Method and device for determining sequence boundary of high-frequency seismic sequence stratigraphy

Abstract

The application discloses a method and device for determining sequence boundaries of high-frequency seismic sequence strata, which comprises the following steps: generating a relative geologic time model according to a three-dimensional seismic data body, extracting an initial seismic-based medium-low-frequency first sequence boundary data body, extracting a seismic-based first-time sequence boundary curve, performing baseline removal, obtaining a seismic-based second sequence boundary data body through first-time waveform difference inversion, extracting a seismic-based third-time sequence boundary curve as a base curve, fusing the base curve with a gamma curve, a porosity curve, a carbonate rock particle curve, a carbonate rock texture curve, a carbonate rock suture line frequency curve, an asphalt content curve and a dolomite content curve which reflect sequence boundaries, and obtaining a seismic-based high-frequency third sequence boundary data body through second-time waveform difference inversion after the fusion, and finally identifying high-frequency seismic sequence boundaries with very high precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbonate rock stratum oil and gas exploration and development, and the seismic aspect division of high-frequency sea level change cycle sequence bodies, in particular to a sequence boundary determination method and device for high-frequency seismic sequence strata. BACKGROUND

[0002] This section is intended to provide background or context to the embodiments of the application recited in the claims. The description herein does not constitute admission of prior art.

[0003] A stratum unit contains a complete base level cycle during deposition in all genetically related depositional environments. The half-cycle boundary of a genetic sequence occurs at the transition point of the base level rising to falling or falling to rising. In different paleogeographic environments, these transition points are manifested as stratigraphic discontinuities or as integrated strata that record the increase or decrease in accommodation space, respectively, usually forming sequence boundaries.

[0004] In sequence stratigraphy, sequences are usually divided into 1-6 levels, of which 1-3 levels correspond to tectonic genetic depositional cycles, belonging to low-frequency sequences (cycles), corresponding to megasequence, supersequence and sequence, respectively; 4-6 levels correspond to climatic genetic depositional cycles, belonging to high-frequency sequences (cycles), also known as Milankovitch cycles, corresponding to parasequence set, parasequence and rhythmite, respectively. In sequence stratigraphy research, sequence division is the basis, and sequence boundary identification is the key to sequence division. Generally, sequence boundaries include unconformities, transgressive onlap surfaces, water-flooded unconformities, paleokarst surfaces, volcanic event surfaces, and lithological conversion surfaces. Different levels of sequences correspond to different levels of sequence boundaries, such as regional unconformities and tectonic conversion surfaces, which usually correspond to low-frequency sequences, while lithological conversion surfaces and depositional unconformities correspond to high-frequency sequences.

[0005] The commonly used sequence boundary determination methods in geology mainly include lithology and lithofacies changes, core observation, INPEFA curve, and wavelet change spectrum. However, in areas where carbonate rocks are the main research object, lithofacies include grainy limestone, grain-containing muddy powder crystal limestone, muddy crystal limestone (containing grains), dolomite and dolomitic limestone, gypsum-containing muddy crystal limestone, etc. Multiple sets of thin layers are developed in shallow banks, bioclastic banks are relatively developed, and multiple sets of bank bodies are developed due to the influence of multiple cycles. For carbonate strata with strong heterogeneity, the existing sequence boundary determination methods can usually only reflect the boundaries of low-frequency sequence strata, and cannot identify higher-frequency sequence strata framework requirements. The current technical solutions cannot effectively determine the sequence boundaries of high-frequency seismic sequence strata. SUMMARY

[0006] In a first aspect, the embodiments of the present application provide a method for determining sequence boundaries of high-frequency seismic sequence strata, which can establish more accurate high-frequency sequence boundary bodies, and thus the sequence boundaries of the identified high-frequency seismic sequence strata are more accurate. The method comprises the following steps:

[0007] calculating a geological model grid according to a three-dimensional seismic data body of a target interval of a target area;

[0008] generating a relative geologic time model according to the geological model grid;

[0009] processing and analyzing the relative geologic time model to extract an initial seismic-based medium-low frequency first sequence boundary data body;

[0010] extracting a seismic-based medium-low frequency first sequence boundary curve of the target interval at a target well point from the initial seismic-based medium-low frequency first sequence boundary data body;

[0011] performing baseline removal processing on the seismic-based medium-low frequency first sequence boundary curve to obtain a seismic-based medium-low frequency second sequence boundary curve after baseline removal processing;

[0012] obtaining a seismic-based second sequence boundary data body through first waveform difference inversion according to the seismic-based medium-low frequency second sequence boundary curve after baseline removal processing;

[0013] extracting a seismic-based third sequence boundary curve of the target interval at the target well point from the seismic-based second sequence boundary data body;

[0014] fusing the seismic-based third sequence boundary curve as a base curve with a gamma curve reflecting a high-frequency sequence boundary, a porosity curve reflecting a high-frequency sequence boundary, a carbonate grain curve reflecting a high-frequency sequence boundary, a carbonate texture curve reflecting a high-frequency sequence boundary, a carbonate suture line frequency curve reflecting a sequence boundary, a bitumen content curve of carbonate reflecting a sequence boundary, and a dolomite content curve of carbonate reflecting a sequence boundary to obtain a seismic-based high-frequency tenth sequence boundary curve;

[0015] performing second waveform difference inversion on the target interval of the target area according to the seismic-based high-frequency tenth sequence boundary curve to obtain a seismic-based high-frequency third sequence boundary data body;

[0016] identifying sequence boundaries of high-frequency seismic sequence strata according to the seismic-based high-frequency third sequence boundary data body.

[0017] In a second aspect, the embodiments of the present application further provide a device for determining a sequence boundary of a high-frequency seismic sequence stratum, which can establish a more accurate high-frequency sequence boundary body, so that the sequence boundary of the identified high-frequency seismic sequence stratum is more accurate, and the device comprises:

[0018] a geological model grid calculation module, configured to calculate a geological model grid according to a three-dimensional seismic data body of a target interval of a target region;

[0019] a relative geologic time model generation module, configured to generate a relative geologic time model according to the geological model grid;

[0020] a sequence thickness boundary data body extraction module, configured to process and analyze the relative geologic time model, and extract an initial seismic-based medium-low frequency first sequence boundary data body;

[0021] a seismic-based sequence boundary curve, configured to extract a seismic-based medium-low frequency first sequence boundary curve of the target interval at a target well point from the initial seismic-based medium-low frequency first sequence boundary data body, perform baseline removal processing on the seismic-based medium-low frequency first sequence boundary curve to obtain a seismic-based baseline-removed medium-low frequency second sequence boundary curve, perform first waveform difference inversion according to the seismic-based baseline-removed medium-low frequency second sequence boundary curve to obtain a seismic-based second sequence boundary data body, and extract a seismic-based third sequence boundary curve of the target interval at the target well point from the seismic-based second sequence boundary data body;

[0022] a fusion processing module, configured to fuse the seismic-based third sequence boundary curve as a basic curve with a gamma curve reflecting a high-frequency sequence boundary, a porosity curve reflecting a high-frequency sequence boundary, a carbonate grain curve reflecting a high-frequency sequence boundary, a carbonate texture curve reflecting a high-frequency sequence boundary, a carbonate suture line frequency curve reflecting a sequence boundary, a bitumen content curve of carbonate reflecting a sequence boundary, and a dolomite content curve of carbonate reflecting a sequence boundary, to obtain a seismic-based high-frequency tenth sequence boundary curve;

[0023] a high-frequency seismic sequence boundary identification module, configured to perform second waveform difference inversion on the target interval of the target region according to the seismic-based high-frequency tenth sequence boundary curve, to obtain a seismic-based high-frequency third sequence boundary data body, and identify a sequence boundary of a high-frequency seismic sequence stratum according to the seismic-based high-frequency third sequence boundary data body.

