CN114764146A - Fracture prediction method and system based on stratum revolution structure tensor - Google Patents

Fracture prediction method and system based on stratum revolution structure tensor Download PDF

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CN114764146A
CN114764146A CN202110030654.9A CN202110030654A CN114764146A CN 114764146 A CN114764146 A CN 114764146A CN 202110030654 A CN202110030654 A CN 202110030654A CN 114764146 A CN114764146 A CN 114764146A
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target area
fracture
target region
structure information
coordinate system
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路保平
袁多
侯绪田
吴超
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China Petroleum and Chemical Corp
Sinopec Research Institute of Petroleum Engineering
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Sinopec Research Institute of Petroleum Engineering
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    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
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    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
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    • G01V1/301—Analysis for determining seismic cross-sections or geostructures
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    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
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Abstract

The invention discloses a fracture prediction method and a system based on a stratum revolution structure tensor, which comprise the following steps: acquiring a seismic profile of a target area; according to the seismic profile, establishing target area structure information matched with the actual stratum condition of a target area; preprocessing the structural information of the target area; and acquiring the preprocessed target area structure information, and performing crack prediction on the target area based on the preprocessed target area structure information to obtain crack possibility index characteristics aiming at the target area. The method can reliably predict the space spread quantitative characteristic information of the cracks from the seismic profile, provides a basis for predicting the oil-gas reservoir and preventing drilling engineering accidents, and meets the requirements of modern oil-gas exploration.

Description

Fracture prediction method and system based on stratum revolution structure tensor
Technical Field
The invention relates to the field of petroleum exploration and development, in particular to a fracture prediction method and system based on a stratum revolution structure tensor.
Background
The underground fracture has important significance for oil and gas resources. Microfractures in reservoir rock are reservoir spaces for oil and gas resources; the cracks with relatively large scale are also migration channels for oil and gas resources to migrate from the oil-producing rock to the reservoir, such as faults and the like. Therefore, in the exploration of oil and gas resources, the fracture prediction becomes an important link of reservoir prediction. Meanwhile, the exploitation of oil and gas resources needs to depend on well drilling technology. The drilling process is drilling into the target reservoir along a planned well trajectory, where fractures may be encountered. However, the fractures may cause well-drilling engineering accidents such as collapse of the well bore, sticking, burying and loss of drilling fluid during the drilling process, which generally results in increased drilling cycle and economic loss. Thus, prediction techniques for subsurface fractures are particularly important.
The fractures of interest in oil and gas exploration and development are typically buried deep in the ground to a depth of several kilometers, and therefore their spatial location cannot be directly ascertained. The crack prediction by means of the seismic exploration method is a path with high feasibility at present. Crack prediction actually identifies cracks in the seismic image.
In addition, the structure tensor method is a widely used method in image processing, and can acquire structural information of an image. In the process of implementing the method, the inventor finds that the traditional structure tensor method is based on a rectangular coordinate system, has low adaptability to the actual stratum, cannot obtain a high-quality fracture prediction result, and cannot solve the problem of aiming at the actual stratum condition.
Therefore, there is a need in the art to provide a fracture prediction scheme that can be adapted to the actual formation conditions.
Disclosure of Invention
In order to solve the technical problem, the invention provides a fracture prediction method based on a stratum revolution structure tensor, which comprises the following steps: a seismic section input step, namely acquiring a seismic section of a target area; the method comprises the steps of generating structural information, namely establishing target area structural information matched with the actual stratum condition of a target area according to a seismic section; preprocessing, namely preprocessing the structural information of the target area; and a crack prediction step of acquiring the preprocessed target region structure information, and performing crack prediction on the target region based on the target region structure information to obtain crack possibility index characteristics aiming at the target region.
