Ancient landform restoration method and system, electronic equipment and storage medium

Abstract

The invention discloses an ancient landform restoration method and system, electronic equipment and a storage medium. The method comprises the steps that drilling data of a target research area, pre-stack gather data and the initial depth of a target stratum are acquired; performing rock physical modeling according to the drilling data to obtain target data; constructing a Poisson's ratio and a Lame coefficient based on the target data, and further performing conversion to obtain a Poisson's ratio threshold value and a function relationship between the Lame coefficient and the porosity; performing inversion based on the pre-stack gather data to obtain a target data volume; a Poisson's ratio body and a Lame coefficient body are constructed based on the target data body, and then sand-to-ground ratio distribution and a porosity body are obtained by combining a Poisson's ratio threshold value and function relation conversion; and performing preliminary recovery on the initial depth of the target stratum by using a layer leveling method, performing compaction amount correction based on a porosity body, and performing paleo-water depth correction based on sand-to-land ratio distribution to obtain the paleo-landform depth. The method can efficiently and accurately restore the ancient landform, and can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, system, electronic device, and storage medium for ancient landform restoration. Background Technology

[0002] Paleomorphology is one of the important factors controlling the development and distribution of sedimentary facies in the later stages of an oil and gas basin, and to a certain extent, it controls the reservoir-seal combination and reservoir distribution in the later stages. Therefore, paleomorphological reconstruction has always been one of the important research contents in oil and gas exploration. There are three main categories of paleomorphological reconstruction methods: (1) paleomorphology reconstruction based on stratigraphic thickness, referred to as the stratigraphic thickness method; (2) paleomorphology reconstruction using sequence stratigraphy or high-resolution sequence stratigraphy, referred to as the sequence stratigraphic method; and (3) paleomorphology reconstruction based on seismic layer flattening method, referred to as the seismic layer flattening method.

[0003] In paleogeographic reconstruction, changes in sediment porosity and thickness caused by the combined effects of gravity and overlying sediment ballast, as well as changes in sediment type caused by variations in water depth, are crucial considerations. However, among the three commonly used methods, stratigraphic thickness and sequence stratigraphy both consider these corrections, but require a large amount of well data, making them unsuitable for areas with limited exploration. Seismic stratigraphic flattening is a fast and convenient method suitable for paleogeographic reconstruction in areas with limited exploration and few wells. However, current seismic stratigraphic flattening methods do not consider various corrections. Summary of the Invention

[0004] This invention aims to at least partially address the limitations of related technologies. To this end, this invention proposes a method, system, electronic device, and storage medium for paleomorphological restoration, capable of efficiently and accurately restoring paleomorphological features.

[0005] On one hand, embodiments of the present invention provide a method for paleomorphological restoration, comprising the following steps:

[0006] Acquire drilling data, pre-stack gather data, and initial depth of the target formation in the target study area;

[0007] Rock physics modeling is performed based on drilling data to obtain target data, including P-wave velocity, S-wave velocity, and density curves.

[0008] Based on the target data, Poisson's ratio and Lamé coefficient are constructed, and then the Poisson's ratio threshold value and the functional relationship between Lamé coefficient and porosity are obtained.

[0009] Inversion is performed based on pre-stack gather data to obtain the target data volume; the target data volume includes the P-wave velocity volume, the S-wave velocity volume, and the density volume.

[0010] Based on the target data volume, Poisson's ratio volume and Lamé coefficient volume are constructed, and then combined with the Poisson's ratio threshold value and functional relationship to obtain the sand-land ratio distribution and porosity volume;

[0011] The initial depth of the target stratum is preliminarily recovered using the layer flattening method, thus obtaining the first depth;

[0012] The second depth is obtained by correcting the compaction amount based on the porosity of the volume at the first depth.

[0013] Based on the sand-to-land ratio distribution, paleowater depth correction was performed on the second depth to obtain the paleogeographic depth.

[0014] Optionally, rock physical modeling is performed based on drilling data to obtain target data, including the following steps:

[0015] Well logging interpretation data is obtained based on drilling data interpretation; well logging interpretation data includes clay content, porosity, and water saturation curves.

[0016] Based on the lithology and physical properties of drilled wells, combined with well logging interpretation data, rock physics modeling is used to construct the rock skeleton and the velocity and density parameters of pores and fluids, and then forward modeling is used to obtain the P-wave velocity, S-wave velocity and density curves.

[0017] Optionally, Poisson's ratio and Lamé coefficient are constructed based on the target data, and then transformed into a Poisson's ratio threshold value and a functional relationship between the Lamé coefficient and porosity, including the following steps:

[0018] Based on the longitudinal wave velocity and the transverse wave velocity, Poisson's ratio is calculated using the first formula, and then the Poisson's ratio threshold value is obtained through quantitative analysis.

[0019] The quantitative analysis is based on cross-plot analysis or histogram analysis of Poisson's ratio and lithology of the target study area; the expression of the first formula is:

[0020]

[0021] In the formula, σ represents Poisson's ratio; V p V represents the longitudinal wave velocity. s Indicates the transverse wave velocity;

[0022] Based on the longitudinal wave velocity, transverse wave velocity and density curves, the Lamé coefficient is calculated using the second formula. Then, cross plot analysis is performed on the Lamé coefficient and porosity to obtain the functional relationship.

[0023] Porosity is derived from drilling data; the expression for the second formula is:

[0024]

[0025] In the formula, λ represents the Lamé coefficient; V p V represents the longitudinal wave velocity. s ρ represents the transverse wave velocity; ρ represents the density, which is determined based on the density curve.

