Layered mining drill hole plugging method and system based on material performance dynamic adaptation

Abstract

The invention discloses a layered mining borehole plugging method and system based on material performance dynamic adaptation, and relates to the technical field of borehole plugging, the method comprises the following steps: detecting a target stratum area and crack information, and defining stratum code distribution based on a crack characteristic-plugging mode; introducing a modified component, constructing a performance adapter according to the ratio of the base material to the modified component, and embedding the performance adapter into a mining central control system; and triggering a performance adapter according to the stratum code distribution, executing parallel decision and mutual verification, determining a performance optimization strategy, establishing a mapping relation, and issuing the performance optimization strategy to the material distribution equipment and the plugging equipment in a distributed manner for directional control. The technical problem that an existing plugging method cannot dynamically adjust the performance of the plugging material according to complex stratum conditions and fracture characteristics, and consequently the plugging effect is unstable is solved, dynamic optimization control over the performance of the plugging material is achieved through stratum coding distribution and the performance adapter, and the plugging effect is improved. And the stability of the plugging effect under the complex geological condition is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of borehole plugging, and in particular to a layered mining borehole plugging method and system based on dynamic adaptation of material properties. Background Art

[0002] In the stratified mining and gas extraction process, plugging technology is key to ensuring gas extraction safety and improving efficiency. However, existing plugging methods rely primarily on manual experience and fixed material ratios, making them difficult to adapt to different geological conditions and fracture characteristics, resulting in unstable plugging results. This is especially difficult to ensure in situations where the coal rock fracture structure varies greatly and the interlayer permeability is uneven. In addition, traditional methods lack real-time monitoring and dynamic adjustment mechanisms for the plugging process, and the performance of the plugging materials often cannot be optimized in a timely manner according to changes in formation conditions. This not only affects the quality of the plugging, but also increases safety risks during the mining process. Summary of the Invention

[0003] The present application provides a layered mining drilling plugging method and system based on dynamic adaptation of material properties, which is used to solve the technical problem that existing plugging methods cannot dynamically adjust the plugging material properties according to complex formation conditions and fracture characteristics, resulting in unstable plugging effects.

[0004] The first aspect of the present application provides a layered mining drilling plugging method based on dynamic adaptation of material properties, the method comprising: defining a formation code distribution based on fracture characteristics-plugging mode according to fracture detection information through detection of the target formation area; introducing a modifying component, constructing a performance adapter with a ratio of base material and modifying component, and embedding it in the mining control system, wherein the modification dimension includes at least rheological properties, expansion properties, and coagulation properties, and the performance adapter uses code elements as machine language, including a first branch based on the response surface principle and a second branch based on a network architecture; triggering the performance adapter for the formation code distribution, executing branch parallel decision-making and mutual verification under code targeting, and determining a performance optimization strategy; establishing a mapping between the performance optimization strategy and the formation code distribution, and distributing it to the material matching equipment and the plugging equipment for directional control and drive.

[0005] The second aspect of the present application provides a layered mining drilling and plugging system based on dynamic adaptation of material properties, the system comprising: a formation code distribution definition module, the formation code distribution definition module is used to define a formation code distribution based on fracture characteristics-plugging mode according to fracture detection information through detection of the target formation area; a performance adapter construction module, the performance adapter construction module is used to introduce a modifying component, and to construct a performance adapter based on the ratio of the base material and the modifying component, and to embed it in the mining control system, wherein the modification dimension includes at least rheological properties, expansion properties, and coagulation properties, and the performance adapter uses code elements as machine language, and includes a first branch based on the response surface principle and a second branch based on the network architecture; a performance optimization module, the performance optimization module is used to trigger the performance adapter for the formation code distribution, execute branch parallel decision-making and mutual verification under the code targeting, and determine the performance optimization strategy; a directional control drive module, the directional control drive module is used to establish a mapping between the performance optimization strategy and the formation code distribution, and distribute it to the material preparation equipment and the plugging equipment for directional control drive.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] The present application provides a layered mining borehole plugging method and system based on dynamic adaptation of material properties, which relates to the field of borehole plugging technology. Through the combination of stratum coding distribution and performance adapter, the performance of the plugging material is dynamically optimized according to the characteristics of the stratum and fracture. The rheological properties, expansibility and coagulation properties are adjusted through the performance adapter. The optimization strategy is determined based on parallel decision-making and mutual verification, and the optimization strategy is sent to the material distribution and plugging equipment through distributed control to achieve precise control and efficient plugging. This solves the technical problem that the existing plugging methods cannot dynamically adjust the performance of the plugging materials according to complex stratum conditions and fracture characteristics, resulting in unstable plugging effects. This realizes the dynamic optimization control of the performance of the plugging materials through stratum coding distribution and performance adapter, and improves the technical effect of improving the stability of the plugging effect under complex geological conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic flow chart of a method for drilling and plugging stratified mining based on dynamic adaptation of material properties provided in an embodiment of the present application;

[0010] Figure 2Schematic diagram of the structure of the layered mining drilling and plugging system based on dynamic adaptation of material properties provided in an embodiment of the present application.

