Multi-stage circulating treatment system and method for drilling cuttings slurry

Abstract

The present invention relates to the technical field of drilling waste treatment, and specifically relates to a multi-stage circulating treatment system and method for drill cuttings and mud, including an automatic classification module, a dynamic monitoring module, a mud purification module, a separation optimization module, a waste residue classification and recycling module, and an intelligent control module; wherein: The automatic classification module: includes a particle identification unit and a variable-frequency classification unit; the particle identification unit uses a multispectral sensor to perform real-time detection of the size, shape, and density of particles in drill cuttings and mud; the variable-frequency classification unit is used to adjust the classification speed according to the detection data provided by the particle identification unit and perform dynamic classification of particles; The dynamic monitoring module: includes an on-line sensor and a data analysis unit; The present invention realizes the efficient classification, filtration, separation, and intelligent classification of waste residues of drill cuttings and mud through intelligent monitoring and automatic adjustment technologies, ensuring the efficient operation of the system, the improvement of resource recovery rate, and the reduction of environmental pollution.

Description

Technical Field

[0001] The present invention relates to the technical field of drilling waste treatment, and particularly to a multi-stage circulating treatment system and method for drill cuttings and mud. Background Art

[0002] During the exploitation of resources such as oil, natural gas, and minerals, drilling operations generate a large amount of drill cuttings and mud. These wastes contain various particles of different sizes, chemical pollutants, and mud components. Treating these wastes is crucial for resource reuse and environmental protection. Existing treatment methods usually adopt single separation, filtration, or chemical purification means, but there are obvious limitations in efficient grading, purification, and classification treatment. Single technologies are difficult to adapt to the complex and changeable characteristics of mud particles, resulting in low treatment efficiency, high energy consumption, easy clogging of equipment, and inability to fully recover valuable resources. In addition, with the improvement of environmental protection requirements and the complexity of drilling operations, the treatment system needs to have efficient and intelligent automatic adjustment capabilities to ensure stable operation under various working conditions.

[0003] The current technical problems mainly focus on three aspects: First, how to achieve efficient grading and filtration of particles of different sizes and densities in the mud to avoid equipment clogging and efficiency reduction; Second, how to dynamically adjust the treatment process according to the changes in particle characteristics and composition in the mud to ensure the automatic optimization operation of the system; Third, how to intelligently classify the separated waste residues to achieve resource utilization and minimize environmental pollution to the greatest extent. Therefore, developing a multi-stage circulating treatment system and method for drill cuttings and mud that can integrate grading, filtration, separation, and waste residue classification treatment and has a dynamic adjustment function has become an urgent need in the current technical field. Summary of the Invention

[0004] Based on the above purposes, the present invention provides a multi-stage circulating treatment system and method for drill cuttings and mud.

[0005] The multi-stage circulating treatment system for drill cuttings and mud includes an automatic grading module, a dynamic monitoring module, a mud purification module, a separation optimization module, a waste residue classification and recovery module, and an intelligent control module; wherein:

[0006] The automatic grading module: includes a particle recognition unit and a variable-frequency grading unit;

[0007] The particle recognition unit detects the size, shape, and density of particles in drill cuttings and mud in real time through a multi-spectral sensor, and identifies the particle size and particle density;

[0008] The variable-frequency grading unit is used to adjust the grading speed according to the detection data provided by the particle recognition unit and dynamically grade the particles;

[0009] Dynamic monitoring module: includes on-line sensors and data analysis unit;

[0010] The on-line sensors are installed between the automatic classification module and the separation optimization module, and are used to monitor the particle flow rate, concentration and pressure in real time after classification;

[0011] The data analysis unit analyzes the particle distribution data and the mud state based on the monitoring data of the on-line sensors to identify the mud state data;

[0012] Mud purification module: includes multi-stage filtration unit and micro chemical treatment unit;

[0013] The multi-stage filtration unit is used to filter particles sequentially through filter meshes with different pore sizes;

[0014] The micro chemical treatment unit is used to automatically adjust the dosage of chemical reagents according to the mud state data of the dynamic monitoring module;

[0015] Separation optimization module: includes a centrifugal separation unit and an automatic screen adjustment unit;

[0016] The centrifugal separation unit is used to automatically adjust the centrifugal speed based on the particle flow rate and concentration data provided by the dynamic monitoring module, so that particles with different particle sizes in the mud are separated;

[0017] The automatic screen adjustment unit is used to adjust the aperture size of the filter screen according to the feedback data of the dynamic monitoring module to ensure the maximum separation efficiency;

[0018] Waste residue classification and recycling module: includes a waste residue classification unit and a resource utilization unit;

[0019] The waste residue classification unit automatically classifies the waste residue based on the separated particle data provided by the separation optimization module;

[0020] The resource utilization unit is used to physically or chemically process the classified waste residue;

[0021] Intelligent control module: includes a data acquisition unit, an analysis and decision-making unit and an execution control unit;

[0022] The data acquisition unit is used to collect the operation data of the automatic classification module, the dynamic monitoring module, the mud purification module, the separation optimization module and the waste residue classification and recycling module in real time;

[0023] The analysis and decision-making unit formulates an optimization strategy for the system operation based on the collected data, combined with historical operation parameters and real-time monitoring data;

[0024] The execution control unit is used to automatically adjust the operation parameters of each module according to the optimization strategy output by the analysis and decision-making unit.

