Methods, devices and electronic equipment for determining the transfer of oil and gas mining rights

Abstract

This application discloses a method, apparatus, and electronic device for determining the transfer of oil and gas mining rights. The method includes: acquiring multi-dimensional mining rights data through multiple data interfaces during oil and gas exploration and development; determining mineral administration constraints corresponding to the multi-dimensional mining rights data based on statutory renewal rules and area reduction rules, wherein the mineral administration constraints are restrictions corresponding to the exploration area, duration, and transferability of the mining rights; determining the first net present value (NPV) of the mining rights on the development path using a first learning model, and determining the second NPV of the mining rights on the transfer path using a second learning model based on the mineral administration constraints; and determining the transfer determination result of the mining rights based on the first and second NPVs. This application solves the technical problem that related technologies only assess the resource attributes of the mining rights themselves and lack standardized rigid constraints and dual-path value assessment, resulting in insufficient scientific rigor and low accuracy in determining the transfer of mining rights.

Description

Technical Field

[0001] This application relates to the field of oil and gas asset management technology, and more specifically, to a method, apparatus and electronic equipment for determining the transfer of oil and gas mining rights. Background Technology

[0002] In the process of oil and gas exploration and development, mineral rights (including exploration rights and mining rights) are core strategic assets of oil and gas companies. Their rational allocation and dynamic transfer directly affect the company's resource succession capacity, capital utilization efficiency, and compliance risk control. Currently, domestic oil and gas companies mainly rely on the subjective experience of management personnel, combined with limited geological and financial information, to manually determine whether a particular mineral right should continue to be invested in exploration and development, or be transferred through the secondary market or internally. This decision-making process lacks unified technical standards and quantitative basis, and is easily affected by individual cognitive differences, information lag, or policy misunderstandings. As a result, a large number of mineral rights face the risk of mandatory reduction or even expiration of certificates due to failure to promptly identify the rigid constraints of statutory renewal and area reduction. Especially when the remaining validity period of exploration rights is much shorter than the entire exploration and development cycle of the company, blindly investing funds and manpower not only wastes resources but may also cause irreversible economic losses by missing the best transfer window and rendering the assets worthless after the statutory deadline.

[0003] In related technologies, transfer assessments are usually based on a single attribute such as resource reserves, without incorporating multidimensional enterprise endowment information into a unified model, nor establishing a closed-loop judgment process that is automatically executed by a computer system. This makes it impossible to achieve real-time comparison of the value of the two paths of "continued development" and "transfer and monetization" with the same caliber. Problems such as fragmented information, subjective judgment, and high risk of asset loss still exist, resulting in a lack of scientific, efficient, and practical decision-making for mining rights transfer.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This application provides a method, apparatus, and electronic device for determining the transfer of oil and gas mining rights, in order to at least solve the technical problems of insufficient scientific rigor and low accuracy in determining the transfer of mining rights, since related technologies only assess the resource attributes of the mining rights themselves and lack standardized rigid constraints and dual-path value assessment.

[0006] According to one aspect of the embodiments of this application, a method for determining the transfer of oil and gas mining rights is provided, comprising: during the oil and gas exploration and development process, acquiring multi-dimensional mining rights data through multiple data interfaces, wherein the multi-dimensional mining rights data includes enterprise operating status, market change information, and attribute data of the oil and gas mining rights themselves; determining mineral administrative constraints corresponding to the multi-dimensional mining rights data based on the statutory renewal rules and area reduction rules of mining rights, wherein the mineral administrative constraints are restrictions corresponding to the exploration area, duration, and transferability of mining rights; determining a first net present value of mining rights on the development path using a first learning model, and determining a second net present value of mining rights on the transfer path using a second learning model based on the mineral administrative constraints; and determining the transfer determination result of mining rights based on the first net present value and the second net present value.

[0007] Optionally, multi-dimensional mining rights data can be obtained through multiple data interfaces, including: obtaining mining rights attribute data throughout the entire lifecycle through a first data interface; obtaining enterprise data on mining rights in multiple dimensions of enterprise operation and management through a second data interface; obtaining market data and policy data corresponding to mining rights through a third data interface; determining the original mining rights data based on the mining rights attribute data, enterprise data, market data, and policy data; and performing data cleaning and standardization on the original mining rights data to obtain multi-dimensional mining rights data.

[0008] Optionally, before determining the mining administrative constraints corresponding to the multidimensional mining rights data based on the statutory renewal rules and area reduction rules for mining rights, the method further includes: determining a mining rights transfer rule base, wherein the mining rights transfer rule base includes mandatory prohibition rules, restrictive rectification rules, and warning risk rules based on mining regulations; verifying the mining rights based on the mining rights transfer rule base to obtain verification results; if the verification results indicate that the mining rights are first-level mining rights, determining that the mining rights can be directly transferred; if the verification results indicate that the mining rights are second-level mining rights, determining that the mining rights can be transferred after rectification, and determining the rectification cost and rectification period of the mining rights, wherein the rectification cost and rectification period will be included in the valuation of the second net present value; if the verification results indicate that the mining rights are third-level mining rights, determining that the mining rights are not transferable.

[0009] Optionally, the mineral administration constraints corresponding to the multidimensional mineral rights data are determined based on the statutory renewal rules and area reduction rules for mineral rights. This includes: analyzing the multidimensional mineral rights data using an effective area decay model based on the statutory renewal rules and area reduction rules to obtain the effective exploration area corresponding to the mineral rights; determining the benchmark transaction value of the mineral rights, and determining the time-limited discount amount corresponding to the mineral rights based on the benchmark transaction value, the statutory renewal rules for mineral rights, and a preset decay coefficient. The time-limited discount amount is used to characterize the depreciation amount of the mineral rights due to their approaching statutory expiration date; determining the time decay factor, which is used to force the cash flow on the development path to zero when the remaining validity period of the mineral rights is less than the enterprise's development cycle; and determining the mineral administration constraints based on the effective exploration area, the time-limited discount amount, and the time decay factor.

[0010] Optionally, a second learning model is used to determine the second net present value of mining rights on the transfer path based on mining policy constraints. This includes: obtaining historical transfer cases corresponding to the mining rights; determining the full-cycle transaction costs of the mining rights; and calculating the benchmark transaction value, full-cycle transaction costs, and time-limited discount amount of the mining rights based on the historical transfer cases using the second learning model to obtain the second net present value of the mining rights on the transfer path. The second learning model is used to quantify the secondary market value of the mining rights.

[0011] Optionally, the method further includes: determining multi-dimensional indicators for the enterprise, wherein the multi-dimensional indicators include at least soft indicators corresponding to the enterprise's technological matching degree, financial adequacy, spatial synergy, strategic fit, and management redundancy; determining a nonlinear adaptation matrix corresponding to the mining rights based on the multi-dimensional indicators, wherein the nonlinear adaptation matrix is ​​used to reflect the enterprise's ability to explore and develop the mining rights; determining the fit between the mining rights and the enterprise based on the nonlinear adaptation matrix; and optimizing the transfer determination result based on the fit to obtain the first transfer determination result.

[0012] Optionally, the method further includes: obtaining uncertainty parameters, wherein the uncertainty parameters are used to represent uncertain parameters appearing in the valuation of the first net present value and the second net present value; determining the joint probability distribution of the uncertainty parameters, wherein the joint probability distribution is used to reflect the degree of nonlinear correlation between the uncertainty parameters; performing Monte Carlo simulation based on the joint probability distribution to generate multiple sets of value samples corresponding to the development path and the transfer path; determining risk indicators based on the value samples, and classifying the risk levels of the development path and the transfer path according to the risk indicators to obtain risk level classification results; and optimizing the first transfer determination result based on the risk level classification results to obtain the second transfer determination result.

[0013] Optionally, the method further includes: obtaining an optimization model containing a multi-objective optimization function, wherein the multi-objective optimization function is used to maximize the net present value between the enterprise and the mining rights, minimize the overall risk between the enterprise and the mining rights, and maximize the enterprise's annual operating cash flow; determining rigid constraints, wherein the rigid constraints include at least one of the following: capital budget constraints, reserve succession constraints, risk ceiling constraints, compliance constraints, and management bandwidth constraints; processing the obtained second transfer determination result through the optimization model to generate a third transfer determination result that satisfies the rigid constraints; and optimizing the third transfer determination result based on the enterprise's operating preference information to obtain the target transfer determination result.

[0014] Optionally, the method further includes: generating a standardized transfer determination report based on the target transfer determination result; determining the parameter fluctuation range, and re-performing the mining rights transfer determination when the mining rights parameters exceed the parameter fluctuation range, and generating a sensitivity analysis report, wherein the mining rights parameters are the relevant parameters in the mining rights transfer determination process; and determining the transfer effect corresponding to the target transfer determination result, and updating the model parameters in the mining rights transfer determination process based on the transfer effect.

