An interpolation processing method and apparatus for a target layer

Abstract

This application provides an interpolation method and apparatus for target strata. The method includes: dividing the target strata into a first stratum, a second stratum, and a target stratum based on the stratigraphic data, wherein the first stratum is located above the target stratum, and the target stratum is located above the second stratum; determining at least one target reference point corresponding to each sampling point in each interstratal region based on the well logging data, the first stratum, and the second stratum, as a set of target reference points corresponding to each sampling point in each interstratal region; and interpolating each sampling point in each interstratal region based on the well logging data, the seismic data matrix of each sampling point in each interstratal region, and the seismic data matrix of each target reference point in the set of target reference points corresponding to each sampling point. This method can accurately determine the interpolation results of complex geological bodies, thereby accurately reflecting the true geological conditions of the target stratum.

Description

Technical Field

[0001] This specification belongs to the field of petroleum exploration technology, and in particular relates to an interpolation processing method and apparatus for target strata. Background Technology

[0002] Seismic inversion can determine the elastic parameters of the subsurface medium using seismic observation data. The seismic amplitude in the seismic observation data can provide the relative values ​​of the elastic parameters for seismic inversion, while the absolute values ​​of the elastic parameters need to be provided by the initial low-frequency model. Therefore, the construction of the initial low-frequency model is crucial.

[0003] However, conventional initial low-frequency models typically employ mathematical interpolation methods such as inverse distance weighting and triangular meshing. Since these methods lack geological information, they suffer from low lateral continuity in interpolation results for complex geological bodies with low well control and rapid lateral variations. Existing initial low-frequency models can also improve interpolation results for complex geological bodies by incorporating correlations between multiple sampling points in seismic data and well logging data. However, when the quality of the acquired seismic data is low, it may be difficult to accurately determine the correlations between multiple sampling points, thus hindering the acquisition of ideal interpolation results.

[0004] There is currently no effective solution for accurately determining the interpolation results of complex geological bodies when the acquired seismic data is of low quality. Summary of the Invention

[0005] This specification provides an interpolation processing method and apparatus for a target stratum. By fusing multi-source information of the target stratum, the interpolation result of the target stratum is accurately determined, thereby achieving the purpose of accurately reflecting the true geological conditions of the target stratum.

[0006] This specification provides a method and apparatus for interpolation processing at a target layer, implemented as follows:

[0007] An interpolation method for a target layer, comprising:

[0008] Acquire seismic data, well logging data, and stratigraphic data of the target formation;

[0009] Based on the stratigraphic data, the target strata are divided into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer, wherein the first stratigraphic layer is located above the target stratigraphic layer, and the target stratigraphic layer is located above the second stratigraphic layer.

[0010] Uniform resampling is performed on the target layer to determine a preset number of interlayer regions within the target layer, wherein each interlayer region has the same number of sampling points;

[0011] Based on the well logging data, the first layer and the second layer, at least one target reference point corresponding to each sampling point in each interlayer region is determined, which is used as the set of target reference points corresponding to each sampling point in each interlayer region.

[0012] Based on the earthquake data, determine the earthquake data matrix of each sampling point in each inter-layer region, and determine the earthquake data matrix of each target reference point in the target reference point set corresponding to each sampling point;

[0013] Based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each interlayer region.

[0014] In one implementation, based on the stratigraphic data, the target strata are divided into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer, including:

[0015] Based on the stratigraphic data, determine the geological conditions of the target stratum;

[0016] Based on the geological conditions of the target stratum, determine the various geological condition points of the target stratum;

[0017] Based on the geological condition points of the target stratum, the target stratum is divided into a first layer, a second layer, and a target layer. The geological condition points in each layer are the same, while the geological condition points between layers are different.

[0018] In one embodiment, based on the well logging data, the first layer, and the second layer, at least one target reference point corresponding to each sampling point in each interlayer region is determined, forming a set of target reference points corresponding to each sampling point in each interlayer region, including:

[0019] Each sampling point in the interlayer region at the edge of the target layer is taken as an edge sampling point, and each sampling point in the interlayer region inside the target layer is taken as an internal sampling point.

[0020] Using each edge sampling point as the center point, determine the first candidate region corresponding to each edge sampling point that meets the preset size;

[0021] Remove the regions that intersect with the first layer in the first candidate region corresponding to each edge sampling point, and use them as the second candidate regions corresponding to each edge sampling point;

[0022] Remove the regions that intersect with the second layer in the second candidate regions corresponding to each edge sampling point, and use them as the target reference regions corresponding to each edge sampling point;

[0023] Based on the well logging data, at least one known condition point in the target reference area corresponding to each edge sampling point is taken as the set of target reference points corresponding to each edge sampling point.

[0024] Based on the well logging data, at least one known condition point within the interlayer region corresponding to each internal sampling point is taken as the target reference point set corresponding to each internal sampling point.

[0025] In one implementation, interpolation is performed on each sampling point in each interlayer region based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, including:

[0026] Based on the well logging data, determine the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point in each interlayer region;

[0027] Sequentially, the seismic data matrix of each sampling point in each inter-layer region is converted into a preset number of quantized scores through a preset number of detection points, so as to determine the score vector of each sampling point in each inter-layer region.

[0028] The seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is converted into a preset number of quantized scores through a preset number of detection points in sequence, so as to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point;

[0029] Based on the score vector of each sampling point in each interlayer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point, the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point is determined.

[0030] Interpolation is performed on each sampling point in each interlayer region based on the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point.

[0031] In one implementation, the seismic data matrix of each sampling point in each inter-layer region is sequentially converted into a preset number of quantized scores through a preset number of detection points to determine the score vector of each sampling point in each inter-layer region, including:

[0032] Determine the weight value of each element in the seismic data matrix of each sampling point in each inter-layer region after weighting by each detection point, and the weighting range of each detection point;

[0033] Determine the x-coordinate and y-coordinate of each sampling point in each interlayer region;

[0034] Based on the x and y coordinates of each sampling point in each inter-layer region, the weighted range of each detection point, and the weighted values ​​of the seismic data from each sampling point after passing through each detection point, the pre-set number of seismic data matrices for each sampling point in each inter-layer region are converted into corresponding quantized scores according to the following formula:

[0035]

[0036] Among them, F k E represents the current detection point. k (i1,j1) represents the quantization score of the seismic data matrix corresponding to the current sampling point determined by the current detection point, where i1 represents the x-coordinate of the current sampling point, j1 represents the y-coordinate of the current sampling point, and F k (a,b) represents the weight value of each element in the seismic data matrix of the current sampling point after being weighted by the current detection point, m represents the weighting range of the current detection point, and P k (i1+a,j1+b) represents the element in the i1+a-th row and j1+b-th column of the seismic data matrix of the current sampling point;

[0037] Based on the quantization score corresponding to the seismic data matrix of each sampling point, the score vector of each sampling point in each inter-layer region is determined according to the following formula:

[0038] e(i1,j1)=[E1,E2,…,E K ]

[0039] Where e(i1,j1) represents the score vector of the current sampling point, E k =E k (i1,j1),k=1…K,K represents the number of detection points.

