Point sand dam distribution prediction method, device and equipment and storage medium

Abstract

The invention discloses a point sand dam distribution prediction method and device, electronic equipment and a storage medium. The method comprises the following steps: determining riverbed distribution information of a meandering river in a target area; according to the riverbed distribution information, determining the riverway distribution information of each stage of the meandering river of the target area; according to the river channel distribution information, determining river channel evolution process information of the meandering river in the target area; point sand dam distribution information of the meandering river of the target area is determined according to the river channel distribution information and the river channel evolution process information, and the point sand dam distribution information represents the distribution range of point sand dams in the three-dimensional space. According to the technical scheme, the riverbed distribution information of the meandering river in the target area is sequentially determined through step-by-step constraint, then the riverway distribution information is determined according to the riverbed distribution information, the riverway evolution process information is determined according to the riverway distribution information, and finally the point sand dam distribution information is determined according to the riverway distribution information and the riverway evolution process information. And point sand dam distribution prediction of the target area is realized.

Description

Technical Field

[0001] This invention relates to the field of sedimentary sand body prediction technology, and in particular to a method, apparatus, equipment and storage medium for predicting the distribution of point sand dams. Background Technology

[0002] Point bars are favorable oil and gas reservoirs, and the distribution of high-quality reservoirs determines subsequent well placement. Point bar reservoirs in meandering rivers constitute a large proportion of major oilfields, and accurately predicting the distribution of point bar reservoirs in meandering rivers plays a crucial role in oil and gas exploration and development.

[0003] In recent years, there has been considerable research on the reservoir architecture of point bar in meandering rivers using drilling data, but less research on the sedimentary evolution of restricted meandering rivers and point bars in underground history. Existing technical solutions rely on point bar prediction models that directly define the boundary range of point bars, making it difficult to accurately identify and characterize their distribution. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and storage medium for predicting the distribution of point sand dams in a target area.

[0005] In a first aspect, embodiments of the present invention provide a method for predicting the distribution of point sand dams, the method comprising:

[0006] Determine the riverbed distribution information of the meandering river in the target area; the riverbed distribution information represents the distribution range of the riverbed in three-dimensional space;

[0007] Based on the riverbed distribution information, the channel distribution information of the meandering river in the target area for each period is determined; the channel distribution information represents the distribution range of the river in three-dimensional space.

[0008] Based on the river channel distribution information, the river channel evolution process information of the meandering river in the target area is determined; the river channel evolution process information includes the distribution range of the river channel in three-dimensional space at different stages over time;

[0009] Based on the river channel distribution information and river channel evolution information, the distribution information of point sandbars in the meandering river of the target area is determined. The point sandbar distribution information represents the distribution range of point sandbars in three-dimensional space.

[0010] Secondly, embodiments of the present invention also provide a point sand dam distribution prediction device, the device comprising:

[0011] The riverbed distribution determination module is used to determine the riverbed distribution information of the meandering river in the target area; the riverbed distribution information represents the distribution range of the riverbed in three-dimensional space.

[0012] The river channel distribution determination module is used to determine the river channel distribution information of the meandering river in the target area at different stages based on the riverbed distribution information; the river channel distribution information represents the distribution range of the river channel in three-dimensional space.

[0013] The river evolution process determination module is used to determine the river evolution process information of the meandering river in the target area based on the river distribution information; the river evolution process information includes the distribution range of the river at different stages in three-dimensional space over time;

[0014] The point sandbar distribution determination module is used to determine the point sandbar distribution information of the meandering river in the target area based on the river channel distribution information and river channel evolution process information. The point sandbar distribution information represents the distribution range of point sandbars in three-dimensional space.

[0015] Thirdly, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the point sand dam distribution prediction method as described in any of the embodiments of the present invention.

[0016] Fourthly, embodiments of the present invention also provide a storage medium for storing computer-executable instructions, which, when executed by a computer processor, are used to perform the point sandbar distribution prediction method as described in any of the embodiments of the present invention.