[0026] Optionally, the target data volume is obtained by inversion based on pre-stack gather data, including the following steps:

[0027] Using a preset root mean square velocity volume, pre-stack gather data is converted into angle gather data; the angle gather data includes near-angle gathers, mid-angle gathers and far-angle gathers, and the interval boundaries of each angle gather overlap.

[0028] Simultaneous inversion is performed using all angle gathers in the angle gather data to obtain the P-wave velocity volume, S-wave velocity volume, and density volume.

[0029] Optionally, a Poisson's ratio volume and a Lamé coefficient volume are constructed based on the target data volume, and then combined with the Poisson's ratio threshold value and functional relationship to obtain the sand-soil ratio distribution and porosity volume, including the following steps:

[0030] Based on the longitudinal wave velocity volume and the transverse wave velocity volume, the Poisson's ratio volume is calculated using the first formula;

[0031] The expression for the first formula is:

[0032]

[0033] In the formula, σ represents the Poisson's ratio. V p V represents the longitudinal wave velocity volume. s Represents a transverse wave velocity volume;

[0034] Based on the Poisson's ratio body, lithological bodies are obtained by using the Poisson's ratio threshold value, and then the sand-to-soil ratio distribution of the target strata is obtained based on the lithological bodies;

[0035] Based on the longitudinal wave velocity volume, the transverse wave velocity volume, and the density volume, the Lamé coefficient volume is calculated using the second formula.

[0036] The expression for the second formula is:

[0037]

[0038] In the formula, λ represents the Lamé coefficient; V p V represents the longitudinal wave velocity volume. s ρ represents the transverse wave velocity volume; ρ represents the density volume.

[0039] Based on the Lamé coefficient, the porosity is obtained using functional relationships.

[0040] Optionally, the second depth is obtained by correcting the compaction amount based on the porosity of the first depth, including the following steps:

[0041] Based on the relationship curve between porosity and formation burial depth in the target study area, the initial porosity is derived by inversely using the theoretical relationship between porosity and depth. The porosity and formation burial depth in the target study area are derived from the interpretation of drilling data. The expression for the theoretical relationship between porosity and depth is as follows:

[0042]

[0043] In the formula, H represents the variables of porosity and depth; represents the initial porosity; c represents the compaction coefficient.

[0044] Based on the initial porosity, the theoretical relationship is used to solve for multiple points at the initial depth, and then the compaction coefficient is obtained by least squares minimization.

[0045] The theoretical relationship for solving multiple points above the initial depth is expressed as follows:

[0046]

[0047] In the formula, This represents the porosity at the i-th point above the initial depth h0; represents the initial porosity; c represents the compaction coefficient; N is the total number of points to be solved;

[0048] The compaction amount is corrected by the ratio of the first depth to the compaction coefficient, and the second depth is obtained.

[0049] Optionally, paleowater depth correction is performed on the second depth based on the sand-soil ratio distribution to obtain the paleogeographic depth, including the following steps:

[0050] The target sand-soil ratio at the depth of the target formation is extracted from the sand-soil ratio distribution.

[0051] Based on the target sand-land ratio, paleowater depth correction coefficients are constructed using pre-defined statistical empirical relationships;

[0052] The expression for the statistical empirical relationship is as follows: In the formula, M represents the paleowater depth correction coefficient, S represents the sand-to-land ratio, and α is a parameter obtained through statistical fitting.

[0053] Paleowater depth correction is performed by using the ratio of the second depth to the paleowater depth correction coefficient, thus obtaining the paleogeographic depth.

[0054] On the other hand, embodiments of the present invention provide a paleomorphological restoration system, comprising:

[0055] The first module is used to acquire drilling data, pre-stack gather data and the initial depth of the target formation in the target study area.

[0056] The second module is used to perform rock physics modeling based on drilling data to obtain target data, including P-wave velocity, S-wave velocity, and density curves.

[0057] The third module is used to construct Poisson's ratio and Lamé coefficient based on the target data, and then convert them into the Poisson's ratio threshold value and the functional relationship between the Lamé coefficient and porosity.

[0058] The fourth module is used to perform inversion based on pre-stack gather data to obtain the target data volume; the target data volume includes the P-wave velocity volume, the S-wave velocity volume, and the density volume.

[0059] The fifth module is used to construct the Poisson's ratio volume and Lamé coefficient volume based on the target data volume, and then combine the Poisson's ratio threshold value and functional relationship to obtain the sand-land ratio distribution and porosity volume;

[0060] The sixth module is used to preliminarily recover the initial depth of the target strata using the layer flattening method, thus obtaining the first depth;

[0061] The seventh module is used to correct the compaction amount of the first depth based on the porosity of the volume, so as to obtain the second depth;

[0062] The eighth module is used to perform paleowater depth correction on the second depth based on the sand-to-land ratio distribution to obtain the paleogeographic depth.

[0063] On the other hand, embodiments of the present invention provide an electronic device, including: a processor and a memory; the memory is used to store a program; the processor executes the program to implement the above-mentioned ancient landform restoration method.

[0064] On the other hand, embodiments of the present invention provide a computer storage medium storing a processor-executable program, which, when executed by a processor, is used to implement the above-described ancient landform restoration method.

