Gypsum salt rock distribution prediction method and system based on well-seismic information collaborative constraint

Abstract

The invention discloses a gypsum salt rock distribution prediction method and system based on well-seismic information collaborative constraint, and relates to the technical field of petroleum and natural gas exploration and development. According to the gypsum salt rock distribution prediction method provided by the invention, the seismic data ancient landform, the gypsum salt rock section seismic horizon seismic attribute and the gypsum rock thickness are firstly analyzed and processed, and then the processing results are classified and fused, so that the gypsum salt rock prediction result can be obtained, and the prediction method can eliminate objective limitations of the two existing technical methods to the greatest extent, and the prediction accuracy is improved. The plane result of gypsum salt rock distribution is accurately predicted, and the well goodness of fit is high. The method is dominated, more accurate and fine gypsum salt rock distribution prediction work is achieved, support is provided for further well location deployment and drilling engineering, a well drilling and completion scheme is optimized on the basis of the prediction result, density optimization and facility preparation are scientifically guided, the clamping leakage rate is reduced, the drilling risk is finally reduced, and the economic benefits of oilfield development are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and natural gas exploration and development, and relates to a method and system for predicting gypsum-salt rock distribution under cooperative constraints of well-seismic information. Background Art

[0002] Years of exploration and development have shown that the gypsum salt rock in the standard limestone section of the Carboniferous System in the Tarim Basin will cause huge economic losses to drilling projects. When encountering gypsum salt rock during drilling, the drill bit has the risk of getting stuck. In the later cementing process, the gypsum salt rock will also squeeze the casing and deform it, causing huge economic losses. Based on previous engineering accidents, the current drilling, logging, and cementing operations have made corresponding improvements to gypsum salt rock, but the project cost and working hours have increased significantly, and a single well can reach nearly 15 million. Therefore, accurate prediction of the distribution of gypsum salt rock can improve economic benefits while controlling engineering risks.

[0003] During the research process, the commonly used methods for predicting the distribution of gypsum salt rock had certain limitations, and the predicted results did not match the wells well. For the characterization of the distribution of the same stratum in a certain area, the paleo-geomorphological analysis before its deposition is one of the commonly used technical methods. However, due to the influence of seismic resolution, the top and bottom of the gypsum mudstone cannot be explained, and it is difficult to obtain accurate paleo-geomorphology before the deposition of the gypsum mudstone. The depositional environment of gypsum salt rock is a shallow water evaporation environment. The thickness of the gypsum salt rock development is strongly controlled by paleo-geomorphology. Gypsum salt rock is usually positively correlated with paleo-geomorphology. However, after the gypsum salt rock is thinned into the tuning thickness, it is limited by the seismic resolution. The range of gypsum salt rock characterization is wide, resulting in the paleo-geomorphological response to the development of gypsum salt rock not meeting the expected requirements.

[0004] Another technical method is seismic amplitude attribute analysis. However, when the gypsum salt rock is thinned to the tuning thickness, the response of the seismic amplitude attribute to the gypsum salt rock will disappear, resulting in the inability to accurately characterize the distribution range of the gypsum salt rock development. In the thinning area of ​​gypsum salt rock, the signal-to-noise ratio of the seismic attribute response to the gypsum salt rock is reduced, and the gypsum salt rock characterization range is small.

[0005] In summary, it is urgent to propose a new method and process to improve the efficiency and accuracy of gypsum-salt rock distribution prediction so as to control engineering risks and improve economic benefits. Summary of the invention

[0006] The purpose of the present invention is to solve the problem of low efficiency and accuracy in the prediction of gypsum-salt rock distribution in the prior art, and to provide a method and system for predicting gypsum-salt rock distribution with coordinated constraints of well-seismic information.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] The present invention proposes a method for predicting the distribution of gypsum-salt rock based on well-seismic information collaborative constraints, comprising the following steps:

[0009] Obtain seismic data paleo-geomorphology, seismic attributes of seismic horizons in gypsum-salt rock sections, and thickness of gypsum rocks;

[0010] Analyze and process the paleo-geomorphology of seismic data, seismic attributes of seismic layers in gypsum-salt rock sections, and thickness of gypsum rocks;

[0011] The processing results are classified and integrated to obtain the prediction results of gypsum-salt rock and realize the prediction of gypsum-salt rock distribution.