[0040] In one implementation, the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is sequentially converted into a preset number of quantized scores through a preset number of detection points, in order to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point, including:

[0041] Determine the weight value of each element in the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, and the weighting range of each detection point;

[0042] Determine the x-coordinate and y-coordinate of each target reference point in the target reference point set corresponding to each sampling point;

[0043] Based on the x and y coordinates of each target reference point in the target reference point set corresponding to each sampling point, the weighted range of each detection point, and the weight value of each element in the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point after being weighted by each detection point, the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is converted into a preset number of quantized scores according to the following formula:

[0044]

[0045] Among them, F k E' represents the current detection point. k (i2,j2) represents the quantization score of the seismic data matrix corresponding to the current target reference point determined by the current detection point, i2 represents the x-coordinate of the current target reference point, j2 represents the y-coordinate of the current target reference point, m represents the range of sampling points participating in the weighting, and F' k (a,b) represents the weight values ​​of each element in the seismic data matrix of the current target reference point after weighting by the current detection point, P' k (i2+a,j2+b) represents the element in the i2+a-th row and j2+b-th column of the seismic data matrix of the current target reference point;

[0046] Based on the quantization score corresponding to the seismic data matrix of each target reference point, the score vector of each target reference point in the target reference point set corresponding to each sampling point is determined according to the following formula:

[0047] e'(i2,j2)=[E'1,E'2,…,E' K ]

[0048] Where e'(i2,j2) represents the score vector of the current target reference point, E' k =E' k (i2,j2),k=1…K,K represents the number of detection points.

[0049] In one implementation, the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point are determined based on the score vectors of each sampling point in each interlayer region and the score vectors of each target reference point in the target reference point set corresponding to each sampling point, including:

[0050] The weight coefficient of each target reference point in the target reference point set corresponding to each sampling point is determined according to the following formula:

[0051]

[0052] Where w(p) represents the weight coefficient of target reference point p in the target reference point set corresponding to the current sampling point, e(i1,j1) represents the score vector of the current sampling point, e'(i2,j2) represents the score vector of the current target reference point, and h represents the hyperparameter.

[0053] In one implementation, interpolation is performed on each sampling point in each interlayer region based on the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point, including:

[0054] Interpolate each sampling point in the target layer according to the following formula:

[0055]

[0056] Where Z′ represents the interpolation result of the current sampling point, P represents the size of the target reference point set corresponding to the current sampling point, w(p) represents the weight coefficient of the target reference point p in the target reference point set corresponding to the current sampling point, and Z p This represents the elasticity parameter of the target reference point p in the set of target reference points corresponding to the current sampling point.

[0057] An interpolation processing apparatus for a target layer, comprising:

[0058] The acquisition module is used to acquire seismic data, well logging data, and stratigraphic data of the target strata.

[0059] The segmentation module is used to divide the target stratum into a first layer, a second layer, and a target layer based on the stratigraphic data, wherein the first layer is located above the second layer, and the target layer is located between the first layer and the second layer.

[0060] The sampling module is used to uniformly resample the target layer to determine a preset number of interlayer regions within the target layer, wherein the number of sampling points in each interlayer region is the same;

[0061] The first determining module is used to determine at least one target reference point corresponding to each sampling point in each interlayer region based on the well logging data, the first layer and the second layer, as the target reference point set corresponding to each sampling point in each interlayer region.

[0062] The second determining module is used to determine the seismic data matrix of each sampling point in each inter-layer region based on the seismic data, and to determine the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point.

[0063] The interpolation module is used to interpolate each sampling point in each interlayer region based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point.

[0064] An electronic device includes a processor and a memory for storing processor-executable instructions, wherein the processor, when executing the instructions, implements the steps of any of the methods described above.

[0065] A computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of any of the methods described above.

[0066] This application provides an interpolation processing method and apparatus for target strata, which involves acquiring seismic data, well logging data, and stratum data of a target formation; dividing the target formation into a first stratum, a second stratum, and a target stratum based on the stratum data, wherein the first stratum is located above the target stratum, and the target stratum is located above the second stratum; uniformly resampling the target stratum to determine a predetermined number of inter-stratum regions within the target stratum, wherein each inter-stratum region has the same number of sampling points; determining at least one target reference point corresponding to each sampling point in each inter-stratum region based on the well logging data, the first stratum, and the second stratum, as a set of target reference points corresponding to each sampling point in each inter-stratum region; determining the seismic data matrix of each sampling point in each inter-stratum region and the seismic data matrix of each target reference point in the set of target reference points corresponding to each sampling point based on the seismic data; and interpolating each sampling point in each inter-stratum region based on the well logging data, the seismic data matrix of each sampling point in each inter-stratum region, and the seismic data matrix of each target reference point in the set of target reference points corresponding to each sampling point. Attached Figure Description

[0067] To more clearly illustrate the embodiments of this specification, the accompanying drawings used in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0068] Figure 1 This is a flowchart of one embodiment of the interpolation processing method for the target layer provided in this application;

[0069] Figure 2 This is a flowchart illustrating a method for establishing an initial model of hierarchical constraint multi-point pattern correlation provided in an embodiment of this application.

[0070] Figure 3 This is a schematic diagram of the inter-layer region division of the method for establishing an initial model of multi-point pattern correlation under layer constraints provided in an embodiment of this application;

[0071] Figure 4 This is a schematic diagram of the interpolation processing of interlayer edge interpolation points in the initial model establishment method for multi-point pattern correlation of layer constraints provided in an embodiment of this application;

[0072] Figure 5 This is a hardware structure block diagram of an electronic device for a target layer interpolation processing method provided in this application;

[0073] Figure 6 This is a schematic diagram of the module structure of one embodiment of the interpolation processing device for the target layer provided in this application. Detailed Implementation

[0074] 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 with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0075] To address the problem that existing interpolation methods cannot accurately determine the interpolation results for complex geological bodies when the acquired seismic data is of low quality, this application provides an interpolation processing method for target layers. Although this application provides method operation steps or apparatus structures as shown in the following embodiments or figures, more or fewer operation steps or module units may be included in the method or apparatus based on conventional or non-inventive effort. In steps or structures where there is no logically necessary causal relationship, the execution order of these steps or the module structure of the apparatus is not limited to the execution order or module structure described in the embodiments and figures of this application. When the method or module structure is applied in actual devices or terminal products, it can be executed sequentially or in parallel according to the method or module structure shown in the embodiments or figures (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed processing environment).