[0024] In a third aspect, the embodiments of the present application further provide a computer device, which comprises a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor implements the above-mentioned method for determining a sequence boundary of a high-frequency seismic sequence stratum when executing the computer program.

[0025] In a fourth aspect, an embodiment of the present application further provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the method for determining sequence boundary of high-frequency seismic sequence stratum.

[0026] In a fifth aspect, an embodiment of the present application further provides a computer program product, which comprises a computer program. The computer program is executed by a processor to implement the method for determining sequence boundary of high-frequency seismic sequence stratum.

[0027] In the embodiment of the present application, the geological model grid is calculated according to the three-dimensional seismic data body of the target zone; the relative geological age model is generated according to the geological model grid; the initial seismic-based medium-low frequency first sequence boundary data body is extracted by processing and analyzing the relative geological age model; the seismic-based medium-low frequency first sequence boundary curve of the target zone is extracted from the initial seismic-based medium-low frequency first sequence boundary data body; the seismic-based medium-low frequency first sequence boundary curve is subjected to baseline removal processing to obtain the seismic-based medium-low frequency second sequence boundary curve after baseline removal processing; the seismic-based second sequence boundary data body is obtained by first waveform difference inversion according to the seismic-based medium-low frequency second sequence boundary curve after baseline removal processing; the seismic-based third sequence boundary curve of the target zone is extracted from the seismic-based second sequence boundary data body; the seismic-based high-frequency tenth sequence boundary curve is obtained by fusing the seismic-based third sequence boundary curve as the base curve with the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate rock particle curve reflecting the high-frequency sequence boundary, the carbonate rock texture curve reflecting the high-frequency sequence boundary, the carbonate rock suture line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate rock reflecting the sequence boundary, and the dolomite content curve of the carbonate rock reflecting the sequence boundary; the seismic-based high-frequency third sequence boundary data body is obtained by second waveform difference inversion of the target zone according to the seismic-based high-frequency tenth sequence boundary curve; and the sequence boundary of the high-frequency seismic sequence stratum is identified according to the seismic-based high-frequency third sequence boundary data body. Compared with the existing sequence interface determination method, the embodiment of the present application extracts the seismic-based medium-low frequency first sequence boundary curve of the target zone, and then performs multiple processing, including baseline removal processing, inversion processing, extraction processing, and fusion with multiple curves reflecting the high-frequency sequence boundary and curves reflecting the sequence boundary, to obtain the high-accuracy high-frequency sequence boundary curve, and finally performs waveform difference-based inversion to obtain the high-frequency sequence boundary data body, and the sequence boundary of the high-frequency seismic sequence stratum is identified according to the high-frequency sequence boundary data body. In the high-frequency sequence boundary body, the larger the value is, the closer it is to the sequence boundary. The above process fuses the gamma curve and the porosity curve of the target zone, and the inverted sequence boundary features are more obvious, thereby improving the accuracy and precision of the sequence interface body identified by fusing the information of the seismic-geological-logging, and making the precision of the sequence boundary of the high-frequency seismic sequence stratum identified higher. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to make the technical solutions in the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments or prior art description will be briefly introduced. Obviously, the accompanying drawings in the following description only need to be some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort. In the drawings:

[0029] Figure 1 The flow chart of the method for determining the sequence boundary of the high-frequency seismic sequence stratum in the embodiments of the present application;

[0030] Figure 2 The flow chart of the method for calculating the geological model grid in the embodiments of the present application;

[0031] Figure 3 The flow chart of the method for generating the relative geological time model in the embodiments of the present application;

[0032] Figure 4 The flow chart of the method for fusing multiple curves in the embodiments of the present application;

[0033] Figure 5 The example diagram of the relative geological time model calculated according to the three-dimensional seismic data body of the region in the embodiments of the present application;

[0034] Figure 6 The example diagram of the well tie profile of the initial seismic-based medium-low frequency first sequence boundary data body extracted by analyzing and extracting the relative geological time model in the embodiments of the present application;

[0035] Figure 7 The example diagram of the seismic-based sequence boundary curve in the embodiments of the present application;

[0036] Figure 8 The example diagram of the well tie profile of the seismic-based second sequence boundary data body obtained by the first wave form difference inversion in the embodiments of the present application;

[0037] Figure 9 The comparison diagram of the gamma curve before and after processing in the embodiments of the present application;

[0038] Figure 10 The comparison diagram of the porosity curve before and after processing in the embodiments of the present application;

[0039] Figure 11 The process example of fusing to obtain the high-frequency sequence boundary curve in the embodiments of the present application;

[0040] Figure 12 The well tie profile example of the high-frequency sequence boundary data body in the embodiments of the present application;

[0041] Figure 13The structural block diagram of the sequence boundary determination device for the high-frequency seismic sequence stratum of the embodiment of the present application is shown in the figure;

[0042] Figure 14 The schematic diagram of the computer device in the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical scheme and advantages of the embodiment of the present application more clear and obvious, the embodiment of the present application is further described in detail below in combination with the figures. Herein, the schematic embodiment of the present application and its description are used to explain the present application, but not as the limitation to the present application.

[0044] Figure 1 The flow chart of the sequence boundary determination method for the high-frequency seismic sequence stratum in the embodiment of the present application is shown in the figure, which comprises:

[0045] Step 101, calculating the geological model grid according to the three-dimensional seismic data body of the target area in the target layer section;

[0046] Step 102, generating the relative geological age model according to the geological model grid;

[0047] Step 103, processing and analyzing the relative geological age model, and extracting the initial seismic-based middle-low frequency first sequence boundary data body;

[0048] Step 104, extracting the seismic-based middle-low frequency first sequence boundary curve of the target well point in the target layer section from the initial seismic-based middle-low frequency first sequence boundary data body;

[0049] Step 105, performing the baseline removal processing on the seismic-based middle-low frequency first sequence boundary curve, and obtaining the seismic-based middle-low frequency second sequence boundary curve after the baseline removal processing;

[0050] Step 106, obtaining the seismic-based second sequence boundary data body through the first waveform difference inversion according to the seismic-based middle-low frequency second sequence boundary curve after the baseline removal processing;

[0051] Step 107, extracting the seismic-based third sequence boundary curve of the target well point in the target layer section from the seismic-based second sequence boundary data body;

[0052] Step 108, fusing the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate grain curve reflecting the high-frequency sequence boundary, the carbonate texture curve reflecting the high-frequency sequence boundary, the carbonate stitching line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate reflecting the sequence boundary and the dolomite content curve of the carbonate reflecting the sequence boundary at the target well point based on the third sequence boundary curve based on the earthquake as the basis curve, to obtain the high-frequency tenth sequence boundary curve based on the earthquake;

[0053] Step 109, according to the high-frequency tenth sequence boundary curve based on the earthquake, the second waveform difference inversion is carried out again on the target area of the target layer, to obtain the high-frequency third sequence boundary data body based on the earthquake;

[0054] Step 110, according to the high-frequency third sequence boundary data body based on the earthquake, the sequence boundary of the high-frequency seismic sequence stratum is identified.

