Delta front channel porosity and permeability model method and system based on spatial trend constraints

Abstract

The present invention discloses a delta front channel porosity and permeability model method and system based on spatial trend constraints, and the method comprises the following steps: using the internal lateral trend constraints of a single-period channel in the channel phase model to establish a lateral trend body of an underwater distributary channel in a study area; using the internal vertical trend constraints of a single-period channel in the channel phase model to establish a vertical trend body of an underwater distributary channel in a study area; setting different weight values ​​for the lateral trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion; according to the porosity data and permeability data in the drilling data, and taking all the different fused trend bodies as modeling constraints, respectively obtain the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion; therefore, the present invention characterizes the internal heterogeneity characteristics of underwater distributary channels at different positions in the delta front subphase based on the multi-directional trend fusion constraint modeling process.

Description

Technical Field

[0001] The invention relates to the technical field of oil reservoir description, and in particular to a delta front channel porosity and permeability model method and system based on spatial trend constraints. Background Art

[0002] The braided river delta front is an important type of oil and gas reservoir and a favorable area for oil and gas exploration in continental sedimentary basins. The braided river delta front has complex sedimentary genesis characteristics. The mutual cutting and superposition of underwater distributary channel sand bodies of different genesis and different periods within the same period leads to differences in physical properties, making the reservoir structure complex, highly heterogeneous, and difficult to tap the remaining oil, which has led to an increasing international interest in the research of braided river delta reservoirs.

[0003] Previous researchers have done a lot of work on braided river delta reservoir modeling, using sequential indicator simulation, deterministic modeling, a combination of deterministic and sequential Gaussian simulation methods, indicator point processes, and multi-point geostatistical methods. At the same time, the geological modeling process is synergistically constrained by seismic inversion, sedimentary forward simulation, two-dimensional trend surface and other data. However, the existing modeling strategies or constraint data are relatively lacking in characterizing the laws of physical property changes in different channels and single-period channels in different directions. Summary of the invention

[0004] The present invention provides a delta front channel porosity and permeability model method and system based on spatial trend constraints, which characterizes the internal heterogeneity characteristics of underwater distributary channels at different positions in the delta front subphase based on a multi-directional trend fusion constraint modeling process, and provides a scientific basis for the distribution of remaining oil in the braided river delta front channel phase reservoir and development decision-making.

[0005] In a first aspect, a delta front channel porosity and permeability model method based on spatial trend constraints is provided, comprising the following steps:

[0006] The drilling data of the underwater distributary channel in the study area were transferred to the PETREL modeling software, and the channel facies model was established based on the drilling data;

[0007] By using the internal lateral trend constraints of the single-period river channel in the river channel facies model, the lateral trend body of the underwater distributary channel in the study area is established;

[0008] By using the vertical trend constraints inside the single-period channel in the channel phase model, the vertical trend body of the underwater distributary channel in the study area is established;

[0009] Setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion;

[0010] According to the porosity data and permeability data in the drilling data, and taking all the different fused trend bodies as modeling constraints, the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion are obtained respectively.

[0011] According to the first aspect, in a first possible implementation manner of the first aspect, the step of “establishing a river channel facies model according to the drilling data” specifically includes the following steps:

[0012] According to the microfacies data of the delta front sedimentary system in the drilling data, the fluvial facies model of the study area was established by using the Fluvsim algorithm.

[0013] According to the first aspect, in a second possible implementation of the first aspect, the step of “using the internal lateral trend constraints of the single-period river channel in the river channel phase model to establish a lateral trend body of the underwater distributary channel in the study area” specifically includes the following steps:

[0014] An initial lateral trend body is obtained by using the lateral trend inside the single-period river channel in the river channel phase model, wherein the lateral trend inside the river channel is defined as a rule that the grain size of the sand body gradually becomes finer and the physical properties gradually become worse from the center of the river channel to both sides;

[0015] The initial lateral trend body is normalized to the lateral trend body of the underwater distributary channel in the study area in the interval [0-1].

[0016] According to the first aspect, in a third possible implementation of the first aspect, the step of “using the internal vertical trend constraint of the single-period river channel in the river channel phase model to establish a vertical trend body of the underwater distributary channel in the study area” specifically includes the following steps:

[0017] The initial vertical trend body is obtained by using the vertical trend inside the single-period river channel in the river channel phase model, wherein the vertical trend inside the river channel is defined as the law that the grain size gradually becomes finer and the physical properties gradually become worse from the bottom to the top of the river channel;

[0018] The initial vertical trend body is normalized to the vertical trend body of the underwater distributary channel in the study area in the interval [0-1].

