Interpolation processing method and device for target horizon

Abstract

The invention provides a target horizon interpolation processing method and device. The method comprises the steps that a target stratum is divided into a first horizon, a second horizon and a target horizon according to horizon data, the first horizon is located above the target horizon, and the target horizon is located above the second horizon; according to the logging data, the first horizon and the second horizon, respectively determining at least one target reference point corresponding to each sampling point in each interlayer region as a target reference point set corresponding to each sampling point in each interlayer region; and interpolating each sampling point in each interlayer region according to the 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. According to the scheme, the interpolation result of the complex geologic body can be accurately determined, so that the real geological condition of the target horizon can be accurately reflected.

Description

Technical Field

[0001] The present invention relates to the field of oil exploration technology, and in particular to an interpolation processing method and device for a target layer. Background Art

[0002] Seismic inversion can determine the elastic parameters of underground media through seismic observation data. The seismic amplitude in the seismic observation data can provide the relative value of the elastic parameters for seismic inversion, while the absolute value of the elastic parameters needs to be provided by the initial low-frequency model. Therefore, the construction of the initial low-frequency model is crucial.

[0003] However, the construction of conventional initial low-frequency models usually adopts mathematical interpolation methods such as inverse distance weighting method and triangular mesh method. Since the mathematical interpolation method does not contain any geological information, for complex geological bodies with low well control and rapid lateral changes in geological bodies, there is a problem of low lateral continuity of interpolation results. The construction of existing initial low-frequency models can also be interpolated based on the correlation between multiple sampling points in seismic data and well logging data to improve the interpolation results of complex geological bodies. However, when the quality of the acquired seismic data is low, there is a situation where the correlation between multiple sampling points cannot be accurately obtained, making it difficult to obtain ideal interpolation results.

[0004] Currently, no effective solution has been proposed for how to accurately determine the interpolation results of complex geological bodies when the quality of the acquired seismic data is low. Summary of the invention

[0005] This specification provides a method and device for interpolation processing of a target layer, which accurately determines the interpolation result of the target layer by fusing multi-source information of the target layer, thereby achieving the purpose of accurately reflecting the real geological conditions of the target layer.

[0006] This specification provides a method and device for interpolation processing of a target layer, which is implemented as follows:

[0007] A target layer interpolation processing method includes:

[0008] Obtain seismic data, well logging data and stratigraphic data of target formations;

[0009] According to the horizon data, the target stratum is divided into a first horizon, a second horizon and a target horizon, wherein the first horizon is located above the target horizon, and the target horizon is located above the second horizon;

[0010] Uniformly resampling 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] Determine at least one target reference point corresponding to each sampling point in each interlayer region according to 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;

[0012] Determine, based on the seismic data, a seismic data matrix of each sampling point in each interlayer region, and a seismic data matrix of each target reference point in a target reference point set corresponding to each sampling point;

[0013] Interpolation is performed on each sampling point in each interlayer region according to 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.

[0014] In one embodiment, according to the horizon data, the target stratum is divided into a first horizon, a second horizon and a target horizon, including:

[0015] Determining the geological conditions of the target stratum according to the stratigraphic data;

[0016] Determining various geological condition points of the target stratum according to the geological conditions of the target stratum;

[0017] According to the geological condition points of the target stratum, the target stratum is divided into a first layer, a second layer and a target layer, wherein the geological condition points in each layer after the division are the same, and the geological condition points between the layers are different.

[0018] In one embodiment, at least one target reference point corresponding to each sampling point in each interlayer region is determined according to 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, including:

[0019] Each sampling point in the interlayer area at the edge of the target layer is regarded as an edge sampling point, and each sampling point in the interlayer area inside the target layer is regarded as an internal sampling point;

[0020] Taking each edge sampling point as a center point, determine a first candidate area with a preset size corresponding to each edge sampling point;

[0021] Remove the areas intersecting with the first layer in the first candidate areas corresponding to the edge sampling points, as the second candidate areas corresponding to the edge sampling points;

[0022] Remove the area intersecting with the second layer in the second candidate area corresponding to each edge sampling point as the target reference area corresponding to each edge sampling point;

[0023] According to the well logging data, at least one known condition point in the target reference area corresponding to each edge sampling point is used as a target reference point set corresponding to each edge sampling point;

[0024] According to the logging data, at least one known condition point inside the interlayer region corresponding to each internal sampling point is used as a target reference point set corresponding to each internal sampling point.

[0025] In one embodiment, interpolating each sampling point in each interlayer region according to 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 includes:

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

[0027] Converting the seismic data matrix of each sampling point in each interlayer region into a preset number of quantitative scores through a preset number of detection points in sequence to determine the score vector of each sampling point in each interlayer region;

[0028] Sequentially converting 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 quantitative scores through a preset number of detection points to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point;

[0029] Determine a weight coefficient of each target reference point in the target reference point set corresponding to each sampling point according to the score vector of each sampling point in each inter-layer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point;

[0030] Interpolate each sampling point in each interlayer region according to the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point and the elasticity parameter of each target reference point in the target reference point set corresponding to each sampling point.

