Well-seismic combined post-stack fracture prediction model construction method and device

Abstract

The invention relates to the field of geophysics and hydraulic fracturing engineering, in particular to a well-seismic combined post-stack fracture prediction model construction method and device. The method comprises the following steps: constructing a fracture seismic facies initial model of a research area according to post-stack seismic data and drilling information; acquiring fracture density interpretation data of the sample well, and determining fracture seismic attributes of the sample well; sampling fracture seismic attributes into the seismic facies initial model to obtain a fracture seismic facies model constrained by fracture density; and acquiring hydraulic fracturing pressure sudden drop data of the sample well, and sampling the hydraulic fracturing pressure sudden drop data into the fracture density constrained fracture seismic facies model to obtain a fracture prediction model. According to the method, a post-stack seismic fracture phase model is constrained by using a static fracture density result of imaging logging or multi-pole acoustic logging information, and a seismic fracture prediction model is dynamically constrained based on hydraulic fracturing pressure drop, so that the prediction precision of natural fractures is improved, and effective fractures are predicted and evaluated.

Description

Technical Field

[0001] This specification relates to the field of geophysics and hydraulic fracturing engineering, and in particular to a method and device for constructing a post-stack fracture prediction model combining well-seismic analysis and prediction. Background Art

[0002] Natural fractures are developed in complex reservoirs such as conglomerate, carbonate fracture reservoirs, tight sandstone, and shale oil to varying degrees, and the degree of fracture development determines the production of a single well to a certain extent. However, it is difficult to accurately predict the density, development characteristics, and distribution of fractures based solely on post-stack seismic data.

[0003] A similar post-stack seismic fracture prediction method is mentioned in the prior art. A fracture zone with a set fracture density is established based on the post-stack seismic data body of the work area, the structural interpretation layer of the study group, the geology describing the fracture development characteristics, and the logging data. The relationship between the variance body attribute values ​​under the corresponding different time window lengths is calculated to obtain the variance body of the work area with the set fracture density, and the variance attribute body of the work area with the set fracture density interval is obtained. Fracture prediction is performed based on the obtained variance attribute body of fracture prediction in the work area. This method realizes the quantitative prediction of medium-large scale fracture zones. However, the prior art predicts fracture zones based only on post-stack seismic data and fracture development characteristics, and the prediction results obtained still have the problem of inaccuracy. Summary of the invention

[0004] In order to solve the problems not solved in the prior art, the embodiments of this specification provide a method and device for constructing a post-stack fracture prediction model combining wellbore and seismic.

[0005] The embodiments of the present specification provide a method for constructing a post-stack fracture prediction model combining well and seismic data, the method comprising: constructing an initial fracture seismic phase model of a study area based on post-stack seismic data and drilling information; obtaining fracture density interpretation data of sample wells to determine fracture seismic attributes of the sample wells; sampling the fracture seismic attributes into the initial seismic phase model to obtain a fracture seismic phase model constrained by fracture density; obtaining hydraulic fracturing pressure drop data of sample wells, sampling the hydraulic fracturing pressure drop data into the fracture seismic phase model constrained by fracture density to obtain a fracture prediction model.

[0006] According to one aspect of an embodiment of the present specification, the drilling information includes at least one of: lost circulation, kick, or full hydrocarbon display.

[0007] According to one aspect of an embodiment of the present specification, constructing an initial model of a fracture seismic phase based on post-stack seismic data and drilling information includes: obtaining denoised post-stack seismic data; extracting seismic three-dimensional curvature, coherence, maximum likelihood volume and ant volume attributes from the post-stack seismic data; using the drilling information in the actual drilling process to calibrate the fracture seismic attributes of the study area, and selecting the fracture seismic attributes with a degree of fit greater than a preset threshold as the fracture seismic phase; and establishing an initial model of the fracture seismic phase corresponding to the study area based on the seismic interpretation horizon and fault interpretation information of the post-stack seismic data.

[0008] According to one aspect of an embodiment of the present specification, based on the seismic interpretation horizons and fault interpretation information of post-stack seismic data, an initial model of the fracture seismic phase corresponding to the study area is established, including: performing structural interpretation on the post-stack seismic data to determine the seismic interpretation horizons and fault interpretation information; using the seismic interpretation horizons and the fault interpretation information to establish a grid model, and inputting the fracture seismic phase into the grid model to obtain the initial model of the fracture seismic phase.

[0009] According to one aspect of an embodiment of the present specification, sampling the fracture seismic attributes into the initial seismic phase model to obtain a fracture seismic phase model constrained by fracture density includes: normalizing the fracture density data of the sample well to obtain the fracture density of the known sample well; simulating the fracture density of the point to be estimated based on the initial fracture seismic phase model and the known fracture density of the sample well; sampling the fracture density of the known sample well and the fracture density of the point to be estimated into the initial fracture seismic phase model based on the longitudinal resolution of the sample well and the resolution of the initial fracture seismic phase model to obtain a fracture seismic phase model constrained by fracture density.

