A method, system, terminal and medium for quantitatively controlling quality of cement properties based on natural gamma

Abstract

The application discloses a natural gamma-based quantitative quality control method and system for cement properties through casing, a terminal and a medium, and belongs to the technical field of well logging, and specifically relates to the following steps: extracting and pre-processing open hole natural gamma curves and casing natural gamma curves, performing hole diameter-mud density correction and casing thickness correction on the casing natural gamma curves; calculating the cross-sectional area of the open hole natural gamma curves and the casing natural gamma curves based on a sliding window, and representing the influence of a cement sheath on a gamma signal; simulating an integrated influence function to inversely solve cement mixing amount and formation density and obtain a cement mixing amount curve; normalizing the dimensions of the cross-sectional area curve and the cement mixing amount curve, calculating an Error value to evaluate the difference between the two, outputting quantitative quality control of cement properties through casing, and correcting the cement mixing amount in an abnormal interval of the cement sheath to realize automatic identification of an abnormal interval and iterative optimization of the cement mixing amount. The application can significantly improve the inversion accuracy of the comprehensive influence of cement density and thickness under complex well conditions.

Description

Technical Field

[0001] This invention belongs to the field of well logging technology, specifically relating to a quantitative quality control method, system, terminal, and medium for the properties of cement through casing based on natural gamma. Background Technology

[0002] Advances in well logging technology have provided key parameters such as porosity, permeability, and hydrocarbon saturation for reservoir evaluation, playing a crucial role in oil and gas resource development. Density logging curves, as important logging data, can be used to assess reservoir properties, laying a solid foundation for reservoir evaluation. Obtaining reservoir data through measurement while drilling in conventional open-hole wells presents significant challenges, and the risks of complex well operations are difficult to manage effectively. To improve the safety of logging operations, through-casing logging has become widely used. Through-casing logging involves installing casing and cementing it in the well. This method effectively prevents borehole collapse, isolates the formation, seals leaky zones and hydrocarbon layers, and creates a stable path for drilling. Generally, casing is installed and cementing is performed after some drilling operations are completed.

[0003] In density logging through casing, the impact of changes in cement sheath properties on measurement results cannot be underestimated. As a crucial isolation medium between the casing and the formation, the uncertainty in the density and thickness of cement can severely interfere with the logging response. When the cement density deviates from the design value due to differences in formulation, uneven curing, or contamination by formation fluids, it alters the attenuation characteristics of gamma rays received by the logging instrument, thus affecting the accuracy of inverting the true formation density. For example, low-density cement areas may cause abnormally high porosity phenomena in the logging curve, while high-density cement zones may obscure the oil and gas-bearing characteristics of the reservoir.

[0004] Furthermore, the heterogeneity of cement sheath thickness also poses a challenge. Near the casing coupling, if the cement sheath is too thin or even missing, the logging signal will directly penetrate the casing-coupling interface, causing an abnormally high apparent density value at the coupling and resulting in local measurement distortion. Conversely, an excessively thick cement sheath may attenuate the effective signal and reduce the vertical resolution of the logging curve. This thickness variation is often closely related to cementing quality, wellbore irregularities, and construction techniques, resulting in a complex heterogeneous three-dimensional spatial distribution of the cement sheath, further exacerbating the ambiguity of logging interpretation.

[0005] In actual backfill density inversion processes, the count rate is difficult to accurately reflect formation density changes due to factors such as measurement errors and data acquisition and transmission, which limits the application and effectiveness of single-density instruments and detector-based count response solving algorithms. Summary of the Invention

[0006] To address the challenges of analyzing the combined effects of cement thickness and density on counting in real-world well conditions due to the complexity of cement properties, this invention provides a quantitative quality control method, system, terminal, and medium for cement properties through casing logging based on natural gamma. This significantly improves the accuracy of inversion of cement density, thickness, and other properties under complex well conditions, providing a reliable technical means for evaluating cement sheath quality and accurately inverting formation density in through casing logging.