Preferably, in the structure information generating step, the method further includes: according to the seismic profile, determining the difference value between the actual stratigraphic dip angle of the target area and the stratigraphic dip angle under the rectangular coordinate system and the difference value of the stratigraphic azimuth angle; converting the rectangular coordinate system into a corresponding stratum coordinate system according to the stratum inclination angle difference value and the azimuth angle difference value; and constructing the structural information of the target area based on the stratum coordinate system and according to the seismic data corresponding to the target area.
Preferably, in the crack prediction step, the method comprises: carrying out characteristic value decomposition processing on the preprocessed target area structure information; and calculating a fracture indicator factor for characterizing the probability of developing the fracture according to the decomposed characteristic values to obtain the fracture probability index characteristic.
Preferably, in the step of preprocessing, the method comprises: and calibrating the rotation direction of each element of the structural information of the target area, and based on the rotation direction, filtering unstable information of each point to be predicted in the seismic section of the target area by utilizing an anisotropic Gaussian function in combination with the position information of each point to be predicted in the target area.
Preferably, the formation coordinate system and the target area structure information are respectively constructed by using the following expressions:
Figure BDA0002891774550000021
Figure BDA0002891774550000022
Figure BDA0002891774550000023
Figure BDA0002891774550000024
Figure BDA0002891774550000025
wherein θ represents the formation dip angle difference,
Figure BDA0002891774550000026
expressing the difference value of the azimuth angles, expressing the position coordinates of each point in a rectangular coordinate system by x, y and z, expressing the position coordinates of each point in a stratum coordinate system by x ', y ' and z ', and SrRepresenting the target area structure information, u representing the seismic data.
Preferably, the fracture indicator is calculated using the expression:
Figure BDA0002891774550000027
wherein ε represents an error constant, f represents the fracture indicator factor, λ1、λ2And respectively representing a plurality of characteristic values obtained by performing characteristic decomposition on the preprocessed target region structure information.
Preferably, the target area structure information is preprocessed using the following expression:
Figure BDA0002891774550000031
Figure BDA0002891774550000032
Figure BDA0002891774550000033
Figure BDA0002891774550000034
dx＝x-x0
dy＝y-y0
dz＝z-z0
wherein, gsRepresenting elements in the preprocessed target area structure information, x, y and z representing position coordinates of each point in a rectangular coordinate system, x ', y ' and z ' representing position coordinates of each point in a stratum coordinate system, giValue, x, representing element i in element-scaled target region structure information0、y0、z0Respectively representing the corresponding position coordinates, sigma, of the points to be predicted in the target regionx'、σy'、σz'Respectively representing the standard deviations of the points to be predicted along the directions of x ', y ' and z ', xwin、ywin、zwinRespectively representing the corresponding preprocessing window radius of the point to be predicted along the x, y and z directions.
In another aspect, the present invention further provides a fracture prediction system based on a formation rotation structure tensor, including: a seismic profile input module configured to obtain a seismic profile of a target area; the structure information generation module is configured to establish target area structure information matched with the actual stratum condition of the target area according to the seismic section; a preprocessing module configured to preprocess the target region structure information; and the crack prediction module is configured to acquire the preprocessed target region structure information, and based on the preprocessed target region structure information, perform crack prediction on the target region to obtain crack possibility index characteristics for the target region.
Preferably, the structure information generating module includes: a rotation difference generating unit configured to determine a difference between an actual stratigraphic inclination of a target region and a stratigraphic inclination in a rectangular coordinate system and a difference between stratigraphic azimuths according to the seismic profile; a formation coordinate system generation unit configured to convert the rectangular coordinate system into a corresponding formation coordinate system according to the formation inclination angle difference and the azimuth angle difference; and the area structure information generating unit is configured to construct the target area structure information according to the seismic data corresponding to the target area based on the stratum coordinate system.
Preferably, the fracture prediction module comprises: a decomposition processing unit configured to perform characteristic value decomposition processing on the preprocessed target region structure information; a prediction result generation unit configured to calculate a fracture indicator characterizing the probability of developing a fracture in the target region according to the decomposed plurality of feature values to obtain the fracture probability index feature.