[0011] Description of the reference numerals: formation code distribution definition module 11, performance adapter construction module 12, performance optimization module 13, directional control driving module 14. DETAILED DESCRIPTION

[0012] The present application provides a layered mining drilling plugging method and system based on dynamic adaptation of material properties, which is used to solve the technical problem that existing plugging methods cannot dynamically adjust the plugging material properties according to complex formation conditions and fracture characteristics, resulting in unstable plugging effects.

[0013] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0014] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0015] Example 1, as Figure 1 As shown, the present application provides a layered mining borehole plugging method based on dynamic adaptation of material properties, the method comprising:

[0016] P10: Through the detection of the target formation area and based on the fracture detection information, the formation code distribution based on the fracture characteristics-sealing mode is defined.

[0017] Among them, the definition of fracture characteristics - blocking mode includes:

[0018] P11a: Setting fracture classification standards; P12a: Based on the fracture classification standards, performing fracture classification and plugging mode matching in the target formation area to determine fracture mode conditions, which are at least divided into large-opening fractures-high-pressure injection mode, network micro-cracks-low-pressure infiltration mode, and interlayer dislocation zone-pulse grouting mode.

[0019] Specifically, by detecting the target formation area and combining it with fracture detection information, the formation code distribution is defined. The key to this process is to accurately identify and classify fracture characteristics and determine the corresponding plugging mode based on different fracture characteristics.

[0020] Specifically, the first step is to define the fracture characteristics—the sealing pattern. Establishing a reasonable fracture classification standard depends on factors such as the fracture geometry, opening size, distribution density, directionality, and connectivity between fractures in the formation. Common fracture classification criteria may include opening size, connectivity, and distribution patterns, such as large-opening fractures, network-like microcracks, and interlayer dislocation zones. By establishing these standards, a clear technical basis can be provided for subsequent fracture classification.

[0021] Subsequently, the target formation area is classified into fracture categories according to the established fracture classification standards, and different types of fractures are matched with corresponding plugging modes. Specifically, the core task of this step is to determine the plugging mode suitable for each fracture type based on the fracture classification results. The selection of the plugging mode must take into account the characteristics of the fracture to ensure the effectiveness and durability of the plugging. For example, for large-opening fractures, which usually have larger channels and stronger water flow conductivity, it is suitable to adopt a high-pressure jetting mode to ensure that the plugging material can quickly enter and fill the fracture. When facing a network of micro-cracks, the permeability requirements of the plugging material are higher, so it is suitable to adopt a low-pressure infiltration mode, so that the plugging material can fully penetrate into the micro-crack network at a lower pressure. For the interlayer dislocation zone, due to its strong dislocation, the pulse grouting mode can provide a fast and effective plugging effect in a short time through high-frequency pulse injection.

[0022] The selection and matching of each plugging mode must be based on the specific conditions of the target formation, such as the fracture morphology, size, distribution characteristics, and responsiveness to pressure and flow. Therefore, the selection and matching of each plugging mode can be based on an analysis of the physical properties of the fractures, the rheological properties of the plugging material, and experimental research and actual application data for different plugging modes.

[0023] In general, the definition of the stratigraphic code distribution of fracture characteristics and plugging modes can not only scientifically evaluate the fracture characteristics of different stratigraphic regions, but also select the most suitable plugging mode according to the characteristics of different fractures, thereby providing accurate guidance for the subsequent plugging process and ensuring the maximization of the plugging effect.

[0024] Furthermore, step P10 in the embodiment of the present application further includes:

[0025] P11: Introducing level constraints and setting a preset coding sequence; P12: Based on the preset coding sequence, performing code element conversion on the fracture pattern conditions under the level constraints to integrate the spatial phase distribution of the target formation area and determine the formation code distribution.

[0026] It should be understood that the definition process of the formation code distribution can be further refined by introducing hierarchical constraints and preset code sequences, performing code element conversion on the fracture pattern conditions, and integrating based on the spatial phase distribution of the target formation area to finally determine the formation code distribution.

[0027] After completing the fissure classification and matching the plugging pattern, hierarchical constraints are introduced and a preset coding sequence is set. Hierarchical constraints classify fissures based on factors such as their size, impact, and plugging priority, thereby determining the order and importance of different levels of fissures during the plugging process. For example, large open fissures that could seriously impact mining safety and efficiency could be assigned a higher level and given priority for plugging. Meanwhile, micro-cracks with less impact on mining could be assigned a lower level, and the plugging order could be arranged based on the actual situation.

[0028] After defining the hierarchical constraints, a preset coding sequence was then established. This coding sequence assigns unique identifiers to different fracture types and their respective plugging patterns. This coding scheme provides a standardized framework for matching fracture types with plugging patterns. By coding fractures, the plugging process can be carried out in a more systematic and standardized manner, facilitating subsequent automated control and decision support.