[0055] In the embodiment of the present application, according to the three-dimensional seismic data body of the target area, the geological model grid is calculated; according to the geological model grid, the relative geological age model is generated; the relative geological age model is processed and analyzed to extract the initial seismic-based medium-low frequency first sequence boundary data body; from the initial seismic-based medium-low frequency first sequence boundary data body, the seismic-based medium-low frequency first sequence boundary curve of the target well point at the target layer is extracted; the seismic-based medium-low frequency first sequence boundary curve is subjected to baseline removal processing to obtain the seismic-based baseline-removed medium-low frequency second sequence boundary curve; according to the seismic-based baseline-removed medium-low frequency second sequence boundary curve, the first wave difference inversion is performed to obtain the seismic-based second sequence boundary data body; from the seismic-based second sequence boundary data body, the seismic-based third sequence boundary curve of the target well point at the target layer is extracted; the seismic-based third sequence boundary curve is taken as the base curve, and is fused with the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate grain curve reflecting the high-frequency sequence boundary, the carbonate texture curve reflecting the high-frequency sequence boundary, the carbonate stitching line frequency curve reflecting the sequence boundary, the asphalt content curve of the carbonate reflecting the sequence boundary, and the dolomite content curve of the carbonate reflecting the sequence boundary to obtain the seismic-based high-frequency tenth sequence boundary curve; according to the seismic-based high-frequency tenth sequence boundary curve, the second wave difference inversion is performed on the target layer of the target area to obtain the seismic-based high-frequency third sequence boundary data body; according to the seismic-based high-frequency third sequence boundary data body, the sequence boundary of the high-frequency seismic sequence stratum is identified. Compared with the existing sequence interface determination method, in the embodiment of the present application, after the seismic-based medium-low frequency first sequence boundary curve of the target well point at the target layer is extracted, multiple processing is performed, including baseline processing, inversion processing, extraction processing, and fusion with multiple curves reflecting the high-frequency sequence boundary and curves reflecting the sequence boundary, to obtain the high-frequency sequence boundary curve with high accuracy, and finally the inversion based on the wave difference is performed to obtain the high-frequency sequence boundary data body, according to which the sequence boundary of the high-frequency seismic sequence stratum is identified. In the high-frequency sequence boundary body, the larger the value is, the closer it is to the sequence boundary. Moreover, the above process fuses the gamma curve and the porosity curve of the target well point, and the inverted sequence boundary features are more obvious, thereby improving the accuracy and precision of the sequence interface body identified by the fusion of the seismic-geological-logging information, and making the precision of the sequence boundary of the high-frequency seismic sequence stratum identified higher.

[0056] In step 101, according to the three-dimensional seismic data body of the target area, the geological model grid is calculated;

[0057] This step is combined with actual logging and three-dimensional seismic data body in seismic data for calculation.

[0058] Referring to Figure 2 , calculating a geological model grid according to a three-dimensional seismic data volume of a target interval of a target area, comprising:

[0059] Step 201, determining an initial geological model grid according to a three-dimensional seismic data volume of a target interval of a target area; here, two methods of determining the initial address model grid are provided.

[0060] In an embodiment, determining an initial geological model grid according to a three-dimensional seismic data volume of a target interval of a target area, comprising:

[0061] When the three-dimensional seismic data volume has seismic horizon data, automatically tracking the seismic horizon data in the three-dimensional seismic data volume, and establishing a geological model grid with the tracked seismic horizon data as a constraint; wherein the seismic horizon data is already present in the three-dimensional seismic data volume;

[0062] When the three-dimensional seismic data volume does not have seismic horizon data, calculating an initial geological model grid according to waveform similarity and relative distance for at least one seed point in the three-dimensional seismic data volume of the target interval of the target area. In specific calculation, a certain algorithm can be used, such as a boundary control-local mapping based algorithm, which is not limited here.

[0063] Step 202, taking the initial geological model grid as a current geological model grid, and repeatedly executing the following steps until the fitting condition of the current geological model grid with the three-dimensional seismic data volume meets a preset condition:

[0064] Step 2021, interactively modifying the correlation between seismic horizons in the current geological model grid; here, each modification will affect the link between nodes in the model grid;

[0065] Step 2022, analyzing the fitting condition of the modified geological model grid with the three-dimensional seismic data volume; in specific implementation, preview can be used for analysis;

[0066] Step 2023, when the fitting condition does not meet the preset condition, optimizing the parameters of the current geological model grid, and taking the optimized geological model grid as the current geological model grid.

[0067] Through the above-mentioned loop iteration, the optimal geological model grid can be obtained.

[0068] In step 102, generating a relative geological age model according to the geological model grid;

[0069] Referring to Figure 3 In an embodiment, generating a relative geological age model according to the geological model grid, comprising:

[0070] Step 301, connecting and interpolating between the cell pieces of the geological model grid to obtain a processed geological model grid;

[0071] Step 302, assigning a relative geological age to each pixel in the processed geological model grid to generate an initial relative geological age model;

[0072] Step 303, extracting a plurality of horizon stacks from the initial relative geological age model to form a relative geological age model represented by a plurality of horizon stacks. The horizon stack generally includes tens of thousands, and the relative geological age model represented by tens of thousands of horizon stacks is more accurate.

[0073] Step 103, processing and analyzing the relative geological age model to extract an initial seismic-based medium-low frequency first sequence boundary data body; The sequence thickness boundary data body is an attribute data body that can reflect the sequence boundary of the stratum, can reflect the change of the vertical and horizontal sequence boundary, and can reflect the sequence interpretation combined with the earthquake. The larger the value is, the greater the same geological age difference is, and the more likely it is a sequence boundary. This is an interpretation method for establishing a high-frequency sequence stratigraphic framework based on the global thinking concept of seismic-geology.

[0074] Step 104, extracting a seismic-based medium-low frequency first sequence boundary curve of a target well point at a target layer section from the initial seismic-based medium-low frequency first sequence boundary data body.

[0075] In an embodiment, extracting a seismic-based medium-low frequency first sequence boundary curve of a target well point at a target layer section from the initial seismic-based medium-low frequency first sequence boundary data body includes:

[0076] Performing well-seismic calibration and first waveform difference inversion on the seismic-based medium-low frequency second sequence boundary curve after baseline removal to obtain a seismic-based second sequence boundary data body.

[0077] Performing baseline removal on the seismic-based medium-low frequency first sequence boundary curve to obtain a seismic-based medium-low frequency second sequence boundary curve after baseline removal. At this time, the seismic-based medium-low frequency second sequence boundary curve after baseline removal obtained can highlight the identification ability of the sequence thickness boundary curve obtained from the seismic data body to the sequence boundary.