[0019] According to the first aspect, in a fourth possible implementation manner of the first aspect, the step of “setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion” specifically includes the following steps:

[0020] For the horizontal trend body P ijk Set the weight value α to the vertical trend body V ijk Set the weight value β, then the fusion trend body ω ijk The weighted calculation method is as follows:

[0021] ω ijk =αP ijk +βV ijk ;

[0022] Among them, 0≤α≤1, 0≤β≤1, α+β=1, 0≤ω ijk ≤1;

[0023] Where i is the east-west grid point position of the trend body; j is the north-south grid point position of the trend body; and k is the vertical grid point position of the trend body.

[0024] According to the first aspect, in a fifth possible implementation of the first aspect, the step of “obtaining the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion, based on the porosity data and permeability data in the drilling data, and taking all the different fused trend bodies as modeling constraints” specifically includes the following steps:

[0025] According to the porosity data in the drilling data, and taking all the different fused trend bodies as modeling constraints, a sequential Gaussian simulation method is used to establish a porosity model of the underwater distributary channel in the study area corresponding to each weighted fusion;

[0026] According to the positive correlation between the porosity data and the permeability data in the drilling data, and taking all the different fused trend bodies and the porosity models as modeling constraints, a sequential Gaussian simulation method is used to establish the permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion.

[0027] According to the first aspect, in a sixth possible implementation manner of the first aspect, after the step of “setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion”, the following steps are specifically included:

[0028] The sand body development probability distribution and the average probability of sand body development of all grids in the fusion trend body corresponding to each weighted fusion are statistically analyzed to obtain the influence trend of different weight values ​​on the sand body development probability distribution and the average probability of sand body development.

[0029] According to the first aspect, in a seventh possible implementation of the first aspect, after the step of “according to the porosity data and permeability data in the drilling data, and taking all the different fused trend bodies as modeling constraints, respectively obtaining the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion”, the following steps are specifically included:

[0030] The average porosity of the porosity model of the underwater distributary channel in the study area corresponding to each weighted fusion is calculated, and the average permeability of the permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion is calculated, and the influence trend of different weight values ​​on the average porosity and the average permeability is obtained.

[0031] Secondly, a delta front channel porosity and permeability model system based on spatial trend constraints is provided, including:

[0032] A data acquisition module is used to transmit the drilling data of the underwater distributary channel in the study area to the PETREL modeling software, and to establish a channel facies model based on the drilling data;

[0033] A lateral trend module, which is in communication connection with the data acquisition module, and is used to constrain the channel phase model by using the lateral trend of the channel to establish a lateral trend body of the underwater distributary channel in the study area;

[0034] A vertical trend module, which is in communication with the data acquisition module and is used to establish a vertical trend body of the underwater distributary channel in the study area by using the vertical trend constraints inside the single-period channel in the channel phase model;

[0035] a fusion module, which is in communication with the horizontal trend module and the vertical trend module, and is used to set different weight values ​​for the horizontal trend body and the vertical trend body respectively for multiple times to obtain a fused trend body corresponding to each weighted fusion; and

[0036] The porosity and permeability construction module is communicatively connected with the data acquisition module and the fusion module, and is used to obtain the porosity model and permeability model of the underwater diversion channel in the study area corresponding to each weighted fusion based on the porosity data and permeability data in the drilling data and taking all the different fusion trend bodies as modeling constraints.

[0037] In a third aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the delta front channel porosity and permeability model method based on spatial trend constraints as described above is implemented.

[0038] Compared with the prior art, the advantages of the present invention are as follows: based on the multi-directional trend fusion constraint modeling process, the internal heterogeneity characteristics of underwater distributary channels at different positions in the delta front subphase are characterized, providing a scientific basis for the distribution of remaining oil in the braided river delta front channel phase reservoir and development decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flow chart of a delta front river channel porosity and permeability model method based on directional trend constraints of the present invention;

[0040] Figure 2 The channel facies model with a sand-to-land ratio of 90.5% in the study area established for the present invention;

[0041] Figure 3 It is a schematic diagram of the lateral trend body inside the underwater diversion channel of the present invention;

[0042] Figure 4 It is a schematic diagram of the vertical trend body inside the underwater diversion channel of the present invention;

[0043] Figure 5 It is a schematic diagram of the fusion trend body under different weights established by the present invention;

[0044] Figure 6 It is a schematic diagram of the fusion trend body profile under different weights established by the present invention;

[0045] Figure 7 It is a schematic diagram of the change in probability of sand bodies developed in the same grid position of the lateral trend body, the vertical trend body and the fusion trend body established by the present invention;

[0046] Figure 8 It is a schematic diagram of a porosity model established based on the fusion trend body constraint of the present invention;

[0047] Fig. 9 It is a cross-sectional schematic diagram of a porosity model established based on the fusion trend body constraint of the present invention;

[0048] Fig.10 It is a schematic diagram of a cross-well section of a porosity model established by the fusion trend body constraint with lateral and vertical weights of 0.5 in the present invention;

[0049] Fig.11 It is a schematic diagram of the positive correlation between the porosity data and the permeability data in the study area of ​​the present invention;

[0050] Fig.12 It is a schematic diagram of a permeability model established based on the fusion trend body constraint of the present invention;