[0015] According to another aspect of the embodiments of this application, an oil and gas mining rights transfer determination device is also provided, comprising: an acquisition module, used to acquire multi-dimensional mining rights data through multiple data interfaces during the oil and gas exploration and development process, wherein the multi-dimensional mining rights data includes enterprise operating status, market change information, and attribute data of the oil and gas mining rights themselves; a mining administration constraint module, used to determine mining administration constraint conditions corresponding to the multi-dimensional mining rights data based on the statutory renewal rules and area reduction rules of mining rights, wherein the mining administration constraint conditions are restrictions corresponding to the exploration area, duration, and transferability of mining rights; a determination module, used to determine the first net present value of mining rights on the development path using a first learning model, and to determine the second net present value of mining rights on the transfer path using a second learning model based on the mining administration constraint conditions; and a transfer determination module, used to determine the transfer determination result of mining rights based on the first net present value and the second net present value.

[0016] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory and a processor, wherein the memory is used to store program instructions; and the processor is connected to the memory and used to execute the above-described method for determining the transfer of oil and gas mining rights.

[0017] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, the non-volatile storage medium including a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned oil and gas mining rights transfer determination method by running the computer program.

[0018] According to another aspect of the embodiments of this application, a computer program product is also provided, including computer instructions, which, when executed by a processor, implement the above-described method for determining the transfer of oil and gas mining rights.

[0019] In this embodiment, multi-dimensional mining rights data is acquired through multiple data interfaces during the oil and gas exploration and development process. This multi-dimensional mining rights data encompasses enterprise operating status, market change information, and attribute data of the oil and gas mining rights themselves. Based on the statutory renewal rules and area reduction rules for mining rights, mineral administrative constraints corresponding to the multi-dimensional mining rights data are determined. These constraints are limitations corresponding to the exploration area, duration, and transferability of the mining rights. A first learning model is used to determine the first net present value of the mining rights on the development path, and a second learning model is used based on the mineral administrative constraints. The method determines the second net present value of mining rights along the transfer path; and determines the transfer judgment result of mining rights based on the first and second net present values. This achieves the purpose of dynamically quantifying and comparing the value of mining rights under the two paths of "continued development" and "transfer and realization". This realizes the technical effect of automated and standardized transfer decision-making based on the heterogeneity of enterprise endowment and the rigid constraints of mining administration. In turn, it solves the technical problem that the relevant technology only evaluates the resource attributes of mining rights themselves and lacks standardized rigid constraints and dual-path value assessment, resulting in insufficient scientificity and low accuracy in the determination of mining rights transfer. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0021] Figure 1 This is a hardware structure diagram of a computer terminal for implementing a method for determining the transfer of oil and gas mining rights, according to an embodiment of this application.

[0022] Figure 2 This is a flowchart of a method for determining the transfer of oil and gas mining rights according to an embodiment of this application;

[0023] Figure 3 This is an overall workflow diagram of a method for determining the transfer of oil and gas mining rights according to an embodiment of this application;

[0024] Figure 4 This is a schematic diagram of a mineral administration constraint modeling process according to an embodiment of this application;

[0025] Figure 5 This is a schematic diagram of a dual-path subject value calculation process according to an embodiment of this application;

[0026] Figure 6This is a structural diagram of an oil and gas mining rights transfer determination device according to an embodiment of this application. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] First, some nouns or terms that appear in the explanation of the embodiments of this application shall be interpreted as follows:

[0030] Oil and gas mining rights refer to the legal rights granted by the state to enterprises or individuals to explore or exploit oil and gas resources (such as petroleum and natural gas) within a specific area. These rights are divided into exploration rights and mining rights. Exploration rights allow enterprises to conduct geological surveys and search for oil and gas resources; mining rights, on the other hand, allow commercial exploitation in areas with proven reserves. Mining rights are core assets of oil and gas companies, characterized by scarcity, non-renewability, and strong policy dependence.

[0031] Mining rights transfer: refers to the process by which oil and gas companies transfer their exploration or mining rights to other companies or entities through transfer, allocation, cooperation, or other means. Transfers can be adjustments between subsidiaries within a company (internal transfers) or public transfers to third parties in the market (market-based transactions). The aim is to optimize asset allocation, revitalize existing assets, mitigate risks, or focus on core businesses.

[0032] Statutory Renewal and Area Reduction: Mining rights have a statutory validity period, which can be renewed before expiration. However, each renewal usually requires a reduction in the exploration area (e.g., a 20% reduction). If the number of renewals is exhausted or the area is reduced to the point where effective exploration is impossible, the mining rights will become invalid, and the assets will be worthless. This is the most important "time-area" dual constraint mechanism in mining rights management.

[0033] Monte Carlo simulation: a statistical method that uses computers to generate a large number of random samples to simulate the operating results of complex systems. In this application, through tens of thousands of simulations, all possible exploration and transfer revenue distributions are generated, thereby calculating key indicators such as loss probability and risk value, providing data support for decision-making.

[0034] NSGA-II Algorithm: An advanced multi-objective optimization algorithm used to find the optimal balance point among multiple conflicting objectives. In this application, it simultaneously optimizes three major objectives: maximizing revenue, minimizing risk, and ensuring the most stable cash flow. From multiple combinations of mining rights transfers, it selects the decision scheme that best aligns with the company's overall strategy, thereby avoiding the trap of local optimization where individual mines are optimal but the overall situation is poor.

[0035] Pareto optimal solution set: refers to a set of solutions that cannot be further improved, where any further optimization of a solution would worsen other objectives. For example, increasing returns increases risk, while reducing risk decreases returns. The NSGA-II algorithm outputs this type of optimal compromise combination, from which companies can choose the final solution based on their own preferences (such as conservative or aggressive).

[0036] This application provides a method for determining the transfer of oil and gas mining rights, which can be implemented in... Figure 1 The computer terminal shown is described below.

[0037] The oil and gas mining rights transfer determination method provided in this application can be executed on a mobile terminal, computer terminal or similar computing device. Figure 1 A hardware block diagram of a computer terminal for implementing a method for determining the transfer of oil and gas mining rights is shown. Figure 1As shown, the computer terminal 10 may include one or more processors (shown as 102a, 102b, ..., 102n in the figure) (the processor may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission module 106 for communication functions connected via wired and / or wireless networks. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, and a BUS bus. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0038] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10. As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0039] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the oil and gas mining rights transfer determination method in this embodiment of the application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned oil and gas mining rights transfer determination method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0040] The transmission module 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission module 106 includes a network interface controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission module 106 may be a radio frequency (RF) module, used for wireless communication with the Internet.

[0041] The display can be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10.

[0042] It should be noted here that, in some optional embodiments, the above... Figure 1 The computer terminal shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 1 This is only one instance of a specific particular instance, and is intended to illustrate the types of components that may exist in the aforementioned computer terminal.

[0043] Under the above operating environment, this application provides an embodiment of a method for determining the transfer of oil and gas mining rights. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0044] Figure 2 This is a flowchart of a method for determining the transfer of oil and gas mining rights according to an embodiment of this application, such as... Figure 2 As shown, the method includes the following steps:

[0045] Step S202: During the oil and gas exploration and development process, multi-dimensional mining rights data is obtained through multiple data interfaces. The multi-dimensional mining rights data includes enterprise operating status, market change information, and attribute data of the oil and gas mining rights themselves.

[0046] In step S202 above, the aim is to achieve automated, structured, and verified collection of multi-dimensional data required for the determination of mining rights transfer through dedicated data interfaces (such as API interfaces, web crawlers, etc.) corresponding to multiple independent data sources (such as enterprise systems, market platforms, mining rights official websites). Its essence is to establish an industrial-grade data input system for oil and gas mining rights management, which is the technical foundation and prerequisite guarantee for the entire intelligent decision-making process.

[0047] Step S204: Determine the mining administration constraints corresponding to the multidimensional mining rights data based on the statutory renewal rules and area reduction rules for mining rights. The mining administration constraints are the restrictions corresponding to the exploration area, duration and transferability of mining rights.

[0048] In step S204 above, the aim is to build a machine-executable mining rights transfer rule library based on relevant mining rights regulations, automatically verify the compliance of each exploration mining right, filter out non-compliant or non-transferable mining rights before value assessment, and transform standardized mining rights regulations (such as statutory renewal rules for mining rights and area reduction rules) into quantifiable rigid constraints of mining administration, ensuring that all subsequent economic calculations are based on legal and operable property rights, and preventing the risk of invalid assessment or asset loss due to policy violations from being ignored.

[0049] Step S206: Use a first learning model to determine the first net present value of the mining right on the development path, and use a second learning model to determine the second net present value of the mining right on the transfer path based on mining policy constraints.

