Geologic horizon plane modeling method based on space curvature constraint

Abstract

The invention discloses a geologic horizon plane modeling method based on space curvature constraint, and relates to the field of geological reservoir characterization. The spatial curvature constrained geologic horizon surface modeling method comprises the following steps: judging missing points to be interpolated on a certain surface element of a structural horizon; dividing the scattered points into a plurality of groups according to azimuth angles; scribing from the point to be interpolated to an interpolation radius to form an azimuth line; the tangential curvature in the neighborhood and the normal curvature in the neighborhood with the scattered points are calculated; calculating the tangential curvature average value of the to-be-interpolated points on the azimuth lines of all azimuth angle groups, and cutting off the weight radius on the azimuth angle groups; a Z value is deduced back from the interpolation point by using a linear trend extrapolation prediction method; calculating to obtain a Z value of the to-be-interpolated point; and forming a point set by the existing points and the interpolation points on the horizon surface elements to establish a continuous horizon surface. According to the geologic horizon plane modeling method based on the space curvature constraint, by comprehensively considering structural deformation in different space directions, the interpolation result of geologic horizon plane modeling can keep geologic features without generating deviation.

Description

Technical Field

[0001] The present application relates to the field of geological reservoir characterization, and in particular to a geological layer plane modeling method with spatial curvature constraints. Background Art

[0002] In seismic interpretation, the spatial distribution of interpretation points is often uneven due to factors such as seismic data quality, observation system, and interpretation method. During geological modeling, the seismic interpretation points need to be interpolated to a uniform distribution before establishing a spatially continuous horizon. Common approaches include inverse distance weighting, kriging, minimum curvature, and sequential Gaussian interpolation. The inverse distance weighting method assumes a simple spatial structure. Kriging interpolation utilizes regional similarity constraints, requiring a certain degree of structural stability and a relatively uniform spatial distribution of scattered points. The minimum curvature method minimizes the sum of curvatures in a local area, aiming for maximum smoothness. Sequential Gaussian conditional simulation requires a normal distribution of data values. However, in practice, seismic interpretation often occurs in complex, undulating structures, where the signal-to-noise ratio is low and horizon selection is difficult, resulting in missing input data during interpolation. These complex structural areas do not fit the assumptions of the aforementioned interpolation methods, and the interpolation results can easily lead to deviations in geological phenomena. Summary of the Invention

[0003] The purpose of this application is to provide a geological layer surface modeling method with spatial curvature constraints, which can maintain the geological characteristics of the interpolation results of geological layer surface modeling without deviation by comprehensively considering the structural deformation in different spatial directions.

[0004] This application is implemented as follows:

[0005] The present application provides a method for geological layer surface modeling with spatial curvature constraints, comprising the following steps:

[0006] S1. Input a spatial point set; set the structural layer bin size, perform spatial point position regularization, and determine whether a point on a certain bin of the structural layer is missing. If missing, call the point a to-be-interpolated point and execute steps S2-S8; if not, execute step S9;

[0007] S2. Plane azimuth grouping: For a certain point to be interpolated, calculate the plane azimuth distribution angles of the existing scattered points in the plane with the interpolation point as the origin within a given interpolation radius, calculate the maximum curvature in the neighborhood of the existing scattered points in the plane, calculate the average curvature, and divide the scattered points into several groups according to the azimuth angle based on the calculated curvature;

[0008] S3, establishing a bearing line; starting from the point to be interpolated, drawing a line to the interpolation radius to form a bearing line;

[0009] S4. Projecting the point onto the azimuth line; using a plane passing through the point to be interpolated and parallel to the Z direction as the tangent plane, and using a plane parallel to the Z direction and perpendicular to the tangent plane as the normal plane; projecting the nearest existing scattered point onto the azimuth line, and calculating the tangential curvature within the neighborhood, and calculating the normal curvature within the neighborhood of the existing scattered point;

[0010] S5, weighted radius truncation on the azimuth group; calculating the tangential curvature of the points to be interpolated on the azimuth lines of all azimuth groups, and obtaining the average value of the tangential curvature, setting a threshold, and truncating the weighted radius on the azimuth group so that the weighted radius of interpolation on different plane azimuth groups is different;

[0011] S6. Interpolation on the orientation groups: For a point to be interpolated, on one of the orientation groups, based on the projection of the point on the orientation line, use the linear trend extrapolation prediction method to deduce the Z value of the interpolation point;

[0012] S7, weighted coefficient processing; summing the curvatures of the projection points on the orientation groups within the truncation radius to obtain A; setting a parameter B, taking A to the power of B as the curvature weight coefficient of the orientation group, summing the orientation curvature weight coefficients of each group, and normalizing the sum to 1.0;

[0013] S8, obtaining interpolation values; multiplying the back-calculated Z value of each group of orientation groups by the normalized weight coefficient, and accumulating them to obtain the Z value of the point to be interpolated;

[0014] S9. Establish a structural layer surface; combine the existing points and interpolation points on the layer surface element into a point set to establish a continuous layer surface.

