A remote data calibration method and system for a neutron measurement system

Abstract

The present application relates to the technical field of data processing and remote maintenance of oil logging instrument, and particularly relates to a remote data calibration method and system for a neutron measurement system. The method comprises the following steps: collecting multi-dimensional time sequence data of downhole instrument, and identifying the current temperature change state; based on the principle of non-steady-state heat conduction, the thermal hysteresis index is calculated by using the temperature change rate and the material thermal saturation limit constant; the real temperature of the crystal is reconstructed by using the thermal hysteresis index to inversely correct the measured temperature of the sensor; and based on the equivalent lattice temperature, the original energy spectrum characteristics are dynamically gain calibrated by using a preset quadratic polynomial multiplication compensation model. By reconstructing the real temperature of the crystal, the present application eliminates the gain hysteresis loop in the up-measuring and down-measuring processes, and significantly improves the interpretation accuracy and consistency of the logging data in a complex variable temperature environment.

Description

Technical Field

[0001] This invention relates to the field of data processing and remote maintenance technology for oil well logging instruments. More specifically, this invention relates to a remote data calibration method and system for neutron measurement systems. Background Technology

[0002] In the field of oil exploration and development, pulsed neutron logging is a core method for evaluating the remaining oil saturation of casing wells. These instruments are typically equipped with highly sensitive scintillation crystal detectors, such as bismuth germanate crystals or lanthanum bromide crystals. The photoelectric conversion efficiency, or light yield, of these crystals is extremely sensitive to temperature changes. As downhole temperature increases, the luminescence efficiency of the crystal decreases significantly, causing the energy spectrum peaks to shift towards lower energies, which in turn severely affects the accuracy of porosity and saturation calculations.

[0003] The currently accepted method for stabilizing and calibrating the spectrum is the static lookup table method. This involves installing a temperature sensor near the internal circuit board of the instrument, pre-determining the correlation curve between temperature and gain attenuation in the laboratory, and then using the sensor readings to find the corresponding gain compensation coefficient during logging. This method aims to adjust the gain in real time by monitoring the internal ambient temperature of the instrument to offset the negative impact of temperature changes on crystal detection efficiency, thereby attempting to ensure the reliability of logging data.

[0004] However, in actual operations, to prevent vibration, the crystal is usually encased in a shock-absorbing sleeve made of poor thermal conductors such as PTFE or silicone rubber, while the temperature sensor is typically mounted directly on the circuit board or close to the metal casing. This structural factor leads to a severe thermal hysteresis effect, meaning that the temperature change of the crystal core lags significantly behind the temperature change of the sensor. Specifically, during downhole heating, the outside is hot and the inside is cold, while during uphole cooling, the outside is cold and the inside is hot. Therefore, when the instrument passes through the same well depth during downhole and uphole operations, existing calibration methods incorrectly use the same temperature value to correct crystals with drastically different actual temperatures. This deviation causes the uphole and downhole logging curves to not coincide, greatly limiting the consistency and interpretation accuracy of logging data. Summary of the Invention

[0005] The purpose of this invention is to propose a remote data calibration method and system for neutron measurement systems, in order to solve the problem that the static lookup table method in the prior art cannot eliminate thermal hysteresis error, resulting in hysteresis loops in the logging curve; to this end, this invention provides solutions in the following two aspects.

[0006] In a first aspect, the present invention provides a remote data calibration method for a neutron measurement system, comprising:

[0007] The system acquires time-stamped temperature sensor sequences and raw energy spectrum characteristics uploaded by downhole instruments through a ground acquisition system. The temperature sensor sequences are then smoothed to identify the current temperature change status of the instruments. Based on the smoothed temperature sensor sequences and a preset material thermal saturation limit constant, a thermal hysteresis index is calculated to characterize the thermal shock intensity at the current moment. This thermal hysteresis index is used to reverse-correct the temperature sensor sequence readings, calculating the equivalent lattice temperature of the region within the crystal that actually participates in photoelectric conversion. The equivalent lattice temperature is then substituted into a preset quadratic polynomial multiplication compensation model to dynamically calibrate the raw energy spectrum characteristics, outputting calibrated normalized gain data.

[0008] In this way, by identifying the temperature change state and introducing time dimension information, a data foundation is provided for subsequent calculation of thermal hysteresis, ensuring that the calibration process is based on a dynamic process rather than a static point, thereby capturing the trend of temperature change.

