Method, device, model and system for correcting while-drilling neutron porosity logging

Abstract

The invention provides a correction method, device, model and system for neutron porosity logging while drilling. According to the while-drilling controllable source porosity logging instrument model, performing simulation analysis on the near-far thermal neutron counting ratio response under different environmental parameters to obtain a simulated neutron data set; according to the simulated neutron data set, performing fitting processing on the real porosity of the stratum to obtain an apparent porosity calculation formula; according to an apparent porosity calculation formula, processing the target environment parameters, and generating a discrete correction value formula for describing a corresponding relationship between the porosity correction value and the apparent porosity under each target environment parameter value; and completing continuous correction of the while-drilling neutron porosity logging based on the correction value formula and the target environment parameters. The discrete influence of environmental factors is converted into a continuous function, dynamic correction under the complex borehole condition is completed, and an efficient and high-precision solution is provided for neutron porosity logging under the complex borehole condition.

Description

Technical Field

[0001] This application relates to the field of porosity logging technology, and in particular to a correction method, device, model and system for neutron porosity logging while drilling. Background Technology

[0002] In the exploration and development of oil and gas resources such as petroleum and natural gas, logging while drilling (LWD) technology is one of the core methods for obtaining subsurface formation parameters. Among them, neutron porosity logging, which involves emitting neutrons into the formation and utilizing the interaction between neutrons and hydrogen nuclei in the formation pores, measures formation porosity and is an important method for evaluating reservoir properties. However, controlled-source neutron porosity logging while drilling faces challenges from complex wellbore environments.

[0003] Current neutron porosity logging correction techniques mainly rely on traditional chemical source and discrete chart correction methods. Chemical source logging establishes a correction model based on the linear or nonlinear relationship between the thermal neutron count ratio and porosity; discrete chart correction generates discrete data tables by simulating logging responses under different environmental factors, and then corrects the data manually using tables or empirical formulas.

[0004] However, the above-mentioned technical solutions cannot handle scenarios with multiple coupled factors, and the coverage of discrete data points is limited, which reduces the correction efficiency and accuracy. Summary of the Invention

[0005] This application provides a method, apparatus, model, and system for correcting neutron porosity logging while drilling, in order to solve the technical problems that existing neutron porosity logging correction technologies cannot handle multi-factor coupled scenarios and have limited coverage of discrete data points, resulting in low correction efficiency and accuracy.

[0006] In a first aspect, embodiments of this application provide a correction method for neutron porosity logging while drilling, including:

[0007] Obtain a simulated neutron dataset, which is a dataset obtained by simulating and analyzing the near- and far-field thermal neutron count ratio response under different environmental parameters based on the controlled-source porosity logging instrument model while drilling. The environmental parameters are wellbore and / or formation conditions that affect the neutron porosity logging response.

[0008] Based on the simulated neutron dataset, the actual porosity of the formation is fitted to obtain the apparent porosity calculation formula.

[0009] Based on the apparent aperture calculation formula, the target environmental parameters are processed to generate a discrete correction formula. The discrete correction formula is used to describe the correspondence between the aperture correction amount and the apparent aperture for each value of the target environmental parameter.

[0010] Based on the discrete correction formula and the target environmental parameters, a continuous correction formula is obtained, which is used to complete the continuous correction of the neutron porosity logging while drilling.

[0011] Furthermore, based on the discrete correction formula and the target environmental parameters, a continuous correction formula is obtained, including:

[0012] Based on the discrete correction formula and the target environment parameters, determine the target discrete correction formula under the target environment parameters;

[0013] Determine the target discrete correction coefficients based on the target discrete correction formula;

[0014] The discrete correction coefficients of the target and the target environmental parameters are fitted to obtain a continuous correction formula.