[0076] Specifically, such as Figure 1 As shown, the interpolation method for the target layer described above may include the following steps:

[0077] S101: Acquire seismic data, well logging data, and stratigraphic data of the target stratum.

[0078] S102: Based on the stratigraphic data, the target strata are divided into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer, wherein the first stratigraphic layer is located above the target stratigraphic layer, and the target stratigraphic layer is located above the second stratigraphic layer.

[0079] The stratigraphic data contains interpretable stratigraphic information about the geological environment of the target strata. After dividing the target strata using this interpretable stratigraphic information, the geological environment within each stratum is the same, while the geological environments differ between strata. Specifically, dividing the target strata into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer based on the stratigraphic data can include:

[0080] Based on the stratigraphic data, determine the geological conditions of the target stratum;

[0081] Based on the geological conditions of the target stratum, determine the various geological condition points of the target stratum;

[0082] Based on the geological condition points of the target stratum, the target stratum is divided into a first layer, a second layer, and a target layer. The geological condition points in each layer are the same, while the geological condition points between layers are different.

[0083] The target stratum after division is located between the first and second strata. Since the geological environments of the first and second strata are different from those of the target stratum, the first and second strata will impose stratigraphic constraints on the interpolation process of the target stratum. Interpolating the target stratum based on stratigraphic constraints can improve the accuracy of the interpolation results.

[0084] S103: Perform uniform resampling on the target layer to determine a preset number of interlayer regions within the target layer, wherein each interlayer region has the same number of sampling points.

[0085] Since the target strata are fluctuating after division, directly determining the interlayer regions of the target strata will result in inconsistent sampling points in each interlayer region, leading to a large error in the final interpolation result. Therefore, the target strata can be uniformly resampled to determine multiple interlayer regions of the target strata, with the same number of sampling points in each interlayer region.

[0086] S104: Based on the well logging data, the first layer and the second layer, determine at least one target reference point corresponding to each sampling point in each interlayer region, as the set of target reference points corresponding to each sampling point in each interlayer region.

[0087] The interpolation results of each sampling point in each interlayer region are determined by the target reference point corresponding to each sampling point. Therefore, it is also necessary to determine the target reference point corresponding to each sampling point. Since each interlayer region is located in a different position in the target layer, sampling points in interlayer regions located at the edge of the target layer or adjacent to the first or second layer can be regarded as edge sampling points, and sampling points located inside the target layer can be regarded as internal sampling points. Specifically, based on the well logging data, at least one known condition point in the interlayer region corresponding to each internal sampling point can be directly regarded as the target reference point of each internal sampling point.

[0088] Furthermore, the target reference point for the edge sampling points needs to be determined based on well logging data, the first layer, and the second layer, which may include the following steps:

[0089] Using each edge sampling point as the center point, determine the first candidate region corresponding to each edge sampling point that meets the preset size;

[0090] Remove the regions that intersect with the first layer in the first candidate region corresponding to each edge sampling point, and use them as the second candidate regions corresponding to each edge sampling point;

[0091] Remove the regions that intersect with the second layer in the second candidate regions corresponding to each edge sampling point, and use them as the target reference regions corresponding to each edge sampling point;

[0092] Based on the well logging data, at least one known condition point in the target reference area corresponding to each edge sampling point is taken as the target reference point set corresponding to each edge sampling point.

[0093] S105: Based on the earthquake data, determine the earthquake data matrix of each sampling point in each inter-layer region, and determine the earthquake data matrix of each target reference point in the target reference point set corresponding to each sampling point.

[0094] Taking sampling point A as an example, the seismic data matrices of each sampling point in each inter-layer region and each target reference point in the corresponding set of target reference points can be obtained as follows: First, a post-stack seismic profile containing sampling point A is determined. Then, a square data template with a side length of n is used to scan the area around sampling point A on the post-stack seismic profile, thereby obtaining the seismic data matrix A1 of sampling point A. Using this method, the seismic data matrices of each sampling point in each inter-layer region and the seismic data matrices of each target reference point in the corresponding set of target reference points can be determined.

[0095] S106: Based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, interpolate each sampling point in each interlayer region.

[0096] Before interpolating each sampling point in each inter-layer region, it is necessary to first determine the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point, and to transform the seismic data matrices of each sampling point in each inter-layer region and the seismic data matrices of each target reference point in the target reference point set corresponding to each sampling point into corresponding score vectors to determine the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point. Then, based on the elastic parameters and weight coefficients of each target reference point in the target reference point set corresponding to each sampling point, the interpolation results of each sampling point in each inter-layer region are determined. Specifically, determining the interpolation results of each sampling point in each inter-layer region may include the following steps:

[0097] S1: Based on the well logging data, determine the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point in each interlayer region.

[0098] S2: Sequentially convert the seismic data matrix of each sampling point in each interlayer region into a preset number of quantized scores through a preset number of detection points, so as to determine the score vector of each sampling point in each interlayer region.

[0099] S3: Sequentially convert the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point into a preset number of quantized scores through a preset number of detection points, so as to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point.

[0100] S4: Based on the score vector of each sampling point in each interlayer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point, determine the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point.

[0101] S5: Based on the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point, interpolate each sampling point in each interlayer region.

[0102] To incorporate the geological data of each sampling point in each interlayer region and the geological data of each target reference point in the corresponding target reference point set into the interpolation process, thereby improving the accuracy and continuity of the interpolation results, the seismic data matrix of each sampling point in each interlayer region and the seismic data matrix of each target reference point in the corresponding target reference point set can be transformed into a corresponding score vector. Specifically, step S2 above can determine the score vector of each sampling point in each interlayer region in the following manner:

[0103] Determine the weight value of each element in the seismic data matrix of each sampling point in each inter-layer region after weighting by each detection point, and the weighting range of each detection point;

[0104] Determine the x-coordinate and y-coordinate of each sampling point in each interlayer region;

[0105] Based on the x and y coordinates of each sampling point in each inter-layer region, the weighted range of each detection point, and the weighted values ​​of the seismic data from each sampling point after passing through each detection point, the pre-set number of seismic data matrices for each sampling point in each inter-layer region are converted into corresponding quantized scores according to the following formula:

[0106]

[0107] Among them, F k E represents the current detection point. k (i1,j1) represents the quantization score of the seismic data matrix corresponding to the current sampling point determined by the current detection point, where i1 represents the x-coordinate of the current sampling point, j1 represents the y-coordinate of the current sampling point, and F k (a,b) represents the weight value of each element in the seismic data matrix of the current sampling point after being weighted by the current detection point, m represents the weighting range of the current detection point, and P k (i1+a,j1+b) represents the element in the i1+a-th row and j1+b-th column of the seismic data matrix of the current sampling point;

[0108] Based on the quantization score corresponding to the seismic data matrix of each sampling point, the score vector of each sampling point in each inter-layer region is determined according to the following formula:

[0109] e(i1,j1)=[E1,E2,…,E K ]

[0110] Where e(i1,j1) represents the score vector of the current sampling point, E k =E k (i1,j1),k=1…K,K represents the number of detection points.