[0025] Optionally, the variable-frequency grading unit includes:

[0026] A speed control sub-unit: Through an electric speed control device, according to the preset grading standard of particle size and density, the rotation speed of the grading equipment is adjusted in real time to ensure that the grading process adapts to the dynamic changes of different particles;

[0027] A frequency adjustment sub-unit: By controlling the circuit to adjust the vibration frequency of the grading device, the switching between high frequency and low frequency is realized to adapt to the particle size and density of different particles;

[0028] A particle guiding sub-unit: Used to adjust the movement path of particles according to the changes in rotation speed and vibration frequency during the grading process, ensuring that various particles enter the corresponding grading areas according to the set trajectories.

[0029] Optionally, the data analysis unit includes:

[0030] A particle distribution calculation sub-unit: By receiving the particle size and concentration provided by the particle recognition unit and the dynamic monitoring module, using the formula where P d is the proportion of particles with particle size d in the total particles, n d is the number of particles with particle size d, N t is the total number of particles, calculate the size distribution curve of the particles;

[0031] A mud viscosity monitoring sub-unit: According to the particle flow rate and pressure measured by the on-line sensor, using the formula where η represents the viscosity of the mud, τ represents the shear stress, represents the shear rate, calculate the real-time viscosity value of the mud;

[0032] A mud composition identification sub-unit: Based on the spectral data provided by the multi-spectral sensor, by comparing with the mud composition database, identify the proportion of each component in the mud.

[0033] Optionally, the multi-stage filtration unit includes:

[0034] A coarse filtration sub-unit: Used for primary particle filtration, including multiple layers of filter meshes with large pore diameters, and the pore diameter range is 0.5 mm to 2 mm;

[0035] A fine filtration sub-unit: Used for filtering smaller particles, and the pore diameter range of the filter mesh is 0.01 mm to 0.5 mm;

[0036] An automatic adjustment sub-unit: Used to automatically adjust the pore diameter selection and filtration order of the filter meshes in the coarse filtration sub-unit and the fine filtration sub-unit according to the particle concentration and size data provided by the dynamic monitoring module.

[0037] Optionally, the microchemical treatment unit includes:

[0038] Chemical reagent dosing sub-unit: Automatically controls the dosing amount of chemical reagents by receiving real-time data on the pollutant concentration and mud flow rate provided by the dynamic monitoring module.

[0039] Concentration adjustment sub-unit: Automatically adjusts the concentration of the dosed chemical reagents based on mud state data, including the pH value or pollutant content in the mud.

[0040] Feedback control sub-unit: Adjusts the subsequent dosing amount according to the feedback data on the treatment effect after chemical reagent dosing, optimizes the subsequent chemical reagent dosing strategy by monitoring the pollutant residue and mud properties after mud treatment, to prevent over-dosing or under-dosing.

[0041] Optionally, the centrifugal separation unit includes:

[0042] Rotation speed control sub-unit: Used to adjust the rotation speed of the centrifugal separation unit according to the particle flow rate and particle concentration data provided by the dynamic monitoring module, ensuring that the rotation speed dynamically matches the flow rate and concentration of particles in the mud.

[0043] Flow rate adjustment sub-unit: Used to control the flow rate of the mud entering the centrifugal separation unit according to the particle flow rate data, so that the flow rate adapts to the rotation speed adjustment of the centrifugal separation.

[0044] Particle size detection feedback sub-unit: Based on the particle size data provided by the dynamic monitoring module, judges the effect of centrifugal separation by real-time detection of the particle size after separation. If the separation effect is detected to be poor, the speed setting of the rotation speed control sub-unit is readjusted.

[0045] Optionally, the automatic screen adjustment unit includes:

[0046] Aperture selection sub-unit: Adjusts the aperture size of the screen by receiving the particle size and flow rate data provided by the dynamic monitoring module, to achieve effective separation of particles with different particle sizes.

[0047] Filtration precision adjustment sub-unit: Used to dynamically adjust the aperture of the screen according to the particle concentration and particle distribution data in the mud provided by the dynamic monitoring module, ensuring an increase in filtration precision when the particle concentration is high.

[0048] A multi-stage circulating treatment method for drill cuttings mud, implemented by the above-mentioned multi-stage circulating treatment system for drill cuttings mud, includes the following steps:

[0049] S1: Conducts preliminary classification of the particles in the drill cuttings mud, adjusts the classification speed in real time by detecting the particle size and density, and conducts dynamic classification according to the characteristics of different particles.

[0050] S2: Monitor the state of the classified mud in real time, obtain data on the flow rate, concentration, and viscosity of the particles, and analyze and identify the state information of the mud;

[0051] S3: Conduct multi-stage filtration on the classified mud, and dynamically adjust the pore size and filtration sequence during the process according to the changes in particle concentration and size;

[0052] S4: Adjust the separation speed in the mud according to the flow rate and concentration of the particles, efficiently separate particles of different particle sizes by adjusting the speed, and dynamically adjust the filtration pore size according to the feedback data to optimize the separation effect;

[0053] S5: Automatically classify the separated waste residue, calculate the mass and shape parameters of the particles, and determine whether they are recyclable;

[0054] S6: Based on the real-time monitored data and historical operation parameters, formulate system optimization strategies, and automatically adjust the operation parameters of each step, including classification speed, filtration pore size, and separation speed, to ensure the best operation state under different operating conditions.

