A reservoir configuration boundary prediction method and system based on waveform feature box

Abstract

The present application relates to the technical field of oil and gas field development, and discloses a reservoir configuration boundary prediction method based on waveform feature box, which comprises the following steps: correcting the reservoir top / bottom interpretation layer to be located at the reflection wave trough / peak position of seismic data; determining the time window range according to the reservoir top interpretation layer and the reservoir bottom interpretation layer, obtaining the reservoir section maximum energy value, the reservoir section seismic amplitude value and the reservoir section seismic waveform skewness value of each seismic trace; obtaining the configuration coefficient according to the reservoir section maximum energy value, the reservoir section seismic amplitude value and the reservoir section seismic waveform skewness value; and drawing the waveform feature box of each seismic trace according to the reservoir section maximum energy value, the reservoir section seismic waveform skewness value and the configuration coefficient to predict the reservoir configuration boundary. The present application directly and accurately predicts the reservoir configuration boundary by using the seismic waveform feature change information, provides fine description of the reservoir, optimizes the speed and quality of oil and gas field development, and brings important value to the oil and gas field development.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to a method and system for predicting reservoir configuration boundaries based on waveform characteristic boxes. Background Technology

[0002] Composite sand bodies refer to complexes formed by the superposition and combination of multiple individual sand bodies. These individual sand bodies are in contact with each other longitudinally and laterally, or separated by mudstone or interlayers. While composite sand bodies are generally considered subsurface reservoirs, with the increasing development of oil and gas fields, fine reservoir characterization requires further clarification of the superposition relationships of individual sand bodies within composite sand bodies, beyond simply identifying the reservoir. This necessitates studying reservoir connectivity to guide well placement and reservoir production allocation. Therefore, predicting the contact locations and relationships (i.e., configuration boundaries) between individual sand bodies is of great significance. However, current technologies primarily utilize seismic attributes to predict composite sand bodies, lacking mature prediction methods for more refined individual sand body configuration boundaries. Many approaches rely on multi-attribute fusion and clustering as workarounds, but these methods lack theoretical basis and generally yield limited results. Summary of the Invention

[0003] This invention provides a method and system for predicting reservoir configuration boundaries based on waveform feature boxes, in order to solve the shortcomings of existing technologies that cannot accurately predict reservoir configuration boundaries.

[0004] This invention provides a reservoir configuration boundary prediction method based on waveform feature boxes, comprising:

[0005] The interpretation planes at the top and bottom of the reservoir are modified so that the interpretation plane at the top of the reservoir is located at the valley of the seismic data reflection wave, and the interpretation plane at the bottom of the reservoir is located at the peak of the seismic data reflection wave.

[0006] The time window range is determined based on the top and bottom interpretation planes of the reservoir, and the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment are obtained.

[0007] The configuration coefficients are obtained based on the maximum energy value of the reservoir section, the seismic amplitude value of the reservoir section, and the seismic waveform skewness value of the reservoir section.

[0008] Based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, the waveform characteristic box of each seismic trace is plotted to predict the reservoir configuration boundary.

[0009] According to the present invention, a reservoir configuration boundary prediction method based on waveform feature boxes is provided, wherein the method corrects the reservoir top interpretation plane and the reservoir bottom interpretation plane so that the reservoir top interpretation plane is located at the valley of the seismic data reflection wave and the reservoir bottom interpretation plane is located at the peak of the seismic data reflection wave, including:

[0010] Based on oilfield reservoir geological data, a longitudinal wave impedance model for composite sand bodies was constructed.

[0011] Based on the longitudinal wave impedance model of composite sand bodies, the amplitude reflection energy, seismic wavelet, and seismic reflection coefficient are obtained;

[0012] The seismic reflection profile is obtained by performing a convolution operation based on the amplitude reflection energy, seismic wavelet, and seismic reflection coefficient.

[0013] Based on the seismic reflection profile, the interpretation planes at the top and bottom of the reservoir are modified so that the interpretation plane at the top of the reservoir is located at the trough of the seismic data reflection wave, and the interpretation plane at the bottom of the reservoir is located at the peak of the seismic data reflection wave.

[0014] According to the present invention, a reservoir configuration boundary prediction method based on waveform characteristic boxes is provided, wherein determining the time window range based on the top and bottom interpretation planes of the reservoir to obtain the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace includes:

[0015] Based on the seismic amplitude values ​​of the reservoir segment, the maximum energy value of the reservoir segment for each seismic trace is obtained through the first expression, where the first expression is: E1=max(|X|). 2 E1 represents the maximum energy value of the reservoir section, X represents the seismic amplitude value of the reservoir section, and max represents taking the maximum value;

[0016] Based on the seismic amplitude values ​​of the reservoir segment, the median of the seismic amplitude values ​​of the reservoir segment for each seismic trace is obtained through the second expression, where the second expression is: m1=median(X), m1 represents the median of the seismic amplitude values ​​of the reservoir segment, X represents the seismic amplitude value of the reservoir segment, and median means taking the median value;

[0017] Based on the seismic amplitude values ​​of the reservoir segment, the mean value of the seismic amplitude values ​​of the reservoir segment for each seismic trace is obtained through the third expression, where the third expression is: a1=mean(X), a1 represents the mean value of the seismic amplitude values ​​of the reservoir segment, X represents the seismic amplitude value of the reservoir segment, and mean represents the average value function;

[0018] Based on the seismic amplitude values ​​of the reservoir segment, the seismic waveform skewness value of each seismic trace is obtained through the fourth expression, where the fourth expression is:

[0019]

[0020] γ1 represents the skewness value of the seismic waveform in the reservoir section, E represents the zero function taking the expected value, X represents the seismic amplitude value in the reservoir section, μ represents the average value of the seismic amplitude value in the reservoir section, and σ represents the standard deviation of the seismic amplitude value in the reservoir section.