[0012] Preferably, the method for obtaining paleogeography from seismic data is as follows:

[0013] The seismic interface after and before the deposition of the gypsum-salt rock section is interpreted from the seismic data, and the paleo-geomorphology before the deposition of the gypsum-salt rock section is obtained using the thickness method.

[0014] Preferably, the highest responsive seismic attribute of the gypsum-salt rock is the seismic attribute of the seismic layer of the gypsum-salt rock section.

[0015] Preferably, the paleo-geomorphology of the seismic data, the seismic attributes of the seismic layers of the gypsum-salt rock section and the thickness of the gypsum rock are subjected to least square fitting processing.

[0016] Preferably, the method for classifying the processing results is as follows:

[0017] When θβ≥αmax, the thickness of gypsum salt rock is α1;

[0018] When αmin<θβ<αmax, the thickness of gypsum salt rock is taken as θβ;

[0019] When 0.5<θβ<αmin, the thickness of gypsum salt rock is taken as θα;

[0020] Among them, α is the paleo-geomorphology of seismic data, β is the seismic attribute of the seismic horizon of the gypsum-salt rock section, θ is the thickness of the gypsum-salt rock, αmax is the minimum value of the paleo-geomorphology of seismic data, αmin is the maximum value of the paleo-geomorphology of seismic data, θα is the thickness of the gypsum-salt rock of the paleo-geomorphology of seismic data, and θβ is the thickness of the gypsum-salt rock of the seismic attribute of the seismic horizon of the gypsum-salt rock section.

[0021] Preferably, the gypsum-salt rock thickness values ​​when θβ≥αmax, αmin<θβ<αmax and 0.5<θβ<αmin are integrated to obtain the gypsum-salt rock prediction result.

[0022] Preferably, during the normal deposition of gypsum mudstone, the relationship between the paleo-geomorphology of seismic data and the thickness of the gypsum salt rock is α≥θ.

[0023] The present invention proposes a gypsum-salt rock distribution prediction system based on well-seismic information collaborative constraints, comprising:

[0024] A parameter acquisition module, which is used to obtain seismic data paleo-geomorphology, seismic attributes of seismic layers in gypsum-salt rock sections, and gypsum rock thickness;

[0025] A parameter analysis module, which is used to analyze and process the paleo-geomorphology of seismic data, seismic attributes of seismic layers in the gypsum-salt rock section, and the thickness of the gypsum rock;

[0026] The parameter classification and fusion module is used to classify and fuse the analysis results, obtain the prediction results of gypsum salt rock, and realize the distribution prediction of gypsum salt rock.

[0027] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a method for predicting gypsum-salt rock distribution with coordinated constraints of well-seismic information when executing the computer program.

[0028] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for predicting gypsum-salt rock distribution with coordinated constraints of well-seismic information.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention proposes a method for predicting the distribution of gypsum salt rock with coordinated constraints of well-seismic information. The method analyzes and processes the paleogeography of seismic data, the seismic attributes of the seismic layers of the gypsum salt rock section, and the thickness of the gypsum rock, and then classifies and integrates the processing results to obtain the prediction results of the gypsum salt rock. The prediction method can eliminate the objective limitations of the two existing technical methods to the greatest extent, accurately predict the planar results of the distribution of gypsum salt rock, and has a high degree of consistency with the wells. With this method as the leading factor, a more accurate and detailed prediction of the distribution of gypsum salt rock can be achieved, providing support for further deployment of well locations and drilling projects, optimizing drilling and completion plans based on the prediction results, scientifically guiding density optimization and facility preparation, reducing the rate of missed cards, and ultimately reducing drilling risks and improving the economic benefits of oilfield development.

[0031] The invention proposes a gypsum-salt rock distribution prediction system with coordinated constraints of well-seismic information, which realizes the prediction of gypsum-salt rock distribution by dividing the system into a parameter acquisition module, a parameter analysis module and a parameter classification fusion module. The modular concept is adopted to make each module independent of each other, which is convenient for unified management of each module. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0033] Figure 1 This is a flow chart of the method for predicting gypsum-salt rock distribution with coordinated constraints of well-seismic information of the present invention.

[0034] Figure 2 This is the paleo-geomorphology map before the standard limestone deposition of the present invention.

[0035] Figure 3 This is the preferred property map of the standard limestone section of the present invention.

[0036] Figure 4 This is the predicted distribution map of gypsum salt rock of the present invention.