[0029] Subsequently, according to the preset coding sequence, the fracture pattern conditions under the level constraint are converted into code elements. Code element conversion is to convert information such as the classification, level and plugging mode of the fracture into a machine-recognizable code element form. These code elements can be numbers, letters or other specific symbol combinations. Through code element conversion, complex fracture information can be standardized and digitized, which is convenient for storage, transmission and analysis in the mining control system. At the same time, based on the spatial phase distribution of the target formation area, integration is carried out, that is, the fracture information of different positions and directions is comprehensively considered according to its spatial distribution relationship in the formation, to ensure that the formation code distribution can comprehensively and accurately reflect the fracture characteristics and plugging requirements of the target formation area. Finally, through this series of operations, the formation code distribution is determined, which provides a more accurate guidance basis for the subsequent performance adaptation of the plugging material and the plugging operation.

[0030] By introducing hierarchical constraints and preset coding sequences, and performing symbol conversion and spatial phase distribution integration, the present embodiment further optimizes the process of defining stratigraphic code distribution. This not only makes the processing of fracture information more systematic and efficient, but also better adapts to the complex geological conditions of the target stratigraphic area, improving the targetedness and reliability of the plugging solution.

[0031] P20: Introduce modifying components, build a performance adapter based on the ratio of base material and modifying components, and embed it into the mining control system. The modification dimensions include at least rheological properties, expansion properties, and coagulation properties. The performance adapter uses code elements as machine language, including a first branch based on the response surface principle and a second branch based on the network architecture.

[0032] Furthermore, it is characterized in that a modifying component is introduced, and a performance adapter is constructed with a ratio of substrate and modifying component. Step P20 of the embodiment of the present application further includes:

[0033] P21: Determine a first modifying component for modifying rheological properties, wherein the first modifying component contains at least a polycarboxylate water-reducing agent; P22: Determine a second modifying component for modifying expansion properties, wherein the second modifying component contains at least a calcium sulfoaluminate expansion agent; P23: Determine a third modifying component for modifying setting properties, wherein the third modifying component contains at least a sodium gluconate retarder; P24: Deploy a performance adapter based on the first modifying component, the second modifying component and the third modifying component by defining the state space-action space.

[0034] Optionally, a modifying component is introduced. By adjusting the ratio of the base material to the modifying component, a performance adapter is constructed and embedded in the mining control system. The core goal of this performance adapter is to adapt the plugging properties of the plugging material to the plugging requirements of different geological conditions and fracture types by adjusting the rheological, expansion, and coagulation properties. Furthermore, this performance adapter uses code elements as a machine language to convert different fracture characteristics and plugging modes into actionable control signals.

[0035] Specifically, during the construction of the performance adapter, the first component for rheological modification is determined. This component contains at least a polycarboxylate superplasticizer. Polycarboxylate superplasticizer is a highly effective water-reducing agent that significantly improves the rheological properties of the plugging material, reducing its yield stress and plastic viscosity, thereby increasing its fluidity and pumpability, making it easier to flow and fill formation fractures.

[0036] Next, a second modifying component for improving expansion properties is determined, which includes at least a calcium sulfoaluminate expansion agent. This agent moderately expands during the setting process of the plugging material, filling tiny gaps within the cracks and strengthening the bond between the plugging material and the crack wall, thereby improving the density and durability of the plugging effect.

[0037] Then, a third modifying component for improving the setting properties is determined, which comprises at least a sodium gluconate retarder. The sodium gluconate retarder can effectively adjust the setting time of the plugging material, allowing it sufficient time to flow and fill the formation fractures while preventing premature setting that would affect the plugging effect.

[0038] After determining the three modifying components mentioned above, a performance adapter based on the first modifying component, the second modifying component, and the third modifying component is deployed by defining the state space-action space. The state space refers to the various possible states of the plugging material under different formation conditions, including the size, shape, connectivity of the fractures, and environmental factors such as the pressure and temperature of the formation; the action space refers to the various modification measures that the performance adapter can take, that is, optimizing the performance of the plugging material by adjusting the ratio of the base material and the modifying component. The performance adapter dynamically adjusts the addition amount and ratio of the modifying component according to the real-time monitored formation state information by mapping and making decisions between the state space and the action space, thereby achieving precise adaptation of the performance of the plugging material to meet the plugging needs under different formation conditions.

[0039] The core of this process is to precisely control the ratio of different modified components to build a performance adapter that can adapt to different fracture types and formation conditions, so that the plugging material has optimal fluidity, expansion and coagulation during the construction process, thereby improving the plugging effect and ensuring maximum gas extraction efficiency.

[0040] Furthermore, to define the state space-action space, step P24 in this embodiment of the application further includes:

[0041] P24-1: Determine the state space elements based on the substrate penetration path, determine the action space elements based on the ratio of the first modifying component to the substrate, and deploy the first spatial structure; P24-2: Determine the state space elements based on the expansion action range based on the layered mining stress environment, determine the dynamic space elements based on the ratio of the second modifying component to the substrate, and deploy the second spatial structure; P24-3: Determine the state space elements based on the retarder distribution gradient, determine the dynamic space elements based on the ratio of the third modifying component to the substrate, and deploy the third spatial structure.