[0055] Advantages of the present invention:

[0056] In the present invention, by real-time monitoring of key data such as particle size, concentration, flow rate, and viscosity in the drill cuttings mud, combined with intelligent adjustment technology, efficient multi-stage classification, filtration, and separation of particles in the mud are achieved. This method can dynamically adjust the classification speed, filtration pore size, and separation speed according to particle characteristics to ensure precise separation of particles of different particle sizes, avoiding problems such as equipment blockage and reduced processing efficiency. At the same time, the system automatically optimizes the processing flow through intelligent decision-making, reduces energy consumption, and improves the overall operation efficiency and stability.

[0057] In the present invention, the separated waste residue is intelligently classified through automatic classification technology, and whether it is recyclable is judged according to the physical and chemical characteristics of the waste residue, thereby realizing the resource utilization of waste. This technology can not only improve the resource recovery rate, but also reduce environmental pollution, lower the cost of waste treatment, and further enhance the environmental protection and economic benefits in drilling operations. Brief Description of the Drawings

[0058] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only for the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0059] Figure 1Schematic diagram of the multi-stage circulating treatment system for drilling waste mud according to an embodiment of the present invention;

[0060] Figure 2 Schematic diagram of the multi-stage circulating treatment method for drilling waste mud according to an embodiment of the present invention. Detailed implementation manners

[0061] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. At the same time, it should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments. For some well-known technologies, those skilled in the art can also adopt other alternative methods for implementation; moreover, the accompanying drawings are only for more specifically describing the embodiments, and are not intended to specifically limit the present invention.

[0062] It should be pointed out that in the specification, when referring to "an embodiment", "embodiment", "exemplary embodiment", "some embodiments", etc., it indicates that the described embodiment may include specific features, structures or characteristics, but not necessarily every embodiment includes such specific features, structures or characteristics. In addition, when combining an embodiment to describe a specific feature, structure or characteristic, implementing such a feature, structure or characteristic in combination with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the relevant art.

[0063] Generally, terms can be understood at least in part from their use in the context. For example, at least in part depending on the context, the term "one or more" used herein can be used to describe any feature, structure or characteristic in a singular sense, or can be used to describe a combination of features, structures or characteristics in a plural sense. In addition, the term "based on" can be understood as not necessarily intended to convey a set of exclusive factors, but rather, at least in part depending on the context, allowing for the existence of other factors that may not be explicitly described.

[0064] As Figure 1 shown, the multi-stage circulating treatment system for drilling waste mud includes an automatic classification module, a dynamic monitoring module, a mud purification module, a separation optimization module, a waste residue classification and recycling module, and an intelligent control module; wherein:

[0065] Automatic classification module: includes a particle recognition unit and a variable-frequency classification unit;

[0066] The particle recognition unit uses a multispectral sensor to perform real-time detection of the size, shape, and density of particles in the drilling waste and mud, and identifies the particle size and particle density;

[0067] The variable-frequency classification unit is used to adjust the classification speed according to the detection data provided by the particle recognition unit, and perform dynamic classification on the particles. The particle size and shape data generated by this automatic classification module are transmitted to the dynamic monitoring module in real time for subsequent processing decisions;

[0068] Dynamic monitoring module: including an online sensor and a data analysis unit;

[0069] The online sensor is installed between the automatic grading module and the separation optimization module, and is used to monitor the flow rate, concentration, and pressure of the particles after grading in real time;

[0070] The data analysis unit analyzes the particle distribution data and the mud state based on the monitoring data of the online sensor to identify the mud state data, including the particle size distribution, particle concentration, particle morphology and density, mud viscosity, and mud composition of the mud; the analysis results are transmitted to the separation optimization module for optimizing the subsequent separation process and are fed back to the intelligent control module to achieve dynamic adjustment of the system parameters;

[0071] Mud purification module: including a multi-stage filtration unit and a micro chemical treatment unit;

[0072] The multi-stage filtration unit is used to sequentially filter particles through filter meshes with different pore sizes, and the residual particles in the mud are fed back to the dynamic monitoring module in real time through the filtration data;

[0073] The micro chemical treatment unit is used to automatically adjust the dosage of chemical reagents according to the mud state data of the dynamic monitoring module to ensure the stable composition of the mud;

[0074] Separation optimization module: including a centrifugal separation unit and an automatic screen adjustment unit;

[0075] The centrifugal separation unit is used to automatically adjust the centrifugal speed based on the particle flow rate and concentration data provided by the dynamic monitoring module to separate particles with different particle sizes in the mud;

[0076] The automatic screen adjustment unit is used to adjust the aperture size of the filter mesh according to the feedback data of the dynamic monitoring module to ensure the maximization of the separation efficiency, and feed back the adjusted particle size and flow rate data to the intelligent control module;

[0077] Waste residue classification and recycling module: including a waste residue classification unit and a resource utilization unit;

[0078] The waste residue classification unit automatically classifies the waste residue based on the separated particle data provided by the separation optimization module;

[0079] The resource utilization unit is used to physically or chemically process the classified waste residue;

[0080] Intelligent control module: including a data acquisition unit, an analysis and decision-making unit, and an execution control unit;

[0081] The data acquisition unit is used to collect the operation data of the automatic classification module, dynamic monitoring module, mud purification module, separation optimization module, and waste residue classification and recycling module in real time;

[0082] The analysis and decision-making unit formulates the optimization strategy for the system operation based on the collected data, combined with the historical operation parameters and real-time monitoring data;

[0083] The execution control unit is used to automatically adjust the operation parameters of each module according to the optimization strategy output by the analysis and decision-making unit to ensure the stable and efficient operation of the overall system.

