Distributed intelligent logging system and logging method

Abstract

The invention discloses a distributed intelligent well logging system and method, and relates to the technical field of intelligent well logging, the system comprises a winch control module, an environment analysis module, a tension analysis module, an assembly control module and a safety early warning module.The method includes the steps that firstly, the winch control module collects basic data in a well, and a winch basic control scheme is set; secondly, analyzing the environment data through an environment analysis module to obtain a winch correction control scheme; the tension analysis module is used for setting a rope control scheme according to analyzed rope tension data; the component control module analyzes distributed component measurement data and sets a component sensor control scheme; and finally, the scheme is analyzed, controlled, changed and pre-warned through a safety pre-warning module, the specific analysis and scheme setting process of each module relates to various data analysis and is used for accurately controlling operation of a winch and assemblies, and the logging safety and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent well logging, and in particular to a distributed intelligent well logging system and a well logging method. Background Art

[0002] As oil and gas exploration and development move towards more complex formations, the requirements for logging data accuracy are unprecedentedly improved. Therefore, a distributed intelligent logging system and logging method are needed.

[0003] In traditional logging processes, the control of the drawworks often relies on experience and simple parameter settings, lacking precise analysis of the complex well environment. Factors such as changes in well diameter, well inclination, and azimuth angle will affect the operation of the drawworks. However, traditional methods make it difficult to adjust the drawworks' operating parameters in real time based on these factors, resulting in limited measurement accuracy and an inability to accurately obtain well data.

[0004] Well logging operations are often conducted in complex geological environments, where environmental factors such as lithology, temperature, formation porosity, permeability, and formation pressure vary significantly across different monitoring layers. Traditional logging systems cannot adapt well to these environmental variations and are unable to modify drawworks control schemes based on environmental data, thus affecting measurement accuracy and efficiency.

[0005] During the logging process, rope tension changes are a key factor. Traditional systems find it difficult to accurately monitor the rope tension value, tension change rate, and tension fluctuation index in real time. When the rope tension is abnormal, it cannot be adjusted in a timely and effective manner, which may lead to rope damage, measuring instrument failure, and other problems, affecting the smooth progress of logging operations. Summary of the Invention

[0006] In view of the above-mentioned technical deficiencies, the present invention aims to provide a distributed intelligent well logging system and a well logging method.

[0007] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a distributed intelligent logging system, comprising the following modules: a winch control module, for collecting basic data in the well, analyzing the basic data in the well, and setting a basic winch control solution.

[0008] The environmental analysis module is used to collect environmental data, analyze the environmental data based on the basic winch control plan, and obtain the winch correction control plan.

[0009] The tension analysis module is used to collect rope tension data, analyze the rope tension data based on the winch correction control plan, and set the rope control plan.

[0010] The component control module is used to collect the measurement data of each distributed component, analyze the measurement data of each distributed component, and set the component sensor control plan.

[0011] The safety warning module is used to collect control change data according to the winch basic control plan, winch correction control plan, rope control plan and component sensor control plan, analyze the control change data and issue warnings.

[0012] Preferably, the described winch basic control scheme is set up, and the specific setting process is as follows: the basic data in the well include the well diameter change rate, well diameter change degree index, well diameter ellipticity, well inclination and azimuth of each monitoring layer. If the well inclination change index of a certain monitoring layer is equal to the well inclination change interval of a certain movement direction and the azimuth change index belongs to the azimuth change index interval of the movement direction, it indicates that the monitoring layer is in the movement direction.

[0013] The wellbore change rate, wellbore change degree index and wellbore ellipticity of each monitoring layer are substituted into the calculation formula of the measurement displacement safety index to obtain the measurement displacement safety index of each monitoring layer. The descent speed corresponding to each measurement displacement safety index is obtained from the database, and then the descent speed of each monitoring layer is obtained. The movement direction and descent speed of each monitoring layer are used to obtain the rope movement speed of each monitoring layer of the winch through the cosine trigonometric function relationship, and then the rope movement speed difference of each monitoring layer of the winch is obtained. The quadrature-axis current given value corresponding to each speed difference is obtained from the database, and then the basic quadrature-axis current given value of each monitoring layer of the winch is obtained. The basic control scheme of the winch is: when the logging platform reaches the monitoring area of each monitoring layer, the magnitude of the quadrature-axis current is changed to the corresponding basic quadrature-axis current given value.