Compared with the prior art, one or more embodiments in the above scheme can have the following advantages or beneficial effects:
the invention discloses a fracture prediction method and system based on a stratum revolution structure tensor. The method and the system firstly utilize the stratum structure information of a target area to construct a stratum rotation structure tensor; then, utilizing a rotational anisotropy Gaussian function to preprocess a stratum rotational structure tensor so as to improve the stability of the stratum rotational structure tensor; and finally, performing eigenvalue decomposition on the preprocessed stratum revolution structure tensor matrix, and constructing a fracture indication factor by using a plurality of decomposed eigenvalues, thereby realizing a fracture prediction quantification result of the target region. The seismic fracture prediction method based on the structure tensor after the formation rotation processing can reliably predict the space distribution quantitative characteristic information of the fracture from the seismic section, provides a basis for prediction and prevention of drilling engineering accidents of an oil-gas reservoir, meets the requirement of modern oil-gas exploration, and has an important effect on oil-gas exploration and development, so that the problem that the conventional means for extracting image structure information is not matched with the actual structural characteristics of the stratum when the conventional means is applied to the seismic section is solved, and the change of the underground horizon can be adapted.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a diagram illustrating steps of a method for predicting a fracture based on a formation rotation structure tensor according to an embodiment of the present application.
Fig. 2 is a specific example of a seismic profile for a target area in a fracture prediction method based on a formation rotation structure tensor according to an embodiment of the present application.
Fig. 3 is a schematic flow chart of a target structure information generation process in the formation rotation structure tensor-based fracture prediction method according to the embodiment of the application.
Fig. 4 is a specific example of a fracture prediction result deployment map for a target region in the fracture prediction method based on the formation rotation structure tensor according to the embodiment of the present application.
FIG. 5 is a block diagram of a fracture prediction system based on the formation rotation structure tensor according to an embodiment of the present application.
Detailed Description
The following detailed description will be given with reference to the accompanying drawings and examples to explain how to apply the technical means to solve the technical problems and to achieve the technical effects. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
Additionally, the steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions. Also, while a logical order is shown in the flow diagrams, in some cases, the steps shown or described may be performed in an order different than here.
The underground fracture has important significance on oil and gas resources. Microfractures in reservoir rock are reservoir spaces for oil and gas resources; the cracks with relatively large scale are also migration channels for oil and gas resources to migrate from the oil-producing rock to the reservoir, such as faults and the like. Therefore, in the exploration of oil and gas resources, the fracture prediction becomes an important link of reservoir prediction. Meanwhile, the exploitation of oil and gas resources needs to depend on well drilling technology. The drilling process is drilling into the target reservoir along a planned well trajectory, where fractures may be encountered. However, the fractures may cause well-drilling engineering accidents such as well bore collapse, drill sticking, drill burying and drilling fluid loss during the well drilling process, and the accidents usually result in increased well drilling period and increased economic loss. Thus, prediction techniques for subsurface fractures are particularly important.
The fractures of interest in oil and gas exploration and development are typically buried deep in the ground to a depth of several kilometers, and therefore their spatial location cannot be directly ascertained. The method for predicting the cracks by means of the seismic exploration method is a path with high feasibility at present. Crack prediction actually identifies cracks in seismic images.
In addition, the structure tensor method is a widely used method in image processing, and can acquire structural information of an image. In the process of implementing the method, the inventor finds that the traditional structure tensor method is based on a rectangular coordinate system, has low adaptability to the actual stratum, cannot obtain a high-quality fracture prediction result, and cannot solve the problem of aiming at the actual stratum condition.