[0017] The technical solution of this invention determines the riverbed distribution information of the meandering river in the target area through hierarchical constraints, then determines the channel distribution information based on the riverbed distribution information, determines the channel evolution process information based on the channel distribution information, and finally determines the point sandbar distribution information based on the channel distribution information and the channel evolution process information, thereby achieving the prediction of the point sandbar distribution in the target area.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a point sand dam distribution prediction method provided in Embodiment 1 of the present invention;

[0021] Figure 2 This is a schematic diagram of drilling data and seismic profile data provided in Embodiment 1 of the present invention;

[0022] Figure 3 This is a schematic diagram of a three-dimensional seismic amplitude attribute plane provided in Embodiment 1 of the present invention;

[0023] Figure 4 This is a schematic diagram of an isochronous stratigraphic slice of three-dimensional seismic data provided in Embodiment 1 of the present invention;

[0024] Figure 5 This is a three-dimensional perspective view of a river channel evolution process and point sandbar formation process provided in Embodiment 1 of the present invention;

[0025] Figure 6 This is a schematic diagram of the planar distribution of a meandering river channel and point sandbars provided in Embodiment 1 of the present invention;

[0026] Figure 7 This is a flowchart of a point sand dam distribution prediction method provided in Embodiment 2 of the present invention;

[0027] Figure 8 This is a schematic diagram of a three-dimensional coherence property plane provided in Embodiment 2 of the present invention;

[0028] Figure 9 This is a schematic diagram of the structure of a point sand dam distribution prediction device provided in Embodiment 3 of the present invention;

[0029] Figure 10 This is a schematic diagram of the structure of an electronic device for implementing the point sand dam distribution prediction method of this invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Example 1

[0033] Figure 1 The flowchart of a point sand dam distribution prediction method is provided in Embodiment 1 of the present invention. This embodiment is applicable to point sand dam distribution prediction. The method can be executed by a point sand dam distribution prediction device, which can be implemented in hardware and / or software. The point sand dam distribution prediction device can be configured in any electronic device with network communication and computing capabilities.

[0034] like Figure 1 As shown, the point sand dam distribution prediction methods include:

[0035] S110. Determine the riverbed distribution information of the meandering river in the target area; the riverbed distribution information represents the distribution range of the riverbed in three-dimensional space.

[0036] In this embodiment, the method primarily targets the prediction of point bar distribution in restricted meandering rivers during underground historical periods. The target area represents a region containing one or more restricted meandering rivers. These rivers are typically single-channel, with gentle slopes, relatively stable course, and strong meandering. The flow of these meandering rivers is stable, and the transport mechanism is mainly suspended loading and mixed loading, resulting in finer sediments, generally consisting of mud and sand. Continuous lateral accretion of sediments eventually forms point bars on the convex bank. Point bars are the result of lateral migration of the riverbed and lateral sediment accretion, and represent the main sedimentary units and reservoirs in meandering river deposits.

[0037] Riverbed distribution information indicates the range or shape of the riverbed in three-dimensional space, including the riverbed's location in the target area, riverbed width, riverbed length, and riverbed area.

[0038] Due to the constraint of the low-sincerity riverbed, the meandering river has a distinct bottom scour surface, resulting in strong channel downcutting and relatively weak lateral oscillation. The channel oscillation is limited by the riverbed, and the river exhibits a strip-like distribution. The core samples primarily show parallel bedding and wedge-shaped cross-bedding, exhibiting bedding characteristics of point bars. Furthermore, multiple channels within the riverbed oscillate back and forth, forming multiple phases of point bars, which are stacked and connected in plan view.

[0039] To determine the distribution range of point bar formations resulting from the migration and evolution of a restrictive meandering river, the riverbed distribution must first be determined. Therefore, the technical solution of this application first determines the riverbed distribution information of the meandering river in the target area, providing data support for subsequent determination of the river channel distribution information, river channel evolution process information, and point bar distribution information, thereby improving the accuracy of point bar distribution prediction.

[0040] As an optional but not limited implementation method, determining the riverbed distribution information of the meandering river in the target area includes the following steps A1-A2:

[0041] Step A1: Determine the seismic reflection characteristics of the meandering riverbed in the target area. The seismic reflection characteristics of the riverbed are relatively small among the candidate amplitudes within a limited range and relatively weak continuity among the seismic in-phase axes within a limited range.

[0042] Step A2: Based on the seismic reflection characteristics of the riverbed, determine the riverbed distribution information of the meandering river in the target area.

[0043] In this embodiment, the riverbed seismic reflection characteristics represent the reflection characteristics of the riverbed on the seismic profile. Due to the influence of the river channel downcutting, the riverbed exhibits weak amplitude and poor continuity wave trough reflection characteristics on the seismic profile. That is, the riverbed seismic reflection characteristics are relatively small among the candidate amplitudes within a limited range and relatively poor continuity among the seismic in-phase axes within a limited range.

[0044] Specifically, in this embodiment, the seismic profile is precisely calibrated using drilling data, which allows for the identification of areas on the seismic profile that correspond to the seismic reflection characteristics of the riverbed.