[0037] Figure 5 This is a diagram of the gypsum-salt rock distribution prediction system based on the coordinated constraints of well-seismic information of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0039] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0041] In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the invention is usually placed when in use, it is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0042] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", which does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0043] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0044] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0045] The present invention proposes a method for predicting the distribution of gypsum-salt rock using coordinated well-seismic information constraints. Figure 1 As shown, the following steps are included:

[0046] S1. Obtain seismic data of paleo-geomorphology, seismic attributes of seismic layers in the gypsum-salt rock section and thickness of gypsum rock;

[0047] The method to obtain paleo-geomorphology from seismic data is as follows:

[0048] The seismic interface after and before the deposition of the gypsum-salt rock section is interpreted from the seismic data, and the paleo-geomorphology before the deposition of the gypsum-salt rock section is obtained using the thickness method.

[0049] The seismic attribute with the highest response of gypsum-salt rock is the seismic attribute of the seismic layer of the gypsum-salt rock section.

[0050] S2. Processing of paleo-geomorphology of seismic data, seismic attributes of seismic layers in gypsum-salt rock sections, and thickness of gypsum rock;

[0051] The least squares fitting method was used to fit the paleo-geomorphology of seismic data, seismic attributes of seismic layers in the gypsum-salt rock section, and the thickness of the gypsum rock.

[0052] S3. Classify and integrate the processing results to obtain the prediction results of gypsum salt rock and realize the distribution prediction of gypsum salt rock.

[0053] The method for classifying the processing results is as follows:

[0054] When θβ≥αmax, the thickness of gypsum salt rock is α1;

[0055] When αmin<θβ<αmax, the thickness of gypsum salt rock is taken as θβ;

[0056] When 0.5<θβ<αmin, the thickness of gypsum salt rock is taken as θα;

[0057] Among them, α is the paleo-geomorphology of seismic data, β is the seismic attribute of the seismic horizon of the gypsum-salt rock section, θ is the thickness of the gypsum-salt rock, αmax is the minimum value of the paleo-geomorphology of seismic data, αmin is the maximum value of the paleo-geomorphology of seismic data, θα is the thickness of the gypsum-salt rock of the paleo-geomorphology of seismic data, and θβ is the thickness of the gypsum-salt rock of the seismic attribute of the seismic horizon of the gypsum-salt rock section.

[0058] The gypsum-salt rock thickness values ​​when θβ≥αmax, αmin<θβ<αmax and 0.5<θβ<αmin are integrated to obtain the gypsum-salt rock prediction results.

[0059] During the normal deposition of gypsum mudstone, the relationship between the paleo-geomorphology of seismic data and the thickness of gypsum salt rock is α≥θ.

[0060] The steps of the prediction method are described in detail below with reference to the accompanying drawings:

[0061] First, depict paleo-geomorphology based on seismic data: conduct detailed interpretation of the stratigraphic positions of the gypsum-salt rock section, first interpret the seismic interface (top interface) after the deposition of the gypsum-salt rock section and the seismic interface (bottom interface) before the deposition of the gypsum-salt rock section based on the seismic data, and then use the thickness method to obtain the paleo-geomorphology before the deposition of the gypsum-salt rock section. Therefore, the paleo-geomorphology data is used as the input feature data α for the next step.

[0062] Second, the seismic attributes of the interpreted gypsum-salt rock section are extracted, and a seismic attribute with the highest response to the gypsum-salt rock is selected. At the same time, statistics are collected on the situation of gypsum-salt rock encountered in the wells drilled in the work area, and the macroscopic range of the gypsum-salt rock distribution is depicted by combining paleo-geomorphology and seismic attributes. Therefore, the seismic attribute data is used as the characteristic data β.

[0063] Third, combined with the first two steps, since the actual pinch-out point of the gypsum-salt rock is between the two gypsum-salt rock characterization methods, it is necessary to perform least squares fitting on the statistical gypsum-salt rock thickness θ, paleo-geomorphology α and the selected seismic attribute β, respectively, in order to solve the low seismic signal-to-noise ratio and low resolution of the gypsum-salt rock distribution, and finely characterize the pinch-out line of the gypsum-salt rock in the thinning area of ​​the gypsum-salt rock to obtain the final predicted distribution map of the gypsum-salt rock.

[0064] This method uses the least square method for fitting. The plane attributes can be calculated using linear relationships and converted into plane θβ values; the plane attributes can be calculated using nonlinear relationships and converted into plane θα values.

