Intelligent temperature control oil field test sample magnetic stirring device and method

Abstract

The invention relates to the technical field of stirring speed control, in particular to an intelligent temperature control oil field test sample magnetic stirring device and method. The method comprises the following steps: firstly, acquiring vibration intensity and stirring speed time sequence data of a magnetic stirrer in a plurality of historical sampling periods during magnetic stirring of an oil field test sample; performing frequency domain analysis on the vibration intensity time sequence data, and determining an abnormal jump characteristic value to identify an abnormal jump condition; analyzing the change characteristics and the confusion degree of the stirring speed time sequence data, determining an instability evaluation value, and quantifying the stability of the stirrer; synthesizing the abnormal bounce characteristic value and the instability evaluation value, analyzing the change synchronism of the abnormal bounce characteristic value and the instability evaluation value in a historical period, and determining a bounce coupling degree; finally, the expected stirring speed of the current sampling period is determined according to the beating coupling degree numerical value characteristics, the preset stirring speed and historical stirring speed time sequence data; on the basis of multi-factor comprehensive analysis, stirring bar abnormity caused by unreasonable stirring speed can be avoided, and accurate control is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of stirring speed control, in particular to an intelligent temperature control oilfield test sample magnetic stirring device and method. BACKGROUND

[0002] In the process of oilfield exploration and development, test analysis is a very key link, which can provide important data support for oil reservoir evaluation, development plan formulation, etc. Among them, the magnetic stirring of oilfield test samples is a common and basic operation, the purpose is to make various components in the sample fully mixed and uniform, and the stirring effect directly affects the accuracy and reliability of the test results, which is a key operation link to ensure the reliability of subsequent test analysis results.

[0003] In order to better meet the high-precision and high-efficiency test requirements in the process of oilfield test, the existing technology usually integrates temperature control sensors and magnetic stirring equipment in intelligent temperature control, so as to ensure the uniformity of internal temperature transfer of oilfield test samples, and at the same time avoid the obvious stratification phenomenon of high viscosity oilfield test samples.

[0004] The magnetic stirring equipment is a stirring device using a magnetic coupler to transfer power, which ensures the stable rotation of the magnetic stirring sub and generates stable eddy current, and improves the uniformity of internal temperature transfer of oilfield test samples. However, due to the abnormal jumping phenomenon of the magnetic stirring sub in the magnetic stirring process, the stability in the magnetic stirring process will be affected, and the existing technology usually uses fixed stirring speed to control and adjust the stirring speed of the magnetic stirring sub, without fully considering the characteristics that the magnetic stirring sub is prone to abnormal jumping, so as to cause poor accuracy of controlling and adjusting the stirring speed of the magnetic stirring sub, and easily cause high-frequency shaking of the magnetic stirring sub or even cause violent fluctuation of the oilfield test sample. SUMMARY

[0005] In order to solve the technical problem that the existing technology usually uses fixed stirring speed to control and adjust the stirring speed of the magnetic stirring sub, without fully considering the characteristics that the magnetic stirring sub is prone to abnormal jumping, so as to cause poor accuracy of controlling and adjusting the stirring speed of the magnetic stirring sub, the present application aims to provide an intelligent temperature control oilfield test sample magnetic stirring device and method, and the technical scheme adopted is as follows:

[0006] An intelligent temperature control oilfield test sample magnetic stirring method, the method comprising:

[0007] In the process of magnetic stirring of oilfield test samples, the vibration intensity time series data and the stirring speed time series data of the magnetic stirring sub in a plurality of historical sampling periods are obtained;

[0008] perform frequency domain analysis on the vibration intensity time series data of each historical sampling period, analyze the difference characteristics between the frequencies corresponding to different energy values, and the numerical characteristics of the energy values, to determine the abnormal jumping characteristic value of the magnetic stirring rod in each historical sampling period;

[0009] In each historical sampling period, analyze the change characteristics and the degree of confusion of the stirring speed time series data, to determine the instability evaluation value of the magnetic stirring rod in each sampling period;

[0010] In the historical sampling period, the abnormal jumping characteristic value and the instability evaluation value of the magnetic stirring rod are analyzed, and the change synchronization between the historical sampling periods is analyzed, to determine the jumping coupling degree of the magnetic stirring rod in the historical sampling period; according to the numerical characteristics of the jumping coupling degree of the magnetic stirring rod in the historical sampling period, the preset stirring speed and the stirring speed time series data corresponding to the historical sampling period, the expected stirring speed of the magnetic stirring rod in the current sampling period is determined.

[0011] Further, the method for obtaining the abnormal jumping characteristic value comprises:

[0012] In each historical sampling period, the vibration intensity time series data is analyzed by using fast Fourier transform to obtain an energy spectrum;

[0013] In the energy spectrum corresponding to each historical sampling period, the difference between the frequencies of different energy values is compared to determine the jumping high frequency coefficient of the magnetic stirring rod in each historical sampling period;

[0014] In the energy spectrum corresponding to each historical sampling period, the numerical difference characteristics of the energy values between different frequencies are analyzed to determine the jumping energy proportion factor of the magnetic stirring rod in each historical sampling period;

[0015] The sum of the jumping high frequency coefficient and the jumping energy proportion factor corresponding to each historical sampling period is normalized, and the value is used as the abnormal jumping characteristic value of the magnetic stirring rod in each historical sampling period.

[0016] Further, the method for obtaining the jumping high frequency coefficient comprises:

[0017] In the energy spectrum, the ratio of the maximum frequency value with a non-zero energy value to the fundamental frequency is used as the jumping high frequency coefficient of the magnetic stirring rod in each historical sampling period.

