Intelligent dynamic fracturing sand supply system and method

Abstract

The invention relates to the technical field of intelligent sand supply, in particular to an intelligent dynamic fracturing sand supply system and method, and the system comprises a liquid supply data acquisition module, a pumping pressure boundary identification module, a target sand ratio correction module, a supply and demand speed difference adjustment module and a control parameter feedback module. According to the method, fluctuation nodes can be identified and key changes can be captured by acquiring the pressure and time information of the fracturing process and constructing the index sequence, so that flow abnormality is prevented from being neglected, pressure differences are compared, trigger signals are generated, sand ratio parameters are dynamically corrected along with real-time pressure, supply and demand deviation caused by sand ratio imbalance is avoided, and the accuracy of the fracturing process is improved. The target sand supply rate is compared with the actual speed of the auger, the running state is corrected in time, over-supply or lag caused by speed difference accumulation is reduced, sand supply execution and the target rate are correspondingly arranged in the time dimension, a closed-loop feedback relation is formed, the sand supply process has the self-adaptive adjustment capacity, stability and accuracy are improved, and the sand supply efficiency is improved. And quick response to sudden working conditions is enhanced, and the risk of manual intervention is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent sand supply, in particular to an intelligent dynamic fracturing sand supply system and method. BACKGROUND

[0002] The technical field of intelligent sand supply relates to a proppant delivery system for fracturing operations in the development process of oil and gas fields, covering the continuous supply of proppants, flow regulation during sand supply, switching and distribution of different types of proppants, and coordinated control with sand mixing systems, etc. The overall technical field mainly realizes the stability and accuracy control of the sand supply process in fracturing construction by setting the sand supply path, adjusting the sand supply rate and controlling the type of proppant. Among them, the traditional intelligent dynamic fracturing sand supply system refers to the equipment system used to provide proppants in the fracturing process of unconventional energy such as shale gas. The technical matters it aims at are the problems existing in high-intensity fracturing operations, such as sand supply flow relying on manual adjustment, response lag, large flow fluctuation, low proppant switching efficiency, and poor linkage between sand supply and sand mixing. The sand supply control is usually carried out by setting a fixed sand supply program, manually adjusting the sand valve, or controlling the operation mode of a single device based on static preset parameters.

[0003] The traditional technology generally relies on fixed programs and manual adjustment in actual operation, and the sand supply rate is difficult to match the real-time working condition, resulting in that the flow fluctuation cannot be captured in time at the key time, thereby showing the problem of slow response under high-intensity fracturing. Since the pressure change can only be judged by manual monitoring, the extreme deviation is difficult to identify quickly, often causing the sand ratio to deviate from the preset range, so that the sand-carrying capacity of the fracturing fluid is insufficient or overloaded, directly affecting the fracture conductivity effect. The sand supply speed relies on manual valve adjustment, and cannot form a continuous closed-loop matching with the target speed, so the speed difference accumulates to cause sand supply shortage or oversupply, which further amplifies the pump pressure fluctuation and affects the fracturing stability. At the same time, there is a lack of fine linkage between sand supply and sand mixing, the parameter adjustment is disconnected with the device operation, forming a lag chain, which is easy to cause sand plugging, pump impact or construction efficiency decline. For example, in shale gas fracturing operations, too low sand ratio will reduce the fracture support capacity, and too high sand ratio will easily plug the pipeline, causing construction interruption. These deficiencies seriously restrict the stability and economy of the construction process. SUMMARY

[0004] In order to solve the technical problems existing in the prior art, the embodiments of the present application provide an intelligent dynamic fracturing sand supply system and method. The technical solution is as follows: On the one hand, an intelligent dynamic fracturing sand supply system is provided, which comprises: The liquid supply data acquisition module acquires the continuous liquid supply pressure and corresponding time information of the fracturing pipeline pressure monitoring, constructs a time index sequence, extracts and identifies the pressure fluctuation changes in the time period, marks the fluctuation time nodes, and generates a liquid supply fluctuation time node group; The pump pressure boundary identification module extracts pressure change values in time windows before and after each node based on the liquid supply fluctuation time node group, identifies pressure extreme value differences, compares limit difference indicators in the fracturing process, screens nodes exceeding the limit value and records characteristic attributes, and generates a boundary trigger signal group; The target sand ratio correction module obtains sand ratio setting parameters and sand mixing device liquid supply pump displacement parameters in the current target sand ratio setting according to the boundary trigger signal group, adjusts the sand ratio setting value in combination with the pressure fluctuation state, records adjustment time and setting value change trend, and generates a sand ratio dynamic adjustment trajectory set; The supply-demand speed difference adjustment module extracts target sand supply rate and actual sand supply speed of the screw auger transmission at corresponding moments based on the sand ratio dynamic adjustment trajectory set, compares the differences, corrects the auger speed according to the difference direction, records adjustment parameters and speed change process, and generates an auger speed difference matching sequence.

[0005] As a further scheme of the application, the liquid supply fluctuation time node group includes a fluctuation starting point, a fluctuation ending point and a fluctuation peak point, the boundary trigger signal group includes a pressure extreme value difference, an over-limit identifier and a characteristic attribute, the sand ratio dynamic adjustment trajectory set includes adjustment time, a setting value change amplitude and a change trend, and the auger speed difference matching sequence includes a target sand supply rate, an actual sand supply speed and a speed correction parameter.

[0006] As a further scheme of the application, the liquid supply data acquisition module includes: A time sequence sub-module acquires continuous liquid supply pressure and corresponding time information of liquid supply pressure monitoring, arranges time and pressure values point by point, establishes an index according to time sequence, and generates a time index sequence value; A fluctuation section sub-module calls liquid supply pressure values in a time period based on the time index sequence value, calculates adjacent time period pressure difference values, compares the pressure difference values with a pressure fluctuation threshold value, screens sections exceeding the threshold value, and generates a pressure fluctuation interval group; A node identification sub-module calls starting and ending time points of sections according to the pressure fluctuation interval group, calculates adjacent section time difference values, merges sections with time difference values less than an interval threshold value, obtains a merged fluctuation starting and ending time point set, and generates a liquid supply fluctuation time node group.

[0007] As a further scheme of the application, the pump pressure boundary identification module includes: A window extraction sub-module calls liquid supply pressure values in time ranges before and after nodes based on the liquid supply fluctuation time node group, collects pressure data in corresponding time periods, constructs a pressure change sequence in time sequence, and generates a node pressure change value group; The extreme difference identification submodule identifies the maximum value and the minimum value difference in the sequence according to the node pressure change value group, judges the difference value according to the fracturing process limit difference index, extracts the data items meeting the conditions, and generates a limit value deviation amplitude group; The feature screening submodule calls the corresponding node information in the limit value deviation amplitude group, screens the target node according to the pressure change amplitude, time position and limit difference exceeding situation, extracts the node corresponding feature information, and generates a boundary trigger signal group.

