A method and system for data acquisition and timing synchronization processing in neutron generators

Abstract

This invention relates to the field of oil well logging technology, and more particularly to a method and system for data acquisition and timing synchronization processing of neutron generators, to solve the technical problems of synchronization loss under high-temperature and rapidly changing environments and the difficulty in achieving high-precision timing correction at low count rates. The method includes: S1, acquiring the neutron trigger signal, gamma time spectrum data, and environmental state data from the downhole instrument; S2, calculating the timing centroid offset index using the energy centroid method; S3, constructing the thermal oscillation confidence coefficient; S4, calculating the final timing compensation step size, and using the timing compensation step size to adjust the trigger delay of the acquisition circuit or the gamma time spectrum data in the buffer. This invention introduces a signal-to-noise ratio constraint, automatically reducing the confidence level when the signal quality is poor, suppressing erroneous adjustments caused by random noise, and ensuring data stability at low count rates.

Description

Technical Field

[0001] This invention relates to the field of oil well logging technology, and in particular to a data acquisition and timing synchronization processing method and system for neutron generators. Background Technology

[0002] Pulsed neutron logging technology uses a neutron generator to emit high-energy neutron pulses into the formation and a detector to collect the gamma rays fed back from the formation to analyze formation characteristics. This technology relies on precise timing control to ensure a strict distinction between the inelastic scattering stage and the thermal neutron capture stage. However, in actual deep well logging operations, the instrument is subjected to extreme high-temperature and high-pressure environments for extended periods, with downhole temperatures reaching as high as 175°C and dynamically varying with depth. This harsh environment causes frequency drift in the crystal oscillator of the acquisition circuit, and the conduction delay characteristics of the high-voltage discharge switch inside the neutron generator also change nonlinearly with increasing temperature and device aging, resulting in severe thermal-timing coupling drift.

[0003] Existing synchronization techniques typically use a fixed set of delay parameters set on the surface to control the acquisition gate. However, when temperature drift and thermal-temporal coupling drift occur downhole, the actual neutron burst time shifts forward or backward relative to the preset acquisition sequence. This causes the acquisition gate to fail to accurately cover the physical window; for example, the non-explosive gate may not accurately cover the neutron burst window, resulting in non-explosive gamma being mixed into the capture count, compromising the accuracy of carbon-oxygen ratio and saturation calculations. This fixed-sequence method cannot adapt to dynamic changes in the downhole environment, leading to a significant decrease in the reliability of measurement data.

[0004] Furthermore, traditional automatic calibration methods typically rely on finding peaks in the energy spectrum to adjust the timing sequence. However, in deep wells and low-porosity formations, gamma count rates are often very low, resulting in significant statistical fluctuations. Simple peak tracking causes the timing sequence to oscillate violently amidst noise, making it impossible to pinpoint the true signal location. If an averaging algorithm with a large time constant is used to suppress noise, the system will be too slow to keep up with the rapid drift caused by drastic temperature changes during rapid downhole runs.

[0005] Therefore, how to achieve high-precision timing synchronization under conditions of high temperature and rapid change and low count rate is a technical problem that urgently needs to be solved. Summary of the Invention

[0006] This invention provides a data acquisition and timing synchronization processing method and system for neutron generators to solve the technical problems of synchronization loss under high temperature and rapid change environment and difficulty in achieving high-precision timing correction under low count rate.

[0007] In a first aspect, the present invention provides a data acquisition and timing synchronization processing method for a neutron generator, comprising:

[0008] S1, acquire the neutron trigger signal, gamma time spectrum data and environmental status data of the downhole instrument, wherein the environmental status data includes ambient temperature data;

[0009] S2, Based on the gamma time spectrum data, the time series centroid offset index is calculated using the energy centroid method. The time series centroid offset index represents the deviation of the system time series from the standard reference at the current moment.

[0010] S3. Calculate the rate of change of ambient temperature based on the environmental state data, and construct a thermal oscillation confidence coefficient by combining the signal-to-noise ratio of the gamma time spectrum data. The thermal oscillation confidence coefficient represents the degree of confidence in the time series centroid shift index.