[0018] Further, the method for obtaining the jumping energy proportion factor comprises:

[0019] In the energy spectrum of each historical sampling period, the ratio of the sum of the energy values corresponding to all frequencies greater than the fundamental frequency to the energy value of the fundamental frequency is used as the jumping energy proportion factor of the magnetic stirring rod in each historical sampling period.

[0020] Further, the method for obtaining the instability evaluation value comprises:

[0021] In each historical sampling period, analyze the change characteristics between the stirring speeds at adjacent sampling moments in the stirring speed time series data, and determine a change intensity factor corresponding to each sampling moment;

[0022] Calculate the permutation entropy of the change intensity factors of all sampling moments in each historical sampling period as a chaos degree value, and calculate the sum of the change intensity factors of all sampling moments in each historical sampling period as a change intensity degree value;

[0023] The sum of the chaos degree value and the change intensity degree value corresponding to each historical sampling period after normalization is taken as the instability evaluation value of the magnetic stirring sub in each historical sampling period.

[0024] Further, the method for obtaining the change intensity factor comprises:

[0025] In the stirring speed time series data of each historical sampling period, optionally take one sampling moment as a to-be-tested moment, calculate the absolute value of the difference between the stirring speeds at the to-be-tested moment and the adjacent previous moment as the change intensity factor of the to-be-tested moment, wherein the change intensity factor of the first sampling moment is a preset value.

[0026] Further, the method for obtaining the jump coupling degree comprises:

[0027] In time sequence, sequentially take the last two historical sampling periods as to-be-tested periods;

[0028] Arrange the abnormal jump characteristic values of the magnetic stirring sub in all historical sampling periods before the to-be-tested period in time sequence to obtain an abnormal jump characteristic sequence;

[0029] Arrange the instability evaluation values of the magnetic stirring sub in all historical sampling periods of the to-be-tested period in time sequence to obtain an instability evaluation characteristic sequence;

[0030] Analyze the change synchronization between the abnormal jump characteristic sequence and the instability evaluation characteristic sequence of the to-be-tested period to determine a first jump coupling factor of the magnetic stirring sub in the to-be-tested period;

[0031] The product of the abnormal jump characteristic value and the instability evaluation value of the magnetic stirring sub in the to-be-tested period after normalization is taken as a second jump coupling factor of the magnetic stirring sub in the to-be-tested period;

[0032] The sum of the first jump coupling factor and the second jump coupling factor of the magnetic stirring sub in the to-be-tested period after normalization is taken as the jump coupling degree of the magnetic stirring sub in the to-be-tested period.

[0033] Further, the first bounce coupling factor acquisition method comprises:

[0034] The DTW distance of the abnormal bounce feature sequence and the instability evaluation feature sequence is calculated and negatively correlated and mapped and normalized, as the first bounce coupling factor of the magnetic stirrer in the to-be-tested period.

[0035] Further, the expected stirring speed acquisition method comprises:

[0036] In terms of time sequence, the last historical sampling period is taken as a comparison period;

[0037] The average value of the stirring speed at all times in the stirring speed time sequence data of the comparison period is taken as a reference value;

[0038] The product of the difference between the bounce coupling degree of the comparison period and the adjacent previous historical sampling period, a preset adjustment coefficient, and the reference value is taken as a stirring speed adjustment value;

[0039] The difference between the reference value and the stirring speed adjustment value is taken as a first stirring speed candidate value, and the maximum value between the first stirring speed candidate value and a preset minimum stirring speed is taken as a second stirring speed candidate value;

[0040] The minimum value between the second stirring speed candidate value and a preset maximum stirring speed is taken as the expected stirring speed of the magnetic stirrer in the current sampling period.

[0041] An intelligent temperature control oil field sample magnetic stirring device comprises an intelligent temperature control magnetic stirring device body and a stirring speed control module, the stirring speed control module comprises a processor and a memory, the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to realize the steps of an intelligent temperature control oil field sample magnetic stirring method.

[0042] The present application has the following beneficial effects:

[0043] In the process of magnetic stirring of oilfield test samples, the vibration intensity and stirring speed time sequence data of the magnetic stirrer in multiple historical sampling periods are obtained. Generally, if the magnetic stirrer of the magnetic stirring device abnormally jumps, the vibration intensity of the magnetic stirrer will have a significant high-frequency abnormal change, so the vibration intensity time sequence data of each historical sampling period is analyzed in the frequency domain, and the difference characteristics between the frequencies corresponding to different energy values and the numerical characteristics of the energy values are analyzed to determine the abnormal jumping characteristic value, and the abnormal jumping of the stirrer in the stirring process is accurately identified. Further, the higher the degree of change of the stirring speed of the magnetic stirrer and the stronger the irregularity, the worse the control effect of the stirring speed of the magnetic stirrer, so the change characteristics and the degree of confusion of the stirring speed time sequence data in each historical sampling period are analyzed to determine the instability evaluation value of the magnetic stirrer in each sampling period. This evaluation method can quantify the stability of the stirrer in the stirring process. Then, the abnormal jumping characteristic value and the instability evaluation value of the magnetic stirrer are comprehensively analyzed, and the change synchronization between the historical sampling periods is analyzed to determine the jumping coupling degree of the magnetic stirrer in the historical sampling period. This step can further explore the internal relationship between the abnormal jumping and instability of the stirrer. Finally, according to the numerical characteristics of the jumping coupling degree of the magnetic stirrer in the historical sampling period, the preset stirring speed and the stirring speed time sequence data corresponding to the historical sampling period, the expected stirring speed of the magnetic stirrer in the current sampling period is determined. The expected stirring speed determined based on the comprehensive analysis of multiple factors can avoid the abnormal situation such as high-frequency jitter of the stirrer caused by unreasonable stirring speed, thereby effectively ensuring the stable operation of the magnetic stirring equipment. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art and the advantages thereof, a brief introduction will be given to the drawings needed in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0045] Figure 1 A structural schematic diagram of a temperature-controlled stirring cover provided by an embodiment of the present application;