[0050] In step S206 above, both the first learning model and the second learning model are quantitative evaluation models built based on industry mechanisms and historical data, possessing parameter adaptive capabilities. They are two structurally independent, functionally specialized, and operationally isolated computer program modules, deployed on two different processor units or computing nodes within the computer system, each independently executing its dedicated data processing task. For example:

[0051] The first learning model is deployed in a dedicated computing unit for exploration and assessment. It can adopt a phased binomial real option model. Its inputs include geological parameters of exploration rights, historical data of enterprise exploration success rate, and oil and gas price fluctuation series. Through the phased binomial real option algorithm, it simulates the full-cycle cash flow path in reverse in an independent thread and outputs the expected net present value of the development path, i.e. the first net present value.

[0052] The second learning model is deployed in a dedicated computing unit for asset transaction evaluation. It can adopt a secondary market-specific value calculation model. Its inputs include mining policy constraints (such as remaining validity period, area reduction ratio, rectification costs), secondary market transaction cases, liquidity discount parameters, etc. Through a comparable transaction correction algorithm, it calculates the risk-corrected net realizable value, i.e., the second net present value, in an independent thread.

[0053] The two do not share computing resources, do not cross-call logic, and do not rely on human intervention. They run in parallel on their own dedicated memory space and processor cores. The central control module uniformly schedules input data, starts calculations, receives results, and summarizes and outputs them in a unified manner. This can decompose complex multi-dimensional evaluation tasks into two independently optimizable computer subtasks, and improve computing efficiency and system stability through a distributed processing mechanism.

[0054] Step S208: Determine the transfer result of the mining rights based on the first net present value and the second net present value.

[0055] In step S208 above, the aim is to transform the economic value comparison into computer-executable control logic, that is, to generate an asset change instruction that can be directly called by the enterprise asset management system based on the transfer determination result.

[0056] In this application embodiment, two parallel transfer modes, namely "external transfer" and "internal transfer", are supported: one is the market-based transfer between oil and gas companies and external third parties, including transfer to other oil and gas companies or professional investment institutions; the other is the transfer of resources between different subsidiaries or business units within oil and gas companies, such as by quantifying the differences in capabilities of each subsidiary and mining rights in terms of technical matching, spatial synergy, and management capacity, to carry out reasonable transfers in order to avoid asset idleness and duplicate investment.

[0057] In this embodiment, the transfer determination result and asset change instruction can be bound to an enterprise-level digital asset platform, and blockchain underlying technology can be introduced to build a trusted circulation system covering the entire chain from decision-making to execution and from registration to evidence storage. The specific implementation is as follows: When the transfer determination result indicates that a mining right should be transferred, a structured digital certificate is generated based on the parameter information corresponding to the mining right (such as mining policy constraints, first net present value, second net present value, etc.), and bound to the unique digital identity of the mining right through encrypted signature. This digital certificate is written to the private blockchain network of the oil and gas company in real time, with multiple potential transferees forming the transfer nodes. Each transfer action, including approval processes, contract signing, and ownership change applications, generates an immutable timestamp record on the chain. Any operation requires multi-node consensus verification to ensure data authenticity, process compliance, and traceability of responsibility. External transferees can access on-chain information through authorization to verify the legal status, historical compliance records, valuation basis, and transfer trajectory of mining rights in real time. During internal transfers, multiple business systems within the enterprise are automatically triggered to update in tandem, synchronously recording operations such as freezing financial budgets, adjusting exploration plans, and redistributing management workloads on the blockchain. All changes are traceable, permissions are controllable, and operations are auditable. Simultaneously, core mining-related data, such as remaining validity period, area reduction ratio, and transfer revenue payment status, are directly connected to the enterprise-level digital asset platform interface and automatically updated by smart contracts, eliminating human error or delays.

[0058] Overall, the embodiments of this application not only realize the scientification of transfer decisions, but also build a digital trust infrastructure for the transfer of mining rights through blockchain technology. This ensures that any transfer between an enterprise and external parties or within an enterprise is based on a solid foundation of reliable technology, transparent processes, and clear ownership. It fundamentally solves the industry pain points of unease and doubt in the traditional model of transfer, and significantly improves the security and credibility of the disposal of mining rights assets.

[0059] Through steps S202 to S208, the goal of dynamically quantifying and comparing the value of mining rights under the two paths of "continued development" and "transfer and monetization" is achieved. This realizes the technical effect of automated and standardized transfer decision-making based on the heterogeneity of enterprise endowments and the rigid constraints of mining regulations. Furthermore, it solves the technical problem of insufficient scientific rigor and low accuracy in mining rights transfer determination, which arises because related technologies only assess the resource attributes of the mining rights themselves and lack standardized rigid constraints and dual-path value assessment. A detailed explanation follows.

[0060] Figure 3 This is an overall workflow diagram of a method for determining the transfer of oil and gas mining rights according to an embodiment of this application. It describes in more detail the process for determining the transfer of mining rights (taking exploration rights as an example) based on the heterogeneity of enterprise endowments and rigid constraints of mining administration, including the following steps:

[0061] Step 1: Multidimensional mining rights data collection and standardization processing.

[0062] Corresponding to step S202 above, specifically, multi-dimensional mining rights data is obtained through multiple data interfaces, including: obtaining mining rights attribute data throughout the entire lifecycle through a first data interface; obtaining enterprise data on mining rights in multiple dimensions of enterprise operation and management through a second data interface; obtaining market data and policy data corresponding to mining rights through a third data interface; determining the original mining rights data based on the mining rights attribute data, enterprise data, market data, and policy data; and performing data cleaning and standardization on the original mining rights data to obtain multi-dimensional mining rights data. The specific process analysis is as follows:

[0063] 1. Automatic collection of multi-dimensional mining rights data.

[0064] First, by connecting to statutory government platforms such as the Mineral Rights Information Disclosure System of the Ministry of Natural Resources through the first data interface, mineral rights attribute data throughout the entire life cycle is automatically obtained, including but not limited to: basic ownership fields (exploration right type, certificate number, initial issued area, issuance date, remaining validity period, number of renewals, statutory maximum number of renewals, area reduction ratio), geological exploration fields (exploration degree, resource reserves, exploration success rate, single well productivity, reservoir characteristics), and compliance status fields (ownership disputes, mortgages and seizures, transfer revenue payment status, and violation records).

[0065] Secondly, by connecting to the internal financial system, exploration project management system, and human resources platform of oil and gas companies through the second data interface, the system automatically obtains five dimensions of enterprise operating data directly related to mining rights, including but not limited to: financial dimension (weighted average cost of capital, financing cost, available funds, exploration budget), technical dimension (exploration success rate of similar blocks of exploration rights, exploration technology level, technical team configuration), strategic dimension (oil and gas type of exploration rights, fit between exploration area and enterprise strategic layout, reserve succession target), management dimension (load rate of existing exploration projects, management team capacity), and collaboration dimension (distance between target exploration rights and existing exploration blocks of the enterprise, reusability of supporting facilities such as pipelines).

[0066] Finally, the third data interface connects to external market and policy databases to automatically obtain market and policy data directly related to mining rights, including but not limited to: oil and gas prices (market average price and fluctuation data of the oil and gas type corresponding to the exploration right), secondary market transaction cases of exploration rights (transaction prices, transaction methods, and transaction costs of similar exploration rights), mining regulations (compliance rules for the transfer of exploration rights, renewal policies, and area reduction policies), and industry cost parameters (exploration costs, construction costs, and transaction tax rates).

[0067] 2. Data cleaning and outlier handling.

[0068] Data cleaning is automatically performed using pre-set computer rules to ensure accuracy: missing values ​​are filled with the median of similar exploration rights data in the same industry, and outliers are removed... The principle is to identify and truncate / correct data (such as daily oil price fluctuations exceeding 10% or abnormally high / low exploration success rates), and to verify the consistency of key data (such as the remaining validity period of exploration rights and ownership status) with the official information published by the Ministry of Natural Resources to avoid data errors.

[0069] 3. Data standardization and normalization processing.

[0070] The cleaned multidimensional mining rights data is standardized to eliminate the influence of dimensions and ensure consistent calculation methods in subsequent calculations.

[0071] For all quantitative indicators, positive and negative attributes are clearly distinguished based on their economic significance: positive indicators, such as exploration success rate, single-well productivity, and net cash flow, have higher values ​​that represent stronger asset value or corporate capabilities. The standard min-max linear normalization method is used to uniformly map their value range to the [0,1] interval. The formula is the original value minus the industry minimum value and then divided by the industry range, ensuring that all positive indicators participate in the calculation on the same scale. Negative indicators, such as financing costs, debt-to-equity ratio, and unit exploration costs, have lower values ​​that are better. The system uses reverse normalization, that is, subtracting the positive normalization result from 1, so that low values ​​correspond to high scores, thereby maintaining a consistent value orientation with positive indicators in the model.

