A seismic geomorphology recovery method based on velocity reconstruction

Abstract

The present application relates to a kind of based on velocity reconstruction seismic geomorphology recovery method, belong to geological exploration research technical field, discuss the control action of early permian paleogeomorphology of China Ordos basin east margin to marine-terrestrial transitional facies shale gas sweet spot area distribution.Using impression method, using velocity reconstruction decompaction correction technology, restore early permian asher late topography, identify karst highland, karst gentle slope, karst depression and so on three geomorphic units.Based on sensitive elastic parameter bayes discrimination method, the plane distribution characteristics of marine-terrestrial transitional facies shale are identified by poststack seismic inversion technology, and accordingly, it is inferred that the distribution of shale gas sweet spot area may be related to the weak reducing environment conducive to the deposition of organic-rich sediments during deposition.Combining velocity reconstruction seismic geomorphology recovery technology and sensitive elastic parameter bayes discrimination high-quality shale identification technology can effectively predict the distribution of marine-terrestrial transitional facies sweet spot area, and provide technical support for well deployment.

Description

Technical Field

[0001] This invention belongs to the field of geological exploration and research technology, specifically relating to a seismic geomorphology restoration method based on velocity reconstruction. Background Technology

[0002] In recent years, China has successively discovered several marine-continental transitional shale gas enrichment areas in the Permian strata on the eastern margin of the Ordos Basin and the Carboniferous-Permian strata on the southern margin of the Sichuan Basin. To date, the proven geological resources amount to 19.79 × 10¹² m³. 3 This accounts for 25% of China's total shale gas resources, with recoverable resources of 3.48 × 10¹² m³. 3 This type of shale gas possesses significant exploration and development potential. While large-scale development of marine shale gas has been achieved in recent years, large-scale development of transitional marine-continental shale gas is still in its early stages globally. Unlike marine shale developed on deep-water shelves, transitional marine-continental shale typically deposits in the transitional environment of epimontane seas, lagoons, and deltas under regressive conditions. It exhibits characteristics of rapid sedimentary cycles in terrestrial shale formations, significant control by sedimentary microfacies, and similar influence from sea-level changes. It is characterized by numerous and thin producing layers, uneven vertical and horizontal distribution, high organic carbon content, moderate maturity, and good gas-bearing capacity. Currently, insufficient understanding of the factors controlling the distribution of transitional marine-continental shale hinders the exploration and development process.

[0003] Previous studies have shown that utilizing paleogeomorphism to constrain sedimentary systems and revealing how tectonic paleogeomorphism controls the type and distribution of sedimentary systems is of significant reference value for identifying favorable oil and gas development areas. Previous studies have analyzed the control of paleogeomorphic features on the deposition of high-quality marine shale through paleogeomorphic reconstruction, suggesting that sedimentary paleogeomorphism determines the planar zonation and development scale of organic-rich shale, thus serving as a basis for selecting favorable shale gas exploration areas. However, the lateral variation of marine-continental transitional shale sediments is significant, and the controlling factors for their distribution are poorly understood, especially the relationship between paleogeomorphic features and the distribution of organic-rich shale sediments. Regarding the marine-continental transitional facies strata of the Lower Permian Shanxi Formation in the eastern margin of the Ordos Basin, a few existing studies have provided good explanations for the control mechanism of the vertical heterogeneity of marine-continental transitional shale distribution, but the controlling factors for the planar heterogeneity of shale distribution remain unclear, hindering the prediction of shale sweet spots and preventing the large-scale development of marine-continental transitional shale production areas.

[0004] Existing research indicates that paleogeographic reconstruction during the sedimentary period has a certain controlling effect on marine organic-rich shale, but whether the distribution of transitional marine-continental shale is controlled by paleogeographic features during the sedimentary period remains a mystery. If it can be confirmed that the planar distribution of transitional marine-continental organic-rich shale has a certain coupling relationship with sedimentary geomorphology, it could effectively solve problems such as the difficulty in predicting shale sweet spots and hinder the process of earthquake geomorphological reconstruction. Summary of the Invention