[0046] Figure 2 A module structural schematic diagram of a stirring speed control module provided by an embodiment of the present application;

[0047] Figure 3 A method flowchart of an intelligent temperature-controlled oilfield test sample magnetic stirring method provided by an embodiment of the present application;

[0048] Figure 4 A method flow chart of an abnormal beat feature value acquisition method provided by an embodiment of the present application;

[0049] Figure 5 A method flow chart of an instability evaluation value acquisition method provided by an embodiment of the present application;

[0050] Figure 6 A method flow chart of a beat coupling degree acquisition method provided by an embodiment of the present application;

[0051] Reference signs: 1-motor, 2-temperature controller display screen, 3-sample bucket cover, 4-coupling, 5-shaft, 6-temperature control probe, 7-magnetic stirrer. DETAILED DESCRIPTION

[0052] In order to further illustrate the technical means and effects taken by the present application to achieve the predetermined purposes, the specific embodiments, structures, features and effects of the intelligent temperature control oilfield sample magnetic stirring device and method according to the present application are described in detail as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0054] The specific scheme of the intelligent temperature control oilfield sample magnetic stirring device and method provided by the present application is described in detail below with reference to the accompanying drawings.

[0055] An intelligent temperature control oilfield sample magnetic stirring device comprises a temperature control magnetic stirring device body and a stirring speed control module. The temperature control magnetic stirring device body is mainly composed of a heat-conducting alloy sample bucket, a 24-slot constant-temperature water bath kettle, a sample bucket cover and a temperature control stirring cover. The heat-conducting alloy sample bucket is made of high-thermal-conductivity material and can quickly absorb heat to shorten the heating time. The sample slots in the 24-slot constant-temperature water bath kettle are distributed in 6 rows and 4 columns, which can meet the batch preheating demand by expansion. The temperature control stirring cover is provided with a magnetic stirrer, which can realize uniform temperature of the oilfield sample and accelerate heat transfer. Please refer to Figure 1 The temperature control stirring cover comprises a motor 1, a temperature controller display screen 2, a sample bucket cover 3 (integrating a temperature control sensor inside, which can monitor the sample temperature in real time), a coupling 4, a shaft 5, a temperature control probe 6 and a magnetic stirrer 7.

[0056] In the embodiment of the present application, a stirring speed control module (not shown in Figure 1 ) is built in the temperature control stirring cover. Please refer toFigure 2 Fig. 1 shows a schematic diagram of a module structure of the stirring speed control module in one embodiment of the present application, comprising a processor 100, a memory 101, a bus 102 and a communication interface 103, wherein the processor 100, the communication interface 103 and the memory 101 are connected through the bus 102; wherein the memory 101 can contain a high-speed random access memory, the bus 102 can be an ISA bus, a PCI bus or an EISA bus, etc., the processor 100 can be an integrated circuit chip with signal processing capability; the memory 101 stores at least one instruction, at least one program, a code set or an instruction set, which are loaded and executed by the processor to implement the steps in the intelligent temperature-controlled oilfield sample magnetic stirring method.

[0057] Please refer to Figure 3 Fig. 2 shows a flow chart of an intelligent temperature-controlled oilfield sample magnetic stirring method provided in one embodiment of the present application, which comprises the following steps:

[0058] Step S1: In the process of magnetic stirring of the oilfield sample, the vibration intensity time series data and the stirring speed time series data of the magnetic stirring sub in a plurality of historical sampling periods are acquired.

[0059] The temperature-controlled magnetic stirring device is a stirring device using a magnetic coupler to transfer power. In the process of magnetic stirring, it is often necessary to monitor the effect of magnetic stirring in real time and control and adjust the stirring speed of the magnetic stirring sub 7 to ensure that the magnetic stirring sub 7 rotates stably and generates stable eddy current, thereby improving the uniformity of the internal temperature transfer of the oilfield sample. However, due to the abnormal jumping phenomenon of the magnetic stirring sub 7 in the process of magnetic stirring, the stability in the process of magnetic stirring is affected, and the abnormal jumping often leads to poor accuracy of controlling and adjusting the stirring speed of the magnetic stirring sub 7, which easily causes high-frequency jitter of the magnetic stirring sub 7 or even causes violent fluctuation of the oilfield sample. Therefore, in the embodiment of the present application, the abnormal jumping phenomenon needs to be analyzed to adjust the stirring speed of the magnetic stirring sub 7.

[0060] Firstly, in the process of magnetic stirring of the oilfield sample, the vibration intensity and the stirring speed of the magnetic stirring sub 7 in the process of magnetic stirring are sampled by the accelerometer and the Hall sensor integrated in the stirring speed control module, wherein the sampling rate is 1 kHz and the time length of the sampling period is 1 s. In the embodiment of the present application, a plurality of historical sampling periods are set, the number of historical sampling periods is set to at least 10, counting starts from the current time, and the vibration intensity time series data and the stirring speed time series data in each historical sampling period must be collected at the same time to ensure time alignment.

[0061] At this point, the vibration intensity time series data of the magnetic stirring rod 7 in multiple historical sampling periods and the stirring speed time series data can be obtained.

[0062] It should be noted that the sampling frequency, the length of the sampling period, and the number of sampling periods can be adjusted according to the implementation scenario, and are not limited herein.

[0063] Step S2: Perform frequency domain analysis on the vibration intensity time series data of each historical sampling period, analyze the difference characteristics between the frequencies corresponding to different energy values and the numerical characteristics of the energy values, and determine the abnormal jumping characteristic value of the magnetic stirring rod in each historical sampling period.