[0072] For non-numerical classification indicators, such as exploration right type (continental, marine, shale gas, etc.), compliance level (A / B / C level), and regional strategic positioning (core / non-core), the system adopts one-hot encoding technology to transform them into multiple binary 0-1 feature variables, forming a sparse matrix input. This allows the model to retain category information without loss and avoids introducing false size relationships due to numerical encoding (such as 1, 2, 3).

[0073] Meanwhile, differentiated update mechanisms are set up for different categories of data, and dynamic management is implemented based on their frequency of change and the intensity of their impact on decision-making: market data such as oil and gas prices, transaction prices, and tax rates are significantly affected by macroeconomic fluctuations and are automatically updated monthly from external interfaces; geological data such as reserve estimates, exploration success rates, and reservoir parameters require on-site exploration verification, so the update cycle is set to quarterly to ensure a balance between data accuracy and collection costs; policy data such as renewal rules, area reduction ratios, and methods for collecting transfer revenue, although changing infrequently, have mandatory force. By establishing a real-time monitoring mechanism with the Ministry of Natural Resources' legal database, once a policy is released, it triggers a reload of parameters across the entire system and automatically notifies relevant mining rights to re-verify.

[0074] In this step, three types of heterogeneous data—mining rights attributes, enterprise operations, and market policies—are acquired through multiple dedicated data interfaces. After being integrated into raw mining rights data, the data undergoes systematic cleaning, anomaly correction, and standardization to form a consistent multidimensional mining rights dataset. This transforms the process from manual, raw information collection to high-precision industrial data input, fundamentally solving the problems of weak judgment basis caused by data silos, inconsistent standards, and delayed updates in traditional mining rights assessment. It provides reliable data support for subsequent quantitative decisions based on enterprise endowments and mining policy constraints, significantly improving the scientific and systematic nature of transfer judgments.

[0075] Step 2: Mineral regulatory constraint modeling and pre-tradability verification, the overall process is as follows: Figure 4 As shown.

[0076] In this embodiment, the pre-verification of tradability includes: determining a mining rights transfer rule base, wherein the mining rights transfer rule base includes mandatory prohibition rules, restrictive rectification rules, and risk warning rules based on mining regulations; verifying the mining rights according to the mining rights transfer rule base to obtain verification results; if the verification result indicates that the mining rights are first-level mining rights, determining that the mining rights can be directly transferred; if the verification result indicates that the mining rights are second-level mining rights, determining that the mining rights can be transferred after rectification, and determining the rectification cost and rectification period of the mining rights, wherein the rectification cost and rectification period will be included in the valuation of the second net present value; if the verification result indicates that the mining rights are third-level mining rights, determining that the mining rights are not transferable. The specific process analysis is as follows:

[0077] 1. Construction of a rule base for the transfer of mining rights.

[0078] Based on relevant laws and regulations concerning mining rights in the industry, a mandatory veto rule (such as exploration rights with disputed ownership, failure to pay transfer revenue, or illegal exploration are prohibited from being transferred), a restrictive rectification rule (such as minor violations that can be transferred after rectification), and a risk warning rule are generated to form a machine-readable mining rights transfer rule library. When policies are adjusted, only parameters need to be updated for iteration.

[0079] 2. Tradeability verification and grading.

[0080] Through a pre-built computer rule engine, the compliance status, remaining validity period, and area reduction of each exploration right are subject to full-element automated joint review. The compliance review process, which originally relied on human experience judgment, is transformed into a traceable and verifiable standardized logical operation, and outputs a three-level tradability rating: Level A (i.e., Level 1 mining right, no compliance defects, can be directly transferred), Level B (i.e., Level 2 mining right, with minor violations, can be transferred after rectification), and Level C (i.e., Level 3 mining right, with mandatory violations or defects that cannot be rectified, cannot be transferred).

[0081] In this application embodiment, the transfer determination of Class C exploration rights is directly excluded, and only Class A and Class B exploration rights are subsequently calculated.

[0082] 3. Quantify the cost and timeframe of rectification.

[0083] For Class B exploration rights, a quantitative modeling mechanism for "rectification costs" and "rectification cycles" is introduced.

[0084] Specifically, based on a database of rectification cases for similar historical exploration rights, the system automatically extracts and analyzes the handling results of past similar violations, such as the amount of administrative penalties, the cost of supplementary geological reports, the interest on transfer revenue, and the time spent on administrative procedures—real expenditure and time data. Through similarity matching and statistical regression algorithms, an automatic rectification cost estimation model is constructed. Subsequently, based on the rectification cost estimation model, the rectification cycle and rectification costs (such as fines and supplementary data costs) corresponding to Class B exploration rights are calculated. The rectification cycle is incorporated into the criteria for determining the timing of transfer, and the rectification cost is included as a rigid expenditure item in the calculation framework of the second net present value of the transfer path. It is deducted alongside transaction taxes, intermediary fees, and liquidity discounts, so that the economic benefits of the transfer after rectification are no longer an idealized estimate, but a net present value result that includes real costs.

[0085] In this embodiment, the mineral regulatory constraint modeling corresponds to step S204 above, which involves determining the mineral regulatory constraints corresponding to the multidimensional mineral rights data based on the statutory renewal rules and area reduction rules for mineral rights. This includes: analyzing the multidimensional mineral rights data using an effective area decay model based on the statutory renewal rules and area reduction rules to obtain the effective exploration area corresponding to the mineral rights; determining the benchmark transaction value of the mineral rights, and determining the time-limited discount amount corresponding to the mineral rights based on the benchmark transaction value, the statutory renewal rules for mineral rights, and a preset decay coefficient, wherein the time-limited discount amount is used to characterize the depreciation amount of the mineral rights due to their approaching statutory expiration date; determining the time decay factor, wherein the time decay factor is used to force the cash flow on the development path to zero when the remaining validity period of the mineral rights is less than the enterprise's development cycle; and determining the mineral regulatory constraints based on the effective exploration area, the time-limited discount amount, and the time decay factor.

[0086] The essence of mineral resource constraint modeling is a systematic approach that deeply integrates national mineral resource management rules into the process of determining the transfer of mineral rights. Its core idea is that the value of mineral rights cannot be determined solely by resource potential or market expectations, but must also be strictly constrained by the dynamic contraction of their legally valid duration and spatial scope. This constraint is not a soft reference, but a hard and rigid valuation premise.

[0087] Specifically, by converting the statutory renewal rules for mining rights and the area reduction rules into rigid constraints and embedding them into the corresponding mathematical model, the following mining policy constraint parameters can be obtained:

[0088] 1. Combining the effective area decay model, the area reduction ratio required for each statutory renewal is transformed into a decreasing function over time. The specific expression is as follows:

[0089]

[0090] In the formula, This indicates the currently valid exploration area of ​​the exploration rights. This indicates the initial area for which exploration rights were granted. This indicates the percentage reduction in the area of ​​a single statutory renewal of a mineral exploration right (e.g., 20%). This indicates the number of times the exploration rights have been renewed.

[0091] 2. Combined with the statutory expiration discount model, this is used to characterize the non-market depreciation caused by the approaching statutory expiration date. The specific expression is as follows:

[0092]

[0093] In the formula, This indicates the time-limited discount amount for exploration rights due to their approaching statutory expiration (insufficient remaining validity period). The higher the discount, the lower the transfer value of the exploration rights. It represents the benchmark transaction value of exploration rights, which is the basis for calculation based on similar exploration rights transaction cases without considering factors such as timeliness and liquidity; This indicates the preset attenuation coefficient, such as the mining constraint attenuation coefficient (a common industry parameter, typically ranging from 0.5 to 1.2). Indicates the maximum number of times a mineral exploration right can be renewed by law (e.g., 3 times); This indicates the number of times the exploration rights have been renewed.

[0094] 3. Introduce an option time decay factor and set a veto mechanism for execution conversion rate: when the remaining validity period of the exploration right is less than the entire cycle of the enterprise's continued exploration and development, the effective cash flow of the development path will be forcibly reduced to zero, and the turnover judgment will be triggered first to prevent ineffective investment and asset loss.

[0095] In the aforementioned process, these three factors collectively constitute a dynamic, non-linear, policy-driven rigid valuation boundary, namely, the mining policy constraint. Only when an exploration right meets the minimum feasibility threshold in all three dimensions is its economic value permitted to exist; once any dimension is breached, the valuation is forcibly corrected or reset to zero. This approach achieves, for the first time, a rigid, endogenous expression of the value of mining rights through mining policy, significantly improving the authenticity and conservatism of the valuation results, and effectively avoiding the risks of overestimating asset value, inducing ineffective investment, and asset loss due to the neglect of policy rigidity in traditional methods.

[0096] Step 3: Value calculation of the two-path entities using the same caliber, the overall process is as follows: Figure 5 As shown.

