Geological analysis parameter protection method and system based on logarithm mapping

Abstract

The invention provides a geological analysis parameter protection method and system based on logarithm mapping, and relates to the technical field of geological exploration data protection, and the method comprises the steps: obtaining an original R parameter, building a linear mapping relation g = aR + b, building logarithm transformation mapping based on the linear mapping relation, converting the original parameter into a transformed parameter value, and obtaining a parameter value; and the transformed parameter values are provided for the data processing party for geological exploration operation, and the data owner recovers the original parameters through an inverse transformation formula after receiving the data obtained by exploration of the data processing party. According to the method, through logarithm transformation, an exploration company cannot identify the stratum type through conventional linear fitting, and sensitive geological information is effectively protected; meanwhile, irreversibility of the transformation process is ensured by adopting random parameters, and a data owner can completely recover original geological parameters through an inverse transformation formula; on the premise of protecting the data security, the normal exploration operation flow and the data processing precision are not influenced.

Description

Technical Field

[0001] This invention relates to the field of geological exploration data protection technology, specifically to a method and system for protecting geological analysis parameters based on logarithmic mapping. Background Technology

[0002] In the application scenario of AVO (Amplitude as Offset) analysis, commonly used in geological exploration, when oil companies commission external exploration companies to conduct seismic exploration, the exploration companies typically collect, process, and submit geophysical data of the target area based on the contract. However, because exploration companies possess core algorithms and technical analysis capabilities during data processing, they may realize data value conversion without the oil companies' knowledge in the following ways: 1) Anonymizing exploration data and integrating it into their own database for training AI models or optimizing inversion algorithms to enhance their commercial service capabilities for other projects; 2) Linking data features with geological information from other regions to form covert cross-regional commercial insights; 3) Providing indirect exploration clues for potential blocks to third parties in a non-directly related manner in the gray area of ​​industry data transactions. Such behavior may infringe on data sovereignty boundaries and needs to be constrained by intellectual property ownership clauses in contracts and data anonymization technical specifications. Existing data protection mechanisms cannot effectively prevent exploration service providers from obtaining these sensitive geological parameters. Traditional data anonymization techniques are mainly aimed at personal privacy information and are difficult to apply to the special nature of geological exploration data. While simple data encryption can protect data transmission security, decryption is still required during data processing and analysis, posing a risk of information leakage. Furthermore, current technologies lack specific protection mechanisms for geological parameters, failing to effectively prevent external service providers from obtaining raw geological information while ensuring the normal operation of exploration activities.

[0003] Furthermore, existing data processing methods typically require data owners and processors to share the same processing algorithms and parameter settings, which further increases the risk of data leakage. In the absence of effective protection mechanisms, mining rights holders are often in a passive position due to information asymmetry, making it difficult to effectively safeguard their data sovereignty and commercial interests. This situation may not only infringe upon the boundaries of data sovereignty but may also lead to economic losses from exploration investments and the loss of strategic advantages. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for protecting geological analysis parameters based on logarithmic mapping that can effectively prevent external service providers from obtaining original geological information, reduce the risk of data leakage, protect data security, and at the same time, not affect the normal exploration operation process and data processing accuracy.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A method for protecting geological analysis parameters based on logarithmic mapping includes the following steps: S1: Obtain the original Parameters, the original The parameters are the amplitude variation parameters with offset distance in AVO analysis during geological exploration; S2: Based on the original R parameters, construct a linear mapping relationship g = aR + b, where a and b are random parameters preset by the data owner; S3: Based on the aforementioned linear mapping relationship, establish a logarithmic transformation mapping f(R) = ln(g) = ln(aR + b), which transforms the original... The parameters are converted into transformed R parameter values; S4: Provide the transformed R parameter values ​​to the data processing team for geological exploration operations to obtain exploration data; S5: After receiving the exploration data obtained by the data processor, the data owner uses the inverse transformation formula. restore the original The parameters are y, where y is the transformed R parameter value.

[0006] Furthermore: In step S2, the random parameters a and b satisfy aR+b>0 and b>|a|.