[0015] In some optional implementations, the interpolation radius and weight values ​​are constrained using spatial curvature.

[0016] In some optional embodiments, spatial weighting values ​​are differentiated in plane azimuth.

[0017] In some optional implementation schemes, in step S2, the greater the average curvature value, the greater the number of azimuth angle groups.

[0018] In some optional implementation schemes, in step S3, spatial points are evenly set at intervals of the layer bin size when drawing a line along the median azimuth starting from the point to be interpolated.

[0019] In some optional implementation schemes, in step S4, a threshold is set to limit the maximum normal projection radius.

[0020] In some optional embodiments, the parameter B is a real number less than or equal to -1.0.

[0021] In some optional implementation schemes, when drawing a line from the point to be interpolated, the line is drawn along the median of the azimuth group.

[0022] The beneficial effects of the present application are as follows: the spatial curvature constrained geological layer surface modeling method provided by the present application includes the following steps: inputting a spatial point set to determine whether a point on a certain face element of the structural layer is missing, thereby determining the missing point to be interpolated; determining the plane azimuth distribution angle of the scattered points within a given interpolation radius of the point to be interpolated, calculating the curvature average of the maximum curvature in the neighborhood of the existing scattered points on the plane, and dividing the scattered points into several groups according to the azimuth; drawing a line from the point to be interpolated to the interpolation radius to form an azimuth line; taking a plane passing through the point to be interpolated and parallel to the Z direction as the tangent plane, and taking a plane parallel to the Z direction and perpendicular to the tangent plane as the normal plane, projecting the nearest existing scattered point onto the azimuth line, and calculating the tangential curvature in the neighborhood, and calculating the normal curvature in the neighborhood of the existing scattered points; calculating all azimuth groups The tangential curvature of the point to be interpolated on the azimuth line is calculated, and the average value of the tangential curvature is calculated. A threshold is set to truncate the weight radius on the azimuth group so that the interpolation weight radius on different plane azimuth groups is different. For a certain point to be interpolated, based on the point projection on the azimuth line, the Z value of the interpolation point is deduced using the linear trend extrapolation prediction method. The curvatures of the projected points on the azimuth group within the truncation radius are summed to obtain A. A parameter B is set, and the power of B is taken as the curvature weight coefficient of the azimuth group. The azimuth curvature weight coefficients of each group are summed and normalized to a total of 1.0. The deduced Z value of each azimuth group is multiplied by the normalized weight coefficient, and the Z value of the point to be interpolated is obtained by accumulation. The existing points and interpolation points on the layer element are combined into a point set to establish a continuous layer surface. The spatial curvature constrained geological layer plane modeling method provided in this application can maintain the geological characteristics of the interpolation results of geological layer plane modeling without deviation by comprehensively considering the structural deformation in different spatial directions. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 A schematic flow chart of a method for modeling geological strata with spatial curvature constraints provided in an embodiment of the present application;

[0025] Figure 2 The input spatial point set diagram in the geological layer plane modeling method with spatial curvature constraint provided in the embodiment of the present application;

[0026] Figure 3 A near-point projection diagram of a plane azimuth line in a geological layer plane modeling method with spatial curvature constraints provided in an embodiment of the present application;

[0027] Figure 4 The interpolation point set and structural layer surface effect diagram in the geological layer surface modeling method with spatial curvature constraints provided in the embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0029] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without making any creative efforts shall fall within the scope of protection of the present application.

[0030] The features and performance of the geological layer plane modeling method with spatial curvature constraints of the present application are further described in detail below in conjunction with the embodiments.

[0031] Please refer to Figure 1 , with reference Figures 2 to 4 As shown, the embodiment of the present application provides a geological layer plane modeling method with spatial curvature constraints, and the specific steps are as follows:

[0032] S1, input spatial point set, which includes:

[0033] S11. Select a geological space. In the geological space, there are scattered points distributed in the XYZ rectangular coordinate system. The distribution length in the X direction is 3680 meters, and the distribution length in the Y direction is 3280 meters. Figure 2 shown.

[0034] S12, parameter setting: set the interpolation radius to 2000 meters and the curvature weight coefficient parameter B to -1.0.