[0097] In this embodiment of the application, the first learning model is used to determine the first net present value of the mining right on the development path, including: using a phased binomial tree real option model, inputting geological parameters of the exploration right, historical data of the enterprise's exploration success rate, oil and gas price fluctuation series, etc., and using the phased binomial tree real option algorithm to reverse simulate the full-cycle cash flow path in an independent thread, and outputting the expected net present value of the development path, i.e., the first net present value.

[0098] In this embodiment of the application, a second learning model is used to determine the second net present value of mining rights on the transfer path based on mining policy constraints. This includes: obtaining historical transfer cases corresponding to mining rights; determining the full-cycle transaction cost of mining rights; and calculating the benchmark transaction value, full-cycle transaction cost, and time-limited discount amount of mining rights based on historical transfer cases using the second learning model to obtain the second net present value of mining rights on the transfer path. The second learning model is used to quantify the secondary market value of mining rights.

[0099] For example, a secondary market-specific value calculation model is adopted, based on mining policy constraints (benchmark transaction value, time-limited discount amount), deducting the full-cycle transaction costs of mining rights (such as taxes, intermediary fees, rectification costs of Class B mining rights, etc.), and combining strategic synergy premium (such as the strategic fit between the transferee and the exploration rights), and using a comparable transaction correction algorithm, to calculate the risk-corrected net realizable value, i.e., the second net present value.

[0100] Finally, based on the first net present value and the second net present value, the value difference between the "development path" and the "transfer path" is clarified: if the first net present value is higher than the second net present value, it is initially determined to be transferable; otherwise, it is determined to be non-transferable.

[0101] In this step, the two paths achieve fair benchmarking under a unified parameter caliber and an independent thread parallel computer system framework. This breaks through the technical limitations of traditional assessments that rely solely on a single calculation of development value and ignore transfer options, significantly improving the scientific nature, compliance, and resource allocation efficiency of mining rights economic decisions.

[0102] Step 4: Enterprise multi-dimensional feature adaptation and optimization.

[0103] In this embodiment, the core objective of this step is to adapt the general model to the enterprise's personalized customization, construct a nonlinear adaptation matrix of multi-dimensional characteristics of the exploration right enterprise, and thereby correct the decision-making benchmark, i.e., the preliminary transfer judgment result obtained in step 3. The specific implementation is as follows: Determine the enterprise's multi-dimensional indicators, which include at least soft indicators corresponding to the enterprise's technological matching degree, financial sufficiency, spatial synergy, strategic fit, and management redundancy; determine the nonlinear adaptation matrix corresponding to the mining right based on the multi-dimensional indicators, where the nonlinear adaptation matrix reflects the enterprise's ability to explore and develop the mining right; determine the compatibility between the mining right and the enterprise based on the nonlinear adaptation matrix; optimize the transfer judgment result based on the compatibility to obtain the first transfer judgment result. The specific process analysis is as follows:

[0104] 1. Quantitative calculation of enterprise multidimensional characteristics.

[0105] The five key soft metrics of the enterprise are all quantified into fitting factors in the range of [0,1].

[0106] 1) Technology matching degree: Combine the success rate of the enterprise's exploration of similar mineral rights and the degree of fit between the existing technology and the exploration technology requirements of the target mineral rights to quantify the enterprise's technical capability to undertake mineral rights exploration.

[0107] 2) Financial Availability: The ratio of a company's available funds to the funds required for exploration / transaction of mineral rights is used to quantify the company's financial capacity.

[0108] 3) Spatial synergy: Quantify the synergy effect by combining the distance between the target exploration right and the company's existing exploration blocks, as well as the reusability of supporting facilities;

[0109] 4) Strategic Alignment: The cosine similarity algorithm is used to quantify the degree of alignment between the target exploration rights and the company's medium- and long-term exploration and development strategy;

[0110] 5) Management redundancy: Based on the existing exploration project load rate of the enterprise, quantify the enterprise's management capability for undertaking mineral exploration rights.

[0111] 2. Construct a nonlinear fit matrix and calculate the overall fit degree.

[0112] First, a nonlinear adaptation matrix is ​​constructed, and the weights of each dimension (which can be adjusted according to the company's strategy) are combined to calculate the overall fit between the oil and gas company and the target exploration right. The higher the overall fit, the more obvious the company's advantage in holding and developing the exploration right, and the lower the transfer priority; conversely, the lower the overall fit, the higher the transfer priority.

[0113] The core principle is that there are interactive reinforcing or inhibiting effects among the various dimensional factors, and they cannot be linearly superimposed. For example, if a company has a high degree of technological matching but its management redundancy is close to 1 (i.e., full load), its overall capabilities may be severely inhibited; conversely, if both its financial resources and spatial synergy are high, even if its technological matching is moderate, its holding value may be significantly enhanced due to the synergistic amplification effect.

[0114] 3. Optimize the flow determination results.

[0115] The first net present value of the development path is modified by comprehensive suitability to obtain the actual retention subjective utility of the enterprise, that is, the actual value of the enterprise holding the exploration right and continuing to develop it. Then, it is compared with the second net present value of the transfer path to modify the preliminary transfer judgment result: if the actual value is lower than the second net present value, the transferable judgment result is strengthened, and vice versa.

[0116] In this step, a closed-loop operation involving soft index quantification, nonlinear fusion, and subjective utility correction was constructed for the first time, establishing a mathematical expression system for enterprise capability adaptation in mining rights assessment. This not only improves the accuracy of transfer judgment decisions but also enables oil and gas enterprises to possess the intelligent attribute of understanding strategy. It provides an engineerable, traceable, and auditable intelligent decision-making foundation for various oil and gas enterprises to carry out dynamic allocation of mining rights in complex policy and market environments, demonstrating distinct originality and systematic innovation value.

[0117] Step 5: Dynamic risk quantification analysis and optimization of multi-source uncertainty coupling.

[0118] In this embodiment, the core purpose of this step is to accurately quantify the risk levels of the development path and the transfer path, providing risk constraints for the transfer determination. The specific implementation is as follows: Obtain uncertainty parameters, whereby the uncertainty parameters represent the uncertainties occurring in the valuation of the first net present value and the second net present value; determine the joint probability distribution of the uncertainty parameters, whereby the joint probability distribution reflects the degree of nonlinear correlation between the uncertainty parameters; perform Monte Carlo simulation based on the joint probability distribution to generate multiple sets of value samples corresponding to the development path and the transfer path; determine risk indicators based on the value samples, and classify the risk levels of the development path and the transfer path according to the risk indicators to obtain the risk level classification results; optimize the first transfer determination result based on the risk level classification results to obtain the second transfer determination result. The specific process analysis is as follows:

[0119] 1. Uncertainty parameter classification and marginal distribution fitting.

[0120] First, all uncertainties in the development and transfer paths are categorized: geological parameters (such as original resource reserves and exploration success rate), market fluctuation parameters (such as international oil and gas price series and unit exploration cost fluctuations), and transaction policy parameters (such as transaction tax rates and secondary market liquidity discount rates). Then, the optimal marginal distributions of each uncertainty parameter are fitted using the KS test (e.g., resource reserves may follow a log-normal distribution, exploration success rate follows a Beta distribution, oil and gas prices follow a generalized error distribution, while liquidity discount rates may exhibit a truncated normal or mixed distribution), laying the foundation for subsequent multi-parameter coupled modeling.

[0121] 2. Constructing a joint distribution based on the Copula function.

[0122] By constructing a joint distribution of all uncertain parameters using the Gaussian-Copula function, we can accurately capture the nonlinear correlations between parameters (such as the positive correlation between oil and gas prices and exploration costs, and the negative correlation between mineral policy adjustments and liquidity discounts), thus restoring the real risk linkage effect of exploration rights transfer and overcoming the shortcomings of the traditional parameter independence assumption.

[0123] 3. Perform Monte Carlo simulation.

[0124] In the Monte Carlo simulation phase, based on the joint distribution constructed above, a large-scale sampling (no less than 10,000 simulations) is performed in a high-dimensional random space using a computer. The value realization sequence of each path (development path and transfer path) under different risk scenarios is generated one by one to capture the probability distribution characteristics of the dual-path value and obtain a massive number of dual-path value samples.

[0125] This process is not a simple repetitive calculation, but rather ensures the statistical stability of the sampling results through a parallel computing architecture and convergence criterion control. For example, when the changes in the Value at Risk (VaR) and Conditional Value at Risk (CVaR) generated by several consecutive simulations are less than a preset threshold (such as 0.5%), the simulation is determined to have converged and the operation is terminated.

[0126] 4. Optimization of risk indicator calculation and transfer judgment results.