[0011] S4. Based on the timing centroid offset index and the thermal oscillation confidence coefficient, calculate the final timing compensation step size, and use the timing compensation step size to adjust the trigger delay of the acquisition circuit or the gamma time spectrum data in the buffer to complete timing synchronization.

[0012] By introducing a time-series centroid offset index and a thermal oscillation confidence coefficient, this invention constructs a thermal-time-series coupled drift model. This model does not rely on a single signal feature, but combines the rate of change of ambient temperature with the signal-to-noise ratio of the signal itself. It can respond quickly when the ambient temperature changes drastically, and suppress noise interference when the signal-to-noise ratio is low, thereby achieving microsecond-level synchronization accuracy under complex well conditions.

[0013] Furthermore, the temporal centroid offset index satisfies the following relationship:

[0014] ;

[0015] In the formula, This is a time-series centroid offset index. The first one in the current sliding window The gamma count value of each time channel, For the first Each time channel corresponds to a relative moment. This is the theoretical central moment of a standard neutron burst. This is the sum of all time-channel gamma counts used for calculation within the current sliding window. As a preset constant, This represents the total number of time channels.

[0016] Compared to directly finding the peak point, the offset index calculated using the energy centroid method is more sensitive to the deviation of the overall waveform by calculating the sum of squares of the weighted terms. It can also smooth out the random statistical fluctuations of individual time channels, avoid the calculation oscillations caused by noise at low count rates, and improve the robustness of offset assessment.

[0017] Furthermore, the thermal shock confidence coefficient satisfies the following relationship:

[0018] ;

[0019] In the formula, This represents the confidence coefficient for thermal oscillation. This represents the absolute value of the rate of change of ambient temperature. The signal-to-noise ratio of the current gamma-ray time spectrum data. and This is the morphological adjustment constant of the Sigmoid function. Based on the confidence constant, It is a natural constant.

[0020] The confidence evaluation system constructed using the Sigmoid function integrates two dimensions: temperature change rate and signal-to-noise ratio (SNR). When the temperature changes rapidly, the system increases the confidence level to quickly track temperature drift; when the SNR is high, the data reliability is high, and the confidence level increases; conversely, when the noise is high, the denominator increases, and the confidence level decreases to prevent spurious adjustments. This mechanism balances the system's sensitivity and stability.

[0021] Furthermore, the absolute value of the rate of change of the ambient temperature satisfies the following relationship:

[0022] ;

[0023] In the formula, This represents the absolute value of the rate of change of ambient temperature. The ambient temperature at the current moment. The ambient temperature at the previous moment. This represents the time interval between the current moment and the previous moment.

[0024] Furthermore, the signal-to-noise ratio of the current gamma time spectrum data is obtained by dividing the peak count outside the pop-up window by the average background count at the end of the capture window to obtain the signal-to-noise ratio.

[0025] Furthermore, the timing compensation step size satisfies the following relationship:

[0026] ;

[0027] In the formula, For timing compensation step size, The overall system gain coefficient. This serves as a drift direction indicator. It is the natural logarithm function. This represents the confidence coefficient for thermal oscillation. This is a time-series centroid offset index.

[0028] By using the natural logarithm to process the confidence level, the dynamic range is compressed, preventing excessively large jump steps under extreme temperature shocks that could lead to system instability, and ensuring the smoothness of the adjustment process.

[0029] Furthermore, the drift direction marker is obtained as follows:

[0030] Calculate the centroid time of the current sliding window gamma-time spectrum. The centroid time satisfies the following relationship:

[0031] ;

[0032] In the formula, This is the centroid moment of the current sliding window gamma time spectrum. This is the sum of all time-channel gamma counts used for calculation within the current window. The first one in the current sliding window The gamma count value of each time channel, For the first Each time channel corresponds to a relative moment;

[0033] like Then the drift direction flag is +1; if Then the drift direction flag takes the value of -1, where, This is the theoretically standard neutron burst center moment.

[0034] Furthermore, the method of adjusting using the timing compensation step size includes hardware layer feedback, wherein the hardware layer feedback is to convert the timing compensation step size into the number of clock cycles and adjust the trigger delay counter of the acquisition circuit in the next cycle.