[0078] In step 108, the seismic-based third sequence boundary curve is used as the base curve and is fused with the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate grain curve reflecting the high-frequency sequence boundary, the carbonate texture curve reflecting the high-frequency sequence boundary, the carbonate suture frequency curve reflecting the sequence boundary, the carbonate bitumen content curve reflecting the sequence boundary, and the carbonate dolomite content curve reflecting the sequence boundary at the target well point to obtain the seismic-based tenth sequence boundary curve.

[0079] See Figure 4 The specific integration steps include:

[0080] Step 401: Using the seismic-based third sequence boundary curve as the base curve, discretize it into multiple columns of data points. After normalizing the gamma curve reflecting the high-frequency sequence boundary, discretize it into multiple columns of data points and then superimpose it onto the multiple columns of data points corresponding to the seismic-based third sequence boundary curve at the corresponding depth point to form the seismic-based fourth high-frequency sequence boundary curve.

[0081] In one embodiment, the method further includes:

[0082] The gamma curve at the target well point is reversed to obtain the inverse gamma curve;

[0083] The inverse gamma curve is de-trended to obtain the de-trended gamma curve.

[0084] The gamma curve after detrending is then subjected to baseline removal to obtain a gamma curve that reflects the high-frequency sequence boundary.

[0085] Step 402: Using the seismic-based fourth sequence boundary curve as the base curve, the data points are discretized into multiple columns. After the porosity curve reflecting the high-frequency sequence boundary is normalized and discretized into multiple columns, it is superimposed onto the multiple columns of data points corresponding to the seismic-based fourth sequence boundary curve at the corresponding depth point, and fused into the seismic-based fifth high-frequency sequence boundary curve.

[0086] In one embodiment, the method further includes:

[0087] The porosity curve at the target well point is de-baselined to obtain a porosity curve that reflects the high-frequency sequence boundary.

[0088] Step 403: Using the seismic-based fifth sequence boundary curve as the base curve, the data points are discretized into multiple columns. The carbonate grain curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns. These columns are then superimposed onto the multiple columns of data points corresponding to the seismic-based fifth sequence boundary curve at the corresponding depth point, thus fusing them into the seismic-based sixth high-frequency sequence boundary curve. The carbonate grain curve reflecting the high-frequency sequence boundary is formed by quantifying carbonate grains into multiple columns of data points ranging from grainy limestone to argillaceous limestone.

[0089] For example, multiple columns of data points quantified from grainy limestone to argillaceous limestone can be -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6. The larger the negative value, the smaller the grain and the higher the argillaceous content. The larger the positive value, the larger the carbonate rock grain and the higher the carbonate rock grain content.

[0090] Among them, the larger the carbonate rock grains, the stronger the energy of seawater activity. Therefore, the carbonate rock grain curve that incorporates normalization can better reflect the sequence boundary information of carbonate rocks.

[0091] Step 404: Using the sixth sequence boundary curve based on seismicity as the base curve, it is discretized into multiple columns of data points. The carbonate rock texture curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the sixth sequence boundary curve based on seismicity at the corresponding depth point, and fused into the seventh high-frequency sequence boundary curve based on seismicity. Among them, the carbonate rock texture curve reflecting the high-frequency sequence boundary is the curve formed by quantifying the rock texture structure of carbonate rocks into multiple columns of data points.

[0092] For example, the texture of carbonate rocks is quantified by integers from 1 to 15, with larger values ​​indicating coarser textures.

[0093] Among them, the carbonate rock texture curve represents the structure and sedimentary cycle characteristics of carbonate rock sedimentary sequence. By integrating the carbonate rock texture curve, the high-frequency sequence boundaries of carbonate rocks can be reflected more precisely.

[0094] Step 405: Using the seismic-based seventh sequence boundary curve as the base curve, the data points are discretized into multiple columns. The suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based seventh sequence boundary curve at the corresponding depth point, and fused into the seismic-based eighth high-frequency sequence boundary curve. The suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is a curve formed by quantifying the suture frequency of carbonate rocks into multiple columns of data points.

[0095] For example, the frequency of sutures in carbonate rocks is quantified as an integer from 1 to 9, with larger values ​​indicating more sutures.

[0096] Among them, the suture frequency curve of carbonate rocks that reflects high-frequency sequence boundaries reflects the changes in tectonic and sequence boundaries caused by diagenesis. The greater the number of sutures, the stronger the reflection of progradation characteristics caused by marine regression, and the more obvious the sequence boundaries caused by coarse-grained sedimentation.

[0097] Step 406: Using the seismic-based eighth sequence boundary curve as the base curve, the data points are discretized into multiple columns. The bitumen content curve of carbonate rocks reflecting the sequence boundary is normalized and then discretized into multiple columns. These columns are then superimposed onto the multiple columns of data points corresponding to the seismic-based eighth sequence boundary curve at the corresponding depth point, and fused into the seismic-based ninth high-frequency sequence boundary curve. The bitumen content curve of carbonate rocks reflecting the sequence boundary is a curve formed by quantifying the bitumen content of carbonate rocks into multiple columns of data points.

[0098] For example, the bitumen content of carbonate rocks is quantified as 0.1 to 0.9, with a higher value indicating a higher bitumen content.

[0099] The bituminous content curve of carbonate rocks reflects the changes in temperature, pressure, and composition during the formation of carbonate reservoirs, and the resulting changes in sequence boundaries. Therefore, integrating the bituminous content curves of carbonate rocks that reflect sequence boundaries can help to accurately identify sequence boundaries.

[0100] Step 407: Using the ninth sequence boundary curve based on seismicity as the base curve, the data points are discretized into multiple columns. The dolomite content curve of carbonate rocks reflecting the sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the ninth sequence boundary curve based on seismicity at the corresponding depth points, and fused into the tenth high-frequency sequence boundary curve based on seismicity. Among them, the dolomite content curve of carbonate rocks reflecting the sequence boundary is a curve formed by quantifying the dolomite to limestone content of carbonate rocks into multiple columns of data points.

[0101] For example, the dolomite to limestone content of carbonate rocks is quantified as 0.1 to 0.9, with a higher value indicating a higher dolomite content. The higher the dolomite content, the more exposed the carbonate rock depositional environment, the shallower the seawater, and the carbonate sequence stratigraphy is located in the upper half-cycle of the regressive environment. The dolomite content curve of carbonate rocks, which reflects the sequence boundary, more finely reflects the high-frequency sequence boundary.

[0102] The final high-frequency sequence boundary curve based on earthquakes (the tenth high-frequency sequence boundary) can reflect information about the high-frequency sequence boundary.

[0103] In step 109, based on the high-frequency tenth sequence boundary curve based on seismic data, a second waveform difference inversion is performed on the target segment of the target area to obtain the high-frequency third sequence boundary data volume based on seismic data. At this time, the high-frequency sequence boundary data volume is clearer and more accurate.

[0104] In step 110, the sequence boundaries of high-frequency seismic sequence strata are identified based on the high-frequency third sequence boundary data volume based on seismic data. Finally, using the global thinking concept based on the high-frequency sequence interface data volume, the sequence boundaries of high-frequency seismic sequence strata with higher accuracy can be automatically identified.

