interpret the stratigraphic information of the sandstone and mudstone sections in this region; Based on existing well logging data in the work area, a high-precision three-dimensional elastic data volume is obtained by using a well-seismic joint inversion method. The elastic data volume includes three data volumes: P-wave velocity volume, S-wave velocity volume, and density volume.

6. The method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 1, characterized in that, In step S4, the acoustic time difference satisfies the following relationship (2). In equation (2), AC ij The time difference for sound waves is expressed in µs / ft; vp ij The longitudinal wave velocity obtained from the inversion is expressed in m / s. Simultaneously, the acoustic transit time curves between layers T1 and T2 in each well of r wells were extracted; Because the sampling rates of well logging data and seismic data differ, and well logging data has a denser sampling density than seismic data, considering computational efficiency, the AC sonic transit time data from well logging... 测 Extraction of seismic traces AC ij Points at the same depth form a new logging sonic transit time data, denoted as AC'. 测 , where AC' 测 The number of data points and seismic traces AC ij The number of data points is consistent, and the logging sonic transit time AC' of each well is obtained. 测 With earthquake track AC ij The similarity between them is used to obtain the similarity influence factor of each well to the passage. The similarity influence factor satisfies the following relationship (3). In equation (3), Simi t For the drilled well t and the seismic trace s to be calculated ij The similarity influence factor between them ranges from 0 to 1. The closer the value is to 1, the more similar the acoustic transit time curve of the well logging data is to the acoustic transit time curve of the seismic trace data.

7. The method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 1, characterized in that, In step S5, the seismic trace s to be calculated ij The geographic coordinates are (x ij ,y ij Let the geographical coordinates of the drilled wells be (x...). i ' j ,y i ' j The distance D between the seismic trace to be calculated and the drilled well t satisfies the following equation (4), and the distance influence factor between the seismic trace of each well and the drilled well t satisfies the relationship (5). In the above formula, Dist t For the tth well already drilled and the seismic trace s to be calculated ij The distance influence factor between them, t = 1, 2, 3, 4....r; p is an important parameter in the distance influence factor. If the seismic trace to be calculated and the drilled well are within the same seismic facies range, the p value is 2; if the seismic trace to be calculated and the drilled well are not within the same seismic facies range, the p value is 1.

8. The method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 1, characterized in that, In step S6, each well is to be calculated as a seismic trace s ij The influence weight is a combination of the similarity influence factor and the distance influence factor. The seismic trace s is obtained by calculating the influence weight of the two influence factors. ij The final influence weight satisfies the following equation (6): Among them, w t For the drilled well t to the seismic trace s ij The influence weight.

9. The method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 1, characterized in that, In step S7, the compaction trend line has two parameters: slope and intercept. The seismic trace s to be calculated is obtained for each parameter. ij The slope of the compaction trend line is: In equation (7), a ij For earthquake traces s ij The slope of the compaction trend line in the sandstone and mudstone strata; w t For the drilled well t to the seismic trace s ij Influence weight, a t The slope of the compaction trend line fitted to the t-logging curve of the drilled well; Calculate seismic traces s ij The intercept of the compaction trend line is: In equation (8), b ij For earthquake traces s ij Intercept of the compaction trend line in the sandstone and mudstone section, b t The intercept of the compaction trend line fitted to the t-logging curve of the drilled well; Obtain earthquake traces s ij The compaction trend line satisfies relation (9). Depth ij =a ij ln(AC ij )+b ij (9)。 10. A method for predicting three-dimensional pore pressure in sandstone and mudstone formations according to claim 9, characterized in that, In step S8, the normal compaction acoustic time difference AC is obtained according to step S7. ij Subsequently, seismic traces were obtained using the Eaton method. ij The formation pore pressure satisfies the following relationship (10). in, For earthquake traces s ij Formation pore pressure; For earthquake traces s ij The pressure of the overlying strata; For earthquake traces s ij The hydrostatic pressure; For earthquake traces s ij The longitudinal wave velocity obtained from the inversion, and the corresponding acoustic time difference; AC ij The normal compaction acoustic time difference is calculated using the normal compaction trend line; N is the Eaton index, a dimensionless adjustment parameter that varies with region and geological age.

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