[0035] Furthermore, the method for adjustment using the aforementioned time-compensation step size also includes data layer reconstruction. The data layer reconstruction involves using an interpolation algorithm to shift and resample the original gamma time spectrum data according to the time-compensation step size. The corrected gamma time spectrum data satisfies the following relationship:

[0036] ;

[0037] In the formula, For the corrected gamma time spectrum data at relative time The count value on For the original gamma time spectrum data in The count value on The relative time is the corrected time with the theoretical neutron burst time as the zero point. This is the timing compensation step size.

[0038] The hardware feedback enables real-time correction for the next cycle, while the software reconstruction repairs the current data. This dual-layer correction mechanism eliminates the drift effect to the greatest extent, ensuring the purity of the non-elastic spectrum and the captured spectrum, and improving the accuracy of geological parameter evaluation.

[0039] Secondly, the present invention provides a data acquisition and timing synchronization processing system for a neutron generator, including a memory and a processor. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned data acquisition and timing synchronization processing method for a neutron generator is implemented.

[0040] The beneficial effects are as follows: This invention constructs a thermal-temporal coupled drift model and introduces the rate of temperature change as a feedforward variable. This allows the synchronization algorithm to predict hardware drift risks and increase correction efforts when well temperatures fluctuate drastically, thus solving the synchronization lock-out problem under high-temperature and rapidly changing environments. Simultaneously, by introducing signal-to-noise ratio constraints, the confidence level is automatically reduced when signal quality is poor, suppressing erroneous adjustments caused by random noise and ensuring data stability at low count rates. Experiments show that the corrected energy spectrum waveform is tall and sharp, with peaks strictly aligned with the standard reference line, significantly reducing the variance of the C / O curve and improving the ability to distinguish between thin oil layers and remaining oil saturation. Attached Figure Description

[0041] Figure 1 A flowchart of a data acquisition and timing synchronization processing method for a neutron generator;

[0042] Figure 2 A comparison chart showing the real-time tracking effect of time-series drift under high-temperature conditions;

[0043] Figure 3 This is a comparison of the neutron gamma energy spectrum quality before and after timing correction. Detailed Implementation

[0044] An embodiment of the data acquisition and timing synchronization processing method for a neutron generator provided by the present invention:

[0045] like Figure 1 As shown, the data acquisition and timing synchronization processing method for a neutron generator includes the following steps:

[0046] S1, acquire the neutron trigger signal, gamma time spectrum data, and environmental status data of the downhole instrument, including ambient temperature data.

[0047] Specifically, the purpose of step S1 is to obtain the basic multidimensional data stream required to construct the drift model. The system acquires three types of data in parallel through the FPGA main control unit of the downhole instrument.

[0048] First, acquire the neutron trigger signal: obtain the synchronization pulse signal at the moment of neutron generator ignition. The synchronization pulse signal may be distorted or have a fixed delay after long-distance transmission and high temperature and high pressure environment, so it is used as a rough reference.

[0049] Secondly, gamma time spectrum data is acquired: the detector records the arrival time of gamma photons in microsecond-level time channels within each neutron pulse cycle; for example, the detector is a LaBr3 or BGO crystal. A sliding time window is set, and the data within the window is accumulated to form a statistically significant basic waveform; for example, the sliding time window buffers the data of the most recent 50 pulse cycles. Let the... The gamma count value of each time channel is The corresponding relative time is .

[0050] Finally, environmental status data is collected: real-time data from the temperature sensors inside the downhole instrument and the high-voltage feedback voltage of the neutron tube are collected.

[0051] The acquired gamma time spectrum data is preprocessed to remove the electronic noise floor, ensuring that subsequent calculations are performed on the valid signal.

[0052] By acquiring neutron trigger signals, gamma time spectrum data, and environmental state data in parallel, comprehensive and real-time data support was provided for subsequent thermal-temporal coupling analysis, ensuring the accuracy of model input.

[0053] S2, Based on the gamma time spectrum data, the time series centroid offset index is calculated using the energy centroid method. The time series centroid offset index represents the deviation of the system time series from the standard reference at the current moment.

[0054] Specifically, in order to avoid random errors caused by directly finding the highest point at a low count rate, in an optional embodiment, the energy centroid method is used to calculate the temporal centroid offset index.