[0065] This invention involves acquiring drilling data, pre-stack gather data, and the initial depth of the target formation in the target study area; performing rock physics modeling based on the drilling data to obtain target data, including P-wave velocity, S-wave velocity, and density curves; constructing Poisson's ratio and Lamé coefficient based on the target data, and then converting them to obtain a Poisson's ratio threshold value and a functional relationship between the Lamé coefficient and porosity; performing inversion based on the pre-stack gather data to obtain the target data volume, including a P-wave velocity volume, a S-wave velocity volume, and a density volume; constructing a Poisson's ratio volume and a Lamé coefficient volume based on the target data volume, and then combining the Poisson's ratio threshold value and the functional relationship to obtain a sand-to-soil ratio distribution and a porosity volume; using a layer flattening method to preliminarily recover the initial depth of the target formation to obtain a first depth; correcting the first depth for compaction based on the porosity volume to obtain a second depth; and correcting the second depth for paleowater depth based on the sand-to-soil ratio distribution to obtain a paleogeographic depth. The main idea of ​​this invention is to carry out multi-parameter inversion by using pre-stack seismic gathers and a small number of wells or wells in adjacent areas, and then calculate compaction correction and paleowater depth correction based on these parameters. Specifically, this invention introduces compaction correction and paleowater depth correction within the technical framework of the seismic layer flattening method, so that better and more accurate paleogeographic reconstruction data can be obtained even in areas with low exploration and few wells. Attached Figure Description

[0066] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0067] Figure 1 This is a schematic diagram of an implementation environment for the method of ancient landform restoration provided in this embodiment of the invention;

[0068] Figure 2 This is a flowchart illustrating a method for ancient landform restoration provided in an embodiment of the present invention;

[0069] Figure 3 A schematic diagram illustrating the unfolding process of step S200 provided in an embodiment of the present invention;

[0070] Figure 4 A schematic diagram illustrating the unfolding process of step S400 provided in an embodiment of the present invention;

[0071] Figure 5 A schematic diagram illustrating the unfolding process of step S700 provided in an embodiment of the present invention;

[0072] Figure 6 A schematic diagram illustrating the unfolding process of step S800 provided in an embodiment of the present invention;

[0073] Figure 7 A schematic diagram illustrating the technical process of the paleomorphological restoration method provided in this embodiment of the invention;

[0074] Figure 8 A schematic diagram illustrating the technical process of layer flattening, compaction amount correction, and paleowater depth correction provided in an embodiment of the present invention;

[0075] Figure 9 This is a schematic diagram of the structure of an ancient landform restoration system provided in an embodiment of the present invention;

[0076] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0077] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0078] It should be noted that although functional modules are divided in the system diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first / S100," "second / S200," etc., in the specification, claims, and the aforementioned figures are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0079] In this invention, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this invention can be combined with other embodiments.

[0080] It is understood that the ancient landform restoration method provided in this embodiment of the invention can be applied to any computer device with data processing and computing capabilities, and this computer device can be various types of terminals or servers. When the computer device in the embodiment is a server, the server is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal can be a smartphone, tablet, laptop, or desktop computer, but it is not limited to these.

[0081] To facilitate understanding of the technical solution of this invention, the technical features and proper nouns that may appear in the embodiments of this invention will first be explained:

[0082] like Figure 1 The diagram shown is a schematic representation of an implementation environment provided by an embodiment of the present invention. (Refer to...) Figure 1 The implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected via a network, either wirelessly or via a wired connection, to complete data transmission and exchange.

[0083] Server 101 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0084] Additionally, server 101 can also be a node server in a blockchain network. Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms.

[0085] Terminal 102 can be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. Terminal 102 and server 101 can be directly or indirectly connected via wired or wireless communication, and this embodiment of the invention does not impose any limitations.

[0086] Exemplary based on Figure 1 The implementation environment shown in this embodiment of the invention provides a method for ancient landform restoration. The following description uses the application of this ancient landform restoration method in server 101 as an example. It can be understood that this ancient landform restoration method can also be applied in terminal 102.

[0087] Reference Figure 2 , Figure 2 This is a flowchart illustrating a paleomorphological restoration method applied to a server, provided in an embodiment of the present invention. The executing entity of this paleomorphological restoration method can be any of the aforementioned computer devices (including servers or terminals). (Refer to...) Figure 2 The method includes the following steps:

[0088] S100: Obtain drilling data, pre-stack gather data, and initial depth of the target formation for the target study area;

[0089] For example, in some specific implementations, drilling data of the target study area is first collected. In some alternative implementations, if no drilling data is available in the study area, drilling data from adjacent areas can be used. Simultaneously, relevant pre-stack gather data is collected to facilitate subsequent data inversion, and the depth of the target strata before paleogeomorphological reconstruction is recorded as h0 (i.e., the initial depth).

[0090] S200. Based on drilling data, perform rock physical modeling to obtain target data;

[0091] The target data includes P-wave velocity, S-wave velocity, and density curves;

[0092] It should be noted that in some embodiments, such as Figure 3 As shown, step S200 may include the following steps: S201, obtaining well logging interpretation data based on drilling data interpretation; the well logging interpretation data includes clay content, porosity and water saturation curve; S202, based on the lithology and physical properties of the drilled well combined with the well logging interpretation data, constructing the rock skeleton and the velocity and density parameters of pores and fluids using rock physics modeling, and then forward modeling to obtain the P-wave velocity, S-wave velocity and density curves.

[0093] For example, in some specific implementations, rock physics modeling requires analyzing rock skeleton, porosity, and fluid parameters based on existing well data in the region, setting reasonable parameters to establish a Xu-White rock physics model, and then performing forward modeling to obtain predicted P-wave velocity, S-wave velocity, and density curves (when the data foundation is clear, the specific forward modeling implementation process can be set according to specific needs, and this embodiment of the invention does not impose limitations). Specifically, by combining the lithology and physical properties of existing wells, as well as the clay content, porosity, and water saturation curves obtained from well logging interpretation, the Xu-White rock physics modeling method can be used to set the velocity and density parameters of the rock skeleton, pores, and fluids, and then perform forward modeling to obtain P-wave velocity, S-wave velocity, and density curves.