[0021] According to the reservoir configuration boundary prediction method based on waveform characteristic boxes provided by the present invention, the configuration coefficient is obtained based on the maximum energy value of the reservoir segment, the seismic amplitude value of the reservoir segment, and the seismic waveform skewness value of the reservoir segment, specifically as follows:

[0022] Based on the maximum energy value, seismic amplitude value, and seismic waveform skewness value of the reservoir segment, the configuration coefficient is obtained through the fifth expression, where the fifth expression is:

[0023]

[0024] c1 represents the configuration coefficient, a1 represents the mean value of the seismic amplitude of the reservoir segment, m1 represents the median value of the seismic amplitude of the reservoir segment, s1 represents the skewness value of the seismic waveform of the reservoir segment, and t1 represents the calculation threshold that has an influence on the configuration coefficient.

[0025] According to the present invention, a reservoir configuration boundary prediction method based on waveform feature boxes includes a method for obtaining calculation thresholds that influence configuration coefficients, comprising:

[0026] Obtain sample data;

[0027] Based on the sample data, the waveform characteristic box of the longitudinal wave impedance model of the composite sand body and the actual sand body configuration boundary are obtained;

[0028] By adjusting the calculation threshold that influences the configuration coefficient, the fit between the waveform characteristic box of the composite sand body longitudinal wave impedance model and the actual sand body configuration boundary reaches the first preset range, thus obtaining the final calculation threshold.

[0029] According to the reservoir configuration boundary prediction method based on waveform characteristic boxes provided by the present invention, the degree of agreement between the waveform characteristic boxes of the composite sand body longitudinal wave impedance model and the actual sand body configuration boundary is obtained through the sixth expression, wherein the sixth expression is:

[0030] acc = n / N·100%

[0031] acc represents the degree of agreement between the waveform characteristic box of the composite sand body P-wave impedance model and the actual sand body configuration boundary; n represents the number of seismic traces whose sand body configuration boundary reflected by the waveform characteristic box of the composite sand body P-wave impedance model is consistent with the actual sand body configuration boundary; and N represents the total number of seismic traces in the composite sand body P-wave impedance model.

[0032] According to the present invention, a method for predicting reservoir configuration boundaries based on waveform feature boxes is provided, wherein the method involves drawing waveform feature boxes for each seismic trace based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, in order to predict the reservoir configuration boundary, including:

[0033] The height of the waveform characteristic box is obtained based on the maximum energy value of the reservoir section;

[0034] The width of the waveform characteristic box is obtained based on the seismic waveform skewness value of the reservoir section;

[0035] The color of the waveform feature box is obtained based on the configuration coefficient;

[0036] Based on the height, width, and color of the waveform feature box, draw the waveform feature box for each seismic trace, and arrange the waveform feature boxes for each seismic trace at preset intervals on the seismic reflection profile.

[0037] Observe the changes between the waveform characteristic boxes, and take the position where the degree of change reaches the second preset range as the predicted reservoir configuration boundary. The changes between the waveform characteristic boxes on both sides of the predicted reservoir configuration boundary reflect the changes in the contact relationship between individual sand bodies.

[0038] The present invention also provides a reservoir configuration boundary prediction system based on waveform feature boxes, comprising:

[0039] The correction module is used to correct the top and bottom interpretation planes of the reservoir, so that the top interpretation plane is located at the valley of the seismic data reflection wave and the bottom interpretation plane is located at the peak of the seismic data reflection wave.

[0040] The numerical calculation module is used to: determine the time window range based on the top and bottom interpretation planes of the reservoir, and obtain the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment;

[0041] The configuration coefficient acquisition module is used to: obtain configuration coefficients based on the maximum energy value of the reservoir segment, the seismic amplitude value of the reservoir segment, and the seismic waveform skewness value of the reservoir segment;

[0042] The reservoir configuration boundary prediction module is used to: draw waveform characteristic boxes for each seismic trace based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, in order to predict the reservoir configuration boundary.

[0043] The present invention also provides an electronic device, including a processor and a memory storing a computer program, characterized in that the processor executes the computer program to implement any of the above-described reservoir configuration boundary prediction methods based on waveform feature boxes.

[0044] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described reservoir configuration boundary prediction methods based on waveform feature boxes.

[0045] The present invention also provides a computer program product, the computer program product including a computer program, the computer program being stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer is able to execute any of the above-described reservoir configuration boundary prediction methods based on waveform feature boxes.

[0046] Seismic reflection waveforms contain rich information such as amplitude, frequency, and phase. Changes in seismic waveforms can reflect changes in the vertical configuration of a single sand body. This invention provides a method and system for predicting reservoir configuration boundaries based on waveform feature boxes. The top interpretation plane of the reservoir is corrected to the trough position of the seismic data reflection wave, and the bottom interpretation plane of the reservoir is corrected to the peak position of the seismic data reflection wave. Based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, waveform feature boxes are drawn for each seismic trace. By utilizing the information on changes in seismic waveform features, reservoir configuration boundaries can be predicted directly and accurately, providing a detailed description of the reservoir, optimizing the speed and quality of oil and gas field development, and bringing significant value to oil and gas field development. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0048] Figure 1 This is one of the flowcharts illustrating a reservoir configuration boundary prediction method based on waveform feature boxes provided by the present invention.