[0008] As a further scheme of the present application, the target sand ratio correction module comprises: The parameter extraction submodule calls the target sand ratio setting parameter and the sand mixing device liquid supply pump displacement parameter based on the boundary trigger signal group, extracts the setting value information and the displacement information in the corresponding time period in combination with the pressure fluctuation state, establishes the corresponding relationship between the two types of parameters, and generates a sand ratio control correlation value group; The setting adjustment submodule judges the matching situation between the setting parameter and the displacement parameter under the current pressure fluctuation state according to the sand ratio control correlation value group, adjusts the target setting parameter according to the setting value change trend, obtains the setting value change amplitude under the difference node, and obtains a sand ratio correction change amount group; The trajectory generation submodule calls the setting value change amplitude and the corresponding adjustment time in the sand ratio correction change amount group, arranges the change path of the setting parameter in time sequence, constructs a continuously changing parameter sequence, and generates a sand ratio dynamic adjustment trajectory set.

[0009] As a further scheme of the present application, the supply-demand speed difference adjustment module comprises: The rate extraction submodule extracts the target sand supply rate information of the time period based on the sand ratio dynamic adjustment trajectory set, obtains the actual sand supply speed record of the spiral auger transmission, performs time corresponding processing on the target rate and the actual speed, screens the matching sample data, and generates a supply-demand rate comparison value group; The speed difference determination submodule identifies the offset direction between the target rate and the actual speed according to the supply-demand rate comparison value group, judges the speed difference change trend, divides the rate offset path of the continuous time period into sections, obtains the speed difference direction information of the sections, and obtains an auger speed difference adjustment direction group; The speed correction submodule calls the speed difference direction information in the auger speed difference adjustment direction group, combines the original speed record of the spiral auger transmission, adjusts the sand supply speed parameter according to the supply-demand offset situation, records the adjustment time and the speed change situation, and generates an auger speed difference matching sequence.

[0010] As a further scheme of the present application, the method further comprises: The control parameter feedback module extracts the sand supply rate values before and after the adjustment stage according to the auger speed difference matching sequence, and performs corresponding comparison with the target rate, and performs serialization arrangement in the time dimension to form the response relationship between the sand supply control execution and the target setting, and generates a dynamic sand supply response offset rate sequence; The dynamic sand supply response offset rate sequence includes an execution rate, a target rate, and a response offset rate. The sand supply control execution refers to the actual sand supply process realized by adjusting the auger driving device. The dynamic sand supply response offset rate sequence is a sequence formed by the offset rate between the sand supply rate and the target rate changing over time.

[0011] As a further scheme of the present application, the control parameter feedback module comprises: The rate extraction submodule extracts the actual sand supply rate records corresponding to the start and end time of the adjustment stage based on the auger speed difference matching sequence, obtains the target sand supply rate value at the time node, arranges the target rate and the actual rate in time sequence, and selects complete paired data to generate a sand supply rate pairing sequence. The target comparison submodule extracts the start and end rate values according to the adjustment stage division rule according to the combination of the time period target rate and the actual rate in the sand supply rate pairing sequence, calculates the supply-demand offset direction of the stage, arranges the distribution of the offset direction in the time sequence, and obtains the time period rate offset trend. The response generation submodule calls the time period offset direction in the time period rate offset trend, combines the sand supply control execution parameter and the target sand supply rate setting value, and performs serialization processing according to the time position to calculate the change of the response offset on the time axis, and generates a dynamic sand supply response offset rate sequence.

[0012] As a further scheme of the present application, the time index sequence is a sequence data structure composed of collected pressure data and time stamps. The segment extraction and feature recognition are based on a preset statistical or signal processing algorithm (sliding window, fluctuation threshold detection) to recognize the features of pressure changes. The liquid supply fluctuation time node group is a set of time points corresponding to when the pressure fluctuation exceeds the preset threshold. The limit difference index refers to the pressure fluctuation range preset according to the construction design or monitoring data in the fracturing construction process, which is used to determine whether the pump pressure is out of limit. The boundary trigger signal group refers to a set of trigger signals generated when the limit difference is exceeded. The sand ratio setting parameter refers to the ratio of solid proppant to sand-carrying liquid set according to the process design or field adjustment in the fracturing construction process, which is used to guide the sand mixing device to maintain the target sand ratio when supplying liquid. The sand ratio dynamic adjustment track set is a set of change curves formed by the adjustment of the sand ratio set value over time. The sand ratio set value refers to the ratio parameter of the solid proppant and the liquid carrying fluid that is set in advance during the fracturing operation, including the operation design scheme, the field input, or the dynamic adjustment based on the pressure fluctuation of the control system. The screw auger transmission is a mechanical transmission device for the screw conveyor (auger) in the sand supply system. The auger speed difference matching sequence is a matching data sequence of the adjusted auger speed and the target speed.

[0013] In another aspect, an intelligent dynamic fracturing sand supply method is executed based on the above-mentioned intelligent dynamic fracturing sand supply system, including the following steps: The liquid supply data acquisition module records the liquid supply pressure value and the corresponding time information, constructs a time index sequence, calculates the pressure fluctuation value in the time period, and judges whether it exceeds the set threshold value, extracts the time node of the fluctuation appearance, and generates a liquid supply fluctuation time node group; Based on the nodes in the liquid supply fluctuation time node group, the pressure change data in the front and rear time windows is extracted, the pressure range and the change rate of the corresponding section are calculated, and the limit difference index set in the fracturing process is compared, the over-limit nodes are screened and the characteristic information is recorded, and a boundary trigger signal group is generated; According to the nodes in the boundary trigger signal group, the target sand ratio set value and the sand mixing device liquid supply pump displacement parameter at the corresponding time are obtained, the correlation characteristics between the sand ratio change trend and the pressure fluctuation state are calculated, and it is judged whether the set parameter needs to be adjusted according to the fluctuation direction, the change track of the set value is recorded in combination with the adjustment time point, and a sand ratio dynamic adjustment track set is generated; Based on the adjustment time nodes recorded in the sand ratio dynamic adjustment track set, the target sand supply rate and the actual sand supply speed data are extracted, the supply-demand speed difference value is calculated and the deviation direction is judged, the sand supply speed of the screw auger transmission system is corrected according to the deviation direction, and an auger speed difference matching sequence is generated; According to the corrected sand supply speed record in the auger speed difference matching sequence, the sand supply rate before and after the adjustment is extracted, and the target set rate is compared, the response deviation degree in the difference period is calculated, and a dynamic sand supply response deviation rate sequence is generated.