[0031] In one embodiment, converting the seismic data matrix of each sampling point in each interlayer region into a preset number of quantitative scores through a preset number of detection points in sequence to determine the score vector of each sampling point in each interlayer region includes:

[0032] Determine the weight value of each element in the seismic data matrix of each sampling point in each interlayer region after weighting through each detection point, and the weighted action range of each detection point;

[0033] Determine the horizontal coordinate and the vertical coordinate of each sampling point in each interlayer region;

[0034] According to the horizontal and vertical coordinates of each sampling point in each interlayer region, the weighted action range of each detection point, and the weight value of the seismic data of each sampling point weighted by each detection point, the preset number of groups of seismic data matrices of each sampling point in each interlayer region are converted into corresponding quantitative scores according to the following formula:

[0035]

[0036] Among them, F k Indicates the current detection point, E k (i1, j1) represents the quantitative score corresponding to the seismic data matrix of the current sampling point determined by the current detection point, i1 represents the horizontal coordinate of the current sampling point, j1 represents the vertical coordinate of the current sampling point, 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 weighted range of the current detection point, P k (i1+a,j1+b) represents the element in row i1+a and column j1+b in the seismic data matrix of the current sampling point;

[0037] According to the quantitative scores corresponding to the seismic data matrix of each sampling point, the score vector of each sampling point in each interlayer region is determined according to the following formula:

[0038] e(i1,j1)=[E1,E2,…,E K ]

[0039] Among them, 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 embodiment, 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 quantitative scores through a preset number of detection points in sequence 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 after weighting by each detection point, and the weighted action range of each detection point;

[0042] Determine the horizontal coordinate and the vertical coordinate of each target reference point in the target reference point set corresponding to each sampling point;

[0043] According to the horizontal coordinate and the vertical coordinate of each target reference point in the target reference point set corresponding to each sampling point, the weighted action 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 weighting 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 quantitative scores according to the following formula:

[0044]

[0045] Among them, F k represents the current detection point, E' k (i2, j2) represents the quantitative score corresponding to the seismic data matrix of the current target reference point determined by the current detection point, i2 represents the horizontal coordinate of the current target reference point, j2 represents the vertical coordinate of the current target reference point, m represents the range of sampling points participating in weighting, F' k (a, b) represents the weight value of each element in the seismic data matrix of the current target reference point after being weighted by the current detection point, P' k (i2+a,j2+b) represents the element in the i2+ath row and j2+bth column in the seismic data matrix of the current target reference point;

[0046] According to the quantitative scores 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] 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.

[0049] In one embodiment, determining a weight coefficient of each target reference point in the target reference point set corresponding to each sampling point according to the score vector of each sampling point in each inter-layer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point includes:

[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] Among them, w(p) represents the weight coefficient of the 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 embodiment, interpolating each sampling point in each interlayer region according to a weight coefficient of each target reference point in a target reference point set corresponding to each sampling point and an elastic parameter of each target reference point in a target reference point set corresponding to each sampling point includes:

[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 Represents the elastic parameter of the target reference point p in the target reference point set corresponding to the current sampling point.

[0057] A target layer interpolation processing device, comprising:

[0058] An acquisition module, used to acquire seismic data, well logging data and stratigraphic data of a target stratum;

[0059] A division module, used for dividing the target stratum into a first stratum, a second stratum and a target stratum according to the stratum data, wherein the first stratum is located above the second stratum and the target stratum is located between the first stratum and the second stratum;

[0060] A sampling module, used for uniformly resampling 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 consistent;

[0061] A first determination module is used to determine at least one target reference point corresponding to each sampling point in each interlayer region according to the well logging data, the first layer and the second layer, as a target reference point set corresponding to each sampling point in each interlayer region;

[0062] A second determination module is used to determine, based on the seismic data, a seismic data matrix of each sampling point in each interlayer region, and to determine a seismic data matrix of each target reference point in a target reference point set corresponding to each sampling point;

[0063] The interpolation module is used to interpolate each sampling point in each interlayer area according to the logging data, the seismic data matrix of each sampling point in each interlayer area, 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 comprises a processor and a memory for storing instructions executable by the processor, wherein the processor implements the steps of any one of the above methods when executing the instructions.

[0065] A computer-readable storage medium stores a computer program / instruction, which implements the steps of any of the above methods when executed by a processor.

[0066] The present application provides a method and device for interpolation processing of a target layer, which obtains seismic data, well logging data and layer data of a target stratum; divides the target stratum into a first layer, a second layer and a target layer according to the layer data, wherein the first layer is located above the target layer and the target layer is located above the second layer; uniformly resamples 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; determines at least one target reference point corresponding to each sampling point in each interlayer region according to the well logging data, the first layer and the second layer, as a target reference point set corresponding to each sampling point in each interlayer region; determines a seismic data matrix of each sampling point in each interlayer region according to the seismic data, and determines a seismic data matrix of each target reference point in a target reference point set corresponding to each sampling point; interpolates each sampling point in each interlayer region according to 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 a target reference point set corresponding to each sampling point. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of this specification, the drawings required for use in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0068] Figure 1 It is a method flow chart of an embodiment of the interpolation processing method of the target layer provided by the present application;

[0069] Figure 2 It is a flowchart of a method for establishing an initial model of layer-constrained multi-point pattern correlation provided by an embodiment of the present application;

[0070] Figure 3 It is a schematic diagram of inter-layer area division of a layer-constrained multi-point pattern correlation initial model establishment method provided by an embodiment of the present application;