[0005] The purpose of this invention is to provide a seismic geomorphological restoration method based on velocity reconstruction, addressing the technical problems existing in the prior art, namely, whether the distribution of marine-continental transitional shale is controlled by paleogeography during the sedimentary period remains a mystery. If it can be confirmed that the planar distribution of organic-rich shale in the marine-continental transitional facies has a certain coupling relationship with the geomorphology during the sedimentary period, it can effectively solve problems such as the difficulty in predicting shale sweet spots and hinder the process of seismic geomorphological restoration and reconstruction.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows: A seismic geomorphology restoration method based on velocity reconstruction includes the following steps: S1: Acquire basic data, which includes seismic data volume, well logging data, and core data; S2: First, multi-parameter rock physics cross-analysis is carried out based on the basic data to determine the sensitive parameters for lithology. On this basis, pre-stack and post-stack seismic inversion is carried out to obtain the spatial distribution of the sensitive parameters. Then, Bayesian statistics are performed using the inversion attributes. Under the premise of high accuracy of lithology identification in wells, Bayesian discrimination is used to classify the lithology of the sensitive parameters under probability statistics. Then, the sensitive parameters obtained by inversion are converted into the spatial distribution of lithology, so as to achieve effective identification of complex lithology in the marine-continental transitional facies. S3: Using the impression method, determine the reference surface for paleogeographic restoration of the upper part of the target stratum, make full use of the mirror relationship between the residual paleogeography and the overlying strata, and use velocity reconstruction-based decompaction correction technology to restore the Early Permian Late Asser landform and identify three geomorphic units: karst highland, karst gentle slope, and karst depression.

[0007] Furthermore, in step S2, the Bayesian statistics are as follows: By comprehensively utilizing population information, sample information, and prior information to perform posterior probability density statistics, we have the following formula (1): (1) In the formula: Refers to a certain type of lithology; j This represents the number of lithological classifications; X The inversion properties of the sample points; It is prior information about the distribution of a certain type of lithology, and in practical applications it is determined by the proportion of samples of that type of lithology in the total number of samples. It is conditional probability, referring to the assumption that... The probability density of the distribution of attribute sample point X under the indicated lithological conditions; It refers to the sum of the probability densities of the distribution of attribute samples under various lithological conditions; It is the posterior conditional probability, which refers to the probability that a given attribute sample point is classified as a certain type of lithology. The lithology with the highest probability is selected from the classification results.

[0008] Furthermore, the classification criteria for lithology determined by formula (1) are as follows: > The lithology of the sample is Conversely, the lithology of the sample is .

[0009] Furthermore, the reference plane is selected in step S3 as follows: A reference surface should meet three conditions: ① It should be an isochronous interface distributed throughout the entire area, representing the sea level at that time; ② The sedimentary interface should be closest to the erosion surface; ③ The reference surface should be easy to identify.

[0010] Furthermore, the decompaction correction in step S3 is as follows: The porosity reduction model is used to recover the sedimentary thickness of different lithological strata, i.e., formula (2): (2) Solving (2), we find that porosity decreases with increasing burial depth, which leads to formula (3): (3) In the formula: Porosity at a certain depth; This represents the original volume of the sediment before deposition. This represents the volume of the sediment after deposition. The depth of burial; Relative burial depth; , It is a constant, dimensionless; Furthermore, based on the porosity conversion model, the restored thickness of different lithologies can be calculated. As in formula (4): (4) In the formula: The original porosity of the sediment; The current thickness of a certain type of lithology; (3) Substituting into (4) we get: (5) In equation (5), the thickness is restored. The restored thickness of a single layer in a certain lithology is given. For complex lithological assemblages in the marine-continental transitional facies, where the same lithology exhibits multiple developmental characteristics, the overall restored thickness of the strata can be expressed as... For example, in formula (6): (6) In the formula: To recover the thickness of a single layer in a certain lithology, i= 1, 2, 3, and 4 represent different lithologies: sandstone, coal seam, mudstone, shale, and carbonaceous shale.j =1,2,3…n represents the 1st, 2nd, 3rd…nth single layer of a certain lithology. By summing the restored thickness of each single layer of different lithologies, the restored thickness of the entire strata can be calculated, and then the paleogeographic features of the top surface can be depicted by the impression method.