[0007] Further: In step S3, the formula used for the logarithmic transformation is f(R) = ln(g) = ln(aR + b).

[0008] Furthermore: In step S2, random parameters a and b are generated by a random number generator, and independent parameter combinations are generated for different exploration tasks.

[0009] Further: In step S3, the logarithmic transformation mapping uses a variable base, and the transformation mapping formula is f(R) = log n (g) = log n (aR + b), where n is a positive number greater than 1.

[0010] Further: In step S5, the inverse transformation formula is as follows: , where n is the base corresponding to the forward transformation.

[0011] Furthermore: In step S2, for distributed exploration scenarios, independent combinations of parameters a and b are assigned to different work areas or time nodes.

[0012] Further: In step S4, the transformed parameter value is transmitted to the data processing party through an encrypted channel.

[0013] Furthermore: Following step S5, a parameter verification step is also included: the data owner verifies the original data being recovered. The parameters are verified by determining the stratigraphic type to ensure the accuracy of the parameter recovery.

[0014] A geological analysis parameter protection system based on logarithmic mapping includes a parameter acquisition module, a mapping construction module, a transformation processing module, a data transmission module, and an inverse transformation module; The parameter acquisition module is used to acquire the original... Parameters; the mapping construction module is used to construct a linear mapping relationship g = aR + b, where a and b are preset random parameters; the transformation processing module is used to perform a logarithmic transformation mapping f(R) = ln(g) = ln(aR + b), transforming the original... The parameters are converted into transformed parameter values; the data transmission module is used to provide the transformed parameter values ​​to the data processor and to receive the data obtained by the data processor from exploration; the inverse transformation module is used to apply the inverse transformation formula... restore the original parameter.

[0015] Furthermore, the mapping construction module includes a random number generation unit to generate independent combinations of parameters a and b for different exploration tasks.

[0016] Furthermore: the transformation processing module supports logarithmic transformations with variable bases, the transformation mapping being f(R) = log n (aR + b), where n is the logarithmic base, and the formula used for the inverse transform is: , where n is the base corresponding to the forward transformation.

[0017] Furthermore, it also includes a parameter management module for storing and managing parameters a, b, and the logarithmic base corresponding to different exploration tasks.

[0018] Compared with the prior art, the present invention has the following advantages: I. This invention constructs a linear mapping relationship g = aR + b and a logarithmic transformation mapping f(R) = ln(aR + b) to transform the original... The linear characteristics of the parameters are transformed into a nonlinear distribution, making it impossible for exploration companies to use the conventional Shuey approximation formula. = R0 + G·sin²θ is used for linear fitting, thereby completely blocking external service providers from accessing the system. The parameters' ability to identify formation type and reservoir fluids, after logarithmic transformation, The values ​​are mapped to completely different numerical ranges, effectively protecting sensitive geological information from being leaked.

[0019] Second, this invention employs random parameters a and b preset by the data owner and supports generating independent parameter combinations for different exploration tasks, ensuring the irreversibility of the transformation process and the confidentiality of the parameters. Exploration companies can only obtain data that has undergone logarithmic transformation; due to the lack of key transformation parameters, they cannot reverse-engineer the original data. The value. Meanwhile, the mining rights company can fully recover the original geological parameters using the inverse transformation formula, ensuring the accuracy of the data recovery.

[0020] Third, this invention protects data security without affecting normal exploration operations and data processing accuracy. The transformed parameter values ​​maintain numerical continuity and processability, allowing exploration companies to continue data acquisition, processing, and analysis as normal, while mining rights companies obtain the original data through inverse transformation. The parameters fully conform to the laws of geology and physics, enabling accurate determination of stratigraphic type and reservoir evaluation, thus achieving an organic balance between data protection and exploration efficiency. Attached Figure Description