[0014] On the other hand, the present invention provides a distributed intelligent logging method, comprising the following steps: Step 1, winch control: collecting basic data in the well, analyzing the basic data in the well, and setting a basic winch control scheme.

[0015] Step 2: Environmental analysis: Collect environmental data, analyze the environmental data based on the basic winch control plan, and obtain the winch correction control plan.

[0016] Step 3: Tension analysis: Collect rope tension data, analyze the rope tension data based on the winch correction control plan, and set the rope control plan.

[0017] Step 4: Component control: Collect measurement data of each distributed component, analyze the measurement data of each distributed component, and set up component sensor control scheme.

[0018] Step 5. Safety warning: Collect control change data, which is used to collect control change data according to the winch basic control plan, winch correction control plan, rope control plan and component sensor control plan, analyze the control change data and issue warnings.

[0019] The beneficial effects of the present invention are: 1. First, the winch control module of the present invention collects basic data in the well and sets the basic winch control plan; secondly, the environmental analysis module analyzes the environmental data to obtain the winch correction control plan; the tension analysis module sets the rope control plan based on the analyzed rope tension data; the component control module analyzes the distributed component measurement data and sets the component sensor control plan; finally, the safety warning module analyzes the above-mentioned plan to change the control data and issue an early warning. The specific analysis and plan setting process of each module involves multiple data analyses, which are used to accurately control the operation of the winch and components, and improve the safety and accuracy of well logging.

[0020] 2. The present invention can control the quadrature-axis current based on the well diameter change and angle change data and on the basis of logging safety, thereby adjusting the motor output torque by controlling the quadrature-axis current, and then controlling the winch speed and winch acceleration of the logging device according to the basic power supply frequency, thereby reducing the safety of the movement of the logging device. At the same time, the detection accuracy is evaluated based on the rock formation environmental data of the set area, thereby ensuring the detection accuracy by controlling the power supply frequency, and controlling the winch speed of the logging device through the control systems at both ends of the motor, thereby improving the safety of the measurement process and increasing the validity of the measurement data.

[0021] 3. The present invention uses a rope tension feedback control model to monitor the rope tension value, tension change rate, and tension fluctuation index in real time. Once abnormal rope expansion and contraction tension is detected, the quadrature-axis current, power supply frequency, and control correction parameters can be quickly adjusted based on the output results to prevent equipment failures caused by rope tension problems, extend equipment service life, and ensure the continuity of logging operations. At the same time, potential safety hazards such as rope breakage and over-stretching can be prevented in advance, underground accidents caused by equipment failure can be avoided, personnel safety can be protected, and economic losses can be reduced.

[0022] 4. The present invention integrates multi-dimensional control to change data, conducts measurement warnings, stops winch movement and issues warnings, and provides all-round, multi-level safety protection for logging operations. It can detect and respond to potential safety risks in the early stages of the system, avoid further expansion of safety hazards, effectively reduce the probability of safety accidents, and improve the safety of logging operations in a safe environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0025] Figure 2 The figure is a schematic flow chart of the steps for implementing the method of the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] according to Figure 1 As shown, the present invention provides a distributed intelligent logging system, which includes the following modules: a drawworks control module, an environmental analysis module, a tension analysis module, a component control module, a safety warning module and a database.

[0028] The environmental analysis module is connected to the winch control module and the tension analysis module respectively, the component control module is connected to the tension analysis module and the safety warning module respectively, and the winch control module, environmental analysis module, tension analysis module, component control module, and safety warning module are all connected to the database.

[0029] The winch control module is used to collect basic data in the well, analyze the basic data in the well, and set the basic winch control plan.

[0030] In a specific embodiment, the basic data in the well is collected, and the specific collection process is as follows: the basic data in the well includes the well diameter change rate, well diameter change degree index, well diameter ellipticity, well inclination and azimuth of each monitoring layer. The well diameters in each direction of each monitoring layer are collected by an ultrasonic well diameter sensor, and the average value is calculated to obtain the average well diameter of each monitoring layer. The difference between the average well diameter of the current monitoring layer and the average well diameter of the previous monitoring layer is subtracted and divided by the depth difference between the monitoring layers to obtain the well diameter change rate of the current monitoring layer, thereby obtaining the well diameter change rate of each monitoring layer.