[0011] Furthermore, the logging data in step S1 is acquired through a deep well data acquisition device, which includes a depth detection unit, an infrared ranging unit, a light intensity detection unit, a lighting adjustment unit, an image acquisition unit, and a data processing unit. The data processing unit, serving as the control core, is connected to the depth detection unit, infrared ranging unit, light intensity detection unit, lighting adjustment unit, and image acquisition unit, respectively. The depth detection unit is used to detect the real-time depth data of the deep well data acquisition device inside the well. The infrared ranging unit is used to detect the real-time distance data between the deep well data acquisition device and the well wall when the device is inside the well. The light intensity detection unit is used to detect the real-time light intensity data of the environment in which the deep well data acquisition device is located when it is inside the well. The lighting adjustment unit is used to adjust the light intensity of the environment in which the deep well data acquisition device is located when it is inside the well to a standard value. The image acquisition unit is used to acquire relevant well logging data.

[0012] Furthermore, the data processing unit controls the depth detection unit to be normally open, and controls the infrared ranging unit, light intensity detection unit, illumination adjustment unit, and image acquisition unit to be normally closed; When the real-time depth data matches the set depth data, the data processing unit controls the infrared ranging unit and the light intensity detection unit to turn on. When the real-time distance data matches the set distance data and the real-time illumination intensity data meets the standard value, the data processing unit controls the image acquisition unit to start. If the real-time light intensity data does not meet the standard value, the data processing unit controls the lighting adjustment unit to turn on.

[0013] A computer-readable storage medium, characterized in that the computer-readable storage medium stores one or more computer programs, which, when executed by one or more processors, implement the above-described seismic geomorphology restoration method based on velocity reconstruction.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: One of the beneficial effects of this scheme is that it explores the control role of Early Permian paleogeography on the distribution of shale gas sweet spots in the marine-continental transitional facies of the Ordos Basin in China. Using the impression method and velocity reconstruction-based decompaction correction technology, the Early Permian Late Asserl geomorphology was reconstructed, identifying three geomorphic units: karst highlands, karst slopes, and karst depressions. Based on the sensitive elastic parameter Bayesian discriminant method, the planar distribution characteristics of marine-continental transitional facies shale were identified through post-stack seismic inversion technology. This suggests that the distribution of shale gas sweet spots may be related to a weakly reducing environment conducive to the preservation of organic-rich sediments during the depositional period. Combining velocity reconstruction seismic geomorphological reconstruction technology with sensitive elastic parameter Bayesian discriminant technology for identifying high-quality shale can effectively predict the distribution of marine-continental transitional facies sweet spots, providing technical support for well location deployment. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the statistical method of the present invention.

[0016] Figure 2 This is a schematic diagram of the microstructure composition of the present invention. Pore volume: pore volume; Skeleton: skeleton volume. Detailed Implementation

[0017] 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 only for explaining the invention and are not intended to limit the invention; that is, the described embodiments are merely some embodiments of the invention, and not all embodiments. The components of the embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0018] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention. It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0019] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0020] like Figure 1 As shown, a seismic geomorphology restoration method based on velocity reconstruction includes the following steps: S1: Acquire basic data, which includes seismic data volume, well logging data, and core data; S2: First, multi-parameter rock physics cross-analysis is carried out based on the basic data to determine the sensitive parameters for lithology. On this basis, pre-stack and post-stack seismic inversion is carried out to obtain the spatial distribution of the sensitive parameters. Then, Bayesian statistics are performed using the inversion attributes. Under the premise of high accuracy of lithology identification in wells, Bayesian discrimination is used to classify the lithology of the sensitive parameters under probability statistics. Then, the sensitive parameters obtained by inversion are converted into the spatial distribution of lithology, so as to achieve effective identification of complex lithology in the marine-continental transitional facies. S3: Using the impression method, determine the reference surface for paleogeographic restoration of the upper part of the target stratum, make full use of the mirror relationship between the residual paleogeography and the overlying strata, and use velocity reconstruction-based decompaction correction technology to restore the Early Permian Late Asser landform and identify three geomorphic units: karst highland, karst gentle slope, and karst depression.