[0014] Compared with the prior art, the advantages and positive effects of the present application are: In the present application, by acquiring the pressure and time information of the fracturing process and constructing the index sequence, the fluctuation nodes can be identified and the key changes can be captured, so as to avoid the flow anomaly being ignored, compare the pressure difference and generate a trigger signal, dynamically correct the sand ratio parameter with real-time pressure, avoid the imbalance of sand ratio causing the supply-demand deviation, compare the target sand supply rate with the actual speed of the auger, timely correct the running state, reduce the oversupply or lag caused by the speed difference accumulation, correspond and arrange the sand supply execution and the target rate in the time dimension, form a closed-loop feedback relationship, so that the sand supply process has self-adaptive adjustment capability, improves the stability and accuracy, and enhances the rapid response to sudden working conditions, reduces the risk of manual intervention. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0016] Figure 1 The system flowchart of the present application; Figure 2 The system block diagram of the present application; Figure 3 The flowchart of the liquid supply data acquisition module of the present application; Figure 4 The flowchart of the pump pressure boundary identification module of the present application; Figure 5 The flowchart of the target sand ratio correction module of the present application; Figure 6 The flowchart of the supply-demand speed difference adjustment module of the present application; Figure 7 The flowchart of the control parameter feedback module of the present application; Figure 8 The method step flowchart of the present application. DETAILED DESCRIPTION

[0017] The technical solutions in the present application will be described below in combination with the drawings.

[0018] In the embodiments of the present application, the words such as "example", "for example" are used to represent as an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0019] In the embodiments of the present application, "image" and "picture" can be used interchangeably, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized.

[0020] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and the meanings expressed are consistent when the distinction is not emphasized.

[0021] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail in combination with the drawings and specific embodiments.

[0022] The embodiments of the present application provide an intelligent dynamic fracturing sand supply system, as shown in Figures 1-2 The intelligent dynamic fracturing sand supply system schematic diagram, the system comprises: The liquid supply data acquisition module acquires the continuous liquid supply pressure and corresponding time information of the fracturing pipeline pressure monitoring, constructs a time index sequence, extracts and identifies the pressure fluctuation changes in the time period, marks the time nodes with fluctuation, and generates a liquid supply fluctuation time node group; The time index sequence is a sequence data structure composed of collected pressure data and time stamps; The section extraction and feature identification is based on a preset statistical or signal processing algorithm (sliding window, fluctuation threshold detection) to identify the characteristics of pressure changes; The liquid supply fluctuation time node group is a set of time points corresponding to when the pressure fluctuation exceeds the preset threshold; The pump pressure boundary identification module extracts the pressure change value in the time window before and after each node based on the liquid supply fluctuation time node group, identifies the pressure extreme difference, compares the limit difference index in the fracturing process, filters the nodes exceeding the limit value and records the feature attributes, and generates a boundary trigger signal group; The limit difference index refers to the pressure fluctuation range preset according to the construction design or monitoring data in the fracturing construction process, which is used to determine whether the pump pressure is out of limit; The boundary trigger signal group refers to the set of trigger signals generated when the limit difference is exceeded; The sand ratio setting parameter refers to the ratio of solid proppant and sand-carrying liquid set according to the process design or on-site adjustment in the fracturing construction process, which is used to guide the liquid supply of the sand mixing device to maintain the target sand ratio; The target sand ratio correction module obtains sand ratio setting parameters in the current target sand ratio setting and displacement parameters of the sand mixing device liquid supply pump according to the boundary trigger signal group, adjusts the sand ratio setting value in combination with the pressure fluctuation state, records the corresponding adjustment time and setting value change trend, and generates a sand ratio dynamic adjustment trajectory set; The sand ratio dynamic adjustment trajectory set is a change curve set formed by the sand ratio setting value adjusting over time; The sand ratio setting value refers to the pre-set ratio parameter of the solid proppant and the liquid carrying fluid in the fracturing construction process, including the construction design scheme, the dynamic adjustment based on the pressure fluctuation by the field input or the control system; The supply-demand speed difference adjustment module extracts the target sand supply rate and the actual sand supply speed of the screw auger transmission at the corresponding time based on the sand ratio dynamic adjustment trajectory set, compares the difference between the two, corrects the auger speed according to the difference direction, records the adjustment parameters and the speed change process, and generates an auger speed difference matching sequence; The screw auger transmission is a mechanical transmission device of a screw conveyor (auger) in the sand supply system; The auger speed difference matching sequence is a matching data sequence of the adjusted auger speed and the target speed; The control parameter feedback module extracts the sand supply rate values before and after the adjustment stage, compares them with the target rate, and serializes the arrangement in the time dimension to form the response relationship between the sand supply control execution and the target setting, and generates a dynamic sand supply response offset rate sequence; The sand supply control execution refers to the actual sand supply process realized by adjusting the auger driving device; The dynamic sand supply response offset rate sequence is a sequence formed by the offset rate between the sand supply rate and the target rate changing over time; The liquid supply fluctuation time node group includes the fluctuation starting point, the fluctuation end point and the fluctuation peak point, the boundary trigger signal group includes the pressure extreme difference, the overrun identifier and the characteristic attribute, the sand ratio dynamic adjustment trajectory set includes the adjustment time, the setting value change amplitude and the change trend, the auger speed difference matching sequence includes the target sand supply rate, the actual sand supply speed and the speed correction parameter, and the dynamic sand supply response offset rate sequence includes the execution rate, the target rate and the response offset rate.

[0023] Specifically, as shown in Figure 2 , 3 The liquid supply data acquisition module includes: The time sequence submodule obtains the continuous liquid supply pressure and the corresponding time information of the liquid supply pressure monitoring, arranges the time and the pressure value point by point, establishes an index according to the time sequence, and generates a time index sequence value; The time series submodule continuously collects the supply pressure and its corresponding time information through the pressure sensor and the control device at a frequency of 5 times per second, forming a one-to-one time and pressure data pair. Starting from the first sampling time, the pressure value is recorded every 0.2 seconds, for example, starting from 14:00:00 to collect 1 hour, 18000 sets of time and pressure pairs will be generated, each pair of data contains a time point and its corresponding pressure value, such as 14:00:00 corresponding to 5.2MPa, 14:00:00.2 corresponding to 5.4MPa, 14:00:00.4 corresponding to 5.1MPa, and so on to 15:00:00 corresponding to 5.3MPa, all time points are arranged in time sequence to form a complete time series, the sequence strictly increases, there is no repeated or skipped time point, at the same time, the pressure value data corresponds to the time one by one, providing accurate data index structure for subsequent extraction of pressure at a certain time or statistics of pressure change, any abnormal value in the collection process will be excluded in the recording stage through the abnormal identification rule, ensuring the data sequence is complete and reliable, forming a standard time index sequence that can be directly referenced, used for subsequent difference operation, window analysis and fluctuation identification.