[0105] The method proposed in this invention can be used for carbonate sequence boundaries, solving the problem that existing methods for obtaining carbonate sequence boundaries only yield low-cycle boundaries and have low resolution. In regions where carbonate oil and gas reservoir development is the primary focus, the genetic mechanism of carbonate reservoir heterogeneity is a fundamental geological issue restricting efficient development. In particular, research on complex carbonate episodic sequence cycles, sedimentary models, and corresponding multi-stage diagenetic evolution is weak. It is necessary to establish a high-frequency sedimentary cycle sequence stratigraphic framework to assist in the study of carbonate diagenetic evolution history and the reservoir-controlling mechanism of multiple geological factors. Therefore, the method of this invention has broad application prospects.

[0106] The following is a specific embodiment to illustrate the application of the method proposed in this invention.

[0107] Taking a region where carbonate oil and gas reservoirs are the main focus of development as an example... Figure 5 This is an example diagram of a relative geological age model calculated based on three-dimensional seismic data of the region in an embodiment of the present invention, wherein... Figure 5 (a) in the figure represents a three-dimensional seismic data volume. Figure 5 (b) in the image represents the geological model grid. Figure 5 (c) in the figure represents the relative geological age model. Figure 6 This is an example well-connected profile diagram illustrating the initial seismic-based mid-to-low frequency first sequence boundary data volume extracted from the relative geological age model in this embodiment of the invention. It shows the instantaneous changes in the relative geological age of each seismic sample point, highlighting the convergence and divergence regions of the geological layers. It is sensitive to unconformities, stratigraphic terminations (underlying, overlying), erosion, compaction, and stratigraphic thickness. The initial seismic-based mid-to-low frequency first sequence boundary data volume is equal to the relative isochronous geological time divided by the seismic two-way reflection time interval. If the denominator, the seismic two-way reflection time interval, is the same, then the larger the numerator, the larger the relative isochronous geological time, indicating a thicker stratigraphic layer.

[0108] Figure 7 This is an example diagram of a seismic-based sequence boundary curve in an embodiment of the present invention, wherein... Figure 7(a) in the figure represents the first sequence boundary curve based on earthquakes at medium and low frequencies. Figure 7 (b) in the figure is the curve after baseline removal processing of the initial sequence boundary curve. Figure 8 This is an example well profile diagram of the second sequence boundary data volume based on seismicity obtained through the first waveform difference inversion in an embodiment of the present invention. Finally, the extracted third sequence boundary curve based on seismicity can highlight the ability of the sequence thickness boundary curve obtained from seismic data to identify sequence boundaries.

[0109] Figure 9 This is a comparison image of the gamma curve before and after processing in an embodiment of the present invention, wherein, Figure 9 In the graph (a), the initial gamma curve is shown. Figure 9 (b) in the figure is the gamma curve reflecting the high-frequency sequence boundary.

[0110] Figure 10 This is a comparison diagram of the porosity curve before and after processing in an embodiment of the present invention, wherein, Figure 10 (a) in the figure represents the initial porosity curve. Figure 10 (b) in the figure represents the porosity curve reflecting the high-frequency sequence boundary.

[0111] Figure 11 This is an example of the process for obtaining a high-frequency tenth sequence boundary curve based on seismic data in an embodiment of the present invention, wherein... Figure 11 In the figure, (a) is the third sequence boundary curve based on earthquakes. Figure 11 (b) in the figure represents the processed sequence boundary curve. Figure 11 (c) in the figure represents the initial gamma curve. Figure 11 (d) in the figure represents the gamma curve reflecting the high-frequency sequence boundary. Figure 11 (e) in the figure represents the initial porosity curve. Figure 11 In the figure, (f) is the porosity curve reflecting the high-frequency sequence boundary. Figure 11 In the figure, (g) is the fifth high-frequency sequence boundary curve based on seismicity obtained by fusion. Other curves can be further fused to finally obtain the tenth high-frequency sequence boundary curve based on seismicity. Figure 12 This is an example of a well profile based on high-frequency third sequence boundary data volume based on seismicity in an embodiment of the present invention. At this time, the high-frequency third sequence boundary data volume based on seismicity is clearer and more accurate. Finally, using the global thinking concept based on high-frequency sequence interface data volume, the sequence boundary of high-frequency seismic sequence strata with higher accuracy can be automatically identified and obtained.

[0112] This invention also proposes a sequence boundary determination and generation device for high-frequency seismic sequence strata, the principle of which is similar to the sequence boundary determination and generation method for high-frequency seismic sequence strata, and will not be described in detail here.

[0113] Figure 13 This is a schematic diagram of a sequence boundary determination and generation device for high-frequency seismic sequence strata in an embodiment of the present invention, comprising:

[0114] The geological model mesh calculation module 1301 is used to calculate the geological model mesh based on the three-dimensional seismic data volume of the target layer in the target area;

[0115] The relative geological age model generation module 1302 is used to generate a relative geological age model based on the geological model grid.

[0116] The sequence thickness boundary data volume extraction module 1303 is used to process and analyze the relative geological age model and extract the initial seismic-based low- and medium-frequency first sequence boundary data volume.

[0117] The seismic sequence boundary curve 1304 is used to extract the seismic first-level seismic sequence boundary curve of the target segment at the target well point from the initial seismic first-level seismic sequence boundary data volume; the seismic first-level seismic sequence boundary curve is subjected to baseline removal processing to obtain the seismic second-level seismic sequence boundary curve; based on the seismic second-level seismic sequence boundary curve, the seismic second-level seismic sequence boundary data volume is obtained through the first waveform difference inversion; and the seismic third-level seismic sequence boundary curve of the target segment at the target well point is extracted from the seismic second-level seismic sequence boundary data volume.

[0118] The fusion processing module 1305 is used to fuse the seismic-based third sequence boundary curve with the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate rock grain curve reflecting the high-frequency sequence boundary, the carbonate rock texture curve reflecting the high-frequency sequence boundary, the carbonate rock suture frequency curve reflecting the sequence boundary, the carbonate rock bitumen content curve reflecting the sequence boundary, and the carbonate rock dolomite content curve reflecting the sequence boundary at the target well point to obtain the seismic-based high-frequency tenth sequence boundary curve.

[0119] The high-frequency seismic sequence boundary identification module 1306 is used to perform a second waveform difference inversion on the target segment of the target area based on the seismic-based high-frequency tenth sequence boundary curve to obtain the seismic-based high-frequency third sequence boundary data volume; and to identify the sequence boundary of the high-frequency seismic sequence strata based on the seismic-based high-frequency third sequence boundary data volume.

[0120] In one embodiment, the geological model grid calculation module is specifically used for:

[0121] Based on the 3D seismic data volume of the target layer in the target area, determine the initial geological model mesh;

[0122] Using the initial geological model mesh as the current geological model mesh, repeat the following steps until the current geological model mesh matches the preset conditions with the 3D seismic data volume:

[0123] In the current geological model grid, the correlation between seismic horizons is interactively corrected;

[0124] Analyze the fit between the corrected geological model mesh and the 3D seismic data volume;

[0125] If the matching conditions do not meet the preset conditions, optimize the parameters of the current geological model mesh and use the optimized geological model mesh as the current geological model mesh.