[0007] To achieve the above objectives, the technical method employed in this invention is as follows:

[0008] A quantitative quality control method for the properties of through-casing cement based on natural gamma includes the following steps:

[0009] Step 1: Using a natural gamma logging tool, measure the natural gamma curves of open hole wells and casing wells as well depth, respectively.

[0010] Step 2: Preprocess the outliers and missing values ​​in the natural gamma curves of open hole wells and cased wells. The natural gamma curve of open hole wells after preprocessing is GR, and the natural gamma curve of cased wells after preprocessing is GRCC.

[0011] Step 3: Correct the GRCC's wellbore diameter, mud density, and casing thickness, and denote the corrected GRCC as GRCC*;

[0012] Step 4: Using GR as the upper curve and GRCC* as the lower curve, employ the sliding window data processing method to obtain the cross area curve of GR and GRCC* within the well depth detection range. After normalization to the maximum and minimum values, the cross area curve is obtained. ;

[0013] Step 5: Using an over-casing gamma probe response model, simulate different formation densities within the well depth detection range. Different sleeve densities Different sleeve thicknesses Different cement densities Different cement thicknesses gamma count of detectors in casing wells Fitting the data yielded the media effects at different depths in the casing well formation density measurement. Influence relationship function;

[0014] The influence relationship function is related to and The relevant terms are used as cement mix content; the cement mix content and formation density of the casing well are inverted and solved using the quasi-Newton method. Furthermore, the cement mixing content curve of the casing well as its depth is obtained. After normalization to the maximum and minimum values, the cement mixing quantity curve was obtained. ;

[0015] Step 6: Based on the cross area curve Cement mixing volume curve The quantitative quality control error value within each window interval is calculated using a sliding window method. :

[0016]

[0017] In the formula, This represents the starting position of each window; This indicates the end position of each window;

[0018] Step 7: For each window interval ,like If the cement sheath quality is less than the first preset threshold, the cement mixture content and formation density corresponding to the window interval are considered to be qualified, and the cement mixture content and formation density corresponding to the window interval are output. ;like If the value is greater than the second preset threshold, the cement ring corresponding to that window interval is considered to be of substandard quality; if If the cement ring corresponding to the window interval is greater than or equal to the first preset threshold and less than or equal to the second preset threshold, then the interval is considered an abnormal interval, based on the cross-area curve. Cement mixing volume curve The process of correcting the cement mixing amount of the corresponding cement ring in the window interval is completed by using the intersection area of ​​the window interval as the corresponding cement mixing amount.

[0019] Furthermore, step 7 also outputs the corrected cement mixing quantity curve for cement quality control.

[0020] Furthermore, the specific preprocessing steps in step 2 are as follows:

[0021] Step 2.1: Use interpolation to remove outliers;

[0022] Step 2.2: Use interpolation to fill in the missing values;

[0023] Step 2.3: Align the natural gamma curves of open-hole and cased-hole wells at depth by means of translation and resolution matching.

[0024] Furthermore, in step 4, the cross-area curve of GR and GRCC* within the well depth detection range is obtained. The specific process is as follows:

[0025] Assuming the sliding step size is t, and P sliding window data processing operations are performed within the well depth detection range, then the th... The set of data points within each sliding window is Where n is the total number of data points contained within the sliding window. For the first sliding window One data point;

[0026] Calculate GR and GRCC* in the first... The cross area within a sliding window :

[0027]

[0028] In the formula, Gamma ray intensity, Indicates GR; Indicates GRCC*;

[0029] Based on the cross area within each sliding window, the cross area curve that varies with the position of the sliding window is obtained. .

[0030] Furthermore, step 5 employs the Monte Carlo method for simulation.

[0031] Furthermore, the specific formula affecting the relational function in step 5 is as follows:

[0032]

[0033] In the formula, , , , , , and All are fitting coefficients;

[0034] This will affect the relational function. This item is used as the amount of cement to mix.

[0035] Furthermore, in step 7, the first preset threshold is set to 0.2, and the second preset threshold is set to 0.8.