[0084] The variable-frequency classification unit includes:

[0085] The speed control sub-unit: Through the electric speed control device, according to the preset classification standard of particle size and density, it adjusts the rotation speed of the classification equipment in real time to ensure that the classification process adapts to the dynamic changes of different particles;

[0086] The frequency adjustment sub-unit: Adjusts the vibration frequency of the classification device through the control circuit to realize the switching between high frequency and low frequency to adapt to the particle size and density of different particles and ensure the accuracy and efficiency of the classification process;

[0087] The particle guiding sub-unit: Used to adjust the movement path of the particles according to the changes in the rotation speed and vibration frequency during the classification process to ensure that various particles enter the corresponding classification area according to the set trajectory and prevent particle mixing; The above variable-frequency classification unit realizes the dynamic adjustment of the equipment rotation speed, frequency, and particle guiding through the collaborative work of the above sub-units, ensuring the accuracy and operability of classification under different particle characteristic conditions.

[0088] In a specific embodiment, when the drill cuttings particles entering the system are relatively large in size (for example, the average diameter D is 2 mm) and high in density (for example, the density ρ is 2.5 g / cm³), the system obtains these parameters through the particle recognition unit and transmits them to the speed control sub-unit; The speed control sub-unit calculates the optimal rotation speed of the equipment according to the formula where k1 is a constant related to the characteristics of the classification equipment. For example, if k1 is a constant 5, the rotation speed N is units / second. This adjustment process ensures that the rotation speed of the system matches the particle size and density, enabling large particles to be effectively coarsely classified while small particles do not leave the classification area prematurely;

[0089] For the above-identified particle size and density information, the frequency adjustment sub-unit is responsible for adjusting the vibration frequency of the equipment to achieve further subdivision of the particles. According to the formula where k2 is a constant of the vibration device. For example, taking k2 = 50, the vibration frequency f is Hertz, which means that smaller particles require a higher vibration frequency for classification to ensure that particles of different sizes can be screened according to a predetermined frequency, so as to improve the accuracy of classification;

[0090] The particle guiding subunit automatically adjusts the movement path of the particles according to the particle recognition data in the above embodiments, the rotational speed N and the frequency f during the classification process, using the formula where θ is the angle of particle guidance and k3 is a constant; assuming k3 is 2, the guiding angle θ is radians. This subunit adjusts the angle of the guiding device so that different particles enter the corresponding processing paths according to their classification results, ensuring precise guidance and preventing particle mixing, thereby improving the efficiency of classification.

[0091] The data analysis unit includes:

[0092] The particle distribution calculation subunit: By receiving the particle size and concentration provided by the particle recognition unit and the dynamic monitoring module, using the formula where P d is the proportion of particles with particle size d in the total particles, n d is the number of particles with particle size d, and N t is the total number of particles, calculates the size distribution curve of the particles. This distribution data can be used for the system to adjust subsequent classification and purification operations in real time to ensure classification accuracy;

[0093] The mud viscosity monitoring subunit: According to the particle flow rate and pressure measured by the online sensor, using the formula where η represents the viscosity of the mud, τ represents the shear stress, represents the shear rate, and calculates the real-time viscosity value of the mud; this viscosity data is used to guide the separation and purification module for adjustment to ensure that the mud fluidity meets the process requirements;

[0094] The mud composition identification subunit: Based on the spectral data provided by the multispectral sensor, by comparing with the mud composition database, identifies the proportion of each component in the mud. This subunit can extract the concentrations of solid particles, liquid components and harmful substances in the mud, and calculates relevant processing parameters based on this to ensure that the purification module adjusts the dosage of chemical reagents according to the actual composition; Through the collaborative work of the above subunits, the data analysis unit can comprehensively and real-time analyze the particle distribution, viscosity and composition of the mud, ensuring that the system adjusts the operating parameters of each processing module under different working conditions to achieve precise and efficient mud treatment.

[0095] The multi-stage filtration unit includes:

[0096] Coarse filter unit: Used for primary particle filtration, including multiple layers of filter screens with large pore diameters ranging from 0.5 mm to 2 mm. The function of this subunit is to remove large particle drill cuttings and impurities in the mud to prevent blockage during the subsequent fine filtration stage and facilitate subsequent processing;

[0097] Fine filter unit: Used for filtering smaller particles, with the pore diameter of the filter screen ranging from 0.01 mm to 0.5 mm. The fine particles are filtered step by step through multiple filter screens with small pore diameters to make the mud reach the required purity. This process ensures that the residual particles in the mud are gradually filtered, providing a finer mud for the subsequent mud purification module;

[0098] Automatic adjustment subunit: Used to automatically adjust the pore diameter selection and filtration sequence of the filter screens in the coarse filter unit and the fine filter unit according to the particle concentration and size data provided by the dynamic monitoring module, ensuring that when the characteristics of the mud particles change, the selection of the filter screen and the filtration path can respond in a timely manner, avoiding a decrease in filtration efficiency or equipment blockage.