[0064] Since the magnetic stirring rod 7 is prone to abnormal jumping during the magnetic stirring process, such as collision between the magnetic stirring rod 7 and the sample barrel wall or too large change in the stirring speed, which can easily cause the magnetic stirring rod 7 to abnormally jump, which can affect the stability of the magnetic stirring process. Therefore, it is necessary to fully excavate the abnormal jumping characteristics of the magnetic stirring rod 7 during the stirring process, so as to more accurately control and adjust the stirring speed during the magnetic stirring process, and avoid causing the magnetic stirring rod 7 to abnormally jump or even cause the oil field test sample to fluctuate violently.

[0065] Generally, the vibration intensity of the magnetic stirring rod 7 will show a low-frequency and stable change characteristic, but if the magnetic stirring rod 7 of the magnetic stirring device abnormally jumps, the vibration intensity of the magnetic stirring rod 7 will abnormally change at a high frequency. Therefore, in the embodiment of the present application, the vibration intensity time series data of each historical sampling period can be first analyzed in the frequency domain, and the difference characteristics between the frequencies corresponding to different energy values and the numerical characteristics of the energy values are compared to determine the abnormal jumping characteristic value of the magnetic stirring rod 7 in each historical sampling period. This index helps to understand the abnormal jumping of the magnetic stirring rod 7 in each historical sampling period.

[0066] Preferably, in an embodiment of the present application, the method for obtaining the abnormal jumping characteristic value comprises:

[0067] Please refer to Figure 4 which shows a method flowchart of the method for obtaining the abnormal jumping characteristic value in an embodiment of the present application, and the method comprises the following steps:

[0068] Step S201: Obtain the energy spectrum of the vibration intensity time series data of each historical sampling period.

[0069] In each historical sampling period, the vibration intensity time series data is analyzed in the frequency domain by using fast Fourier transform to obtain the energy spectrum. The energy spectrum can directly present the energy distribution of different frequency components in the vibration intensity time series data.

[0070] It should be noted that the fast Fourier transform is a known technology, and the specific process is not described here.

[0071] Step S202: In the energy spectrum corresponding to each historical sampling period, the difference between the frequencies of different energy values is compared to determine the jump high frequency coefficient of the magnetic stirrer in each historical sampling period.

[0072] During the magnetic stirring process, the vibration generated by normal stirring mainly has low frequency and stable characteristics, while abnormal jumping introduces high frequency vibration.

[0073] Therefore, in the energy spectrum of each historical sampling period, the maximum frequency value with a non-zero energy value is counted as a high frequency characteristic value, and the fundamental frequency (referring to the frequency corresponding to the maximum energy value in the energy spectrum) is obtained. The high frequency characteristic value reflects the highest frequency vibration component of the magnetic stirrer 7 during stirring, and the fundamental frequency represents the main vibration frequency of the magnetic stirrer 7 during stirring. Therefore, the ratio of the high frequency characteristic value to the fundamental frequency is calculated as the jump high frequency coefficient of the magnetic stirrer 7 in each historical sampling period. The greater the jump high frequency coefficient, the greater the degree of high frequency vibration introduced by abnormal jumping compared to the fundamental frequency vibration during normal stirring. It can be considered as a high frequency feature of the abnormal jump of the magnetic stirrer 7, and the abnormal jump of the magnetic stirrer 7 is more serious.

[0074] Step S203: In the energy spectrum corresponding to each historical sampling period, the numerical difference characteristics of the energy values between different frequencies are analyzed to determine the jump energy proportion factor of the magnetic stirrer in each historical sampling period.

[0075] During the magnetic stirring process, abnormal jumping will cause an increase in high frequency vibration energy. Therefore, in the energy spectrum of each historical sampling period, the sum of the energy values corresponding to all frequencies greater than the fundamental frequency is counted as the high frequency energy sum. The greater the high frequency energy sum, the more significant the high frequency vibration energy. The energy value of the fundamental frequency represents the main vibration energy of the magnetic stirrer 7 during normal stirring, which is the energy benchmark for stable operation of the stirrer. The ratio of the high frequency vibration energy sum to the energy value of the fundamental frequency is calculated as the jump energy proportion factor of the magnetic stirrer 7 in each historical sampling period. When abnormal jumping occurs, additional high frequency vibration energy is introduced. If the ratio of the high frequency vibration energy sum to the energy value of the fundamental frequency is large, that is, the jump energy proportion factor is large, it means that the high frequency vibration energy accounts for a high proportion compared to the fundamental frequency vibration energy during normal stirring, which indicates that abnormal jumping has a significant impact on the vibration of the magnetic stirrer 7, causing a significant change in vibration energy distribution and deviating from the normal stirring state.

[0076] Step S204: combine the beat high frequency coefficient and the beat energy proportion factor corresponding to each historical sampling period to obtain an abnormal beat feature value of the magnetic stirrer in each historical sampling period.

[0077] Based on the analysis in steps S202 and S203, the beat high frequency coefficient and the beat energy proportion factor corresponding to each historical sampling period are positively correlated with the abnormal beat degree of the magnetic stirrer 7 in the historical sampling period. Therefore, the sum of the beat high frequency coefficient and the beat energy proportion factor corresponding to each historical sampling period after normalization is taken as the abnormal beat feature value of the magnetic stirrer 7 in each historical sampling period. The greater the abnormal beat feature value, the higher the significance of the abnormal beat of the magnetic stirrer 7 in the historical sampling period, and the more likely to cause high-frequency vibration of the magnetic stirrer 7 or even cause the oil field test sample to fluctuate violently. Therefore, the stirring speed of the magnetic stirrer 7 during the magnetic stirring process needs to be timely controlled and adjusted to avoid a more serious impact on the stable rotation of the magnetic stirrer 7. The normalization is a technology known to those skilled in the art, and the normalization function can be linear normalization or standard normalization. The specific normalization method is not limited herein.