[0031] If the well diameter of the current monitoring layer is greater than or equal to the well diameter of the previous monitoring layer, the difference between the maximum well diameter of the current monitoring layer and the average well diameter is divided by the average well diameter to obtain the well diameter change index of the current monitoring layer. If the well diameter of the current monitoring layer is smaller than the well diameter of the previous monitoring layer, the difference between the average well diameter and the minimum well diameter of the current monitoring layer is divided by the average well diameter to obtain the well diameter change index of the current monitoring layer. In this way, the well diameter change index of each monitoring layer is obtained, and the difference between the maximum well diameter and the minimum well diameter of each monitoring layer is divided by the average well diameter to obtain the well diameter ellipticity of each monitoring layer.

[0032] The well inclination angle of each monitoring layer is collected by a fluxgate sensor, and the azimuth angle of each monitoring layer is collected by an accelerometer.

[0033] In a specific embodiment, the described winch basic control scheme is set up, and the specific setting process is as follows: if the well inclination angle change index of a certain monitoring layer is equal to the well inclination angle change range of a certain movement direction and the azimuth angle change index belongs to the azimuth angle change index range of the movement direction, it indicates that the monitoring layer is the movement direction.

[0034] It should be noted that if the movement direction angle corresponding to the well inclination angle change index is different from the movement direction angle corresponding to the azimuth angle change index, if the difference between the movement direction angle corresponding to the well inclination angle change index and the movement direction angle corresponding to the azimuth angle change index is greater than the preset movement direction angle difference, the maximum movement direction angle is selected as the corresponding movement direction angle; if the difference between the movement direction angle corresponding to the well inclination angle change index and the movement direction angle corresponding to the azimuth angle change index is less than or equal to the preset movement direction angle difference, the average of the movement direction angle corresponding to the well inclination angle change index and the movement direction angle corresponding to the azimuth angle change index is selected as the preset movement direction angle.

[0035] The preset movement direction angle difference is set by the staff.

[0036] The wellbore change rate, wellbore change degree index and wellbore ellipticity of each monitoring layer are substituted into the calculation formula of the measurement displacement safety index to obtain the measurement displacement safety index of each monitoring layer. The descent speed corresponding to each measurement displacement safety index is obtained from the database, and then the descent speed of each monitoring layer is obtained. The movement direction and descent speed of each monitoring layer are used to obtain the rope movement speed of each monitoring layer of the winch through the cosine trigonometric function relationship, and then the rope movement speed difference of each monitoring layer of the winch is obtained. The quadrature-axis current given value corresponding to each speed difference is obtained from the database, and then the basic quadrature-axis current given value of each monitoring layer of the winch is obtained. The basic control scheme of the winch is: when the logging platform reaches the monitoring area of each monitoring layer, the magnitude of the quadrature-axis current is changed to the corresponding basic quadrature-axis current given value.

[0037] It should be noted that the calculation formula for the measurement displacement safety index is: ,in, is the measurement displacement safety index of monitoring layer a, a is the monitoring layer number, and the value of a is a positive integer. 、 and are the wellbore change rate, wellbore change index and wellbore ellipticity of monitoring layer a respectively. 、 and They are standard well diameter change rate, standard well diameter change index and standard well diameter ellipticity, 、 and are the wellbore change rate weight factor, the wellbore change degree index weight factor and the wellbore ellipticity weight factor, respectively. , , , .

[0038] Standard parameters 、 and The well diameter change rate threshold, well diameter change index threshold and well diameter ellipticity threshold of the normal monitoring layer are shown in Figure 1. When the well diameter change rate, well diameter change index and well diameter ellipticity of the monitoring layer a are greater than the threshold, it indicates that the well diameter change of the monitoring layer a is abnormal, which increases the risk of rope movement. The specific values are set by the staff, for example 0.19, 0.39 and is 0.28, and the weight factor is 、 and Staff settings, specific values such as 0.2, is 0.2 and is 0.6.

[0039] The environmental analysis module is used to collect environmental data, analyze the environmental data based on the basic winch control plan, and obtain the winch correction control plan.

[0040] In a specific embodiment, the environmental data is collected, and the specific collection process is as follows: the environmental data includes the lithology correction index, temperature, formation porosity, permeability and formation pressure of each measuring point of each monitoring layer, the temperature of each measuring point of each monitoring layer is collected by a temperature sensor, the formation porosity of each measuring point of each monitoring layer is collected by a formation porosity sensor, the permeability of each measuring point of each monitoring layer is collected by a nuclear magnetic resonance permeability sensor, and the formation pressure of each measuring point of each monitoring layer is collected by a formation pressure sensor.