[0051] Fig.13 It is a schematic diagram of the probability distribution of sand body development in the fused probability body with different weight values ​​according to the present invention;

[0052] Fig.14 It is a schematic diagram of the influence of different weight values ​​on the average porosity and average permeability in the fused probability body of the present invention. DETAILED DESCRIPTION

[0053] Reference will now be made in detail to specific embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Although the present invention will be described in conjunction with specific embodiments, it will be understood that it is not intended to limit the present invention to the embodiments described. On the contrary, it is intended to cover changes, modifications and equivalents included in the spirit and scope of the present invention as defined by the appended claims. It should be noted that the method steps described herein can all be implemented by any functional block or functional arrangement, and any functional block or functional arrangement can be implemented as a physical entity or a logical entity, or a combination of the two.

[0054] In order to enable those skilled in the art to better understand the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0055] Note: The example to be introduced below is only a specific example, and is not intended to limit the embodiments of the present invention to the following specific steps, values, conditions, data, sequences, etc. Those skilled in the art can apply the concept of the present invention to construct more embodiments not mentioned in this specification by reading this specification.

[0056] See also Figure 1 As shown, an embodiment of the present invention provides a delta front channel porosity and permeability model method based on spatial trend constraints, comprising the following steps:

[0057] S100, transmitting the drilling data of the underwater distributary channel in the study area to the PETREL modeling software, and establishing a channel facies model based on the drilling data;

[0058] S200, using the internal lateral trend constraints of the single-period river channel in the river channel phase model to establish a lateral trend body of the underwater distributary channel in the study area;

[0059] S300, using the internal vertical trend constraint of the single-period river channel in the river channel phase model, establishing a vertical trend body of the underwater distributary channel in the study area;

[0060] S400, setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion;

[0061] S500, based on the porosity data and permeability data in the drilling data, and taking all the different fused trend bodies as modeling constraints, respectively obtain the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion.

[0062] Specifically, in this embodiment, the previous research on the heterogeneity of the braided river delta front reservoir and the distribution law of sand bodies has deepened the understanding of the internal development law of the underwater distributary channel, but in the traditional process of constructing the delta physical property model, sequential indicator simulation, deterministic modeling, combination of deterministic and sequential Gaussian simulation methods, indicative point process and multi-point geostatistical modeling methods are used. The limitations of the above algorithms are reflected in the challenges of finding the centerline and boundary position of the underwater distributary channel, which makes the establishment of the internal trend body of a single-period channel a major difficulty. Usually, in the process of using these algorithms, seismic inversion data, sedimentary forward simulation or two-dimensional plane trend surface constraint model are used, and the model results are affected by the accuracy of the constraint data in characterizing the changing laws of different channels and single-period channels in different directions. Therefore, in view of the above problems, the present invention is based on the multi-directional trend fusion constraint modeling process to characterize the internal heterogeneity characteristics of underwater distributary channels at different positions in the delta front subphase, and provide a scientific basis for the distribution of remaining oil in the braided river delta front channel phase reservoir and development decision-making.

[0063] Preferably, in another embodiment of the present application, the step of "S100, establishing a river channel facies model according to the drilling data" specifically includes the following steps:

[0064] According to the microfacies data of the delta front sedimentary system in the drilling data, the fluvial facies model of the study area was established by using the Fluvsim algorithm.

[0065] Specifically, in this embodiment, the Fluvsim algorithm is a simulation method proposed by Deutsch for building complex river channels, also known as the "target-based simulation method". This modeling method uses the target object as the simulation unit, mainly describes the spatial distribution of various discrete geological features, and can well describe the geometric morphology of the river channel.

[0066] The sand-to-ground ratio data in the microfacies data are obtained based on the well logging interpretation data and core observation data obtained during the underground drilling process of the oil and gas field. The target-based method is used to establish a river channel facies model with a sand-to-ground ratio of 90.5% in the study area, including 90.5% underwater distributary channels and 9.5% inter-channel mud. For details, see Figure 2 As shown. Figure 2 The numbers 1-10 represent the 1st to 10th river channels; 0 is the background mud; and the numbers 22, 20, 18, and 1 represent the well locations.

[0067] Preferably, in another embodiment of the present application, the step of "S200, using the internal lateral trend constraints of the single-period river channel in the river channel phase model to establish a lateral trend body of the underwater distributary channel in the study area" specifically includes the following steps:

[0068] S210, obtaining an initial lateral trend body by using the lateral trend of the single-period channel in the channel phase model, wherein the lateral trend of the channel is defined as a rule that the sand body particle size gradually becomes finer and the physical properties gradually become worse from the center of the channel to both sides;

[0069] S220, normalizing the initial lateral trend body to a lateral trend body of the underwater distributary channel in the study area in the interval [0-1].