[0015] Furthermore, the discrete correction coefficients of the target and the target environmental parameters are fitted to obtain a continuous correction formula, including:

[0016] Regression analysis is performed on the values ​​of the target discrete correction coefficient and the target environmental parameter to obtain a polynomial function relationship, which is the relationship between the target discrete correction coefficient and the target environmental parameter.

[0017] The polynomial function relationship is substituted into the target discrete correction formula for fitting to obtain the continuous correction formula.

[0018] Furthermore, based on the aforementioned aperture clearance calculation formula, the target environmental parameters are processed to generate a discrete correction formula, including:

[0019] Determine the target environmental parameters and the actual porosity under the target environmental parameters;

[0020] Calculate the aperture under the target environmental parameters according to the aperture calculation formula.

[0021] The porosity is compared with the apparent porosity under the target environmental parameters to obtain the porosity correction amount.

[0022] Using the apparent porosity under the target environmental parameters as the independent variable, the porosity correction amount is fitted by a function to obtain the discrete correction amount formula.

[0023] Furthermore, after performing regression analysis on the values ​​of the target discrete correction coefficients and the target environmental parameters to obtain a polynomial function relationship, the method further includes:

[0024] Based on the target environmental parameters, determine the environmental parameter cross terms;

[0025] Based on the environmental parameter cross terms, the polynomial function relationship is subjected to dimensional expansion processing to obtain the updated polynomial function relationship;

[0026] The updated polynomial function relationship is substituted into the target discrete correction formula for fitting to obtain the continuous correction formula.

[0027] Furthermore, based on the simulated sub-dataset, the actual formation porosity is fitted to obtain the apparent porosity calculation formula, including:

[0028] Based on the simulated neutron dataset, determine the near- and far-field thermal neutron count ratios under each of the target environmental parameters and under each of the actual porosities of the formation;

[0029] Based on the near-far thermal neutron count ratios of each formation, the actual porosity of each formation is fitted to obtain the apparent porosity calculation formula.

[0030] Furthermore, the wellbore and / or formation conditions include wellbore diameter, eccentricity, mud salinity, formation water salinity, temperature, and pressure.

[0031] Secondly, embodiments of this application provide a correction device for neutron porosity logging while drilling, comprising:

[0032] The simulated neutron dataset acquisition module is used to acquire a simulated neutron dataset, which is a dataset obtained by simulating and analyzing the near- and far-field thermal neutron count ratio response under different environmental parameters based on the controllable source porosity logging instrument model while drilling. The environmental parameters are wellbore and / or formation conditions that affect the neutron porosity logging response.

[0033] The apparent porosity calculation formula acquisition module is used to fit the actual porosity of the formation based on the simulated sub-data set to obtain the apparent porosity calculation formula.

[0034] The discrete correction formula generation module is used to process the target environment parameters according to the apparent aperture calculation formula and generate a discrete correction formula. The discrete correction formula is used to describe the correspondence between the aperture correction amount and the apparent aperture under different values ​​of the target environment parameters.

[0035] The continuous correction formula generation module is used to obtain a continuous correction formula based on the discrete correction formula and the target environmental parameters. The continuous correction formula is used to complete the continuous correction of the neutron porosity logging while drilling.

[0036] Thirdly, embodiments of this application provide a model of a controlled-source porosity logging instrument while drilling, including:

[0037] The shield is a pulsed neutron source made of tungsten metal;

[0038] The near-thermal neutron detector and the far-thermal neutron detector are provided, wherein the sensitive medium of the near-thermal neutron detector and the far-thermal neutron detector is a ³He tube.

[0039] Fourthly, embodiments of this application provide a correction system for neutron porosity logging while drilling, including a computer program that, when executed by a processor, implements the method described in any of the first aspects.