[0065] In the normal sedimentation process, the relationship between the stratum and the gypsum thickness should be α≥θ, so the distribution range of gypsum should be analyzed by classification:

[0066] When θβ≥αmax, the value is α, and its geophysical meaning is that the gypsum is completely deposited and filled in this section of the stratum, and the stronger attribute value is due to the change in the rock physical properties caused by the crystallization mode of the gypsum salt rock, which leads to the enhancement of rock velocity and attribute value;

[0067] When αmin<θβ<αmax, the value is θβ, and its geophysical significance is: a relatively accurate quantitative prediction result at seismic resolution;

[0068] When 0.5<θβ<αmin, the value is θα. Its geophysical significance is: the prediction result of gypsum rock under the influence of seismic tuning thickness. The thickness of gypsum-salt rock below 0.5m is too low, the seismic signal-to-noise ratio is low, the geophysical prediction effect is poor, and the impact on drilling engineering is small. Therefore, 0.5m is taken as the lowest cutoff value.

[0069] Fourth, plane data fusion

[0070] The thickness of gypsum salt rock in the three cases is superimposed and fused to obtain the predicted distribution map of gypsum salt rock, as shown in Figure 4 The results are shown in Figure 2 and verified by using post-test wells.

[0071] Taking the early warning work of a well in a certain area of ​​the Tarim Basin as an example (the target layer for clastic rock drilling in this area is the thin sand layer of the middle mudstone section of the Carboniferous System and the Donghe sandstone), the risk of encountering gypsum salt rock in the WELL12 well is predicted by the method of the present invention. The process and results of this embodiment are as follows:

[0072] 1) Statistics on the thickness of gypsum-salt rock encountered in the Carboniferous standard limestone section of the wells drilled in the work area;

[0073] 2) Conduct detailed interpretation of the stratigraphic positions of the gypsum-salt rock section. First, interpret the seismic interface after deposition (top interface) and the seismic interface before deposition (bottom interface) of the gypsum-salt rock section on the seismic data. The interpretation density is 1X1, and the top and bottom interfaces are subtracted to obtain the paleo-geomorphology before deposition, such as Figure 2 As shown;

[0074] 3) Extract the plane attributes of seismic amplitude using the interpreted seismic horizon of the gypsum-salt rock section, and perform cross-plot analysis using the well statistics of gypsum-salt rock thickness and the attribute values ​​at the well points on the plane map to select the best attributes. The seismic attribute that best matches the prediction of gypsum-salt rock distribution in this area is the seismic instantaneous frequency attribute, such as Figure 3 As shown;

[0075] 4) The selected seismic attributes are integrated with the paleo-geomorphology, and then the intersection force fitting analysis is performed with the statistical thickness of the gypsum salt rock encountered in the drilled wells to determine the threshold value of the integrated attributes of the gypsum salt development, and the plane distribution prediction map of the gypsum salt development is drawn based on this, such as Figure 4 shown.

[0076] 5) Based on the plane prediction results, the drilling risk of WELL12 was effectively predicted and an early warning was made in the PPT. The actual drilling results were consistent with the prediction.

[0077] The present invention proposes a gypsum-salt rock distribution prediction system based on well-seismic information collaborative constraints, such as Figure 5 As shown, it includes a parameter acquisition module, a parameter parsing module and a parameter classification fusion module;

[0078] The parameter acquisition module is used to obtain seismic data paleo-geomorphology, seismic attributes of seismic layers in gypsum-salt rock sections, and thickness of gypsum rock;

[0079] The parameter analysis module is used to analyze and process the paleo-geomorphology of seismic data, seismic attributes of seismic layers in the gypsum-salt rock section, and the thickness of the gypsum rock;

[0080] The parameter classification and fusion module is used to classify and fuse the analysis results, obtain the gypsum salt rock prediction results, and realize the gypsum salt rock distribution prediction.

[0081] The terminal device provided in an embodiment of the present invention comprises: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0082] The computer program may be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to accomplish the present invention.

[0083] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0084] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0085] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0086] If the module / unit integrated in the terminal device is implemented in the form of 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 present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0087] The present invention proposes a method for predicting the distribution of gypsum-salt rock with coordinated constraints of well-seismic information, which can eliminate the objective limitations of the previous two technical methods to the greatest extent, accurately predict the planar results of the distribution of gypsum-salt rock, and have a high degree of fit to the wells. With this method as the main guide, a more accurate and detailed prediction of the distribution of gypsum-salt rock has been achieved in Oilfield A, providing strong support for the further deployment of well sites and drilling projects. Based on the prediction results, the drilling and completion plans are optimized, and scientific guidance is given to density optimization and facility preparation, reducing the leakage rate, ensuring that the cementing qualification rate reaches the 70% red line, and the average single well engineering cost savings are much lower than before, providing strong support for the further deployment of well sites and comprehensive management in Oilfield A.