[0041] The rock images of each measuring point of each monitoring layer are collected by the camera, and the rock type of each measuring point of each monitoring layer is obtained by image recognition technology. The lithology correction index corresponding to each rock type is obtained from the database to obtain the lithology correction index of each measuring point of each monitoring layer.

[0042] In a specific embodiment, the environmental data is analyzed, and the specific analysis process is as follows: the lithology correction index, temperature, formation porosity, permeability and formation pressure of each measuring point of each monitoring layer are substituted into the measurement accuracy index calculation formula to obtain the measurement accuracy index of each measuring point of each monitoring layer, and the maximum measurement accuracy index of each measuring point is recorded as the measurement accuracy index corresponding to each monitoring layer, thereby obtaining the measurement accuracy index of each monitoring layer, and obtaining the measurement movement speed corresponding to each measurement accuracy index from the database, thereby obtaining the measurement movement speed of each monitoring layer.

[0043] It should be noted that the calculation formula of the measurement accuracy index is: ,in, is the measurement accuracy index of the measurement point b in the monitoring layer a, b is the number of the measurement point, 、 、 and are the lithology correction index, temperature, formation porosity, permeability and formation pressure of the measuring point b in the monitoring layer a, 、 、 and They are the preset standard temperature, standard formation porosity, standard permeability and standard formation pressure, 、 、 and are the preset temperature weight factor, formation porosity weight factor, permeability weight factor and formation pressure weight factor, respectively. , , , , .

[0044] Standard parameters 、 、 and The setup process and standard parameters The setup process is the same as for 1.3, 0.9, is 0.8 and is 0.56, the weight factor 、 、 and The setting process and weight factor The setup process is the same as for 0.3, 0.3, is 0.3 and is 0.1.

[0045] The power supply frequency corresponding to each measured moving speed is obtained from the database to obtain the corrected power supply frequency of each monitoring layer. The winch correction control scheme is: if the measured moving speed of a monitoring layer is greater than or equal to the rope movement speed, it indicates that the power supply frequency of the monitoring layer is the preset power supply frequency. If the measured moving speed of a monitoring layer is less than the rope movement speed, the power supply frequency of the monitoring layer is changed to the corrected power supply frequency.

[0046] It should be noted that, during power supply frequency control, the corrected power supply frequency is multiplied by the current control correction parameter for correction before control is performed.

[0047] The tension analysis module is used to collect rope tension data, analyze the rope tension data based on the winch correction control plan, and set the rope control plan.

[0048] In a specific embodiment, the rope tension data is collected, and the specific collection process is as follows: the rope tension value collected each time is collected by a strain gauge tension sensor, and then the current rope tension value is obtained.

[0049] The average value of the rope tension collected each time is calculated to obtain the average tension value. The difference between the current rope tension value and the average tension value is divided by the average tension value to obtain the current rope tension change rate. The rope tension values collected each time are differenced to obtain the rope tension difference of each time. If the rope tension difference of a certain collection is greater than the preset standard rope tension difference, the collection is recorded as a fluctuation collection, and the number of fluctuation collections is counted to obtain the number of fluctuation collections. The number of fluctuation collections is divided by the total number of collections to obtain the tension fluctuation index of the current rope.

[0050] It should be noted that the standard rope tension difference is the tension difference threshold during normal rope movement. When the rope tension difference is greater than the threshold, it indicates that the current rope tension has fluctuated to the point where it may cause a fault. The specific value is set by the staff.

[0051] In a specific embodiment, the rope tension data is analyzed, and the specific analysis process is as follows: the rope tension data includes the current rope tension value, tension change rate and tension fluctuation index, and the current rope tension value, tension change rate and tension fluctuation index are input into the rope tension feedback control model to obtain the output result of the current rope, and the output result value includes -1, 0 and 1.

[0052] If the output result is 0, it indicates that the current rope expansion and contraction tension is normal. If the output result is not 0, it indicates that the current rope expansion and contraction tension is abnormal, and rope control is performed. The rope control scheme is: when the output result is -1, the quadrature-axis current of the standard unit is increased, the power supply frequency of the standard unit is increased, and the control correction parameter of the preset value is increased. When the output result is 1, the quadrature-axis current of the standard unit is reduced, the power supply frequency of the standard unit is reduced, and the control correction parameter of the preset value is reduced.