[0099] The specific steps for adjusting the pore diameter and filtration sequence of the filter screens in the coarse filter unit and the fine filter unit are as follows:

[0100] First, by receiving the particle concentration C p and particle size D p data, using the formula where A f represents the currently selected filter screen pore diameter, and m1 is a constant related to the filter screen characteristics of the filtration equipment. This formula ensures that when the particle size is large D p and the concentration is low C p , a filter screen with a larger pore diameter is selected for rapid filtration; when the particle size is small and the concentration is high, a filter screen with a smaller pore diameter is selected to improve the filtration accuracy;

[0101] Then, based on the particle size data D p , the sequence of the coarse filter unit and the fine filter unit is adjusted by judging the change trend of the particle size. Specifically, by judging the relationship between D p and the preset particle size threshold D th . If D p > D th , the coarse filter unit is preferentially enabled for preliminary filtration; if D p ≤D th , the fine filter unit is preferentially enabled for detailed filtration; ensuring dynamic adjustment of the filtration sequence according to the size and characteristics of the particles.

[0102] The trace chemical treatment unit includes:

[0103] Chemical reagent dosing subunit: By receiving the pollutant concentration C in the mud provided by the dynamic monitoring modulep and the mud flow rate Q m Based on the real-time data, automatically control the dosage of chemical reagents. The specific formula is: V t = m2·C p ·Q m , where V t is the dosage volume of chemical reagents, m2 is a proportionality constant related to the characteristics of specific reagents and mud, ensuring that the dosage of chemical reagents matches the pollutant concentration and mud flow rate to achieve the best treatment effect;

[0104] Concentration adjustment sub-unit: Based on the mud state data, including the pH value or pollutant content in the mud, automatically adjust the concentration of the chemical reagents put in. Specifically, through the monitoring feedback of the mud, calculate whether the current reagent concentration meets the treatment requirements. If not, the system will calculate according to the formula C r = C b +ΔC, where C r is the adjusted reagent concentration, C b is the basic reagent concentration, and ΔC is the concentration increment adjusted according to the monitoring data, ensuring that the chemical reagent concentration remains balanced with the needs of pollutants in the mud;

[0105] Feedback control sub-unit: According to the feedback data of the treatment effect after the chemical reagents are put in, adjust the subsequent dosage. By monitoring the pollutant residue and mud properties after mud treatment, optimize the subsequent chemical reagent dosing strategy to prevent overdosage or underdosage. The system adjusts the dosing formula V f = V t ·F, where V f is the final dosage of chemical reagents, and F is the feedback correction coefficient, ensuring the dynamic adjustment and optimization of the chemical reagent dosing process; Through the automatic dosing, concentration adjustment and feedback control of chemical reagents, the dosing amount of chemical reagents can be accurately controlled according to the mud state data provided by the dynamic monitoring module, ensuring stable and accurate treatment effects and avoiding reagent waste and improper treatment problems.

[0106] The centrifugal separation unit includes:

[0107] Rotation speed control sub-unit: Used to adjust the rotation speed N p of the centrifugal separation unit according to the particle flow velocity v p and particle concentration C c data provided by the dynamic monitoring module. The formula is: where N c is the rotation speed of the centrifugal separation unit, and k3 is a constant related to the equipment characteristics, ensuring that the rotation speed is dynamically matched with the particle flow velocity and concentration in the mud. Particles with high concentration or high flow velocity require a higher rotation speed to ensure effective separation, while particles with low concentration or low flow velocity are suitable for a lower rotation speed;

[0108] Flow rate adjustment sub - unit: used to control the flow rate of the slurry entering the centrifugal separation unit according to the particle flow rate v p data, so that the flow rate adapts to the rotational speed adjustment of the centrifugal separation. The function of the flow rate adjustment sub - unit is to ensure that the particles in the centrifugal separation unit can be effectively separated within an appropriate time, and to avoid the influence of too fast or too slow flow on the separation effect;

[0109] Particle size detection and feedback sub - unit: Based on the particle size data D provided by the dynamic monitoring module p , by real - time detecting the size of the separated particles, judge the effect of the centrifugal separation. If it is detected that the separation effect is not good (for example, small particles are not effectively separated), then re - adjust the speed setting of the rotational speed control sub - unit to make the rotational speed better match the separation requirements of different particle sizes; Through the collaborative work of the above - mentioned sub - units, the centrifugal separation unit can dynamically adjust the centrifugal speed according to the flow rate and concentration data of the particles in the slurry, ensure the efficient separation of particles with different particle sizes in the slurry, improve the separation accuracy and efficiency, and at the same time prevent the over - load of the equipment or waste of resources.

[0110] The automatic screen adjustment unit includes:

[0111] Aperture selection sub - unit: By receiving the particle size D provided by the dynamic monitoring module p and the flow rate v p data, adjust the aperture size of the screen to achieve the effective separation of particles with different particle sizes; The specific adjustment formula is: A s = f1·D p , where A s is the aperture size of the screen, and f1 is a constant related to the characteristics of the screen. This sub - unit automatically selects the optimal screen aperture according to the change of the particle size, ensures that large particles are quickly filtered, and small particles can enter the next filtration stage;

[0112] Filtration precision adjustment sub - unit: used to dynamically adjust the aperture of the screen according to the particle concentration C in the slurry and the particle distribution data provided by the dynamic monitoring module p to ensure that the filtration precision is improved when the particle concentration is high. Specifically, when the particle concentration is high, the system will automatically reduce the aperture of the screen to improve the screening efficiency; conversely, when the particle concentration is low, the aperture is appropriately increased to improve the processing speed.