[0010] According to one aspect of an embodiment of the present specification, the fracture density of the point to be estimated is determined as the fracture density to be simulated. According to the initial model of the fracture seismic phase and the fracture density of the known sample well, simulating the fracture density of the point to be estimated includes: determining the weight of the fracture density to be simulated at the first adjacent point according to the covariance between the fracture density to be simulated and the second adjacent point, the covariance between the fracture density to be simulated and the fracture density of the known sample well at the first adjacent point and the point to be estimated, and the covariance between the fracture density to be simulated and the second adjacent point; determining the weight of the fracture density to be simulated at the first adjacent point according to the covariance between the fracture density to be simulated and the fracture density of the known sample well at the first adjacent point and the point to be estimated ... of the known sample well and the fracture density to be simulated The weight of the known sample well fracture density at the point to be estimated is determined according to the covariance between the fracture densities of the known sample wells, the variance of the fracture density of the known sample wells at the point to be estimated, and the covariance between the fracture density of the known sample wells and the fracture density to be simulated at the point to be estimated; the cokriging mean of the fracture density to be simulated at the point to be estimated is determined according to the weight of the fracture density to be simulated at the first adjacent point, the weight of the fracture density of the known sample wells at the point to be estimated, the variable value of the fracture density to be simulated at the first adjacent point and the variable value of the fracture density of the known sample wells at the point to be estimated; the fracture density of the point to be estimated is simulated according to the cokriging mean of the fracture density to be simulated at all the points to be estimated in the initial seismic phase model.

[0011] According to one aspect of an embodiment of the present specification, hydraulic fracturing pressure data of a sample well is obtained, and sampling the hydraulic fracturing pressure data into a fracture seismic phase model constrained by fracture density includes: extracting pressure drop data from a hydraulic fracturing pressure construction curve of the sample well and normalizing the data to obtain pressure drop normalized data; determining points corresponding to the pressure drop normalized data as known points; simulating pressure drop data of unknown points using a Gaussian random cokriging simulation method; and sampling the pressure drop data of unknown points and known points into a fracture seismic phase model constrained by fracture density to construct a fracture prediction model.

[0012] The embodiments of the present specification also provide a method and device for constructing a post-stack fracture prediction model combining well and seismic data, the device comprising: a model construction unit, used to construct an initial model of the fracture seismic phase of the study area based on the post-stack seismic data and drilling information; a fracture seismic attribute determination unit, used to obtain fracture density interpretation data of the sample well and determine the fracture seismic attributes of the sample well; a fracture seismic phase model determination unit, used to sample the fracture seismic attributes into the initial model of the seismic phase to obtain a fracture seismic phase model constrained by the fracture density; a fracture prediction model determination unit, used to obtain the hydraulic fracturing pressure drop data of the sample well, sample the hydraulic fracturing pressure drop data into the fracture seismic phase model constrained by the fracture density, and obtain a fracture prediction model.

[0013] The embodiment of the present specification also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method for constructing a post-stack fracture prediction model combining well-seismic and post-stack fracture prediction model when executing the computer program.

[0014] The embodiments of the present specification also provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for constructing a post-stack fracture prediction model combining wellbore and seismic is implemented.

[0015] This manual utilizes the advantages of imaging logging and multipole acoustic logging data in the interpretation of fracture density in the vertical direction of the wellbore with high accuracy and reliability, and the advantages of post-stack 3D seismic data in fracture prediction and dynamic identification of fractures with sudden pressure drop of hydraulic fracturing, and effectively combines the advantages of logging, seismic and hydraulic fracturing to carry out fracture prediction by combining well logging and seismic. This method can improve the accuracy and reliability of fracture prediction and realize the prediction and evaluation of effective fractures. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a flow chart of a method for constructing a post-stack fracture prediction model combining wellbore and seismic in an embodiment of this specification;

[0018] Figure 2 The flowchart of a method for determining the correlation between an initial three-dimensional geological model and real gravity anomaly data according to an embodiment of the present specification is shown;

[0019] Figure 3 The figure is a flow chart of a method for adjusting an initial three-dimensional geological model according to an embodiment of the present specification;

[0020] Figure 4 This is a flow chart of a method for constructing an initial three-dimensional geological model according to an embodiment of this specification;

[0021] Figure 5 The figure is a flow chart of a method for determining the thermophysical property parameters of a target area according to an embodiment of the present specification;

[0022] Figure 6 The figure shows a flow chart of a method for setting a temperature boundary for a three-dimensional geological model according to an embodiment of the present specification;

[0023] Figure 7 It is a schematic diagram of the structure of a well-seismic combined post-stack fracture prediction model building device according to an embodiment of this specification;

[0024] Figure 8 A crack prediction map of a post-stack ant body according to an embodiment of this specification;

[0025] Fig. 9 This is a WellB single well imaging logging fracture density interpretation diagram of the embodiment of this specification;

[0026] Fig.10 A seismic fracture prediction plan view constrained by imaging logging fracture density is provided for an embodiment of the present specification;

[0027] Fig.11 This is a pressure drop diagram of the hydraulic fracture development section of WellA well according to the embodiment of this specification;

[0028] Fig. 12A This is a high-precision fracture prediction plane map of static fracture density of imaging logging and dynamic pressure drop constraint of hydraulic fracturing according to the embodiment of this specification;

[0029] Fig. 12B This is a high-precision fracture prediction profile diagram of an imaging logging static fracture density and hydraulic fracturing dynamic pressure drop constraint in the embodiment of this specification;

[0030] Fig.13 The figure shows a schematic diagram of the structure of a computer device according to an embodiment of the present specification.

[0031] Description of the accompanying symbols:

[0032] 701, model building unit;

[0033] 702. Fracture seismic attribute determination unit;

[0034] 703. Fracture seismic phase model determination unit;

[0035] 704. Crack prediction model determination unit;

[0036] 1302. Computer equipment;

[0037] 1304. Processor;

[0038] 1306. Memory;

[0039] 1308, driving mechanism;

[0040] 1310, input / output module;

[0041] 1312. Input devices;

[0042] 1314. Output device;

[0043] 1316. Presentation equipment;

[0044] 1318. Graphical user interface;

[0045] 1320, network interface;

[0046] 1322, communication link;

[0047] 1324. Communication bus. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0049] It should be noted that the terms "first", "second", etc. in the description and claims of this specification and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of this specification described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0050] This specification provides method operation steps as described in the embodiments or flow charts, but more or fewer operation steps may be included based on routine or non-creative work. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the system or device product is executed in practice, it can be executed in the order of the method shown in the embodiments or the drawings or in parallel.