[0042] Specifically, the definition of the state space-action space can be further refined, and corresponding spatial structures can be deployed for different modified components and performance dimensions to achieve more precise performance adaptation. In other words, by configuring the elements of the state space and action space, the plugging material can be adaptively adjusted according to different formation conditions and fracture characteristics.

[0043] First, we define the state space and action space. The state space includes factors such as temperature, stress, fracture rate, and osmotic pressure. These factors are configured according to specific dimensions and reflect the physical and chemical characteristics of the formation. The action space includes factors such as water-cement ratio, proportion of modified components, and stirring speed, which are used to adjust the performance of the plugging material to adapt to different formation conditions. Based on this, we make the following specific arrangements:

[0044] First, the state space elements are determined based on the substrate's infiltration path, while the action space elements are determined based on the ratio of the first modifying component (polycarboxylate superplasticizer) to the substrate, thereby deploying the first spatial structure. The substrate's infiltration path involves factors such as the morphology, size, and connectivity of the fractures, as well as the permeability of the formation. Since the polycarboxylate superplasticizer is primarily used to improve the rheological properties of the plugging material, the action space elements include the water-cement ratio and the amount of superplasticizer added. In this structure, the performance adapter dynamically adjusts the water-cement ratio and the amount of superplasticizer added based on real-time monitoring of fracture morphology and formation permeability, optimizing the rheological properties of the plugging material and ensuring smooth penetration and filling of the fractures.

[0045] Next, the state space elements are determined based on the expansion range under the layered mining stress environment, and the action space elements are determined based on the ratio of the second modifying component (calcium sulfoaluminate expander) to the base material. The second space structure is then deployed. The expansion range is affected by factors such as formation stress, fracture distribution, and connectivity. State space elements include formation stress, fracture density, and fracture connectivity. The calcium sulfoaluminate expander is primarily used to improve the expansion performance of the plugging material. Action space elements include the amount of expander added and the ratio of expander to base material. In this structure, the performance adapter dynamically adjusts the amount and ratio of the expander based on real-time monitoring of formation stress and fracture distribution, optimizing the expansion performance of the plugging material. This ensures that the material expands appropriately under formation stress, filling micro-voids within the fractures and enhancing the plugging effect.

[0046] Next, the state space elements are determined based on the retarder distribution gradient, and the action space elements are determined based on the ratio of the third modifying component (sodium gluconate retarder) to the base material, thus deploying the third space structure. The retarder distribution gradient involves factors such as formation temperature, humidity, and fracture distribution. State space elements include formation temperature, humidity, and fracture density. The sodium gluconate retarder is primarily used to adjust the setting time of the plugging material. Action space elements include the retarder dosage and the retarder-to-base material ratio. In this structure, the performance adapter dynamically adjusts the retarder dosage and ratio based on real-time monitoring of formation temperature, humidity, and fracture distribution, optimizing the setting performance of the plugging material and ensuring sufficient time for the material to flow and fill the formation while preventing premature setting that could compromise the plugging effectiveness.

[0047] Through the above operations, the embodiment of the present application deploys corresponding spatial structures for different modified components and performance dimensions, realizes the effective combination of state space and action space, further improves the adaptability and effectiveness of the performance adapter, enables it to better cope with complex formation environments, and provide more reliable material performance support for layered mining drilling and plugging operations.

[0048] Furthermore, to construct a performance adapter, step P24 of the embodiment of the present application further includes:

[0049] P24-4: Deploy the first decision node according to the first spatial structure, deploy the second decision node according to the second spatial structure, and deploy the third decision node according to the third spatial structure to determine the decision architecture, wherein the first decision node, the second decision node and the third decision node are in a parallel relationship; P24-5: Perform first-order training based on the response surface principle on the decision architecture to determine the first branch; P24-6: Perform second-order training based on neural network learning on the decision architecture to determine the second branch; P24-7: Run the first branch and the second branch in parallel as the performance adapter.

[0050] Optionally, the performance adapter construction process can be further refined by introducing the design and training process of the decision architecture to build a performance adapter that can adapt to different geological conditions and fracture characteristics.

[0051] In the process of building the performance adapter, the first decision node, the second decision node, and the third decision node are first deployed according to the three aforementioned spatial structures. These three decision nodes are independently deployed according to their corresponding spatial structures, and each is responsible for the decision-making process of the corresponding spatial structure. Specifically, the first decision node makes decisions based on the first spatial structure, mainly for parameters related to rheological properties; the second decision node makes decisions based on the second spatial structure, for parameters related to expansion properties; and the third decision node mainly handles decisions related to coagulation properties based on the third spatial structure. The three decision nodes are in a parallel relationship, which means that they make decisions independently and are not affected by each other, but the final decisions will be converged to form an overall blocking strategy.

[0052] Subsequently, the entire decision-making framework undergoes first-order training based on the response surface principle. The response surface principle is a statistical method used for optimization and modeling. By modeling the relationship between multiple input variables (such as the ratio of modified components and stirring speed) and output results (such as rheological properties and dilatancy), it helps determine the optimal plugging strategy. Through first-order training, the system can quickly calculate the performance changes of the plugging material based on the input decision parameters and generate corresponding optimized decision results. The main purpose of this training is to provide decision support for the first branch of the performance adapter to ensure that the rheological properties are optimized under different geological conditions.