[0024] The fluctuation section submodule calls the supply pressure value within the time period based on the time index sequence value, calculates the pressure difference value of adjacent time periods, compares the pressure difference value with the pressure fluctuation threshold value, filters the sections exceeding the threshold value, and generates a pressure fluctuation interval group; The fluctuation section submodule extracts a fixed time length pressure data window from the complete time index sequence for segment-by-segment analysis, usually the window length is set to 10 seconds, each window contains 50 consecutive pressure values, from the 1st second to the 10th second is the first section, the 2nd second to the 11th second is the second section, and so on. The difference between the adjacent two pressure values in each section is calculated in turn, and the difference is taken as the absolute value. For example, the pressure values between the 3rd second and the 3.2nd second in a section are 5.1 MPa and 5.45 MPa respectively, and the difference is 0.35 MPa. If the set fluctuation threshold is 0.3 MPa, the difference is marked as an overrun value, and the section is recorded as the fluctuation starting point. From the 3rd second to the overrun stopping point, a fluctuation section is formed. When multiple consecutive adjacent differences exceed the threshold value, the system combines them into a complete fluctuation section. For example, if 5 consecutive differences exceed 0.3 MPa, they are combined into a 10-second fluctuation section. The fluctuation interval is generated from the first overrun time point to the last overrun point. This method is repeatedly executed in the entire collection period. For example, 1 hour of data can generate 17 fluctuation sections. The start and end time of each fluctuation section is recorded as an independent interval. For example, a section is from 14:03:20 to 14:03:22, indicating that the liquid supply pressure in this interval has changed significantly. The fluctuation threshold is usually set with reference to the standard deviation of the overall pressure sequence. For example, if the overall standard deviation is 0.18 MPa, then 1.5 times of it, i.e. 0.27 MPa, can be selected as the preliminary fluctuation reference value, and the actual execution threshold is rounded up to 0.3 MPa.

[0025] The node identification submodule calls the start and end time points of the sections according to the pressure fluctuation interval group, calculates the time difference value of adjacent sections, and merges the sections with a time difference value less than the interval threshold to obtain the merged fluctuation start and end time point set, and generates the liquid supply fluctuation time node group. The node identification submodule extracts the start and end time of each section in succession on the basis of the existing multiple pressure fluctuation intervals, constructs an initial section set, and calculates the interval between the start time of the current section and the end time of the previous section from the second section. For example, the start time of the third section is 14:10:30, and the end time of the previous section is 14:10:25. The interval between the two is 5 seconds. If the merging judgment threshold is set to 10 seconds, the time difference is less than the threshold, and the system automatically merges the previous and subsequent two sections into one fluctuation section. The judgment and merging process are continuously performed on all adjacent sections. For example, the intervals between the subsequent sections are 7 seconds, 12 seconds, and 9 seconds, respectively. It is judged whether the merging condition of less than 10 seconds is met. For the sections that meet the condition, they are merged into the previous section. For the sections that do not meet the condition, they are regarded as new sections. Finally, a new fluctuation section set is generated. The start point and end point of each section are the fluctuation nodes. The start and end node set obtained through the merging operation is used to describe the actual liquid supply fluctuation occurrence time point. The merging threshold can be set according to the sampling frequency and the actual fluctuation duration. For example, if the sampling frequency is 5 times per second, 50 points can be obtained in 10 seconds. In order to adapt to the continuity and segmentation, the merging time difference threshold is generally set to 5 to 15 seconds, and the recommended value is 10 seconds. The difference is obtained by subtracting the time. The unit is converted to seconds for judgment. During the processing, data analysis tools can be used to batch execute the above calculation and comparison logic, thereby generating a high-quality fluctuation node sequence. For example, the finally identified nodes are 14:10:20, 14:10:32, 14:18:40, and 14:18:55, which comprehensively cover all significant fluctuation event start and end time points.

[0026] Specifically, as shown in Figure 2 , 4 The pump pressure boundary identification module includes: The window extraction submodule calls the liquid supply pressure value in the time range before and after the node based on the liquid supply fluctuation time node group, collects the pressure data in the corresponding time period, constructs a pressure change sequence in chronological order, and generates a node pressure change value group. The window extraction submodule reads the pressure data in the set time range before and after each node based on the liquid supply fluctuation time node group, and the pressure sampling frequency is set to 5 times per second. For each node, the pressure records of the previous 10 seconds and the following 15 seconds are extracted to form a continuous time period covering 25 seconds, which contains a total of 125 pressure data points. All data are arranged in chronological order to form a complete pressure change sequence. For example, if the time of a certain node is 14:15:00, the extracted data range is from 14:14:50 to 14:15:15. Each data contains a timestamp and a corresponding pressure value, such as 5.3 MPa at 14:14:50, 5.2 MPa at 14:14:50.2, and 5.6 MPa at 14:15:15. The extraction and sorting process is repeated for each node to form multiple node corresponding pressure change sequences, and finally a set of pressure change data associated with each node is constructed as the node pressure change value group.

[0027] The range recognition submodule identifies the maximum and minimum value difference in the sequence based on the node pressure change value group, judges the difference value according to the fracturing process limit difference index, extracts the data items that meet the conditions, and generates the limit value deviation amplitude group. The range recognition submodule identifies the maximum and minimum pressure value difference in each group of data based on the node pressure change value group. In the pressure change sequence of each node, the maximum pressure and the minimum pressure are found, and the difference between them is the pressure fluctuation amplitude of the node. For example, if the maximum pressure in a certain node data is 5.6 MPa and the minimum pressure is 5.1 MPa, the difference is 0.5 MPa, which is the pressure range of the node. After the same process is performed for each node, a set consisting of multiple ranges is formed. Then each range value is compared with the set fracturing limit difference value. If the range of a certain node is higher than the limit difference standard, it is considered that the pressure fluctuation of the node exceeds the control range and it is included in the abnormal node category. For example, if the limit difference value is set to 0.4 MPa and the range of a certain node is 0.5 MPa, it meets the over-limit condition. The limit difference standard is set according to historical fracturing pressure fluctuation data. For example, if 90% of the node pressure ranges are less than or equal to 0.4 MPa, 0.4 MPa can be selected as the threshold value. All nodes that meet this condition are extracted and merged into the limit value deviation amplitude group.