[0088] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for predicting the distribution of gypsum-salt rock based on the coordinated constraints of wellbore and seismic information. It is characterized in that The steps include: Obtain seismic data paleo-geomorphology, seismic attributes of seismic horizons in gypsum-salt rock sections, and thickness of gypsum rocks; Analyze and process the paleo-geomorphology of seismic data, seismic attributes of seismic layers in gypsum-salt rock sections, and thickness of gypsum rocks; The processing results are classified and integrated to obtain the prediction results of gypsum-salt rock and realize the prediction of gypsum-salt rock distribution.

2. The method for predicting gypsum-salt rock distribution based on well-seismic information collaborative constraints according to claim 1, It is characterized in that The method to obtain paleo-geomorphology from seismic data is as follows: The seismic interface after and before the deposition of the gypsum-salt rock section is interpreted from the seismic data, and the paleo-geomorphology before the deposition of the gypsum-salt rock section is obtained using the thickness method.

3. The method for predicting gypsum-salt rock distribution based on well-seismic information collaborative constraints according to claim 1, It is characterized in that The seismic attribute with the highest response of gypsum-salt rock is the seismic attribute of the seismic layer of the gypsum-salt rock section.

4. The method for predicting gypsum-salt rock distribution based on well-seismic information collaborative constraints according to claim 1, It is characterized in that The least squares fitting method was used to fit the paleo-geomorphology of seismic data, seismic attributes of seismic layers in the gypsum-salt rock section, and the thickness of the gypsum rock.

5. The method for predicting gypsum-salt rock distribution based on well-seismic information collaborative constraints according to claim 1, It is characterized in that The method for classifying the processing results is as follows: When θβ≥αmax, the thickness of gypsum salt rock is α1; When αmin<θβ<αmax, the thickness of gypsum salt rock is taken as θβ; When 0.5<θβ<αmin, the thickness of gypsum salt rock is taken as θα; Among them, α is the paleo-geomorphology of seismic data, β is the seismic attribute of the seismic horizon of the gypsum-salt rock section, θ is the thickness of the gypsum-salt rock, αmax is the minimum value of the paleo-geomorphology of seismic data, αmin is the maximum value of the paleo-geomorphology of seismic data, θα is the thickness of the gypsum-salt rock of the paleo-geomorphology of seismic data, and θβ is the thickness of the gypsum-salt rock of the seismic attribute of the seismic horizon of the gypsum-salt rock section.

6. The method for predicting gypsum-salt rock distribution based on well-seismic information collaborative constraints according to claim 5, It is characterized in that The gypsum-salt rock thickness values ​​when θβ≥αmax, αmin<θβ<αmax and 0.5<θβ<αmin are integrated to obtain the gypsum-salt rock prediction results.

7. The method for predicting gypsum-salt rock distribution based on well-seismic information collaborative constraints according to claim 5, It is characterized in that During the normal deposition of gypsum mudstone, the relationship between the paleo-geomorphology of seismic data and the thickness of gypsum salt rock is α≥θ.

8. A gypsum-salt rock distribution prediction system based on well-seismic information collaborative constraints. It is characterized in that include: A parameter acquisition module, which is used to obtain seismic data paleo-geomorphology, seismic attributes of seismic layers in gypsum-salt rock sections, and gypsum rock thickness; A parameter analysis module, which is used to analyze and process the paleo-geomorphology of seismic data, seismic attributes of seismic layers in the gypsum-salt rock section, and the thickness of the gypsum rock; The parameter classification and fusion module is used to classify and fuse the analysis results, obtain the prediction results of gypsum salt rock, and realize the distribution prediction of gypsum salt rock.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program. It is characterized in that When the processor executes the computer program, the steps of the method for predicting the distribution of gypsum-salt rock with coordinated constraints of well-seismic information are implemented as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program. It is characterized in that When the computer program is executed by a processor, the steps of the method for predicting gypsum-salt rock distribution with coordinated constraints of well-seismic information are implemented as described in any one of claims 1 to 7.

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