[0049] Figure 2 (a) shows the longitudinal wave impedance model of the composite sand body. Figure 2 (b) shows the seismic data, the top interpretation level of the reservoir, the bottom interpretation level of the reservoir, and the waveform characteristic box plot.

[0050] Figure 3 The image shows the seismic reflection profile of the well trajectory along the S1 sand body in the Bohai A oilfield and the waveform characteristic box diagram obtained by the reservoir configuration boundary prediction method based on waveform characteristic boxes provided by this invention.

[0051] Figure 4 The seismic reflection profile and logging interpretation of the well trajectory along the S1 sand body in the Bohai A oilfield are shown.

[0052] Figure 5 This is a schematic diagram of a reservoir configuration boundary prediction system based on waveform feature boxes provided by the present invention.

[0053] Figure 6This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, embodiments of this invention, and should not be construed as limiting the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention. In the description of this invention, it should be understood that the terminology used is for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0055] The following is combined Figures 1-6 This invention describes the reservoir configuration boundary prediction method, system, device, and medium based on waveform feature boxes provided by the present invention.

[0056] Figure 1 This is a flowchart illustrating the reservoir configuration boundary prediction method based on waveform feature boxes provided by the present invention.

[0057] Reference Figure 1 The present invention provides a reservoir configuration boundary prediction method based on waveform feature boxes, which may include:

[0058] Step S110: Correct the top and bottom interpretation layers of the reservoir so that the top interpretation layer is located at the valley of the seismic data reflection wave and the bottom interpretation layer is located at the peak of the seismic data reflection wave.

[0059] Step S120: Determine the time window range based on the top and bottom interpretation planes of the reservoir to obtain the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment.

[0060] Step S130: Obtain the configuration coefficient based on the maximum energy value of the reservoir section, the seismic amplitude value of the reservoir section, and the seismic waveform skewness value of the reservoir section;

[0061] Step S140: Based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, draw the waveform characteristic box of each seismic trace to predict the reservoir configuration boundary.

[0062] It should be noted that the execution subject of the reservoir configuration boundary prediction method based on waveform feature box provided by the present invention can be any terminal-side device that meets the technical requirements, such as a reservoir configuration boundary prediction device based on waveform feature box.

[0063] Seismic reflection waveforms contain rich information such as amplitude, frequency, and phase. Changes in seismic waveforms can reflect changes in the configuration of a single sand body in the vertical direction. The reservoir configuration boundary prediction method and system based on waveform feature boxes provided in this invention uses the information of seismic waveform feature changes to predict reservoir configuration boundaries, which can obtain a more accurate and refined description of reservoir configuration boundaries, and is helpful for oil and gas field development.

[0064] In one embodiment, step S110 may include:

[0065] Based on oilfield reservoir geological data, a longitudinal wave impedance model for composite sand bodies was constructed.

[0066] Based on the longitudinal wave impedance model of composite sand bodies, the amplitude reflection energy, seismic wavelet, and seismic reflection coefficient are obtained;

[0067] The seismic reflection profile is obtained by performing a convolution operation based on the amplitude reflection energy, seismic wavelet, and seismic reflection coefficient.

[0068] Based on the seismic reflection profile, the interpretation planes at the top and bottom of the reservoir are modified so that the interpretation plane at the top of the reservoir is located at the trough of the seismic data reflection wave, and the interpretation plane at the bottom of the reservoir is located at the peak of the seismic data reflection wave.

[0069] Specifically, taking the Bohai A oilfield as an example, based on the reservoir geological conditions of the Bohai A oilfield, the sandstone velocity is determined to be approximately 2450 m / s, the mudstone velocity approximately 2650 m / s, the sandstone density approximately 2.10 g / cm³, the mudstone density approximately 2.25 g / cm³, the seismic wavelet reflection energy approximately 5000, the composite sand body thickness approximately 15 m, and the width-to-thickness ratio approximately 50:1. Based on the above oilfield reservoir geological data, a P-wave impedance model of the composite sand body is constructed (see...). Figure 2 The amplitude reflection energy, seismic wavelet, and seismic reflection coefficient are obtained, and the seismic reflection profile is obtained according to the convolution expression.

[0070] The convolution expression is:

[0071] d=s·w*r (1)

[0072] In the convolution expression, d represents the seismic reflection profile, s represents the amplitude reflection energy, s = 5000, w represents the seismic wavelet, using the Ricker wavelet with a main frequency of 30Hz (this wavelet is the most commonly used theoretical wavelet in the field of exploration geophysics), and r represents the seismic reflection coefficient, which can be obtained by combining the composite sand body longitudinal wave impedance model constructed above with equation (2).

[0073] r i =(A i -A i-1 ) / (A i +A i-1 (2)

[0074] In equation (2), i represents the i-th sampling point, and r i Let A represent the seismic reflection coefficient at the i-th sampling point. i A i-1 Let A represent the longitudinal wave impedance values ​​of the composite sand body longitudinal wave impedance model at the i-th and (i-1)-th sampling points, respectively. i =D i ·V i D i V represents the velocity value at the i-th sampling point in the longitudinal wave impedance model of the composite sand body. i This represents the density value at the i-th sampling point in the longitudinal wave impedance model of the composite sand body. * indicates convolution operation, which is widely used in the natural sciences. The convolution calculation formula is:

[0075] X(n)=Σh(m)×x(nm) (3)

[0076] In equation (3), n represents the sequence, m is the offset, and X(n) represents the convolution of h(m) and x(nm).