[0021] Figure 1 A flowchart of a geological analysis parameter protection method based on logarithmic mapping provided by the present invention; Figure 2 A schematic diagram of a geological analysis parameter protection system based on logarithmic mapping provided by the present invention; Figure 3 To describe the original using a linear model A diagram illustrating the parameters; Figure 4 This is a schematic diagram illustrating the impact of using different ab parameters on the final result; Figure 5 This is a schematic diagram comparing the results of the linear model extracted after conversion by this invention with the original model. Detailed Implementation

[0022] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1 like Figure 1 As shown: This invention provides a method for protecting geological analysis parameters based on logarithmic mapping, including the steps of obtaining original parameters, constructing a linear mapping relationship, establishing a logarithmic transformation mapping, providing transformed parameter values, and restoring the original parameters. Specifically, in the AVO analysis process, the mining rights company first obtains the original parameters using seismic exploration equipment. The parameters, namely the amplitude variation with offset, are then used by the mining rights company to preset random parameters a and b, for example, a = 3.2 and b = 1.8, to construct a linear mapping relationship g = aR + b. Subsequently, based on the linear mapping relationship, a logarithmic transformation mapping f(R) = ln(aR + b) is established to transform the original... The parameters are converted into transformed parameter values, which the mining rights company then provides to the exploration company for geological exploration. After the exploration company completes data processing, the mining rights company uses the inverse transformation formula... Restore the original Parameters. This invention, through logarithmic mapping transformation technology, effectively prevents external exploration companies from obtaining accurate geological information while ensuring that data owners can fully recover the original data, thus protecting the data assets and potential commercial interests of mining rights companies.

[0024] In one specific implementation of this embodiment, the random parameters a and b in step S2 satisfy the constraints aR+b>0 and b>|a|. Specifically, the constraint aR+b>0 ensures the validity of the domain of the logarithmic function, preventing mathematical calculation errors caused by negative or zero values. The constraint b>|a| guarantees the numerical stability of the transformation, preventing numerical overflow or loss of calculation precision caused by extreme parameter values. The establishment of these constraints ensures the mathematical validity and computational stability of the logarithmic transformation, providing a fundamental guarantee for the reliability of the entire data protection scheme.

[0025] In one specific implementation of this embodiment, the specific formula used for the logarithmic transformation in step S3 is f(R) = ln(aR + b). Specifically, the derivative of the natural logarithm function ln is 1 / x, and its integral form is relatively simple, facilitating numerical calculation and theoretical analysis. After applying the natural logarithm transformation, the original... Linear relationship with sin²θ ≈ R0 + G·sin²θ is transformed into a nonlinear relationship between ln(aR + b) and sin²θ, which effectively disrupts the conventional linear fitting mode of AVO analysis, changes the numerical characteristics and distribution patterns of the original data, and makes it impossible for exploration companies to extract effective R0 and G parameters through conventional linear regression methods, thereby protecting key geological information.

[0026] In one specific implementation of this embodiment, the random parameters a and b in step S2 are generated using a random number generator, and independent parameter combinations are generated for different exploration tasks. Specifically, the mining rights company uses a pseudo-random number generation algorithm to generate parameters, ensuring the randomness and unpredictability of the generated parameters. The mining rights company assigns a unique task identifier to each exploration project and generates a corresponding parameter combination. The system maintains a historical record of parameter generation to avoid parameter reuse and provides a parameter strength assessment function to ensure that the generated parameter combinations meet safety requirements. This effectively prevents data correlation analysis between different projects. Even if the exploration company obtains transformed data from multiple projects, it cannot deduce the transformation pattern through statistical analysis or machine learning methods, greatly improving the security of data protection.

[0027] In one specific embodiment of this example, the logarithmic transformation mapping in step S3 uses a variable base, and the transformation mapping formula is f(R) = log n (aR + b), where n is a positive number greater than 1. Specifically, using a variable base further enhances the complexity of the transformation and improves security. Even if parameters a and b are partially leaked, attackers still cannot accurately recover the original data. Different base choices produce significantly different numerical distributions; the transformation values ​​produced by base 2 are generally greater than those produced by base 10, completely altering the data distribution characteristics. Mining companies can choose different bases according to different security level requirements. This variable base design greatly increases the difficulty of cracking and provides a more flexible and secure technical means for geological data protection.