Therefore, in order to solve the above technical problem, an embodiment of the present invention provides a fracture prediction method and system based on a formation rotation structure tensor. Firstly, constructing a stratum structure tensor matched with the actual stratum structure condition of a target area based on a seismic profile of the target area; preprocessing a stratum structure tensor of a target area by utilizing a rotational anisotropy Gaussian function; and predicting the crack development possibility of the target area according to the preprocessed tensors of the stratum structures of the target area, so that the crack information of different target positions can be predicted quantitatively from the seismic section.
Fig. 1 is a diagram illustrating steps of a method for predicting a fracture based on a formation rotation structure tensor according to an embodiment of the present application. The crack prediction method according to the embodiment of the present invention will be described with reference to fig. 1.
First, in step S110, a seismic profile for a target area is acquired. Fig. 2 is a specific example of a seismic profile for a target area in a fracture prediction method based on a formation rotation structure tensor according to an embodiment of the present application. FIG. 2 illustrates a partial seismic profile of a certain reservoir region. It should be noted that, in the embodiment of the present invention, the target region refers to a three-dimensional region where crack prediction is currently required. Preferably, the three-dimensional target region has similar stratigraphic structural characteristics and can be represented by the same stratigraphic dip angle and the same stratigraphic azimuth angle.
After the seismic profile of the target area is obtained, the process proceeds to step S120. Step S120 is to establish structural information matched with the actual stratum characteristic condition of the target area, namely the structural information of the target area according to the seismic section. In this embodiment of the present invention, the target region structure information is preferably an image structure tensor of the current target region.
Fig. 3 is a schematic flow chart of a target structure information generation process in the formation rotation structure tensor-based fracture prediction method according to the embodiment of the application. The implementation of step S120 will be described with reference to fig. 1 and 3.
In an actual application process, in order to deal with the problem that the conventional structure tensor method is based on a rectangular coordinate system, and cannot solve the fracture prediction problem for the actual formation condition, however, the actual formation structure does not conform to the rectangular coordinate system, and therefore, in order to consider the influence of the actual formation structure factor, the embodiment of the invention needs to construct the structure tensor information which conforms to the actual formation rotation characteristic condition in step S120.
As shown in fig. 3, step S1201 determines a difference between the actual stratigraphic inclination of the target region and the stratigraphic inclination in the rectangular coordinate system (stratigraphic inclination difference) and a difference between the actual stratigraphic azimuth of the target region and the stratigraphic azimuth in the rectangular coordinate system (azimuth difference), respectively, according to the seismic profile about the target region obtained in step S110, and then the process proceeds to step S1202.
Step S1202 converts the rectangular coordinate system into a corresponding formation coordinate system according to the formation dip angle difference and the formation azimuth angle difference obtained in step S1201. In this way, the coordinate conversion operation from the rectangular coordinate system to the formation coordinate system conforming to the actual formation structure characteristic is completed, and the process proceeds to step S1203. In step S1202, the conversion of the rectangular coordinate system into the formation coordinate system is realized using the following expression:
Figure BDA0002891774550000061
where theta represents the formation dip angle difference,
Figure BDA0002891774550000062
the azimuth difference of the stratum is represented, x, y and z represent position coordinates of each point in a rectangular coordinate system, and x ', y ' and z ' represent position coordinates of each point in a stratum coordinate system.
Step S1203 constructs target area structure information based on the formation coordinate system constructed in step S1202 and according to the seismic data corresponding to the target area. And the target area structure information is a stratum structure tensor obtained after coordinate rotation processing is finished aiming at the target area. In step S1203, a structure-stratum-structure tensor matrix of the target area is constructed in the stratum coordinate system by using the following expression:
Figure BDA0002891774550000063
Figure BDA0002891774550000064
Figure BDA0002891774550000071
Figure BDA0002891774550000072
wherein S isrRepresenting target zone structural information and u representing seismic data corresponding to the target zone (obtained directly from the seismic profile based on the position of the target zone).