[0077] Based on seismic reflection profiles, the interpretation of the reservoir top and bottom interpretation layers can be corrected by using the automatic peak and trough layer tracking interpretation function in existing software. This ensures that the reservoir top interpretation layer is located at the seismic data reflection trough position (i.e., the position with negative reflection value and maximum amplitude), and the reservoir bottom interpretation layer is located at the seismic data reflection peak position (i.e., the position with positive reflection value and maximum amplitude).

[0078] In one embodiment, step S120 may include:

[0079] Based on the seismic amplitude values ​​of the reservoir segment, the maximum energy value of the reservoir segment for each seismic trace is obtained through the first expression, where the first expression is: E1=max(|X|). 2 E1 represents the maximum energy value of the reservoir section, X represents the seismic amplitude value of the reservoir section, and max represents taking the maximum value;

[0080] Based on the seismic amplitude values ​​of the reservoir segment, the median of the seismic amplitude values ​​of the reservoir segment for each seismic trace is obtained through the second expression, where the second expression is: m1=median(X), m1 represents the median of the seismic amplitude values ​​of the reservoir segment, X represents the seismic amplitude value of the reservoir segment, and median means taking the median value;

[0081] Based on the seismic amplitude values ​​of the reservoir segment, the mean value of the seismic amplitude values ​​of the reservoir segment for each seismic trace is obtained through the third expression, where the third expression is: a1=mean(X), a1 represents the mean value of the seismic amplitude values ​​of the reservoir segment, X represents the seismic amplitude value of the reservoir segment, and mean represents the average value function;

[0082] Based on the seismic amplitude values ​​of the reservoir segment, the seismic waveform skewness value of each seismic trace is obtained through the fourth expression, where the fourth expression is:

[0083]

[0084] In equation (4), γ1 represents the skewness value of the seismic waveform in the reservoir section, E represents the zero function with the expected value, X represents the seismic amplitude value in the reservoir section, μ represents the average value of the seismic amplitude value in the reservoir section, and σ represents the standard deviation of the seismic amplitude value in the reservoir section.

[0085] In one embodiment, step S130 may specifically be as follows:

[0086] Based on the maximum energy value, seismic amplitude value, and seismic waveform skewness value of the reservoir segment, the configuration coefficient is obtained through the fifth expression, where the fifth expression is:

[0087]

[0088] In Equation (5), c1 represents the configuration coefficient, a1 represents the mean value of the seismic amplitude of the reservoir section, m1 represents the median value of the seismic amplitude of the reservoir section, s1 represents the skewness value of the seismic waveform of the reservoir section, and t1 represents the calculation threshold that influences the configuration coefficient. Equation (5) indicates that when the skewness value of the seismic waveform of the reservoir section is less than or equal to the calculation threshold, the waveform is basically centrally symmetrical, the waveform is unskewed, and the configuration coefficient is 0; when the skewness value of the seismic waveform of the reservoir section is greater than the calculation threshold, the waveform is asymmetrical. Specifically, when the mean value of the seismic amplitude of the reservoir section is less than the median value of the seismic amplitude of the reservoir section, there is an upward skewness of the waveform, reflecting that the mudstone interlayers between individual sand bodies are biased downward in the vertical direction, and the configuration coefficient is -1. When the mean value of the seismic amplitude of the reservoir section is greater than the median value of the seismic amplitude of the reservoir section, there is a downward skewness of the waveform, reflecting that the mudstone interlayers between individual sand bodies are biased upward in the vertical direction, and the configuration coefficient is 1. The positions where the aforementioned three configuration coefficients change represent the positions of the configuration boundaries.

[0089] Specifically, the calculation threshold that influences the configuration coefficient can be obtained through the following steps:

[0090] Obtain sample data;

[0091] Based on the sample data, the waveform characteristic box of the longitudinal wave impedance model of the composite sand body and the actual sand body configuration boundary are obtained;

[0092] By adjusting the calculation threshold that influences the configuration coefficient, the fit between the waveform characteristic box of the composite sand body longitudinal wave impedance model and the actual sand body configuration boundary reaches the first preset range, thus obtaining the final calculation threshold.

[0093] Taking the Bohai A oilfield as an example, using the reservoir geological data of the Bohai A oilfield as sample data, we can obtain its composite sand body P-wave impedance model, and then obtain the waveform characteristic box of the composite sand body P-wave impedance model. Then, we can obtain the actual sand body configuration boundary based on the actual drilling of the Bohai A oilfield. When adjusting the calculation threshold that has an influence on the configuration coefficient, when the fit between the waveform characteristic box of the composite sand body P-wave impedance model and the actual sand body configuration boundary reaches the first preset range, we can obtain the final calculation threshold.

[0094] It should be noted that in this embodiment, the first preset range is above 80%, that is, by adjusting the calculation threshold that has an influence on the configuration coefficient, when the waveform characteristic box of the composite sand body longitudinal wave impedance model matches the actual sand body configuration boundary by 80%, the calculation threshold at this time is used as the final calculation threshold.