[0113] The waste residue classification unit specifically includes:

[0114] Receive the particle size and particle density data from the separation optimization module, calculate the mass of the particles, and judge the physical properties of the particles according to the volume and density characteristics of the particles, so as to provide a basis for subsequent classification;

[0115] Evaluate the recyclability of particles using their mass and shape parameters. By calculating the recovery coefficient, determine whether the particles have recycling value. If the recovery coefficient reaches the preset threshold, mark them as recyclable particles; otherwise, classify them as non-recyclable waste residues.

[0116] For recyclable particles, calculate the recovery value based on their mass and purity, and sort them according to the market value of the particles to ensure that particles with higher recovery value are processed first, facilitating the maximization of resource reuse.

[0117] For non-recyclable waste residues, calculate their environmental hazard coefficient based on the chemical composition and density of the particles. If the hazard coefficient exceeds the preset threshold, the particles will be marked as hazardous waste residues and require special treatment; otherwise, classify them as general waste for conventional treatment.

[0118] According to the classification results, guide the recyclable and non-recyclable waste residues to different treatment paths. The recyclable waste residues enter the resource utilization unit for reuse, and the non-recyclable waste residues enter the safety treatment process according to their environmental hazard levels to complete the automatic classification process. Through the above steps, the waste residue classification unit can effectively classify the waste residues automatically, ensure the maximization of recycled resources and the safe treatment of waste, and improve the overall processing efficiency and environmental protection effect of the system.

[0119] The specific operation steps for automatically classifying waste residues are as follows:

[0120] First, receive the particle size D p and particle density ρ p data provided by the separation optimization module, and calculate the mass m p of the particles. The formula is: m p =V p ·ρ p , where V p is the volume of the particles, and the volume V p is calculated based on the particle size D p . The purpose of this step is to provide the basic physical properties of the particles for subsequent classification.

[0121] Then, based on the calculated particle mass m p and particle shape parameter S p (this shape parameter is provided by real-time detection of the dynamic monitoring module), determine whether the particles are recyclable waste residues. The formula is: where k4 is a constant related to the characteristics of the waste residue, and calculate the recovery coefficient R p of the particles. If R p ≥R th (where R thIf the recovery coefficient of the particle is greater than or equal to the preset recovery coefficient threshold, the particle is marked as recyclable; otherwise, the particle will enter the non-recyclable waste residue category;

[0122] Next, the recyclable waste residues are further classified according to their recovery value, and the recovery value V of each particle is calculated. r , through the formula V r = C m ·m p ·γ, where C m is the market price of the recycled material, and γ is the purity coefficient of the particle (provided by the dynamic monitoring module). The recovery value is calculated based on the purity and quality of the particle. This step ensures that the recycled particles are prioritized according to their market value, facilitating resource utilization;

[0123] Finally, for the non-recyclable waste residues, further based on their chemical composition data C p and density ρ p , through the formula calculate the environmental hazard coefficient H p of the particle. If H p ≥ H th (where H th is the threshold of the environmental hazard coefficient), then the particle enters the hazardous waste residue category and needs to be specially treated; if H p < H th , the particle is treated as general waste.

[0124] The analysis and decision-making unit specifically includes:

[0125] Receive real-time data from the dynamic monitoring module and other modules, including the particle distribution data, particle flow rate, concentration, and viscosity values of the mud. At the same time, call the operating parameters in the system historical database, including data on the mud treatment efficiency, equipment load, filtration efficiency, and energy consumption for processing similar working conditions in the past. The purpose of this step is to obtain a comprehensive data basis to ensure that the optimization strategy can be adjusted in combination with the current working conditions and past experience;

[0126] Compare and analyze the real-time data with the historical operating parameters to identify the differences between the current system operating state and the historical best state. Through comparison and analysis, if it is found that data such as the particle concentration and flow rate in the mud show fluctuations different from the historical data, the analysis and decision-making unit will mark these changes as potential system operating abnormal points, indicating the areas that need to be optimized;

[0127] Based on the data comparison results, calculate the optimized paths for different operation strategies, and propose multiple optimization strategies according to the parameters of the equipment's operating load, separation efficiency, and filter screen life, combined with the proven best operation strategies in historical working conditions. These solutions will formulate a set of optional optimization strategies according to different objectives such as minimizing energy consumption, maximizing efficiency, and extending equipment life;

[0128] Evaluate the potential effects of all optimization strategies, predict the treatment effects, energy consumption, and equipment wear after adopting different strategies under current conditions, and identify the best optimized path in advance through prediction to provide a basis for subsequent decision-making; Through these steps, the analysis and decision-making unit can intelligently formulate and execute the optimization strategies for system operation, ensure that the system makes decisions in combination with real-time working conditions and historical best experiences, and continuously optimize the efficiency and stability of the entire treatment process.