[0127] The following four core risk indicators are extracted from the massive value samples generated by simulation: probability of loss (i.e. the proportion of samples with net present value less than zero), value at risk (VaR) (the maximum possible loss at a given confidence level), value at conditional risk (CVaR) (the average loss exceeding the VaR threshold, measuring the depth of tail risk), and value volatility coefficient (the ratio of standard deviation to expected value, measuring relative volatility).

[0128] Based on risk indicators, exploration rights are classified into risk levels (low, medium, and high) according to preset thresholds. For example, a CVaR exceeding 30% of the expected value of the development path is defined as high risk.

[0129] Finally, based on the enterprise risk appetite data, the first transfer determination result in step 4 is further revised: if the transfer / development path indicated by the first transfer determination result is high risk and the alternative path is low / medium risk, it is automatically corrected to the alternative path; if both paths are high risk, "temporarily suspend transfer + risk mitigation suggestion" is output to ensure that the transfer decision risk is controllable.

[0130] In this step, a dynamic risk quantification system with five characteristics is constructed through a four-stage progressive technical process: intelligent parameter classification, adaptive edge distribution, explicit modeling of dependency structure, controllable simulation convergence, and risk indicator-driven decision correction. Its technical implementation relies entirely on computer automation without human intervention and has the engineering attributes of being reproducible, auditable, and integrable. It provides energy companies with intelligent decision-making support that is scientific, robust, and compliant against the backdrop of increasing global energy volatility and rising policy uncertainty.

[0131] Step 6: Multi-objective global optimization.

[0132] In this embodiment, the core purpose of this step is to integrate a single exploration right into the overall business framework of the enterprise, complete the final judgment, avoid conflicts between the optimal single exploration right and the overall optimal of the enterprise, and achieve optimization of the combination of exploration rights. The specific implementation is as follows: Obtain an optimization model containing a multi-objective optimization function, where the multi-objective optimization function is used to maximize the net present value between the enterprise and the mining right, minimize the overall risk between the enterprise and the mining right, and maximize the enterprise's annual operating cash flow; determine rigid constraints, where the rigid constraints include at least one of the following: capital budget constraints, reserve succession constraints, risk ceiling constraints, compliance constraints, and management bandwidth constraints; process the obtained second transfer judgment result through the optimization model to generate a third transfer judgment result that satisfies the rigid constraints; optimize the third transfer judgment result based on the enterprise's business preference information to obtain the target transfer judgment result. The specific process analysis is as follows:

[0133] 1. Definition of basic parameters and decision variables for global optimization.

[0134] Set up a binary integer decision variable of 0-1 (1 represents "do not transfer, continue development", 0 represents "transfer"). The input parameters are all from the key results in the previous steps (such as the first net present value, the second net present value, risk indicators, etc.) and the enterprise's global operating parameters (such as annual exploration budget, reserve replacement target, maximum risk tolerance threshold, management capacity, etc.). There is no need to add any parameters without a source.

[0135] 2. Construction of multi-objective optimization model.

[0136] The multi-objective optimization function is determined, and three core optimization objectives are defined to balance corporate revenue, risk and cash flow: 1) Maximize the overall net present value of the corporate exploration rights portfolio (core revenue objective); 2) Minimize the overall risk of the corporate exploration rights portfolio (risk control objective); 3) Optimize the corporate annual operating cash flow (cash flow guarantee objective).

[0137] 3. Setting rigid constraints.

[0138] Establish rigid red lines that cannot be crossed in enterprise operations. All transfer judgments must meet the following conditions: 1) Funding budget constraints (total investment in exploration rights development ≤ annual exploration budget); 2) Reserve replacement constraints (total proven reserves of exploration rights development ≥ annual reserve replacement target); 3) Risk ceiling constraints (overall portfolio risk ≤ maximum risk tolerance threshold of the enterprise); 4) Compliance constraints (C-level exploration rights are prohibited from transfer); 5) Management bandwidth constraints (number of exploration rights development ≤ maximum management capacity of the enterprise). Judgments that do not meet the constraints will be directly invalidated.

[0139] 4. Optimize model solution and select the optimal solution.

[0140] The NSGA-II algorithm with its own elite strategy is used to solve the multi-objective optimization model, generating a Pareto optimal solution set (all combinations of transfer decisions that satisfy rigid constraints), and obtaining the third transfer decision result. Subsequently, combined with the enterprise's operating preferences (such as aggressive, conservative, and cash flow-tight), the global optimal solution that best meets the enterprise's needs is selected from the third transfer decision result, and the final judgment conclusion of the transfer of each exploration right is output, thus obtaining the target transfer decision result of the exploration right.

[0141] In this step, a system-level optimization model is constructed with multiple objective functions, including maximizing corporate net present value, minimizing overall risk, and maximizing annual cash flow. This model integrates rigid constraints such as capital budget, reserve succession, risk ceiling, compliance, and management bandwidth. For the first time, the determination of the transfer of individual exploration rights is elevated from isolated optimality to a global decision-making dimension of corporate portfolio optimality. Under the premise of meeting the company's hard operational constraints, the model automatically identifies and generates optimal transfer portfolio strategies across mining rights and paths. This achieves Pareto optimization of risk and return at the corporate asset portfolio level. Furthermore, it incorporates corporate strategic preferences (such as conservative / aggressive tendencies) for preference-weighted fine-tuning, ultimately outputting a target transfer determination result that combines economy, robustness, and strategic synergy. This significantly enhances the long-term value creation capability and dynamic risk resistance capability of oil and gas companies' asset portfolios under complex constraints, demonstrating distinct systemic innovation and engineering implementation value.

[0142] Step 7: Output the flow determination result and perform dynamic closed-loop iteration.

[0143] In this embodiment, the core purpose of this step is to upgrade from static judgment to dynamic iteration, ensuring the long-term effectiveness of the transfer judgment. The specific implementation is as follows: A standardized transfer judgment report is generated based on the target transfer judgment result; the parameter fluctuation range is determined, and if the mining right parameters exceed the parameter fluctuation range, the mining right transfer judgment is re-executed, and a sensitivity analysis report is generated. Here, the mining right parameters are the relevant parameters in the mining right transfer judgment process; the transfer effect corresponding to the target transfer judgment result is determined, and the model parameters in the mining right transfer judgment process are updated based on the transfer effect. A detailed analysis follows:

[0144] 1. Judgment Output: Automatically generates standardized transfer judgment reports, which clearly define the final judgment conclusion (transfer / non-transfer) for each exploration right, transfer priority, suggested secondary market listing price (if transferred), key points of risk prevention and control, and execution process guidelines, making it easier for enterprises to implement.

[0145] 2. Dynamic Iteration: Set the parameter fluctuation range / interval. When the mineral rights parameters (such as geological data of exploration rights, oil and gas prices, mining policies, and enterprise operation parameters) change and trigger the parameter threshold, the entire process calculation of steps 1-6 will be automatically restarted, the transfer judgment results will be updated, and a sensitivity analysis report will be output, marking the safety margin of the judgment results to provide a basis for subsequent dynamic iterations.

[0146] 3. Post-event review and parameter self-calibration: Regularly review the output flow judgment results, compare the actual flow effect with the calculation results, automatically calibrate the model parameters in the flow judgment process, and improve the accuracy of subsequent flow judgments.

[0147] In this step, three technologies work together to ensure the implementation of mining rights transfers: standardized output to ensure execution, fluctuation range triggering to achieve accurate recalculation, and transfer effect feedback to drive model evolution. This transforms mining rights transfer determination from a one-time assessment into a continuously evolving digital twin decision engine in the company's long-term asset strategy. While ensuring the timeliness of decision-making, it significantly improves the long-term accuracy and environmental adaptability of decisions.

[0148] In this embodiment of the application, the following exemplary multidimensional mining rights data is obtained, using exploration rights as the determination object:

[0149] Mining rights information: The initial license area is set at 120 square kilometers; the license was issued in March 2020, with a validity period of 5 years. It has been renewed twice, with a maximum of 3 renewals allowed by law. The remaining validity period is 18 months. The legally allowed single renewal area reduction ratio is 20%. The exploration level is preliminary, with proven technically recoverable tight gas reserves of 1.2 billion cubic meters. There are no ownership disputes, mortgages, or seizures. The transfer proceeds have been 100% paid in full.

[0150] Company basic information: A large oil and gas company focuses on deep-sea oil and gas development, and onshore tight gas is a non-core business; its historical exploration success rate for similar blocks is 42%; the current operating project load rate is 92%; the complete development cycle of this mining right is 24 months; there is no specialized technology for efficient tight gas exploration; there is sufficient available working capital, but no development budget for this block.

[0151] Fixed market and policy parameters: The average transaction price of tight gas mineral rights in the secondary market during the same period is set at RMB 0.18 per cubic meter; the risk-free rate of return is 2.5%; the comprehensive transaction fee rate of the entire chain is 8.5%; and the attenuation coefficient k=0.8.