[0036] A quantitative quality control system for through-casing cement properties based on natural gamma ray is provided to implement the aforementioned quantitative quality control method for through-casing cement properties. Specifically, it includes a natural gamma logging module, a preprocessing module, a correction module, a cross-area curve calculation module, a cement mixing quantity curve calculation module, a quantitative quality control error value calculation module, and a quantitative quality control result output and correction module; wherein:

[0037] The natural gamma logging module is used to measure the natural gamma curves of open-hole and cased wells as well depth, and input them into the preprocessing module;

[0038] The preprocessing module is used to preprocess outliers and missing values ​​in the natural gamma curves of open hole wells and cased wells. The preprocessed natural gamma curve GR of the open hole well is input to the cross area curve calculation module, and the preprocessed natural gamma curve GRCC of the cased well is input to the correction module.

[0039] The correction module is used to correct the well diameter, mud density and casing thickness of the pre-processed natural gamma curve GRCC of the casing well. The corrected natural gamma curve GRCC* of the casing well is then input into the cross area curve calculation module.

[0040] The cross-area curve calculation module is used to obtain the cross-area curve of GR and GRCC* within the well depth detection range. Input the value into the quantitative quality control error value calculation module;

[0041] The cement mixing volume curve calculation module is used to fit the gamma count of the detector at different depths of the medium in the casing well formation density measurement. The influence relationship function is used to determine the expression for cement mixture quantity, and the cement mixture quantity and formation density of the casing well are solved by inversion. This allows us to obtain the cement mixing content curve of the casing well as its depth. Input the value into the quantitative quality control error value calculation module;

[0042] The quantitative quality control error value calculation module is used to calculate... and Quantitative quality control error values ​​between ;

[0043] The quantitative quality control result output and correction module is used to output and correct the results. The results are compared with the first preset threshold and the second preset threshold. Based on the comparison results, the quantitative quality control results of the cement ring are output, and the results are classified as follows: those falling between the first preset threshold and the second preset threshold are... ,according to Correction .

[0044] A terminal includes a memory, a processor, and a computer program stored in the memory, the processor executing the computer program to implement the steps of the quantitative quality control method for the properties of through-casing cement based on natural gamma.

[0045] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the quantitative quality control method for the properties of over-sleeve cement based on natural gamma.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] 1. This invention proposes a quantitative quality control method, system, terminal, and medium for cement properties through casing based on natural gamma. First, the natural gamma curves of open-hole and casing wells are extracted. After data preprocessing, the casing well natural gamma curve is corrected for diameter-mud density and casing thickness to remove wellbore environmental interference and retain the true radioactive response characteristics of the cement sheath and formation. The cross area between the open-hole and casing well natural gamma curves is calculated using a sliding window technique to quantify their separation degree, thus characterizing the influence of the cement sheath on the gamma signal. A comprehensive influence function characterizing the casing, cement, and formation is obtained through simulation. The cement mixture amount and formation density are then inverted to obtain the cement mixture amount curve. The dimensions of the cross area curve and the cement mixture amount curve are unified using a maximum-minimum normalization method. The error value is calculated again using the sliding window technique to evaluate the difference between the two, outputting the quantitative quality control of cement properties through casing. The cement mixture amount in abnormal cement sheath intervals is corrected, achieving automatic identification of abnormal intervals and iterative optimization of cement mixture amount.

[0048] 2. This invention utilizes spontaneously generated radioactive gamma signals from the formation (without external excitation) and overcomes the limitations of traditional single-instrument inversion methods in solving cement sheath parameters by using sliding window variance-area joint analysis and normalization constraints. Experimental results show that the method of this invention significantly improves the inversion accuracy of the comprehensive influence of cement density and thickness under complex well conditions, providing a reliable technical means for cement sheath quality evaluation and accurate formation density inversion in through-casing logging. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating the quantitative quality control method for the properties of through-sleeve cement based on natural gamma proposed in Example 1.