[0051] It should be noted that the method for constructing a post-stack fracture prediction model combining well-seismic analysis in this specification can be used in the field of oil and gas field exploration and development, and this specification does not limit the application field of the method and device for constructing a post-stack fracture prediction model combining well-seismic analysis.

[0052] Figure 1The flowchart of a method for constructing a post-stack fracture prediction model combining wellbore and seismic analysis according to an embodiment of the present specification is shown, which specifically includes the following steps:

[0053] Step 101, constructing an initial model of fracture seismic phases in the study area based on post-stack seismic data and drilling information.

[0054] In this step, multiple seismic records are stacked according to a certain algorithm to obtain post-stack three-dimensional seismic data. Through stacking, the signal of the seismic data can be enhanced, making the features that may have been masked by noise more obvious. Furthermore, the post-stack seismic data is subjected to denoising processing such as smoothing or filtering to eliminate the influence of noise on the effective signal as much as possible, thereby improving the signal-to-noise ratio, enhancing the readability and analysis effect of seismic data, better understanding and interpretation of seismic data, and more accurately evaluating the properties and structure of underground rocks.

[0055] In practical applications, it is difficult to effectively identify fractures based on a single seismic attribute, and the fracture scales identified by different seismic attributes are limited, making it impossible to effectively identify the development of fractures at different scales. Therefore, the drilling information generated by the sample wells during the drilling process is combined with the post-stack seismic data to construct an initial model of the fracture seismic phase corresponding to the study area, which can effectively predict the degree of fracture development in the study area.

[0056] Specifically, drilling information includes: well leakage, well kick, full hydrocarbon display and other common situations in drilling projects. Among them, well leakage refers to a situation in which various working fluids (including drilling fluid, cement slurry, completion fluid and other fluids) directly enter the formation under the action of pressure difference during downhole operations such as drilling, cementing, testing or well repair. Well leakage includes three types: permeability loss, fracture loss and cave loss. Most drilling processes have leakage to varying degrees. Severe well leakage will cause the pressure in the well to drop, affecting normal drilling, causing well wall instability, inducing formation fluid to flow into the wellbore and may cause blowout.

[0057] Among them, a kick refers to the phenomenon that underground fluid or mud suddenly rushes into the wellbore due to pressure. During the drilling process, if the underground pressure exceeds the pressure in the wellbore, a kick may occur. The full hydrocarbon display means that the hydrocarbon component content is continuously monitored and presented to geologists in the form of a full hydrocarbon curve, which plays a very important role in immediately understanding the gas content of the formation. Especially in high-pressure, low-permeability fractured formations, the full hydrocarbon curve shows a high value display feature.

[0058] Step 102, obtaining fracture density interpretation data of the sample wells, and determining fracture seismic attributes of the sample wells.

[0059] In this step, the fracture density interpretation data of the sample wells include: single well imaging logging or multipole acoustic logging fracture density interpretation. For example, the single well imaging logging or multipole acoustic logging fracture density interpretation of WellB is obtained, such as Fig. 9 shown.

[0060] Furthermore, the fracture density interpretation data of the sample wells are normalized and scaled to the range of 0-1. Specifically, the normalization process is as follows:

[0061] B_norm=(B-B_min) / (B_max-B_min), where B_norm represents the normalized fracture density, and B_max and B_min represent the maximum fracture density and the minimum fracture density interpreted by imaging logging or multipole acoustic logging, respectively.

[0062] Step 103, sampling the fracture seismic attributes into the initial seismic phase model to obtain a fracture seismic phase model constrained by fracture density.

[0063] In this step, the seismic attributes of the fractures on the well are sampled into the grid model. Because the length and scale ratio of the well trajectory of the actual well are inconsistent with the length and initial ratio of the grid model, it is necessary to sample the seismic attributes of the fractures on the sample well into the grid model at a certain ratio. For example, the sampling rate of the fracture density interpretation data of the sample well WellB in the longitudinal direction of the wellbore is 0.125 meters / point, that is, the wellbore trajectory is divided according to a point of 0.125 meters. The grid model is divided into 1 meter / point in the longitudinal direction. If WellB well has 5 fractures at the 3000th meter in the longitudinal direction of the wellbore and 4 fractures at the 3000.5th meter, when the fracture density at these two positions is sampled into the grid model according to the division ratio of the grid model, that is, the fracture density value of 3000-3001 meters in the grid model is 4.5 fractures, so that all the seismic attributes of the fractures on the sample well are sampled into the grid model.

[0064] Step 104, obtaining hydraulic fracturing pressure drop data of the sample wells, sampling the hydraulic fracturing pressure drop data into a fracture seismic phase model constrained by fracture density, and obtaining a fracture prediction model.

[0065] In this step, the hydraulic fracturing pressure drop data of the sample well is collected from the hydraulic fracturing pressure construction curve of the sample well. For example, according to the hydraulic fracturing pressure construction curve of WellA, the well section with sudden pressure drop and the pressure values ​​before and after the sudden pressure drop are extracted to obtain the hydraulic fracturing pressure drop data.

[0066] Similarly, the pressure drop value of the well pressure drop section in the hydraulic fracturing pressure data is normalized and the pressure drop value is scaled to the range of 0-1.