[0126] In one embodiment, the geological model grid calculation module is specifically used for:

[0127] When seismic horizon data exists in the three-dimensional seismic data volume, the seismic horizon data in the three-dimensional seismic data volume is automatically tracked, and a geological model mesh is established using the tracked seismic horizon data as a constraint.

[0128] When the three-dimensional seismic data volume does not contain seismic horizon data, an initial geological model mesh is calculated for at least one seed point in the three-dimensional seismic data volume of the target segment of the target area, based on waveform similarity and relative distance.

[0129] In one embodiment, the relative geological age model generation module is specifically used for:

[0130] Connect and interpolate the surface patches of the geological model mesh to obtain the processed geological model mesh;

[0131] Assign a relative geological age to each pixel in the processed geological model mesh to generate an initial relative geological age model;

[0132] Multiple stratigraphic stacks are extracted from the initial relative geological age model to form a relative geological age model represented by multiple stratigraphic stacks.

[0133] In one embodiment, the seismic sequence boundary curve is specifically used for:

[0134] Well-seismic calibration and first waveform difference inversion were performed on the mid-to-low frequency second sequence boundary curves after baseline removal based on seismic data to obtain the second sequence boundary data volume based on seismic data.

[0135] In one embodiment, the fusion processing module is specifically used for:

[0136] The gamma curve at the target well point is reversed to obtain the inverse gamma curve;

[0137] The inverse gamma curve is de-trended to obtain the de-trended gamma curve.

[0138] The gamma curve after detrending is then subjected to baseline removal to obtain a gamma curve that reflects the high-frequency sequence boundary.

[0139] In one embodiment, the fusion processing module is specifically used for:

[0140] The porosity curve at the target well point is de-baselined to obtain a porosity curve that reflects the high-frequency sequence boundary.

[0141] In one embodiment, the fusion processing module is specifically used for:

[0142] Using the seismic-based third sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The gamma curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based third sequence boundary curve at the corresponding depth point, and fused into the seismic-based fourth high-frequency sequence boundary curve.

[0143] Using the seismic-based fourth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. After the porosity curve reflecting the high-frequency sequence boundary is normalized and discretized into multiple columns of data points, it is superimposed onto the multiple columns of data points corresponding to the seismic-based fourth sequence boundary curve at the corresponding depth point, and fused into the seismic-based fifth high-frequency sequence boundary curve.

[0144] Using the seismic-based fifth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The carbonate grain curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based fifth sequence boundary curve at the corresponding depth points, and fused into the seismic-based sixth high-frequency sequence boundary curve. Among them, the carbonate grain curve reflecting the high-frequency sequence boundary is formed by quantifying carbonate grains into multiple columns of data points from grainy limestone to argillaceous limestone.

[0145] Using the sixth sequence boundary curve based on seismicity as the base curve, it is discretized into multiple columns of data points. The carbonate rock texture curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the sixth sequence boundary curve based on seismicity at the corresponding depth point, and fused into the seventh high-frequency sequence boundary curve based on seismicity. Among them, the carbonate rock texture curve reflecting the high-frequency sequence boundary is the curve formed by quantifying the rock texture structure of carbonate rocks into multiple columns of data points.

[0146] Using the seismic-based seventh sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based seventh sequence boundary curve at the corresponding depth point, and fused into the seismic-based eighth high-frequency sequence boundary curve. Among them, the suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is a curve formed by quantizing the suture frequency of carbonate rocks into multiple columns of data points.

[0147] Using the seismic-based eighth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The bitumen content curve of carbonate rocks reflecting the sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based eighth sequence boundary curve at the corresponding depth points, and fused into the seismic-based ninth high-frequency sequence boundary curve. Among them, the bitumen content curve of carbonate rocks reflecting the sequence boundary is a curve formed by quantifying the bitumen content of carbonate rocks into multiple columns of data points.

[0148] Using the ninth sequence boundary curve based on seismicity as the base curve, it is discretized into multiple columns of data points. The dolomite content curve of carbonate rocks reflecting the sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the ninth sequence boundary curve based on seismicity at the corresponding depth points, and fused into the tenth high-frequency sequence boundary curve based on seismicity. Among them, the dolomite content curve of carbonate rocks reflecting the sequence boundary is formed by quantifying the dolomite to limestone content of carbonate rocks into multiple columns of data points.

[0149] In summary, in the method and apparatus proposed in this invention, a geological model mesh is calculated based on the three-dimensional seismic data volume of the target segment in the target area; a relative geological age model is generated based on the geological model mesh; the relative geological age model is processed and analyzed to extract the initial seismic-based mid-to-low frequency first sequence boundary data volume; from the initial seismic-based mid-to-low frequency first sequence boundary data volume, the seismic-based mid-to-low frequency first sequence boundary curve of the target segment at the target well point is extracted; the seismic-based mid-to-low frequency first sequence boundary curve is subjected to baseline removal processing to obtain the seismic-based baseline-removed mid-to-low frequency second sequence boundary curve; based on the seismic-based baseline-removed mid-to-low frequency second sequence boundary curve, the seismic-based second sequence boundary data volume is obtained through the first waveform difference inversion; from the seismic-based second sequence boundary data volume, the target... The seismic-based third sequence boundary curve of the target segment at the well point is obtained. Using this seismic-based third sequence boundary curve as the base curve, it is fused with the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate grain curve reflecting the high-frequency sequence boundary, the carbonate texture curve reflecting the high-frequency sequence boundary, the carbonate suture frequency curve reflecting the sequence boundary, the carbonate bitumen content curve reflecting the sequence boundary, and the carbonate dolomite content curve reflecting the sequence boundary at the target well point to obtain the seismic-based tenth sequence boundary curve. Based on the seismic-based tenth sequence boundary curve, a second waveform difference inversion is performed on the target segment in the target area to obtain the seismic-based third sequence boundary data volume. Based on the seismic-based third sequence boundary data volume, the sequence boundaries of the high-frequency seismic sequence strata are identified. Compared with existing sequence boundary determination methods, this invention extracts the first low-to-medium frequency sequence boundary curve based on seismic data for the target segment at the target well point. This process involves multiple steps, including baseline processing, inversion processing, extraction processing, and fusion with various curves reflecting high-frequency sequence boundaries to obtain accurate high-frequency sequence boundary curves. Finally, waveform difference-based inversion is performed to obtain high-frequency sequence boundary data volumes. Based on these data volumes, the sequence boundaries of high-frequency seismic sequence strata are identified. Within these data volumes, larger values ​​indicate a closer approximation of a sequence boundary. Furthermore, the process incorporates gamma curves and porosity curves from the target well point, resulting in more pronounced sequence boundary features. This improves the accuracy and precision of identifying sequence boundaries using seismic-geological-well logging fusion information, leading to higher precision in identifying the sequence boundaries of high-frequency seismic sequence strata.

[0150] This invention also provides a computer device. Figure 14This is a schematic diagram of a computer device in an embodiment of the present invention. The computer device 1400 includes a memory 1410, a processor 1420, and a computer program 1430 stored in the memory 1410 and executable on the processor 1420. When the processor 1420 executes the computer program 1430, it implements the above-mentioned method for determining the sequence boundary of high-frequency seismic sequence strata.