[0028] In one specific embodiment of this example, the inverse transformation formula corresponding to the variable base in step S5 is: , where n is the base corresponding to the forward transformation. Specifically, the variable base inverse transformation mechanism ensures that the mining rights company can accurately recover the original geological parameters, providing a reliable data foundation for subsequent AVO analysis and stratigraphic determination.

[0029] In one specific implementation of this embodiment, step S2 assigns independent combinations of parameters a and b to different work areas or time nodes for distributed exploration scenarios, effectively preventing data correlation analysis between regions or time series. Even if some parameters are leaked, it will not affect the data security of other regions or time periods, greatly improving the robustness of overall data protection.

[0030] In one specific implementation of this embodiment, the transformed parameter value in step S4 is transmitted to the data processor via an encrypted channel. Specifically, digital signatures are used during data transmission to ensure the authenticity and non-repudiation of the data. Fragmentation technology is employed during transmission, breaking down the large dataset into multiple smaller blocks for transmission. Each data block uses an independent encryption key, further reducing the risk of data leakage. Encrypted transmission and logarithmic transformation form a double security barrier; even if network transmission is intercepted, attackers will only obtain the double-protected data and will not be able to acquire any valuable geological information.

[0031] In one specific embodiment of this example, a parameter verification step is included after step S5, whereby the data owner verifies the original data being recovered. The parameters are verified for stratigraphic type identification to ensure the accuracy of parameter recovery. Specifically, the verification process includes checking the physical rationality of the AVO analysis, verifying whether the recovered R0 and G parameters conform to geophysical laws, such as checking whether the R0 value is within a reasonable range of reflection coefficients and whether the G value is consistent with known rock physical characteristics. This ensures the accuracy of data transfer during transformation and inverse transformation processes, providing reliable data for subsequent geological analysis and decision-making.

[0032] Example 2 The present invention also provides a geological analysis parameter protection system based on logarithmic mapping, including a parameter acquisition module, a mapping construction module, a transformation processing module, a data transmission module, and an inverse transformation module.

[0033] Specifically, the parameter acquisition module obtains raw data through a standard seismic data interface. It provides parameters and data quality check functions to ensure the integrity and validity of input data.

[0034] The mapping construction module is used to construct a linear mapping relationship g = aR + b, where a and b are preset random parameters.

[0035] The transformation processing module is used to perform the logarithmic transformation mapping f(R) = ln(g) = ln(aR + b), transforming the original... The parameters are converted into transformed parameter values.

[0036] The data transmission module is responsible for exchanging data with external exploration companies, while the inverse transformation module uses the inverse transformation formula after receiving the processing results. Perform parameter restoration to ensure the complete restoration of the original geological information.

[0037] The system adopts a modular design, with each module connected through a standard data transmission interface, which facilitates system deployment, maintenance, and functional expansion.

[0038] In one specific embodiment of this example, the mapping construction module further includes a random number generation unit to generate independent combinations of parameters a and b for different exploration tasks.

[0039] In one specific embodiment of this example, the transformation processing module supports logarithmic transformations with variable bases, the transformation mapping being f(R) = log n (aR + b), where n is the logarithmic base, and the formula used in the inverse transformation process is: , where n is the base corresponding to the forward transformation. This variable base design makes the data protection scheme more flexible and secure, and can adapt to the specific needs of different types of exploration projects.

[0040] In one specific embodiment of this example, the system further includes a parameter management module for storing and managing parameters a, b, and the logarithmic base corresponding to different exploration tasks, thereby further improving the modularity of the system.

[0041] It should be noted that, As crucial raw data for AVO analysis, it can be obtained from seismic data. In actual geological exploration, exploration companies typically rely on data acquired from seismic data... Data, fitted using the Shuey approximation formula from multi-angle seismic amplitude data. R 0 and G:

[0042] Based on this formula, geological prospectors can... Assess geological features as shown in the table below. Example of correspondence:

[0043] Geologists can extract from exploration data The original model was created and the geological conditions were inferred from the model. This invention will... After conversion, it can be freely modified according to a and b randomly selected by the mining rights company. The range, thus affecting the acquisition of each exploration. Value, and through The extracted linear relationship results.