[0053] It should be noted that the power supply frequency of the standard unit, the quadrature-axis current of the standard unit and the control correction parameters for increasing the preset values are preset by the staff.

[0054] In a specific embodiment, the rope tension feedback control model expression is: ,in, To output the results, A, B and C are the current rope tension value, tension change rate and tension fluctuation index respectively. is the preset standard rope tension range, and are the lower and upper limits of the standard rope tension range, respectively. and They are the preset standard tension change rate and standard tension fluctuation index respectively.

[0055] It should be noted that the tension values of abnormal expansion and contraction tension in the database are summarized to obtain the standard rope tension range , and They are the lower and upper thresholds of the standard rope tension range, respectively. The specific values are as follows: 0.18 and is 0.39, standard parameters and They are the tension change rate threshold and the tension fluctuation index threshold, and the specific values are set by the staff, for example 1.2 and is 1.1.

[0056] The component control module is used to collect the measurement data of each distributed component, analyze the measurement data of each distributed component, and set the component sensor control plan.

[0057] In a specific embodiment, the measurement data of each distributed component is collected, and the specific collection process is as follows: the measurement data of each distributed component is the type of each component and the corresponding measurement value collected each time. After each collection, the measurement value of the sensor of each component is uploaded to obtain the measurement value collected each time of each component, and the type of each component is obtained from the database.

[0058] In a specific embodiment, the measurement data of each distributed component is analyzed, and the specific analysis process is as follows: the measurement data of each distributed component is the type of each component and the corresponding measurement value collected each time. Each component is summarized according to the corresponding type to obtain the measurement value collected each time corresponding to each type of distributed component, and the average value is calculated to obtain the average measurement value collected each time for each type of distributed component.

[0059] Based on the average measurement value collected each time for each type of distributed component, the deviation of the measurement value collected each time corresponding to each component of each type of distributed component is calculated to obtain the measurement deviation of each collection corresponding to each component of each type of distributed component. In this way, the measurement deviation of each component collected each time is obtained. The measurement deviation of each component collected each time is fitted with the descent distance interval of each collection as the unit to obtain the curve of the measurement deviation of each component changing with the descent distance, which is recorded as the measurement deviation change curve of each component.

[0060] It should be noted that the deviation calculation process is: subtract the absolute value of the difference between the measurement values of each collection corresponding to each component of each distributed component and the measurement average value, and divide it by the measurement average value to obtain the measurement deviation of each collection corresponding to each component of each distributed component.

[0061] The image slope of each component collected each time is extracted from the measurement deviation change curve of each component through image recognition technology, and the displacement value fluctuation rate corresponding to each image slope is obtained from the database, thereby obtaining the displacement value fluctuation rate of each component collected each time.

[0062] The measurement deviation and displacement value fluctuation rate of each component collected each time are respectively substituted into the component measurement data anomaly index calculation formula and the depth measurement data anomaly index calculation formula to obtain the component measurement data anomaly index of each component and the depth measurement data anomaly index of each collection. The depth of each collection is obtained through the database to obtain the depth measurement data anomaly index of each depth.

[0063] It should be noted that the calculation formula for the component measurement data anomaly index is: ,in, is the component measurement data anomaly index of component c, where c is the number of each component, , , the value of n is the total number of components, and are the measurement deviation and displacement fluctuation rate of component c collected d times, d is the number of each collection, , , the value of m is the total number of acquisitions, and are the standard measurement deviation and standard displacement numerical fluctuation rate, and are the measurement deviation weight factor and displacement value volatility weight factor, respectively. , , , is the weight factor of the preset d acquisitions, , .

[0064] Standard parameters and The setup process and standard parameters The setup process is the same as for 1.57 and is 0.6, the weight factor 、 and The setting process and weight factor The setup process is the same as for 0.4, is 0.6 and is 0.1.

[0065] The calculation formula for the depth measurement data anomaly index is: ,in, is the abnormal index of the depth measurement data collected d times, is the weight factor of component c, , .

[0066] Weighting Factor The setting process and weight factor The setup process is the same as for is 0.16.