[0021] In the aforementioned study, six wells in the Benxi Formation of the research area were examined. Core observations identified different lithologies, including coal, fine-grained sandstone, siltstone, silty mudstone, and shale, and recorded lithological combinations from different profiles. The data also includes well logging data from these six wells. The 3D seismic data covers an area of ​​100 km. 2The effective bandwidth is 15–60 Hz, and the dominant frequency is 35 Hz. Available seismic data is provided by China National Petroleum Corporation Coalbed Methane Company. This scheme takes the control of Early Permian paleogeography on the distribution of shale gas sweet spots in the marine-continental transitional facies of the Ordos Basin in China as an example. Considering the complex lithological assemblage, rapid vertical and horizontal variations, and numerous challenges in seismic prediction within the study area's marine-continental transitional facies, a Bayesian statistical approach is adopted to identify complex lithologies. First, multi-parameter petrophysical cross-analysis is conducted based on geological and well logging data to determine lithologically sensitive parameters. Based on this, pre-stack and post-stack seismic inversions are performed to obtain the spatial distribution of these sensitive parameters. Then, Bayesian statistics are performed using the inversion attributes. Under the premise of high accuracy in well lithology identification, Bayesian discrimination is used to classify the sensitive parameters using probabilistic statistics, thereby converting the inverted sensitive parameters into a spatial distribution of lithology, achieving effective identification of complex lithologies in the marine-continental transitional facies. Due to the varied sedimentary environments and frequent transitions between marine and terrestrial facies during the depositional period in the study area, and the influence of early geomorphology, the central part of the study area has a large containment space, resulting in the deposition of a large amount of sand and mud sediments. The residual thickness of these sediments makes it difficult to accurately characterize the karst paleogeographic features at the top. Furthermore, the well spacing in the study area is relatively large, averaging approximately 5 km. Using well data alone, it is difficult to reconstruct high-resolution paleogeographic features of this period. Three-dimensional seismic data provides high-precision data for reconstructing high-resolution geomorphic features. The imprinting method is used to determine the reference surface for paleogeographic reconstruction above the target stratum. The mirror relationship between the residual paleogeography and the overlying strata is fully utilized, and the paleogeographic reconstruction is achieved by analyzing the thickness of the overlying strata.

[0022] Furthermore, in step S2, the Bayesian statistics are as follows: By comprehensively utilizing population information, sample information, and prior information to perform posterior probability density statistics, we have the following formula (1): (1) In the formula: Refers to a certain type of lithology; j This represents the number of lithological classifications; X The inversion properties of the sample points; It is prior information about the distribution of a certain type of lithology, and in practical applications it is determined by the proportion of samples of that type of lithology in the total number of samples. It is conditional probability, referring to the assumption that... The probability density of the distribution of attribute sample point X under the indicated lithological conditions; It refers to the sum of the probability densities of the distribution of attribute samples under various lithological conditions; It is the posterior conditional probability, which refers to the probability that a given attribute sample point is classified as a certain type of lithology. The lithology with the highest probability is selected from the classification results.

[0023] Furthermore, the classification criteria for lithology determined by formula (1) are as follows: > The lithology of the sample is Conversely, the lithology of the sample is .

[0024] Furthermore, the reference plane is selected in step S3 as follows: A reference surface should meet three conditions: ① It should be an isochronous interface distributed throughout the entire area, representing the sea level at that time; ② The sedimentary interface should be closest to the erosion surface; ③ The reference surface should be easy to identify.

[0025] To restore the geomorphological features of the study area using the impression method, it is necessary to perform decompaction correction on the strata below the base level and above the interface to be restored. Compaction correction is used to restore the strata to their state before compaction. Since the study area is a typical marine-continental transitional sedimentary system, the marine-continental transitional sediments above the weathering crust of the Dongdayao limestone and below the coal seam are mainly limestone, carbonaceous shale, mudstone, coal seam, and sandstone. The current strata all exhibit a certain degree of compaction, and their thickness is the thickness after compaction, which does not reflect the original depositional thickness. Therefore, when restoring the paleogeomorphological features of the top surface, it is necessary to perform decompaction correction on the strata thickness from below the coal seam base level to the top surface of the Dongdayao limestone to restore the strata thickness during the depositional period. This study uses a porosity reduction model to restore the depositional thickness of strata of different lithologies. The change in strata thickness during the compaction process is formed by the continuous decrease in the pore volume of the rock strata, but the strata skeleton volume remains unchanged before and after compaction (e.g., Figure 2 (As shown).