[0111] Furthermore, step S3 above can determine the score vector of each target reference point in the target reference point set corresponding to each sampling point in the following manner:

[0112] Determine the weight value of each element in the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, and the weighting range of each detection point;

[0113] Determine the x-coordinate and y-coordinate of each target reference point in the target reference point set corresponding to each sampling point;

[0114] Based on the x and y coordinates of each target reference point in the target reference point set corresponding to each sampling point, the weighted range of each detection point, and the weight value of each element in the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point after being weighted by each detection point, the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is converted into a preset number of quantized scores according to the following formula:

[0115]

[0116] Among them, F k E' represents the current detection point. k (i2,j2) represents the quantization score of the seismic data matrix corresponding to the current target reference point determined by the current detection point, i2 represents the x-coordinate of the current target reference point, j2 represents the y-coordinate of the current target reference point, m represents the range of sampling points participating in the weighting, and F' k (a,b) represents the weight values ​​of each element in the seismic data matrix of the current target reference point after weighting by the current detection point, P' k (i2+a,j2+b) represents the element in the i2+a-th row and j2+b-th column of the seismic data matrix of the current target reference point;

[0117] Based on the quantization score corresponding to the seismic data matrix of each target reference point, the score vector of each target reference point in the target reference point set corresponding to each sampling point is determined according to the following formula:

[0118] e'(i2,j2)=[E'1,E'2,…,E' K ]

[0119] Where e'(i2,j2) represents the score vector of the current target reference point, E' k =E' k (i2,j2),k=1…K,K represents the number of detection points.

[0120] Based on the score vectors of each sampling point in each interlayer region and the score vectors of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each interlayer region using a non-uniform local interpolation method. Specifically, step S4 above can determine the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point according to the following formula:

[0121]

[0122] Where w(p) represents the weight coefficient of target reference point p in the target reference point set corresponding to the current sampling point, e(i1,j1) represents the score vector of the current sampling point, e'(i2,j2) represents the score vector of the current target reference point, and h represents the hyperparameter.

[0123] Furthermore, to ensure that the sum of the weight coefficients of all target reference points in the target reference point set corresponding to each sampling point is 1, the weight coefficients of each target reference point can be corrected according to the following formula:

[0124]

[0125] Where P represents the number of each target reference point in the target reference point set corresponding to each sampling point.

[0126] Furthermore, based on the elastic parameters and weighting coefficients of each target reference point in the target reference point set corresponding to each sampling point, step S5 above can be used to interpolate each sampling point in the target layer according to the following formula:

[0127]

[0128] Where Z′ represents the interpolation result of the current sampling point, P represents the size of the target reference point set corresponding to the current sampling point, w(p) represents the weight coefficient of the target reference point p in the target reference point set corresponding to the current sampling point, and Z p This represents the elasticity parameter of the target reference point p in the set of target reference points corresponding to the current sampling point.

[0129] The above method will be described below with reference to a specific embodiment. However, it is worth noting that this specific embodiment is only for better illustration of this application and does not constitute an improper limitation of this application.

[0130] In this embodiment, considering the problem that existing interpolation methods cannot accurately determine the interpolation results of complex geological bodies when the quality of the acquired seismic data is low, this application embodiment provides a method for establishing an initial model of correlation of layer-constrained multi-point patterns. This method can determine the correlation between the interpolation point to be interpolated and the interpolation points in the complex geological body based on the seismic data of the complex geological body, so as to further determine the weight coefficient of the interpolation points. Then, combined with the layer data, well logging data and the weight coefficient of the interpolation points, the interpolation point to be interpolated is interpolated to accurately determine the interpolation result of the interpolation point to be interpolated, thereby accurately reflecting the real geological conditions of the complex geological body.

[0131] Specifically, such as Figure 2 As shown, the implementation steps of a method for establishing an initial model of multi-point pattern correlation under hierarchical constraints in this embodiment are as follows:

[0132] S201: Obtain multi-point pattern correlation on seismic records based on multiple filters.

[0133] The seismic data for each of the above points were obtained from the post-stack seismic profile using the filters defined in the FILTERSIM algorithm. Specifically, given a post-stack seismic profile S, it is used as a training image. Then, a square data template with a side length of n is defined. The template is used to scan around point S(i,j) in the training image to obtain the seismic data matrix corresponding to point S(i,j).

[0134] The seismic data matrix of points S(i,j) obtained from the training image is sequentially passed through six two-dimensional filters to transform it into six corresponding score values, the expression of which is:

[0135]

[0136] Among them, F k (k = 1, 2, ..., 6) represents the current filter, E k (i,j) represents the score value corresponding to the seismic data matrix determined by the current filter, F k (a,b) represents the weight value of each element in the seismic data matrix after being weighted by the current filter, and P(i+a,j+b) represents the element in the (i+a)th row and (j+b)th column of the seismic data matrix.

[0137] Furthermore, the six sets of seismic data scores for point S(i,j) are defined as a score vector, the expression of which is:

[0138] e(i,j)=[E1,E2,E3,E4,E5,E6]

[0139] Where e(i,j) represents the score vector of the current sampling point, E k =Ek (i,j),k=1…6.

[0140] Furthermore, for each sampling point requiring interpolation and its corresponding interpolation points, a post-stack seismic profile containing the target point can be determined first, as described above. Then, the area around the target point is scanned on the post-stack seismic profile to obtain the seismic data matrix of the target point. Six filters are then used to transform the seismic data matrix of the target point into six corresponding score values, which are then defined as a score vector. The similarity of patterns between any two points can be determined using their corresponding score vectors. This similarity represents not only the relationship between the two points but also the relationship between the geological patterns surrounding them.

[0141] S202: Establish interpolation equations based on well logging data and multi-point model correlation.