[0053] Furthermore, a second-order training based on neural network learning is performed. This training process leverages the powerful learning capabilities of neural networks to further optimize the decision-making process, especially when faced with complex nonlinear problems. Neural networks can identify and learn the intricate relationships between inputs and outputs. This second-order training enables the system to gain a deeper understanding of the interactions between different modification components and automatically adjust the weights and priorities of each decision node based on the specific characteristics of the formation. This process optimizes the second branch of the performance adapter, thereby improving decision-making accuracy and adaptability.

[0054] Ultimately, the first branch, based on response surface theory, and the second branch, based on neural network learning, were integrated in parallel to form a complete performance adapter. The first branch, trained using response surface theory, focuses on optimizing rheological properties; the second branch, trained using neural network learning, focuses on optimizing expansibility and coagulation. This parallel structure enables the performance adapter to combine the strengths of two distinct decision-making approaches. In practical applications, the performance adapter can make decisions simultaneously through both branches based on real-time formation state information, selecting the optimal decision based on the actual situation, thereby achieving dynamic and precise adaptation of plugging material performance.

[0055] Through the above steps, the performance adapter can dynamically adjust the material ratio and performance according to geological conditions and fracture characteristics in actual applications, thereby effectively improving the sealing effect of gas extraction boreholes and ensuring that the sealing material has optimal rheological properties, expansion properties and coagulation properties in multi-layer boreholes.

[0056] Furthermore, for the first-order training and the second-order training, step P24 in this embodiment of the application further includes:

[0057] P24-1a: According to the preset coding sequence, sample conversion is performed based on the codeword-entry conversion relationship to determine the codeword sample; P24-2a: Based on the codeword sample, first-order training and second-order training are performed, wherein the samples of the first-order training and the second-order training are the same sample or different samples.

[0058] In one possible embodiment of the present application, the first-order and second-order training processes can be further refined to ensure the accuracy and efficiency of the performance adapter. Through sample conversion and symbol-based analysis, the traditional method of interpreting the meaning of the data is avoided, thereby simplifying the model training process.

[0059] Before conducting first-order and second-order training, sample conversion is first performed based on the preset coding sequence and the code element-entry conversion relationship to determine the code element sample. In this process, each code element represents a specific entry dimension, that is, each code represents a specific physical quantity or parameter, avoiding the step of interpreting the meaning of the data in traditional methods. With this method, sample data no longer needs to be manually interpreted or converted into specific physical quantities one by one, but can be directly logically analyzed based on the characteristics of the code elements. This method can eliminate the differences caused by different interpretations of meaning, making subsequent training and analysis more pure and efficient. Using code element samples can significantly simplify subsequent analysis steps, especially when faced with large amounts of data, and can quickly establish an effective mapping relationship, thereby improving the efficiency and reliability of the analysis.

[0060] Then, based on the obtained codeword samples, first-order training and second-order training are carried out. First-order training is based on the response surface principle. By establishing a mathematical model to describe the relationship between input variables and output performance, the optimal output of each decision node under different input conditions is preliminarily determined. Second-order training is based on neural network learning. Through training with a large amount of sample data, it automatically learns the complex nonlinear relationship between input and output, and further optimizes the decision-making process. It is worth noting that the samples of first-order training and second-order training can be the same sample or different samples. The same sample refers to the use of the same sample data in the two training stages. This method can ensure the consistency and coherence of the training process; different samples refer to the use of different sample data in the two training stages. This method can increase the diversity of training samples and improve the generalization ability and adaptability of the performance adapter.

[0061] Through this method, the training process is more automated and can quickly adapt to different formation conditions and fracture characteristics, ultimately optimizing the performance of the plugging material and ensuring its effectiveness in different geological environments.

[0062] P30: Based on the stratum code distribution, trigger the performance adapter, execute branch parallel decision-making and mutual verification under code targeting, and determine the performance optimization strategy.

[0063] Furthermore, step P30 in the embodiment of the present application further includes:

[0064] P31: Input the stratigraphic code distribution into the first branch and the second branch in the performance adapter, execute branch parallel decision-making for each coding sequence, and determine the first strategy and the second strategy; P32: Execute the proofreading of the first strategy and the second strategy, perform optimization correction of non-co-frequency strategy points, and add them into the performance optimization strategy.

[0065] Specifically, for the defined stratum coding distribution, the performance adapter is triggered to perform branch parallel decision-making and mutual verification under coding targeting, thereby determining the final performance optimization strategy.

[0066] First, the stratigraphic code distribution is input into the first and second branches of the performance adapter. The stratigraphic code distribution encodes specific stratigraphic characteristics based on factors such as fracture characteristics, stress environment, and temperature, providing foundational data for subsequent decision-making. By inputting these code sequences into the two branches of the performance adapter, parallel branch decision-making is performed for the first and second branches, respectively, and preliminary strategies for both are determined. The first branch uses mathematical model analysis to preliminarily determine a performance optimization solution that matches the stratigraphic code distribution, forming the first strategy. The second branch utilizes the deep learning capabilities of a neural network to analyze the same code sequence and derive the second strategy. The decision-making process of these two branches proceeds in parallel, leveraging the strengths of the two different decision-making methods to improve the comprehensiveness and accuracy of decisions.