[0151] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for determining the sequence boundaries of high-frequency seismic sequence strata.

[0152] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for determining the sequence boundaries of high-frequency seismic sequence strata.

[0153] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0154] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0155] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0156] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0157] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for determining the sequence boundaries of high-frequency seismic sequence strata, characterized in that, include: Calculate the geological model mesh based on the 3D seismic data volume of the target layer in the target area; Generate a relative geological age model based on the geological model grid; The relative geological age model was processed and analyzed to extract the initial seismic-based low- and medium-frequency first sequence boundary data volume; From the initial seismic-based low-frequency first sequence boundary data volume, extract the seismic-based low-frequency first sequence boundary curve of the target segment at the target well point; Baseline removal processing was performed on the seismically based mid-to-low frequency first sequence boundary curve to obtain the seismically based mid-to-low frequency second sequence boundary curve after baseline removal. Based on the mid-to-low frequency second sequence boundary curve after baseline removal based on seismic data, the second sequence boundary data volume based on seismic data is obtained through the first waveform difference inversion. Extract the seismic-based third sequence boundary curve of the target segment at the target well point from the seismic-based second sequence boundary data volume; Using the seismic-based third sequence boundary curve as the base curve, it is fused with the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate grain curve reflecting the high-frequency sequence boundary, the carbonate texture curve reflecting the high-frequency sequence boundary, the carbonate suture frequency curve reflecting the sequence boundary, the carbonate bitumen content curve reflecting the sequence boundary, and the carbonate dolomite content curve reflecting the sequence boundary at the target well point to obtain the seismic-based tenth sequence boundary curve. Based on the seismic-based high-frequency tenth sequence boundary curve, a second waveform difference inversion is performed on the target segment of the target area to obtain the seismic-based high-frequency third sequence boundary data volume. Sequence boundaries of high-frequency seismic sequence strata are identified based on seismic-based high-frequency third sequence boundary data volumes.

2. The method according to claim 1, characterized in that, Based on the 3D seismic data volume of the target layer in the target area, calculate the geological model mesh, including: Based on the 3D seismic data volume of the target layer in the target area, determine the initial geological model mesh; Using the initial geological model mesh as the current geological model mesh, repeat the following steps until the current geological model mesh matches the preset conditions with the 3D seismic data volume: In the current geological model grid, the correlation between seismic horizons is interactively corrected; Analyze the fit between the corrected geological model mesh and the 3D seismic data volume; If the matching conditions do not meet the preset conditions, optimize the parameters of the current geological model mesh and use the optimized geological model mesh as the current geological model mesh.

3. The method according to claim 2, characterized in that, Based on the 3D seismic data volume of the target layer in the target area, the initial geological model mesh is determined, including: When seismic horizon data exists in the three-dimensional seismic data volume, the seismic horizon data in the three-dimensional seismic data volume is automatically tracked, and a geological model mesh is established using the tracked seismic horizon data as a constraint. When the three-dimensional seismic data volume does not contain seismic horizon data, an initial geological model mesh is calculated for at least one seed point in the three-dimensional seismic data volume of the target segment of the target area, based on waveform similarity and relative distance.

4. The method according to claim 1, characterized in that, Based on the geological model grid, a relative geological age model is generated, including: Connect and interpolate the surface patches of the geological model mesh to obtain the processed geological model mesh; Assign a relative geological age to each pixel in the processed geological model mesh to generate an initial relative geological age model; Multiple stratigraphic stacks are extracted from the initial relative geological age model to form a relative geological age model represented by multiple stratigraphic stacks.

5. The method according to claim 1, characterized in that, Based on the mid-to-low frequency second sequence boundary curve after baseline removal based on seismic data, the second sequence boundary data volume based on seismic data is obtained through the first waveform difference inversion, including: Well-seismic calibration and first waveform difference inversion were performed on the mid-to-low frequency second sequence boundary curves after baseline removal based on seismic data to obtain the second sequence boundary data volume based on seismic data.

6. The method according to claim 1, characterized in that, Also includes: The gamma curve at the target well point is reversed to obtain the inverse gamma curve; The inverse gamma curve is de-trended to obtain the de-trended gamma curve. The gamma curve after detrending is then subjected to baseline removal to obtain a gamma curve that reflects the high-frequency sequence boundary.

7. The method according to claim 1, characterized in that, Also includes: The porosity curve at the target well point is de-baselined to obtain a porosity curve that reflects the high-frequency sequence boundary.

8. The method according to claim 1, characterized in that, Using the seismic-based third sequence boundary curve as the base curve, it is fused with the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate grain size curve reflecting the high-frequency sequence boundary, the carbonate texture curve reflecting the high-frequency sequence boundary, the carbonate suture frequency curve reflecting the sequence boundary, the bitumen content curve reflecting the sequence boundary, and the dolomite content curve reflecting the sequence boundary at the target well point, respectively, to obtain the seismic-based high-frequency tenth sequence boundary curve, including: Using the seismic-based third sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The gamma curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based third sequence boundary curve at the corresponding depth point, and fused into the seismic-based fourth high-frequency sequence boundary curve. Using the seismic-based fourth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. After the porosity curve reflecting the high-frequency sequence boundary is normalized and discretized into multiple columns of data points, it is superimposed onto the multiple columns of data points corresponding to the seismic-based fourth sequence boundary curve at the corresponding depth point, and fused into the seismic-based fifth high-frequency sequence boundary curve. Using the seismic-based fifth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The carbonate grain curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based fifth sequence boundary curve at the corresponding depth points, and fused into the seismic-based sixth high-frequency sequence boundary curve. Among them, the carbonate grain curve reflecting the high-frequency sequence boundary is formed by quantifying carbonate grains into multiple columns of data points from grainy limestone to argillaceous limestone. Using the sixth sequence boundary curve based on seismicity as the base curve, it is discretized into multiple columns of data points. The carbonate rock texture curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the sixth sequence boundary curve based on seismicity at the corresponding depth point, and fused into the seventh high-frequency sequence boundary curve based on seismicity. Among them, the carbonate rock texture curve reflecting the high-frequency sequence boundary is the curve formed by quantifying the rock texture structure of carbonate rocks into multiple columns of data points. Using the seismic-based seventh sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based seventh sequence boundary curve at the corresponding depth point, and fused into the seismic-based eighth high-frequency sequence boundary curve. Among them, the suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is a curve formed by quantizing the suture frequency of carbonate rocks into multiple columns of data points. Using the seismic-based eighth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The bitumen content curve of carbonate rocks reflecting the sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based eighth sequence boundary curve at the corresponding depth points, and fused into the seismic-based ninth high-frequency sequence boundary curve. Among them, the bitumen content curve of carbonate rocks reflecting the sequence boundary is a curve formed by quantifying the bitumen content of carbonate rocks into multiple columns of data points. Using the ninth sequence boundary curve based on seismicity as the base curve, it is discretized into multiple columns of data points. The dolomite content curve of carbonate rocks reflecting the sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the ninth sequence boundary curve based on seismicity at the corresponding depth points, and fused into the tenth high-frequency sequence boundary curve based on seismicity. Among them, the dolomite content curve of carbonate rocks reflecting the sequence boundary is formed by quantifying the dolomite to limestone content of carbonate rocks into multiple columns of data points.