[0067] The normalization formula is as follows:

[0068] S_norm = (S-S_min) / (S_max-S_min); S_norm represents the normalized hydraulic fracturing pressure drop value; S_max and S_min represent the maximum and minimum values ​​of the hydraulic fracturing pressure drop value, respectively.

[0069] According to the same principle as the fracture density data, the normalized hydraulic fracturing pressure drop data are sampled into the fracture seismic phase model constrained by the fracture density to obtain the fracture prediction model.

[0070] This manual targets natural fractures in conglomerate bodies, carbonate fracture reservoirs, tight sandstones, and shale oil reservoirs. It uses the advantages of high accuracy and reliability of fracture density interpretation in the vertical direction of the wellbore using imaging logging or multipole acoustic logging data. It can better reflect fracture information by combining post-stack 3D seismic data, and hydraulic fracturing pressure drop can dynamically reflect fracture information. The organic combination of the three can improve the accuracy and reliability of fracture prediction and achieve effective fracture prediction and evaluation.

[0071] Figure 2 The flowchart of a method for constructing a fracture earthquake initial model according to an embodiment of the present specification is shown, which specifically includes the following steps:

[0072] Step 201, obtaining denoised post-stack seismic data.

[0073] In this step, the post-stack seismic data that has undergone denoising is the post-stack seismic data that has undergone interpretive preprocessing. The interpretive preprocessing can effectively improve the signal-to-noise ratio of the post-stack seismic data, and the recognition accuracy of fracture identification for the current reservoir can be significantly improved.

[0074] Step 202: extract seismic 3D curvature, coherence, maximum likelihood volume and ant volume attribute volumes from the post-stack seismic data.

[0075] In this step, seismic attributes are extracted from the post-stack seismic data, and the geometric shape and characteristics of the seismic waves are derived through mathematical transformation. The seismic attributes are related to the geometric shape of the waveform-level seismic horizon. The seismic attributes include at least one of high-precision coherence, maximum likelihood, maximum curvature, and ant volume tracking.

[0076] In the embodiment of the present specification, the post-stack seismic data is subjected to fracture feature enhancement processing, and the fault ant volume attribute volume is extracted using the ant tracking algorithm. Specifically, a large number of electronic ants are spread in the three-dimensional seismic data volume, and fracture conditions are set. The fracture traces in the seismic data are tracked and interpreted according to the preset fracture conditions. The fracture data obtained by the electronic ants tracking are integrated into the seismic attribute volume data, so as to link the seismic attribute information with the location of the fracture.

[0077] In the embodiments of this specification, a seismic three-dimensional curvature attribute body can be calculated based on the post-stack seismic data body. The seismic three-dimensional curvature attribute reflects the curvature of the underground geological body in three-dimensional space. By measuring the curvature change of the seismic reflection interface, the deformation characteristics of the underground rock layer, such as folds, faults and cracks, can be revealed. In this specification, the seismic data body is divided into three-dimensional grids, and the curvature value is calculated at each grid point to calculate the curvature attribute of the seismic reflection interface.

[0078] In the embodiments of this specification, the seismic coherence attribute body is extracted by measuring the similarity of seismic attributes between adjacent seismic traces. Seismic coherence attributes are a technique for reflecting the continuity or fracture characteristics of underground geological bodies. Areas with high coherence attributes indicate good continuity of geological bodies, while areas with low coherence attributes may indicate fractures, cracks or lithological changes. Specifically, the coherence attributes between adjacent seismic traces are calculated using a coherence algorithm.

[0079] In the embodiments of the present specification, a suitable statistical model is established according to the characteristics of the seismic data, and the seismic data is processed using the principle of maximum likelihood method to obtain a maximum likelihood volume attribute volume.

[0080] In summary, seismic 3D curvature, coherence, maximum likelihood volume and ant volume attribute extraction can all reflect different characteristics and information of underground geological bodies. However, the recognition effects of different seismic attributes may be different, so it is necessary to select seismic attributes with good recognition effects for calculation, overcome the subjectivity in fracture interpretation, and realize automatic fracture recognition.

[0081] Step 203, using the drilling information in the actual drilling process, calibrate the fracture seismic attributes of the study area, and select the fracture seismic attributes with a degree of fit greater than a preset threshold as the fracture seismic phase.

[0082] In the examples of this specification, in some embodiments, the drilling information includes leaks, kicks, and full hydrocarbon display. In the process of extracting the seismic attribute body in step 202, it is not clear whether leaks, kicks, or other situations occur during the drilling process. Therefore, it is necessary to use the leaks, kicks, and full hydrocarbon display during the drilling process of the sample well to calibrate the three-dimensional curvature, coherence, maximum likelihood body, and ant body attributes in step 302, and select the seismic attributes with a degree of fit greater than a preset threshold as the fracture seismic phase. The fracture seismic phase selected in this way has a high degree of fit with the drilling process and accurately reflects the characteristics of fracture development in the underground geological body.

[0083] In this manual, in addition to drilling information such as lost circulation and well kick, well logging, vertical seismic profiles and other data can also be used to calibrate and calibrate the denoised post-stack seismic data to ensure the consistency of the seismic reflection layer and the geological layer.

[0084] Step 204, establishing an initial fracture seismic phase model corresponding to the study area according to the seismic interpretation horizon of the post-stack seismic data, the fault interpretation information and the fracture seismic phase.

[0085] In this step, the corresponding seismic interpretation horizon and fault interpretation information are determined based on the post-stack seismic data. Based on the seismic interpretation horizon, fault interpretation information and grid model, the fracture seismic phase is sampled into the grid model to establish the initial fracture seismic phase model corresponding to the study area. For a detailed description of establishing the initial fracture seismic phase model, see Figure 3 .