[0045] See Figure 2 The diagram shows a composite bar chart of drilling data and seismic profile data. The left side shows the overall histogram of drilling data, with the blue dashed lines marking the locations of riverbeds, channels, and point sandbars on the wells. The right side shows the seismic profile chart derived from the drilling data, with the blue dashed lines reflecting the seismic reflection characteristics of the riverbed. Figure 2 As can be seen from the data, the riverbed exhibits seismic reflection characteristics with weak amplitude and poor continuity on the seismic profile, that is, it is relatively small among the candidate amplitudes within a limited range and has relatively poor continuity among the seismic phase axes within a limited range.

[0046] Specifically, based on the established seismic reflection characteristics of the riverbed and real-time measured seismic data, the riverbed distribution information of the meandering river in the target area can be determined.

[0047] As an optional but not limited implementation, the riverbed distribution information of the meandering river in the target area is determined based on the seismic reflection characteristics of the riverbed, including steps B1-B2:

[0048] Step B1: Extract the along-layer amplitude attributes of the target layer based on the seismic reflection characteristics of the riverbed.

[0049] Step B2: Interpret the along-layer amplitude attributes using the seismic attribute interpretation method to determine the riverbed distribution information of the meandering river in the target area.

[0050] In this embodiment, the amplitude properties along the layer include average amplitude, maximum amplitude, amplitude change rate, and other properties.

[0051] Specifically, three-dimensional seismic data of the target area is acquired. Based on the seismic reflection characteristics of the riverbed, combined with drilling data and seismic profiles, the target layer containing the riverbed on the seismic profile is determined. The attribute extraction method is used to extract the along-layer amplitude attributes of the target layer in the three-dimensional seismic data.

[0052] In practical applications, the riverbed exhibits a weak-amplitude, poorly continuous wave trough reflection on seismic profiles, while the sides of the riverbed show a strong-amplitude, well-continuous wave trough reflection. The seismic reflection characteristics differ significantly, and the amplitude attributes of the riverbed area differ from those of the surrounding strata. Therefore, the along-layer amplitude attributes of the target layer in 2D or 3D seismic data can be extracted based on the riverbed's seismic reflection characteristics. These extracted along-layer amplitude attributes can then be interpreted using seismic attribute interpretation methods to determine the specific distribution and extent of the riverbed, i.e., the riverbed distribution information.

[0053] See Figure 3 The image shows a three-dimensional planar schematic diagram of seismic amplitude attributes. The yellow solid line represents the boundary of the riverbed. Figure 3 The information can clearly reflect the riverbed distribution.

[0054] S120. Based on the riverbed distribution information, determine the channel distribution information of the meandering river in the target area for each period; the channel distribution information represents the distribution range of the river in three-dimensional space.

[0055] In this embodiment, the river distribution information represents the distribution range or shape of the river in three-dimensional space, including the river's location in the target area, river direction, river width, and river curvature.

[0056] It should be noted that, due to the constraints of the low-sincerity riverbed, the channel incision is strong, and the lateral swinging capacity is relatively weak. The channel swinging is limited by the riverbed, resulting in an overall strip-like distribution. Therefore, the channel distribution range is within the riverbed distribution range. Based on the riverbed distribution information, determining the channel distribution information of the meandering river in the target area at different stages can effectively narrow down the range of the determined channel distribution.

[0057] S130. Based on the river channel distribution information, determine the river channel evolution process information of the meandering river in the target area; the river channel evolution process information includes the distribution range of the river channel in three-dimensional space at different stages over time.

[0058] In this embodiment, the river evolution process information represents the migration direction and evolution pattern of the river over time, including the distribution range of the river in three-dimensional space from the early to the late stages.

[0059] Specifically, based on the established information on river channel distribution at different times, we can analyze the migration direction and evolution patterns of the river channels.

[0060] As an optional but not limited implementation, based on the river channel distribution information, the river channel evolution process information of the meandering river in the target area is determined, including steps C1-C3:

[0061] Step C1: Determine the three-dimensional seismic coherence volume of the target area.

[0062] Step C2: Process the three-dimensional seismic coherence volume to create isochronous stratigraphic slices.

[0063] Step C3: Based on the isochronous stratigraphic slices and channel distribution information, determine the channel evolution process information of the target meandering river.

[0064] In this embodiment, the three-dimensional seismic coherence volume is a dataset that reflects the continuity and discontinuity of underground geological structures. In the three-dimensional seismic coherence volume, high coherence regions usually represent areas with good continuity of underground geological structures, while low coherence regions usually represent areas with discontinuity of underground geological structures, such as faults, fractures, and lithological changes.

[0065] Specifically, the 3D seismic coherence volume is obtained by performing coherence calculations on 3D seismic data. The coherence calculation uses a cross-correlation algorithm or a similarity algorithm. By comparing the seismic signals between adjacent seismic traces, the coherence values ​​between the 3D seismic data are calculated, and these coherence values ​​are combined into a 3D dataset, namely the 3D seismic coherence volume.