[0142] Because determining the weight coefficients of each interpolation point corresponding to a sampling point using the traditional Kriging interpolation method involves unstable results and high computational cost due to the inversion operation, a nonlocal mean interpolation method that does not require inversion calculation can be used to interpolate the sampling points. The weight coefficients of each interpolation point corresponding to the sampling point can be determined by calculating the sampling point and the score vector of each interpolation point corresponding to the sampling point. Specifically, the weight coefficients of each interpolation point corresponding to the sampling point can be determined according to the following formula:

[0143]

[0144] Where l represents the current interpolation point, L represents the number of interpolation points corresponding to the sampling point, e1(i,j) represents the score vector of the sampling point, e2(i,j) represents the score vector of the current interpolation point, and h represents the hyperparameter.

[0145] Furthermore, to ensure that the sum of the weight coefficients of each interpolation point corresponding to the sampling point is 1, the weight coefficients of each interpolation point can be corrected according to the following formula:

[0146]

[0147] Furthermore, the final interpolation modeling result of the sampling points can be expressed as:

[0148]

[0149] Where Z′ represents the interpolation result of the sampling point, Z l This represents the elasticity parameter of the interpolation point.

[0150] S203: Using the interpreted stratigraphic horizon, establish a stratigraphic framework and delineate the interpolation region.

[0151] When seismic data is poor, manually interpreted stratigraphic information can be used to establish an initial model that conforms to the actual underground structural morphology using the aforementioned interpolation equations. Stratigraphic information is mainly used to limit the interpolation points selected during the interpolation process. The target strata are divided into upper, lower, and inter-strata regions based on the stratigraphic information. The inter-strata region lies between the upper and lower regions. Specifically, the target strata can be divided into upper, lower, and inter-strata regions based on their geological environmental conditions. Within each of the upper, lower, and inter-strata regions, the geological environmental conditions are the same, but the geological environmental conditions differ between the different regions.

[0152] Furthermore, to avoid the cumulative error caused by multi-point vertical averaging of interpolation, a stratigraphic framework of the interlayer region can be constructed by dividing the upper and lower layers. Considering the undulations between the upper and lower layers, directly dividing the interlayer region into multiple sub-regions would lead to inconsistent sampling point numbers in each sub-region. Therefore, evenly spaced resampling can be used to ensure consistent sampling point numbers in each sub-region. Specifically, for example... Figure 3 As shown, the black curve represents the upper and lower two-layer regions, and the black dashed line represents the constructed interlayer stratigraphic framework with equal intervals. In the interpolation process, it is only necessary to horizontally extrapolate the sampling points corresponding to each sub-region to achieve the modeling of inter-well elastic parameters. There is no need to perform a weighted average of the vertical sampling points of the well data, which can effectively improve the resolution and reliability of the modeling results.

[0153] Furthermore, the upper and lower regions impose constraints on the sampling points located at the edges of the interlayer region. Specifically, the sampling points at the edges do not need to select the surrounding L interpolation points; only the interpolation points within the interlayer region are used. This makes the sample point values ​​participating in the weighted average more reasonable, thereby improving the accuracy of the interpolation results. Figure 4 As shown, grid "X" represents the seismic record, grid "Y" represents known condition points, the "black solid line" represents the boundary between the lower layer region and the interlayer region, and grid "Z" represents the sampling point. A search area (the area inside the dashed line) is defined with the sampling point as the center. Within this area, known condition points that are in the interlayer region but not in the lower layer region are searched as interpolation points for the sampling point. If the influence of layer constraints is not considered, four condition points can be found in the search area shown in the figure. If the influence of layer constraints is considered, only the two condition points above the black solid line can be used for interpolation. Sampling points located inside the interlayer region are interpolated based on the interpolation points within the sub-region corresponding to the sampling point.

[0154] S204: Combine the established stratigraphic framework and interpolation equations to perform regional interpolation modeling.

[0155] In the example above, by using the above-mentioned method for establishing an initial model of correlation in a multi-point pattern constrained by stratigraphy, the correlation between the interpolation point to be interpolated and the interpolation points in the complex geological body can be determined based on the seismic data of the complex geological body. This allows for the determination of the weight coefficients of the interpolation points. Then, by combining stratigraphic data, well logging data, and the weight coefficients of the interpolation points, the interpolation point to be interpolated is interpolated to accurately determine the interpolation result of the interpolation point, thereby accurately reflecting the true geological conditions of the complex geological body.

[0156] The methods and embodiments provided in the above-described embodiments of this application can be executed in a mobile terminal, computer terminal, or similar computing device. Taking operation on an electronic device as an example... Figure 5 This is a hardware structure block diagram of an electronic device for a target layer interpolation processing method provided in this application. For example... Figure 5 As shown, the electronic device 10 may include one or more (only one is shown in the figure) processors 02 (processors 02 may include, but are not limited to, microprocessors MCUs or programmable logic devices FPGAs, etc.), a memory 04 for storing data, and a transmission module 06 for communication functions. Those skilled in the art will understand that... Figure 5 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device described above. For example, electronic device 10 may also include... Figure 5 The more or fewer components shown, or having the same Figure 5 The different configurations shown.

[0157] The memory 04 can be used to store software programs and modules of application software, such as the program instructions / modules corresponding to the interpolation processing method at the target level in this embodiment of the application. The processor 02 executes various functional applications and data processing by running the software programs and modules stored in the memory 04, that is, to implement the interpolation processing method at the target level of the application described above. The memory 04 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 04 may further include memory remotely located relative to the processor 02, and these remote memories can be connected to the electronic device 10 via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0158] The transmission module 06 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the electronic device 10. In one example, the transmission module 06 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission module 06 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0159] At the software level, the interpolation processing device at the aforementioned target level can be as follows: Figure 6 As shown, it includes:

[0160] The acquisition module 601 is used to acquire seismic data, well logging data, and stratigraphic data of the target strata.

[0161] The division module 602 is used to divide the target stratum into a first layer, a second layer and a target layer according to the stratigraphic data, wherein the first layer is located above the second layer and the target layer is located between the first layer and the second layer.

[0162] The sampling module 603 is used to uniformly resample the target layer to determine a preset number of interlayer regions within the target layer, wherein the number of sampling points in each interlayer region is the same;

[0163] The first determining module 604 is used to determine at least one target reference point corresponding to each sampling point in each interlayer region based on the well logging data, the first layer and the second layer, as the target reference point set corresponding to each sampling point in each interlayer region.

[0164] The second determining module 605 is used to determine the seismic data matrix of each sampling point in each inter-layer region based on the seismic data, and to determine the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point.