[0086] Figure 3 The flowchart of a method for constructing an initial model of fracture seismic phases in an embodiment of this specification is shown, which specifically includes the following steps:

[0087] Step 301, performing structural interpretation on the post-stack seismic data to determine seismic interpretation horizons and fault interpretation information.

[0088] In this step, different structural layers are divided according to the wave field characteristics of the seismic profile in the preprocessed post-stack seismic data. The geological properties of each reflection layer are identified and interpreted, including the thickness, lithology, contact relationship, etc. of the stratum, so as to determine the seismic interpretation horizon. Furthermore, faults are identified on the seismic profile, and judgments are made based on the dislocation, bifurcation, merging, and distortion of the reflection wave event axis. Special waves (such as section waves and diffraction waves) and breakpoint control are used to determine the position and shape of the fault plane, thereby determining the fault interpretation information.

[0089] Step 302: Use the seismic interpretation horizon and the fault interpretation information to establish a grid model, and input the fracture seismic phase into the grid model to obtain an initial fracture seismic phase model.

[0090] In this specification, an initial model of the fracture seismic phase corresponding to the study area is established based on the seismic interpretation horizon and fault interpretation information and using a grid model.

[0091] Among them, in the vertical direction of the grid model, it is necessary to consider the fracture seismic phase of the study area, sample the fracture seismic phase into the grid model, optimize the vertical resolution of the grid model, and thus obtain the initial model of the fracture seismic phase.

[0092] Specifically, during the process of acquiring post-stack seismic data for seismic exploration, seismic CDP bins are determined;

[0093] The length of the vertical grid in the grid model is determined according to the seismic CDP bin.

[0094] Among them, the seismic CDP bin is a basic unit divided for data acquisition and processing during seismic data acquisition and processing. The size and shape of the CDP bin is determined according to the needs of exploration and geological conditions. The CDP spacing (i.e., the size of the bin) affects the resolution and imaging quality of seismic data. In order to ensure that the initial model of the fracture seismic phase of the subsequent structure matches the seismic resolution, it is necessary to control the plane grid of the grid model to be consistent with the seismic CDP bin, thereby ensuring that the vertical grid of the grid model is consistent with the seismic sampling rate.

[0095] Figure 4 The flowchart of a method for constructing a fracture seismic phase model constrained by fracture density is shown in an embodiment of this specification, which specifically includes the following steps:

[0096] Step 401, normalize the fracture density data of the sample well to obtain the fracture density of the known sample well. In this step, the sample well imaging logging or multipole acoustic logging data is used to perform a statistical analysis of the fracture density of the sample well to obtain the fracture density data of the sample well. Among them, it can be collected that the fracture development density of the fracture development section in the sample well is different, or that some well sections have no fracture development. Therefore, the fracture density data of the sample well after normalization is called the fracture density of the known sample well, indicating that the points on the sample well where the fracture density data is collected are known, but the points where there is no fracture density data or the fracture density data cannot be collected can be understood as unknown points. The points where there is no fracture density data or the fracture density data cannot be collected can be simulated or estimated based on the grid with fracture density data near the point, so that in the subsequent steps, the fracture density data of each point needs to be sampled into the initial model of the fracture seismic phase constructed as described above.

[0097] Therefore, in this step, the points corresponding to the known sample well fracture density can be called adjacent points, and the unknown points can be called estimated points.

[0098] Step 402: simulate the fracture density of the point to be estimated according to the initial fracture seismic phase model and the known fracture density of the sample well.

[0099] This step uses the initial fracture seismic phase model corresponding to the sample well as the known model, and performs sequential Gaussian random cokriging simulation on the normalized fracture density of the known sample well. Specifically, based on the known model and the fracture density data of the adjacent points, the fracture density of the point to be estimated is simulated, so that the fracture density of the adjacent points and the point to be estimated can be determined, and the construction of the fracture seismic phase model constrained by the fracture density can be further realized. For a detailed description, see Figure 5 .

[0100] Step 403, based on the longitudinal resolution of the sample well and the resolution of the initial model of the fracture seismic phase, the fracture density of the known sample well and the fracture density of the point to be estimated are sampled into the initial model of the fracture seismic phase to obtain a fracture seismic phase model constrained by the fracture density. In this step, the vertical resolution of the well trajectory of the sample well can be determined according to the sampling rate of the fracture density interpretation data in the longitudinal direction of the wellbore. The resolution of the initial model of the fracture seismic phase can be adjusted according to the longitudinal resolution of the sample well, and then the fracture density of each point is sampled into the initial model of the fracture seismic phase.

[0101] Figure 5 The flowchart of a method for simulating the crack density of a point to be estimated according to an embodiment of the present specification is shown, which specifically includes the following steps:

[0102] Step 501, determine the weight of the to-be-simulated fracture density at the first adjacent point according to the covariance between the to-be-simulated fracture density at the first adjacent point and the second adjacent point, the covariance between the to-be-simulated fracture density and the fracture density of the known sample wells at the first adjacent point and the to-be-estimated point, and the covariance between the to-be-estimated point and the second adjacent point.