[0071] Figure 4 It is a schematic diagram of interpolation processing of interlayer edge points to be interpolated in a method for establishing an initial model of layer-constrained multi-point pattern correlation provided by an embodiment of the present application;

[0072] Figure 5 It is a hardware structure block diagram of an electronic device for an interpolation processing method of a target layer provided by the present application;

[0073] Figure 6 It is a schematic diagram of the module structure of an embodiment of an interpolation processing device for a target layer provided in the present application. DETAILED DESCRIPTION

[0074] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0075] In view of the problem that the existing interpolation methods cannot accurately determine the interpolation results of complex geological bodies when the quality of the acquired seismic data is low, an interpolation processing method for a target layer is provided in an embodiment of the present application. Although the present application provides method operation steps or device structures as shown in the following embodiments or drawings, more or fewer operation steps or module units may be included in the method or device based on routine or no creative labor. In the steps or structures where there is no necessary causal relationship logically, the execution order of these steps or the module structure of the device is not limited to the execution order or module structure described in the embodiments of the present application and shown in the drawings. When the method or module structure is applied to an actual device or terminal product, it can be connected according to the method or module structure shown in the embodiment or drawings for sequential execution or parallel execution (for example, a parallel processor or a multi-threaded processing environment, or even a distributed processing environment).

[0076] Specifically, Figure 1 As shown, the above-mentioned target layer interpolation processing method may include the following steps:

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

[0078] S102: According to the horizon data, the target stratum is divided into a first horizon, a second horizon and a target horizon, wherein the first horizon is located above the target horizon and the target horizon is located above the second horizon.

[0079] The horizon data includes interpretation horizon information of the geological environment of the target stratum. After dividing the target stratum by interpreting the horizon information, the geological environment in each stratum after the division can be the same, and the geological environment between the strata can be different. Specifically, according to the horizon data, dividing the target stratum into a first horizon, a second horizon and a target horizon can include:

[0080] Determining the geological conditions of the target stratum according to the stratigraphic data;

[0081] Determining various geological condition points of the target stratum according to the geological conditions of the target stratum;

[0082] According to the geological condition points of the target stratum, the target stratum is divided into a first layer, a second layer and a target layer, wherein the geological condition points in each layer after the division are the same, and the geological condition points between the layers are different.

[0083] The divided target stratum is located between the first stratum and the second stratum. Since the geological environments of the first stratum, the second stratum and the target stratum are different, the first stratum and the second stratum will produce stratigraphic constraints on the interpolation processing of the target stratum. Interpolation processing of the target stratum based on the stratigraphic constraints can improve the accuracy of the interpolation results.

[0084] S103: uniformly resample the target layer to determine a preset number of interlayer regions in the target layer, wherein each interlayer region has the same number of sampling points.

[0085] Since the target layer after division has fluctuations, if the interlayer areas of the target layer are determined directly, the number of sampling points in each interlayer area will be inconsistent, resulting in a large error in the final interpolation result. Therefore, the target stratum can be uniformly resampled to determine multiple interlayer areas of the target layer, and the number of sampling points in each interlayer area is consistent.

[0086] S104: Determine at least one target reference point corresponding to each sampling point in each interlayer region according to the logging data, the first layer and the second layer, as a target reference point set corresponding to each sampling point in each interlayer region.

[0087] The interpolation results of each sampling point in each interlayer area 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. Because the positions of each interlayer area in the target layer are different, the sampling points in the interlayer area at the edge of the target layer and adjacent to the first layer or the second layer can be used as edge sampling points, and the sampling points inside the target layer can be used as internal sampling points. Specifically, according to the logging data, at least one known condition point in the interlayer area corresponding to each internal sampling point can be directly used as the target reference point of each internal sampling point.

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

[0089] Taking each edge sampling point as a center point, determine a first candidate area with a preset size corresponding to each edge sampling point;

[0090] Remove the areas intersecting with the first layer in the first candidate areas corresponding to the edge sampling points, as the second candidate areas corresponding to the edge sampling points;

[0091] Remove the area intersecting with the second layer in the second candidate area corresponding to each edge sampling point as the target reference area corresponding to each edge sampling point;

[0092] According to the logging data, at least one known condition point in the target reference area corresponding to each edge sampling point is used as a target reference point set corresponding to each edge sampling point.

[0093] S105: Determine, based on the seismic data, a seismic data matrix of each sampling point in each interlayer region, and determine a seismic data matrix of each target reference point in a target reference point set corresponding to each sampling point.

[0094] Taking sampling point A as an example, the acquisition of the seismic data matrix of each sampling point in each interlayer region and each target reference point in the target reference point set corresponding to each sampling point can be achieved as follows: first determine a post-stack seismic profile containing sampling point A, and then scan the periphery of sampling point A on the post-stack seismic profile through a square data template with a side length of n, so as to obtain the seismic data matrix A1 of sampling point A. Through the above method, 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 can be determined.

[0095] S106: interpolating each sampling point in each interlayer region according to 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.

[0096] Before interpolating each sampling point in each interlayer 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 convert 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 into a corresponding score vector to determine the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point, and then determine the interpolation result of each sampling point in each interlayer region according to the elastic parameters and weight coefficient of each target reference point in the target reference point set corresponding to each sampling point. Specifically, determining the interpolation result of each sampling point in each interlayer region may include the following steps:

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

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

[0099] S3: Converting 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 quantitative scores through a preset number of detection points in turn to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point.