[0055] The temporal centroid offset index satisfies the following relationship:

[0056] ;

[0057] In the formula, This is a time-series centroid offset index. The first one in the current sliding window The gamma count value of each time channel, For the first Each time channel corresponds to a relative moment. This represents the theoretical central moment of a standard neutron burst, where... This is a preset constant, for example, 10. , It is the sum of all time-channel gamma counts used for calculation within the current sliding window, i.e. . Let be a pre-defined positive real constant, for example, The value is set to 10.0, which is used to construct a smooth convex function to prevent numerical instability. This represents the total number of time channels.

[0058] If there is no gamma count within the current sliding window, set the timing centroid offset index to 0.

[0059] For example, suppose there are 3 time channels within the sliding time window, i.e. The theoretical standard neutron burst center time is , .

[0060] The collected data is as follows: 1) Time track 1: ;2) Time Channel 2: ;3) Time Channel 3: .

[0061] First, calculate the sum of all time-based gamma counts: .

[0062] Then, calculate the summation term under the square root in the formula:

[0063] 1) The first item ( : .

[0064] 2) The second item ( : .

[0065] 3) The third item ( : .

[0066] The summation result is: .

[0067] Next, substitute the values ​​into the relational expression to calculate the time series centroid offset index: .

[0068] It can be seen that when the gamma count is mainly concentrated near the theoretical center of a standard neutron burst, the time series centroid shift index is very small, close to 0.

[0069] Assuming a drift occurs, the entire data will shift backward by 1. And the amplitude remains unchanged: 1) The offset at time 1) is 0; 2) The offset at time is 1; 3) The offset at time is 2.

[0070] During calculation, the sum of all time-channel gamma counts used for calculation within the current sliding window remains 80. The summation term under the square root in the calculation formula: 1) The first term ( :0;2) The second item ( : ;3) The third item ( : The summation result is: .

[0071] Substitute the values ​​into the relational expression to calculate the time series centroid offset index: .

[0072] As can be seen, when drift occurs, the timing centroid offset index increases from 0.012 to 0.099, which can characterize the timing offset of the system.

[0073] By using the energy centroid method to calculate the timing centroid offset index and utilizing the logic of the sum of squares of weighted terms, the algorithm assigns greater weight to signals that deviate far from the theoretical zero point, effectively capturing the overall movement trend of the waveform, avoiding interference from single-point noise, and improving the accuracy of offset assessment.

[0074] S3. Calculate the rate of change of ambient temperature based on the environmental state data, and construct a thermal oscillation confidence coefficient by combining the signal-to-noise ratio of the gamma time spectrum data. The thermal oscillation confidence coefficient represents the degree of confidence in the time series centroid shift index.

[0075] Specifically, the confidence coefficient for thermal shock satisfies the following relationship:

[0076] ;

[0077] In the formula, The absolute value of the rate of change of ambient temperature is calculated as follows: ,in, and These are the current and previous ambient temperatures, respectively. This represents the time interval between the current moment and the previous moment. This is the signal-to-noise ratio of the current gamma time spectrum data, obtained by dividing the peak count outside the pop-up window by the average background count at the end of the capture window. , This is the morphological adjustment constant of the Sigmoid function, for example, ; Based on the confidence constant, for example, =0.1.

[0078] Let's take two scenarios as examples:

[0079] Scenario A: Scenario A is characterized by rapid temperature changes and has a generally low signal-to-noise ratio.

[0080] Assumption , , Index term: Denominator: . At this point, the confidence level is high, and the system will respond actively to temperature changes.

[0081] Scene B: Scene B has a stable temperature and an extremely low signal-to-noise ratio.

[0082] Assumption , Index term: Denominator: . .

[0083] At this point, the thermal oscillation confidence coefficient falls back to near the base value, mainly determined by the base confidence constant. This means that when there is a lot of noise and the temperature is stable, the algorithm will only retain the minimum fine-tuning, suppressing false large adjustments caused by noise.