[0103] Specifically, the weight of the fracture density to be simulated at the first adjacent point is determined according to the following formula:

[0104]

[0105] Among them, N represents the total number of adjacent points, α represents the sequence number of the adjacent points, Represents the nearby point x α The weight of Indicates that the variable z2 to be simulated is near the point x α At and near point x β The covariance between Indicates that the variable to be simulated z2 and the known variable z1 are at the adjacent point x α The covariance between the estimated point x0 and the estimated point x0, Indicates that the variable z2 to be simulated is near the point x βThe covariance between the estimated point x0 and the estimated point x0. The estimated point x0 represents a point in the nearby grid that has no fracture density data of a sample well, and the nearby point represents a point in the nearby grid that has fracture density data of a sample well. Specifically, x α is the first neighboring point in this step, x β is the second adjacent point in this step.

[0106] The variable z2 to be simulated is the fracture density to be simulated, and the known variable is the fracture density of the known point in the initial model of the fracture seismic phase.

[0107] Step 502, determining the weight of the known sample well fracture density at the point to be estimated based on the covariance between the known sample well fracture density and the fracture density to be simulated at the first adjacent point and the second adjacent point, the variance of the known sample well fracture density at the point to be estimated, and the covariance between the known sample well fracture density and the fracture density to be simulated at the point to be estimated.

[0108] Specifically, the weight of the fracture density of the known sample well at the point to be estimated is determined according to the following formula:

[0109] in,

[0110] It means that the variable Z2 to be simulated is at the estimated point x0 and the second adjacent point x β The covariance between Indicates that the variables to be simulated Z2 and z1 are at the first adjacent point x α At the second nearest point x β The covariance between Represents the variance of the known variable z1 at the estimated point x0; Represents the covariance between the known variable z1 and the variable to be simulated z2 at the estimated point x0.

[0111] Step 503, determining the cokriging mean of the fracture density to be simulated at the point to be estimated based on the weight of the fracture density to be simulated at the first adjacent point, the weight of the fracture density of the known sample well at the point to be estimated, the variable value of the fracture density to be simulated at the first adjacent point, and the variable value of the fracture density of the known sample well at the point to be estimated.

[0112] Specifically, the co-kriging mean of the fracture density to be simulated at the estimated point is determined according to the following formula:

[0113]

[0114] σ 2 (x0) = Var[Z2(x0) * -Z2(x0)];

[0115] Among them, Z2(x0)* represents the cokriging mean of the variable Z2 to be simulated at the estimated point x0, Z2(x0) represents the variable value of the variable Z2 to be simulated at the estimated point x0; Z2(x α ) indicates that the variable Z2 to be simulated is at the first neighboring point x α The variable value at ; Indicates that the variable Z2 to be simulated is at the first adjacent point x α The weight coefficient at ; Represents the weight of the known variable Z1 at the point to be estimated x0.

[0116] Step 504: simulate the fracture density of the point to be estimated based on the co-kriging mean of the fracture density to be simulated at all the points to be estimated in the initial seismic phase model. The co-kriging mean of the density to be simulated at the point to be estimated in step 503 is the fracture density of the point to be estimated obtained by simulation.

[0117] Figure 6 The flowchart of a method for constructing a crack prediction model according to an embodiment of the present specification is shown, which specifically includes the following steps:

[0118] Step 601 : extracting pressure drop data from the hydraulic fracturing pressure construction curve of the sample well and normalizing the data to obtain pressure drop normalized data.

[0119] In this step, based on the hydraulic fracturing pressure construction curve of the sample well, the well section with sudden pressure drop and the pressure values ​​before and after the sudden pressure drop are extracted. Fig.11 The figure shows the pressure drop diagram of the hydraulic fracturing crack development section of WellA. In the figure, between time 22 and time 30, the oil pressure curve of WellA experiences a pressure drop, so that the data of the well section where the pressure suddenly drops and the pressure values ​​before and after the pressure drop can be collected. After the pressure drop data is collected, the pressure drop data is normalized, and the normalized data can be called pressure drop normalized data.

[0120] Step 602, the point corresponding to the normalized pressure drop data is determined as a known point. In this step, the position of the value of the collected pressure data in the well section is determined as a known point, indicating that the pressure value at a certain position in the well section is known. For other areas of the well section where the pressure is stable and no sudden drop occurs, since there is no pressure sudden drop data, these areas are determined as unknown points.

[0121] Step 603, using the Gaussian random cokriging simulation method to simulate the pressure drop data of the unknown point. Figure 5 The same method is used to simulate the pressure drop data of unknown points in the initial model of the fracture seismic phase, so as to obtain the simulated pressure drop data of the unknown points. Specifically, it includes:

[0122] The weight of the known pressure drop data at the point to be estimated is determined based on the covariance between the known pressure drop data and the pressure drop data to be simulated at the first adjacent point and the second adjacent point, the variance of the known pressure drop data at the point to be estimated, and the covariance between the known pressure drop data and the pressure drop data to be simulated at the point to be estimated.

[0123] According to the weight of the pressure drop data to be simulated at the first adjacent point, the weight of the known pressure drop data at the point to be estimated, the variable value of the pressure drop data to be simulated at the first adjacent point and the variable value of the known pressure drop data at the point to be estimated, the cokriging mean of the pressure drop data to be simulated at the point to be estimated is determined. The cokriging mean of the pressure drop data to be simulated at the point to be estimated is the simulated pressure drop data of the unknown point.

[0124] Step 604: based on the pressure drop data of the unknown points and the known points, the pressure drop data are sampled into the fracture seismic phase model constrained by the fracture density to construct a fracture prediction model. In this step, the pressure drop data of the unknown points and the known points are sampled into the fracture seismic phase model constrained by the fracture density according to the scale ratio of the initial fracture seismic phase model and the scale ratio of the fracture seismic phase model constrained by the fracture density, and the pressure drop data of all points are sampled into the fracture seismic phase model constrained by the fracture density.