[0040] This application provides a correction method, device, model, and system for neutron porosity logging while drilling. Based on a controlled-source porosity logging instrument model, the near- and far-field thermal neutron count ratio responses under different environmental parameters are simulated and analyzed to obtain a simulated neutron dataset. Based on the simulated neutron dataset, the actual formation porosity is fitted to obtain a formula for calculating apparent porosity. Based on the apparent porosity calculation formula, the target environmental parameters are processed to generate a discrete correction formula describing the correspondence between the porosity correction amount and the apparent porosity for each target environmental parameter value. Based on the correction formula and the target environmental parameters, continuous correction of neutron porosity logging while drilling is completed. This transforms the discrete influence of environmental factors into a continuous function, achieving dynamic correction under complex wellbore conditions and providing an efficient and high-precision solution for neutron porosity logging under complex wellbore conditions. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0042] Figure 1 A schematic flowchart of Embodiment 1 of the correction method for neutron porosity logging while drilling provided in this application;

[0043] Figure 2 A schematic flowchart of Embodiment 2 of the correction method for neutron porosity logging while drilling provided in this application;

[0044] Figure 3 A schematic flowchart of Embodiment 3 of the correction method for neutron porosity logging while drilling provided in this application;

[0045] Figure 4 This is the standard well logging response diagram proposed in this application;

[0046] Figure 5 This is a diagram illustrating the effect of wellbore discretization correction proposed in this application;

[0047] Figure 6 The effect diagram of discretization correction for eccentricity, formation water salinity, mud salinity, temperature and pressure provided for this application;

[0048] Figure 7 A schematic diagram of the structure of the correction device for logging-while-drilling neutron porosity provided in this application;

[0049] Figure 8 This is a schematic diagram of the structure of the controlled-source porosity logging instrument model proposed in this application.

[0050] The accompanying drawings have illustrated specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0051] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0052] This application applies to controlled-source neutron porosity logging scenarios during drilling in oil and gas exploration. Its typical network architecture includes a neutron generator (such as a tungsten-shielded pulsed neutron source, PNG), a 3He neutron detector, a wellbore environment simulation module (such as parameters like wellbore diameter, eccentricity, and mud salinity), and a data processing unit. During drilling operations, the logging instrument acquires near-field and far-field thermal neutron count ratio data in real time. A dynamic correction formula eliminates interference from wellbore environmental factors (such as wellbore diameter variations, instrument eccentricity, and salinity differences) on porosity measurements, ultimately outputting the corrected formation porosity value, providing a reliable basis for reservoir evaluation and drilling decisions.

[0053] Based on the above scenarios, it is evident that existing calibration methods for chemical source neutron logging rely on discrete charts or empirical formulas. Their calibration models are constructed based on specific wellbore conditions and cannot adapt to the high-energy neutron characteristics of controlled-source neutron logging. Traditional methods require factor-by-factor lookup corrections, resulting in a cumbersome calibration process and limited accuracy, especially in scenarios with multiple coupled factors (such as the coexistence of high-temperature, high-pressure wells and high-salinity drilling mud), where calibration errors are significant. Furthermore, discrete charts cannot cover unsimulated environmental parameters (such as non-standard wellbore diameters or extreme temperatures), limiting the generalization ability of the calibration methods.

[0054] This application constructs a mathematical modeling and continuous correction framework to transform the influence of multiple environmental factors in controlled-source neutron porosity logging while drilling into dynamically adaptable mathematical relationships, thereby achieving efficient and high-precision correction under complex wellbore conditions. This concept is based on simulation of a controlled-source neutron logging instrument model while drilling, combining cubic equation fitting and continuous formula derivation to overcome the limitations of traditional discrete chart correction, solve the correction problem in multi-factor coupled scenarios, and achieve adaptive correction of unsimulated environmental data through mathematical modeling.

[0055] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0056] Figure 1 This is a schematic flowchart of an embodiment of the correction method for neutron porosity logging while drilling provided in this application. Figure 1 As shown, the method includes:

[0057] S101. Obtain the simulated sub-dataset.