[0009] Preferably, the smoothing and state identification of the temperature sensor sequence specifically includes: digitally filtering the original temperature sensor sequence using a moving average window of a preset length to obtain smoothed temperature data; calculating the first-order time difference of the smoothed temperature data; if the first-order time difference is positive and its absolute value is greater than a preset threshold, marking the current state as a downward temperature rise state; if the first-order time difference is negative and its absolute value is greater than the preset threshold, marking the current state as an upward temperature fall state; if the absolute value of the first-order time difference is less than or equal to the preset threshold, marking the current state as a steady state.

[0010] Thus, by using moving average filtering and differential analysis, electronic thermal noise can be effectively filtered out, and the instrument can be accurately determined whether it is in a heating, cooling or steady state, providing a basis for selecting the correct calibration logic.

[0011] Preferably, the length of the moving average window is 20, and the smoothing process is used to filter out electronic thermal noise generated by the downhole circuit.

[0012] Preferably, the expression for the thermal hysteresis index satisfies: In the formula, The thermal hysteresis index at the current moment. The sensor's measured temperature at the current moment. The sensor measured the temperature at the previous moment. To fix the sampling period of the system, It is the thermal saturation limiting constant of the material.

[0013] Thus, by introducing a nonlinear correction term, not only the rate of temperature change is considered, but also the effect of the degradation of the material's thermal conductivity at high temperatures, thereby accurately assessing the thermal shock intensity at the current moment.

[0014] Preferably, the thermal saturation limit constant of the material is taken as the temperature resistance limit value of the damping material, and the fixed sampling period of the system is a non-zero constant.

[0015] In this way, by setting a fixed sampling period, the division-to-zero error caused by repeated timestamps is avoided, ensuring the robustness of the algorithm.

[0016] Preferably, the expression for the equivalent lattice temperature satisfies: In the formula, The equivalent lattice temperature at the current moment. The sensor's measured temperature at the current moment. The thermal hysteresis index at the current moment. This is the hysteresis coupling coefficient.

[0017] Preferably, the method for determining the hysteresis coupling coefficient is as follows: adjusting the coefficient through laboratory thermal cycling calibration experiments. The value, until the calculated The corresponding energy spectrum characteristics of the heating section and the cooling section coincide at the same temperature point.

[0018] In this way, by using the thermal hysteresis index to correct the sensor temperature in reverse, the true equivalent temperature inside the crystal was successfully reconstructed, solving the physical problem of the inconsistency between the sensor temperature and the crystal temperature.

[0019] Preferably, the quadratic polynomial multiplication compensation model satisfies: ;in, In the formula, This is the calibrated normalized gain. The original energy spectrum characteristics, This is the temperature drift compensation coefficient. This is the secondary temperature drift compensation coefficient. This is the reference calibration temperature.

[0020] Thus, by adopting a multiplicative polynomial model with all positive terms, the risk of the denominator being zero in the traditional division model is eliminated. At the same time, the thermal quenching effect at high temperatures is compensated by the quadratic term, ensuring that stable calibration values ​​can be output even at extreme high temperatures.

[0021] Preferably, the primary temperature drift compensation coefficient is used to compensate for the linear decay of the crystal's light output with temperature, and the secondary temperature drift compensation coefficient is used to compensate for the nonlinear accelerated decay of the light output at high temperatures.

[0022] In a second aspect, a remote data calibration system for neutron measurement systems includes:

[0023] The processor; the memory storing computer instructions for remote data calibration of a neutron measurement system, which, when executed by the processor, cause the system to perform the aforementioned remote data calibration method for a neutron measurement system.

[0024] The beneficial effects of this invention are as follows: By introducing time series analysis, this invention calculates the thermal hysteresis exponent using the rate of temperature change and nonlinear correction factors, thereby reconstructing the equivalent lattice temperature of the crystal, thus solving the problem of asynchronous sensor and crystal temperatures. By using the reconstructed equivalent temperature for dynamic gain calibration, the hysteresis loop in the logging curve caused by the thermal hysteresis effect in traditional methods is eliminated, resulting in a high degree of overlap between the upper and lower logging data, significantly improving data consistency.

[0025] Meanwhile, the quadratic polynomial multiplication compensation model and fixed sampling period strategy adopted in this invention avoid the risk of division by zero in mathematical logic, have extremely high engineering robustness, and are particularly suitable for use in automated, unattended remote data processing centers. They can track the thermal state of crystals in real time, improving the data confidence and logging operation timeliness under complex temperature variations. Attached Figure Description

[0026] Figure 1 This is a flowchart of the steps of the remote data calibration method for a neutron measurement system in this embodiment;

[0027] Figure 2 This is a schematic diagram comparing the dynamic response of the sensor's measured temperature with the equivalent lattice temperature reconstructed by the algorithm of this invention.