The elements in the structure tensor matrix obtained in the conventional structure tensor algorithm are gradient data in a rectangular coordinate system:
Figure BDA0002891774550000073
directly constructed, without consideration of the influencing factors of the actual stratigraphic structural characteristics. In the embodiment of the invention, in the stratum rotation structure tensor matrix, each element is formed by gradient data after coordinate rotation is considered
Figure BDA0002891774550000074
The actual structural feature information of the stratum is considered for construction. In this way, in the embodiment of the present invention, the stratum structure tensor matrix corresponding to the actual stratum structure feature of the target area is obtained through the steps S1201 to S1203.
With continued reference to fig. 1, after the construction of the target area structure information is completed, the process proceeds to step S130. Step S130 preprocesses the target region structure information (the tensor matrix of the stratigraphic structure with respect to the target region) constructed in step S120.
In the practical application process, abnormal factors such as noise generally exist in data read from the seismic profile, and the spatial stability of each element in the structure tensor matrix after the stratum rotates is influenced. Therefore, in order to improve the stability and further consider the formation structure characteristic factors, the embodiment of the present invention needs to perform a preprocessing operation based on the rotational anisotropy gaussian function on each element in the formation rotation structure tensor matrix in step S130.
As shown in fig. 1, in step S130, the rotation direction of each element of the target area structure information is calibrated, and based on this, the unstable information of each point to be predicted in the seismic section of the target area is filtered out by using an anisotropic gaussian function. Since there are points to be predicted (points for which the crack probability state needs to be predicted) distributed at different positions in the target region, the embodiment of the present invention performs step S130 for each point to be predicted, so as to filter out unstable information of all the points to be predicted in the target region. It should be noted that, since the unstable information filtering method of each point to be predicted is the same, in the embodiment of the present invention, only one point filtering method is taken as an example for description. Specifically, step S130 firstly performs rotation direction calibration on each element in the target area structure information according to the target area structure information obtained in step S120.
Specifically, each element in the stratum structure tensor matrix after coordinate rotation about the target area is calibrated according to the following mode: g1＝gx'gx'，g2＝gy'gy'，g3＝gz'gz'，g4＝gx'gy'，g5＝gx'gz'，g6＝gy'gz'。
Then, step S130 may also perform preprocessing on the structural information of the target area (filtering the seismic section noise of the current point to be predicted) by using an anisotropic gaussian function according to the structural information of the target area where element calibration is completed and combining with the position information of the current point to be predicted in the target area, so as to filter the unstable information of each element in the matrix (to filter the unstable information of the current point to be predicted). Specifically, the target area structure information preprocessing operation is performed according to the following expression:
Figure BDA0002891774550000081
Figure BDA0002891774550000082
Figure BDA0002891774550000083
Figure BDA0002891774550000084
dx＝x-x0 (10)
dy＝y-y0 (11)
dz＝z-z0 (12)
wherein, gsRepresenting elements within the preprocessed target region structure information, giA value (i ═ 1, 2.. 6), x, representing an element i in the element-labeled target region structure information0、y0、z0Respectively representing the corresponding position coordinates, sigma, of the point to be predicted in the current target areax'、σy'、σz'Representing the standard deviations of the current point to be predicted along the directions of x ', y ' and z ', xwin、ywin、zwinAnd indicating the radius of the preprocessing window corresponding to the current point to be predicted along the x, y and z directions respectively. For example: sigmax'＝5，σy'＝1，σz'＝1，xwin＝10，ywin＝2，zwin＝2。
Therefore, in the embodiment of the present invention, the step S130 completes the task of preprocessing the structure information of the target area for each point to be predicted in the target area, and further obtains a corresponding preprocessing result for each point to be predicted, so that on the basis of considering the actual stratigraphic structure characteristics, the instability factor of each element in the structure information of the target area is filtered, and the spatial stability of the structure information of the target area is improved. Then, the process proceeds to step S140.