[0066] In practical applications, based on the three-dimensional seismic coherence volume, isochronous stratigraphic slices are made from the seismic phase axis from bottom to top. The isochronous stratigraphic slices and river channel distribution information can reflect the longitudinal migration direction and evolution process of the river channel.

[0067] See Figure 4 The image shows a schematic diagram of isochronous stratigraphic slices of a set of 3D seismic data. Specifically, four stratigraphic slices were created from bottom to top. Slice 1 reflects the initial rudimentary river channel, which gradually became more meandering and developed through multiple stages. Slice 2 inherits the evolutionary characteristics of the early river channel, with increased meandering. Slice 3 reflects the cutting and straightening of the river channel over time. Slice 4 reflects the abandonment of the original river channel, forming a late-stage oxbow lake.

[0068] S140. Based on the river channel distribution information and river channel evolution process information, determine the point sandbar distribution information of the meandering river in the target area, wherein the point sandbar distribution information represents the distribution range of point sandbars in three-dimensional space.

[0069] In this embodiment, the point sand dam distribution information represents the distribution range or distribution pattern of point sand dams in three-dimensional space, including the distribution location of point sand dams in the target area, the shape of point sand dams, and the number of point sand dams.

[0070] It should be noted that during the evolution of meandering rivers, the river water is influenced by various factors such as topography and flow velocity, forming an asymmetrical lateral circulation system. This circulation system causes the river water to continuously erode the riverbed on the concave bank (the inner side of the meander), while the eroded sediments are deposited on the convex bank (the outer side of the meander). Over time, this lateral erosion and deposition accumulate, and the sediment on the convex bank gradually thickens, forming the rudiments of a point bar. With the action of periodic floods, lateral deposition continues, the meandering of the river channel increases, and the point bar gradually develops and grows, forming a single-point bar.

[0071] Therefore, based on the information on river channel distribution, river channel evolution process, and the causes of point sandbar formation, the location and distribution of point sandbar formation can be determined, that is, the distribution information of point sandbars in the meandering river of the target area.

[0072] See Figure 5 The diagram shows a three-dimensional perspective view of the river channel, illustrating its evolution and the formation of point bar formation. The red line represents the first stage of the river channel, which is meandering. The green line represents the second stage, where the meandering increases. The blue line represents the third stage, where the meandering continues to increase. The yellow area represents point bars formed by the erosion of the convex bank and the deposition of sediment on the concave bank due to the river's migration and evolution.

[0073] As an optional but not limited implementation, the distribution information of point sandbars in the meandering river of the target area is determined based on the river channel distribution information and river channel evolution process information, including steps D1-D2:

[0074] Step D1: Based on the river channel distribution information and river channel evolution information, determine the candidate convex bank locations of the meandering river channel.

[0075] Step D2: Select a reference area at the candidate convex bank location that matches the seismic reflection characteristics of the point sandbar as the distribution information of the point sandbar. The seismic reflection characteristics of the point sandbar are the maximum amplitude among all candidate amplitudes within a limited range and relatively strong continuity among all candidate seismic phase axes within a limited range.

[0076] In this embodiment, the candidate convex bank position represents the convex bank position of the river channel distribution pattern.

[0077] It should be noted that, based on the formation mechanism of point bar, point bars typically form at bends in meandering rivers. When a river flows through a bend, the inertia of the water flow causes the outer flow velocity to be faster, eroding the concave bank of the river channel, while the inner flow velocity is slower, causing sediment to accumulate on the convex bank, gradually forming a point bar. Therefore, point bars are highly likely to form on the convex bank of a river channel.

[0078] Therefore, based on the information on river channel distribution and river evolution, the candidate convex bank locations of the meandering river are determined, and the areas on the candidate convex bank locations that match the seismic reflection characteristics of point sandbars are further identified as reference areas for the distribution of point sandbars, serving as information on the distribution of point sandbars.

[0079] It should be noted that point sandbars exhibit strong amplitude and good continuity reflection characteristics on seismic profiles. That is, the seismic reflection characteristics of point sandbars are the maximum amplitude among all candidate amplitudes within a finite range and relatively strong continuity among all candidate seismic phase axes within a finite range.

[0080] Furthermore, point sandbars are identified based on the location of the convex bank of the river channel and the seismic reflection characteristics of the point sandbars in the three-dimensional seismic data. The distribution location of point sandbars is then predicted based on the information on the evolution process of the point sandbars.