[0026] Furthermore, the decompaction correction in step S3 is as follows: The porosity reduction model is used to recover the sedimentary thickness of different lithological strata, i.e., formula (2): (2) Solving (2), we find that porosity decreases with increasing burial depth, which leads to formula (3): (3) In the formula: Porosity at a certain depth; This represents the original volume of the sediment before deposition. This represents the volume of the sediment after deposition. The depth of burial; Relative burial depth; , It is a constant, dimensionless; Furthermore, based on the porosity conversion model, the restored thickness of different lithologies can be calculated. As in formula (4): (4) In the formula: The original porosity of the sediment; The current thickness of a certain type of lithology; (3) Substituting into (4) we get: (5) In equation (5), the thickness is restored. The restored thickness of a single layer in a certain lithology is given. For complex lithological assemblages in the marine-continental transitional facies, where the same lithology exhibits multiple developmental characteristics, the overall restored thickness of the strata can be expressed as... For example, in formula (6): (6) In the formula: To recover the thickness of a single layer in a certain lithology, i= 1, 2, 3, and 4 represent different lithologies: sandstone, coal seam, mudstone, shale, and carbonaceous shale. j =1,2,3…n represents the 1st, 2nd, 3rd…nth single layer of a certain lithology. By summing the restored thickness of each single layer of different lithologies, the restored thickness of the entire strata can be calculated, and then the paleogeographic features of the top surface can be depicted by the impression method.

[0027] Furthermore, the logging data in step S1 is acquired through a deep well data acquisition device, which includes a depth detection unit, an infrared ranging unit, a light intensity detection unit, a lighting adjustment unit, an image acquisition unit, and a data processing unit. The data processing unit, serving as the control core, is connected to the depth detection unit, infrared ranging unit, light intensity detection unit, lighting adjustment unit, and image acquisition unit, respectively. The depth detection unit is used to detect the real-time depth data of the deep well data acquisition device inside the well. The infrared ranging unit is used to detect the real-time distance data between the deep well data acquisition device and the well wall when the device is inside the well. The light intensity detection unit is used to detect the real-time light intensity data of the environment in which the deep well data acquisition device is located when it is inside the well. The lighting adjustment unit is used to adjust the light intensity of the environment in which the deep well data acquisition device is located when it is in the well to a standard value (set according to the image acquisition unit being able to acquire logging data normally). The image acquisition unit is used to acquire relevant well logging data.

[0028] Furthermore, the data processing unit controls the depth detection unit to be normally open, and controls the infrared ranging unit, light intensity detection unit, illumination adjustment unit, and image acquisition unit to be normally closed; When the real-time depth data matches the set depth data (the depth value set according to actual needs), the data processing unit controls the infrared ranging unit and the light intensity detection unit to be turned on. When the real-time distance data matches the set distance data (the distance value set according to actual needs) and the real-time light intensity data meets the standard value, the data processing unit controls the image acquisition unit to start. If the real-time light intensity data does not meet the standard value, the data processing unit controls the lighting adjustment unit to turn on.

[0029] In the above scheme, the orderly coordination and activation of the depth detection unit, infrared ranging unit, light intensity detection unit, lighting adjustment unit, and image acquisition unit can avoid some devices from processing invalid actions for a long time, and can also avoid detecting or collecting a large amount of invalid data, thereby reducing energy consumption. Furthermore, the sequential activation of each unit can ensure the reliability of the subsequent logging data, that is, the logging data is collected under the conditions of set depth, set distance, and standard illumination.

[0030] A computer-readable storage medium, characterized in that the computer-readable storage medium stores one or more computer programs, which, when executed by one or more processors, implement the above-described seismic geomorphology restoration method based on velocity reconstruction.

[0031] The above are preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention shall fall within the protection scope of the present invention.