[0058] The simulated neutron dataset is a dataset obtained by simulating and analyzing the near- and far-field thermal neutron count ratio responses under different environmental parameters based on the controlled-source porosity logging instrument model during drilling. The environmental parameters are the wellbore and / or formation conditions that affect the neutron porosity logging response. The wellbore and / or formation conditions include well diameter, eccentricity, mud salinity, formation water salinity, temperature, and pressure.

[0059] Specifically, a controlled-source porosity logging instrument model is first established based on the instrument's dimensions, component composition, and other relevant parameters. This model is constructed based on the instrument's actual physical dimensions (e.g., an outer diameter of 7.42 inches) and internal structure (including the pulsed neutron source PNG, near / far thermal neutron detectors, etc.). Subsequently, the formation lithology is set as limestone, the pore fluid as water, and simulations are performed within a porosity range of 0% to 40% (e.g., in 5% increments).

[0060] In one feasible approach, when establishing a controlled-source porosity logging (VRLP) instrument model, the Monte Carlo method is used to simulate the interaction between neutrons and the formation (e.g., neutron deceleration paths), or finite element analysis is used to simulate the microstructure of instrument components (e.g., the boron sheath shielding characteristics of the detector). For example, when simulating wellbore variations, the Monte Carlo method can refine the collision process between neutrons and the wellbore wall, ensuring the accuracy of the thermal neutron count ratio. Exemplarily, when simulating high-diameter scenarios, the sampling density of the wellbore wall collision process is increased to ensure the reliability of the calibration formula under extreme conditions. This technique provides higher-quality foundational data for constructing calibration formulas, resolving the calibration bias problem caused by the neglect of microscopic characteristics in traditional models.

[0061] On the other hand, when establishing a controlled-source porosity logging instrument model for drilling, parameter sensitivity analysis is used to identify the environmental factors (such as well diameter D and eccentricity e) that have the greatest impact on the thermal neutron count ratio response, and simulation parameter settings are optimized accordingly (such as increasing the sampling density for highly sensitive factors). For example, when simulating well diameter changes, the sampling density for high-diameter scenarios is increased to ensure the reliability of the calibration formula under extreme conditions.

[0062] For the model settings of the wellbore environment and formation environment, the formation lithology is ensured to be limestone, the pore fluid is water, and the remaining environmental influencing factors to be investigated include: well diameter, eccentricity, mud salinity, formation water salinity, temperature and pressure. Different influencing factors also have different values. The near-far thermal neutron count ratio response of the formation under various conditions was simulated.

[0063] The key is to systematically change and simulate a variety of environmental parameters, including but not limited to: wellbore (D, e.g., 8 inches, 8.5 inches, 10 inches, 11 inches, 12 inches), eccentricity (e, e.g., -0.5 inches, -0.25 inches, 0 inches, 0.25 inches, 0.5 inches), mud salinity (Cm, e.g., 0, 50, 150, 200 kppm), formation water salinity (Cw, e.g., 0, 10, 50, 100 kppm), temperature (T, e.g., 25°C, 50°C, 75°C, 125°C, 175°C), and pressure (P, e.g., 0.1, 100, 150, 200 MPa).

[0064] The purpose of this application is to construct a comprehensive and reliable database, laying the foundation for the derivation of all subsequent calibration formulas. Through systematic numerical simulation, a "digital chart" covering a wide range of operating conditions was constructed, overcoming the shortcomings of high cost and limited data points in traditional physical experiments, and providing sufficient data support for subsequent continuous calibration.

[0065] S102. Based on the simulated neutron dataset, determine the near-far thermal neutron count ratio under each target environmental parameter and the actual porosity of each formation.

[0066] In this step, the first step is to define the setup conditions for the standard well, such as: 8-inch diameter, no eccentricity, mud and formation water salinity of 0 kppm, temperature of 25℃, and pressure of 0.1 MPa.

[0067] Then, based on the simulation data of S101, the near-far thermal neutron count ratio corresponding to the true porosity of different formations under the standard conditions is extracted.