[0081] In addition, point sand dams can be identified on the logging curves of a single well by analyzing their characteristics. Specifically, point sand dams are characterized by low GR (Gamma Ray Logging) and low SP (Spontaneous Potential Logging) values ​​on the logging curves, and their shapes are box-shaped and bell-shaped.

[0082] See Figure 6The diagram shows the planar distribution of the meandering river channel and point sandbars. The orange area represents the distribution information of point sandbars, including the distribution range, shape, and number of point sandbars. The light blue line represents the distribution information of the river channel, including the distribution range, length, and shape.

[0083] The technical solution of this invention determines the riverbed distribution information of the meandering river in the target area through hierarchical constraints, then determines the channel distribution information based on the riverbed distribution information, determines the channel evolution process information based on the channel distribution information, and finally determines the point sandbar distribution information based on the channel distribution information and the channel evolution process information, thereby achieving the prediction of the point sandbar distribution in the target area.

[0084] Example 2

[0085] Figure 7 This is a flowchart of a point sand dam distribution prediction method provided in Embodiment 2 of the present invention. This embodiment is applicable to point sand dam distribution prediction. The method can be executed by a point sand dam distribution prediction device, which can be implemented in hardware and / or software. This device can be configured in any electronic device with network communication and computing capabilities. The embodiments of the present invention further specify the methods described above. For example... Figure 7 As shown, the method includes:

[0086] S210. Determine the riverbed distribution information of the meandering river in the target area; the riverbed distribution information represents the distribution range of the riverbed in three-dimensional space.

[0087] S220. Determine the seismic reflection characteristics of the meandering river in the target area; the seismic reflection characteristics are discontinuous in the in-phase axes of each candidate earthquake within a finite range.

[0088] In this embodiment, the river channel seismic reflection characteristics represent the reflection features of the river channel on the seismic profile. River channel downcutting causes a break in the seismic phase axis. According to seismic profile analysis, the location of the break in the wave trough is the location of the river channel. Therefore, the river channel seismic reflection characteristics manifest as a discontinuity in the seismic phase axis within the seismic profile, i.e., a discontinuity in the seismic phase axes of each candidate seismic line within a finite range.

[0089] S230. Based on the seismic reflection characteristics of the river channel and the riverbed distribution information, determine the river channel distribution information of the meandering river in the target area for each period.

[0090] In this embodiment, since the river channel meanders within the riverbed, the river channel distribution information of the meandering river in the target area can be determined from the three-dimensional seismic data based on the river channel seismic reflection characteristics and riverbed distribution information.

[0091] As an optional but not limited implementation, based on the seismic reflection characteristics of the river channel and the riverbed distribution information, the channel distribution information of the meandering river in the target area at each stage is determined, including steps E1-E2:

[0092] Step E1: Extract the coherence properties along the layers of each target layer in the target region.

[0093] Step E2: Based on the seismic reflection characteristics of the river channel and the riverbed distribution information, determine the candidate location information of the seismic phase axis discontinuity in the coherence attributes along the layer of each target layer.

[0094] Step E3: Use the candidate location information as the channel distribution information of the meandering river in the target area for each period.

[0095] In this embodiment, the layer coherence attribute represents the similarity or degree of coherence between adjacent seismic traces in seismic data. The coherence attribute is usually represented by a numerical value. The larger the value, the higher the degree of coherence, that is, the greater the similarity between adjacent seismic traces; the smaller the value, the lower the degree of coherence, that is, the greater the difference between adjacent seismic traces. The seismic coherence attribute can effectively identify underground faults.

[0096] It should be noted that a coherence attribute along a layer can only reflect the information on the distribution of underground channels at a certain period, including the distribution range, location, and morphology of the channels.

[0097] Candidate location information indicates the distribution of river channels within the riverbed area.

[0098] Specifically, by determining the coherence properties along different target layers on different seismic slopes, candidate location information matching the seismic reflection characteristics of the river channel is identified within the riverbed distribution range. The seismic reflection characteristics of the river channel are defined as the discontinuity of seismic phase axes in the seismic profile, i.e., the discontinuity of the seismic phase axes among the candidate seismic sources within a finite range. The candidate location information corresponding to each different target layer is then used as the river channel distribution information for each period of the meandering river in the target area.

[0099] See Figure 8 This is a schematic diagram of the three-dimensional coherence properties along the layer, where the curved lines in the diagram represent the river channel.

[0100] S240. Based on the river channel distribution information, determine the river channel evolution process information of the meandering river in the target area; the river channel evolution process information includes the distribution range of the river channel in three-dimensional space at different stages over time.

[0101] S250. Based on the river channel distribution information and river channel evolution process information, determine the distribution information of point sandbars in the meandering river of the target area. The point sandbar distribution information represents the distribution range of point sandbars in three-dimensional space.