Claims

1. A seismic geomorphology restoration method based on velocity reconstruction, characterized in that, Includes the following steps: S1: Acquire basic data, which includes seismic data volume, well logging data, and core data; S2: First, multi-parameter rock physics cross-analysis is carried out based on the basic data to determine the sensitive parameters for lithology. On this basis, pre-stack and post-stack seismic inversion is carried out to obtain the spatial distribution of the sensitive parameters. Then, Bayesian statistics are performed using the inversion attributes. Under the premise of high accuracy of lithology identification in wells, Bayesian discrimination is used to classify the lithology of the sensitive parameters under probability statistics. Then, the sensitive parameters obtained by inversion are converted into the spatial distribution of lithology, so as to achieve effective identification of complex lithology in the marine-continental transitional facies. S3: Using the impression method, determine the reference surface for paleogeographic restoration of the upper part of the target stratum, make full use of the mirror relationship between the residual paleogeography and the overlying strata, and use velocity reconstruction-based decompaction correction technology to restore the early Permian Late Asser landform and identify three geomorphic units: karst highland, karst gentle slope, and karst depression. In step S2, the Bayesian statistics are as follows: By comprehensively utilizing population information, sample information, and prior information to perform posterior probability density statistics, we have the following formula (1): (1) In the formula: Refers to a certain type of lithology; j This represents the number of lithological classifications; X The inversion properties of the sample points; It is prior information about the distribution of a certain type of lithology, and in practical applications it is determined by the proportion of samples of that type of lithology in the total number of samples. It is conditional probability, referring to the assumption that... The probability density of the distribution of attribute sample point X under the indicated lithological conditions; It refers to the sum of the probability densities of the distribution of attribute samples under various lithological conditions; It is the posterior conditional probability, which refers to the probability that a given attribute sample point is classified as a certain type of lithology. The classification result selects the lithology with the highest probability. The classification criteria for lithology based on formula (1) are as follows: > The lithology of the sample is Conversely, the lithology of the sample is ; The reference plane is selected in step S3 as follows: A reference surface should meet three conditions: ① It should be an isochronous interface distributed throughout the entire area, representing the sea level at that time; ② The sedimentary interface should be closest to the erosion surface; ③ The reference surface should be easy to identify. The specific steps for decompaction correction in step S3 are as follows: The porosity reduction model is used to recover the sedimentary thickness of different lithological strata, i.e., formula (2): (2) Solving (2), we find that porosity decreases with increasing burial depth, which leads to formula (3): (3) In the formula: Porosity at a certain depth; This represents the original volume of the sediment before deposition. This represents the volume of the sediment after deposition. The depth of burial; Relative burial depth; , It is a constant, dimensionless; Furthermore, based on the porosity conversion model, the recovery thickness of different lithologies can be calculated. As in formula (4): (4) In the formula: The original porosity of the sediment; The current thickness of a certain type of lithology; (3) Substituting into (4) we get: (5) In equation (5), the thickness is restored. The restored thickness of a single layer in a certain lithology is given. For complex lithological assemblages in the marine-continental transitional facies, where the same lithology exhibits multiple developmental characteristics, the overall restored thickness of the strata can be expressed as... For example, in formula (6): (6) In the formula: To recover the thickness of a single layer in a certain lithology, i= 1, 2, 3, and 4 represent different lithologies: sandstone, coal seam, mudstone, shale, and carbonaceous shale. j =1,2,3…n represents the 1st, 2nd, 3rd…nth single layer of a certain lithology. By summing the restored thickness of each single layer of different lithologies, the restored thickness of the entire strata can be calculated, and then the paleogeographic features of the top surface can be depicted by the impression method.

2. The seismic geomorphology restoration method based on velocity reconstruction according to claim 1, characterized in that, The logging data in step S1 is acquired by a deep well data acquisition device, which includes a depth detection unit, an infrared ranging unit, a light intensity detection unit, a lighting adjustment unit, an image acquisition unit, and a data processing unit. The data processing unit, serving as the control core, is connected to the depth detection unit, infrared ranging unit, light intensity detection unit, lighting adjustment unit, and image acquisition unit, respectively. The depth detection unit is used to detect the real-time depth data of the deep well data acquisition device inside the well. The infrared ranging unit is used to detect the real-time distance data between the deep well data acquisition device and the well wall when the device is inside the well. The light intensity detection unit is used to detect the real-time light intensity data of the environment in which the deep well data acquisition device is located when it is inside the well. The lighting adjustment unit is used to adjust the light intensity of the environment in which the deep well data acquisition device is located when it is inside the well to a standard value. The image acquisition unit is used to acquire relevant well logging data.

3. The seismic geomorphology restoration method based on velocity reconstruction according to claim 2, characterized in that, The data processing unit controls the depth detection unit to be normally open, and controls the infrared ranging unit, light intensity detection unit, illumination adjustment unit, and image acquisition unit to be normally closed. When the real-time depth data matches the set depth data, the data processing unit controls the infrared ranging unit and the light intensity detection unit to turn on. When the real-time distance data matches the set distance data and the real-time illumination intensity data meets the standard value, the data processing unit controls the image acquisition unit to start. If the real-time light intensity data does not meet the standard value, the data processing unit controls the lighting adjustment unit to turn on.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more computer programs that, when executed by one or more processors, implement a velocity-reconstruction-based seismic geomorphology restoration method as described in any one of claims 1-3.

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