[0068] This step establishes a standard wellbore environment benchmark, providing a unified reference standard for the subsequent calibration of the porosity calculation formula. This ensures the benchmark consistency of the calibration system and avoids systematic errors caused by inconsistent benchmarks.

[0069] S103. Based on the near-far thermal neutron count ratio, the actual porosity of each stratum is fitted to obtain the apparent porosity calculation formula.

[0070] Apparent porosity is the apparent porosity calculated based on the count ratio and needs to be corrected to the true porosity using a correction formula.

[0071] In this step, the near-far thermal neutron ratio and porosity under standard well conditions are fitted to obtain the apparent porosity calculation formula, and it is ensured that the apparent porosity calculation formula can accurately calculate porosity under standard well conditions.

[0072] Specifically, the standard well setup conditions are as follows: well diameter 8 inches, eccentricity 0 inches, mud salinity 0 kppm, formation water salinity 0 kppm, temperature 25°C, pressure 0.1 MPa, and formation lithology of limestone.

[0073] The near- and far-field thermal neutron count ratios were obtained through MCNP simulations. A graph showing the response relationship between the near- and far-field thermal neutron count ratios and porosity under standard well conditions was plotted. Using this data, the apparent porosity calculation formula was derived as follows:

[0074]

[0075] Where φ is the apparent porosity and R is the thermal neutron count ratio. This formula can accurately convert the count ratio into apparent porosity under standard well conditions, and its calculation results are basically consistent with the actual porosity, with an error close to zero.

[0076] The apparent porosity calculation formula established by the nonlinear fitting in this application can accurately characterize the mapping relationship between the count ratio and porosity under standard conditions, providing a reliable benchmark for subsequent environmental factor correction and ensuring the accuracy of the correction process.

[0077] S104. Based on the apparent aperture calculation formula, process the target environmental parameters to generate a discrete correction formula.

[0078] The discrete correction formula is used to describe the correspondence between the porosity correction and the apparent porosity for each target environmental parameter value.

[0079] In this step, the apparent porosity of limestone under different influencing factors is calculated, and the porosity correction Δφ is obtained. A cubic equation is fitted to the porosity correction Δφ and the apparent porosity φ to obtain the formula for the porosity correction under discrete conditions of different influencing factors, as follows:

[0080]

[0081] Where a, b, c, and d are coefficients related to the selected target environmental parameter values.

[0082] The discrete correction formula established by the step of this application through cubic polynomial fitting can accurately describe the correction law under a specific value of a single environmental factor, solving the problem that traditional charts can only provide finite discrete correction values, and laying the mathematical model foundation for continuous correction.

[0083] S105. Based on the discrete correction formula and the target environment parameters, the continuous correction formula is obtained.

[0084] The continuous correction formula is used to complete the continuous correction of neutron porosity logging while drilling.

[0085] When constructing the continuous correction formula, the coefficients (such as cubic polynomial coefficients a, b, c, d) in the discrete correction formula are first extracted. Then, these coefficients are used to establish a polynomial function relationship with environmental parameters (such as well diameter D and eccentricity e). Finally, these functional relationships are substituted into the discrete correction formula of S104 to obtain a final continuous correction formula in which the coefficients can change continuously with the environmental parameters, ensuring the correction results under any environmental parameter value.

[0086] This application's embodiments address the inefficiency and coverage limitations of traditional discrete map calibration methods by constructing a continuous calibration formula. By establishing a logging instrument model to simulate responses under different environmental parameters, it provides foundational data for subsequent calibration. A discrete calibration formula is generated based on nonlinear fitting to ensure calibration accuracy for specific environmental parameter values. Finally, by fitting the mathematical relationship between the coefficients of the discrete formula and the environmental parameters, a continuous calibration formula is constructed. This allows the calibration results to dynamically adapt to any environmental parameter value, reducing the tedious manual table lookup and minimizing error accumulation in multi-factor coupled scenarios. This dynamic adaptation provides an efficient and high-precision solution for neutron porosity logging under complex wellbore conditions.