9. A sequence boundary determination device for high-frequency seismic sequence strata, characterized in that, include: The geological model mesh calculation module is used to calculate the geological model mesh based on the three-dimensional seismic data volume of the target layer in the target area; The relative geological age model generation module is used to generate a relative geological age model based on the geological model grid. The sequence thickness boundary data volume extraction module is used to process and analyze the relative geological age model and extract the initial seismic-based low- and medium-frequency first sequence boundary data volume. Seismic sequence boundary curves are used to extract the first seismic sequence boundary curve of the target segment at the target well point from the initial seismic-based mid-to-low frequency first sequence boundary data volume; the first seismic sequence boundary curve is then subjected to baseline removal processing to obtain the second seismic sequence boundary curve; based on the second seismic sequence boundary curve, the second seismic sequence boundary data volume is obtained through a first waveform difference inversion; and the third seismic sequence boundary curve of the target segment at the target well point is extracted from the second seismic sequence boundary data volume. The fusion processing module is used to fuse the seismically-based third sequence boundary curve with the gamma curve reflecting the high-frequency sequence boundary, the porosity curve reflecting the high-frequency sequence boundary, the carbonate grain curve reflecting the high-frequency sequence boundary, the carbonate texture curve reflecting the high-frequency sequence boundary, the carbonate suture frequency curve reflecting the sequence boundary, the carbonate bitumen content curve reflecting the sequence boundary, and the carbonate dolomite content curve reflecting the sequence boundary at the target well point to obtain the seismically-based high-frequency tenth sequence boundary curve. The high-frequency seismic sequence boundary identification module is used to perform a second waveform difference inversion on the target segment of the target area based on the seismic-based high-frequency tenth sequence boundary curve to obtain the seismic-based high-frequency third sequence boundary data volume; and to identify the sequence boundary of the high-frequency seismic sequence strata based on the seismic-based high-frequency third sequence boundary data volume.

10. The apparatus according to claim 9, characterized in that, The geological model grid calculation module is specifically used for: Based on the 3D seismic data volume of the target layer in the target area, determine the initial geological model mesh; Using the initial geological model mesh as the current geological model mesh, repeat the following steps until the current geological model mesh matches the preset conditions with the 3D seismic data volume: In the current geological model grid, the correlation between seismic horizons is interactively corrected; Analyze the fit between the corrected geological model mesh and the 3D seismic data volume; If the matching conditions do not meet the preset conditions, optimize the parameters of the current geological model mesh and use the optimized geological model mesh as the current geological model mesh.

11. The apparatus according to claim 10, characterized in that, The geological model grid calculation module is specifically used for: When seismic horizon data exists in the three-dimensional seismic data volume, the seismic horizon data in the three-dimensional seismic data volume is automatically tracked, and a geological model mesh is established using the tracked seismic horizon data as a constraint. When the three-dimensional seismic data volume does not contain seismic horizon data, an initial geological model mesh is calculated for at least one seed point in the three-dimensional seismic data volume of the target segment of the target area, based on waveform similarity and relative distance.

12. The apparatus according to claim 9, characterized in that, The relative geological age model generation module is specifically used for: Connect and interpolate the surface patches of the geological model mesh to obtain the processed geological model mesh; Assign a relative geological age to each pixel in the processed geological model mesh to generate an initial relative geological age model; Multiple stratigraphic stacks are extracted from the initial relative geological age model to form a relative geological age model represented by multiple stratigraphic stacks.

13. The apparatus according to claim 9, characterized in that, Sequence boundary curves based on earthquakes are specifically used for: Well-seismic calibration and first waveform difference inversion were performed on the mid-to-low frequency second sequence boundary curves after baseline removal based on seismic data to obtain the second sequence boundary data volume based on seismic data.

14. The apparatus according to claim 9, characterized in that, The fusion processing module is also used for: The gamma curve at the target well point is reversed to obtain the inverse gamma curve; The inverse gamma curve is de-trended to obtain the de-trended gamma curve. The gamma curve after detrending is then subjected to baseline removal to obtain a gamma curve that reflects the high-frequency sequence boundary.

15. The apparatus according to claim 9, characterized in that, The fusion processing module is also used for: The porosity curve at the target well point is de-baselined to obtain a porosity curve that reflects the high-frequency sequence boundary.

16. The apparatus according to claim 9, characterized in that, The fusion processing module is specifically used for: Using the seismic-based third sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The gamma curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based third sequence boundary curve at the corresponding depth point, and fused into the seismic-based fourth high-frequency sequence boundary curve. Using the seismic-based fourth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. After the porosity curve reflecting the high-frequency sequence boundary is normalized and discretized into multiple columns of data points, it is superimposed onto the multiple columns of data points corresponding to the seismic-based fourth sequence boundary curve at the corresponding depth point, and fused into the seismic-based fifth high-frequency sequence boundary curve. Using the seismic-based fifth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The carbonate grain curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based fifth sequence boundary curve at the corresponding depth points, and fused into the seismic-based sixth high-frequency sequence boundary curve. Among them, the carbonate grain curve reflecting the high-frequency sequence boundary is formed by quantifying carbonate grains into multiple columns of data points from grainy limestone to argillaceous limestone. Using the sixth sequence boundary curve based on seismicity as the base curve, it is discretized into multiple columns of data points. The carbonate rock texture curve reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the sixth sequence boundary curve based on seismicity at the corresponding depth point, and fused into the seventh high-frequency sequence boundary curve based on seismicity. Among them, the carbonate rock texture curve reflecting the high-frequency sequence boundary is the curve formed by quantifying the rock texture structure of carbonate rocks into multiple columns of data points. Using the seismic-based seventh sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based seventh sequence boundary curve at the corresponding depth point, and fused into the seismic-based eighth high-frequency sequence boundary curve. Among them, the suture frequency curve of carbonate rocks reflecting the high-frequency sequence boundary is a curve formed by quantizing the suture frequency of carbonate rocks into multiple columns of data points. Using the seismic-based eighth sequence boundary curve as the base curve, it is discretized into multiple columns of data points. The bitumen content curve of carbonate rocks reflecting the sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the seismic-based eighth sequence boundary curve at the corresponding depth points, and fused into the seismic-based ninth high-frequency sequence boundary curve. Among them, the bitumen content curve of carbonate rocks reflecting the sequence boundary is a curve formed by quantifying the bitumen content of carbonate rocks into multiple columns of data points. Using the ninth sequence boundary curve based on seismicity as the base curve, it is discretized into multiple columns of data points. The dolomite content curve of carbonate rocks reflecting the sequence boundary is normalized and then discretized into multiple columns of data points. These are then superimposed onto the multiple columns of data points corresponding to the ninth sequence boundary curve based on seismicity at the corresponding depth points, and fused into the tenth high-frequency sequence boundary curve based on seismicity. Among them, the dolomite content curve of carbonate rocks reflecting the sequence boundary is formed by quantifying the dolomite to limestone content of carbonate rocks into multiple columns of data points.

17. A computer 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 computer program, it implements the method of any one of claims 1 to 8.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 8.

19. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 8.

Images