[0035] S13. Set the structural layer plane and regularize the spatial point positions. Take out the minimum X and maximum X, minimum Y and maximum Y of the existing points to set a plane rectangular range. Set the plane size of the layer element to 40 meters × 40 meters, and divide the plane into a finite number of elements within the above rectangle. Set the element number to (i, j), where i and j are integers. Starting from the element where the minimum X and minimum Y are located, first set it to number (0, 0), keep Y unchanged, and set it to (0, 1), (0, 2), etc. in the direction of increasing X. After reaching the maximum X, increase Y by 40 meters. Similarly, set the element number at the minimum X to (1, 0), and set it to (1, 1), (1, 2), etc. in the direction of increasing X. Follow this rule until the maximum X and maximum Y are reached, and the numbering ends.

[0036] S14. Determine whether a point on a certain surface element of the layer is missing. If it is missing, the point is called a point to be interpolated and steps S2-S8 are executed; if it is not missing, step S9 is executed.

[0037] S2, plane azimuth grouping. Take the bin number (47, 52) as an example. The bin center is located at Figure 3 The middle blue square points. Given an interpolation radius of 2000 meters, the orientation of existing scattered points on the plane relative to the point to be interpolated is calculated within this radius, with a distribution of 0°-360°. The maximum curvature within the neighborhood of the existing scattered points is calculated, and the average curvature is calculated. Based on this average, the scattered points are divided into 16 groups according to their orientation angles.

[0038] S3. Establishing an orientation line: Starting from the bin number point (47, 52), spatial points are evenly set at intervals of the layer bin size until the interpolation radius is reached.

[0039] S4. Projection of points on the azimuth line. A plane passing through the interpolated point and parallel to the Z direction is used as the tangent plane, and a plane parallel to the Z direction and perpendicular to the tangent plane is used as the normal plane. For points on the azimuth line, the nearest existing scattered point is projected onto it, and the tangential curvature within the neighborhood is calculated. Because the scattered points are spatially distributed and fluctuate on the normal plane, the projection will produce discreteness and deviation. Therefore, the normal curvature within the neighborhood of the existing scattered points is calculated, and a threshold is set to limit the maximum normal projection radius.

[0040] S5. Weighted radius truncation on azimuth groups. Calculate the tangential curvature for all azimuth groups and take the average value. This average value represents the tangential deformation intensity within the interpolation radius. Based on this value, a threshold is set to truncate the weighted radius on the azimuth groups. That is, the interpolation weighted radius varies for different plane azimuth groups.

[0041] S6. Interpolation on the orientation groups. On one of the orientation groups, based on the projection of the points on the orientation line, use the linear trend extrapolation prediction method to deduce the Z value of the interpolation point.

[0042] S7. Weighting coefficient processing. The greater the tangential deformation, the greater the difference in geological structural characteristics from the interpolation point. Sum the curvatures of the projected points on the azimuth group within the truncation radius, A. Set the curvature weight coefficient parameter B to -1.0. Raise A to the power of B as the curvature weight coefficient for the azimuth group. Sum the curvature weight coefficients for each group of azimuths and normalize them to a total of 1.0.

[0043] S8. Calculate the interpolation value. Multiply the back-calculated Z value of each set of orientations by the normalized weight coefficient, and add them up to obtain the Z value of the point to be interpolated.

[0044] S9. Establish a structural layer surface. The existing points and interpolation points on the layer element are combined into a point set to establish a continuous layer surface, such as Figure 4 Indicated by the middle dot.

[0045] The spatial curvature constrained geological layer surface modeling method provided in the embodiment of the present application determines whether a point on a certain face element of the structural layer is missing after inputting a spatial point set, thereby determining the missing point to be interpolated, and then determining the plane azimuth distribution angle of the scattered points of the point to be interpolated within a given interpolation radius, calculating the curvature average of the maximum curvature in the neighborhood of the existing scattered points in the plane, dividing the scattered points into several groups according to the azimuth angle, and then drawing a line from the point to be interpolated to the interpolation radius to form an azimuth line, using a plane passing through the point to be interpolated and parallel to the Z direction as the tangent plane, and using a plane parallel to the Z direction and perpendicular to the tangent plane as the normal plane, projecting the nearest existing scattered point onto the azimuth line, and calculating the tangential curvature in the neighborhood and the normal curvature in the neighborhood of the existing scattered points; calculating the azimuth line of all azimuth groups The tangential curvature of the point to be interpolated is obtained, and the average value of the tangential curvature is calculated. A threshold is set to truncate the weight radius on the azimuth group so that the interpolation weight radius on different plane azimuth groups is different. For a certain point to be interpolated, based on the point projection on the azimuth line, the Z value of the interpolation point is deduced using the linear trend extrapolation prediction method. The curvatures of the projected points on the azimuth group within the truncation radius are summed to obtain A. A parameter B is set, and the power of B with A as the base is taken as the curvature weight coefficient of the azimuth group. The azimuth curvature weight coefficients of each group are summed and normalized to a total of 1.0. The deduced Z value of each azimuth group is multiplied by the normalized weight coefficient, and the Z value of the point to be interpolated is obtained after accumulation. The existing points and interpolation points on the layer element are combined into a point set to establish a continuous layer surface. The spatial curvature constrained geological layer plane modeling method provided in this application can maintain the geological characteristics of the interpolation results of geological layer plane modeling without deviation by comprehensively considering the structural deformation in different spatial directions.