[0094] S300. Based on the target data, construct Poisson's ratio and Lamé coefficient, and then convert them to obtain the Poisson's ratio threshold value and the functional relationship between Lamé coefficient and porosity;

[0095] It should be noted that in some embodiments, step S300 may include the following steps:

[0096] S301. Based on the longitudinal wave velocity and the transverse wave velocity, Poisson's ratio is calculated using the first formula, and then the Poisson's ratio threshold value is obtained through quantitative analysis.

[0097] The quantitative analysis is based on cross-plot analysis or histogram analysis of Poisson's ratio and lithology of the target study area; the expression of the first formula is:

[0098]

[0099] In the formula, σ represents Poisson's ratio; V p V represents the longitudinal wave velocity. s Indicates the transverse wave velocity;

[0100] S302. Based on the longitudinal wave velocity, transverse wave velocity and density curves, the Lamé coefficient is calculated using the second formula. Then, the cross-plot analysis of the Lamé coefficient and porosity is performed to obtain the functional relationship.

[0101] Porosity is derived from drilling data; the expression for the second formula is:

[0102]

[0103] In the formula, λ represents the Lamé coefficient; V p V represents the longitudinal wave velocity. s ρ represents the transverse wave velocity; ρ represents the density, which is determined based on the density curve.

[0104] For example, in some specific embodiments, the P-wave velocity, S-wave velocity, and density curves obtained through rock physics modeling are expressed using formulas. (in, σ is Poisson's ratio, V p V is the longitudinal wave velocity. s (where the transverse wave velocity is used) to obtain the Poisson's ratio curve. Through histogram analysis, a threshold value for Poisson's ratio to identify sandstone and mudstone (i.e., the Poisson's ratio threshold value) is set. Specifically, the Poisson's ratio threshold value is set based on the quantitative relationship between rock physical parameters and lithology; that is, the Poisson's ratio threshold value is obtained after analyzing the cross-plot or histogram of Poisson's ratio and lithology.

[0105] Furthermore, the P-wave velocity, S-wave velocity, and density curves obtained through rock physics modeling are calculated using formulas. (where λ is the Lamé coefficient, V) p V is the longitudinal wave velocity. s Let ρ be the transverse wave velocity and ρ be the density. The Lamé coefficient curve is obtained, and the functional relationship between the Lamé coefficient and porosity is fitted using cross-plot analysis. Specifically, the functional relationship between the Lamé coefficient and porosity is calculated using a two-parameter cross-plot to determine a reasonable fit, i.e., the functional relationship.

[0106] S400. Inversion is performed based on pre-stack gather data to obtain the target data volume;

[0107] The target data volume includes the P-wave velocity volume, the S-wave velocity volume, and the density volume;

[0108] It should be noted that in some embodiments, such as Figure 4 As shown, step S400 may include the following steps: S401, using a preset root mean square velocity volume, converting pre-stack gather data into angle gather data; wherein, the angle gather data includes near-angle gathers, mid-angle gathers and far-angle gathers, and the interval boundaries of each angle gather overlap; S402, using all angle gathers in the angle gather data for simultaneous inversion to obtain the P-wave velocity volume, S-wave velocity volume and density volume.

[0109] For example, in some specific embodiments, the pre-stack gather data is converted into angle gather data using the root mean square velocity volume. For instance, 3-15° is stacked as a near-angle gather, 13-25° as a mid-angle gather, and 23-35° as a far-angle gather (the angle range of each gather can be fine-tuned according to actual needs; the above ranges are only illustrative examples). Finally, the P-wave velocity volume, S-wave velocity volume, and density volume are obtained using simultaneous gather inversion. Specifically, during the pre-stack simultaneous inversion process, some elastic parameters are calculated through the differences between the near, mid, and far-angle data volumes. Inter-cell overlap is used to make the calculation results more stable. When the data foundation is clear, the specific inversion implementation process can be set according to specific needs; this embodiment of the invention does not impose limitations.

[0110] S500: Based on the target data volume, construct the Poisson's ratio volume and Lamé coefficient volume, and then combine the Poisson's ratio threshold value and functional relationship to obtain the sand-land ratio distribution and porosity volume;

[0111] It should be noted that in some embodiments, step S500 may include the following steps:

[0112] S501. Based on the longitudinal wave velocity volume and the transverse wave velocity volume, the Poisson's ratio volume is calculated using the first formula.

[0113] The expression for the first formula is:

[0114]

[0115] In the formula, σ represents the Poisson's ratio. V p V represents the longitudinal wave velocity volume. s Represents a transverse wave velocity volume;

[0116] S502. Based on Poisson's ratio bodies, lithological bodies are obtained by using Poisson's ratio threshold values, and then the sand-to-soil ratio distribution of the target strata is obtained based on the lithological bodies.

[0117] S503. Based on the longitudinal wave velocity volume, the transverse wave velocity volume, and the density volume, the Lamé coefficient volume is calculated using the second formula.

[0118] The expression for the second formula is:

[0119]

[0120] In the formula, λ represents the Lamé coefficient; V p V represents the longitudinal wave velocity volume. s ρ represents the transverse wave velocity volume; ρ represents the density volume.

[0121] S504. Based on the Lamé coefficient, the porosity is obtained using functional relationships.

[0122] For example, in some specific embodiments, the obtained P-wave velocity body and S-wave velocity body are used, and the formula is applied. (in, σ is Poisson's ratio, V p V is the longitudinal wave velocity. s (For shear wave velocity), the Poisson's ratio is calculated. Based on the Poisson's ratio threshold value for sandstone and mudstone set by the rock physics modeling steps mentioned above, the lithological body is obtained, and the sand-to-soil ratio distribution of the target stratigraphic unit (i.e., the target formation) is calculated.