[0051] Figure 2 This is a schematic diagram showing the position and structure of the natural gamma logging tool used in Example 1 when measuring open hole and casing wells respectively;

[0052] Figure 3 These are the natural gamma curves of open-hole and cased-hole wells as a function of well depth, as measured in Example 1;

[0053] Figure 4 The natural gamma curve of the casing well after correction for well diameter and mud density (a) and casing thickness (b) in Example 1;

[0054] Figure 5 It is the cross area curve in Example 1. ;

[0055] Figure 6 It is the cross area curve in Example 1 Mixing amount curve with cement The comparison chart. Detailed Implementation

[0056] To further understand the present invention, preferred embodiments of the present invention are described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, and not for limiting the scope of the claims.

[0057] Example 1

[0058] This embodiment proposes a quantitative quality control method for the properties of through-casing cement based on natural gamma radiation. The process is as follows: Figure 1 As shown, it includes the following steps:

[0059] Step 1, as follows Figure 2 As shown, using a natural gamma logging tool, the natural gamma curves of open-hole and cased-hole wells as a function of well depth were measured respectively. The measurement results are as follows. Figure 3 As shown.

[0060] The natural gamma ray logging tool consists of an instrument casing, a thermos, and a detector. Randomly distributed natural gamma ray sources exist within the formation, spontaneously emitting gamma rays. In the open-hole scenario, gamma rays in the formation propagate directly towards the detector, which receives the gamma ray signals radiated naturally from the formation. Even in the cased-back scenario, despite the presence of casing, cement, and other structures, the target of natural gamma ray logging remains the naturally occurring gamma ray sources within the formation. The detector receives these gamma rays to analyze geological information such as formation lithology and clay content. Unlike cased-back density logging, which relies on chemical sources, natural gamma ray logging is based on the formation's own radioactive characteristics for measurement.

[0061] In natural gamma-ray logging, naturally occurring radioactive nuclides in the formation (such as uranium-series, thorium-series, and potassium-40) spontaneously decay, releasing gamma rays. As these gamma rays propagate towards the detector, they interact with the formation material through photoelectric and Compton effects, altering their energy and propagation direction, while simultaneously transmitting information about the radioactive characteristics of the formation material. After one or more scattering events, the rays are received by the detector.

[0062] The scintillation detector used in natural gamma logging works as follows: Gamma rays are absorbed when they enter the scintillation crystal, generating secondary electrons. These secondary electrons lose energy within the scintillator, causing numerous molecules or atoms to become excited and ionized. When the excited molecules / atoms return to their ground state, they release photons. The fluorescence emitted by the scintillator is incident on the photocathode of a photomultiplier tube, ejecting photoelectrons. These photoelectrons multiply in the photomultiplier tube and are eventually collected at the anode, outputting an electrical signal. The signal strength is related to the kinetic energy of the secondary electrons. By using the scintillation crystal, the intensity of gamma rays can be detected, and gamma counts from different detectors can be obtained.

[0063] During actual measurements, the natural gamma logging instrument is lowered along with the carrier, collecting gamma counts from each detector at regular intervals. A continuous curve is plotted with depth on the horizontal axis and detector counts on the vertical axis. Curve windows are recorded according to energy ranges, reflecting the formation's radioactive characteristics: formations with high clay content have high gamma counts; different lithologies exhibit different gamma counts due to variations in radionuclide content. By analyzing the curve characteristics, geological information such as formation lithology and clay content can be retrieved, providing crucial evidence for formation evaluation.

[0064] Step 2: Preprocess outliers and missing values ​​in the natural gamma curves of open-hole and cased-hole wells. The specific process is as follows:

[0065] Step 2.1: Use interpolation to remove outliers from the natural gamma curves of open-hole and cased-hole wells;

[0066] Step 2.2: Use interpolation to fill in the missing values ​​in the natural gamma curves of open-hole and cased-hole wells;

[0067] Step 2.3: Align the natural gamma curves of the open hole well and the casing well with depth by means of translation and resolution matching to complete the preprocessing process. The natural gamma curve of the open hole well after preprocessing is denoted as GR, and the natural gamma curve of the casing well after preprocessing is denoted as GRCC.