Step S140 obtains the preprocessed target region structure information (corresponding to each point to be predicted), and based on this, performs crack prediction on the target region to obtain crack possibility index features for the target region (that is, to obtain corresponding crack possibility index features for each point to be predicted in the target region). In step S140, corresponding preprocessed target area structure information is obtained for each point to be predicted according to the preprocessing result of each element in the target area structure information for each point to be predicted obtained in step S130. The preprocessed target area structure information is represented by the following expression:
Figure BDA0002891774550000091
wherein S isrpRepresenting the preprocessed target region structure information. Then, in step S140, a feature value decomposition process is performed on the preprocessed target area structure information corresponding to each point to be predicted, so as to obtain a plurality of decomposed feature values (corresponding to each point to be predicted). In the eigenvalue decomposition processing process, the preprocessed target region structure information is converted from a matrix form into an eigenvalue expression form, so that the preprocessed target region structure information represented in the eigenvalue expression form is represented by the following expression:
Figure BDA0002891774550000092
wherein λ is1、λ2、λ3Respectively representing a plurality of eigenvalues, v, obtained after the eigenvalue decomposition process1、v2、v3Respectively representing a plurality of eigenvectors obtained after eigenvalue decomposition processing.
Then, after obtaining the plurality of feature values, step S140 further calculates a crack indicator characterizing the possibility of developing cracks in the target region (calculates a crack indicator for each point to be predicted in each target region) according to the decomposed plurality of feature values (corresponding to each point to be predicted), so as to obtain corresponding crack possibility index feature information for each point to be predicted. In step S140, the crack indicator is calculated by using the following expression:
Figure BDA0002891774550000093
where ε represents the error constant and f represents the fracture indicator. First, in expression (15), the error constant is a positive number close to zero, so that the stability of the calculation result is ensured. Secondly, in expression (15), the value of the crack indicator f is between 0 and 1, and is used for characterizing the possibility degree of the crack development of the point domain to be predicted currently in the target region. The smaller the value of the crack indicating factor is, the smaller the possibility of developing cracks at the current point to be predicted is; the larger the value of the crack indicating factor is, the more likely the crack is to develop at the current point to be predicted.
Thus, the embodiment of the present invention utilizes the above steps S110 to S140 to quantitatively express the possibility of crack development in the target region. Furthermore, after the crack prediction method described in the above steps S110 to S140 is continuously performed, the crack prediction result information corresponding to different target area positions can be predicted from the seismic section of the entire work area, see fig. 4, so that the spatial distribution of cracks can be effectively predicted from the seismic section. Therefore, corresponding quantitative data basis is provided for predicting and preventing drilling engineering accidents of the oil and gas reservoir, and the requirements of modern oil and gas exploration and drilling are met.
Fig. 4 is a specific example of a fracture prediction result deployment map for a target region in the fracture prediction method based on the formation rotation structure tensor according to the embodiment of the present application. Fig. 4 shows a spatial distribution situation after a fracture prediction is performed on a certain oil reservoir region by using the fracture prediction method according to the embodiment of the present invention.
On the other hand, the invention also provides a fracture prediction system based on the stratum revolution structure tensor based on the fracture prediction method. FIG. 5 is a block diagram of a fracture prediction system based on the formation rotation structure tensor according to an embodiment of the present application. As shown in fig. 5, a fracture prediction system based on a formation rotation structure tensor (hereinafter referred to as "fracture prediction system") according to an embodiment of the present invention includes: a seismic profile input module 51, a structural information generation module 52, a preprocessing module 53, and a fracture prediction module 54.
The seismic profile input module 51 is implemented according to the method described in step S110, and is configured to obtain a seismic profile of the target area. The structural information generating module 52 is implemented according to the method described in step S120 above, and is configured to establish target area structural information matching the actual stratigraphic conditions of the target area based on the seismic profile. The preprocessing module 53 is implemented according to the method described in the above step S130, and is configured to perform preprocessing on the above target area structure information. The crack prediction module 54 is implemented according to the method described in the step S140, and is configured to obtain the preprocessed target region structure information, and based on this, perform crack prediction on the target region to obtain crack possibility index features for the target region.