[0100] S4: Determine a weight coefficient of each target reference point in the target reference point set corresponding to each sampling point according to the score vector of each sampling point in each inter-layer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point.

[0101] S5: interpolating each sampling point in each interlayer region according to the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameter of each target reference point in the target reference point set corresponding to each sampling point.

[0102] In order to introduce the geological data of each sampling point in each interlayer region and the geological data of each target reference point in the target reference point set corresponding to each sampling point into the interpolation process to improve the accuracy and continuity of the interpolation result, 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 can be converted into a corresponding score vector. Specifically, the above step S2 can determine the score vector of each sampling point in each interlayer region in the following way:

[0103] Determine the weight value of each element in the seismic data matrix of each sampling point in each interlayer region after weighting through each detection point, and the weighted action range of each detection point;

[0104] Determine the horizontal coordinate and the vertical coordinate of each sampling point in each interlayer region;

[0105] According to the horizontal and vertical coordinates of each sampling point in each interlayer region, the weighted action range of each detection point, and the weight value of the seismic data of each sampling point weighted by each detection point, the preset number of groups of seismic data matrices of each sampling point in each interlayer region are converted into corresponding quantitative scores according to the following formula:

[0106]

[0107] Among them, F k Indicates the current detection point, E k (i1, j1) represents the quantitative score corresponding to the seismic data matrix of the current sampling point determined by the current detection point, i1 represents the horizontal coordinate of the current sampling point, j1 represents the vertical coordinate of the current sampling point, 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 weighted range of the current detection point, P k (i1+a,j1+b) represents the element in row i1+a and column j1+b in the seismic data matrix of the current sampling point;

[0108] According to the quantitative scores corresponding to the seismic data matrix of each sampling point, the score vector of each sampling point in each interlayer region is determined according to the following formula:

[0109] e(i1,j1)=[E1,E2,…,E K ]

[0110] Among them, 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, the above step S3 may 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 after weighting by each detection point, and the weighted action range of each detection point;

[0113] Determine the horizontal coordinate and the vertical coordinate of each target reference point in the target reference point set corresponding to each sampling point;

[0114] According to the horizontal coordinate and the vertical coordinate of each target reference point in the target reference point set corresponding to each sampling point, the weighted action 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 weighting 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 quantitative scores according to the following formula:

[0115]

[0116] Among them, F k represents the current detection point, E' k (i2, j2) represents the quantitative score corresponding to the seismic data matrix of the current target reference point determined by the current detection point, i2 represents the horizontal coordinate of the current target reference point, j2 represents the vertical coordinate of the current target reference point, m represents the range of sampling points participating in weighting, F' k (a, b) represents the weight value of each element in the seismic data matrix of the current target reference point after being weighted by the current detection point, P' k (i2+a,j2+b) represents the element in the i2+ath row and j2+bth column in the seismic data matrix of the current target reference point;

[0117] According to the quantitative scores 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] 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.

[0120] According to the score vector of each sampling point in each inter-layer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point, each sampling point in each inter-layer region is interpolated by a non-uniform local interpolation method. Specifically, the above step S4 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:

[0121]

[0122] Among them, w(p) represents the weight coefficient of the 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, in order to make the sum of the weight coefficients of each target reference point in the target reference point set corresponding to each sampling point equal to 1, the weight coefficient of each target reference point can be corrected according to the following formula:

[0124]

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

[0126] Further, according to the elastic parameters and weight coefficients of each target reference point in the target reference point set corresponding to each sampling point, the above step S5 can 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 Represents the elastic parameter of the target reference point p in the target reference point set corresponding to the current sampling point.

[0129] The above method is described below in conjunction with a specific embodiment. However, it should be noted that this specific embodiment is only for better illustrating the present application and does not constitute an improper limitation on the present application.

[0130] In this embodiment, taking into account the problem that the existing interpolation methods cannot accurately determine the interpolation results of complex geological bodies when the quality of the acquired seismic data is low, a method for establishing an initial model of a stratigraphically constrained multi-point pattern correlation is provided in an embodiment of the present application. This method can be used to determine the correlation between the points to be interpolated and the points participating in the interpolation in the complex geological body based on the seismic data of the complex geological body, so as to further determine the weight coefficients of the points participating in the interpolation, and then combine the stratigraphic data, well logging data and the weight coefficients of the points participating in the interpolation to interpolate the points to be interpolated, so as to accurately determine the interpolation results of the points to be interpolated, thereby accurately reflecting the real geological conditions of the complex geological body.

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

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

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

[0134] The seismic data matrix of point S(i,j) obtained from the training image is converted into six corresponding score values ​​through six two-dimensional filters in sequence, and the expression 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+ath row and j+bth column in the seismic data matrix.

[0137] Furthermore, the score values ​​of the six groups of seismic data at point S(i,j) are defined as a score vector, which is expressed as follows:

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

[0139] Among them, 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 that needs to be interpolated and the participating interpolation points corresponding to each sampling point, the post-stack seismic profile containing the target point can be first determined according to the above method, and then the surrounding of the target point is scanned on the post-stack seismic profile to obtain the seismic data matrix of the target point, and then the seismic data matrix of the target point is converted into six corresponding score values ​​through six filters, and then the six score values ​​are defined as a score vector. The similarity of the patterns between any two points can be judged by the score vectors corresponding to the two points. The similarity between the patterns not only represents the relationship between the two points, but also represents the relationship between the geological patterns around the two points.