[0070] Specifically, in this embodiment, according to geological laws and previous geological research results, it is known that in a single-period river channel, there is a rule that the sand body particle size gradually becomes finer and the physical properties gradually become worse from the center of the river channel to both sides. Based on the above geological knowledge, a probability body that can characterize the lateral trend of the single-period river channel is established.

[0071] In order to constrain the law of physical property changes from the center of the river to both sides, the lateral trend constraint is introduced to establish the lateral trend probability body inside the river. The initial lateral trend body established based on the target algorithm represents the law of gradual changes from the center of the river to both sides, such as Figure 3 a. However, the Fluvsim algorithm is used to characterize the centerline of the river channel, and the center value of the river channel is set to -1, and increases towards the river channel boundary. In order to constrain the physical property trend inside the river channel, the initial lateral trend body is normalized into a model body in the range of 0-1. Figure 3 The initial lateral trend body in a is treated as a lateral trend body whose probability value approaches 1 in the center of the river channel, decreases from the center to the boundary of the sediment body, and approaches 0 at the edge of the river channel, such as Figure 3 As shown in b, this final lateral trend body is used to constrain the distribution law of sand bodies inside the river channel, indicating that the physical properties of the center of the river channel are better and the physical properties of the two sides are worse. Figure 3 The numbers 22, 20, 18, and 1 represent well locations.

[0072] Preferably, in another embodiment of the present application, the step of "S300, using the internal vertical trend constraint of the single-period river channel in the river channel phase model to establish a vertical trend body of the underwater distributary channel in the study area" specifically includes the following steps:

[0073] The initial vertical trend body is obtained by using the vertical trend inside the single-period river channel in the river channel phase model, wherein the vertical trend inside the river channel is defined as the law that the grain size gradually becomes finer and the physical properties gradually become worse from the bottom to the top of the river channel;

[0074] The initial vertical trend body is normalized to the vertical trend body of the underwater distributary channel in the study area in the interval [0-1].

[0075] Specifically, in this embodiment, according to geological laws and previous geological research results, it is known that the river channel generally presents a positive rhythm, and the reservoirs with better physical properties are distributed at the bottom, while the reservoirs with relatively poor physical properties are mostly located in the upper-middle part of the sedimentary cycle. In order to constrain the law of physical property changes from top to bottom in the river channel, a vertical trend constraint is introduced to establish a vertical trend probability body inside the river channel, such as Figure 4 As shown, Figure 4 The numbers 22, 20, 18, and 1 in the figure represent the well locations. The vertical trend describes the distance between each grid and the top of the channel. The distance to the top of the channel is 0, and the distance value increases gradually from the top to the bottom. The distance to the bottom of the channel is 1, which represents the vertical physical property regularity trend inside the channel.

[0076] Preferably, in another embodiment of the present application, the step of "S400, setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion" specifically includes the following steps:

[0077] For the horizontal trend body P ijk Set the weight value α to the vertical trend body V ijk Set the weight value β, then the fusion trend body ω ijk The weighted calculation method is as follows:

[0078] ω ijk =αP ijk +βV ijk ;

[0079] Among them, 0≤α≤1, 0≤β≤1, α+β=1;

[0080] Where i is the east-west grid point position of the trend body; j is the north-south grid point position of the trend body; and k is the vertical grid point position of the trend body.

[0081] Specifically, in this embodiment, the single trend constraint channel phase modeling cannot fully reflect the complex strong heterogeneity characteristics inside the channel. Therefore, considering the geological change law inside the channel, different weights are set for the plane probability body and the vertical probability body, and the probability bodies are fused in a weighted addition manner, and different weight values ​​are given to each grid in the model to reflect the heterogeneity characteristics inside the channel, such as Figure 5-6 shown.

[0082] Assume that α and β represent the relative importance of the horizontal (plane) and vertical directions, and satisfy 0≤α≤1, 0≤β≤1, and α+β=1, then the fusion trend body ω obtained by comprehensive weighting in the two directions is ijk :

[0083] ω ijk =αP ijk +βV ijk, satisfying 0≤ω ijk ≤1.

[0084] Where V is the vertical trend body, such as Figure 5 a,6a, P is a horizontal trend body, such as Figure 5 k, 6k, i is the east-west grid point position of the work area, j is the north-south grid point position of the work area, and k is the vertical grid point position of the work area. Therefore, changing the values ​​of α and β, that is, changing the proportion of the plane and the vertical, can change the comprehensive weight value of any point in the fusion trend body.

[0085] In reservoir geological modeling and even engineering, i, j, and k usually represent unit vectors in three-dimensional space. In layman's terms, i, j, and k are unit vectors parallel to the x, y, and z axes in a three-dimensional rectangular coordinate system. Usually, i represents the unit length to the right of the horizontal axis, j represents the unit length on the vertical axis, and k points to the unit length in the perpendicular direction of the plane formed by the first two. Through these three vectors, the position of a point or object in three-dimensional space can be accurately defined.