[0102] Specific implementation examples

[0103] Large, restricted meandering river deposits have developed in a certain area of ​​Basin A, forming multiple superimposed point bars. This study aims to identify and predict the distribution of point bars in the meandering rivers of Basin A, using this specific area as the target region.

[0104] The specific steps for determining the riverbed distribution information of meandering rivers in Basin A of the target area are as follows:

[0105] First, through detailed calibration of the drilled wells, the seismic reflection characteristics of the riverbed of the restricted meandering river were clarified. The seismic reflection characteristics of the target layer in the target area are weak amplitude and poor continuity of the trough reflection. That is, the seismic reflection characteristics of the riverbed are relatively small among the candidate amplitudes within a limited range and relatively weak continuity among the seismic phase axes within a limited range.

[0106] Secondly, based on the seismic reflection characteristics of the riverbed, the amplitude attributes along the target layer of the two-dimensional and three-dimensional seismic data are extracted.

[0107] Then, the seismic attribute interpretation method was used to interpret the along-layer amplitude attributes of each target layer to determine the riverbed distribution information of the restricted meandering river in the target area. (See [link to seismic attribute interpretation method]). Figure 3 The riverbed distribution information is shown in the 3D seismic amplitude attribute planar map. The riverbed width is 6-26 km, the riverbed length is 155 km, and the riverbed area is nearly 3800 km². 2 .

[0108] The specific steps for determining the channel distribution and evolution information of meandering rivers in Basin A, the target area, are as follows:

[0109] First, based on the seismic profile characteristics, the seismic reflection characteristics of the river channel are determined. Analysis of the seismic profile in the target area reveals that the location of the break in the wave trough corresponds to the location of the river channel; that is, the seismic reflection characteristics of the river channel are discontinuous across candidate seismic phase axes within a finite range. Based on these river channel seismic reflection characteristics, the coherence attributes along each target layer are extracted. Candidate locations of discontinuities in the seismic phase axes along the coherence attributes are then identified, and these candidate locations are used to reflect the river channel distribution information.

[0110] Secondly, the 3D seismic data is processed using a coherence algorithm to generate a 3D seismic coherence volume. Then, isochronous stratigraphic slices are created from bottom to top along the seismic phase axes of the 3D seismic coherence volume within the riverbed. Based on these isochronous stratigraphic slices, the longitudinal migration and evolution patterns of the river channel are determined. (See also...) Figure 4These are isochronous stratigraphic slices of 3D seismic data. Slice 1 reflects the rudimentary river channel, which gradually became more meandering and developed through multiple stages. Slice 2 inherits the evolutionary characteristics of the early river channel, with increased meandering. Slice 3 reflects the river channel cutting into each other and straightening over time. Slice 4 reflects the abandonment of the original river channel, forming an oxbow lake.

[0111] The specific steps for determining the distribution information of point sandbars in the meandering river of Basin A in the target area are as follows:

[0112] First, a sub-volume of the target layer is extracted from the full 3D seismic data volume. Through 3D perspective analysis, the direction of paleocurrent and the formation process of point sandbars can be determined. (See also...) Figure 5 This is a three-dimensional perspective view of the river channel, showing the evolution process and point bar formation process. The red line represents the first stage of the river channel, where meandering rivers begin to form and the channel becomes more curved. The green line represents the second stage of the river channel, where the channel curvature increases. The blue line represents the third stage of the river channel, where the curvature continues to increase. The yellow area represents the point bars formed by the erosion of the convex bank and the deposition of sediment on the concave bank due to the migration and evolution of the river channel.

[0113] Secondly, the distribution range of composite point sandbars was defined by extracting areas with maximum wave trough amplitude attributes, relatively good seismic phase axis continuity, and relatively strong amplitude at the convex bank of the river channel, i.e., areas matching the seismic reflection characteristics of point sandbars. Within the target area, the total area of ​​point sandbars depicted was 741 km². 2 The estimated reservoir resources are 186 million tons. The recommended deployment of wells SP39 and SP40 can yield industrial oil and gas flows. See also... Figure 6 This is a plan view of the meandering river channel and point sandbars. The orange area represents the distribution information of point sandbars, including the distribution range, shape, and number of point sandbars. The light blue line represents the distribution information of the river channel, including the distribution range, length, and shape of the river channel.

[0114] Based on the results of actual drilling, the point sandbar distribution prediction method is effective and feasible for predicting the distribution range of point sandbars in restricted meandering rivers, and it is worth promoting and applying it in similar areas.