[0141] S202: Establishing an interpolation equation based on the logging data and multi-point pattern correlation.

[0142] When the weight coefficients of each participating interpolation point corresponding to the sampling point are determined by the traditional Kriging interpolation method, the inverse operation has the problems of unstable results and large amount of calculation. Therefore, the sampling point can be interpolated by using the non-local mean interpolation method that does not require inverse calculation. The weight coefficients of each participating interpolation point corresponding to the sampling point are determined by calculating the score vectors of the sampling point and each participating interpolation point corresponding to the sampling point. Specifically, the weight coefficients of each participating interpolation point corresponding to the sampling point can be determined according to the following formula:

[0143]

[0144] Among them, l represents the current participating interpolation point, L represents the number of participating 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 participating interpolation point, and h represents the hyperparameter.

[0145] Furthermore, in order to make the sum of the weight coefficients of each interpolation point corresponding to the sampling point equal to 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] Among them, Z′ represents the interpolation result of the sampling point, Z l Represents the elastic parameters of the points involved in the interpolation.

[0150] S203: Using the interpreted horizons, establish a stratigraphic framework and divide the interpolation area.

[0151] In the case of poor seismic data, the manually interpreted stratigraphic information can be used to establish an initial model that conforms to the actual underground structural morphology using the above interpolation equations between layers. The stratigraphic information is mainly used to limit the participating interpolation points selected in the interpolation process. The target stratum is divided into an upper layer area, a lower layer area and an interlayer area through the stratigraphic information. The interlayer area is between the upper layer area and the lower layer area. Specifically, the target stratum can be divided into an upper layer area, a lower layer area and an interlayer area according to the geological environmental conditions of the target stratum, wherein the geological environmental conditions in each area of ​​the upper layer area, the lower layer area and the interlayer area are the same, and the geological environmental conditions between the areas are different.

[0152] Furthermore, in order to avoid the cumulative error caused by the longitudinal average of multiple points of interpolation, the stratigraphic framework of the interlayer area can be constructed through the upper and lower areas. Considering the ups and downs of the upper and lower areas, directly dividing the interlayer area into multiple sub-areas will lead to inconsistent numbers of sampling points in each sub-area. Therefore, equal-interval resampling can be used to ensure the consistency of the number of sampling points in each sub-area. Specifically, Figure 3 As shown in the figure, the black curve represents the upper and lower layers, and the black dotted line represents the constructed equally spaced interlayer stratigraphic framework. During the interpolation process, it is only necessary to horizontally extrapolate the sampling points corresponding to each sub-area to achieve inter-well elastic parameter modeling, and there is no need to perform weighted averaging of the vertical sampling points of the well data, so the resolution and reliability of the modeling results can be effectively improved.

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

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

[0155] In the above example, through the above-mentioned method for establishing the initial model of the stratum-constrained multi-point pattern correlation, the correlation between the points to be interpolated and the points participating in the interpolation in the complex geological body can be determined according to the seismic data of the complex geological body, so as to further determine the weight coefficients of the points participating in the interpolation, and then the stratum data, logging data and the weight coefficients of the points participating in the interpolation are combined to interpolate the points to be interpolated, so as to accurately determine the interpolation results of the points to be interpolated, thereby accurately reflecting the real geological conditions of the complex geological body.

[0156] The method embodiments provided in the above embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on an electronic device as an example, Figure 5 This is a hardware structure block diagram of an electronic device for an interpolation processing method of a target layer provided by this application. Figure 5 As shown, the electronic device 10 may include one or more (only one is shown in the figure) processors 02 (the processor 02 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 04 for storing data, and a transmission module 06 for communication functions. It can be understood by those skilled in the art that Figure 5 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 5 More or fewer components as shown, or with Figure 5 Different configurations are shown.

[0157] The memory 04 can be used to store software programs and modules of application software, such as program instructions / modules corresponding to the interpolation processing method of the target layer in the embodiment of the present 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, the interpolation processing method of the target layer of the above-mentioned application is realized. The memory 04 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 04 may further include a memory remotely arranged relative to the processor 02, and these remote memories may be connected to the electronic device 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0158] The transmission module 06 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the electronic device 10. In one example, the transmission module 06 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission module 06 can be a radio frequency (Radio Frequency, RF) module, which is used to communicate with the Internet wirelessly.

[0159] At the software level, the interpolation processing device of the above target layer can be as follows Figure 6 As shown, including:

[0160] An acquisition module 601 is used to acquire seismic data, well logging data and stratigraphic data of a target stratum;

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

[0162] A 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 consistent;

[0163] A first determination module 604 is used to determine at least one target reference point corresponding to each sampling point in each interlayer region according to the well logging data, the first layer and the second layer, as a target reference point set corresponding to each sampling point in each interlayer region;

[0164] A second determination module 605 is used to determine, based on the seismic data, a seismic data matrix of each sampling point in each interlayer region, and a seismic data matrix of each target reference point in a target reference point set corresponding to each sampling point;

[0165] The interpolation module 606 is used to interpolate each sampling point in each interlayer area according to the logging data, the seismic data matrix of each sampling point in each interlayer area, 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 through the above-mentioned division module 602, including: determining the geological conditions of the target stratum according to the stratum data; determining each geological condition point of the target stratum according to the geological conditions of the target stratum; dividing the target stratum into a first stratum, a second stratum and a target stratum according to the geological condition points of the target stratum, wherein each geological condition point in each stratum after division is the same, and the geological condition points between each stratum are different.