[0165] The interpolation module 606 is used to interpolate each sampling point in each interlayer region based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point.

[0166] In one embodiment, the target stratum can be divided into a first stratum, a second stratum, and a target stratum by the division module 602, including: determining the geological conditions of the target stratum based on the stratum data; determining each geological condition point of the target stratum based on the geological conditions of the target stratum; and dividing the target stratum into the first stratum, the second stratum, and the target stratum based on the geological condition points of the target stratum, wherein the geological condition points in each stratum are the same, and the geological condition points between different strata are different.

[0167] In one embodiment, the first determining module 604 determines at least one target reference point corresponding to each sampling point in each interlayer region based on the well logging data, the first layer, and the second layer, as a set of target reference points corresponding to each sampling point in each interlayer region. This may include: designating each sampling point in the interlayer region located at the edge of the target layer as edge sampling points, and each sampling point in the interlayer region located inside the target layer as internal sampling points; determining a first candidate region of a preset size corresponding to each edge sampling point, with each edge sampling point as the center point; removing the region intersecting with the first layer in the first candidate region corresponding to each edge sampling point, as a second candidate region corresponding to each edge sampling point; removing the region intersecting with the second layer in the second candidate region corresponding to each edge sampling point, as a target reference region corresponding to each edge sampling point; based on the well logging data, designating at least one known condition point in the target reference region corresponding to each edge sampling point as a set of target reference points corresponding to each edge sampling point; and based on the well logging data, designating at least one known condition point inside the interlayer region corresponding to each internal sampling point as a set of target reference points corresponding to each internal sampling point.

[0168] In one embodiment, based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, the interpolation module 606 interpolates each sampling point in each interlayer region, including:

[0169] S1: Based on the well logging data, determine the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point in each interlayer region.

[0170] S2: Sequentially convert the seismic data matrix of each sampling point in each interlayer region into a preset number of quantized scores through a preset number of detection points, so as to determine the score vector of each sampling point in each interlayer region.

[0171] S3: Sequentially convert the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point into a preset number of quantized scores through a preset number of detection points, so as to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point.

[0172] S4: Based on the score vector of each sampling point in each interlayer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point, determine the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point.

[0173] S5: Based on the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point, interpolate each sampling point in each interlayer region.

[0174] In one implementation, step S2 above can determine the score vector of each sampling point in each interlayer region as follows:

[0175] Determine the weight value of each element in the seismic data matrix of each sampling point in each inter-layer region after weighting by each detection point, and the weighting range of each detection point;

[0176] Determine the x-coordinate and y-coordinate of each sampling point in each interlayer region;

[0177] Based on the x and y coordinates of each sampling point in each inter-layer region, the weighted range of each detection point, and the weighted values ​​of the seismic data from each sampling point after passing through each detection point, the pre-set number of seismic data matrices for each sampling point in each inter-layer region are converted into corresponding quantized scores according to the following formula:

[0178]

[0179] Among them, F k E represents the current detection point. k (i1,j1) represents the quantization score of the seismic data matrix corresponding to the current sampling point determined by the current detection point, where i1 represents the x-coordinate of the current sampling point, j1 represents the y-coordinate of the current sampling point, and F k (a,b) represents the weight value of each element in the seismic data matrix of the current sampling point after being weighted by the current detection point, m represents the weighting range of the current detection point, and P k (i1+a,j1+b) represents the element in the i1+a-th row and j1+b-th column of the seismic data matrix of the current sampling point;

[0180] Based on the quantization score corresponding to the seismic data matrix of each sampling point, the score vector of each sampling point in each inter-layer region is determined according to the following formula:

[0181] e(i1,j1)=[E1,E2,…,E K ]

[0182] Where e(i1,j1) represents the score vector of the current sampling point, E k =E k (i1,j1),k=1…K,K represents the number of detection points.

[0183] In one implementation, step S3 above can determine the score vector of each target reference point in the target reference point set corresponding to each sampling point in the following manner:

[0184] Determine the weight value of each element in the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, and the weighting range of each detection point;

[0185] Determine the x-coordinate and y-coordinate of each target reference point in the target reference point set corresponding to each sampling point;

[0186] Based on the x and y coordinates of each target reference point in the target reference point set corresponding to each sampling point, the weighted range of each detection point, and the weight value of each element in the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point after being weighted by each detection point, the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is converted into a preset number of quantized scores according to the following formula:

[0187]

[0188] Among them, F k E' represents the current detection point. k (i2,j2) represents the quantization score of the seismic data matrix corresponding to the current target reference point determined by the current detection point, i2 represents the x-coordinate of the current target reference point, j2 represents the y-coordinate of the current target reference point, m represents the range of sampling points participating in the weighting, and F' k (a,b) represents the weight values ​​of each element in the seismic data matrix of the current target reference point after weighting by the current detection point, P' k (i2+a,j2+b) represents the element in the i2+a-th row and j2+b-th column of the seismic data matrix of the current target reference point;

[0189] Based on the quantization score corresponding to the seismic data matrix of each target reference point, the score vector of each target reference point in the target reference point set corresponding to each sampling point is determined according to the following formula:

[0190] e'(i2,j2)=[E'1,E'2,…,E' K ]

[0191] Where e'(i2,j2) represents the score vector of the current target reference point, E' k =E' k (i2,j2),k=1…K,K represents the number of detection points.

[0192] In one implementation, step S4 above can determine the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point according to the following formula:

[0193]

[0194] Where w(p) represents the weight coefficient of target reference point p in the target reference point set corresponding to the current sampling point, e(i1,j1) represents the score vector of the current sampling point, e'(i2,j2) represents the score vector of the current target reference point, and h represents the hyperparameter.

[0195] In one implementation, step S5 above can be used to interpolate each sampling point in the target layer according to the following formula:

[0196]

[0197] Where Z′ represents the interpolation result of the current sampling point, P represents the size of the target reference point set corresponding to the current sampling point, w(p) represents the weight coefficient of the target reference point p in the target reference point set corresponding to the current sampling point, and Z p This represents the elasticity parameter of the target reference point p in the set of target reference points corresponding to the current sampling point.