[0123] Furthermore, using the obtained P-wave velocity volume, S-wave velocity volume, and density volume, the formula is applied. (where λ is the Lamé coefficient, V) p V is the longitudinal wave velocity. s Let ρ be the transverse wave velocity and ρ be the density. Calculate the Lamé coefficient volume. Based on the functional relationship between the Lamé coefficient and porosity obtained from the rock physics model in the preceding steps, calculate the porosity volume, denoted as [formula missing]. 's' indicates that the porosity volume was obtained through calculation using seismic data.

[0124] S600. The initial depth of the target stratum is initially recovered using the layer flattening method to obtain the first depth;

[0125] For example, in some specific implementations, for the target stratum, the commonly used seismic layer flattening method is used, i.e., the thicker the stratum, the lower the paleomorphology, and the thinner the stratum, the higher the paleomorphology, to complete the preliminary paleomorphology reconstruction. The depth of the target stratum before paleomorphology reconstruction is denoted as h0, and the paleomorphology depth after preliminary reconstruction is denoted as h1 (i.e., the first depth).

[0126] S700. Based on the porosity of the volume, the compaction amount of the first depth is corrected to obtain the second depth;

[0127] It should be noted that in some embodiments, such as Figure 5 As shown, step S700 may include the following steps:

[0128] S701. Based on the relationship curve between porosity and formation burial depth in the target study area, the initial porosity is derived by using the theoretical relationship between porosity and depth; wherein, the porosity and formation burial depth of the target study area are obtained based on the interpretation of drilling data; the expression for the theoretical relationship between porosity and depth is:

[0129]

[0130] In the formula, H represents the variables of porosity and depth; represents the initial porosity; c represents the compaction coefficient.

[0131] S702. Based on the initial porosity, the theoretical relationship is used to solve for multiple points above the initial depth, and then the compaction coefficient is obtained by least squares minimization.

[0132] The theoretical relationship for solving multiple points above the initial depth is expressed as follows:

[0133]

[0134] In the formula, This represents the porosity at the i-th point above the initial depth h0; represents the initial porosity; c represents the compaction coefficient; N is the total number of points to be solved;

[0135] S703. The compaction amount is corrected by the ratio of the first depth to the compaction coefficient to obtain the second depth.

[0136] For example, in some specific embodiments, the compaction correction amount can be calculated as follows:

[0137] During sediment burial, under the combined effects of gravity and overlying sediment ballast, formation porosity decreases systematically with increasing depth. The theoretical relationship between porosity and depth is as follows:

[0138]

[0139] in, Porosity at depth H, %; ρ is the initial porosity of the surface, %; c is the compaction coefficient, m. -1 H is the burial depth of the strata, in meters. Regional porosity experimental data were used. The initial porosity is obtained by calculating the relationship curve between porosity and burial depth H. Furthermore, the compaction coefficient at depth h0 of the target formation is obtained by solving the following equation:

[0140]

[0141] To obtain a more stable compaction coefficient c, the solution is performed at multiple points above the target formation depth h0, as shown in the following formula:

[0142]

[0143] Since there may be some discrepancies between the actual data and the theoretical relationship (Equation 1), Equation 3 is further solved using the least squares minimization method to obtain the compaction coefficient c. The compaction amount is then corrected using h1 / c. The depth at which the compaction amount correction is completed is denoted as h2 (i.e., the second depth).

[0144] S800, based on the sand-land ratio distribution, paleowater depth correction is performed on the second depth to obtain the paleogeographic depth;

[0145] It should be noted that in some embodiments, such as Figure 6 As shown, step S800 may include the following steps: S801, extracting the target sand-soil ratio at the depth of the target stratum from the sand-soil ratio distribution; S802, constructing a paleowater depth correction coefficient based on the target sand-soil ratio using a preset statistical empirical relationship; S803, completing paleowater depth correction by using the ratio of the second depth to the paleowater depth correction coefficient to obtain the paleogeographic depth. Specifically, firstly, a wide range of successful paleogeographic reconstruction examples are collected globally, with sedimentary backgrounds similar to the target area. These examples were reconstructed using other methods (such as stratigraphic thickness method, sequence stratigraphy method), and measured data are available. The paleowater depth correction coefficient and corresponding sand-soil ratio data are extracted from these examples; then, a statistical fitting method is used to obtain the empirical relationship between the paleowater depth correction coefficient and the sand-soil ratio. The initial form of the empirical relationship is selected as follows: (Where, M represents the paleowater depth correction factor, %; S represents the sand-to-soil ratio, %; parameter α needs to be obtained through fitting).

[0146] For example, in some specific implementations, paleowater depth correction can be achieved as follows: During the deposition of strata, the water depth of the depositional environment may change, requiring further paleowater depth correction to obtain a more accurate depth of the paleogeography. The shallower the paleowater depth in the paleodepositional environment, the higher the sand-to-soil ratio of the strata; conversely, the deeper the paleowater depth in the paleodepositional environment, the lower the sand-to-soil ratio. Since there are abundant examples of paleogeographic reconstruction, some examples utilize extensive well data. By statistically analyzing the relationships in these examples, an empirical relationship between the paleowater depth correction coefficient and the sand-to-soil ratio can be established: (Where, M is the paleowater depth correction coefficient, %; S is the sand-soil ratio, %; parameter α needs to be obtained through fitting). Obtain the sand-soil ratio S(h0) at the target stratum depth from the sand-soil ratio distribution calculated in the preceding steps, and calculate the paleowater depth correction coefficient M based on the aforementioned empirical relationship. Complete the paleowater depth correction using h2 / M to obtain the final paleogeographic depth h3.

[0147] To explain in detail the principle of the technical solution of the present invention, the overall process of the present invention will be described below with reference to some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and should not be regarded as a limitation of the present invention.