[0044] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All equivalent transformations or modifications made in accordance with the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for protecting geological analysis parameters based on logarithmic mapping, characterized in that: Includes the following steps: S1: Obtain the original R parameters, which are the amplitude variation parameters of AVO analysis in geological exploration as a function of offset distance; S2: Based on the original R parameters, construct a linear mapping relationship g = aR + b, where a and b are random parameters preset by the data owner; S3: Based on the linear mapping relationship, establish a logarithmic transformation mapping f(R) = ln(g) = ln(aR + b) to convert the original R parameters into transformed R parameter values; S4: Provide the transformed R parameter values ​​to the data processing team for geological exploration operations to obtain exploration data; S5: After receiving the exploration data obtained by the data processor, the data owner uses the inverse transformation formula. , restore the original R parameters, where y is the transformed R parameter value.

2. The method for protecting geological analysis parameters based on logarithmic mapping according to claim 1, characterized in that: In step S2, the random parameters a and b satisfy aR+b>0 and b>|a|.

3. The method for protecting geological analysis parameters based on logarithmic mapping according to claim 1, characterized in that: In step S3, the formula used for the logarithmic transformation is f(R) = ln(g) = ln(aR + b).

4. The method for protecting geological analysis parameters based on logarithmic mapping according to claim 1, characterized in that: In step S2, random parameters a and b are generated by a random number generator, and independent parameter combinations are generated for different exploration tasks.

5. A method for protecting geological analysis parameters based on logarithmic mapping according to claim 1, characterized in that: In step S3, the logarithmic transformation mapping uses a variable base, and the transformation mapping formula is f(R) = logn(g) = logn(aR + b), where n is a positive number greater than 1.

6. The method for protecting geological analysis parameters based on logarithmic mapping according to claim 5, characterized in that: In step S5, the inverse transformation formula is: , where n is the base corresponding to the forward transformation.

7. The method for protecting geological analysis parameters based on logarithmic mapping according to claim 1, characterized in that: In step S2, for distributed exploration scenarios, independent combinations of parameters a and b are assigned to different work areas or time nodes.

8. The method for protecting geological analysis parameters based on logarithmic mapping according to claim 1, characterized in that: In step S4, the transformed parameter values ​​are transmitted to the data processing party through an encrypted channel.

9. The method for protecting geological analysis parameters based on logarithmic mapping according to claim 1, characterized in that: The step S5 is followed by a parameter verification step: the data owner verifies the formation type of the recovered original R parameters to ensure the accuracy of the parameter recovery.

10. A geological analysis parameter protection system based on logarithmic mapping, characterized in that, It includes a parameter acquisition module, a mapping construction module, a transformation processing module, a data transmission module, an inverse transformation module, and a parameter management module; The parameter acquisition module is used to acquire the original R parameters; the mapping construction module is used to construct a linear mapping relationship g = aR + b, where a and b are preset random parameters; the transformation processing module is used to perform a logarithmic transformation mapping f(R) = ln(g) = ln(aR + b), transforming the original... The parameters are converted into transformed parameter values; the data transmission module is used to provide the transformed parameter values ​​to the data processor and to receive the data obtained by the data processor from exploration; the inverse transformation module is used to apply the inverse transformation formula... restore the original parameter; The mapping construction module includes a random number generation unit, which generates independent combinations of parameters a and b for different exploration tasks; The transformation processing module supports logarithmic transformations with variable bases, the transformation mapping being f(R) = logn(aR + b), where n is the logarithmic base, and the corresponding inverse transformation uses the formula: , where n is the base corresponding to the forward transformation; The parameter management module is used to store and manage parameters a, b, and the logarithmic base corresponding to different exploration tasks.

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