[0087] Figure 2This is a schematic flowchart of Embodiment 2 of the correction method for neutron porosity logging while drilling provided in this application. Figure 2 As shown, based on Example 1, a continuous correction formula is obtained according to the discrete correction formula and the target environmental parameters, including:

[0088] S201. Based on the discrete correction formula and the target environment parameters, determine the target discrete correction formula under the target environment parameters.

[0089] In this step, for the selected target environmental parameter (e.g., eccentricity e), multiple discrete correction formulas are obtained through step S104 of Example 1 under multiple discrete values, providing a sufficient data basis for subsequent coefficient continuity and ensuring the integrity of the continuity process.

[0090] S202. Determine the target discrete correction coefficient according to the target discrete correction formula.

[0091] In this embodiment of the application, to achieve continuous correction of influencing factors, it is necessary to extract the polynomial coefficients, namely a, b, c, and d, from the discrete correction formulas determined in S201. By extracting the coefficients, the complex correction formulas are decomposed into independently analyzable parameters, creating conditions for establishing a continuous relationship between the coefficients and environmental parameters, and realizing modular processing of complex problems.

[0092] S203. Regression analysis is performed on the values ​​of the target discrete correction coefficient and the target environmental parameters to obtain the polynomial function relationship.

[0093] Among them, the polynomial function relationship is the relationship between the target discrete correction coefficient and the target environmental parameters.

[0094] Specifically, in this step, the coefficients (a, b, c, d) extracted in S202 are fitted with cubic polynomials to the values ​​of the target environmental parameter (e) to establish a continuous relationship between the coefficients and the environmental parameter.

[0095] For example, taking the continuous correction study of eccentricity as an example, the four coefficients a, b, c, and d in the formula for calculating the eccentricity porosity correction under different well diameter conditions are extracted to obtain the relationship between the four coefficients and the eccentricity, and a cubic polynomial fit is performed on them:

[0096]

[0097] Then, by substituting this cubic polynomial into the porosity correction formula, we can obtain the continuous calculation formula for the porosity correction, which in turn yields the continuous correction formula for the eccentricity.

[0098] The cubic equation fitting proposed in this step captures the complex relationship between the porosity correction Δφ and the apparent porosity φ more accurately through nonlinear modeling. For example, in scenarios where mineralization and temperature change together, the higher-order terms (φ³) of the cubic equation can explicitly model such nonlinear relationships, significantly reducing the errors caused by neglecting higher-order terms in traditional linear models. This technique provides a more flexible mathematical tool for correction in complex wellbore environments and solves the problem of insufficient adaptability of traditional models in nonlinear scenarios.

[0099] S204. Substitute the polynomial function relationship into the target discrete correction formula for fitting to obtain the continuous correction formula.

[0100] In another embodiment of this application, after performing regression analysis on the values ​​of the target discrete correction coefficients and the target environmental parameters to obtain the polynomial function relationship, the following steps can be performed:

[0101] Based on the target environmental parameters, environmental parameter interaction terms are determined. Specifically, when there are two or more target environmental parameters, such as considering both wellbore diameter and eccentricity, environmental parameter interaction terms need to be constructed to accurately characterize the synergistic effect (i.e., interaction effect) of these two environmental factors on the correction coefficient. Interaction terms are combinations of products of different environmental parameter variables. By introducing these interaction terms, the correction model can capture the nonlinear response generated by the combined effect of multiple parameters, which cannot be described by changes in a single environmental parameter.