[0148] like Figure 7 and Figure 8 As shown, the paleomorphological restoration method provided in this embodiment of the invention can be implemented through the following steps:

[0149] The first step is rock physics modeling. First, drilling data for the target study area is collected. If no drilling data is available for the study area, drilling data from neighboring areas can be used. Combining the lithological and physical properties of the drilled wells, as well as the clay content, porosity, and water saturation curves obtained from well logging interpretation, the Xu-White rock physics modeling method is used to set the velocity and density parameters of the rock skeleton, pores, and fluids. Forward modeling is then performed to obtain the P-wave velocity, S-wave velocity, and density curves.

[0150] The second step involves using formulas to analyze the P-wave velocity, S-wave velocity, and density curves obtained from rock physics modeling. (in, σ is Poisson's ratio, V p V is the longitudinal wave velocity. s (where the transverse wave velocity is used) to obtain the Poisson's ratio curve. Histogram analysis is then used to set a threshold value for Poisson's ratio to distinguish between sandstone and mudstone.

[0151] The third step involves using formulas to analyze the P-wave velocity, S-wave velocity, and density curves obtained from rock physics modeling. (where λ is the Lamé coefficient, V) p V is the longitudinal wave velocity. s (where ρ is the transverse wave velocity and ρ is the density), obtain the Lamé coefficient curve, and use cross-plot analysis to fit the functional relationship between the Lamé coefficient and porosity.

[0152] The fourth step is to use the root mean square velocity volume to convert the pre-stack gather data into angle gather data. The 3-15° stack is set as the near-angle gather, the 13-25° stack is set as the mid-angle gather, and the 23-35° stack is set as the far-angle gather. The P-wave velocity volume, S-wave velocity volume and density volume are obtained by using the simultaneous inversion of the gathers.

[0153] The fifth step involves using the obtained P-wave and S-wave velocity volumes to apply the formula... (in, σ is Poisson's ratio, V p V is the longitudinal wave velocity. s (For shear wave velocity), the Poisson's ratio volume is determined. Based on the Poisson's ratio threshold value for sandstone and mudstone set in the second step based on rock physics modeling, the lithological volume is obtained, and the sand-to-soil ratio distribution of the target layer is determined.

[0154] Step 6: Using the obtained P-wave velocity volume, S-wave velocity volume, and density volume, apply the formula... (where λ is the Lamé coefficient, V) p V is the longitudinal wave velocity. s Let ρ be the transverse wave velocity and ρ be the density. Calculate the Lamé coefficient volume. Based on the functional relationship between the Lamé coefficient and porosity obtained from the rock physics model in step three, calculate the porosity volume, denoted as [formula missing]. 's' indicates that the porosity volume was obtained through calculation using seismic data.

[0155] Step 7: For the target stratum, the commonly used seismic layer flattening method is used, where thicker strata represent lower paleomorphic features and thinner strata represent higher paleomorphic features, to complete the preliminary paleomorphic reconstruction. The depth of the target stratum before paleomorphic reconstruction is denoted as h0, and the depth of the paleomorphic features after preliminary reconstruction is denoted as h1.

[0156] Step 8: Calculation of compaction correction. During sediment burial, under the combined effects of gravity and overlying sediment load, formation porosity decreases systematically with increasing depth. The theoretical relationship between porosity and depth is as follows:

[0157]

[0158] in, Porosity at depth H, %; ρ is the initial porosity of the surface, %; c is the compaction coefficient, m. -1 H is the burial depth of the strata, in meters. Regional porosity experimental data were used. The initial porosity is obtained by calculating the relationship curve between porosity and burial depth H. Furthermore, the compaction coefficient at depth h0 of the target formation is obtained by solving the following equation:

[0159]

[0160] To obtain a more stable compaction coefficient c, the solution is performed at multiple points above the target formation depth h0, as shown in the following formula:

[0161]

[0162] Since there may be some discrepancies between the actual data and the theoretical relationship (Equation 1), Equation 3 is further solved using the least squares minimization method to obtain the compaction coefficient c. The compaction amount is then corrected using h1 / c. The depth at which the compaction amount correction is completed is denoted as h2.

[0163] Step 9: Paleowater depth correction. During the depositional process, the water depth of the sedimentary environment may change, requiring further paleowater depth correction to obtain a more accurate depth of the paleogeography. Shallower paleowater in the paleodepositional environment results in a higher sand-to-soil ratio, while deeper paleowater results in a lower sand-to-soil ratio. Since there are abundant examples of paleogeographic reconstruction, some of which utilize extensive well data, an empirical relationship between the paleowater depth correction coefficient and the sand-to-soil ratio can be established by statistically analyzing the relationships in these examples. (Where, M is the paleowater depth correction coefficient, %; S is the sand-soil ratio, %; parameter α needs to be obtained through fitting). Obtain the sand-soil ratio S(h0) at the target stratum depth from the sand-soil ratio distribution calculated in step five, and calculate the paleowater depth correction coefficient M based on the aforementioned empirical relationship. Complete the paleowater depth correction using h2 / M to obtain the final paleogeographic depth h3.

[0164] In summary, this invention incorporates compaction correction and paleowater depth correction within the technical framework of the seismic layer flattening method, enabling better and more accurate paleogeographic reconstruction even in areas with limited exploration and few wells. The main idea of ​​this invention is to utilize pre-stack seismic gathers and a small number of wells or adjacent wells to conduct multi-parameter inversion, and then calculate compaction correction and paleowater depth correction based on these parameters.

[0165] Compared with the prior art, the present invention has at least the following beneficial effects:

[0166] (1) Existing paleogeographic restoration techniques cannot perform compaction correction and paleowater depth correction in the absence of wells. To address this deficiency, this invention fully utilizes the rich lithological and physical property information of pre-stack earthquakes in the seismic layer flattening technique. The lithological and physical property data obtained by simultaneous inversion calculation before stacking are combined with parameters obtained by rock physics modeling to calculate the compaction correction and water depth correction coefficients.