[0095] The fit between the waveform characteristic box of the composite sand body longitudinal wave impedance model and the actual sand body configuration boundary can be obtained through the sixth expression, where the sixth expression is:

[0096] acc = n / N·100% (6)

[0097] In Equation (6), acc represents the degree of agreement between the waveform characteristic box of the composite sand body P-wave impedance model and the actual sand body configuration boundary, n represents the number of seismic traces whose sand body configuration boundary reflected by the waveform characteristic box of the composite sand body P-wave impedance model is consistent with the actual sand body configuration boundary, and N represents the total number of seismic traces of the composite sand body P-wave impedance model.

[0098] In one embodiment, step S140 may include:

[0099] The height of the waveform characteristic box is obtained based on the maximum energy value of the reservoir section;

[0100] The width of the waveform characteristic box is obtained based on the seismic waveform skewness value of the reservoir section;

[0101] The color of the waveform feature box is obtained based on the configuration coefficient;

[0102] Based on the height, width, and color of the waveform feature box, draw the waveform feature box for each seismic trace, and arrange the waveform feature boxes for each seismic trace at preset intervals on the seismic reflection profile.

[0103] Observe the changes between the waveform characteristic boxes, and take the position where the degree of change reaches the second preset range as the predicted reservoir configuration boundary. The changes between the waveform characteristic boxes on both sides of the predicted reservoir configuration boundary reflect the changes in the contact relationship between individual sand bodies.

[0104] It should be noted that each waveform feature box includes data in three dimensions: height, width, and color. After obtaining the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, it is necessary to first perform lateral smoothing on the maximum energy value of the reservoir segment and the seismic waveform skewness value of the reservoir segment, and then use the smoothed maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient as the data basis for drawing the waveform feature box.

[0105] The height of the waveform characteristic box is plotted based on the maximum energy value of the reservoir segment. Specifically, each seismic trace in the seismic reflection profile has a maximum energy value for a reservoir segment. All maximum energy values ​​of reservoir segments in the entire seismic reflection profile are normalized to values ​​within the range of 0 to 1. The normalized maximum energy value of the k-th seismic trace is denoted as F. k When plotting the k-th waveform characteristic box, the reservoir bottom position (denoted as B) is located at the k-th seismic trace on the seismic reflection profile. k Starting from point B, draw a straight line downwards to point B. k +q·F k The position is given by q, which represents the preset longitudinal scaling factor (q = 20 in this embodiment, which can be adjusted appropriately according to different seismic reflection profiles), and the length of the straight line reflects the height of the waveform feature box.

[0106] The width of the waveform characteristic box is plotted based on the seismic waveform skewness values ​​of the reservoir segments. Specifically, each seismic trace in the seismic reflection profile has a seismic waveform skewness value for a reservoir segment. All seismic waveform skewness values ​​of all reservoir segments in the entire seismic reflection profile are normalized to values ​​within the range of 0 to 1. The normalized waveform skewness of the k-th seismic trace is denoted as Q. k When drawing the k-th waveform feature box, the width of the aforementioned straight line reflecting the height of the waveform feature box is set to z*Q. k , where z represents the preset lateral scaling factor (in this embodiment, z = 5, which can be adjusted appropriately according to different seismic reflection profiles), and the width of the straight line reflects the width of the waveform feature box.

[0107] The color of the waveform feature box is drawn based on the configuration coefficient. Specifically, each seismic trace in the seismic reflection profile has a configuration coefficient. When drawing the k-th waveform feature box, the line drawn is filled with red when the configuration coefficient c1 = 1, black when c1 = 0, and green when c1 = -1. Different colors reflect different configuration boundary types: red represents the upper part of the sand body, green represents the lower part, and black represents the middle part.

[0108] After drawing the waveform feature box for each seismic trace using the above method, draw the waveform feature box on the seismic reflection profile at a preset interval (in this embodiment, one waveform feature box is drawn for every 1 seismic trace, which can be adjusted appropriately according to the actual seismic reflection profile trace spacing), thus completing the drawing of the waveform feature box for each trace on the seismic reflection profile.

[0109] Then, observe the changes between the waveform feature boxes, and take the position where the degree of change reaches the second preset range as the predicted reservoir configuration boundary (in this embodiment, the position where the color of adjacent waveform feature boxes changes directly (e.g., from black to green, from red to green, from green to black, etc.) or the width of adjacent waveform feature boxes changes significantly (e.g., the width of the left waveform feature box is only one-tenth of the width of the right waveform feature box, etc.) is taken as the predicted reservoir configuration boundary). The changes between the waveform feature boxes on both sides of the predicted reservoir configuration boundary reflect the changes in the contact relationship between individual sand bodies. The contact relationship can be, for example, two sand bodies stacked in front and below, two sand bodies stacked in front and above, or a single sand body without stacking, etc. Based on the actual situation, it can be judged whether the changes between the waveform feature boxes are relevant to the prediction of the configuration boundary.

[0110] This invention extracts seismic reflection profiles along the development well trajectory of the S1 composite sand body in the Bohai A oilfield. The top and bottom interpretation planes of the reservoir are corrected to the peak and trough positions of the seismic data reflection waves, respectively. Based on the maximum energy value of the reservoir section, the seismic waveform skewness value of the reservoir section, and the configuration coefficient, waveform characteristic boxes are plotted for each seismic trace in the seismic reflection profile along the well trajectory (see...). Figure 3 The location where the degree of change reaches a second preset range (e.g., the location where the color of adjacent waveform feature boxes changes directly) is used as the predicted reservoir configuration boundary. Figure 4 The drilling lithological interpretation of the development well that encountered the sand body is shown. The prediction results are consistent with the drilling lithological interpretation results, confirming that the well encountered the configuration boundary of the sand body. This verifies the rationality and accuracy of the prediction results obtained by the reservoir configuration boundary prediction method based on waveform characteristic box provided by this invention.