[0086] In the process of underground geological modeling of oil and gas fields, the model body established can reach several kilometers to tens of kilometers in the plane and several meters to hundreds of meters in the vertical direction. The spatial grid point information that needs to be counted is too large. Limited by the overall computing power of the computer, the step length of 10-200m is generally set as a single grid plane step length in the plane, and the step length of 0.2-5m is set as a single grid vertical step length in the vertical direction. Then the grid corresponding to an ijk in space is a cube shape. However, the accuracy of the grid step length depends on the size of the modeling area and the enrichment of geological data.

[0087] In particular, when α = 0, β = 1, the comprehensive weight is the vertical weight, and the established sandstone three-dimensional probability volume is as follows: Figure 5 a, the cross section of the river channel is shown in 6a. With a step size of 0.1, the plane weight is gradually increased and the vertical weight is reduced to obtain different fused trend bodies. When α = 0.1 and β = 0.9, the sandstone probability body established by trend body fusion is as follows: Figure 5 b, and the channel section is shown in 6b. When α = 0.2, β = 0.8, the sandstone probability volume established by trend volume fusion is shown in Figure 5 c, and the channel section is shown in 6c. When α = 0.3, β = 0.7, the sandstone probability body established by trend body fusion is shown in Figure 5 d, and the channel section is shown in 6d. When α = 0.4, β = 0.6, the sandstone probability volume established by trend fusion is as follows Figure 5 e, and the channel section is shown in 6e. When α = 0.5, β = 0.5, the sandstone probability volume established by trend volume fusion is shown in Figure 5f, and the channel section is shown in 6f. When α = 0.6, β = 0.4, the sandstone probability volume established by trend volume fusion is shown in Figure 5 g, and the channel section is shown in 6g. When α = 0.7, β = 0.3, the sandstone probability volume established by trend volume fusion is shown in Figure 5 h, and the channel section is shown in 6h. When α = 0.8, β = 0.2, the sandstone probability body established by trend body fusion is shown in Figure 5 i, and the channel section is shown in 6i. When α = 0.9, β = 0.1, the sandstone probability body established by trend body fusion is shown in Figure 5 When α = 1, β = 0, the comprehensive weight is the horizontal (plane) weight, and the sandstone probability volume established is Figure 5 k, and the channel section is shown in 6k. It is worth noting that this embodiment provides the probability value changes of the development of sand bodies in the horizontal trend body, the vertical trend body and the fusion trend body at the same grid position when α=0.4 and β=0.6, as shown in Figure 7 shown.

[0088] Preferably, in another embodiment of the present application, the step of "S500, according to the porosity data and permeability data in the drilling data, and taking all the different fusion trend bodies as modeling constraints, respectively obtaining the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion" specifically includes the following steps:

[0089] S510, based on the porosity data in the drilling data and taking all the different fused trend bodies as modeling constraints, a porosity model of the underwater distributary channel in the study area corresponding to each weighted fusion is established using a sequential Gaussian simulation method;

[0090] S520, based on the positive correlation between the porosity data and the permeability data in the drilling data, and taking all the different fused trend bodies and the porosity models as modeling constraints, a sequential Gaussian simulation method is used to establish a permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion.

[0091] Specifically, in this embodiment, the porosity data in the well condition data is used as hard data, and the physical property model is established by combining deterministic and stochastic modeling through phase control constraints. Mudstone is developed in the inter-channel phase, which is a non-oil and gas reservoir. The deterministic modeling method is used to simulate the inter-channel phase, and the porosity values ​​of the inter-channel phase are set to 0. For the underwater distributary channel phase of the dominant reservoir, Figure 5 The sandstone probability volume after fusion of different weights is used as trend constraint, and the porosity model is established by using the sequential Gaussian simulation method under phase control, such as Figure 8-9 shown.

[0092] When the vertical weight value is 1, the grid at the bottom of the river channel presents a higher porosity value, and the porosity value gradually decreases from bottom to top ( Figure 8 a, 9a). As the plane weight increases, the porosity of different layers begins to decrease from the middle of the river channel to the edge in both the plane and the section ( Figure 8-9 The fused sandstone probability body has both vertical development rules and planar distribution characteristics ( Figure 8 b-8j, 9b-9j). For channels under different periods or depositional conditions, the influence of factors such as sediment supply, water flow intensity, and channel curvature leads to differences in the heterogeneity of sand bodies in channels of different periods. Therefore, according to the actual development law and geological characteristics of underwater distributary channels at different positions of the delta front reservoir, the probability bodies of sandstones in different directions can be quantitatively characterized and fused, thereby constraining the physical property modeling process. In the underwater distributary channels in the study area, a fusion trend body with lateral and vertical weights of 0.5 and 0.5, respectively, was selected ( Figure 8 f, 9f) constrain the porosity modeling process, and the model results can simulate the internal rhythm and physical property change characteristics of a single-period river channel. The physical properties of the river channel bottom are better than those of the top, and the physical properties of the river channel center are better than those of the two sides. Fig.10 shown.