[0046] The embodiments described above are part of the embodiments of the present application, rather than all of the embodiments. The detailed description of the embodiments of the present application is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

Claims

1. A method for geological layer plane modeling with spatial curvature constraints, characterized in that: The following steps are involved: S1, input spatial point set; Set the bin size of the structural layer, perform spatial point position regularization, and determine whether a point on a certain bin of the structural layer is missing. If missing, call the point to be interpolated and execute steps S2-S8; if not missing, execute step S9; S2. Plane azimuth grouping: For a certain point to be interpolated, calculate the plane azimuth distribution angles of the existing scattered points in the plane with the interpolation point as the origin within a given interpolation radius, calculate the maximum curvature in the neighborhood of the existing scattered points in the plane, calculate the average curvature, and divide the scattered points into several groups according to the azimuth angle based on the calculated curvature; S3, establish a bearing line; Draw a line from the point to be interpolated to the interpolation radius to form a bearing line; S4. Projecting the point onto the azimuth line; using a plane passing through the point to be interpolated and parallel to the Z direction as the tangent plane, and using a plane parallel to the Z direction and perpendicular to the tangent plane as the normal plane; projecting the nearest existing scattered point onto the azimuth line, and calculating the tangential curvature within the neighborhood, and calculating the normal curvature within the neighborhood of the existing scattered point; S5, weighted radius truncation on the azimuth group; calculating the tangential curvature of the points to be interpolated on the azimuth lines of all azimuth groups, and obtaining the average value of the tangential curvature, setting a threshold, and truncating the weighted radius on the azimuth group so that the weighted radius of interpolation on different plane azimuth groups is different; S6. Interpolation on the orientation groups: For a point to be interpolated, on one of the orientation groups, based on the projection of the point on the orientation line, use the linear trend extrapolation prediction method to deduce the Z value of the interpolation point; S7, weighted coefficient processing; summing the curvatures of the projection points on the orientation group within the truncation radius to obtain A; Set a parameter B, take the power of B with base A as the curvature weight coefficient of the orientation group, sum the orientation curvature weight coefficients of each group, and normalize them to a total of 1.0; S8, obtaining interpolation values; multiplying the back-calculated Z value of each group of orientation groups by the normalized weight coefficient, and accumulating them to obtain the Z value of the point to be interpolated; S9. Establish a structural layer surface; combine the existing points and interpolation points on the layer surface element into a point set to establish a continuous layer surface.

2. The method for geological layer plane modeling with spatial curvature constraint according to claim 1, characterized in that: Use space curvature to constrain the interpolation radius and weight value.

3. The method for geological layer plane modeling with spatial curvature constraint according to claim 1, characterized in that: The spatial weighted values ​​are distinguished in the plane azimuth.

4. The method for geological layer plane modeling with spatial curvature constraint according to claim 1, characterized in that: In step S2, the greater the average curvature value, the greater the number of azimuth angle groups.

5. The method for geological layer plane modeling with spatial curvature constraint according to claim 1, characterized in that: In step S3, starting from the point to be interpolated, spatial points are evenly set at intervals of the layer bin size when drawing a line along the median azimuth angle.

6. The method for geological layer plane modeling with spatial curvature constraint according to claim 1, characterized in that: In step S4, a threshold is set to limit the maximum normal projection radius.

7. The method for geological layer plane modeling with spatial curvature constraint according to claim 1, characterized in that: The parameter B is a real number less than or equal to -1.

0.

8. The method for geological layer plane modeling with spatial curvature constraint according to claim 1, characterized in that: When drawing a line from the point to be interpolated, start from the median azimuth of the azimuth group.

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