[0078] Thus, the abnormal beat feature value of the magnetic stirrer 7 in each historical sampling period can be obtained.

[0079] Step S3: analyze the change characteristics and the degree of confusion of the stirring speed time series data in each historical sampling period to determine the instability evaluation value of the magnetic stirrer in each sampling period.

[0080] The stirring speed is a key parameter in the operation process of the magnetic stirrer 7, and the change of the time series data thereof can directly reflect the operation state of the magnetic stirrer. Under normal circumstances, the stirring speed should remain relatively stable or fluctuate within a certain reasonable range. If the stirring speed changes abnormally and the irregularity of the dramatic change of the stirring speed is stronger, it is likely that the magnetic stirrer 7 is unstable, which means that the control effect of the stirring speed of the magnetic stirrer 7 is worse, and is not conducive to the stable rotation of the magnetic stirrer 7. Therefore, in this embodiment of the present application, the change characteristics and the degree of confusion of the stirring speed time series data in each historical sampling period are analyzed to determine the instability evaluation value of the magnetic stirrer 7 in each sampling period.

[0081] Preferably, in an embodiment of the present application, the method for obtaining the instability evaluation value comprises:

[0082] Please refer to Figure 5 which shows a method flowchart of the method for obtaining the instability evaluation value in an embodiment of the present application. The method comprises the following steps:

[0083] Step S301: In each historical sampling period, analyze the change characteristics between the stirring speeds at adjacent sampling moments in the stirring speed time series data, and determine the change intensity factor corresponding to each sampling moment.

[0084] During the operation of the magnetic stirrer 7, the change of the stirring speed at adjacent sampling moments can reflect the dynamic characteristics. Therefore, in the stirring speed time series data of each historical sampling period, an optional sampling moment is selected as the to-be-tested moment for ease of explanation and description.

[0085] Then, the absolute value of the difference between the stirring speeds at the to-be-tested sampling moment and the adjacent previous sampling moment is calculated as the change intensity factor of the to-be-tested sampling moment. The change intensity factor can intuitively reflect the change degree of the stirring speed in a local time range. The greater the value, the more intense the change. The change intensity factor of the first sampling moment is set to a preset value because there is no adjacent previous sampling moment. In this embodiment of the present application, the preset value is taken as the change intensity factor of the second historical sampling. The reason is that the time series is close, and the changes may be more similar.

[0086] At this point, the change intensity factor at each sampling moment in each historical sampling period can be obtained.

[0087] Step S302: Analyze the confusion degree of the change intensity factors of all sampling moments in each historical sampling period, and determine the instability evaluation value of the magnetic stirrer in each historical sampling period in combination with the numerical characteristics of the change intensity factors.

[0088] The change intensity factor calculated in step S301 reflects the degree of the instantaneous change of the stirring speed of the magnetic stirrer 7 at each sampling moment. If the comprehensive level of the degree of the change of the stirring speed in a period of time is higher, and the irregularity of the degree of the change of the stirring speed in a short period of time is higher, it can be explained that the control effect on the magnetic stirrer 7 is worse, and it is more unfavorable for the stable rotation of the magnetic stirrer 7.

[0089] Therefore, here, the permutation entropy of the change violent factor at all sampling time points in each historical sampling period is calculated as the chaos degree value, and the sum of the change violent factors at all sampling time points in each historical sampling period is taken as the change violent degree value. Based on the foregoing analysis, it can be known that the chaos degree value and the change violent degree value are positively correlated with the instability of the stirring condition of the magnetic stirring rod 7 in the historical sampling period, so finally, the sum of the chaos degree value and the change violent degree value corresponding to each historical sampling period is taken as the instability evaluation value of the magnetic stirring rod 7 in each historical sampling period after normalization. At this time, the greater the instability evaluation value, the worse the control effect of the stirring speed of the magnetic stirring rod 7 at this time, and the more unfavorable the stable rotation of the magnetic stirring rod 7, and even the problem of the violent jumping of the magnetic stirring rod 7 may be caused. The normalization is a technical means familiar to those skilled in the art, and the selection of the normalization function can be linear normalization or standard normalization, and the specific normalization method is not limited here.

[0090] Step S4: In the historical sampling period, the abnormal jumping characteristic value and the instability evaluation value of the magnetic stirring rod are comprehensively analyzed for the change synchronism between the historical sampling periods, and the jumping coupling degree of the magnetic stirring rod in the historical sampling period is determined; and the expected stirring speed of the magnetic stirring rod in the current sampling period is determined according to the numerical characteristics of the jumping coupling degree of the magnetic stirring rod in the historical sampling period, the preset stirring speed and the stirring speed time sequence data corresponding to the historical sampling period.

[0091] The abnormal jumping characteristic value reflects the abnormal jumping characteristic of the magnetic stirring rod 7 of the magnetic stirring device, and the instability evaluation value reflects the instability characteristic of the stirring speed control of the magnetic stirring rod 7. If the similarity between the abnormal jumping characteristic value and the instability evaluation value of the historical sampling period is higher, and the abnormal jumping characteristic value and the instability evaluation value at the current collection time are both at a high level, it can be indicated that the coupling jumping state of the magnetic stirring rod 7 in the historical sampling period is more serious. In order to avoid causing the high-frequency shaking of the magnetic stirring rod 7 and even causing the violent fluctuation of the oil field test sample, the coupling jumping state can be used as a key index for subsequent adjustment of the stirring speed.