[0125] In this specification, the advantage of dynamic fracture identification of sudden drop in hydraulic fracturing pressure is used and combined with fracture density interpretation data in the vertical direction of the wellbore and post-stack seismic data to achieve prediction and evaluation of effective fractures.

[0126] like Figure 7 The figure shows a schematic diagram of a structure of a post-stack fracture prediction model construction device for combining well-seismic with well-seismic in an embodiment of the present specification. In this figure, the basic structure of the post-stack fracture prediction model construction device for combining well-seismic with well-seismic is described. The functional units and modules therein can be implemented in software, or a general chip or a specific chip can be used to implement the construction of the post-stack fracture prediction model for combining well-seismic with well-seismic. The device specifically includes:

[0127] The model building unit 701 is used to construct an initial model of fracture seismic phases in the study area based on post-stack seismic data and drilling information;

[0128] The fracture seismic attribute determination unit 702 is used to obtain fracture density interpretation data of the sample well and determine the fracture seismic attribute of the sample well;

[0129] A fracture seismic phase model determination unit 703 is used to sample fracture seismic attributes into the initial seismic phase model to obtain a fracture seismic phase model constrained by fracture density;

[0130] The fracture prediction model determination unit 704 is used to obtain the hydraulic fracturing pressure drop data of the sample well, sample the hydraulic fracturing pressure drop data into the fracture seismic phase model constrained by the fracture density, and obtain the fracture prediction model.

[0131] This scheme takes advantage of the high accuracy and reliability of imaging logging and multipole acoustic logging data in interpreting fracture density in the vertical direction of the wellbore, and the advantages of post-stack 3D seismic data in fracture prediction and dynamic identification of fractures with sudden pressure drop of hydraulic fracturing, and effectively combines the advantages of logging, seismic and hydraulic fracturing to carry out fracture prediction by combining well logging and seismic. This method can improve the accuracy and reliability of fracture prediction and realize the prediction and evaluation of effective fractures.

[0132] Figure 8 This is a fracture prediction diagram of a post-stack ant body in an embodiment of this specification. The figure shows the fractures of WellA, WellB and WellC predicted after extracting ant body attributes from post-stack seismic data.

[0133] Fig. 9 This is a WellB single well imaging logging fracture density interpretation diagram for the embodiment of this specification. The left half of the figure is a schematic diagram of the fracture accumulation of WellB, and the right half of the figure is a schematic diagram of the fracture density of WellB. It can be seen from the left half of the figure that the fractures appear at a depth of 3,500 meters in the well section and are concentrated at an inclination of about 90°.

[0134] Fig.10 This is an example of a seismic fracture prediction plane map constrained by imaging logging fracture density. After sampling the fracture seismic attributes into the initial seismic phase model, we get Fig.10 The earthquake crack prediction results are shown.

[0135] Fig.11 This is a pressure drop diagram of the hydraulic fracture development section of WellA well in the embodiment of this specification. In the figure, between time 22 and time 30, the oil pressure curve of WellA well has a sudden pressure drop, so that the data of the well section with sudden pressure drop and the pressure values ​​before and after the sudden pressure drop can be collected.

[0136] Fig. 12A This is a high-precision fracture prediction plane map of static fracture density of imaging logging and dynamic pressure drop constraint of hydraulic fracturing according to the embodiment of this specification; Fig. 12B This is a high-precision fracture prediction profile diagram based on static fracture density of imaging logging and sudden pressure drop constraints of hydraulic fracturing according to an embodiment of the present specification.

[0137] like Fig.13As shown, a computer device provided by an embodiment of this specification. The post-stack fracture prediction model construction method of the well-seismic combination described in this application can be applied to the computer device. The computer device 1302 may include one or more processors 1304, such as one or more central processing units (CPUs), and each processing unit may implement one or more hardware threads. The computer device 1302 may also include any memory 1306, which is used to store any kind of information such as code, settings, data, etc. Non-limiting, for example, the memory 1306 may include any one or more combinations of the following: any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc. More generally, any memory can use any technology to store information. Further, any memory can provide volatile or non-volatile retention of information. Further, any memory can represent a fixed or removable component of the computer device 1302. In one case, when the processor 1304 executes an associated instruction stored in any memory or a combination of memories, the computer device 1302 can perform any operation of the associated instruction. The computer device 1302 also includes one or more drive mechanisms 1308 for interacting with any storage, such as a hard disk drive mechanism, an optical disk drive mechanism, etc.

[0138] The computer device 1302 may also include an input / output module 1310 (I / O) for receiving various inputs (via input devices 1312) and for providing various outputs (via output devices 1314). A specific output mechanism may include a presentation device 1316 and an associated graphical user interface (GUI) 1318. In other embodiments, the input / output module 1310 (I / O), input device 1312, and output device 1314 may not be included, and the computer device 1302 may be used as a computer device in a network. The computer device 1302 may also include one or more network interfaces 1320 for exchanging data with other devices via one or more communication links 1322. One or more communication buses 1324 couple the components described above together.

[0139] The communication link 1322 may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 1322 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

[0140] Corresponds to Figures 1 to 6 The method in the embodiment of the present specification also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are executed.

[0141] The embodiment of the present specification also provides a computer-readable instruction, wherein when the processor executes the instruction, the program therein causes the processor to execute the following Figures 1 to 6 The method shown.

[0142] It should be understood that in the various embodiments of this specification, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this specification.

[0143] It should also be understood that in the embodiments of this specification, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this specification generally indicates that the associated objects before and after are in an "or" relationship.

[0144] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this specification can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this specification.

[0145] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0146] In the several embodiments provided in this specification, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0147] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of this specification.