[0093] Using the same method as the above porosity model, based on the fusion trend body constraint modeling process under different weights, the positive correlation between porosity and permeability in the study area is studied, such as Fig.11 As shown in the figure, the porosity model is used to establish the permeability model of the study area. The simulation results are shown in Fig.12 shown.

[0094] Preferably, in another embodiment of the present application, after the step of "S400, setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion", the following steps are specifically included:

[0095] The sand body development probability distribution and the average probability of sand body development of all grids in the fusion trend body corresponding to each weighted fusion are statistically analyzed to obtain the influence trend of different weight values ​​on the sand body development probability distribution and the average probability of sand body development.

[0096] Specifically, in this embodiment, different lateral and vertical weight values ​​have an impact on the probability body value range, as shown in Table 1.

[0097] Table 1

[0098]

[0099] The step size of weight increase or decrease is set to 0.1. When the plane weight value is 0 and the vertical weight value is 1, the corresponding fusion probability volume interval is 2%-92%, which means that the probability of sand body development of all grids in the underwater distributary channel is between 2%-92%, and the average probability of sand body development of grids in the underwater distributary channel is 36%. When the plane weight value is 0.1 and the vertical weight value is 0.9, the corresponding fusion probability volume interval is 2%-93%, which means that the probability of sand body development of all grids in the underwater distributary channel is between 2%-93%, and the average probability of sand body development of grids in the underwater distributary channel is 38%. When the plane weight value is 0.2 and the vertical weight value is 0.8, the corresponding fusion probability volume interval is 2%-93%, which means that the probability of sand body development of all grids in the underwater distributary channel is between 2%-93%, and the average probability of sand body development of grids in the underwater distributary channel is 40%. When the plane weight value is 0.3 and the vertical weight value is 0.7, the corresponding fusion probability volume interval is 1%-94%, which means that the probability of sand body development in all grids inside the underwater distributary channel is between 1%-94%, and the average probability of sand body development in the grids inside the underwater distributary channel is 42%. When the plane weight value is 0.4 and the vertical weight value is 0.6, the corresponding fusion probability volume interval is 1%-95%, which means that the probability of sand body development in all grids inside the underwater distributary channel is between 1%-95%, and the average probability of sand body development in the grids inside the underwater distributary channel is 44%. When the plane weight value is 0.5 and the vertical weight value is 0.5, the corresponding fusion probability volume interval is 1%-96%, which means that the probability of sand body development in all grids inside the underwater distributary channel is between 1%-96%, and the average probability of sand body development in the grids inside the underwater distributary channel is 45%. When the plane weight value is 0.6 and the vertical weight value is 0.4, the corresponding fusion probability volume interval is 1%-97%, which means that the probability of sand body development in all grids inside the underwater distributary channel is between 1%-97%, and the average probability of sand body development in the grids inside the underwater distributary channel is 47%. When the plane weight value is 0.7 and the vertical weight value is 0.3, the corresponding fusion probability volume interval is 1%-98%, which means that the probability of sand body development in all grids inside the underwater distributary channel is between 1%-98%, and the average probability of sand body development in the grids inside the underwater distributary channel is 49%. When the plane weight value is 0.8 and the vertical weight value is 0.2, the corresponding fusion probability volume interval is 0-98%, which means that the probability of sand body development in all grids inside the underwater distributary channel is between 0-98%, and the average probability of sand body development in the grids inside the underwater distributary channel is 51%. When the plane weight value is 0.9 and the vertical weight value is 0.1, the corresponding fusion probability volume interval is 0-95%, which means that the probability distribution of sand body development in all grids inside the underwater distributary channel is between 0-95%, and the average probability of sand body development in the grids inside the underwater distributary channel is 53%.When the plane weight value is 1 and the vertical weight value is 0, the corresponding fusion probability range is 0-100%, which means that the probability distribution of sand body development in all grids inside the underwater distributary channel is between 0-100%, and the average probability of sand body development in the grid inside the underwater distributary channel is 55%, as shown in Table 2. In general, with the increase of plane weight value and the decrease of vertical weight value, the overall probability value and probability range of sand body development in the channel gradually increase, and the average probability value also increases with the increase of plane weight, such as. Fig.13 shown.

[0100] Preferably, in another embodiment of the present application, after the step of "S500, according to the porosity data and permeability data in the drilling data, and taking all the different fusion trend bodies as modeling constraints, respectively obtaining the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion", the following steps are specifically included:

[0101] The average porosity of the porosity model of the underwater distributary channel in the study area corresponding to each weighted fusion is calculated, and the average permeability of the permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion is calculated, and the influence trend of different weight values ​​on the average porosity and the average permeability is obtained.