[0028] The feature screening submodule calls the corresponding node information in the limit value deviation amplitude group, screens the target node according to the pressure change amplitude, time position and limit difference exceeding situation, extracts the node corresponding feature information, and generates the boundary trigger signal group. The feature screening submodule carries out screening operation based on the identified node information in the limit deviation amplitude group. In the first step, whether each node belongs to the high amplitude fluctuation type is judged according to the pressure change amplitude, and the threshold value is set to 0.45 MPa. Any node whose range reaches or exceeds the value is marked as a high amplitude node. In the second step, the time position of the node is evaluated, and the offset seconds of the node occurrence time relative to the fracturing start time are calculated. For example, if the fracturing start time is 13:30:00, and the time of a certain node is 14:00:00, then the relative time position of the node is 1800 seconds. According to the time stage division standard, the fracturing process is divided into early stage (0-600 seconds), middle stage (600-1800 seconds), and late stage (1800 seconds later). The node belongs to the late stage. In the third step, it is detected whether the node is in a continuous overrun state, i.e., whether the range values of the adjacent nodes before and after the node are also higher than the limit difference value. If the current node range is 0.48 MPa, and the ranges before and after it are 0.46 MPa and 0.50 MPa respectively, all of which are greater than the set 0.4 MPa, then it is marked as a continuous abnormal fluctuation node. The node that meets all the screening conditions is extracted as the target node, and its number, pressure range, relative time position and other characteristic information are integrated to form a boundary trigger signal group, which is used to represent the key pressure change nodes in the fracturing process. The high amplitude threshold is set to 90 percent of the historical range, and the key time stage is determined by the process division. The continuity is judged by comparing the adjacent data values. The whole process does not depend on formula expression, but realizes automatic recognition and screening through pressure value comparison and logical judgment.

[0029] Specifically, as shown in Figure 2 、 5 The target sand ratio correction module includes: The parameter extraction submodule calls the target sand ratio setting parameters and the displacement parameters of the sand mixing device liquid supply pump based on the boundary trigger signal group, extracts the setting value information and displacement information in the corresponding time period combined with the pressure fluctuation state, establishes the corresponding relationship between the two types of parameters, and generates a sand ratio control correlation value group. The parameter extraction submodule obtains node time information item by item based on the boundary trigger signal group, calls the target sand ratio setting parameter and the displacement parameter of the sand mixing device liquid supply pump correspondingly, the setting parameter and the displacement data are both from the field sand mixing control system and the pump group flow acquisition module, the sampling frequency is 1 time per second as an example, the node time is extended forward by 5 seconds and backward by 5 seconds, an extraction time period of 11 seconds is constructed, all sand ratio setting values and pump displacement data in the period are read in turn during the period, the sampling results of each second are recorded, the average values of the sand ratio setting values and the pump displacement in the period are calculated respectively, for example, the node time is 13:45:00, the value range is 13:44:55 to 13:45:05, assuming that the sand ratio setting data are 0.07, 0.07, 0.08, 0.08, 0.08, 0.08, 0.09, 0.09, 0.09, 0.08, 0.08 in turn, the average value is 0.082 after calculation, the pump displacement data are 5.1, 5.2, 5.3, 5.3, 5.4, 5.3, 5.2, 5.2, 5.1, 5.0, 4.9 L / s, the average value is 5.18 L / s, the two are combined according to the node time to form a group of parameter correlation values, the process is repeated at all boundary trigger nodes to generate multiple pairing records of sand ratio setting and displacement parameters, combined with the pressure fluctuation state classification mark at the node, finally a sand ratio control correlation value group is formed, which is used for subsequent analysis and control logic execution.

[0030] The setting adjustment submodule judges the matching between the setting parameter and the displacement parameter under the current pressure fluctuation state according to the sand ratio control correlation value group, adjusts the target setting parameter according to the setting value change trend, obtains the setting value change amplitude at the difference node, and obtains a sand ratio correction change amount group. The setting adjustment sub-module performs parameter matching and setting correction operation on the basis of the sand ratio control associated value group. First, the set sand ratio value and pump displacement value of each pair are judged, and the ratio of sand ratio and displacement in the historical stable period data is taken as the judgment basis. For example, the majority of the node ratio in the statistical history is about 0.0158, which can be set as the reference ratio, and the error range is set to ±10%, that is, the ratio is between 0.0142 and 0.0174, which is a reasonable interval. When the ratio of the current node set sand ratio divided by the displacement exceeds the interval, it is considered that the node has a setting deviation, and the error size needs to be recorded and judged whether it needs to be corrected. Further, the trend change of the set value between adjacent nodes is judged. If the set value continuously decreases or increases by more than two nodes, it is considered that the trend is abnormal. For example, the set value of the node sequence is 0.09, 0.08, 0.07, which is a clear downward trend. At this time, the correction strategy is determined in combination with the error direction. If the error is negative and there is a downward trend, upward correction is performed. The correction value is obtained by multiplying the error size by the adjustment coefficient. The adjustment coefficient can be set to 0.7. For example, if the error is 0.002, the correction value is 0.0014. Finally, the current set value is adjusted to 0.0714. All nodes that have undergone setting correction are executed according to the same logic, and the correction amplitude of each node is recorded. The result forms a sand ratio correction change amount group, which is used by the subsequent dynamic trajectory construction module.

[0031] The trajectory generation sub-module calls the set value change amplitude and the corresponding adjustment time in the sand ratio correction change amount group, arranges the change path of the set parameter in time sequence, constructs a continuously changing parameter sequence, and generates a sand ratio dynamic adjustment trajectory set. The trajectory generation sub-module arranges the set parameter change path item by item based on the set value change amplitude and time information of each node in the sand ratio correction change amount group. In the operation process, the node time corresponding to each change amount is first extracted to ensure that all correction points have clear time sequence positioning. Then, all change amplitudes are sequentially superimposed on the original set value according to the time sequence to form a continuous sand ratio set sequence. The starting value is the set value at the previous time of the node. For example, the starting set is 0.07, the first change amount is +0.0014, then the updated value is 0.0714, the second change amount is +0.002, then the updated value is 0.0734, the third change amount is -0.0005, then the set value is 0.0729, and so on. All values are increased or decreased based on the previous time. The trajectory nodes are connected at intervals of 1 second to construct a complete and continuous set change path, ensuring that there is no jump or breakpoint on the time axis. In the trajectory generation process, numerical superposition and time sorting are used to organize data, which does not involve complex calculation logic. All constructed nodes are finally unified and summarized to form a sand ratio dynamic adjustment trajectory set, which is the basis for further execution of the control system.