[0092] Firstly, the abnormal jumping characteristic value and the instability evaluation value of the magnetic stirring rod 7 can be comprehensively analyzed in the historical sampling period, and the change synchronism between the historical sampling periods is analyzed, so as to determine the jumping coupling degree of the magnetic stirring rod 7 in the historical sampling period.

[0093] Preferably, in an embodiment of the present application, the method for obtaining the jumping coupling degree comprises:

[0094] Please refer to Figure 6Fig. 1 shows a flow chart of a method for acquiring the coupling degree of the jump in one embodiment of the present application, which comprises the following steps:

[0095] Step S401: In time sequence, the last two historical sampling periods are taken as the to-be-tested periods respectively, the abnormal jump feature sequence and the stability evaluation feature sequence corresponding to the to-be-tested periods are acquired and the change synchronism between them is analyzed, and the first jump coupling factor of the magnetic stirrer in the to-be-tested period is determined.

[0096] The abnormal jump feature values of the magnetic stirrer 7 in all the historical sampling periods before the to-be-tested period are arranged in time sequence to obtain the abnormal jump feature sequence; similarly, the instability evaluation values of the magnetic stirrer 7 in all the historical sampling periods before the to-be-tested period are arranged in time sequence to obtain the instability evaluation feature sequence.

[0097] At this time, the feature sequence contains rich dynamic information, which can clearly reflect the change of the abnormal jump feature value and the instability evaluation value in different periods, then the DTW distance of the abnormal jump feature sequence and the instability evaluation feature sequence is calculated, the smaller the DTW distance, the more similar the change between them, which can be regarded as the coupling state of the abnormal jump and instability of the magnetic stirrer 7 being more significant up to the to-be-tested period, so the DTW distance is negatively correlated and normalized to correct the logical relationship, and the first jump coupling factor of the magnetic stirrer 7 in the to-be-tested period is obtained, the greater the first jump coupling factor, the higher the change synchronism between the abnormal jump feature sequence and the instability evaluation feature sequence, the more serious the coupling state, and the higher the possibility of the high-frequency jitter of the magnetic stirrer 7 and the decline of the speed control accuracy. The negative correlation and normalization processing can be performed by the formula wherein, represents the exponential function with the natural constant e as the base, and x represents the independent variable.

[0098] It should be noted that the calculation of the DTW distance is a known technology, and the specific process is not described here.

[0099] Step S402: The abnormal jump feature value and the instability evaluation value in the to-be-tested period are fused to determine the second jump coupling factor of the magnetic stirrer in the to-be-tested period.

[0100] Based on the analysis in steps S2 and S3, when the abnormal jumping characteristic value and the instability evaluation value are both at a high level, it indicates that the magnetic stirring sub 7 is more likely to be in a high-frequency jitter state in the historical sampling period, and the stirring speed needs to be timely controlled and adjusted. Therefore, the product of the abnormal jumping characteristic value and the instability evaluation value of the magnetic stirring sub 7 in the to-be-tested period after normalization is taken as the second jumping coupling factor of the magnetic stirring sub 7 in the to-be-tested period. The larger the second coupling factor is, the greater the impact on the magnetic stirring sub 7 in the historical sampling period is, the worse the running state is, and the higher the possibility of abnormal jumping is. The normalization is a technique familiar to those skilled in the art, and the selection of the normalization function can be linear normalization or standard normalization, and the specific normalization method is not limited here.

[0101] Step S403: obtaining the jumping coupling degree of the magnetic stirring sub in the to-be-tested period according to the first jumping coupling factor and the second jumping coupling factor corresponding to the to-be-tested period.

[0102] Based on the analysis in steps S401 and S402, the first jumping coupling factor and the second jumping coupling factor corresponding to the to-be-tested period are positively correlated with the possibility of abnormal jumping of the magnetic stirring sub 7 in the to-be-tested period. Therefore, the sum of the first jumping coupling factor and the second jumping coupling factor of the magnetic stirring sub 7 in the to-be-tested period after normalization is taken as the jumping coupling degree of the magnetic stirring sub 7 in the to-be-tested period. The jumping coupling degree reflects the coupling between the abnormal jumping characteristic and the control instability characteristic of the magnetic stirring sub 7. The larger the jumping coupling degree is, the more significant the coupling between the abnormal jumping characteristic and the control instability characteristic is, indicating that the magnetic stirring sub 7 is more likely to collide with the sample barrel wall in the to-be-tested period. Therefore, in order to avoid causing the magnetic stirring sub 7 to appear high-frequency jitter or even causing the oil field test sample to fluctuate violently, it is necessary to timely adjust the stirring speed of the magnetic stirring sub 7 to ensure the stability of the rotation of the magnetic stirring sub 7.

[0103] The jumping coupling degree is an important indicator for measuring the running state of the magnetic stirring sub 7. Therefore, the expected stirring speed of the magnetic stirring sub 7 in the current sampling period can be determined based on the numerical characteristics of the jumping coupling degree of the magnetic stirring sub 7 in the historical sampling period, the preset stirring speed, and the stirring speed time sequence data corresponding to the historical sampling period.

[0104] Preferably, the method for obtaining the expected stirring speed in an embodiment of the present application comprises:

[0105] In terms of time sequence, the last historical sampling period is taken as the comparison period because it is closest to the current time.

[0106] The mean value of the stirring speed at all time points in the stirring speed time sequence data of the comparison period is taken as a reference value, which provides a reference adjustment range for subsequent stirring speed adjustment and reflects the approximate running speed characteristics of the stirrer in the historical sampling period closest to the current sampling period.