[0028] Figure 3 This is a schematic diagram of the hysteresis loop phenomenon caused by the change of gain with temperature under existing technology calibration.

[0029] Figure 4 This is a schematic diagram illustrating the gain consistency effect after calibration using the method of this invention to eliminate hysteresis loops. Detailed Implementation

[0030] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0031] like Figure 1 As shown in this embodiment, a remote data calibration method for a neutron measurement system includes the following steps:

[0032] Step S1: Obtain the time-stamped temperature sensor sequence and raw energy spectrum characteristics uploaded by the downhole instrument through the ground acquisition system, and smooth the temperature sensor sequence to identify the current temperature change status of the instrument.

[0033] The first step in calibration is to acquire complete temporal information, not just depth information. Specifically, the surface acquisition system of the IPS networked logging system synchronously records data uploaded by the downhole instrument at a fixed sampling interval of 100 milliseconds. The acquired data includes temperature sensor sequences and raw energy spectrum characteristics. The temperature sensor sequences are readings uploaded in real time by the temperature sensors installed on the main control circuit board of the downhole instrument. Raw energy spectrum characteristics refer to the channel addresses of characteristic peaks that have not undergone temperature correction, such as the 2.22 MeV captured gamma peak of hydrogen or the 7.6 MeV captured gamma peak of iron.

[0034] Due to the presence of electronic thermal noise in downhole circuits, directly using raw temperature data to calculate gradients would introduce significant errors. Therefore, the system uses a length of... A moving average window is used to digitally filter the temperature sensor sequence to obtain a smoothed temperature curve. In this embodiment... The value is set to 20. Next, the first-order time difference of the smoothed temperature is calculated. Based on the sign and magnitude of the first-order time difference, the system automatically labels the current data with a status tag: if the first-order time difference is positive and its absolute value is greater than a preset threshold, it indicates that the instrument is moving towards a higher temperature range, and the current state is marked as a downward temperature rise state; if the first-order time difference is negative and its absolute value is greater than the preset threshold, it indicates that the instrument is moving towards a lower temperature range, and the current state is marked as an upward temperature fall state; if the absolute value of the first-order time difference is less than or equal to the preset threshold, it indicates that the instrument is in a fixed-point measurement or static state, and the current state is marked as a steady state. The preset threshold is an empirical constant, and its value can be adaptively set according to the actual usage scenario.

[0035] In this way, high signal-to-noise ratio temperature time series data were obtained through high-frequency sampling and digital filtering, and the thermal state of the instrument was accurately identified, providing a reliable input basis for subsequent thermal hysteresis calculations.

[0036] Step S2: Based on the smoothed temperature sensor sequence and combined with the preset material thermal saturation limit constant, calculate the thermal hysteresis index to characterize the thermal shock intensity at the current moment.

[0037] Specifically, based on the principle of unsteady-state heat conduction, the temperature difference between the crystal core and the sensor surface is inferred using the rate of temperature change. Considering that it takes time for heat to transfer from the sensor location to the crystal core, and that the thermal conductivity of damping materials such as PTFE or silicone rubber inside the instrument will nonlinearly degrade at high temperatures, the following thermal hysteresis exponential calculation model with nonlinear correction is constructed.

[0038] The expression for the thermal hysteresis exponent satisfies:

[0039] ;

[0040] in, The thermal hysteresis index represents the current moment and reflects the direction and intensity of the driving force for heat conduction. The sensor's measured temperature at the current moment. The sensor measured the temperature at the previous moment. To fix the sampling period of the system, It is the thermal saturation limiting constant of the material.

[0041] The thermal saturation limit constant of the material is taken as the temperature limit value of the damping material, and the system sampling period is a non-zero constant. For example, the system sampling period is set... The thermal saturation limiting constant of materials (Corresponding to the temperature resistance limit of the damping material).

[0042] Assuming the sensor temperature at the previous moment Current sensor temperature Therefore, the calculated thermal hysteresis index is 7, indicating that the thermal shock intensity at the current moment is 7. However, without considering nonlinear correction, the result is only 5, demonstrating that the thermal hysteresis effect is significantly amplified under high-temperature conditions.

[0043] Thus, by introducing a temperature-related nonlinear correction term, this step can accurately assess the thermal shock intensity under different temperature conditions, especially compensating for the impact of the deterioration of the material's thermal conductivity at high temperatures, making the calculated thermal hysteresis index more consistent with physical facts.