[0032] Specifically, as Figure 2 ,6 The supply-demand speed difference adjustment module includes: The rate extraction submodule dynamically adjusts the target sand supply rate information of the trajectory set extraction period based on the sand ratio, obtains the actual sand supply speed record of the screw auger transmission, performs time corresponding processing on the target rate and the actual speed, screens the matching sample data, and generates a supply-demand rate comparison value group; The rate extraction submodule dynamically adjusts the target sand supply rate information of the trajectory set extraction period based on the sand ratio, obtains the actual sand supply speed record of the screw auger transmission, performs time corresponding processing on the target rate and the actual speed, screens the matching sample data, and generates a supply-demand rate comparison value group;

[0033] The speed difference determination submodule identifies the deviation direction between the target rate and the actual speed according to the supply-demand rate comparison value group, judges the speed difference change trend, divides the rate deviation path of the continuous period into sections, obtains the speed difference direction information of the sections, and obtains the auger speed difference adjustment direction group. The speed difference determination sub-module identifies the deviation direction according to the target and actual speed data in the supply-demand speed rate reference value group, and determines the speed difference trend. First, the speed difference is calculated for each set of paired values, which is the target speed rate minus the actual speed rate. For example, if the target is 0.416 L / s and the actual is 0.38 L / s, the speed difference is 0.036 L / s, and the judgment direction is positive deviation, indicating that the actual supply speed is low. After all the speed differences are calculated, they are sorted by time to form a speed difference path. The path is divided into sections, and the continuous same direction speed difference is used as the division standard. For example, if the speed difference is positive for 5 consecutive seconds, it is recorded as a positive deviation section. Further, the speed difference direction information in each section is determined. If the deviation direction of most points is consistent, the section direction is confirmed as positive or negative deviation. The deviation direction proportion is set as the threshold in the division process. For example, if 80% is set as the reference, if more than 80% of the data in a section is positive deviation, it is marked as a positive deviation section. If it is less than -0.05 L / s, it is recorded as a significant negative deviation interval, and if it is less than -0.1 L / s, it is recorded as a serious negative deviation interval. Special marks are made for significant and serious sections in the division process for subsequent speed correction module judgment and processing priority. Finally, the speed difference direction information in each section is output in time sequence to form the auger speed difference adjustment direction group.

[0034] The speed correction sub-module calls the speed difference direction information in the auger speed difference adjustment direction group, combines the original speed record of the spiral auger transmission, adjusts the sand supply speed parameter according to the supply-demand deviation, records the adjustment time and speed change, and generates the auger speed difference matching sequence. The speed correction sub-module executes the speed parameter correction operation according to the direction information in each time period in the auger speed difference adjustment direction group, combined with the original sand supply speed record. First, the actual supply speed and target supply speed paired values in each time period are extracted to determine the supply-demand deviation type. If it is positive deviation, it is judged as insufficient supply, and vice versa. The correction direction is set according to different deviation types. For insufficient supply, the supply speed is adjusted upward, and for excessive supply, the supply speed is adjusted downward. The correction amplitude is calculated according to the deviation and the adjustment coefficient. If the adjustment coefficient is 0.6 and the current speed difference is -0.05 L / s, the correction value is 0.03 L / s, and the original sand supply speed is adjusted from 0.38 L / s to 0.41 L / s. The speed adjustment can be set to a minimum adjustment unit of 0.01 L / s to avoid system instability caused by frequent adjustment. Each adjustment records the adjustment time, original speed, corrected speed and deviation value to form a speed adjustment point sequence. The sequence is sorted by time to form the auger speed difference matching sequence. The whole process is continuously executed in each section to finally build a time-varying path of the actual supply speed and the target rate trend for subsequent analysis and operation of the control system.

[0035] Specifically, as Figure 2 , 7As shown, the control parameter feedback module comprises: The rate extraction submodule extracts the actual sand supply rate records corresponding to the start and end time of the adjustment stage based on the auger speed difference matching sequence, obtains the target sand supply rate value at the time node, arranges the target rate and the actual rate in time sequence, and screens complete paired data to generate a sand supply rate pairing sequence. The rate extraction submodule extracts the actual sand supply rate data corresponding to the start and end time node of the adjustment stage based on the auger speed difference matching sequence. First, the adjustment stage time interval recorded in the matching sequence is read, for example, the start is 100 seconds and the end is 160 seconds. The actual sand supply rate value at each time point is extracted in the interval in seconds. The unit of sand supply rate is L / s, which is usually collected and recorded in the system log by the sensor. The target sand supply rate at each time point is obtained synchronously. The target value is obtained by multiplying the sand ratio and the pump displacement. If the sand ratio is 0.1 and the pump displacement is 4.5 L / s, the target rate is 0.45 L / s. For the entire time interval, the target sand supply rate value at each time is calculated in sequence to construct a target rate data column corresponding to the actual rate. The target rate and the actual rate are paired in time sequence to form a group of speed combinations, for example, the target rate at 105 seconds is 0.45 L / s and the actual rate is 0.41 L / s, which constitutes a group of paired data. After the arrangement is completed, the screening operation is performed to remove missing records or paired data with obvious abnormalities. The screening basis is whether the absolute value of the difference between the target and actual rate exceeds the set threshold, for example, the threshold is 0.2 L / s. If the difference at a certain time exceeds the threshold, it is considered abnormal. After this process is completed, a complete sand supply rate pairing sequence is generated, which records the corresponding relationship between all effective target and actual sand supply rates in the entire adjustment stage.

[0036] The target comparison submodule extracts the start and end rate values according to the combination of the time period target rate and the actual rate in the sand supply rate pairing sequence, calculates the supply-demand offset direction of the stage, arranges the distribution of the offset direction in the time sequence, and obtains the time period rate offset trend. The target comparison sub-module uses the target and actual rate value combination information in the sand supply rate pairing sequence to first segment the time interval according to the stage division rule, assuming that 30 seconds is one adjustment stage division unit, two stages can be divided in the interval, the target sand supply rate and the actual sand supply rate at the start and end time points of each stage are extracted respectively, for example, the first stage is from the 100th second to the 130th second, the starting target rate is 0.45 L / s, the terminal target rate is 0.50 L / s, the actual rates are 0.38 L / s and 0.43 L / s respectively, the supply-demand rate difference of the stage is calculated, the result is target minus actual, the offset direction is positive, indicating that the target is higher than the actual, this difference calculation operation is performed for each stage, and the result offset direction is recorded, then the offset directions of all stages are sorted in time sequence to form a time sequence offset distribution, if the offset direction is continuous and consistent, such as multiple stages are positive, it can be considered that there is a continuous deviation in the interval, in addition, a supply-demand difference judgment standard can be set, if the offset value is greater than 0.05 L / s, it is ordinary deviation, and if it exceeds 0.1 L / s, it is significant deviation, the overall trend of the offset direction on the time axis is identified through this way, and then the time period change of the rate adjustment is marked, and finally the period rate offset trend record is formed.