[0115] The technical solution of this invention determines the riverbed distribution information of the target area through hierarchical constraints, then determines the channel distribution information based on the riverbed distribution information, determines the channel evolution process information based on the channel distribution information, and finally determines the point sandbar distribution information based on the channel distribution information and the channel evolution process information, thereby achieving the prediction of the point sandbar distribution in the target area.

[0116] Example 3

[0117] Figure 9This is a schematic diagram of the structure of a point sand dam distribution prediction device provided in Embodiment 3 of the present invention. This embodiment is applicable to point sand dam distribution prediction. The point sand dam distribution prediction device can be implemented in hardware and / or software, and can be configured in any electronic device with network communication and computing capabilities. For example... Figure 9 As shown, the device includes:

[0118] The riverbed distribution determination module 310 is used to determine the riverbed distribution information of the meandering river in the target area; the riverbed distribution information represents the distribution range of the riverbed in three-dimensional space;

[0119] The river channel distribution determination module 320 is used to determine the river channel distribution information of the meandering river in the target area at each stage based on the riverbed distribution information; the river channel distribution information represents the distribution range of the river channel in three-dimensional space.

[0120] The river evolution process determination module 330 is used to determine the river evolution process information of the meandering river in the target area based on the river distribution information; the river evolution process information includes the distribution range of the river at different stages in three-dimensional space over time;

[0121] The point sandbar distribution determination module 340 is used to determine the point sandbar distribution information of the meandering river in the target area based on the river distribution information and the river evolution process information. The point sandbar distribution information represents the distribution range of point sandbars in three-dimensional space.

[0122] Optionally, the riverbed distribution determination module 310 includes:

[0123] Determine the seismic reflection characteristics of the meandering riverbed in the target area, wherein the seismic reflection characteristics of the riverbed are relatively small among various candidate amplitudes within a finite range and relatively weak continuity among various seismic phase axes within a finite range;

[0124] Based on the seismic reflection characteristics of the riverbed, the riverbed distribution information of the meandering river in the target area is determined.

[0125] Optionally, the riverbed distribution determination module 310 includes:

[0126] Based on the seismic reflection characteristics of the riverbed, the along-layer amplitude attributes of the target layer are extracted;

[0127] The seismic attribute interpretation method is used to interpret the amplitude attributes along the layer to determine the riverbed distribution information of the meandering river in the target area.

[0128] Optionally, the channel layout determination module 320 includes:

[0129] Determine the seismic reflection characteristics of the meandering river channel in the target area; the seismic reflection characteristics are discontinuous in the in-phase axes of various candidate earthquakes within a finite range;

[0130] Based on the seismic reflection characteristics and riverbed distribution information of the river channel, the river channel distribution information of the meandering river in the target area at each stage is determined.

[0131] Optionally, the channel layout determination module 320 includes:

[0132] Extract the layer coherence attributes of each target segment in the target region;

[0133] Based on the seismic reflection characteristics of the river channel and the riverbed distribution information, candidate location information for the discontinuity of seismic phase axes in the coherence properties along the layers of each target layer is determined.

[0134] The candidate location information is used as the channel distribution information of the meandering river in the target area at each stage.

[0135] Optionally, the river channel evolution determination module 330 includes:

[0136] Determine the three-dimensional seismic coherence volume of the target area;

[0137] The three-dimensional seismic coherence volume is processed to create isochronous stratigraphic slices;

[0138] Based on the isochronous stratigraphic slices and river channel distribution information, the river channel evolution process information of the target meandering river is determined.

[0139] Optionally, the point sandbar distribution determination module 340 includes:

[0140] Based on information on river channel distribution and evolution, the candidate convex bank locations of meandering rivers are determined.

[0141] A reference area matching the seismic reflection characteristics of a point sandbar is selected at the candidate convex bank location as the distribution information of the point sandbar. The seismic reflection characteristics of the point sandbar are the maximum amplitude among all candidate amplitudes within a limited range and relatively strong continuity among all candidate seismic phase axes within a limited range.

[0142] The technical solution of this invention determines the riverbed distribution information of the meandering river in the target area through hierarchical constraints, then determines the channel distribution information based on the riverbed distribution information, determines the channel evolution process information based on the channel distribution information, and finally determines the point sandbar distribution information based on the channel distribution information and the channel evolution process information, thereby achieving the prediction of the point sandbar distribution in the target area.

[0143] The point sand dam distribution prediction device provided in the embodiments of the present invention can execute the point sand dam distribution prediction method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0144] Example 4

[0145] Figure 10 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0146] like Figure 10 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0147] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0148] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as point sandbar distribution prediction methods.

[0149] In some embodiments, the point sandbar distribution prediction method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the point sandbar distribution prediction method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the point sandbar distribution prediction method by any other suitable means (e.g., by means of firmware).