[0067] In a specific embodiment, the component sensor control scheme is set up, and the specific setting process is as follows: If the component measurement data anomaly index of a component is greater than the standard component measurement data anomaly index, replace the component measurement device of the component; if the depth measurement data anomaly index of a certain depth is greater than the standard depth measurement data anomaly index, record it as an abnormal depth, thereby obtaining each abnormal depth, increase the number of measurements of each abnormal depth and each measurement point by a preset unit number, collect the data of each measurement of each component at each measurement point at each abnormal depth, filter out the data of each normal measurement of each component at each measurement point at each abnormal depth through the interquartile range method, calculate the average value to obtain the mean measurement data of each component at each measurement point at each abnormal depth, and record it as the measurement data of each component at each measurement point at each abnormal depth.

[0068] It should be noted that the standard component measurement data anomaly index is the component measurement data anomaly index threshold of a normal component. When the component measurement data anomaly index is greater than the threshold, it indicates that the corresponding component is prone to failure. The standard depth measurement data anomaly index is the depth measurement data anomaly index threshold during normal measurement. When the depth measurement data anomaly index is greater than the threshold, it indicates that errors are prone to occur in the corresponding depth analysis and more data is needed. The interquartile range method is a method in descriptive statistics and is an existing technology. It can be specifically queried on the Internet and will not be repeated here.

[0069] The safety warning module is used to collect control change data according to the winch basic control plan, winch correction control plan, rope control plan and component sensor control plan, analyze the control change data and issue warnings.

[0070] In a specific embodiment, the specific collection process of the control change data is as follows: the control change data includes the basic winch control times, the winch correction control times, the rope control times and the component measuring device replacement times within a preset time period. When the cross-axis current changes, the basic winch control times are recorded to obtain the basic winch control times within the preset time period. When the power supply frequency changes, the winch correction control times are recorded to obtain the winch correction control times within the preset time period. When the output result of the rope tension feedback control model is not 0, the rope control times are recorded to obtain the rope control times within the preset time period. When the component measuring device is replaced, the component measuring device replacement times are recorded to obtain the component measuring device replacement times within the preset time period.

[0071] In a specific embodiment, the control change data is analyzed, and the specific analysis process is as follows: the number of basic winch controls, winch correction controls, rope controls and component measurement device replacements within a preset time period are substituted into the measurement warning index calculation formula to obtain the measurement warning index within the preset time period. If the measurement warning index within the preset time period is greater than the preset standard measurement warning index, the winch movement is stopped and an early warning is issued.

[0072] It should be noted that the calculation formula for the measurement early warning index is: , in, To measure the early warning index, 、 、 and They are the number of winch basic control times, winch correction control times, rope control times and component measurement device replacement times, 、 、 and They are the preset standard winch basic control times, standard winch correction control times, standard rope control times and standard component measuring device replacement times. 、 、 and They are the preset winch basic control times weight factor, winch correction control times weight factor, rope control times weight factor and component measurement device replacement times weight factor, , , , , .

[0073] Standard parameters 、 、 and The setup process and standard parameters The setup process is the same as for 1.5, 1.7, 1.7 and The weight factor is 0.67. 、 、 and The setting process and weight factor The setup process is the same as for 0.2, 0.3, is 0.3 and is 0.2.

[0074] The standard measurement warning index is the measurement warning index threshold during normal measurement. When the measurement warning index is greater than the threshold, it indicates that the current measurement is inefficient due to dangerousness and low accuracy. The specific value is set by the staff.

[0075] The database is used to store the descent speed corresponding to each measured displacement safety index, the quadrature-axis current set value corresponding to each speed difference, the measured moving speed corresponding to each measurement accuracy index, the power supply frequency corresponding to each measured moving speed, the displacement value fluctuation rate corresponding to each image slope, and the depth of each acquisition.

[0076] according to Figure 2 As shown, the present invention provides a distributed intelligent logging method, comprising the following steps: Step 1, winch control: collecting basic data in the well, analyzing the basic data in the well, and setting a basic winch control scheme.

[0077] Step 2: Environmental analysis: Collect environmental data, analyze the environmental data based on the basic winch control plan, and obtain the winch correction control plan.

[0078] Step 3: Tension analysis: Collect rope tension data, analyze the rope tension data based on the winch correction control plan, and set the rope control plan.

[0079] Step 4: Component control: Collect measurement data of each distributed component, analyze the measurement data of each distributed component, and set up component sensor control scheme.