[0044] Step S3: The readings of the temperature sensor sequence are reversed using the thermal hysteresis index to calculate the equivalent lattice temperature of the actual region inside the crystal that participates in photoelectric conversion.

[0045] Because there is a phase difference between the crystal core temperature and the surface sensor temperature during rapid heating or cooling, this step uses the calculated thermal hysteresis index to reverse the sensor reading in order to estimate the true temperature inside the crystal.

[0046] The expression for the equivalent lattice temperature is as follows:

[0047] ;

[0048] in, The equivalent lattice temperature at the current moment. The sensor's measured temperature at the current moment. The thermal hysteresis index at the current moment. This is the hysteresis coupling coefficient, whose value is determined through a laboratory thermal cycling calibration platform, i.e., by adjustment. Until utilization The calculated energy spectrum characteristics of the heating section and the cooling section coincide at the same temperature point.

[0049] Continuing from the example in step S2, assume that the hysteresis coupling coefficient is determined through calibration. Current sensor temperature The calculated thermal hysteresis index Then the equivalent lattice temperature is: .

[0050] It is evident that the calculated result is lower than the current sensor temperature, which is highly consistent with physical facts: during the heating process in the well ( The external sensor has reached 120°C, but the inside of the crystal, encased in insulation material, is still relatively cold, at only 106°C. Similarly, during the cooling process at the surface, the difference is negative. When a number is negative, subtracting a negative number is equivalent to adding a positive number, resulting in... It will be higher than It conforms to the characteristics of being cold on the outside and hot on the inside.

[0051] Thus, by correcting the hysteresis coupling coefficient and thermal hysteresis exponent, the true temperature of the crystal was successfully reconstructed, eliminating the time phase error caused by the difference in the temperature measurement point position, and providing a correct temperature reference for subsequent accurate calibration.

[0052] Step S4: Substitute the equivalent lattice temperature into the preset quadratic polynomial multiplication compensation model, perform dynamic gain calibration on the original energy spectrum characteristics, and output the calibrated normalized gain data.

[0053] Specifically, utilizing the reconstructed Replace the original The final calibration is performed by taking into account the intrinsic temperature drift characteristics of the crystal. To ensure that the formula is valid and free of singularities at extreme temperatures, a quadratic polynomial multiplication compensation model with all positive terms is adopted.

[0054] The quadratic polynomial multiplication compensation model satisfies:

[0055] ;

[0056] in, ;

[0057] In the formula, This is the calibrated normalized gain. This refers to the original energy spectrum characteristics (e.g., the channel address of characteristic peaks). This is the temperature drift compensation coefficient. This is the secondary temperature drift compensation coefficient. For reference calibration, room temperature is usually used. .

[0058] Continuing from the example in step S3, assume the current equivalent lattice temperature Reference temperature Then the temperature difference Assuming the original measured gain (Relative values ​​before normalization); Crystal calibration parameters are: , Therefore, the final calibration gain can be calculated to be 109.41.

[0059] The results show that the original signal weakens (100) due to the decrease in crystal luminescence efficiency caused by the increase in temperature. The algorithm automatically amplifies the signal by about 9.4% (109.41) by calculating the actual crystal temperature, thereby restoring it to the level of standard room temperature.

[0060] Thus, by using quadratic polynomial compensation based on equivalent lattice temperature, not only is the linear temperature drift corrected, but the nonlinear effect of thermal quenching at high temperatures is also compensated. Furthermore, the multiplicative model completely eliminates the mathematical risk of the denominator being zero, ensuring the output stability of the system across the entire temperature range.

[0061] The following is combined with Figures 2 to 4 The effects of this embodiment will be further explained.

[0062] Figure 2 This study compares the sensor-measured temperature with the algorithm-reconstructed equivalent lattice temperature during a complete well logging operation. It shows that during the heating phase, the algorithm-reconstructed equivalent lattice temperature curve consistently lies below the sensor-measured temperature curve, exhibiting a lag. During the cooling phase, the algorithm-reconstructed equivalent lattice temperature curve reverses and rises above the sensor-measured temperature curve, exhibiting a lead. This accurately reflects the physical lag phenomenon of heat conduction.

[0063] Figure 3 The results of calibration using existing technology (uncorrected sensor temperature) show that the curves representing the downhole process and the curves representing the uphole process are completely separated, forming a distinct spindle-shaped hysteresis loop. Figure 4 The results of applying the method of this invention are shown. The curve representing the temperature rise in the well and the curve representing the temperature drop in the well perfectly coincide and closely fit the baseline, proving that the invention effectively eliminates dynamic and static measurement errors.