[0198] This application also provides a specific implementation of an electronic device capable of implementing all steps of the target layer interpolation processing method in the above embodiments. The electronic device specifically includes: a processor, a memory, a communication interface, and a bus; wherein the processor, memory, and communication interface communicate with each other via the bus; the processor is used to call a computer program in the memory, and when the processor executes the computer program, it implements all steps of the target layer interpolation processing method in the above embodiments. For example, when the processor executes the computer program, it implements the following steps:

[0199] Step 1: Obtain seismic data, well logging data, and stratigraphic data of the target stratum;

[0200] Step 2: Based on the stratigraphic data, the target strata are divided into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer, wherein the first stratigraphic layer is located above the target stratigraphic layer, and the target stratigraphic layer is located above the second stratigraphic layer;

[0201] Step 3: Perform uniform resampling on the target layer to determine a preset number of interlayer regions within the target layer, wherein each interlayer region has the same number of sampling points;

[0202] Step 4: Based on the well logging data, the first layer and the second layer, determine at least one target reference point corresponding to each sampling point in each interlayer region, as the set of target reference points corresponding to each sampling point in each interlayer region;

[0203] Step 5: Based on the seismic data, determine the seismic data matrix of each sampling point in each inter-layer region, and determine the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point;

[0204] Step 6: Based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, interpolate each sampling point in each interlayer region.

[0205] Embodiments of this application also provide a computer-readable storage medium capable of implementing all steps of the target layer interpolation processing method in the above embodiments. The computer-readable storage medium stores a computer program that, when executed by a processor, implements all steps of the target layer interpolation processing method in the above embodiments. For example, when the processor executes the computer program, it implements the following steps:

[0206] Step 1: Obtain seismic data, well logging data, and stratigraphic data of the target stratum;

[0207] Step 2: Based on the stratigraphic data, the target strata are divided into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer, wherein the first stratigraphic layer is located above the target stratigraphic layer, and the target stratigraphic layer is located above the second stratigraphic layer;

[0208] Step 3: Perform uniform resampling on the target layer to determine a preset number of interlayer regions within the target layer, wherein each interlayer region has the same number of sampling points;

[0209] Step 4: Based on the well logging data, the first layer and the second layer, determine at least one target reference point corresponding to each sampling point in each interlayer region, as the set of target reference points corresponding to each sampling point in each interlayer region;

[0210] Step 5: Based on the seismic data, determine the seismic data matrix of each sampling point in each inter-layer region, and determine the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point;

[0211] Step 6: Based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, interpolate each sampling point in each interlayer region.

[0212] As described above, this application embodiment acquires seismic data, well logging data, and stratigraphic data of the target formation; based on the stratigraphic data, the target formation is divided into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer, wherein the first stratigraphic layer is located above the target stratigraphic layer, and the target stratigraphic layer is located above the second stratigraphic layer; uniform resampling is performed on the target stratigraphic layer to determine a predetermined number of inter-stratigraphic regions within the target stratigraphic layer, wherein each inter-stratigraphic region has the same number of sampling points; based on the well logging data, the first stratigraphic layer, and the second stratigraphic layer, at least one target reference point corresponding to each sampling point in each inter-stratigraphic region is determined, serving as the target reference point set corresponding to each sampling point in each inter-stratigraphic region; based on the seismic data, the seismic data matrix of each sampling point in each inter-stratigraphic region is determined, as well as the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is determined; based on the well logging data, the seismic data matrix of each sampling point in each inter-stratigraphic region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each inter-stratigraphic region. The above method can accurately determine the interpolation results of complex geological bodies even when the quality of the acquired seismic data is low, thereby achieving the goal of accurately reflecting the true geological conditions of the target stratum.

[0213] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are relatively simple in description because they are fundamentally similar to method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0214] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0215] While this application provides the method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual device or client product execution, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0216] While this specification provides method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual device or end product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in the process, method, product, or apparatus that includes said elements is not excluded.

[0217] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing the embodiments of this specification, the functions of each module can be implemented in one or more software and / or hardware components, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0218] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0219] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0220] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of computer program products implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0221] The embodiments described in this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0222] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, system embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. In the description of this specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments in this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0223] The above description is merely an embodiment of the present specification and is not intended to limit the embodiments of the present specification. For those skilled in the art, various modifications and variations can be made to the embodiments of the present specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of the present specification should be included within the scope of the claims of the embodiments of the present specification.

Claims

1. An interpolation processing method for a target layer, characterized in that, include: Acquire seismic data, well logging data, and stratigraphic data of the target formation; Based on the stratigraphic data, the target strata are divided into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer, wherein the first stratigraphic layer is located above the target stratigraphic layer, and the target stratigraphic layer is located above the second stratigraphic layer. Uniform resampling is performed on the target layer to determine a preset number of interlayer regions within the target layer, wherein each interlayer region has the same number of sampling points; Based on the well logging data, the first layer and the second layer, at least one target reference point corresponding to each sampling point in each interlayer region is determined, which is used as the set of target reference points corresponding to each sampling point in each interlayer region. Based on the earthquake data, determine the earthquake data matrix of each sampling point in each inter-layer region, and determine the earthquake data matrix of each target reference point in the target reference point set corresponding to each sampling point; Based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each interlayer region. Specifically, based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each interlayer region, including: Based on the well logging data, determine the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point in each interlayer region; Sequentially, the seismic data matrix of each sampling point in each inter-layer region is converted into a preset number of quantized scores through a preset number of detection points, so as to determine the score vector of each sampling point in each inter-layer region. The seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is converted into a preset number of quantized scores through a preset number of detection points in sequence, so as to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point; Based on the score vector of each sampling point in each interlayer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point, the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point is determined. Based on the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each interlayer region. The seismic data at each sampling point is obtained from the post-stack seismic profile using the filters defined in the FILTERSIM algorithm. Specifically, given a post-stack seismic profile, the post-stack seismic profile is used as a training image. A square data template is defined, and the template is used to scan around each sampling point of the training image to obtain the seismic data matrix corresponding to each sampling point.

2. The method according to claim 1, characterized in that, Based on the stratigraphic data, the target strata are divided into a first stratigraphic layer, a second stratigraphic layer, and a target stratigraphic layer, including: Based on the stratigraphic data, determine the geological conditions of the target stratum; Based on the geological conditions of the target stratum, determine the various geological condition points of the target stratum; Based on the geological condition points of the target stratum, the target stratum is divided into a first layer, a second layer, and a target layer. The geological condition points in each layer are the same, while the geological condition points between layers are different.

3. The method according to claim 1, characterized in that, Based on the well logging data, the first layer, and the second layer, at least one target reference point corresponding to each sampling point in each interlayer region is determined, forming a set of target reference points corresponding to each sampling point in each interlayer region, including: Each sampling point in the interlayer region at the edge of the target layer is taken as an edge sampling point, and each sampling point in the interlayer region inside the target layer is taken as an internal sampling point. Using each edge sampling point as the center point, determine the first candidate region corresponding to each edge sampling point that meets the preset size; Remove the regions that intersect with the first layer in the first candidate region corresponding to each edge sampling point, and use them as the second candidate regions corresponding to each edge sampling point; Remove the regions that intersect with the second layer in the second candidate regions corresponding to each edge sampling point, and use them as the target reference regions corresponding to each edge sampling point; Based on the well logging data, at least one known condition point in the target reference area corresponding to each edge sampling point is taken as the set of target reference points corresponding to each edge sampling point. Based on the well logging data, at least one known condition point within the interlayer region corresponding to each internal sampling point is taken as the target reference point set corresponding to each internal sampling point.