Further, the structural information generating module 52 includes: a rotation difference value generating unit 521, a formation coordinate system generating unit 522, and a region structure information generating unit 523. Specifically, the rotation difference generation unit 521 is configured to determine a difference between an actual stratigraphic inclination of the target region and a stratigraphic inclination in the rectangular coordinate system and a difference between stratigraphic azimuths according to the seismic profile of the target region; the formation coordinate system generating unit 522 is configured to convert the rectangular coordinate system into a corresponding formation coordinate system according to the formation inclination angle difference and the azimuth angle difference; the area structure information generating unit 523 is configured to construct target area structure information from the seismic data corresponding to the target area based on the stratigraphic coordinate system output by the stratigraphic coordinate system generating unit 522.
Further, the crack prediction module 54 includes: a decomposition processing unit 541 and a prediction result generating unit 542. Specifically, the decomposition processing unit 541 is configured to perform eigenvalue decomposition processing on the preprocessed target region structure information; the prediction result generation unit 542 is configured to calculate a fracture indicator that characterizes the likelihood of developing a fracture in the target region, based on the decomposed plurality of feature values, to obtain the fracture likelihood index feature described above.
The invention discloses a fracture prediction method and a fracture prediction system based on a stratum rotation structure tensor. The method and the system firstly utilize the stratum structure information of a target area to construct a stratum revolution structure tensor; then, utilizing a rotational anisotropy Gaussian function to preprocess a stratum rotational structure tensor so as to improve the stability of the stratum rotational structure tensor; and finally, performing eigenvalue decomposition on the preprocessed formation rotation structure tensor matrix, and constructing a fracture indication factor by using a plurality of decomposed eigenvalues, thereby realizing a fracture prediction quantification result of the target region. The seismic fracture prediction method based on the structure tensor after the formation rotation processing can reliably predict the space distribution quantitative characteristic information of the fracture from the seismic section, provides a basis for prediction and prevention of drilling engineering accidents of an oil-gas reservoir, meets the requirement of modern oil-gas exploration, and has an important effect on oil-gas exploration and development, so that the problem that the conventional means for extracting image structure information is not matched with the actual structural characteristics of the stratum when the conventional means is applied to the seismic section is solved, and the change of the underground horizon can be adapted.
While the invention has been described with reference to specific preferred embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the following claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
It is to be understood that the disclosed embodiments of the invention are not limited to the particular structures, process steps, or materials disclosed herein but are extended to equivalents thereof as would be understood by those ordinarily skilled in the relevant arts. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.
Reference in the specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Thus, the appearances of the phrase "one embodiment" or "an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (10)

1. A fracture prediction method based on a stratum rotation structure tensor comprises the following steps:
a seismic section input step, namely acquiring a seismic section of a target area;
the method comprises the steps of generating structural information, namely establishing target area structural information matched with the actual stratum condition of a target area according to a seismic section;
preprocessing, namely preprocessing the structural information of the target area;
and a crack prediction step of acquiring the preprocessed target region structure information, and performing crack prediction on the target region based on the target region structure information to obtain crack possibility index characteristics aiming at the target region.
2. The crack prediction method according to claim 1, wherein the structural information generation step includes:
according to the seismic profile, determining the difference value between the actual stratigraphic dip angle of the target area and the stratigraphic dip angle under the rectangular coordinate system and the difference value of the stratigraphic azimuth angle;
converting the rectangular coordinate system into a corresponding stratum coordinate system according to the stratum inclination angle difference value and the azimuth angle difference value;
and constructing the structural information of the target area based on the stratum coordinate system and according to the seismic data corresponding to the target area.
3. The fracture prediction method according to claim 1 or 2, characterized by comprising, in the fracture prediction step:
carrying out characteristic value decomposition processing on the preprocessed target area structure information;
and calculating a fracture indicator factor for characterizing the probability of developing the fracture according to the decomposed characteristic values to obtain the fracture probability index characteristic.