[0068] Step 3: Correct the GRCC's wellbore diameter, mud density, and casing thickness, and denote the corrected GRCC as GRCC*;

[0069] Specifically, we analyzed and experimented with various environmental parameters that appeared in natural gamma measurement in casing wells, such as considering the influence of mud density and well diameter on API (natural gamma logging unit) value, as well as the influence of casing thickness density on API value, and constructed a natural gamma correction chart after casing.

[0070] Based on existing post-application natural gamma correction charts (i.e., correction relationship charts for various environmental parameters and API correction values), we obtain, as follows: Figure 4The calibration chart shown in (a) illustrates different wellbore diameters and mud densities. In actual use, inputting mud density and wellbore diameter information yields the total calibration value, which is then used to correct the API value. Similarly, based on... Figure 4 The casing thickness correction chart shown in (b) is used to correct the casing thickness density. After the correction is completed, the GRCC* curve can be obtained, which mainly reflects the information of the formation and cement, and can be used as one of the input curves in step 4.

[0071] Step 4: Using GR as the upper curve and GRCC* as the lower curve, employ the sliding window data processing method to obtain the cross area curve of GR and GRCC* within the well depth detection range. After normalization to the maximum and minimum values, the cross area curve is obtained. ;

[0072] The specific process is as follows:

[0073] Assuming the sliding step size is t, and P sliding window data processing operations are performed within the well depth detection range, then the th... The set of data points within each sliding window is Where n is the total number of data points contained within the sliding window. For the first sliding window One data point;

[0074] Calculate GR and GRCC* in the first... The cross area within a sliding window :

[0075]

[0076] In the formula, Gamma ray intensity, Indicates GR; Indicates GRCC*;

[0077] The cross area is the enclosed area within the sliding window. This physical quantity reflects the degree of separation between the back-mounted and naked-eye GR. This physical quantity can represent the influence of cement to a certain extent.

[0078] Since well logging data consists of discrete data points, the trapezoidal rule is used for approximate integration in practice. The specific formula is as follows:

[0079]

[0080] In the formula, The interval between adjacent sampling points in GR and GRCC*;

[0081] Based on the cross area within each sliding window, the cross area curve that varies with the position of the sliding window is obtained. ,like Figure 5 As shown, after normalization to the maximum and minimum values, the cross area curve is obtained. .

[0082] Step 5: Using the over-casing gamma ray probe response model and the Monte Carlo method, simulate different formation densities within the well depth detection range. Different sleeve densities Different sleeve thicknesses Different cement densities Different cement thicknesses gamma count of detectors in casing wells Fitting the data yielded the media effects at different depths in the casing well formation density measurement. The influence relationship function, the specific formula is as follows:

[0083]

[0084] In the formula, , , , , , and All are fitting coefficients;

[0085] The influence of the relation function This item is used as the cement mixing quantity;

[0086] Based on the influence relationship function, the formation density is solved simultaneously. Cement mixing amount and casing calibration amount Three unknown variables. By designing a loss function, the problem of solving linear equations can be transformed into an optimization problem. The loss function is designed to calculate values ​​using the corresponding forward modeling expression. Counting with actual detectors The goal is to minimize the sum of squared errors between the parameters. By iteratively solving the problem using conventional optimization methods such as the quasi-Newton method, the optimal numerical solution for the environmental parameters can be obtained.

[0087] This allows us to obtain the cement mixing content curve of the casing well as its depth. After normalization to the maximum and minimum values, the cement mixing quantity curve was obtained. .

[0088] Step 6, as follows Figure 6 As shown, based on the cross area curve Cement mixing volume curve The quantitative quality control error value within each window interval is calculated using a sliding window method. :

[0089]

[0090] In the formula, This is the starting position of each window; This indicates the end position of each window;

[0091] In this embodiment, the sliding step size of the sliding window in step 6 is the same as that in step 4, both being t, and the total number of data points in each sliding window is the same as in step 4, both being n. Therefore, the same sliding window as in step 4 is used for... calculate.