4. The method according to claim 1, characterized in that, The seismic data matrix of each sampling point in each inter-layer region is sequentially converted into a preset number of quantized scores through a preset number of detection points, in order to determine the score vector of each sampling point in each inter-layer region, including: Determine the weight value of each element in the seismic data matrix of each sampling point in each inter-layer region after weighting by each detection point, and the weighting range of each detection point; Determine the x-coordinate and y-coordinate of each sampling point in each interlayer region; Based on the x and y coordinates of each sampling point in each inter-layer region, the weighted range of each detection point, and the weighted values ​​of the seismic data from each sampling point after passing through each detection point, the pre-set number of seismic data matrices for each sampling point in each inter-layer region are converted into corresponding quantized scores according to the following formula: Among them, F k E represents the current detection point. k (i1,j1) represents the quantization score of the seismic data matrix corresponding to the current sampling point determined by the current detection point, where i1 represents the x-coordinate of the current sampling point, j1 represents the y-coordinate of the current sampling point, and F k (a,b) represents the weight value of each element in the seismic data matrix of the current sampling point after being weighted by the current detection point, m represents the weighting range of the current detection point, and P k (i1+a,j1+b) represents the element in the i1+a-th row and j1+b-th column of the seismic data matrix of the current sampling point; Based on the quantization score corresponding to the seismic data matrix of each sampling point, the score vector of each sampling point in each inter-layer region is determined according to the following formula: e(i1,j1)=[E1,E2,…,E K ] Where e(i1,j1) represents the score vector of the current sampling point, E k =E k (i1,j1),k=1…K,K represents the number of detection points.

5. The method according to claim 1, characterized in that, The seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is sequentially converted into a preset number of quantized scores through a preset number of detection points, in order to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point, including: Determine the weight value of each element in the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, and the weighting range of each detection point; Determine the x-coordinate and y-coordinate of each target reference point in the target reference point set corresponding to each sampling point; Based on the x and y coordinates of each target reference point in the target reference point set corresponding to each sampling point, the weighted range of each detection point, and the weight value of each element in the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point after being weighted by each detection point, the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is converted into a preset number of quantized scores according to the following formula: Among them, F k E represents the current detection point. ' k (i2,j2) represents the quantization score of the seismic data matrix corresponding to the current target reference point determined by the current detection point, i2 represents the x-coordinate of the current target reference point, j2 represents the y-coordinate of the current target reference point, m represents the range of sampling points participating in the weighting, and F k ' (a,b) represents the weight values ​​of each element in the seismic data matrix of the current target reference point after weighting by the current detection point, P k ' (i2+a,j2+b) represents the element in the i2+a-th row and j2+b-th column of the seismic data matrix of the current target reference point; Based on the quantization score corresponding to the seismic data matrix of each target reference point, the score vector of each target reference point in the target reference point set corresponding to each sampling point is determined according to the following formula: have been ' (i2,j2)=[E1 ' ,HAVE BEEN ' 2,…,E ' K ] Among them, e ' (i2,j2) represents the score vector of the current target reference point, E ' k =E ' k (i2,j2),k=1…K,K represents the number of detection points.

6. The method according to claim 1, characterized in that, Based on the score vectors of each sampling point in each interlayer region and the score vectors of each target reference point in the target reference point set corresponding to each sampling point, the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point are determined, including: The weight coefficient of each target reference point in the target reference point set corresponding to each sampling point is determined according to the following formula: Where w(p) represents the weight coefficient of target reference point p in the target reference point set corresponding to the current sampling point, and e(i1,j1) represents the score vector of the current sampling point. ' (i2,j2) represents the score vector of the current target reference point, and h represents the hyperparameter.

7. The method according to claim 1, characterized in that, Based on the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each interlayer region, including: Interpolate each sampling point in the target layer according to the following formula: Where Z′ represents the interpolation result of the current sampling point, P represents the size of the target reference point set corresponding to the current sampling point, w(p) represents the weight coefficient of the target reference point p in the target reference point set corresponding to the current sampling point, and Z p This represents the elasticity parameter of the target reference point p in the set of target reference points corresponding to the current sampling point.

8. An interpolation processing device for a target layer, characterized in that, include: The acquisition module is used to acquire seismic data, well logging data, and stratigraphic data of the target strata. The segmentation module is used to divide the target stratum into a first layer, a second layer, and a target layer based on the stratigraphic data, wherein the first layer is located above the second layer, and the target layer is located between the first layer and the second layer. The sampling module is used to uniformly resample the target layer to determine a preset number of interlayer regions within the target layer, wherein the number of sampling points in each interlayer region is the same; The first determining module is used to determine at least one target reference point corresponding to each sampling point in each interlayer region based on the well logging data, the first layer and the second layer, as the target reference point set corresponding to each sampling point in each interlayer region. The second determining module is used to determine the seismic data matrix of each sampling point in each inter-layer region based on the seismic data, and to determine the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point. The interpolation module is used to interpolate each sampling point in each interlayer region based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point. Specifically, based on the well logging data, the seismic data matrix of each sampling point in each interlayer region, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each interlayer region, including: Based on the well logging data, determine the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point in each interlayer region; Sequentially, the seismic data matrix of each sampling point in each inter-layer region is converted into a preset number of quantized scores through a preset number of detection points, so as to determine the score vector of each sampling point in each inter-layer region. The seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point is converted into a preset number of quantized scores through a preset number of detection points in sequence, so as to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point; Based on the score vector of each sampling point in each interlayer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point, the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point is determined. Based on the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point, interpolation is performed on each sampling point in each interlayer region. The seismic data at each sampling point is obtained from the post-stack seismic profile using the filters defined in the FILTERSIM algorithm. Specifically, given a post-stack seismic profile, the post-stack seismic profile is used as a training image. A square data template is defined, and the template is used to scan around each sampling point of the training image to obtain the seismic data matrix corresponding to each sampling point.

9. An electronic device comprising a processor and a memory for storing processor-executable instructions, characterized in that, When the processor executes the instructions, it implements the steps of the method according to any one of claims 1 to 7.

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