[0167] In one embodiment, the first determination module 604 determines at least one target reference point corresponding to each sampling point in each interlayer region according to the well logging data, the first layer and the second layer, as a target reference point set corresponding to each sampling point in each interlayer region, which may include: taking each sampling point in the interlayer region at the edge of the target layer as an edge sampling point, and taking each sampling point in the interlayer region inside the target layer as an internal sampling point; taking each edge sampling point as a center point, determining a first candidate region with a preset size corresponding to each edge sampling point; removing an area 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 an area 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; taking at least one known condition point in the target reference region corresponding to each edge sampling point as a target reference point set corresponding to each edge sampling point according to the well logging data; taking at least one known condition point inside the interlayer region corresponding to each internal sampling point as a target reference point set corresponding to each internal sampling point according to the well logging data.

[0168] In one embodiment, interpolation is performed on each sampling point in each interlayer region by an interpolation module 606 according to 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:

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

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

[0171] S3: Converting 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 quantitative scores through a preset number of detection points in turn to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point.

[0172] S4: Determine a weight coefficient of each target reference point in the target reference point set corresponding to each sampling point according to the score vector of each sampling point in each inter-layer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point.

[0173] S5: interpolating each sampling point in each interlayer region according to the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point and the elastic parameter of each target reference point in the target reference point set corresponding to each sampling point.

[0174] In one embodiment, the above step S2 may determine the score vector of each sampling point in each inter-layer region in the following manner, including:

[0175] Determine the weight value of each element in the seismic data matrix of each sampling point in each interlayer region after weighting through each detection point, and the weighted action range of each detection point;

[0176] Determine the horizontal coordinate and the vertical coordinate of each sampling point in each interlayer region;

[0177] According to the horizontal and vertical coordinates of each sampling point in each interlayer region, the weighted action range of each detection point, and the weight value of the seismic data of each sampling point weighted by each detection point, the preset number of groups of seismic data matrices of each sampling point in each interlayer region are converted into corresponding quantitative scores according to the following formula:

[0178]

[0179] Among them, F k Indicates the current detection point, E k (i1, j1) represents the quantitative score corresponding to the seismic data matrix of the current sampling point determined by the current detection point, i1 represents the horizontal coordinate of the current sampling point, j1 represents the vertical coordinate of the current sampling point, 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 weighted range of the current detection point, P k (i1+a,j1+b) represents the element in row i1+a and column j1+b in the seismic data matrix of the current sampling point;

[0180] According to the quantitative scores corresponding to the seismic data matrix of each sampling point, the score vector of each sampling point in each interlayer region is determined according to the following formula:

[0181] e(i1,j1)=[E1,E2,…,E K ]

[0182] Among them, 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 embodiment, the above step S3 may determine the score vector of each target reference point in the target reference point set corresponding to each sampling point in the following manner, including:

[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 after weighting by each detection point, and the weighted action range of each detection point;

[0185] Determine the horizontal coordinate and the vertical coordinate of each target reference point in the target reference point set corresponding to each sampling point;

[0186] According to the horizontal coordinate and the vertical coordinate of each target reference point in the target reference point set corresponding to each sampling point, the weighted action 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 weighting 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 quantitative scores according to the following formula:

[0187]

[0188] Among them, F k represents the current detection point, E' k (i2, j2) represents the quantitative score corresponding to the seismic data matrix of the current target reference point determined by the current detection point, i2 represents the horizontal coordinate of the current target reference point, j2 represents the vertical coordinate of the current target reference point, m represents the range of sampling points participating in weighting, F' k (a, b) represents the weight value of each element in the seismic data matrix of the current target reference point after being weighted by the current detection point, P' k (i2+a,j2+b) represents the element in the i2+ath row and j2+bth column in the seismic data matrix of the current target reference point;

[0189] According to the quantitative scores 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] 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.

[0192] In one embodiment, the above step S4 may 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] Among them, w(p) represents the weight coefficient of the 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 embodiment, the above step S5 may 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 Represents the elastic parameter of the target reference point p in the target reference point set corresponding to the current sampling point.

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

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

[0200] Step 2: According to the horizon data, the target stratum is divided into a first horizon, a second horizon and a target horizon, wherein the first horizon is located above the target horizon, and the target horizon is located above the second horizon;

[0201] Step 3: uniformly resample 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: determining at least one target reference point corresponding to each sampling point in each interlayer region according to the well logging data, the first layer and the second layer, as a target reference point set corresponding to each sampling point in each interlayer region;

[0203] Step 5: Determine the seismic data matrix of each sampling point in each interlayer region according to the seismic data, 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: Interpolate each sampling point in each interlayer area according to the logging data, the seismic data matrix of each sampling point in each interlayer area, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point.