[0111] Seismic reflection waveforms contain rich information such as amplitude, frequency, and phase. Changes in seismic waveforms can reflect changes in the vertical configuration of a single sand body. This invention provides a method and system for predicting reservoir configuration boundaries based on waveform feature boxes. The top interpretation plane of the reservoir is corrected to the trough position of the seismic data reflection wave, and the bottom interpretation plane of the reservoir is corrected to the peak position of the seismic data reflection wave. Based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, waveform feature boxes are drawn for each seismic trace. By utilizing the information on changes in seismic waveform features, reservoir configuration boundaries can be predicted directly and accurately, providing a detailed description of the reservoir, optimizing the speed and quality of oil and gas field development, and bringing significant value to oil and gas field development.

[0112] The reservoir configuration boundary prediction system based on waveform feature boxes provided by the present invention is described below. The reservoir configuration boundary prediction system based on waveform feature boxes described below can be referred to in correspondence with the reservoir configuration boundary prediction method based on waveform feature boxes described above.

[0113] Reference Figure 5 The present invention provides a reservoir configuration boundary prediction system based on waveform feature boxes, which may include:

[0114] The correction module 510 is used to correct the top and bottom interpretation layers of the reservoir so that the top interpretation layer is located at the valley of the seismic data reflection wave and the bottom interpretation layer is located at the peak of the seismic data reflection wave.

[0115] The numerical calculation module 520 is used to: determine the time window range based on the top and bottom interpretation planes of the reservoir, and obtain the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment;

[0116] Configuration coefficient module 530 is used to: obtain configuration coefficients based on the maximum energy value of the reservoir segment, the seismic amplitude value of the reservoir segment, and the seismic waveform skewness value of the reservoir segment;

[0117] The reservoir configuration boundary prediction module 540 is used to: draw the waveform characteristic box of each seismic trace based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, so as to predict the reservoir configuration boundary.

[0118] In one embodiment, the correction module may include:

[0119] The model building submodule is used to: construct a composite sand body P-wave impedance model based on oilfield reservoir geological data;

[0120] The data acquisition submodule is used to: obtain the amplitude reflection energy, seismic wavelet, and seismic reflection coefficient based on the longitudinal wave impedance model of the composite sand body;

[0121] The convolution submodule is used to perform convolution operations based on amplitude reflection energy, seismic wavelet, and seismic reflection coefficient to obtain a seismic reflection profile.

[0122] The correction submodule is used to correct the top and bottom interpretation planes of the reservoir based on the seismic reflection profile, so that the top interpretation plane is located at the valley of the seismic data reflection wave and the bottom interpretation plane is located at the peak of the seismic data reflection wave.

[0123] In one embodiment, the numerical calculation module may include:

[0124] The first calculation submodule is used to: obtain the maximum energy value of the reservoir segment for each seismic trace based on the seismic amplitude value of the reservoir segment using a first expression, where the first expression is: E1=max(|X|). 2 E1 represents the maximum energy value of the reservoir section, X represents the seismic amplitude value of the reservoir section, and max represents taking the maximum value;

[0125] The second calculation submodule is used to: obtain the median value of the reservoir segment seismic amplitude for each seismic trace based on the reservoir segment seismic amplitude value through a second expression, where the second expression is: m1 = median(X), m1 represents the median value of the reservoir segment seismic amplitude value, X represents the reservoir segment seismic amplitude value, and median represents taking the median value;

[0126] The third calculation submodule is used to: obtain the mean value of the reservoir segment seismic amplitude for each seismic trace based on the reservoir segment seismic amplitude value through the third expression, where the third expression is: a1=mean(X), a1 represents the mean value of the reservoir segment seismic amplitude, X represents the reservoir segment seismic amplitude value, and mean represents the average value function;

[0127] The fourth calculation submodule is used to: obtain the reservoir segment seismic waveform skewness value for each seismic trace based on the reservoir segment seismic amplitude value using the fourth expression, where the fourth expression is:

[0128]

[0129] γ1 represents the skewness value of the seismic waveform in the reservoir section, E represents the zero function taking the expected value, X represents the seismic amplitude value in the reservoir section, μ represents the average value of the seismic amplitude value in the reservoir section, and σ represents the standard deviation of the seismic amplitude value in the reservoir section.

[0130] In one embodiment, the configuration factor obtaining module is specifically used for:

[0131] Based on the maximum energy value, seismic amplitude value, and seismic waveform skewness value of the reservoir segment, the configuration coefficient is obtained through the fifth expression, where the fifth expression is:

[0132]

[0133] c1 represents the configuration coefficient, a1 represents the mean value of the seismic amplitude of the reservoir segment, m1 represents the median value of the seismic amplitude of the reservoir segment, s1 represents the skewness value of the seismic waveform of the reservoir segment, and t1 represents the calculation threshold that has an influence on the configuration coefficient.

[0134] It should be noted that methods for obtaining the calculation thresholds that influence the configuration coefficients include:

[0135] Obtain sample data;

[0136] Based on the sample data, the waveform characteristic box of the longitudinal wave impedance model of the composite sand body and the actual sand body configuration boundary are obtained;

[0137] By adjusting the calculation threshold that influences the configuration coefficient, the fit between the waveform characteristic box of the composite sand body longitudinal wave impedance model and the actual sand body configuration boundary reaches the first preset range, thus obtaining the final calculation threshold.