[0167] (2) By introducing compaction correction and paleowater depth correction into the layer flattening technology, the problem of paleogeographic restoration in areas with low exploration level and few wells has been solved.

[0168] (3) When calculating compaction parameters based on pre-stack inversion parameters and theoretical relationships, considering the possible differences between actual data and theoretical relationships, a least squares optimization algorithm for compaction coefficients is proposed.

[0169] On the other hand, such as Figure 9As shown, this embodiment of the invention provides a paleomorphological restoration system 900, which may include:

[0170] The first module 901 is used to acquire drilling data, pre-stack gather data and the initial depth of the target formation in the target study area;

[0171] The second module 902 is used to perform rock physics modeling based on drilling data to obtain target data, including P-wave velocity, S-wave velocity, and density curves.

[0172] The third module 903 is used to construct Poisson's ratio and Lamé coefficient based on the target data, and then convert them to obtain the Poisson's ratio threshold value and the functional relationship between the Lamé coefficient and porosity;

[0173] Module 4, 904, is used to perform inversion based on pre-stack gather data to obtain the target data volume; the target data volume includes the P-wave velocity volume, the S-wave velocity volume, and the density volume.

[0174] The fifth module 905 is used to construct the Poisson's ratio volume and Lamé coefficient volume based on the target data volume, and then combine the Poisson's ratio threshold value and functional relationship to obtain the sand-land ratio distribution and porosity volume;

[0175] Module 6, 906, is used to preliminarily recover the initial depth of the target strata using the layer flattening method, thus obtaining the first depth;

[0176] The seventh module 907 is used to correct the compaction amount of the first depth based on the porosity of the volume to obtain the second depth;

[0177] Module 8, 908, is used to perform paleowater depth correction on the second depth based on the sand-to-land ratio distribution to obtain the paleogeographic depth.

[0178] The content of the method embodiments of the present invention is applicable to the system embodiments. The specific functions implemented in the system embodiments are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0179] On the other hand, embodiments of the present invention also provide an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described ancient landform restoration method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0180] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0181] like Figure 10 As shown, Figure 10The hardware structure of an electronic device 1000 according to another embodiment is illustrated. The electronic device 1000 includes:

[0182] The processor 1001 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (aSIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention.

[0183] The memory 1002 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RaM). The memory 1002 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1002 and is called and executed by the processor 1001 to execute the network node population optimization method of the embodiments of this invention.

[0184] Input / output interface 1003 is used to implement information input and output;

[0185] The communication interface 1004 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0186] Bus 1005 transmits information between various components of the device (e.g., processor 1001, memory 1002, input / output interface 1003, and communication interface 1004);

[0187] The processor 1001, memory 1002, input / output interface 1003 and communication interface 1004 are connected to each other within the device via bus 1005.

[0188] The electronic device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0189] The content of the method embodiments of the present invention is applicable to the embodiments of the present electronic device. The specific functions implemented by the embodiments of the present electronic device are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0190] Another aspect of this invention provides a computer-readable storage medium storing a program that is executed by a processor to implement the aforementioned method.

[0191] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD to ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein computer-readable program code is carried. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0192] The content of the method embodiments of the present invention is applicable to the computer-readable storage medium embodiments. The specific functions implemented by the computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0193] This invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned method.

[0194] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0195] It should be noted that although several modules for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0196] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, portable hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of the present invention.

[0197] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented in this invention. Alternative embodiments are contemplated, in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0198] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the system disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0199] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0200] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, system, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, system, or device). For the purposes of this specification, "computer-readable medium" can mean any system that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, system, or device.

[0201] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0202] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0203] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0204] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0205] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A method for ancient landform restoration, characterized in that, Includes the following steps: Acquire drilling data, pre-stack gather data, and initial depth of the target formation in the target study area; Rock physics modeling is performed based on the drilling data to obtain target data; the target data includes P-wave velocity, S-wave velocity, and density curve. Based on the target data, Poisson's ratio and Lamé coefficient are constructed, and then the Poisson's ratio threshold value and the functional relationship between the Lamé coefficient and porosity are obtained. Inversion is performed based on the pre-stack gather data to obtain the target data volume; the target data volume includes a P-wave velocity volume, a S-wave velocity volume, and a density volume. Based on the target data volume, a Poisson's ratio volume and a Lamé coefficient volume are constructed, and then combined with the Poisson's ratio threshold value and the functional relationship to obtain the sand-land ratio distribution and porosity volume; The initial depth of the target stratum is initially recovered using a layer flattening method to obtain a first depth; Based on the porosity volume, the first depth is corrected for compaction amount to obtain the second depth; Based on the sand-land ratio distribution, the second depth is corrected for paleowater depth to obtain the paleogeographic depth.

2. The paleomorphological restoration method according to claim 1, characterized in that, The process of performing rock physical modeling based on the drilling data to obtain target data includes the following steps: Well logging interpretation data is obtained based on the interpretation of the drilling data; the well logging interpretation data includes clay content, porosity, and water saturation curves. Based on the lithology and physical properties of the drilled wells, combined with the well logging interpretation data, rock physics modeling is used to construct the rock skeleton and the velocity and density parameters of pores and fluids, and then forward modeling is used to obtain the P-wave velocity, the S-wave velocity, and the density curves.