[0080] Step 5. Safety warning: Collect control change data, which is used to collect control change data according to the winch basic control plan, winch correction control plan, rope control plan and component sensor control plan, analyze the control change data and issue warnings.

[0081] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. A distributed intelligent well logging system, characterized in that: Includes the following modules: The winch control module is used to collect and analyze the basic data in the well and set the basic control plan for the winch; Environmental analysis module, used to collect environmental data, analyze the environmental data based on the basic winch control plan, and obtain the winch correction control plan; The tension analysis module is used to collect rope tension data, analyze the rope tension data and set the rope control plan based on the winch correction control plan; The component control module is used to collect the measurement data of each distributed component, analyze the measurement data of each distributed component, and set the component sensor control plan; The safety warning module is used to collect control change data according to the winch basic control plan, winch correction control plan, rope control plan and component sensor control plan, analyze the control change data and issue warnings.

2. A distributed intelligent well logging system according to claim 1, characterized in that: The specific setting process of setting the basic winch control scheme is as follows: The basic data in the well include the well diameter change rate, well diameter change degree index, well diameter ellipticity, well inclination and azimuth of each monitoring layer. If the well inclination change index of a monitoring layer is equal to the well inclination change interval of a certain movement direction and the azimuth change index belongs to the azimuth change index interval of the movement direction, it indicates that the monitoring layer is moving in this direction; The wellbore change rate, wellbore change degree index and wellbore ellipticity of each monitoring layer are substituted into the calculation formula of the measurement displacement safety index to obtain the measurement displacement safety index of each monitoring layer. The descent speed corresponding to each measurement displacement safety index is obtained from the database, and then the descent speed of each monitoring layer is obtained. The movement direction and descent speed of each monitoring layer are used to obtain the rope movement speed of each monitoring layer of the winch through the cosine trigonometric function relationship, and then the rope movement speed difference of each monitoring layer of the winch is obtained. The quadrature-axis current given value corresponding to each speed difference is obtained from the database, and then the basic quadrature-axis current given value of each monitoring layer of the winch is obtained. The basic control scheme of the winch is: when the logging platform reaches the monitoring area of each monitoring layer, the magnitude of the quadrature-axis current is changed to the corresponding basic quadrature-axis current given value.

3. A distributed intelligent well logging system according to claim 2, characterized in that: The environmental data is analyzed, and the specific analysis process is as follows: The environmental data include the lithologic correction index, temperature, formation porosity, permeability and formation pressure of each measuring point of each monitoring layer. The lithologic correction index, temperature, formation porosity, permeability and formation pressure of each measuring point of each monitoring layer are substituted into the measurement accuracy index calculation formula to obtain the measurement accuracy index of each measuring point of each monitoring layer. The maximum measurement accuracy index of each measuring point is recorded as the measurement accuracy index of the corresponding monitoring layer to obtain the measurement accuracy index of each monitoring layer. The measurement movement speed corresponding to each measurement accuracy index is obtained from the database to obtain the measurement movement speed of each monitoring layer. The power supply frequency corresponding to each measured moving speed is obtained from the database to obtain the corrected power supply frequency of each monitoring layer. The winch correction control scheme is: if the measured moving speed of a monitoring layer is greater than or equal to the rope movement speed, it indicates that the power supply frequency of the monitoring layer is the preset power supply frequency. If the measured moving speed of a monitoring layer is less than the rope movement speed, the power supply frequency of the monitoring layer is changed to the corrected power supply frequency.

4. A distributed intelligent well logging system according to claim 3, characterized in that: The rope tension data is analyzed, and the specific analysis process is as follows: The rope tension data includes the current rope tension value, tension change rate and tension fluctuation index. The current rope tension value, tension change rate and tension fluctuation index are input into the rope tension feedback control model to obtain the output result of the current rope. The output result has the values of -1, 0 and 1. If the output result is 0, it indicates that the current rope expansion and contraction tension is normal. If the output result is not 0, it indicates that the current rope expansion and contraction tension is abnormal, and rope control is performed. The rope control scheme is: when the output result is -1, the quadrature-axis current of the standard unit is reduced, the power supply frequency of the standard unit is reduced, and the control correction parameter of the preset value is increased. When the output result is 1, the quadrature-axis current of the standard unit is increased, the power supply frequency of the standard unit is increased, and the control correction parameter of the preset value is reduced.