[0138] It should be noted that the sixth expression is used to obtain the degree of agreement between the waveform characteristic box of the composite sand body longitudinal wave impedance model and the actual sand body configuration boundary. The sixth expression is as follows:

[0139] acc = n / N·100%

[0140] acc represents the degree of agreement between the waveform characteristic box of the composite sand body P-wave impedance model and the actual sand body configuration boundary; n represents the number of seismic traces whose sand body configuration boundary reflected by the waveform characteristic box of the composite sand body P-wave impedance model is consistent with the actual sand body configuration boundary; and N represents the total number of seismic traces in the composite sand body P-wave impedance model.

[0141] In one embodiment, the reservoir configuration boundary prediction module may include:

[0142] The first drawing submodule is used to: obtain the height of the waveform feature box based on the maximum energy value of the reservoir section;

[0143] The second drawing submodule is used to: obtain the width of the waveform feature box based on the seismic waveform skewness value of the reservoir section;

[0144] The third drawing submodule is used to: obtain the color of the waveform feature box based on the configuration coefficient;

[0145] The fourth drawing submodule is used to: draw the waveform feature box of each seismic trace according to the height, width and color of the waveform feature box, and arrange the waveform feature box of each seismic trace on the seismic reflection profile according to the preset interval;

[0146] The prediction submodule is used to: observe the changes between waveform feature boxes, and take the position where the degree of change reaches the second preset range as the predicted reservoir configuration boundary. The changes between the waveform feature boxes on both sides of the predicted reservoir configuration boundary reflect the changes in the contact relationship between individual sand bodies.

[0147] Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute a reservoir configuration boundary prediction method based on waveform feature boxes, the method including:

[0148] The interpretation planes at the top and bottom of the reservoir are modified so that the interpretation plane at the top of the reservoir is located at the valley of the seismic data reflection wave, and the interpretation plane at the bottom of the reservoir is located at the peak of the seismic data reflection wave.

[0149] The time window range is determined based on the top and bottom interpretation planes of the reservoir, and the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment are obtained.

[0150] The configuration coefficients are obtained based on the maximum energy value of the reservoir section, the seismic amplitude value of the reservoir section, and the seismic waveform skewness value of the reservoir section.

[0151] Based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, the waveform characteristic box of each seismic trace is plotted to predict the reservoir configuration boundary.

[0152] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0153] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, wherein when the computer program is executed by a processor, the computer is able to execute the reservoir configuration boundary prediction method based on waveform feature boxes provided by the above methods, the method comprising:

[0154] The interpretation planes at the top and bottom of the reservoir are modified so that the interpretation plane at the top of the reservoir is located at the valley of the seismic data reflection wave, and the interpretation plane at the bottom of the reservoir is located at the peak of the seismic data reflection wave.

[0155] The time window range is determined based on the top and bottom interpretation planes of the reservoir, and the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment are obtained.

[0156] The configuration coefficients are obtained based on the maximum energy value of the reservoir section, the seismic amplitude value of the reservoir section, and the seismic waveform skewness value of the reservoir section.

[0157] Based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, the waveform characteristic box of each seismic trace is plotted to predict the reservoir configuration boundary.

[0158] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the reservoir configuration boundary prediction method based on waveform feature boxes provided by the above methods, the method comprising:

[0159] The interpretation planes at the top and bottom of the reservoir are modified so that the interpretation plane at the top of the reservoir is located at the valley of the seismic data reflection wave, and the interpretation plane at the bottom of the reservoir is located at the peak of the seismic data reflection wave.

[0160] The time window range is determined based on the top and bottom interpretation planes of the reservoir, and the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment are obtained.

[0161] The configuration coefficients are obtained based on the maximum energy value of the reservoir section, the seismic amplitude value of the reservoir section, and the seismic waveform skewness value of the reservoir section.

[0162] Based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, the waveform characteristic box of each seismic trace is plotted to predict the reservoir configuration boundary.

[0163] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0164] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A reservoir configuration boundary prediction method based on waveform feature boxes, characterized in that, include: The interpretation planes at the top and bottom of the reservoir are modified so that the interpretation plane at the top of the reservoir is located at the valley of the seismic data reflection wave, and the interpretation plane at the bottom of the reservoir is located at the peak of the seismic data reflection wave. The time window range is determined based on the top and bottom interpretation planes of the reservoir, and the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment are obtained. The configuration coefficients are obtained based on the maximum energy value of the reservoir section, the seismic amplitude value of the reservoir section, and the seismic waveform skewness value of the reservoir section. Based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, the waveform characteristic box of each seismic trace is plotted to predict the reservoir configuration boundary. The step of drawing waveform characteristic boxes for each seismic trace based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient to predict the reservoir configuration boundary includes: The height of the waveform characteristic box is obtained based on the maximum energy value of the reservoir section; The width of the waveform characteristic box is obtained based on the seismic waveform skewness value of the reservoir section; The color of the waveform feature box is obtained based on the configuration coefficient; Based on the height, width, and color of the waveform feature box, draw the waveform feature box for each seismic trace, and arrange the waveform feature boxes for each seismic trace at preset intervals on the seismic reflection profile. Observe the changes between the waveform characteristic boxes, and take the position where the degree of change reaches the second preset range as the predicted reservoir configuration boundary. The changes between the waveform characteristic boxes on both sides of the predicted reservoir configuration boundary reflect the changes in the contact relationship between individual sand bodies.