[0092] Step 7, as follows Figure 6 As shown, for each window interval ,like If the value is less than 0.2, the cement sheath quality corresponding to the window interval is considered qualified, and the cement mixture content and formation density corresponding to the window interval are output. ;like If the value is greater than 0.8, the cement ring quality corresponding to that window interval is considered unqualified, and engineers are advised to check this data segment; if... If the value is greater than or equal to 0.2 and less than or equal to 0.8, then the cement ring corresponding to this window interval is considered an abnormal interval. Figure 6 (the pink area in the image), based on the cross area curve Cement mixing volume curve The process of correcting the cement mixing amount of the corresponding cement ring in the window interval is completed by using the intersection area of ​​the window interval as the corresponding cement mixing amount.

[0093] Because the actual measurement environment after inversion is complex and variable, and the main objective is to solve for the density value, the cement mixture content is often treated as an error term during the inversion process in many cases, resulting in an inversion accuracy that is usually lower than that of density. Since the solution process of the forward and inversion equations may further amplify the error, it is necessary to further correct for the cement mixture content. The existence of the cross area can effectively indicate the influence of cement and provide a reference for the correction of the cement mixture content.

[0094] Furthermore, although the difference curves and area curves constructed from the natural gamma intervals of the image with and without lens coverage are physically similar, their corresponding specific values ​​differ. To facilitate anomaly analysis of the area curves and cement mixing volume, normalization is required. This paper employs the max-min normalization method to linearly map the original data to a specified interval, enabling effective comparisons within windows of different depth ranges.

[0095] The above embodiments are provided to better understand the present invention and are not limited to the preferred embodiments described. They do not constitute a limitation on the content and scope of protection of the present invention. Any product that is the same as or similar to the present invention, derived by any person under the guidance of the present invention or by combining the features of the present invention with other prior art, is within the scope of protection of the present invention.

Claims

1. A quantitative quality control method for the properties of through-casing cement based on natural gamma, characterized in that, Includes the following steps: Step 1: Using a natural gamma logging tool, measure the natural gamma curves of open-hole wells and casing wells respectively; Step 2: Preprocess the outliers and missing values ​​in the natural gamma curves of open hole wells and cased wells. The natural gamma curve of open hole wells after preprocessing is GR, and the natural gamma curve of cased wells after preprocessing is GRCC. Step 3: Correct the GRCC's wellbore diameter, mud density, and casing thickness, and denote the corrected GRCC as GRCC*; Step 4: Using GR as the upper curve and GRCC* as the lower curve, employ the sliding window data processing method to obtain the cross area curve of GR and GRCC* within the well depth detection range. After normalization, the cross area curve is obtained. ; Step 5: Use the over-casing gamma probe response model to simulate different formation densities. Different sleeve densities Different sleeve thicknesses Different cement densities Different cement thicknesses gamma count of detectors in casing wells Fitting the data yielded the media effects at different depths in the casing well formation density measurement. Influence relationship function; The influence relationship function is related to and The relevant terms are used as cement mix content, and the cement mix content and formation density of the casing well are inverted to solve for them. This allows us to obtain the cement mixing content curve of the casing well as its depth. After normalization, the cement mixing content curve was obtained. ; Step 6: Based on the cross area curve Cement mixing volume curve The quantitative quality control error value within each window interval is calculated using a sliding window method. : ； In the formula, This is the starting position of each window; This indicates the end position of each window; Step 7: For each window interval ,like If the cement sheath quality is less than the first preset threshold, the cement mixture content and formation density corresponding to the window interval are considered to be qualified, and the cement mixture content and formation density corresponding to the window interval are output. ;like If the value is greater than the second preset threshold, the cement ring corresponding to that window interval is considered to be of substandard quality; if If the cement ring corresponding to the window interval is greater than or equal to the first preset threshold and less than or equal to the second preset threshold, then the interval is considered an abnormal interval, based on the cross-area curve. Cement mixing volume curve The process of correcting the cement mixing amount of the corresponding cement ring in the window interval is completed by using the intersection area of ​​the window interval as the corresponding cement mixing amount.