[0107] Then, the difference between the jump coupling degree of the comparison period and the adjacent previous historical sampling period is calculated. If the difference is positive, it indicates that the jump coupling degree of the comparison period is higher than that of the previous historical sampling period, and the rotational stability of the magnetic stirrer 7 is poorer, so the stirring speed of the magnetic stirrer 7 in the current sampling period needs to be appropriately reduced to avoid more serious high-frequency jitter. Conversely, if the difference is negative, it indicates that the jump coupling degree of the comparison period is lower than that of the previous historical sampling period, and the rotational stability of the magnetic stirrer 7 in the comparison period is better, so the stirring speed of the magnetic stirrer 7 in the current sampling period can be appropriately increased to improve the uniformity of the internal temperature transfer of the oilfield test sample. Therefore, the product of the difference, the preset adjustment coefficient, and the reference value is taken as the stirring speed adjustment value. Based on the foregoing logic, the stirring speed adjustment value is positive, indicating that the stirring speed needs to be reduced, and the stirring speed adjustment value is negative, indicating that the stirring speed needs to be increased. The absolute value is the adjustment amount of the stirring speed.

[0108] It should be noted that the preset adjustment coefficient is used to avoid excessive or insufficient adjustment of the stirring speed. The value range can be set to 0.1-0.2, and the value of the embodiment of the present application can be 0.15.

[0109] Therefore, the difference between the reference value and the stirring speed adjustment value is taken as the first stirring speed candidate value, which is the stirring speed after preliminary adjustment. In actual production, excessively low stirring speed can lead to insufficient stirring, affecting quality and efficiency. The preset minimum stirring speed is the lowest limit to ensure that the stirring process can proceed normally. Therefore, the maximum value between the first stirring speed candidate value and the preset minimum stirring speed is taken as the second stirring speed candidate value, which can effectively avoid excessively small final stirring speed.

[0110] Further, the preset maximum stirring speed reflects the highest limit for the stirring process to proceed normally. Exceeding this value can cause safety problems such as equipment damage, stirrer falling off, and splashing of stirring medium. Therefore, the minimum value between the second stirring speed candidate value and the preset maximum stirring speed is taken as the expected stirring speed of the magnetic stirrer 7 in the current sampling period. The expected stirring speed obtained at this time can ensure that the stirring speed in the current sampling period is within a reasonable range and can avoid high-frequency jitter of the magnetic stirrer 7, better adapting to the current operating state.

[0111] It should be noted that the preset minimum stirring speed and the preset maximum stirring speed can be set and adjusted according to the requirements of the implementation scene, and in this embodiment of the application, the preset minimum stirring speed and the preset maximum stirring speed are respectively taken as the empirical values of 500 rpm / min and 1000 rpm / min.

[0112] After obtaining the expected stirring speed in the current sampling period, the stirring speed of the magnetic stirrer 7 can be adjusted by the stirring speed control module, so as to accurately control the stirring speed thereof.

[0113] In summary, in the process of magnetic stirring of oilfield test samples, the time sequence data of the vibration intensity and the stirring speed of the magnetic stirrer in multiple historical sampling periods are obtained. Generally, if the magnetic stirrer of the magnetic stirring device abnormally jumps, the vibration intensity of the magnetic stirrer will have a significant high-frequency abnormal change, so the time sequence data of the vibration intensity of each historical sampling period is analyzed in the frequency domain, and the difference characteristics between the frequencies corresponding to different energy values and the numerical characteristics of the energy values are analyzed to determine the abnormal jumping characteristic value, so as to accurately identify the abnormal jumping of the stirrer in the stirring process. Further, the higher the degree of change of the stirring speed of the magnetic stirrer and the stronger the irregularity, the worse the control effect of the stirring speed of the magnetic stirrer, so the change characteristics and the degree of confusion of the stirring speed time sequence data in each historical sampling period are analyzed to determine the instability evaluation value of the magnetic stirrer in each sampling period. This evaluation method can quantify the stability degree of the stirrer in the stirring process. Then, the abnormal jumping characteristic value and the instability evaluation value of the magnetic stirrer are comprehensively analyzed, and the change synchronism between the historical sampling periods is analyzed, so as to determine the jumping coupling degree of the magnetic stirrer in the historical sampling period. This step can further explore the internal relationship between the abnormal jumping and the instability of the stirrer. Finally, according to the numerical characteristics of the jumping coupling degree of the magnetic stirrer in the historical sampling period, the preset stirring speed and the stirring speed time sequence data corresponding to the historical sampling period, the expected stirring speed of the magnetic stirrer in the current sampling period is determined. The expected stirring speed determined based on the comprehensive analysis of multiple factors can avoid the abnormal situation such as high-frequency jitter of the stirrer caused by unreasonable stirring speed, so as to effectively ensure the stable operation of the magnetic stirring equipment.

[0114] It should be noted that the above-mentioned embodiment sequence of the application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or may be advantageous.

[0115] The various embodiments described in this specification are presented by way of example, and each embodiment is not inherently more important than any other embodiment.

Claims

1. A method for magnetically stirring oilfield laboratory samples with intelligent temperature control, characterized in that, The method includes: During the magnetic stirring of oilfield test samples, time-series data of vibration intensity and stirring speed of the magnetic stirrer were obtained in multiple historical sampling periods. Frequency domain analysis was performed on the vibration intensity time series data for each historical sampling period to analyze the difference characteristics between frequencies corresponding to different energy values ​​and the numerical characteristics of energy values, and to determine the abnormal jumping characteristic value of the magnetic stirrer in each historical sampling period. Within each historical sampling period, the variation characteristics and disorder of the stirring speed time series data are analyzed to determine the instability assessment value of the magnetic stirrer in each sampling period; Within the historical sampling period, the abnormal jumping characteristic value and instability assessment value of the magnetic stirrer are combined and their changes are analyzed to determine the jumping coupling degree of the magnetic stirrer under the historical sampling period. Based on the numerical characteristics of the jumping coupling degree of the magnetic stirrer under the historical sampling period, the preset stirring speed, and the stirring speed time series data corresponding to the historical sampling period, the expected stirring speed of the magnetic stirrer under the current sampling period is determined.