[0152] Based on the above exemplary parameters, the statutory renewal rules for mining rights and the area reduction rules are converted into rigid constraints. By embedding the corresponding mathematical model, the following data can be obtained:

[0153] Effective exploration area: km 2

[0154] Benchmark transaction value: ,in, This indicates the recoverable resource reserves of the block corresponding to the exploration right. This indicates the average transaction price of mining rights in the secondary market;

[0155] Full-cycle transaction costs: ;

[0156] Time-limited discount amount: ;

[0157] First Net Present Value Calculation for the Development Path: Due to the triggering of a veto mechanism, the effective cash flow of the development path becomes zero, and the final net present value of the development is calculated. (Sunk costs already invested in preliminary exploration) with no possibility of profit;

[0158] Second net present value calculation for the transfer path: ;

[0159] The potential private acquirer has a 78% success rate in exploring similar blocks, with a development cycle of 12 months. Calculate its net present value for development. Cross-entity arbitrage space The transfer is feasible.

[0160] Subsequently, by combining the enterprise's multi-dimensional feature adaptation optimization, dynamic risk quantification analysis and optimization of multi-source uncertainty coupling, and multi-objective optimization operations, the preliminary transfer feasibility judgment results are deeply optimized to obtain the final transfer disposal conclusion and output a standardized transfer judgment report.

[0161] Overall, this application innovatively constructs an intelligent transfer judgment system for oil and gas mining rights that integrates the heterogeneous endowments of enterprises with the rigid constraints of mining administration. For the first time, it realizes the quantitative comparison of development and transfer paths with the same caliber, the economic discount modeling of statutory failure risk, the nonlinear coupling analysis of multi-source risks, and the dynamic closed-loop decision-making of single mining rights to combined global optimization. It breaks through the technical limitations of traditional methods that rely solely on experience-based judgment, ignore enterprise capabilities, and separate compliance from economic value. It pioneers a paradigm shift in oil and gas asset transfer from subjective experience to data-driven and intelligent closed-loop systems.

[0162] According to embodiments of this application, an oil and gas mining rights transfer determination device is provided. It should be noted that the oil and gas mining rights transfer determination device of this application embodiment can be used to execute the oil and gas mining rights transfer determination method provided in this application embodiment. The following describes the oil and gas mining rights transfer determination device provided in this application embodiment.

[0163] Figure 6 This is a structural diagram of an oil and gas mining rights transfer determination device provided according to an embodiment of this application. Figure 6 As shown, the device includes:

[0164] The acquisition module 60 is used to acquire multi-dimensional mining rights data through multiple data interfaces during the oil and gas exploration and development process. The multi-dimensional mining rights data includes enterprise operating status, market change information and attribute data of the oil and gas mining rights themselves.

[0165] The mineral administration constraint module 62 is used to determine the mineral administration constraint conditions corresponding to the multidimensional mineral rights data based on the statutory renewal rules and area reduction rules of mineral rights. The mineral administration constraint conditions are the restrictions corresponding to the exploration area, duration and transferability of mineral rights.

[0166] The determination module 64 is used to determine the first net present value of the mining right on the development path using a first learning model, and to determine the second net present value of the mining right on the transfer path using a second learning model based on mining policy constraints.

[0167] The transfer determination module 66 is used to determine the transfer determination result of the mining rights based on the first net present value and the second net present value.

[0168] By utilizing the acquisition module, mineral administration constraint module, determination module, and transfer determination module in the aforementioned oil and gas mining rights transfer determination device, the goal of dynamically quantifying and comparing the value of mining rights under the two paths of "continued development" and "transfer and monetization" is achieved. This realizes the technical effect of automated and standardized transfer decision-making based on the heterogeneous endowment of enterprises and the rigid constraints of mineral administration. Furthermore, it solves the technical problem that the relevant technologies only assess the resource attributes of the mining rights themselves and lack standardized rigid constraints and dual-path value assessment, resulting in insufficient scientificity and low accuracy in mining rights transfer determination.

[0169] In the oil and gas mining rights transfer determination device provided in this application embodiment, the acquisition module is further used to acquire mining rights attribute data throughout the entire life cycle through a first data interface; acquire enterprise data of mining rights in multiple dimensions of enterprise operation and management through a second data interface; acquire market data and policy data corresponding to mining rights through a third data interface; determine the original mining rights data based on the mining rights attribute data, enterprise data, market data and policy data; and perform data cleaning and standardization processing on the original mining rights data to obtain multi-dimensional mining rights data.

[0170] In the oil and gas mining rights transfer determination device provided in this application embodiment, the mining administration constraint module is also used to determine the mining rights transfer rule base, wherein the mining rights transfer rule base includes mandatory prohibition rules, restrictive rectification rules, and warning risk rules based on mining administration regulations; the mining rights are verified according to the mining rights transfer rule base to obtain the verification result; if the verification result indicates that the mining right is a first-level mining right, it is determined that the mining right can be directly transferred; if the verification result indicates that the mining right is a second-level mining right, it is determined that the mining right can be transferred after rectification, and the rectification cost and rectification period of the mining right are determined, wherein the rectification cost and rectification period will be included in the value accounting of the second net present value; if the verification result indicates that the mining right is a third-level mining right, it is determined that the mining right is not transferable.

[0171] In the oil and gas mining rights transfer determination device provided in this application embodiment, the mining administration constraint module is further used to analyze multi-dimensional mining rights data based on the statutory renewal rules and area reduction rules of mining rights, and obtain the effective exploration area corresponding to the mining rights through an effective area decay model; determine the benchmark transaction value of the mining rights, and determine the time-limited discount amount corresponding to the mining rights based on the benchmark transaction value, the statutory renewal rules of mining rights, and the preset decay coefficient, wherein the time-limited discount amount is used to characterize the depreciation amount of the mining rights due to the approaching statutory expiration date; determine the time decay factor, wherein the time decay factor is used to force the cash flow on the development path to zero when the remaining validity period of the mining rights is less than the enterprise's development cycle; and determine the mining administration constraint conditions based on the effective exploration area, the time-limited discount amount, and the time decay factor.

[0172] In the oil and gas mining rights transfer determination device provided in this application embodiment, the determination module is also used to obtain historical transfer cases corresponding to the mining rights; determine the full-cycle transaction cost of the mining rights; and calculate the benchmark transaction value, full-cycle transaction cost and time-limited discount amount of the mining rights through a second learning model based on the historical transfer cases to obtain the second net present value of the mining rights on the transfer path. The second learning model is used to quantify the secondary market value of the mining rights.

[0173] In the oil and gas mining rights transfer determination device provided in this application embodiment, the transfer determination module is further used to determine the enterprise's multi-dimensional indicators, wherein the multi-dimensional indicators include at least soft indicators corresponding to the enterprise's technological matching degree, financial adequacy, spatial synergy, strategic fit and management redundancy; determine the nonlinear adaptation matrix corresponding to the mining rights based on the multi-dimensional indicators, wherein the nonlinear adaptation matrix is ​​used to reflect the enterprise's ability to explore and develop the mining rights; determine the fit degree between the mining rights and the enterprise based on the nonlinear adaptation matrix; optimize the transfer determination result based on the fit degree to obtain the first transfer determination result.

[0174] In the oil and gas mining rights transfer determination device provided in this application embodiment, the transfer determination module is further used to obtain uncertainty parameters, wherein the uncertainty parameters are used to represent the uncertain parameters that appear in the value accounting of the first net present value and the second net present value; determine the joint probability distribution of the uncertainty parameters, wherein the joint probability distribution is used to reflect the degree of nonlinear correlation between the uncertainty parameters; perform Monte Carlo simulation based on the joint probability distribution to generate multiple sets of value samples corresponding to the development path and the transfer path; determine risk indicators based on the value samples, and classify the risk levels of the development path and the transfer path according to the risk indicators to obtain the risk level classification result; optimize the first transfer determination result based on the risk level classification result to obtain the second transfer determination result.

[0175] In the oil and gas mining rights transfer determination device provided in this application embodiment, the transfer determination module is further used to obtain an optimization model containing a multi-objective optimization function, wherein the multi-objective optimization function is used to maximize the net present value between the enterprise and the mining rights, minimize the overall risk between the enterprise and the mining rights, and maximize the enterprise's annual operating cash flow; determine rigid constraints, wherein the rigid constraints include at least one of the following: capital budget constraints, reserve succession constraints, risk ceiling constraints, compliance constraints, and management bandwidth constraints; process the obtained second transfer determination result through the optimization model to generate a third transfer determination result that satisfies the rigid constraints; optimize the third transfer determination result based on the enterprise's operating preference information to obtain the target transfer determination result.