[0067] Next, the first strategy and the second strategy are proofread, and optimization correction of non-isofrequency strategy points is performed. The main task of this link is to compare the strategies generated by the two branches to ensure that the two are consistent under the same formation conditions. If it is found that certain strategy points have significant differences in frequency or other parameters, that is, non-isofrequency strategy points, further optimization correction is required. The optimization and correction process may include adjusting the proportion of modified components, optimizing the stirring speed and other operations to ensure the coordination of the first strategy and the second strategy in the overall performance optimization. Finally, the corrected strategies are integrated and added to the final performance optimization strategy to ensure that the plugging materials can achieve the best plugging effect according to different formation characteristics during multi-layer mining.

[0068] Through the above steps, the performance of the plugging material can be dynamically adjusted according to the formation code distribution, ensuring the optimal ratio of rheology, expansibility and coagulation under different mining layers and geological conditions, thereby improving the plugging effect of gas extraction boreholes and ensuring the stability and durability of the plugging process.

[0069] P40: Establish a mapping between the performance optimization strategy and the formation code distribution, and distribute it to the material distribution equipment and plugging equipment for directional control and driving.

[0070] Furthermore, step P40 in this embodiment of the present application further includes:

[0071] P41: The stratum code distribution corresponds one-to-one with the performance optimization strategy, and a mapping relationship is established; P42: The stratum code distribution is decentralized to the plugging equipment, and the performance optimization strategy is decentralized to the material distribution equipment, and the same-frequency control is performed based on the mapping relationship.

[0072] Optionally, the performance optimization strategy is ultimately mapped to the formation code distribution, and the mapping results are distributed and sent to the material distribution equipment and plugging equipment for directional control and drive to ensure accurate control and optimized execution of the entire plugging process.

[0073] First, a one-to-one mapping relationship is established between the stratigraphic code distribution and the performance optimization strategy. The stratigraphic code distribution has encoded different stratigraphic regions based on multiple factors such as fracture characteristics, temperature, and stress, allowing subsequent operations to be precisely controlled for different stratigraphic conditions. The performance optimization strategy, based on the characteristics and requirements of different stratigraphic regions in the aforementioned steps, optimizes properties such as rheology, expansibility, and coagulation. By mapping the stratigraphic code distribution to the optimization strategy, it is possible to ensure that the plugging requirements of each stratigraphic region can be met through a specific optimization strategy. This mapping relationship is established based on the corresponding characteristics between the two, ensuring that the plugging material has the most appropriate performance under different stratigraphic conditions.

[0074] Next, the established formation code distribution is transferred to the plugging equipment, while the performance optimization strategy is transferred to the material preparation equipment, and synchronous control is performed based on the previously established mapping relationship. Specifically, the formation code distribution is transmitted to the plugging equipment, which performs specific plugging operations based on this information; the performance optimization strategy is transmitted to the material preparation equipment, which adjusts key parameters such as the ingredient ratio and stirring speed based on the optimization strategy. This process ensures that the proportion and performance of the plugging material can be dynamically adjusted in real time according to the formation conditions, and the operations between the material preparation equipment and the plugging equipment remain synchronized, ensuring the consistency and efficiency of the entire plugging process.

[0075] Through these steps, the entire performance optimization strategy can be precisely implemented from theory to practice, ensuring that the performance of the plugging materials is optimally adjusted for different geological conditions. Through directional control of material selection and plugging equipment, the effectiveness and efficiency of gas extraction borehole plugging are improved. This distributed management and control approach effectively reduces manual intervention, enhances the system's automation, and enables optimization and adjustment based on real-time data, ensuring the stability and durability of the plugging process.

[0076] In summary, the embodiments of the present application have at least the following technical effects:

[0077] This application dynamically adjusts the rheological properties, expansibility and coagulation properties of the plugging material based on the combination of formation code distribution and performance adapter, ensuring that the plugging material achieves optimal performance under different formation conditions; introduces performance adapters and distributed control systems to achieve automatic adjustment and optimization of the plugging process without manual intervention, thereby improving the accuracy and efficiency of the system; optimizes the performance of the plugging material, reduces gas leakage, ensures the stability of the plugging effect, and thus improves the efficiency and safety of gas extraction; through the mapping of formation code distribution and plugging material performance optimization strategy, accurate adaptation to complex geological conditions and fracture characteristics is achieved, solving the problem that the existing technology cannot adapt to different geological environments.

[0078] The technical effect of achieving dynamic optimization control of plugging material performance through formation coding distribution and performance adapter and improving the stability of plugging effect under complex geological conditions has been achieved.