[0148] In addition, each functional unit in each embodiment of this specification may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0149] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this specification is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of this specification. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0150] Specific embodiments are used in this specification to illustrate the principles and implementation methods of this specification. The description of the above embodiments is only used to help understand the methods and core ideas of this specification. At the same time, for those skilled in the art, according to the ideas of this specification, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on this specification.

Claims

1. A method for constructing a post-stack fracture prediction model combining wellbore and seismic data, characterized in that: The method comprises: Based on post-stack seismic data and drilling information, an initial model of fracture seismic phases in the study area was constructed; Obtain fracture density interpretation data of sample wells and determine fracture seismic attributes of sample wells; Sampling the fracture seismic attributes into the initial seismic phase model to obtain a fracture seismic phase model constrained by fracture density; The hydraulic fracturing pressure drop data of the sample wells are obtained, and the hydraulic fracturing pressure drop data are sampled into the fracture seismic phase model constrained by fracture density to obtain a fracture prediction model.

2. The method according to claim 1, characterized in that The drilling information includes at least one of lost circulation, kick or full hydrocarbon display.

3. The method according to claim 2, characterized in that Based on post-stack seismic data and drilling information, the initial model of fracture seismic phases in the structural study area includes: Acquire denoised post-stack seismic data; Extracting seismic three-dimensional curvature, coherence, maximum likelihood volume and ant volume attributes from the post-stack seismic data; The drilling information in the actual drilling process is used to calibrate the fracture seismic attributes in the study area, and the fracture seismic attributes with a degree of fit greater than a preset threshold are selected as fracture seismic phases; According to the seismic interpretation horizons of the post-stack seismic data, the fault interpretation information and the fracture seismic phase, an initial fracture seismic phase model corresponding to the study area is established.

4. The method according to claim 3, characterized in that According to the seismic interpretation horizon of the post-stack seismic data, the fault interpretation information and the fracture seismic phase, an initial fracture seismic phase model corresponding to the study area is established, including: Performing structural interpretation on the post-stack seismic data to determine seismic interpretation horizons and fault interpretation information; A grid model is established using the seismic interpretation horizon and the fault interpretation information, and the fracture seismic phase is input into the grid model to obtain an initial fracture seismic phase model.

5. The method according to claim 4, characterized in that Sampling the fracture seismic attributes into the initial seismic phase model to obtain a fracture seismic phase model constrained by fracture density includes: Normalizing the fracture density data of the sample well to obtain the fracture density of the known sample well; Simulating the fracture density of the point to be estimated according to the fracture seismic phase initial model and the known fracture density of the sample well; According to the vertical resolution of the sample well and the resolution of the initial model of the fracture seismic phase, the fracture density of the known sample well and the fracture density of the point to be estimated are sampled into the initial model of the fracture seismic phase to obtain a fracture seismic phase model constrained by the fracture density.

6. The method according to claim 5, characterized in that Determining the fracture density of the to-be-estimated point as the fracture density to be simulated, and simulating the fracture density of the to-be-estimated point according to the fracture seismic phase initial model and the known fracture density of the sample well includes: Determine the weight of the fracture density to be simulated at the first adjacent point according to the covariance between the fracture density to be simulated at the first adjacent point and the second adjacent point, the covariance between the fracture density to be simulated and the fracture density of the known sample well at the first adjacent point and the point to be estimated, and the covariance between the fracture density to be simulated at the point to be estimated and the second adjacent point; Determine the weight of the known sample well fracture density at the point to be estimated based on the covariance between the known sample well fracture density and the fracture density to be simulated at the first adjacent point and the second adjacent point, the variance of the known sample well fracture density at the point to be estimated, and the covariance between the known sample well fracture density and the fracture density to be simulated at the point to be estimated; Determine the cokriging mean of the fracture density to be simulated at the point to be estimated according to the weight of the fracture density to be simulated at the first adjacent point, the weight of the fracture density of the known sample well at the point to be estimated, the variable value of the fracture density to be simulated at the first adjacent point and the variable value of the fracture density of the known sample well at the point to be estimated; According to the co-kriging mean of the fracture density to be simulated at all the points to be estimated in the initial seismic phase model, the fracture density of the point to be estimated is simulated.

7. The method according to claim 1, characterized in that Obtaining hydraulic fracturing pressure drop data of sample wells and sampling the hydraulic fracturing pressure drop data into a fracture seismic phase model constrained by fracture density includes: Extract the pressure drop data from the hydraulic fracturing pressure construction curve of the sample well and normalize it to obtain the pressure drop normalized data; Determine the point corresponding to the normalized data of the pressure drop as a known point; Use Gaussian random cokriging simulation method to simulate the pressure drop data of unknown points; According to the pressure drop data of unknown points and known points, the fracture seismic phase model constrained by fracture density is sampled and the fracture prediction model is constructed.

8. A post-stack fracture prediction model construction device combining well-seismic and post-stack fracture prediction, characterized in that: The device comprises: The model building unit is used to construct an initial model of fracture seismic phases in the study area based on post-stack seismic data and drilling information; A fracture seismic attribute determination unit, used to obtain fracture density interpretation data of a sample well and determine the fracture seismic attributes of the sample well; A fracture seismic phase model determination unit, used for sampling fracture seismic attributes into the initial seismic phase model to obtain a fracture seismic phase model constrained by fracture density; The fracture prediction model determination unit is used to obtain the hydraulic fracturing pressure drop data of the sample well, sample the hydraulic fracturing pressure drop data into the fracture seismic phase model constrained by the fracture density, and obtain the fracture prediction model.

9. 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, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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