[0084] By introducing the rate of change of ambient temperature and the signal-to-noise ratio to construct a confidence coefficient, the system can increase the correction force to catch up with drift when the temperature changes rapidly, and reduce the confidence to suppress misjudgment when the signal quality is poor, thus realizing an adaptive dynamic adjustment strategy.

[0085] S4. Based on the timing centroid offset index and the thermal oscillation confidence coefficient, calculate the final timing compensation step size, and use the timing compensation step size to adjust the trigger delay of the acquisition circuit or the gamma time spectrum data in the buffer to complete timing synchronization.

[0086] Specifically, the timing compensation step size satisfies the following relationship:

[0087] ;

[0088] In the formula, For example, the overall system gain coefficient. =1000, used to map minute time-series centroid offset metrics to the microsecond level. This serves as a drift direction indicator. This is the timing compensation step size.

[0089] When obtaining the drift direction flag: first, the centroid time of the current sliding window gamma time spectrum is calculated, and the centroid time satisfies the following relationship:

[0090] ;

[0091] In the formula, This is the centroid moment of the current sliding window gamma time spectrum. This is the sum of all time-channel gamma counts used for calculation within the current window. The first one in the current sliding window The gamma count value of each time channel, For the first Each time channel corresponds to a relative moment.

[0092] like This indicates pulse hysteresis, and the value of the drift direction flag is... Conversely, the drift direction flag takes the value of... .

[0093] The formula for the timing compensation step size uses the natural logarithm to process the thermal oscillation confidence coefficient, which compresses the dynamic range and prevents system oscillations from occurring when the thermal oscillation confidence coefficient is too large.

[0094] For example, continuing from the above example, where, Assuming the scenario is scenario A, where, Calculated The drift direction indicator takes the value of , .

[0095] .

[0096] After calculating the specific compensation microseconds, the system performs a two-layer correction, consisting of hardware layer feedback and data layer reconstruction.

[0097] In this context, hardware-level feedback refers to converting the timing compensation step size into FPGA clock cycles and dynamically adjusting the trigger delay counter of the acquisition circuit for the next cycle. For example, if there is a lag, the hardware acquisition delay is reduced, causing the acquisition gate to move forward.

[0098] Data layer reconstruction refers to shifting and resampling the original time spectrum data based on the time-series compensation step size using an interpolation algorithm for the data currently in the cache.

[0099] The corrected gamma-time spectrum data satisfy the following relationship:

[0100] ;

[0101] In the formula, For the corrected gamma time spectrum data at relative time The count value on For the original gamma time spectrum data in The count value on The relative time is the corrected time with the theoretical neutron burst time as the zero point. This is the timing compensation step size.

[0102] In one example, refer to Figure 2 and Figure 3 , Figure 2 The invention demonstrates that, under high-temperature conditions, the adaptive compensation curve can closely follow the drift trend of the actual working conditions, proving the algorithm's rapid response to environmental changes. Figure 3 The correction effect is demonstrated; existing technology results in waveform broadening and peak deviation, while the corrected waveform of this invention is sharp with peaks precisely aligned at 20°. The standard reference line eliminates data ambiguity.

[0103] By calculating the final timing compensation step size and implementing dual adjustments in hardware and software, the subsequent acquisition timing was corrected not only at the physical level but also at the data level, thereby eliminating the impact of high-temperature drift on well logging data and ensuring the accurate alignment of energy spectrum data and the reliability of geological parameter calculations.

[0104] An embodiment of the data acquisition and timing synchronization processing system for a neutron generator provided by the present invention:

[0105] The data acquisition and timing synchronization processing system for a neutron generator includes a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement the aforementioned data acquisition and timing synchronization processing method for a neutron generator.

[0106] The data acquisition and timing synchronization processing system for the neutron generator also includes other components well known to those skilled in the art, such as communication interfaces. Their settings and functions are known in the art and will not be described in detail here.

[0107] In addition, in the description of this specification, "multiple" means at least two, such as two, three or more, etc., unless otherwise expressly and specifically defined.