[0102] Specifically, in this embodiment, Figure 8 The porosity models with different weights in each (a total of 11 porosity models) are averaged to obtain Fig.14 Similarly, for Fig.12 The permeability models with different weights in the formula (11 permeability models in total) are averaged to obtain Fig.14 11 average permeabilities in the model. Due to the change of weights in different directions, the average porosity and average permeability of the model generally show an increasing trend, but it is not a linear relationship. This also shows that the average porosity and permeability values ​​inside the river channel are affected by the weights, but they are not the only controlling factors. In the same delta front subphase, affected by the sedimentary environment and hydrodynamic conditions, the internal physical property ranges of underwater distributary channels at different locations are different, and the degree of influence controlled by the plane or vertical direction is also different. It is worth noting that rivers with smaller curvatures such as underwater distributary channels are generally mainly controlled by vertical trends, but for meandering channels with higher curvatures, they are mainly controlled by plane trends during the river scouring stage.

[0103] The embodiment of the present invention further provides a delta front channel porosity and permeability model system based on spatial trend constraints, comprising:

[0104] A data acquisition module is used to transmit the drilling data of the underwater distributary channel in the study area to the PETREL modeling software, and to establish a channel facies model based on the drilling data;

[0105] A lateral trend module, which is in communication connection with the data acquisition module, is used to establish a lateral trend body of the underwater distributary channel in the study area by using the internal lateral trend constraints of the single-period river channel in the river channel phase model;

[0106] A vertical trend module, which is in communication with the data acquisition module and is used to establish a vertical trend body of the underwater distributary channel in the study area by using the vertical trend constraints inside the single-period channel in the channel phase model;

[0107] a fusion module, which is in communication with the horizontal trend module and the vertical trend module, and is used to set different weight values ​​for the horizontal trend body and the vertical trend body respectively for multiple times to obtain a fused trend body corresponding to each weighted fusion; and

[0108] The porosity and permeability construction module is communicatively connected with the data acquisition module and the fusion module, and is used to obtain the porosity model and permeability model of the underwater diversion channel in the study area corresponding to each weighted fusion based on the porosity data and permeability data in the drilling data and taking all the different fusion trend bodies as modeling constraints.

[0109] Previous studies on the heterogeneity of braided river delta front reservoirs and the distribution of sand bodies have deepened the understanding of the development laws of underwater distributary channels. However, in the traditional process of constructing delta physical property models, sequential indicator simulation, deterministic modeling, a combination of deterministic and sequential Gaussian simulation methods, indicative point processes, and multi-point geostatistical modeling methods are used. The limitations of the above algorithms are reflected in the challenges of finding the centerline and boundary positions of underwater distributary channels, which makes it difficult to establish a trend body inside a single-period channel. Usually, in the process of using these algorithms, seismic inversion data, sedimentary forward simulation, or two-dimensional plane trend surface constraint models are used. The model results are affected by the accuracy of the constraint data in characterizing the changing laws of different channels and single-period channels in different directions. Therefore, in response to the above problems, the present invention characterizes the internal heterogeneity characteristics of underwater distributary channels at different positions in the delta front subphase based on the multi-directional trend fusion constraint modeling process, and provides a scientific basis for the distribution of remaining oil in the braided river delta front channel phase reservoir and development decisions.

[0110] Specifically, this embodiment corresponds one-to-one to the above method embodiment, and the functions of each module have been described in detail in the corresponding method embodiment, so they will not be repeated here.

[0111] Based on the same inventive concept, an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, all or part of the method steps of the above method are implemented.

[0112] The present invention implements all or part of the process in the above method, and can also be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0113] Based on the same inventive concept, an embodiment of the present application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program running on the processor, and when the processor executes the computer program, all or part of the method steps in the above method are implemented.

[0114] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of a computer device, and uses various interfaces and lines to connect various parts of the entire computer device.

[0115] The memory can be used to store computer programs and / or modules. The processor realizes various functions of the computer device by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required for a function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, video data, etc.). In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0116] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, servers or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention 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 and optical storage, etc.) containing computer-usable program codes.

[0117] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), servers, and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as a combination of processes and / or blocks 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 produce 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.

[0118] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0120] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A delta front channel porosity model method based on spatial trend constraints, characterized in that: The following steps are involved: The drilling data of the underwater distributary channel in the study area were transferred to the PETREL modeling software, and the channel facies model was established based on the drilling data; By using the internal lateral trend constraints of the single-period river channel in the river channel facies model, the lateral trend body of the underwater distributary channel in the study area is established; By using the vertical trend constraints inside the single-period channel in the channel phase model, the vertical trend body of the underwater distributary channel in the study area is established; Setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion; According to the porosity data and permeability data in the drilling data, and taking all the different fused trend bodies as modeling constraints, the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion are obtained respectively; The step of "using the internal lateral trend constraints of the single-period river channel in the river channel phase model to establish the lateral trend body of the underwater distributary channel in the study area" specifically includes the following steps: An initial lateral trend body is obtained by using the lateral trend inside the single-period river channel in the river channel phase model, wherein the lateral trend inside the river channel is defined as a rule that the grain size of the sand body gradually becomes finer and the physical properties gradually become worse from the center of the river channel to both sides; Normalizing the initial lateral trend body to a lateral trend body of the underwater distributary channel in the study area in the interval [0, 1]; The step of "using the internal vertical trend constraints of the single-period river channel in the river channel phase model to establish the vertical trend body of the underwater distributary channel in the study area" specifically includes the following steps: The initial vertical trend body is obtained by using the vertical trend inside the single-period river channel in the river channel phase model, wherein the vertical trend inside the river channel is defined as the law that the grain size gradually becomes finer and the physical properties gradually become worse from the bottom to the top of the river channel; The initial vertical trend body is normalized to a vertical trend body of the underwater distributary channel in the study area in the interval [0, 1].