3. The paleomorphological restoration method according to claim 1, characterized in that, The process of constructing Poisson's ratio and Lamé coefficient based on the target data, and then converting them into a Poisson's ratio threshold value and a functional relationship between the Lamé coefficient and porosity, includes the following steps: Based on the longitudinal wave velocity and the transverse wave velocity, the Poisson's ratio is calculated using the first formula, and then the Poisson's ratio threshold value is obtained through quantitative analysis. The quantitative analysis is based on cross-plot analysis or histogram analysis of the Poisson's ratio and the lithology of the target study area; the expression of the first formula is: In the formula, σ represents Poisson's ratio; V p V represents the longitudinal wave velocity. s Indicates the transverse wave velocity; Based on the longitudinal wave velocity, the transverse wave velocity, and the density curve, the Lamé coefficient is calculated using the second formula. Then, a cross-plot analysis is performed on the Lamé coefficient and the porosity to obtain the functional relationship. Wherein, the porosity is obtained based on the interpretation of the drilling data; the expression of the second formula is: In the formula, λ represents the Lamé coefficient; V p V represents the longitudinal wave velocity. s ρ represents the transverse wave velocity; ρ represents the density, which is determined based on the density curve.

4. The paleomorphological restoration method according to claim 1, characterized in that, The inversion based on the pre-stack gather data to obtain the target data volume includes the following steps: Using a preset root mean square velocity volume, the pre-stack gather data is converted into angle gather data; wherein, the angle gather data includes near-angle gathers, mid-angle gathers and far-angle gathers, and the interval boundaries of each angle gather overlap. Simultaneous inversion is performed using all angle gathers in the angle gather data to obtain the P-wave velocity volume, the S-wave velocity volume, and the density volume.

5. The paleomorphological restoration method according to claim 1, characterized in that, The process of constructing a Poisson's ratio volume and a Lamé coefficient volume based on the target data volume, and then combining the Poisson's ratio threshold value and the functional relationship to obtain the sand-land ratio distribution and porosity volume, includes the following steps: Based on the longitudinal wave velocity volume and the transverse wave velocity volume, the Poisson's ratio volume is calculated using the first formula; The expression for the first formula is: In the formula, σ represents the Poisson's ratio. V p V represents the longitudinal wave velocity volume. s Represents a transverse wave velocity volume; Based on the Poisson's ratio body, lithological bodies are obtained by using the Poisson's ratio threshold value, and then the sand-to-soil ratio distribution of the target stratum is obtained based on the lithological bodies; Based on the longitudinal wave velocity volume, the transverse wave velocity volume, and the density volume, the Lamé coefficient volume is calculated using the second formula. The expression for the second formula is: In the formula, λ represents the Lamé coefficient; V p V represents the longitudinal wave velocity volume. s ρ represents the transverse wave velocity volume; ρ represents the density volume. Based on the Lamé coefficient, the porosity is obtained using the functional relationship.

6. The method for paleomorphological restoration according to claim 1, characterized in that, The step of correcting the compaction amount of the first depth based on the porosity volume to obtain the second depth includes the following steps: Based on the porosity-formation burial depth relationship curve of the target study area, the initial porosity is derived by using the theoretical relationship between porosity and depth; wherein, the porosity and formation burial depth of the target study area are obtained based on the interpretation of the drilling data; the expression for the theoretical relationship between porosity and depth is: In the formula, H represents the variables of porosity and depth; represents the initial porosity; c represents the compaction coefficient. Based on the initial porosity, the theoretical relationship is used to solve for multiple points at the initial depth, and then the compaction coefficient is obtained by least squares minimization. The theoretical relationship, used to solve for multiple points above the initial depth, is expressed as follows: In the formula, This represents the porosity at the i-th point above the initial depth h0; represents the initial porosity; c represents the compaction coefficient; N is the total number of points to be solved; The compaction amount is corrected by the ratio of the first depth to the compaction coefficient, and the second depth is obtained.

7. The method for paleomorphological restoration according to claim 1, characterized in that, The process of performing paleowater depth correction on the second depth based on the sand-soil ratio distribution to obtain the paleogeographic depth includes the following steps: The target sand-soil ratio at the depth of the target stratum is extracted from the sand-soil ratio distribution. Based on the target sand-land ratio, paleowater depth correction coefficients are constructed using preset statistical empirical relationships; The expression for the statistical empirical relationship is as follows: In the formula, M represents the paleowater depth correction coefficient, S represents the sand-to-land ratio, and α is a parameter obtained through statistical fitting. The paleowater depth is obtained by performing paleowater depth correction using the ratio of the second depth to the paleowater depth correction coefficient.

8. A paleogeographic restoration system, characterized in that, include: The first module is used to acquire drilling data, pre-stack gather data and the initial depth of the target formation in the target study area. The second module is used to perform rock physics modeling based on the drilling data to obtain target data; the target data includes P-wave velocity, S-wave velocity, and density curve. The third module is used to construct Poisson's ratio and Lamé coefficient based on the target data, and then convert them into a Poisson's ratio threshold value and a functional relationship between the Lamé coefficient and porosity. The fourth module is used to perform inversion based on the pre-stack gather data to obtain the target data volume; the target data volume includes the P-wave velocity volume, the S-wave velocity volume, and the density volume; The fifth module is used to construct the Poisson's ratio volume and Lamé coefficient volume based on the target data volume, and then combine the Poisson's ratio threshold value and the functional relationship to obtain the sand-land ratio distribution and porosity volume; The sixth module is used to preliminarily recover the initial depth of the target stratum using a layer flattening method to obtain a first depth; The seventh module is used to correct the compaction amount of the first depth based on the porosity volume to obtain the second depth; The eighth module is used to perform paleowater depth correction on the second depth based on the sand-land ratio distribution to obtain the paleogeographic depth.

9. An electronic device, characterized in that, Including the processor and memory; The memory is used to store programs; The processor executes the program to implement the method as described in any one of claims 1 to 7.

10. A computer storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to implement the method as described in any one of claims 1 to 7.

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