[0176] In the oil and gas mining rights transfer determination device provided in this application embodiment, the transfer determination module is further used to generate a standardized transfer determination report based on the target transfer determination result; determine the parameter fluctuation range, and when the mining rights parameters exceed the parameter fluctuation range, re-execute the mining rights transfer determination and generate a sensitivity analysis report, wherein the mining rights parameters are relevant parameters in the mining rights transfer determination process; and determine the transfer effect corresponding to the target transfer determination result, and update the model parameters in the mining rights transfer determination process based on the transfer effect.

[0177] This application also provides an electronic device, including: a memory and a processor, wherein the memory is used to store program instructions; the processor is connected to the memory and is used to execute the above-described method for determining the transfer of oil and gas mining rights.

[0178] It should be noted that the aforementioned electronic equipment is used to perform Figure 2 The method for determining the transfer of oil and gas mining rights shown above also applies to this electronic device, and will not be repeated here.

[0179] This application also provides a non-volatile storage medium, which includes a stored computer program, wherein the device containing the non-volatile storage medium executes the above-mentioned oil and gas mining rights transfer determination method by running the computer program.

[0180] It should be noted that the aforementioned non-volatile storage media is used for execution. Figure 2 The method for determining the transfer of oil and gas mining rights shown above is also applicable to this non-volatile storage medium, and will not be repeated here.

[0181] This application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the above-described method for determining the transfer of oil and gas mining rights.

[0182] It should be noted that the above-mentioned computer program product is used to execute Figure 2 The method for determining the transfer of oil and gas mining rights shown above is also applicable to this computer program product, and will not be repeated here.

[0183] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0184] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0185] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0186] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0187] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0188] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0189] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for determining the transfer of oil and gas mining rights, characterized in that, include: During the oil and gas exploration and development process, multi-dimensional mining rights data is obtained through multiple data interfaces. The multi-dimensional mining rights data includes enterprise operating status, market change information, and attribute data of the oil and gas mining rights themselves. Based on the statutory renewal rules and area reduction rules for mining rights, the mineral administration constraints corresponding to the multidimensional mining rights data are determined, wherein the mineral administration constraints are restrictions corresponding to the exploration area, duration and transferability of mining rights. A first learning model is used to determine the first net present value of the mining right on the development path, and a second learning model is used to determine the second net present value of the mining right on the transfer path based on the mining administrative constraints. The transfer determination result of the mining rights is determined based on the first net present value and the second net present value.

2. The method according to claim 1, characterized in that, Multidimensional mining rights data is obtained through multiple data interfaces, including: Obtain mining rights attribute data throughout their entire lifecycle through the first data interface; The mining rights data are obtained from multiple dimensions of enterprise operation and management through the second data interface. Obtain market and policy data corresponding to the mining rights through a third data interface; The original mining rights data is determined based on the mining rights attribute data, the enterprise data, the market data, and the policy data. The original mining rights data is cleaned and standardized to obtain the multidimensional mining rights data.

3. The method according to claim 1, characterized in that, Before determining the mineral administration constraints corresponding to the multidimensional mineral rights data based on the statutory renewal rules and area reduction rules for mineral rights, the method further includes: A mining rights transfer rule base is established, which includes mandatory prohibition rules, restrictive rectification rules, and risk warning rules based on mining regulations; The mining rights are verified according to the mining rights transfer rule base, and the verification results are obtained; If the verification result indicates that the mining right is a first-level mining right, it is determined that the mining right can be directly transferred; If the verification result indicates that the mining right is a secondary mining right, it is determined that the mining right can be transferred after rectification, and the rectification cost and rectification period of the mining right are determined, wherein the rectification cost and the rectification period will be included in the valuation of the second net present value; If the verification result indicates that the mining right is a third-level mining right, then the mining right is determined to be non-transferable.

4. The method according to claim 1, characterized in that, Based on the statutory renewal rules and area reduction rules for mining rights, the mineral administration constraints corresponding to the multidimensional mining rights data are determined, including: Based on the statutory renewal rules and area reduction rules for mining rights, the multidimensional mining rights data are analyzed using an effective area decay model to obtain the effective exploration area corresponding to the mining rights. The benchmark transaction value of the mining right is determined, and the time-limited discount amount corresponding to the mining right is determined based on the benchmark transaction value, the statutory renewal rules of the mining right, and the preset depreciation coefficient. The time-limited discount amount is used to characterize the amount of depreciation of the mining right due to its approaching statutory expiration date. A time decay factor is determined, wherein the time decay factor is used to force the cash flow on the development path to zero when the remaining validity period of the mining right is less than the enterprise's development cycle; The mineral administration constraints are determined based on the effective exploration area, the time-limited discount amount, and the time decay factor.

5. The method according to claim 4, characterized in that, The second learning model is used to determine the second net present value of the mining right along the transfer path based on the aforementioned mining policy constraints, including: Obtain historical transfer cases corresponding to the mining rights; Determine the full-cycle transaction costs of the mining rights; Based on the historical transfer cases, the benchmark transaction value of the mining rights, the full-cycle transaction cost, and the time-limited discount amount are calculated using the second learning model to obtain the second net present value of the mining rights on the transfer path. The second learning model is used to quantify the secondary market value of the mining rights.

6. The method according to claim 1, characterized in that, The method further includes: Determine the enterprise's multi-dimensional indicators, wherein the multi-dimensional indicators include at least soft indicators corresponding to the enterprise's technology matching degree, financial adequacy, spatial synergy, strategic fit and management redundancy; A nonlinear adaptation matrix corresponding to the mining right is determined based on the multi-dimensional indicators, wherein the nonlinear adaptation matrix is ​​used to reflect the enterprise's ability to explore and develop the mining right; The fit between the mining rights and the enterprise is determined based on the nonlinear adaptation matrix. The flow determination result is optimized based on the adaptability to obtain the first flow determination result.

7. The method according to claim 6, characterized in that, The method further includes: Obtain uncertainty parameters, wherein the uncertainty parameters are used to represent uncertain parameters that occur in the valuation of the first net present value and the second net present value; Determine the joint probability distribution of the uncertainty parameters, wherein the joint probability distribution is used to reflect the degree of nonlinear correlation between the uncertainty parameters; Monte Carlo simulation is performed based on the joint probability distribution to generate multiple sets of value samples corresponding to the development path and the transfer path; Risk indicators are determined based on the value sample, and the risk levels of the development path and the transfer path are classified according to the risk indicators to obtain the risk level classification results; The first circulation determination result is optimized based on the risk level classification result to obtain the second circulation determination result.

8. The method according to claim 7, characterized in that, The method further includes: Obtain an optimization model containing a multi-objective optimization function, wherein the multi-objective optimization function is used to maximize the net present value between the enterprise and the mining rights, minimize the overall risk between the enterprise and the mining rights, and maximize the annual operating cash flow of the enterprise; Define rigid constraints, which include at least one of the following: funding budget constraints, reserve succession constraints, risk ceiling constraints, compliance constraints, and management bandwidth constraints. The second circulation determination result is processed by the optimization model to generate a third circulation determination result that satisfies the rigid constraint condition. The third circulation determination result is optimized based on the enterprise's business preference information to obtain the target circulation determination result.

9. The method according to claim 8, characterized in that, The method further includes: A standardized flow determination report is generated based on the target flow determination results; and The parameter fluctuation range is determined, and if the mining right parameters exceed the fluctuation range, the mining right transfer determination is re-executed, and a sensitivity analysis report is generated. The mining right parameters are the relevant parameters from the mining right transfer determination process. Determine the transfer effect corresponding to the target transfer determination result, and update the model parameters in the mining rights transfer determination process based on the transfer effect.

10. A device for determining the transfer of oil and gas mining rights, characterized in that, include: The acquisition module is used to acquire multidimensional mining rights data through multiple data interfaces during the oil and gas exploration and development process. The multidimensional mining rights data includes enterprise operating status, market change information and attribute data of the oil and gas mining rights themselves. The mineral administration constraint module is used to determine the mineral administration constraint conditions corresponding to the multidimensional mineral rights data based on the statutory renewal rules and area reduction rules for mineral rights. The mineral administration constraint conditions are restrictions corresponding to the exploration area, duration and transferability of mineral rights. The determination module is used to determine the first net present value of the mining right on the development path using a first learning model, and to determine the second net present value of the mining right on the transfer path using a second learning model based on the mining administrative constraints. The transfer determination module is used to determine the transfer determination result of the mining right based on the first net present value and the second net present value.

11. An electronic device, characterized in that, include: A memory and a processor, wherein the memory is used to store program instructions; The processor, connected to the memory, is used to execute the method for determining the transfer of oil and gas mining rights as described in any one of claims 1 to 9.

12. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored computer program, wherein the device containing the non-volatile storage medium executes the oil and gas mining rights transfer determination method according to any one of claims 1 to 9 by running the computer program.

13. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the oil and gas mining rights transfer determination method according to any one of claims 1 to 9.

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