[0205] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all steps in the interpolation processing method for the target horizon in the above embodiments. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all steps of the interpolation processing method for the target horizon in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

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

[0207] Step 2: According to the horizon data, the target stratum is divided into a first horizon, a second horizon and a target horizon, wherein the first horizon is located above the target horizon, and the target horizon is located above the second horizon;

[0208] Step 3: uniformly resample 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: determining at least one target reference point corresponding to each sampling point in each interlayer region according to the well logging data, the first layer and the second layer, as a target reference point set corresponding to each sampling point in each interlayer region;

[0210] Step 5: Determine the seismic data matrix of each sampling point in each interlayer region according to the seismic data, 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: Interpolate each sampling point in each interlayer area according to the logging data, the seismic data matrix of each sampling point in each interlayer area, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point.

[0212] As can be seen from the above description, the embodiment of the present application obtains seismic data, well logging data and stratigraphic data of the target stratum; according to the stratigraphic data, divides the target stratum 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; uniformly resamples the target stratigraphic layer to determine a preset number of interlayer regions within the target stratigraphic layer, wherein each interlayer region has the same number of sampling points; according to the well logging data, the first stratigraphic layer and the second stratigraphic layer, respectively determines at least one target reference point corresponding to each sampling point in each interlayer region as a target reference point set corresponding to each sampling point in each interlayer region; according to the seismic data, determines a seismic data matrix of each sampling point in each interlayer region, and determines a seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point; interpolates each sampling point in each interlayer region according to 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 above scheme can accurately determine the interpolation results of complex geological bodies when the quality of the acquired seismic data is low, thereby achieving the purpose of accurately reflecting the real geological conditions of the target layer.

[0213] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the hardware + program embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0214] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0215] Although the present application provides method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-creative labor. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the actual device or client product is executed, it can be executed in the order of the method shown in the embodiments or the drawings or in parallel (for example, in a parallel processor or multi-threaded processing environment).

[0216] Although the present specification embodiment provides the method operation steps as described in the embodiment or flow chart, more or less operation steps may be included based on conventional or non-creative means. The order of steps listed in the embodiment is only one way in the order of execution of many steps, and does not represent a unique execution order. When the device or terminal product in practice is executed, it can be executed in sequence or in parallel (such as a parallel processor or a multi-threaded processing environment, or even a distributed data processing environment) according to the method shown in the embodiment or the accompanying drawings. The term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, product or equipment including a series of elements not only includes those elements, but also includes other elements not clearly listed, or also includes elements inherent to such process, method, product or equipment. In the absence of more restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or equipment including the elements.

[0217] For the convenience of description, the above devices are described in various modules according to their functions. Of course, when implementing the embodiments of this specification, the functions of each module can be implemented in the same or more software and / or hardware, or the module implementing the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0218] Those skilled in the art also know that, in addition to implementing the controller in a purely computer-readable program code, the controller can be made to implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered as a hardware component, and the devices for implementing various functions included therein can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules for implementing the method and structures within the hardware component.

[0219] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0220] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, the embodiments of this specification may take the form of complete hardware embodiments, complete software embodiments or embodiments combining software and hardware. Moreover, the embodiments of this specification may take the form of a computer program product 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 codes.

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

[0222] Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. In the description of this specification, the description of the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of this specification. In this specification, the schematic representation of the above terms does not necessarily target the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, in the absence of contradiction, a person skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0223] The above is only an example of the embodiment of the present specification and is not intended to limit the embodiment of the present specification. For those skilled in the art, the embodiment of the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiment of the present specification shall be included in the scope of the claims of the embodiment of the present specification.

Claims

1. A target layer interpolation processing method, characterized in that: include: Obtain seismic data, well logging data and stratigraphic data of target formations; According to the horizon data, the target stratum is divided into a first horizon, a second horizon and a target horizon, wherein the first horizon is located above the target horizon, and the target horizon is located above the second horizon; Uniformly resampling 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; Determine at least one target reference point corresponding to each sampling point in each interlayer region according to 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; Determine, based on the seismic data, a seismic data matrix of each sampling point in each interlayer region, and a seismic data matrix of each target reference point in a target reference point set corresponding to each sampling point; Interpolation is performed on each sampling point in each interlayer region based on the 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.

2. The method according to claim 1, characterized in that According to the horizon data, the target stratum is divided into a first horizon, a second horizon and a target horizon, including: Determining the geological conditions of the target stratum according to the stratigraphic data; Determining various geological condition points of the target stratum according to the geological conditions of the target stratum; According to the geological condition points of the target stratum, the target stratum is divided into a first layer, a second layer and a target layer, wherein the geological condition points in each layer after the division are the same, and the geological condition points between the layers are different.

3. The method according to claim 1, characterized in that According to 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 respectively determined as a target reference point set corresponding to each sampling point in each interlayer region, including: Each sampling point in the interlayer area at the edge of the target layer is regarded as an edge sampling point, and each sampling point in the interlayer area inside the target layer is regarded as an internal sampling point; Taking each edge sampling point as a center point, determine a first candidate area with a preset size corresponding to each edge sampling point; Remove the areas intersecting with the first layer in the first candidate areas corresponding to the edge sampling points, as the second candidate areas corresponding to the edge sampling points; Remove the area intersecting with the second layer in the second candidate area corresponding to each edge sampling point as the target reference area corresponding to each edge sampling point; According to the well logging data, at least one known condition point in the target reference area corresponding to each edge sampling point is used as a target reference point set corresponding to each edge sampling point; According to the logging data, at least one known condition point inside the interlayer region corresponding to each of the internal sampling points is used as a target reference point set corresponding to each of the internal sampling points.