[0102] Secondly, based on the interaction terms of the environmental parameters, the polynomial function relationship is expanded in dimension to obtain an updated polynomial function relationship. Specifically, the interaction terms of the environmental parameters are added as new independent variables to the initial polynomial function relationship established in step S203. For example, the initial coefficient function is only a function of a single environmental parameter (such as eccentricity); after dimensional expansion, the updated coefficient function becomes a function of multiple environmental parameters (such as well diameter and eccentricity) and their interaction terms. By performing a new round of regression analysis (such as multiple linear regression or nonlinear least squares fitting) on ​​the expanded variable set (including the original parameters and interaction terms), the updated, dimensionally expanded polynomial function relationship can be obtained.

[0103] Finally, the updated polynomial function relationship is substituted into the target discrete correction formula for fitting, resulting in a continuous correction formula. Specifically, this step is consistent with the core operation of step S204, but uses a more precise "updated polynomial function relationship". Substituting the updated coefficient function into the discrete correction formula, a multidimensional continuous correction formula capable of simultaneously and continuously responding to multiple environmental parameters and their interactions is obtained.

[0104] The steps described above explicitly model the synergistic or offsetting effects between different environmental factors by introducing environmental parameter interaction terms. For example, in the complex scenario of "large wellbore accompanied by instrument eccentricity," the effects of wellbore diameter and eccentricity on thermal neutron flux are not simply linear superpositions. Interaction terms can dynamically adjust the correction coefficients to accurately capture this coupling effect, thereby solving the error accumulation problem caused by neglecting interaction in traditional single-factor sequential correction or simple superposition correction.

[0105] Furthermore, it achieves true multi-factor synchronous continuous correction: the correction formula built based on this extended step is a unified mathematical model. In practical applications, only all relevant, measured environmental parameter values ​​need to be input once to directly output a comprehensive porosity correction, eliminating the need for tedious, potentially error-inducing, multi-step chart lookup and interpolation calculations. This greatly simplifies the operation process and improves correction efficiency and reliability.

[0106] Meanwhile, the generalization and predictive ability of the correction method proposed in this application are enhanced: since the model structure itself contains the mathematical expression of the interaction between factors, even for some multi-factor combination conditions that are not fully covered by the training data (simulation data), the model can make more reasonable predictions through its inherent mathematical relationships, showing stronger extrapolation ability and adaptability, and providing strong technical support for accurate logging under extreme or atypical well conditions.

[0107] In this embodiment, polynomial function modeling is used, and the continuous correction formula can accurately express the dynamic relationship between environmental parameters and correction coefficients, eliminating the correction blind zone of discrete plots under non-standard well diameters. In addition, the explicit expression of polynomial functions supports adaptive correction for unsimulated environmental parameters (such as non-standard eccentricity or extreme mineralization), significantly improving the generalization ability of the correction results.

[0108] Figure 3 This is a schematic flowchart of Embodiment 3 of the correction method for neutron porosity logging while drilling provided in this application. Figure 3 As shown, based on Example 1, the target environmental parameters are processed according to the apparent aperture calculation formula to generate a discrete correction formula, including:

[0109] S301. Determine the target environmental parameters and the actual porosity under the target environmental parameters.

[0110] In this embodiment of the application, it is necessary to simulate different values ​​of various influencing factors (well diameter, eccentricity, mud salinity, formation water salinity, temperature and pressure) within a porosity range of 0-40% to obtain the near-far thermal neutron count ratio.

[0111] For example, a target environmental parameter to be studied (e.g., well diameter D) is selected, and a series of discrete values ​​to be simulated are determined. Simultaneously, the simulation range (0-40%) and step size of the formation's true porosity are determined. This systematic parameter setting ensures the comprehensiveness and representativeness of the discrete correction formulas, providing a guarantee for establishing a reliable correction system.

[0112] S302. Calculate the aperture under the target environmental parameters according to the aperture calculation formula.

[0113] In this step, the thermal neutron count ratios obtained from the simulation of S101 under different well diameters and different actual porosities are substituted into the apparent porosity calculation formula obtained from S103 to calculate the apparent porosity φ under the corresponding working conditions.