[0037] The response generation submodule calls the period rate offset trend in the period offset direction, combines the sand supply control execution parameters and the target sand supply rate set value, and performs sequential processing according to the time position, calculates the change of the response offset on the time axis, and generates a dynamic sand supply response offset rate sequence; The response generation submodule processes according to the period rate offset trend in each period offset direction, simultaneously introduces the sand supply control parameters and the target sand supply rate value to construct a time sequence, and calculates the offset rate at each time point according to the difference between the target rate and the actual rate, the offset rate is the ratio of the difference between the target rate and the actual rate to the target rate, for example, the target rate is 0.45 L / s at a certain time, and the actual rate is 0.38 L / s, the calculation result is about 15.56%, the offset rate calculation operation is continuously performed in the entire time period, and a complete offset rate list is obtained point by point, on this basis, different stages can be set with different control weights, and each time period offset rate is given a corresponding weight value, for example, the main control period is set to 1.2, and the ordinary period is set to 1.0, the offset rate of all time points is combined with the corresponding weight, and the response offset rate of each stage is obtained by weighted average, and finally the result is sorted in time sequence to form a sand supply response offset rate sequence reflecting dynamic changes, which can be used as an important basis for subsequent control strategy adjustment and response speed matching.

[0038] Please refer to Figure 8 , the intelligent dynamic fracturing sand supply method is executed based on the above-mentioned intelligent dynamic fracturing sand supply system, comprising the following steps: The liquid supply pressure value recorded by the liquid supply data acquisition module and corresponding time information are acquired, a time index sequence is constructed, a pressure fluctuation value in a time period is calculated, and it is determined whether the set threshold is exceeded, a time node at which fluctuation appears is extracted, and a liquid supply fluctuation time node group is generated; Based on the nodes in the liquid supply fluctuation time node group, pressure change data in the front and rear time windows is extracted, the pressure range and change rate of the corresponding section are calculated, and are compared with the limit difference index set in the fracturing process, the over-limit nodes are screened and the characteristic information is recorded, the boundary trigger signal group is generated; According to the nodes in the boundary trigger signal group, the target sand ratio set value and the sand mixing device liquid supply pump displacement parameter at the corresponding moment are acquired, the correlation characteristics between the sand ratio change trend and the pressure fluctuation state are calculated, and it is determined whether the set parameter needs to be adjusted according to the fluctuation direction, the change trajectory of the set value is recorded in combination with the adjustment time point, and the sand ratio dynamic adjustment trajectory set is generated; Based on the adjustment time nodes recorded in the sand ratio dynamic adjustment trajectory set, the target sand supply rate and the actual sand supply speed data are extracted, the supply-demand speed difference value is calculated and the deviation direction is determined, the sand supply speed of the spiral auger transmission system is corrected according to the deviation direction, and the auger speed difference matching sequence is generated; According to the corrected sand supply speed record in the auger speed difference matching sequence, the sand supply rates before and after adjustment are extracted, and are compared with the target set rate, the response deviation degree in the difference period is calculated, and the dynamic sand supply response deviation rate sequence is generated.

[0039] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any skilled person in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An intelligent dynamic fracturing sand supply system, characterized in that: The system comprises: The fluid supply data acquisition module obtains the continuous fluid supply pressure and corresponding time information of the fracturing pipeline pressure monitoring, constructs a time index sequence, extracts and identifies the pressure fluctuation changes within the time period, marks the time nodes with fluctuations, and generates a fluid supply fluctuation time node group; The pump pressure boundary identification module extracts the pressure change value in the time window before and after each node based on the fluid supply fluctuation time node group, identifies the pressure extreme value difference, compares the limit difference index during the fracturing process, selects the nodes that exceed the limit value and records the characteristic attributes, and generates a boundary trigger signal group; The target sand ratio correction module obtains the sand ratio setting parameters and the displacement parameters of the sand mixing device liquid supply pump in the current target sand ratio setting according to the boundary trigger signal group, adjusts the sand ratio setting value in combination with the pressure fluctuation state, and records the adjustment time and the setting value change trend to generate a sand ratio dynamic adjustment trajectory set; The supply-demand speed difference adjustment module extracts the target sand supply rate and the actual sand supply speed of the spiral auger transmission at the corresponding moment based on the dynamic adjustment trajectory set of the sand ratio, compares the differences, corrects the auger speed according to the direction of the difference, records the adjustment parameters and speed change process, and generates an auger speed difference matching sequence.

2. The intelligent dynamic fracturing sand supply system according to claim 1, characterized in that: The liquid supply fluctuation time node group includes the fluctuation starting point, the fluctuation end point, and the fluctuation peak point; the boundary trigger signal group includes the pressure extreme value difference, the over-limit mark, and the characteristic attributes; the sand ratio dynamic adjustment trajectory set includes the adjustment time, the set value change amplitude, and the change trend; the auger speed difference matching sequence includes the target sand supply rate, the actual sand supply speed, and the speed correction parameter.

3. The intelligent dynamic fracturing sand supply system according to claim 1, characterized in that: The liquid supply data acquisition module includes: The time series submodule obtains the continuous liquid supply pressure and corresponding time information of the liquid supply pressure monitoring, arranges the time and pressure values ​​point by point, establishes an index according to the time sequence, and generates a time index sequence value; The fluctuation segment submodule calls the liquid supply pressure value within the time period based on the time index sequence value, calculates the pressure difference value of adjacent time periods, compares the pressure difference value with the pressure fluctuation threshold, selects the segments exceeding the threshold, and generates a pressure fluctuation interval group; The node identification submodule calls the start and end time points of the segment according to the pressure fluctuation interval group, calculates the time difference value of adjacent segments, merges the segments whose time difference value is less than the interval threshold, obtains the merged fluctuation start and end time point set, and generates the liquid supply fluctuation time node group.

4. The intelligent dynamic fracturing sand supply system according to claim 3, characterized in that: The pump pressure boundary identification module includes: The window extraction submodule calls the liquid supply pressure values ​​within the time range before and after the node based on the liquid supply fluctuation time node group, collects the pressure data within the corresponding time period, constructs a pressure change sequence in chronological order, and generates a node pressure change value group; The range identification submodule identifies the difference between the maximum and minimum values ​​in the sequence according to the node pressure change value group, judges the difference value according to the fracturing process limit index, extracts the data items that meet the conditions, and generates a limit deviation amplitude group; The feature screening submodule calls the corresponding node information in the limit deviation amplitude group, screens the target nodes according to the pressure change amplitude, time position and limit deviation exceeding situation, extracts the corresponding feature information of the nodes, and generates a boundary trigger signal group.