[0064] The present invention also provides a remote data calibration system for neutron measurement systems. The system includes a processor and a memory, the memory storing computer program instructions. When the processor executes the computer program instructions, it implements the remote data calibration method for neutron measurement systems described above according to the present invention.

[0065] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and therefore will not be described in detail here.

[0066] In this invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used or combined with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc., or any other medium that can be used to store desired information and can be accessed by an application, module, or both. Any such computer storage medium can be part of a device or accessible to or connected to a device. Any application or module described in this invention can be implemented by computer-readable / executable instructions stored or otherwise maintained on such a computer-readable medium.

[0067] In the description of this specification, "multiple" means at least two, such as two, three or more, etc., unless otherwise expressly and specifically defined.

[0068] While various embodiments of the invention have been shown and described in this specification, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention.

Claims

1. A remote data calibration method for a neutron measurement system, characterized in that, include: The temperature sensor sequence and raw energy spectrum characteristics uploaded by the downhole instrument are obtained through the ground acquisition system, and the temperature sensor sequence is smoothed to identify the current temperature change status of the instrument. Based on the smoothed temperature sensor sequence and a preset material thermal saturation limit constant, the thermal hysteresis index, used to characterize the intensity of thermal shock at the current moment, is calculated. ; In the formula, The thermal hysteresis index at the current moment. The sensor's measured temperature at the current moment. This is the sensor's measured temperature at the previous moment. To fix the sampling period of the system, This is the thermal saturation limiting constant of the material; The thermal hysteresis index is used to reverse the readings of the temperature sensor sequence to calculate the equivalent lattice temperature of the actual region inside the crystal that participates in photoelectric conversion. The equivalent lattice temperature is substituted into a preset quadratic polynomial multiplication compensation model to perform dynamic gain calibration on the original energy spectrum characteristics, and the calibrated normalized gain data is output.

2. The remote data calibration method for neutron measurement systems according to claim 1, characterized in that, The smoothing and state identification of the temperature sensor sequence specifically includes: The original temperature sensor sequence is digitally filtered using a sliding average window of preset length to obtain smoothed temperature data; Calculate the first-order time difference of the smoothed temperature data; If the first-order time difference is positive and its absolute value is greater than a preset threshold, the current state is marked as the next temperature rise state. If the first-order time difference is negative and its absolute value is greater than a preset threshold, the current state is marked as the upper-measured cooling state. If the absolute value of the first-order time difference is less than or equal to the preset threshold, the current state is marked as a steady state.

3. The remote data calibration method for neutron measurement systems according to claim 2, characterized in that, The length of the moving average window is 20, and the smoothing process is used to filter out electronic thermal noise generated by the downhole circuit.

4. The remote data calibration method for neutron measurement systems according to claim 1, characterized in that, The thermal saturation limit constant of the material is taken as the temperature resistance limit of the damping material, and the fixed sampling period of the system is a non-zero constant.

5. The remote data calibration method for a neutron measurement system according to claim 1, characterized in that, The expression for the equivalent lattice temperature satisfies: ； In the formula, The equivalent lattice temperature at the current moment. The sensor's measured temperature at the current moment. The thermal hysteresis index at the current moment. This is the hysteresis coupling coefficient.

6. The remote data calibration method for a neutron measurement system according to claim 5, characterized in that, The method for determining the hysteresis coupling coefficient is as follows: by adjusting the coefficient through laboratory thermal cycling calibration experiments. The value, until the calculated The corresponding energy spectrum characteristics of the heating section and the cooling section coincide at the same temperature point.

7. The remote data calibration method for a neutron measurement system according to claim 1, characterized in that, The quadratic polynomial multiplication compensation model satisfies: ； in, ; In the formula, This is the calibrated normalized gain. The original energy spectrum characteristics, This is the temperature drift compensation coefficient. This is the secondary temperature drift compensation coefficient. This is the reference calibration temperature.

8. The remote data calibration method for a neutron measurement system according to claim 7, characterized in that, The primary temperature drift compensation coefficient is used to compensate for the linear decay of the crystal's light output with temperature, and the secondary temperature drift compensation coefficient is used to compensate for the nonlinear accelerated decay of the light output at high temperatures.

9. A remote data calibration system for neutron measurement systems, characterized in that, include: processor; A memory storing computer instructions for remote data calibration of a neutron measurement system, which, when executed by the processor, cause the system to perform the remote data calibration method for a neutron measurement system according to any one of claims 1-8.

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