[0079] Example 2 is based on the same inventive concept as the layered mining drilling plugging method based on dynamic adaptation of material properties in the previous embodiment. Figure 2 As shown, the present application provides a layered mining drilling plugging system based on dynamic adaptation of material properties. The system and method embodiments in the present application are based on the same inventive concept. The system includes:

[0080] The formation code distribution definition module 11 is used to define the formation code distribution based on the fracture characteristics-sealing mode according to the fracture detection information through the detection of the target formation area.

[0081] The performance adapter construction module 12 is used to introduce the modifying component, construct the performance adapter with the ratio of the substrate and the modifying component, and embed it in the mining control system, wherein the modification dimension at least includes rheological properties, expansion properties, and coagulation properties. The performance adapter uses code elements as machine language, and includes a first branch based on the response surface principle and a second branch based on the network architecture.

[0082] The performance optimization module 13 is used to trigger the performance adapter according to the stratum code distribution, execute branch parallel decision and mutual verification under code targeting, and determine the performance optimization strategy.

[0083] The directional control driving module 14 is used to establish a mapping between the performance optimization strategy and the formation code distribution, and distribute it to the material distribution equipment and the plugging equipment for directional control driving.

[0084] Furthermore, the stratum code distribution definition module 11 is further configured to perform the following steps:

[0085] Set a fracture classification standard; according to the fracture classification standard, perform fracture classification and plugging mode matching in the target formation area to determine the fracture mode conditions, wherein at least the fracture mode conditions are divided into large-opening fractures-high-pressure injection mode, network micro-fractures-low-pressure infiltration mode, and interlayer dislocation zone-pulse grouting mode.

[0086] Furthermore, the stratum code distribution definition module 11 is further configured to perform the following steps:

[0087] A level constraint is introduced and a preset coding sequence is set; according to the preset coding sequence, the fracture pattern condition under the level constraint is converted into code elements to integrate the spatial phase distribution of the target formation area to determine the formation code distribution.

[0088] Furthermore, the performance adapter construction module 12 is further configured to perform the following steps:

[0089] Determine a first modifying component for modifying rheological properties, wherein the first modifying component at least contains a polycarboxylate water-reducing agent; determine a second modifying component for modifying expansive properties, wherein the second modifying component at least contains a calcium sulfoaluminate expansive agent; determine a third modifying component for modifying setting properties, wherein the third modifying component at least contains a sodium gluconate retarder; and deploy a performance adapter based on the first modifying component, the second modifying component, and the third modifying component by defining a state space-action space.

[0090] Furthermore, the performance adapter construction module 12 is further configured to perform the following steps:

[0091] The state space elements are determined by the substrate penetration path, the action space elements are determined based on the ratio of the first modifying component to the substrate, and the first spatial structure is deployed; the state space elements are determined by the expansion action range based on the layered mining stress environment, the dynamic space elements are determined based on the ratio of the second modifying component to the substrate, and the second spatial structure is deployed; the state space elements are determined by the retarder distribution gradient, the dynamic space elements are determined based on the ratio of the third modifying component to the substrate, and the third spatial structure is deployed.

[0092] Furthermore, the performance adapter construction module 12 is further configured to perform the following steps:

[0093] A first decision node is deployed according to the first spatial structure, a second decision node is deployed according to the second spatial structure, and a third decision node is deployed according to the third spatial structure to determine a decision architecture, wherein the first decision node, the second decision node and the third decision node are in a parallel relationship; first-order training based on the response surface principle is performed on the decision architecture to determine the first branch; second-order training based on neural network learning is performed on the decision architecture to determine the second branch; the first branch and the second branch are parallelized to serve as the performance adapter.

[0094] Furthermore, the performance adapter construction module 12 is further configured to perform the following steps:

[0095] According to the preset coding sequence, sample conversion is performed based on the codeword-entry conversion relationship to determine the codeword sample; based on the codeword sample, first-order training and second-order training are performed, wherein the samples of the first-order training and the second-order training are the same sample or different samples.

[0096] Furthermore, the performance optimization module 13 is further configured to perform the following steps:

[0097] The stratigraphic code distribution is input into the first branch and the second branch in the performance adapter, and branch parallel decision-making is performed for each coding sequence to determine the first strategy and the second strategy; the first strategy and the second strategy are proofread, and optimization correction of non-co-frequency strategy points is performed, and the performance optimization strategy is added.

[0098] Furthermore, the directional control driving module 14 is further configured to perform the following steps:

[0099] The stratum code distribution corresponds to the performance optimization strategy one by one, and a mapping relationship is established; the stratum code distribution is decentralized to the plugging equipment, and the performance optimization strategy is decentralized to the material distribution equipment, and the same frequency control is performed based on the mapping relationship.

[0100] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0101] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

[0102] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A layered mining drilling plugging method based on dynamic adaptation of material properties, characterized in that: The method comprises: By detecting the target formation area and based on the fracture detection information, the formation code distribution based on the fracture characteristics and plugging mode is defined; A modifying component is introduced, and a performance adapter is constructed based on the ratio of the base material to the modifying component. The adapter is embedded and deployed in the mining control system. The modification dimensions include at least rheological properties, expansion properties, and coagulation properties. The performance adapter uses code elements as machine language and includes a first branch based on the response surface principle and a second branch based on the network architecture. According to the stratum code distribution, the performance adapter is triggered to perform branch parallel decision and mutual verification under code targeting to determine the performance optimization strategy; A mapping between the performance optimization strategy and the formation code distribution is established, and distributed to the material distribution equipment and the plugging equipment for directional control and driving.