5. A distributed intelligent well logging system according to claim 4, characterized in that: The rope tension feedback control model expression is: ,in, To output the results, A, B and C are the current rope tension value, tension change rate and tension fluctuation index respectively. is the preset standard rope tension range, and are the lower and upper limits of the standard rope tension range, respectively. and They are the preset standard tension change rate and standard tension fluctuation index respectively.

6. A distributed intelligent well logging system according to claim 4, characterized in that: The measurement data of each distributed component is analyzed, and the specific analysis process is as follows: The measurement data of each distributed component is the type of each component and the corresponding measurement value collected each time. The components are summarized according to the corresponding type to obtain the measurement value collected each time corresponding to each type of distributed component. The average value is calculated to obtain the average measurement value collected each time for each type of distributed component. Based on the average measurement value collected each time by each type of distributed component, the deviation of the measurement value collected each time corresponding to each component of each type of distributed component is calculated to obtain the measurement deviation of each collection corresponding to each component of each type of distributed component. In this way, the measurement deviation of each collection of each component is obtained. The measurement deviation of each collection of each component is fitted with the descent distance interval of each collection as a unit to obtain a curve of the measurement deviation of each component changing with the descent distance, which is recorded as the measurement deviation change curve of each component; The image slope of each component collected at each time is extracted from the measurement deviation change curve of each component through image recognition technology, and the displacement value fluctuation rate corresponding to each image slope is obtained from the database, thereby obtaining the displacement value fluctuation rate of each component collected at each time; The measurement deviation and displacement value fluctuation rate of each component collected each time are respectively substituted into the component measurement data anomaly index calculation formula and the depth measurement data anomaly index calculation formula to obtain the component measurement data anomaly index of each component and the depth measurement data anomaly index of each collection. The depth of each collection is obtained through the database to obtain the depth measurement data anomaly index of each depth.

7. A distributed intelligent well logging system according to claim 6, characterized in that: The specific setting process of setting the component sensor control scheme is as follows: If the component measurement data anomaly index of a component is greater than the standard component measurement data anomaly index, replace the component measurement device of the component; if the depth measurement data anomaly index of a certain depth is greater than the standard depth measurement data anomaly index, record it as an abnormal depth, thereby obtaining each abnormal depth, increase the number of measurements of each abnormal depth and each measurement point by a preset unit number, collect the data of each measurement of each component at each measurement point at each abnormal depth, filter out the data of each normal measurement of each component at each measurement point at each abnormal depth through the interquartile range method, calculate the average value to obtain the mean measurement data of each component at each measurement point at each abnormal depth, and record it as the measurement data of each component at each measurement point at each abnormal depth.

8. A distributed intelligent well logging system according to claim 6, characterized in that: The control change data is analyzed, and the specific analysis process is as follows: The control change data includes the number of basic winch controls, winch correction controls, rope controls and component measuring device replacements within a preset time period. The basic winch controls, winch correction controls, rope controls and component measuring device replacements within the preset time period are substituted into the measurement warning index calculation formula to obtain the measurement warning index within the preset time period. If the measurement warning index within the preset time period is greater than the preset standard measurement warning index, the winch movement is stopped and an early warning is issued.

9. A distributed intelligent well logging system according to claim 1, characterized in that: It also includes a database for storing the descent speed corresponding to each measured displacement safety index, the cross-axis current set value corresponding to each speed difference, the measured moving speed corresponding to each measurement accuracy index, the power supply frequency corresponding to each measured moving speed, the displacement value fluctuation rate corresponding to each image slope, and the depth of each acquisition.

10. A well logging method using the distributed intelligent well logging system according to any one of claims 1 to 9, characterized in that: The steps include: Step 1: Winch control: Collect and analyze the basic data in the well and set up the basic control scheme for the winch; Step 2: Environmental analysis: Collect environmental data, analyze the environmental data based on the basic winch control plan, and obtain the winch correction control plan; Step 3: Tension analysis: Collect rope tension data, analyze the rope tension data based on the winch correction control plan, and set the rope control plan; Step 4: Component control: Collect measurement data from each distributed component, analyze the measurement data from each distributed component, and set up component sensor control schemes; Step 5. Safety warning: Collect control change data, which is used to collect control change data according to the winch basic control plan, winch correction control plan, rope control plan and component sensor control plan, analyze the control change data and issue warnings.

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