2. The quantitative quality control method for the properties of through-casing cement based on natural gamma as described in claim 1, characterized in that, Step 7 also outputs the corrected cement mixing quantity curve for cement quality control.

3. The quantitative quality control method for the properties of through-casing cement based on natural gamma as described in claim 1, characterized in that, The specific preprocessing steps in step 2 are as follows: Step 2.1: Use interpolation to remove outliers; Step 2.2: Use interpolation to fill in the missing values; Step 2.3: Align the natural gamma curves of open-hole and cased-hole wells at depth by means of translation and resolution matching.

4. The quantitative quality control method for the properties of through-casing cement based on natural gamma as described in claim 1, characterized in that, In step 4, the cross-area curves of GR and GRCC* within the well depth detection range are obtained. The specific process is as follows: Assuming the sliding step size is t, and P sliding window data processing operations are performed within the well depth detection range, then the th... The set of data points within each sliding window is Where n is the total number of data points contained within the sliding window. For the first sliding window One data point; Calculate GR and GRCC* in the first... The cross area within a sliding window : ； In the formula, Gamma ray intensity, Indicates GR; Indicates GRCC*; Based on the cross area within each sliding window, the cross area curve that varies with the position of the sliding window is obtained. .

5. The quantitative quality control method for the properties of through-casing cement based on natural gamma as described in claim 1, characterized in that, Step 5 uses the Monte Carlo method for simulation.

6. The quantitative quality control method for the properties of through-casing cement based on natural gamma as described in claim 1, characterized in that, The specific formula affecting the relation function in step 5 is as follows: ； In the formula, , , , , , and All are fitting coefficients; This will affect the relational function. This item is used as the amount of cement to mix.

7. The quantitative quality control method for the properties of through-casing cement based on natural gamma as described in claim 1, characterized in that, In step 7, the first preset threshold is set to 0.2, and the second preset threshold is set to 0.

8.

8. A quantitative quality control system for the properties of through-casing cement based on natural gamma radiation, used to implement the quantitative quality control method for the properties of through-casing cement based on natural gamma radiation as described in any one of claims 1 to 7, characterized in that, It includes a natural gamma logging module, a preprocessing module, a correction module, a cross-area curve calculation module, a cement mixing quantity curve calculation module, a quantitative quality control error value calculation module, and a quantitative quality control result output and correction module; among which: The natural gamma logging module is used to measure the natural gamma curves of open-hole and cased wells as well depth, and input them into the preprocessing module; The preprocessing module is used to preprocess outliers and missing values ​​in the natural gamma curves of open hole wells and cased wells. The preprocessed natural gamma curve GR of the open hole well is input to the cross area curve calculation module, and the preprocessed natural gamma curve GRCC of the cased well is input to the correction module. The correction module is used to correct the well diameter, mud density and casing thickness of the pre-processed natural gamma curve GRCC of the casing well. The corrected natural gamma curve GRCC* of the casing well is then input into the cross area curve calculation module. The cross-area curve calculation module is used to obtain the cross-area curve of GR and GRCC* within the well depth detection range. Input the value into the quantitative quality control error value calculation module; The cement mixing volume curve calculation module is used to fit the gamma count of the detector at different depths of the medium in the casing well formation density measurement. The influence relationship function is used to determine the expression for cement mixture quantity, and the cement mixture quantity and formation density of the casing well are solved by inversion. This allows us to obtain the cement mixing content curve of the casing well as its depth. Input the value into the quantitative quality control error value calculation module; The quantitative quality control error value calculation module is used to calculate... and Quantitative quality control error values ​​between ; The quantitative quality control result output and correction module is used to output and correct the results. The results are compared with the first preset threshold and the second preset threshold. Based on the comparison results, the quantitative quality control results of the cement ring are output, and the results are classified as follows: those falling between the first preset threshold and the second preset threshold are... ,according to Correction .

9. A terminal, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method for quantitative quality control of the properties of through-casing cement based on natural gamma, as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the quantitative quality control method for the properties of through-sleeve cement based on natural gamma, as described in any one of claims 1 to 7.

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