4. The fracture prediction method according to claim 3, comprising, in the preprocessing step:
and calibrating the rotation direction of each element of the structural information of the target area, and based on the rotation direction, filtering unstable information of each point to be predicted in the seismic section of the target area by utilizing an anisotropic Gaussian function in combination with the position information of each point to be predicted in the target area.
5. The fracture prediction method of claim 2, wherein the formation coordinate system and the target region structure information are respectively constructed by using the following expressions:
Figure FDA0002891774540000021
Figure FDA0002891774540000022
Figure FDA0002891774540000023
Figure FDA0002891774540000024
Figure FDA0002891774540000025
wherein θ represents the formation dip angle difference,
Figure FDA0002891774540000026
expressing the difference value of the azimuth angles, expressing the position coordinates of each point in a rectangular coordinate system by x, y and z, expressing the position coordinates of each point in a stratum coordinate system by x ', y ' and z ', and SrRepresenting the target area structure information, u representing the seismic data.
6. The fracture prediction method of claim 3, wherein the fracture indicator is calculated using the expression:
Figure FDA0002891774540000027
where ε represents the error constant, f represents the fracture indicator, λ1、λ2And respectively representing a plurality of characteristic values obtained by performing characteristic decomposition on the preprocessed target region structure information.
7. The crack prediction method of claim 4, wherein the target region structure information is preprocessed using the following expression:
Figure FDA0002891774540000028
Figure FDA0002891774540000029
Figure FDA00028917745400000210
Figure FDA00028917745400000211
dx＝x-x0
dy＝y-y0
dz＝z-z0
wherein, gsRepresenting elements in the preprocessed target region structure information, x, y and z representing position coordinates of each point in a rectangular coordinate system, x ', y ' and z ' representing position coordinates of each point in a stratum coordinate system, giValue, x, representing element i in the element-scaled target region structure information0、y0、z0Respectively representing the position coordinates, sigma, corresponding to the points to be predicted in the target regionx'、σy'、σz'Respectively representing the standard deviations of the points to be predicted along the directions of x ', y ' and z ', xwin、ywin、zwinRespectively representing the corresponding preprocessing window radius of the point to be predicted along the x, y and z directions.
8. A fracture prediction system based on a formation rotation structure tensor, comprising:
a seismic profile input module configured to obtain a seismic profile of a target area;
the structure information generation module is configured to establish target area structure information matched with the actual stratum condition of the target area according to the seismic section;
a preprocessing module configured to preprocess the target region structure information;
and the crack prediction module is configured to acquire the preprocessed target region structure information, and based on the preprocessed target region structure information, perform crack prediction on the target region to obtain crack possibility index characteristics for the target region.
9. The fracture prediction system of claim 8, wherein the structural information generation module comprises:
a rotation difference generating unit configured to determine a difference between an actual stratigraphic inclination of a target region and a stratigraphic inclination in a rectangular coordinate system and a difference between stratigraphic azimuths according to the seismic profile;
a formation coordinate system generation unit configured to convert the rectangular coordinate system into a corresponding formation coordinate system according to the formation inclination angle difference and the azimuth angle difference;
and the area structure information generating unit is configured to construct the target area structure information according to the seismic data corresponding to the target area based on the stratum coordinate system.
10. The fracture prediction system of claim 8 or 9, wherein the fracture prediction module comprises:
a decomposition processing unit configured to perform characteristic value decomposition processing on the preprocessed target region structure information;
a prediction result generation unit configured to calculate a fracture indicator characterizing the probability of developing a fracture in the target region according to the decomposed plurality of feature values to obtain the fracture probability index feature.
CN202110030654.9A 2021-01-11 2021-01-11 Fracture prediction method and system based on stratum revolution structure tensor Pending CN114764146A (en)

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