[0129] The specific operation steps are as follows:

[0130] First, compare the real-time monitoring data, including particle concentration C p (unit: particles per cubic meter), flow velocity v p (unit: meters per second), viscosity η p (unit: pascal-second), and equipment load L r (unit: percentage), with the historical operation parameters, such as treatment efficiency E h (unit: percentage), equipment wear W h (unit: wear rate), filtration efficiency F h (unit: percentage), historical equipment load L h (unit: percentage), and calculate the difference: ΔD = D r - D h , where D r is the real-time data, D h is the historical data, and ΔD is the difference value. If the difference value ΔD exceeds the preset threshold ΔD th , it is marked as the area that needs to be optimized;

[0131] Next, according to the comparison results, calculate the priorities of different optimized paths, considering energy consumption E, separation efficiency E f and equipment life L. The formula for calculating the priority score of the optimized path is: where P o is the priority score of the optimized path, w1, w2, and w3 are the weights of energy consumption, efficiency, and equipment life respectively, E min is the historical minimum energy consumption, E f,max is the historical best separation efficiency, and L max is the maximum life of the equipment;

[0132] Then, according to the prediction model, calculate the expected impact of different optimization strategies on the system, focusing on predicting changes in separation efficiency and equipment life. The effect prediction formula for the optimization strategy is: where E pred is the predicted processing efficiency, C p is the real-time particle concentration, C p,max is the maximum particle concentration processed by the system, and L is the current equipment life. Preferably, based on the above analysis, select the optimal operating strategy and calculate the adjusted operating parameters. For example, for the centrifugal separation unit, the adjusted rotational speed N opt is determined by the following formula: where N base is the basic rotational speed of the centrifugal equipment, and ΔD is the difference between real-time and historical data. The adjusted rotational speed is optimized according to the difference value to ensure the maximization of separation efficiency.

[0133] As Figure 2 shown, a multi-stage circulation treatment method for drill cuttings slurry is implemented by the above-mentioned multi-stage circulation treatment system for drill cuttings slurry, and includes the following steps:

[0134] S1: Conduct preliminary classification on the particles in the drill cuttings slurry. By detecting the size and density of the particles, adjust the classification speed in real time, and conduct dynamic classification according to the characteristics of different particles to ensure the effectiveness of preliminary particle separation;

[0135] S2: Monitor the state of the classified slurry in real time, obtain data on the flow rate, concentration, and viscosity of the particles, analyze and identify the state information of the slurry, and provide a decision-making basis for subsequent purification and separation treatment;

[0136] S3: Conduct multi-stage filtration on the classified slurry, and dynamically adjust the pore size and filtration sequence during the process according to changes in particle concentration and size to ensure the maximization of filtration efficiency;

[0137] S4: Adjust the separation speed in the slurry according to the flow rate and concentration of the particles, conduct efficient separation of particles with different particle sizes by adjusting the speed, and at the same time dynamically adjust the filtration pore size according to the feedback data to optimize the separation effect and ensure that particles with different particle sizes can be effectively separated;

[0138] S5: Automatically classify the separated waste residue, calculate the mass and shape parameters of the particles, judge whether they are recyclable, conduct resource utilization treatment on the recyclable waste residue, and conduct safe disposal on the non-recyclable waste residue to ensure the efficiency and accuracy of classification treatment;

[0139] S6: Based on the real-time monitored data and historical operating parameters, formulate system optimization strategies and automatically adjust the operating parameters of each step, including the classification speed, filtration aperture, and separation speed, to ensure the best operating state is always maintained under different operating conditions.

[0140] The present invention covers any alternatives, modifications, equivalent methods, and solutions made to the essence and scope of the present invention. For the public to have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, and those skilled in the art can fully understand the present invention without the description of these details. Additionally, well-known methods, processes, procedures, components, and circuits, etc., are not described in detail to avoid unnecessary confusion to the essence of the present invention.

[0141] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. Multi-stage circulation treatment system for drilling slurry, characterized by: It includes automatic classification module, dynamic monitoring module, mud purification module, separation optimization module, waste residue classification and recovery module and intelligent control module; among which: Automatic classification module: including particle recognition unit and variable frequency classification unit; The particle identification unit detects the size, shape and density of particles in the drill cuttings and mud in real time through a multi-spectral sensor, and identifies the particle size and particle density; The variable frequency classification unit is used to adjust the classification speed according to the detection data provided by the particle recognition unit to dynamically classify the particles; Dynamic monitoring module: including online sensors and data analysis units; The online sensor is installed between the automatic classification module and the separation optimization module to monitor the flow rate, concentration and pressure of the classified particles in real time; The data analysis unit analyzes the particle distribution data and the mud state based on the monitoring data of the online sensor to identify the mud state data; Mud purification module: including multi-stage filtration unit and trace chemical treatment unit; The multi-stage filtration unit is used to filter particles in sequence through filter screens with different pore sizes; The trace chemical processing unit is used to automatically adjust the amount of chemical reagents according to the mud status data of the dynamic monitoring module; Separation optimization module: including centrifugal separation unit and automatic screen adjustment unit; The centrifugal separation unit is used to automatically adjust the centrifugal speed based on the particle flow rate and concentration data provided by the dynamic monitoring module to separate particles of different particle sizes in the mud; The automatic screen adjustment unit is used to adjust the pore size of the filter according to the feedback data of the dynamic monitoring module to ensure the maximum separation efficiency; Waste residue classification and recycling module: including waste residue classification unit and resource utilization unit; The waste residue classification unit automatically classifies the waste residue based on the separation particle data provided by the separation optimization module; Resource utilization unit, used to physically or chemically treat the classified waste residues; Intelligent control module: including data acquisition unit, analysis and decision-making unit and execution control unit; The data acquisition unit is used to collect the operation data of the automatic classification module, the dynamic monitoring module, the mud purification module, the separation optimization module and the waste residue classification and recovery module in real time; The analysis and decision-making unit formulates optimization strategies for system operation based on the collected data, combined with historical operating parameters and real-time monitoring data; The execution control unit is used to automatically adjust the operating parameters of each module according to the optimization strategy output by the analysis and decision-making unit.