5. The intelligent dynamic fracturing sand supply system according to claim 4, characterized in that: The target sand ratio correction module includes: The parameter extraction submodule calls the target sand ratio setting parameters and the displacement parameters of the sand mixing device liquid supply pump based on the boundary trigger signal group, extracts the setting value information and displacement information within the corresponding time period in combination with the pressure fluctuation state, establishes a corresponding relationship between the two types of parameters, and generates a sand ratio control associated value group; The setting adjustment submodule determines the matching between the setting parameters and the displacement parameters under the current pressure fluctuation state according to the sand ratio control associated value group, adjusts the target setting parameters according to the setting value change trend, obtains the setting value change amplitude under the difference node, and obtains the sand ratio correction change amount group; The trajectory generation submodule calls the set value change amplitude and corresponding adjustment time in the sand ratio correction change group, arranges the change path of the set parameters in chronological order, constructs a continuously changing parameter sequence, and generates a sand ratio dynamic adjustment trajectory set.

6. The intelligent dynamic fracturing sand supply system according to claim 5, characterized in that: The supply-demand speed difference adjustment module includes: The rate extraction submodule extracts the target sand supply rate information of the time period based on the sand ratio dynamic adjustment trajectory set, obtains the actual sand supply speed record of the spiral auger drive, performs time correspondence processing on the target rate and the actual speed, filters and matches sample data, and generates a supply and demand rate comparison value group; The speed difference determination submodule identifies the offset direction between the target speed and the actual speed according to the supply and demand speed comparison value group, determines the speed difference change trend, divides the speed offset path of the continuous time period into sections, obtains the speed difference direction information of the sections, and obtains the auger speed difference adjustment direction group; The speed correction submodule calls the speed difference direction information in the auger speed difference adjustment direction group, combines the original speed record of the spiral auger transmission, adjusts the sand supply speed parameter according to the supply and demand offset, records the adjustment time and speed change, and generates an auger speed difference matching sequence.

7. The intelligent dynamic fracturing sand supply system according to claim 1, characterized in that: The method further comprises: The control parameter feedback module extracts the sand supply rate values ​​before and after the adjustment stage according to the auger speed difference matching sequence, compares them with the target rate, and serializes them in the time dimension to form a response relationship between the sand supply control execution and the target setting, and generates a dynamic sand supply response offset rate sequence; The dynamic sand supply response deviation rate sequence includes an execution rate, a target rate, and a response deviation rate; The sand supply control execution refers to the actual sand supply process achieved by adjusting the auger drive device; The dynamic sand supply response deviation rate sequence is a sequence formed by the deviation rate between the sand supply rate and the target rate changing over time.

8. The intelligent dynamic fracturing sand supply system according to claim 7, characterized in that: The control parameter feedback module includes: The rate extraction submodule extracts the actual sand supply rate records corresponding to the start and end times of the adjustment phase based on the auger speed difference matching sequence, obtains the target sand supply rate value at the time node, sorts the target rate and the actual rate in chronological order, and screens the complete matching data to generate a sand supply rate matching sequence; The target comparison submodule extracts the starting and ending rate values ​​according to the combination of the target rate and the actual rate in the time period of the sand supply rate pairing sequence, according to the adjustment stage division rule, calculates the supply and demand offset direction of the stage, organizes the distribution of the offset direction in the time series, and obtains the time period rate offset trend; The response generation submodule calls the period offset direction in the period rate offset trend, combines the sand supply control execution parameters and the target sand supply rate setting value, performs serial processing according to the time position, calculates the change of the response offset on the time axis, and generates a dynamic sand supply response offset rate sequence.

9. The intelligent dynamic fracturing sand supply system according to claim 1, characterized in that: The time index sequence is a sequence data structure composed of collected pressure data and timestamps; The segment extraction and feature recognition is based on a preset statistical or signal processing algorithm to identify the characteristics of pressure changes; The liquid supply fluctuation time node group is a set of time points corresponding to when the pressure fluctuation exceeds a preset threshold; The tolerance index refers to the pressure fluctuation range preset according to the construction design or monitoring data during the fracturing operation; The boundary trigger signal group refers to a set of trigger signals generated when the limit difference is exceeded; The sand ratio setting parameter refers to the ratio of solid proppant to sand-carrying liquid set according to process design or on-site adjustment during fracturing construction; The dynamic adjustment trajectory set of the sand ratio is a set of change curves formed by adjusting the sand ratio setting value over time; The sand ratio setting value refers to the pre-set parameters of the solid proppant and liquid-carrying fluid ratio during the fracturing operation, including the operation design plan, field input or dynamic adjustment of the control system based on pressure fluctuations; The spiral auger transmission is a mechanical transmission device using a screw conveyor (auger) in the sand supply system; The auger speed difference matching sequence is a matching data sequence of the adjusted auger speed and the target speed.

10. An intelligent dynamic fracturing sand supply method, characterized in that: The intelligent dynamic fracturing sand supply system according to any one of claims 1 to 9 comprises the following steps: Obtain the liquid supply pressure value and corresponding time information recorded by the liquid supply data acquisition module, construct a time index sequence, calculate the pressure fluctuation value within the time period, and determine whether it exceeds the set threshold, extract the time nodes where the fluctuation occurs, and generate a liquid supply fluctuation time node group; Based on the nodes in the fluid supply fluctuation time node group, extract the pressure change data in the previous and next time windows, calculate the pressure range and change rate of the corresponding section, and compare them with the limit difference indicators set in the fracturing process, screen out-of-limit nodes and record characteristic information to generate a boundary trigger signal group; According to the nodes in the boundary trigger signal group, the target sand ratio setting value and the displacement parameter of the sand mixing device liquid supply pump at the corresponding moment are obtained, the correlation characteristics between the sand ratio change trend and the pressure fluctuation state are calculated, and the setting parameter is judged whether it needs to be adjusted based on the fluctuation direction. The change trajectory of the setting value is recorded at the adjustment time point to generate a sand ratio dynamic adjustment trajectory set; Based on the adjustment time nodes recorded in the dynamic adjustment trajectory of the sand ratio, the target sand supply rate and the actual sand supply speed data are extracted, the supply and demand speed difference is calculated and the deviation direction is determined, the sand supply speed of the spiral auger transmission system is corrected according to the deviation direction, and the auger speed difference matching sequence is generated; According to the corrected sand supply speed record in the auger speed difference matching sequence, the sand supply rate before and after adjustment is extracted and compared with the target set rate, the response deviation degree within the difference period is calculated, and a dynamic sand supply response deviation rate sequence is generated.

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