Claims

1. A method for data acquisition and timing synchronization processing in a neutron generator, characterized in that, include: S1, acquire the neutron trigger signal, gamma time spectrum data and environmental status data of the downhole instrument, wherein the environmental status data includes ambient temperature data; S2, Based on the gamma time spectrum data, the time series centroid offset index is calculated using the energy centroid method. The time series centroid offset index represents the deviation of the system time series from the standard reference at the current moment. S3. Calculate the rate of change of ambient temperature based on the environmental state data, and construct a thermal oscillation confidence coefficient by combining the signal-to-noise ratio of the gamma time spectrum data. The thermal oscillation confidence coefficient represents the degree of confidence in the time series centroid shift index. S4. Based on the time-series centroid offset index and the thermal oscillation confidence coefficient, calculate the final time-series compensation step size, satisfying the following relationship: ； In the formula, For timing compensation step size, The overall system gain coefficient. This serves as a drift direction indicator. It is the natural logarithm function. This represents the confidence coefficient for thermal oscillation. This is a time-series centroid offset indicator; The timing compensation step size is used to adjust the trigger delay of the acquisition circuit or the gamma time spectrum data in the buffer to complete timing synchronization.

2. The data acquisition and timing synchronization processing method for a neutron generator according to claim 1, characterized in that, The time-series centroid offset index satisfies the following relationship: ； In the formula, This is a time-series centroid offset index. The first one in the current sliding window The gamma count value of each time channel, For the first Each time channel corresponds to a relative moment. This is the theoretical central moment of a standard neutron burst. This is the sum of all time-channel gamma counts used for calculation within the current sliding window. As a preset constant, This represents the total number of time channels.

3. The data acquisition and timing synchronization processing method for a neutron generator according to claim 1, characterized in that, The thermal shock confidence coefficient satisfies the following relationship: ； In the formula, This represents the confidence coefficient for thermal oscillation. This represents the absolute value of the rate of change of ambient temperature. The signal-to-noise ratio of the current gamma-ray time spectrum data. and This is the morphological adjustment constant of the Sigmoid function. Based on the confidence constant, It is a natural constant.

4. The data acquisition and timing synchronization processing method for a neutron generator according to claim 3, characterized in that, The absolute value of the rate of change of ambient temperature satisfies the following relationship: ； In the formula, This represents the absolute value of the rate of change of ambient temperature. The ambient temperature at the current moment. The ambient temperature at the previous moment. This represents the time interval between the current moment and the previous moment.

5. The data acquisition and timing synchronization processing method for a neutron generator according to claim 3, characterized in that, The signal-to-noise ratio of the current gamma time spectrum data is obtained by dividing the peak count outside the pop-up window by the average background count at the end of the capture window.

6. The data acquisition and timing synchronization processing method for a neutron generator according to claim 1, characterized in that, The drift direction indicator is obtained as follows: Calculate the centroid time of the current sliding window gamma-time spectrum. The centroid time satisfies the following relationship: ； In the formula, This is the centroid moment of the current sliding window gamma time spectrum. This is the sum of all time-channel gamma counts used for calculation within the current window. The first one in the current sliding window The gamma count value of each time channel, For the first Each time channel corresponds to a relative moment; like Then the drift direction flag is +1; if Then the drift direction flag takes the value of -1, where, This is the theoretically standard neutron burst center moment.

7. The data acquisition and timing synchronization processing method for a neutron generator according to any one of claims 1-6, characterized in that, The method of adjusting using the timing compensation step size includes hardware layer feedback, wherein the hardware layer feedback is to convert the timing compensation step size into the number of clock cycles and adjust the trigger delay counter of the acquisition circuit in the next cycle.

8. The data acquisition and timing synchronization processing method for a neutron generator according to claim 7, characterized in that, The method for adjustment using the time-compensation step size also includes data layer reconstruction. The data layer reconstruction involves using an interpolation algorithm to shift and resample the original gamma time spectrum data according to the time-compensation step size. The corrected gamma time spectrum data satisfies the following relationship: ； In the formula, For the corrected gamma time spectrum data at relative time The count value on For the original gamma time spectrum data in The count value on The relative time is the corrected time with the theoretical neutron burst time as the zero point. This is the timing compensation step size.

9. A data acquisition and timing synchronization processing system for a neutron generator, characterized in that, It includes a memory and a processor, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the data acquisition and timing synchronization processing method for a neutron generator as described in claim 8 is implemented.

Images