2. The multi-stage circulation treatment system for drilling slurry according to claim 1 is characterized in that: The variable frequency classification unit comprises: Speed ​​control subunit: Through the electric speed control device, the speed of the grading equipment is adjusted in real time according to the preset grading standards of particle size and density to ensure that the grading process adapts to the dynamic changes of different particles; Frequency adjustment subunit: adjusts the vibration frequency of the grading device through the control circuit to achieve switching between high frequency and low frequency to adapt to different particle sizes and densities; Particle guide subunit: used to adjust the movement path of particles according to the changes in rotation speed and vibration frequency during the classification process, ensuring that each type of particle enters the corresponding classification area according to the set trajectory.

3. The multi-stage circulation treatment system for drilling sludge according to claim 1 is characterized in that: The data analysis unit comprises: Particle distribution calculation subunit: by receiving the particle size and concentration provided by the particle recognition unit and the dynamic monitoring module, using the formula Among them, P d is the proportion of particles with a particle size of d to the total particles, n d is the number of particles with a particle size of d, N t is the total number of particles, and the particle size distribution curve is calculated; Mud viscosity monitoring subunit: Based on the particle flow rate and pressure measured by the online sensor, the formula Among them, η represents the viscosity of the mud, τ represents the shear stress, Indicates the shear rate and calculates the real-time viscosity value of the mud; Mud component identification subunit: Based on the spectral data provided by the multispectral sensor, the proportion of each component in the mud is identified by comparing it with the mud component database.

4. The multi-stage circulation treatment system for drilling slurry according to claim 1 is characterized in that: The multi-stage filtration unit comprises: Coarse filter unit: used for primary particle filtration, including multiple layers of filter screens with large pore sizes ranging from 0.5 mm to 2 mm; Fine filter unit: used to filter smaller particles, the filter mesh pore size range is 0.01 mm to 0.5 mm; Automatic adjustment subunit: used to automatically adjust the aperture selection and filtering sequence of the filter screens in the coarse filter subunit and the fine filter subunit according to the particle concentration and size data provided by the dynamic monitoring module.

5. The multi-stage circulation treatment system for drilling slurry according to claim 1 is characterized in that: The trace chemical processing unit comprises: Chemical reagent delivery subunit: automatically controls the delivery amount of chemical reagents by receiving real-time data of pollutant concentration and mud flow in the mud provided by the dynamic monitoring module; Concentration adjustment subunit: automatically adjusts the concentration of chemical reagents based on mud status data, including pH value or pollutant content in the mud; Feedback control subunit: According to the feedback data of the treatment effect after the chemical reagent is added, the subsequent addition amount is adjusted, and by monitoring the residual pollutants and mud properties after mud treatment, the subsequent chemical reagent addition strategy is optimized to prevent over- or under-dosage.

6. The multi-stage circulation treatment system for drilling slurry according to claim 1 is characterized in that: The centrifugal separation unit comprises: Speed ​​control subunit: used to adjust the speed of the centrifugal separation unit according to the particle flow rate and particle concentration data provided by the dynamic monitoring module to ensure that the speed dynamically matches the flow rate and concentration of particles in the mud; Flow rate regulating subunit: used to control the flow rate of mud entering the centrifugal separation unit according to the particle flow rate data, so that the flow rate can adapt to the speed adjustment of centrifugal separation; Particle size detection feedback subunit: Based on the particle size data provided by the dynamic monitoring module, the effect of centrifugal separation is judged through real-time detection of the particle size after separation. If it is detected that the separation effect is not good, the speed setting of the speed control subunit is readjusted.

7. The multi-stage circulation treatment system for drilling slurry according to claim 1 is characterized in that: The automatic screen adjustment unit comprises: Aperture selection subunit: by receiving the particle size and flow rate data provided by the dynamic monitoring module, the aperture size of the screen is adjusted to achieve effective separation of particles of different sizes; Filtration accuracy adjustment subunit: It is used to dynamically adjust the aperture of the screen according to the particle concentration and particle distribution data in the mud provided by the dynamic monitoring module to ensure that the filtration accuracy is improved when the particle concentration is high.

8. A multi-stage circulation method for treating drilling mud, which is implemented by the multi-stage circulation system for treating drilling mud according to any one of claims 1 to 7, characterized in that: The following steps are involved: S1: Preliminary classification of particles in drilling mud, by detecting the size and density of particles, adjusting the classification speed in real time, and dynamically classifying them according to the characteristics of different particles; S2: Real-time monitoring of the mud state after classification, obtaining data on particle velocity, concentration, and viscosity, and analyzing and identifying mud state information; S3: Perform multi-stage filtration on the classified mud, and dynamically adjust the pore size and filtration order during the filtration process according to the changes in particle concentration and size; S4: According to the flow rate and concentration of particles, the separation speed in the mud is adjusted, and particles of different sizes are efficiently separated by adjusting the speed. At the same time, the filter aperture is dynamically adjusted according to the feedback data to optimize the separation effect; S5: Automatically classify the separated waste residues, calculate the mass and shape parameters of the particles, and determine whether they are recyclable; S6: Based on real-time monitoring data and historical operating parameters, formulate system optimization strategies and automatically adjust the operating parameters of each step, including classification speed, filtration pore size and separation speed, to ensure that the best operating state is always maintained under different operating conditions.

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