4. The method according to claim 1, characterized in that: Interpolating each sampling point in each interlayer region according to 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: Determine, based on the well logging data, the elastic parameters of each target reference point in the target reference point set corresponding to each sampling point in each interlayer region; Converting the seismic data matrix of each sampling point in each interlayer region into a preset number of quantitative scores through a preset number of detection points in sequence to determine the score vector of each sampling point in each interlayer region; Sequentially converting 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 quantitative scores through a preset number of detection points to determine the score vector of each target reference point in the target reference point set corresponding to each sampling point; Determine a weight coefficient of each target reference point in the target reference point set corresponding to each sampling point according to the score vector of each sampling point in each inter-layer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point; Interpolate each sampling point in each interlayer region according to the weight coefficient of each target reference point in the target reference point set corresponding to each sampling point and the elasticity parameter of each target reference point in the target reference point set corresponding to each sampling point.

5. The method according to claim 4, characterized in that The seismic data matrix of each sampling point in each interlayer region is converted into a preset number of quantitative scores through a preset number of detection points in sequence to determine the score vector of each sampling point in each interlayer region, including: Determine the weight value of each element in the seismic data matrix of each sampling point in each interlayer region after weighting through each detection point, and the weighted action range of each detection point; Determine the horizontal coordinate and the vertical coordinate of each sampling point in each interlayer region; According to the horizontal and vertical coordinates of each sampling point in each interlayer region, the weighted action range of each detection point, and the weight value of the seismic data of each sampling point weighted by each detection point, the preset number of groups of seismic data matrices of each sampling point in each interlayer region are converted into corresponding quantitative scores according to the following formula: Among them, F k Indicates the current detection point, E k (i1, j1) represents the quantitative score corresponding to the seismic data matrix of the current sampling point determined by the current detection point, i1 represents the horizontal coordinate of the current sampling point, j1 represents the vertical coordinate of the current sampling point, 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 weighted range of the current detection point, P k (i1+a,j1+b) represents the element in row i1+a and column j1+b in the seismic data matrix of the current sampling point; According to the quantitative scores corresponding to the seismic data matrix of each sampling point, the score vector of each sampling point in each interlayer region is determined according to the following formula: e(i1,j1)=[E1,E2,…,E K ] Among them, 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.

6. The method according to claim 4, characterized in that 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 quantitative scores through a preset number of detection points in sequence 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 after weighting by each detection point, and the weighted action range of each detection point; Determine the horizontal coordinate and the vertical coordinate of each target reference point in the target reference point set corresponding to each sampling point; According to the horizontal coordinate and the vertical coordinate of each target reference point in the target reference point set corresponding to each sampling point, the weighted action 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 weighting 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 quantitative scores according to the following formula: Among them, F k represents the current detection point, E' k (i2, j2) represents the quantitative score corresponding to the seismic data matrix of the current target reference point determined by the current detection point, i2 represents the horizontal coordinate of the current target reference point, j2 represents the vertical coordinate of the current target reference point, m represents the range of sampling points participating in weighting, F′ k (a, b) represents the weight value of each element in the seismic data matrix of the current target reference point after being weighted by the current detection point, P′ k (i2+a,j2+b) represents the element in the i2+ath row and j2+bth column in the seismic data matrix of the current target reference point; According to the quantitative scores 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: e'(i2,j2)=[E′1,E′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.

7. The method according to claim 4, characterized in that Determining a weight coefficient of each target reference point in the target reference point set corresponding to each sampling point according to the score vector of each sampling point in each inter-layer region and the score vector of each target reference point in the target reference point set corresponding to each sampling point, 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: Among them, w(p) represents the weight coefficient of the 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.

8. The method according to claim 4, characterized in that Interpolating each sampling point in each interlayer region according to a weight coefficient of each target reference point in a target reference point set corresponding to each sampling point and an elastic parameter of each target reference point in a target reference point set corresponding to each sampling point, 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 Represents the elastic parameter of the target reference point p in the target reference point set corresponding to the current sampling point.

9. An interpolation processing device for a target layer, characterized in that: include: An acquisition module, used to acquire seismic data, well logging data and stratigraphic data of a target stratum; A division module, used for dividing the target stratum into a first stratum, a second stratum and a target stratum according to the stratum data, wherein the first stratum is located above the second stratum and the target stratum is located between the first stratum and the second stratum; A sampling module, used for uniformly resampling 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 consistent; A first determination module is used to determine at least one target reference point corresponding to each sampling point in each interlayer region according to the well logging data, the first layer and the second layer, as a target reference point set corresponding to each sampling point in each interlayer region; A second determination module is used to determine, based on the seismic data, a seismic data matrix of each sampling point in each interlayer region, and to determine a seismic data matrix of each target reference point in a target reference point set corresponding to each sampling point; The interpolation module is used to interpolate each sampling point in each interlayer area according to the logging data, the seismic data matrix of each sampling point in each interlayer area, and the seismic data matrix of each target reference point in the target reference point set corresponding to each sampling point.

10. An electronic device comprising a processor and a memory for storing instructions executable by the processor, characterized in that: When the processor executes the instructions, the steps of the method according to any one of claims 1 to 8 are implemented.

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