2. The reservoir configuration boundary prediction method based on waveform feature boxes according to claim 1, characterized in that, The process of determining the time window range based on the top and bottom interpretation planes of the reservoir to obtain the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment includes: Based on the seismic amplitude values ​​of the reservoir segment, the maximum energy value of the reservoir segment for each seismic trace is obtained through the first expression, where the first expression is: E1=max(| X |) 2 E1 represents the maximum energy value of the reservoir section. X This represents the seismic amplitude value of the reservoir section, with max indicating the maximum value. Based on the seismic amplitude values ​​of the reservoir segments, the median seismic amplitude value of each seismic trace is obtained through the second expression, where the second expression is: m1 = median ( X m1 represents the median value of the seismic amplitude in the reservoir section, and median means taking the median value; Based on the seismic amplitude values ​​of the reservoir segment, the mean seismic amplitude value of the reservoir segment for each seismic trace is obtained through the third expression, where the third expression is: a1 = mean ( X ), a1 represents the mean value of the seismic amplitude of the reservoir section, and mean represents the average value function; Based on the seismic amplitude values ​​of the reservoir segment, the seismic waveform skewness value of each seismic trace is obtained through the fourth expression, where the fourth expression is: γ1 represents the seismic waveform skewness value of the reservoir section, and E represents the zero function taking the expected value. μ This represents the average value of the seismic amplitude in the reservoir section. σ This represents the standard deviation of the seismic amplitude values ​​in the reservoir section.

3. The reservoir configuration boundary prediction method based on waveform feature boxes according to claim 2, characterized in that, The configuration coefficients are obtained based on the maximum energy value of the reservoir segment, the seismic amplitude value of the reservoir segment, and the seismic waveform skewness value of the reservoir segment, specifically as follows: Based on the maximum energy value, seismic amplitude value, and seismic waveform skewness value of the reservoir segment, the configuration coefficient is obtained through the fifth expression, where the fifth expression is: c1 represents the configuration coefficient, s1 represents the seismic waveform skewness value of the reservoir section, and t1 represents the calculation threshold that has an influence on the configuration coefficient.

4. The reservoir configuration boundary prediction method based on waveform feature boxes according to claim 3, characterized in that, Methods for obtaining computational thresholds that influence configuration coefficients include: Obtain sample data; Based on the sample data, the waveform characteristic box of the longitudinal wave impedance model of the composite sand body and the actual sand body configuration boundary are obtained; By adjusting the calculation threshold that influences the configuration coefficient, the fit between the waveform characteristic box of the composite sand body longitudinal wave impedance model and the actual sand body configuration boundary reaches the first preset range, thus obtaining the final calculation threshold.

5. The reservoir configuration boundary prediction method based on waveform feature boxes according to claim 4, characterized in that, The sixth expression is used to obtain the fit between the waveform characteristic box of the composite sand body longitudinal wave impedance model and the actual sand body configuration boundary. The sixth expression is: acc=n / N 100% acc represents the degree of agreement between the waveform characteristic box of the composite sand body P-wave impedance model and the actual sand body configuration boundary; n represents the number of seismic traces whose sand body configuration boundary reflected by the waveform characteristic box of the composite sand body P-wave impedance model is consistent with the actual sand body configuration boundary; and N represents the total number of seismic traces in the composite sand body P-wave impedance model.

6. A reservoir configuration boundary prediction system based on waveform feature boxes, characterized in that, include: The correction module is used to correct the top and bottom interpretation planes of the reservoir, so that the top interpretation plane is located at the valley of the seismic data reflection wave and the bottom interpretation plane is located at the peak of the seismic data reflection wave. The numerical calculation module is used to: determine the time window range based on the top and bottom interpretation planes of the reservoir, and obtain the maximum energy value, seismic amplitude value, and seismic waveform skewness value of each seismic trace in the reservoir segment; The configuration coefficient acquisition module is used to: obtain the configuration coefficients based on the maximum energy value of the reservoir section, the seismic amplitude value of the reservoir section, and the seismic waveform skewness value of the reservoir section; The reservoir configuration boundary prediction module is used to: draw waveform characteristic boxes for each seismic trace based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient, in order to predict the reservoir configuration boundary. The step of drawing waveform characteristic boxes for each seismic trace based on the maximum energy value of the reservoir segment, the seismic waveform skewness value of the reservoir segment, and the configuration coefficient to predict the reservoir configuration boundary includes: The height of the waveform characteristic box is obtained based on the maximum energy value of the reservoir section; The width of the waveform characteristic box is obtained based on the seismic waveform skewness value of the reservoir section; The color of the waveform feature box is obtained based on the configuration coefficient; Based on the height, width, and color of the waveform feature box, draw the waveform feature box for each seismic trace, and arrange the waveform feature boxes for each seismic trace at preset intervals on the seismic reflection profile. Observe the changes between the waveform characteristic boxes, and take the position where the degree of change reaches the second preset range as the predicted reservoir configuration boundary. The changes between the waveform characteristic boxes on both sides of the predicted reservoir configuration boundary reflect the changes in the contact relationship between individual sand bodies.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the reservoir configuration boundary prediction method based on waveform feature boxes as described in any one of claims 1 to 5.

8. A computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, wherein when the computer program is executed by a processor, the computer is capable of performing the reservoir configuration boundary prediction method based on waveform feature boxes as described in any one of claims 1 to 5.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the reservoir configuration boundary prediction method based on waveform feature boxes as described in any one of claims 1 to 5.

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