2. The layered mining drilling plugging method based on dynamic adaptation of material properties according to claim 1 is characterized in that: Define fracture characteristics - sealing mode, including: Setting criteria for fracture classification; According to the fracture classification standard, the fracture classification of the target formation area is matched with the plugging mode to determine the fracture mode conditions, which are at least divided into large-opening fractures-high-pressure injection mode, network micro-cracks-low-pressure infiltration mode, and interlayer dislocation zone-pulse grouting mode.

3. The method for drilling and plugging in stratified mining based on dynamic adaptation of material properties according to claim 2, characterized in that: Introduce hierarchical constraints and set a preset coding sequence; According to the preset code sequence, the fracture mode conditions under the level constraint are converted into code elements, so as to be integrated based on the spatial phase distribution of the target formation area to determine the formation code distribution.

4. The method for drilling and plugging in stratified mining based on dynamic adaptation of material properties according to claim 3, characterized in that: Introduce modifying components and build performance adapters based on the ratio of base material to modifying components, including: determining a first modifying component for modifying rheological properties, wherein the first modifying component comprises at least a polycarboxylate water-reducing agent; Determining a second modifying component for modifying expansion properties, wherein the second modifying component at least comprises a calcium sulfoaluminate expansion agent; determining a third modifying component for modifying setting properties, wherein the third modifying component comprises at least a sodium gluconate retarder; By defining a state space-action space, a performance adapter based on the first modifying component, the second modifying component and the third modifying component is deployed.

5. The layered mining drilling plugging method based on dynamic adaptation of material properties according to claim 4 is characterized in that: Define the state space-action space, including: Determining state space elements based on the substrate penetration path, determining action space elements based on the ratio of the first modifying component to the substrate, and deploying a first spatial structure; Determine the state space element based on the expansion effect range of the layered mining stress environment, determine the dynamic space element based on the ratio of the second modified component to the base material, and deploy the second space structure; The state space elements are determined by the retarder distribution gradient, the dynamic space elements are determined based on the ratio of the third modified component to the base material, and the third space structure is deployed.

6. The method for drilling and plugging in stratified mining based on dynamic adaptation of material properties according to claim 5, characterized in that: Deploy a first decision node according to the first spatial structure, deploy a second decision node according to the second spatial structure, and deploy a third decision node according to the third spatial structure to determine a decision architecture, wherein the first decision node, the second decision node, and the third decision node are in a parallel relationship; performing first-order training based on response surface theory on the decision architecture to determine the first branch; performing second-order training based on neural network learning on the decision architecture to determine the second branch; The first branch and the second branch are operated in parallel as the performance adapter.

7. The method for drilling and plugging in stratified mining based on dynamic adaptation of material properties according to claim 6, characterized in that: The first-order training and the second-order training include: According to the preset coding sequence, sample conversion is performed based on the conversion relationship between code element and term to determine the code element sample; Taking the code element samples as a reference, first-order training and second-order training are performed, wherein the samples of the first-order training and the second-order training are the same samples or different samples.

8. The method for drilling and plugging in stratified mining based on dynamic adaptation of material properties according to claim 1, characterized in that: Perform branch parallel decision-making and cross-verification under coding targets to determine performance optimization strategies, including: Inputting the stratigraphic code distribution into the first branch and the second branch of the performance adapter, executing branch parallel decision making for each code sequence, and determining a first strategy and a second strategy; The first strategy and the second strategy are verified, and optimization correction of non-co-frequency strategy points is performed, and the performance optimization strategy is added.

9. The method for drilling and plugging in stratified mining based on dynamic adaptation of material properties according to claim 1, characterized in that: The stratum code distribution corresponds to the performance optimization strategy in a one-to-one manner, and a mapping relationship is established; The formation code distribution is decentralized to the plugging equipment, and the performance optimization strategy is decentralized to the material matching equipment, and the same-frequency control is performed based on the mapping relationship.

10. A layered mining drilling and plugging system based on dynamic adaptation of material properties, characterized in that: The system comprises: A formation code distribution definition module, wherein the formation code distribution definition module is used to define a formation code distribution based on fracture characteristics and a plugging mode according to fracture detection information through detection of a target formation area; A performance adapter building module is used to introduce a modifying component, build a performance adapter based on the ratio of the base material to the modifying component, and embed it into the mining control system. The modification dimensions include at least rheological properties, expansion properties, and coagulation properties. The performance adapter uses code elements as machine language and includes a first branch based on the response surface principle and a second branch based on a network architecture. A performance optimization module, configured to trigger the performance adapter based on the stratum code distribution, execute branch parallel decision-making and mutual verification under code targeting, and determine a performance optimization strategy; A directional control driving module is used to establish a mapping between the performance optimization strategy and the formation code distribution, and distribute it to the material distribution equipment and the plugging equipment for directional control driving.

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