2. The method for intelligent temperature-controlled magnetic stirring of oilfield test samples according to claim 1, characterized in that, The method for obtaining the abnormal fluctuation feature value includes: Within each historical sampling period, the vibration intensity time series data are analyzed in the frequency domain using Fast Fourier Transform to obtain the energy spectrum; In the energy spectrum corresponding to each historical sampling period, the differences in the frequencies of different energy values ​​are compared to determine the high-frequency coefficient of the magnetic stir bar in each historical sampling period. In the energy spectrum corresponding to each historical sampling period, the numerical difference characteristics of energy values ​​between different frequencies are analyzed to determine the jumping energy ratio factor of the magnetic stirrer in each historical sampling period. The sum of the high-frequency jumping coefficient and the jumping energy ratio factor corresponding to each historical sampling period is normalized and used as the abnormal jumping characteristic value of the magnetic stirrer in each historical sampling period.

3. The method for intelligent temperature-controlled magnetic stirring of oilfield test samples according to claim 2, characterized in that, The method for obtaining the high-frequency coefficient of the jumping motion includes: In the energy spectrum, the ratio of the maximum frequency value with a non-zero energy value to the fundamental frequency is used as the high-frequency coefficient of the magnetic stirrer in each historical sampling period.

4. The method for intelligent temperature-controlled magnetic stirring of oilfield test samples according to claim 2, characterized in that, The method for obtaining the jumping energy proportion factor includes: In the energy spectrum of each historical sampling period, the sum of the energy values ​​corresponding to all frequencies greater than the fundamental frequency, and the ratio of the energy value of the fundamental frequency, are used as the jumping energy ratio factor of the magnetic stirrer in each historical sampling period.

5. The method for intelligent temperature-controlled magnetic stirring of oilfield test samples according to claim 1, characterized in that, The method for obtaining the instability assessment value includes: Within each historical sampling period, the variation characteristics of stirring speed between adjacent sampling times in the stirring speed time series data are analyzed to determine the drastic change factor corresponding to each sampling time. The permutation entropy of the drastic change factors at all sampling moments in each historical sampling period is used as the disorder level value, and the drastic change factors and values ​​at all sampling moments in each historical sampling period are used as the drastic change level value. The normalized sum of the disorder level value and the drastic change value corresponding to each historical sampling period is used as the instability assessment value of the magnetic stirrer in each historical sampling period.

6. The method for intelligent temperature-controlled magnetic stirring of oilfield test samples according to claim 5, characterized in that, The method for obtaining the drastic change factor includes: In the time series data of stirring speed in each historical sampling period, a sampling time is randomly selected as the time to be measured. The absolute value of the difference between the stirring speed of the sampling time to be measured and the stirring speed of the adjacent previous sampling time is calculated as the drastic change factor of the sampling time to be measured. The drastic change factor of the first sampling time is a preset value.

7. The method for intelligent temperature-controlled magnetic stirring of oilfield test samples according to claim 1, characterized in that, The method for obtaining the jump coupling degree includes: In terms of timing, the last two historical sampling periods are taken as the test periods respectively; The abnormal jumping feature values ​​of the magnetic stirrer in all historical sampling periods before the period to be tested are arranged in time sequence to obtain the abnormal jumping feature sequence; The instability assessment values ​​of the magnetic stirrer under all historical sampling periods of the test period are arranged in time sequence to obtain the instability assessment characteristic sequence; The synchronization of changes between the abnormal jumping characteristic sequence and the instability assessment characteristic sequence of the test period is analyzed to determine the first jumping coupling factor of the magnetic stirrer under the test period. The normalized product of the abnormal jumping characteristic value and the instability evaluation value of the magnetic stirrer under the test period is used as the second jumping coupling factor of the magnetic stirrer under the test period. The normalized sum of the first and second jumping coupling factors of the magnetic stirrer under the test period is taken as the jumping coupling degree of the magnetic stirrer under the test period.

8. The method for intelligent temperature-controlled magnetic stirring of oilfield test samples according to claim 7, characterized in that, The method for obtaining the first jitter coupling factor includes: The DTW distance between the abnormal jumping feature sequence and the instability assessment feature sequence is calculated, and negative correlation mapping and normalization are performed to obtain the first jumping coupling factor of the magnetic stirrer under the test period.

9. The method for intelligent temperature-controlled magnetic stirring of oilfield test samples according to claim 1, characterized in that, The method for obtaining the desired stirring speed includes: In terms of timing, the last historical sampling period is used as the comparison period; The average stirring speed at all times in the time series data of the stirring speed of the comparison period is used as the baseline value; The product of the difference in the jump coupling degree between the comparison period and the adjacent previous historical sampling period, the preset adjustment coefficient, and the reference value is used as the stirring speed adjustment value. The difference between the baseline value and the stirring speed adjustment value is used as the first stirring speed candidate value, and the maximum value between the first stirring speed candidate value and the preset minimum stirring speed is used as the second stirring speed candidate value. The minimum value between the second candidate stirring speed and the preset maximum stirring speed is taken as the expected stirring speed of the magnetic stirrer in the current sampling period.

10. A smart temperature-controlled magnetic stirring device for oilfield laboratory samples, comprising a smart temperature-controlled magnetic stirring device body and a stirring speed control module, characterized in that, The stirring speed control module includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. When the processor loads and executes the at least one instruction, at least one program, code set, or instruction set, it implements the steps of the intelligent temperature-controlled magnetic stirring method for oilfield test samples as described in any one of claims 1-9.

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