[0150] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0151] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0152] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0153] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0154] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0155] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0156] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0157] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for predicting the distribution of point sand dams, characterized in that, include: Determine the riverbed distribution information of the meandering rivers in the target area; The riverbed distribution information indicates the range of riverbed distribution in three-dimensional space; Based on the riverbed distribution information, determine the channel distribution information of the meandering river in the target area for each period; The river channel distribution information indicates the range of river channel distribution in three-dimensional space; Based on the river channel distribution information, the river channel evolution process information of the meandering river in the target area is determined; the river channel evolution process information includes the distribution range of the river channel in three-dimensional space at different stages over time; Based on the river channel distribution information and river channel evolution information, the distribution information of point sandbars in the meandering river of the target area is determined. The point sandbar distribution information represents the distribution range of point sandbars in three-dimensional space.

2. The method according to claim 1, characterized in that, Determine the riverbed distribution information of the meandering river in the target area, including: Determine the seismic reflection characteristics of the meandering riverbed in the target area, wherein the seismic reflection characteristics of the riverbed are relatively small among various candidate amplitudes within a finite range and relatively weak continuity among various seismic phase axes within a finite range; Based on the seismic reflection characteristics of the riverbed, the riverbed distribution information of the meandering river in the target area is determined.

3. The method according to claim 2, characterized in that, Based on the seismic reflection characteristics of the riverbed, the riverbed distribution information of the meandering river in the target area is determined, including: Based on the seismic reflection characteristics of the riverbed, the along-layer amplitude attributes of the target layer are extracted; The seismic attribute interpretation method is used to interpret the amplitude attributes along the layer to determine the riverbed distribution information of the meandering river in the target area.

4. The method according to claim 1, characterized in that, Based on the riverbed distribution information, the channel distribution information of the meandering river in the target area for each period is determined, including: Determine the seismic reflection characteristics of the meandering river channel in the target area; the seismic reflection characteristics are discontinuous in the in-phase axes of various candidate earthquakes within a finite range; Based on the seismic reflection characteristics and riverbed distribution information of the river channel, the river channel distribution information of the meandering river in the target area at each stage is determined.

5. The method according to claim 4, characterized in that, Based on the aforementioned seismic reflection characteristics and riverbed distribution information, the riverbed distribution information of the meandering river in the target area at various stages is determined, including: Extract the layer coherence attributes of each target segment in the target region; Based on the seismic reflection characteristics of the river channel and the riverbed distribution information, candidate location information for the discontinuity of seismic phase axes in the coherence properties along the layers of each target layer is determined. The candidate location information is used as the channel distribution information of the meandering river in the target area at each stage.

6. The method according to claim 1, characterized in that, Based on the aforementioned river channel distribution information, the river channel evolution process information of the meandering river in the target area is determined, including: Determine the three-dimensional seismic coherence volume of the target area; The three-dimensional seismic coherence volume is processed to create isochronous stratigraphic slices; Based on the isochronous stratigraphic slices and river channel distribution information, the river channel evolution process information of the target meandering river is determined.

7. The method according to claim 1, characterized in that, Based on the aforementioned river channel distribution information and river evolution process information, the distribution information of point sandbars in the meandering river of the target area is determined, including: Based on information on river channel distribution and evolution, the candidate convex bank locations of meandering rivers are determined. A reference area matching the seismic reflection characteristics of a point sandbar is selected at the candidate convex bank location as the distribution information of the point sandbar. The seismic reflection characteristics of the point sandbar are the maximum amplitude among all candidate amplitudes within a limited range and relatively strong continuity among all candidate seismic phase axes within a limited range.

8. A point sand dam distribution prediction device, characterized in that, include: The riverbed distribution determination module is used to determine the riverbed distribution information of meandering rivers in the target area; The riverbed distribution information indicates the range of riverbed distribution in three-dimensional space; The river channel distribution determination module is used to determine the river channel distribution information of the meandering river in the target area at each stage based on the riverbed distribution information. The river channel distribution information indicates the range of river channel distribution in three-dimensional space; The river evolution process determination module is used to determine the river evolution process information of the meandering river in the target area based on the river distribution information; the river evolution process information includes the distribution range of the river at different stages in three-dimensional space over time; The point sandbar distribution determination module is used to determine the point sandbar distribution information of the meandering river in the target area based on the river channel distribution information and river channel evolution process information. The point sandbar distribution information represents the distribution range of point sandbars in three-dimensional space.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for predicting the distribution of point sandbars as described in any one of claims 1-7.

10. A storage medium for storing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the method for predicting the distribution of point sandbars as described in any one of claims 1-7.

Images