2. The delta front river channel porosity and permeability model method based on spatial trend constraints according to claim 1 is characterized in that: The step of "establishing a river channel facies model according to the drilling data" specifically includes the following steps: According to the microfacies data of the delta front sedimentary system in the drilling data, the fluvial facies model of the study area was established by using the Fluvsim algorithm.

3. The delta front river channel porosity and permeability model method based on spatial trend constraints according to claim 1, characterized in that: The step of "setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion" specifically includes the following steps: For the horizontal trend body P ijk Set the weight value α to the vertical trend body V ijk Set the weight value β, then the fusion trend body ω ijk The weighted calculation method is as follows: oh ijk =αP ijk +βV ijk ; Where, 0≤α≤1, 0≤β≤1, α+β=1, 0≤ω ijk ≤1; Where i is the east-west grid point position of the trend body; j is the north-south grid point position of the trend body; and k is the vertical grid point position of the trend body.

4. The delta front river channel porosity and permeability model method based on spatial trend constraints according to claim 1, characterized in that: The step of "obtaining the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion based on the porosity data and permeability data in the drilling data and taking all the different fusion trend bodies as modeling constraints" specifically includes the following steps: According to the porosity data in the drilling data, and taking all the different fused trend bodies as modeling constraints, a sequential Gaussian simulation method is used to establish a porosity model of the underwater distributary channel in the study area corresponding to each weighted fusion; According to the positive correlation between the porosity data and the permeability data in the drilling data, and taking all the different fused trend bodies and the porosity models as modeling constraints, a sequential Gaussian simulation method is used to establish the permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion.

5. The delta front channel porosity and permeability model method based on spatial trend constraints according to claim 1, characterized in that: After the step of "setting different weight values ​​for the horizontal trend body and the vertical trend body for multiple times to obtain a fused trend body corresponding to each weighted fusion", the following steps are specifically included: The sand body development probability distribution and the average probability of sand body development of all grids in the fusion trend body corresponding to each weighted fusion are statistically analyzed to obtain the influence trend of different weight values ​​on the sand body development probability distribution and the average probability of sand body development.

6. The delta front channel porosity and permeability model method based on spatial trend constraints according to claim 1, characterized in that: After the step of "according to the porosity data and permeability data in the drilling data, and taking all the different fusion trend bodies as modeling constraints, respectively obtaining the porosity model and permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion", the following steps are specifically included: The average porosity of the porosity model of the underwater distributary channel in the study area corresponding to each weighted fusion is calculated, and the average permeability of the permeability model of the underwater distributary channel in the study area corresponding to each weighted fusion is calculated, and the influence trend of different weight values ​​on the average porosity and the average permeability is obtained.

7. A delta front channel porosity and permeability model system based on spatial trend constraints, characterized in that: include: A data acquisition module is used to transmit the drilling data of the underwater distributary channel in the study area to the PETREL modeling software, and to establish a channel facies model based on the drilling data; A lateral trend module, which is in communication connection with the data acquisition module, is used to establish a lateral trend body of the underwater distributary channel in the study area by using the internal lateral trend constraints of the single-period river channel in the river channel phase model; A vertical trend module, which is in communication with the data acquisition module and is used to establish a vertical trend body of the underwater distributary channel in the study area by using the vertical trend constraints inside the single-period channel in the channel phase model; A fusion module, which is in communication with the horizontal trend module and the vertical trend module, and is used to set different weight values ​​for the horizontal trend body and the vertical trend body respectively for multiple times to obtain a fused trend body corresponding to each weighted fusion; as well as, A porosity and permeability construction module, which is in communication with the data acquisition module and the fusion module, is used to obtain the porosity model and permeability model of the underwater diversion channel in the study area corresponding to each weighted fusion based on the porosity data and permeability data in the drilling data and taking all the different fusion trend bodies as modeling constraints; The delta front river channel porosity and permeability model system based on spatial trend constraints implements the delta front river channel porosity and permeability model method based on spatial trend constraints as claimed in claim 1.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the delta front channel porosity and permeability model method based on spatial trend constraints is implemented as claimed in any one of claims 1 to 6.

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