[0114] The use of a unified formula for calculating apparent aperture ensures the consistency of calculation results under different environmental conditions, providing a reliable basis for the accurate calculation of subsequent correction quantities.

[0115] S303. Compare the actual porosity with the apparent porosity under the target environmental parameters to obtain the porosity correction amount.

[0116] In this step, the apparent porosity φ is compared with the actual formation porosity φ. tu By comparison, the porosity correction amount Δφ is obtained, and the formula is as follows:

[0117]

[0118] Where, φ tu φ represents the actual porosity of the formation; φ represents the apparent porosity. The calculated porosity correction value Δφ provides a clear optimization objective for establishing an accurate correction model.

[0119] S304. Using the apparent porosity under the target environmental parameters as the independent variable, perform a function fitting on the porosity correction amount to obtain the discrete correction amount formula.

[0120] In this step, a cubic function is fitted to the porosity correction amount under the same well diameter conditions to obtain the discrete correction amount formula for that specific well diameter (D), as follows:

[0121]

[0122] Where D is the well diameter.

[0123] Finally, substituting the apparent porosity into the fitting formula, we obtain the porosity correction amount calculated using the mathematical representation relationship. The corrected porosity is then:

[0124]

[0125] Where, φ c To correct the porosity, cubic function fitting can accurately capture the nonlinear characteristics of the correction amount as a function of apparent porosity. Compared with traditional linear or quadratic fitting, it has higher accuracy and provides a high-quality discrete basic model for subsequent continuous correction.

[0126] This application embodiment systematically determines the target environmental parameters and the actual porosity, calculates the apparent porosity, compares and obtains the correction amount, and performs cubic function fitting to construct a high-precision discrete correction amount formula. This solves the problems of inaccurate correction and large interpolation error caused by the traditional chart method relying on finite discrete data points, and provides a reliable and accurate mathematical model foundation for subsequent continuous correction.

[0127] Figure 4 This is the standard well logging response diagram proposed in this application. (Example:) Figure 4 As shown in Example 1, the apparent porosity under standard well conditions was calculated using the porosity calculation formula and compared with the actual porosity. The results showed that the apparent porosity under different actual porosity conditions basically fell on the diagonal, that is, the error between the apparent porosity and the actual porosity under standard well conditions was basically 0, which verified the effectiveness of the apparent porosity calculation formula.

[0128] Figure 5 This is a diagram illustrating the effect of wellbore discretization correction proposed in this application. Figure 5 As shown, in Figure 3 Based on the examples, taking the continuous correction study of well diameter as an example, the Monte Carlo method was used to simulate controlled source porosity logging while drilling under well diameters of 8 inches, 8.5 inches, 10 inches, 11 inches and 12 inches to obtain the near and far thermal neutron counts of the instrument detector. Then, the logging response effect diagram was plotted with the thermal neutron count ratio under different well diameter conditions and the actual formation porosity. Finally, the apparent porosity can be obtained using the apparent porosity calculation formula.

[0129] Figure 6 The diagram shows the effect of discretization correction for eccentricity, formation water salinity, mud salinity, temperature, and pressure provided in this application. (See attached image.) Figure 6 As shown, in Figure 3 Based on the examples, the correction steps for influencing factors such as eccentricity, formation water salinity, mud salinity, temperature, and pressure are shown.

[0130] Figure 7 A schematic diagram of the correction device for neutron porosity logging while drilling provided in this application. Figure 7 As shown, the calibration device 70 for neutron porosity logging while drilling provided in this embodiment includes:

[0131] The simulated neutron dataset acquisition module 701 is used to acquire the simulated neutron dataset. The simulated neutron dataset is a dataset obtained by simulating and analyzing the near- and far-field thermal neutron count ratio response under different environmental parameters based on the controllable source porosity logging instrument model while drilling. The environmental parameters are the wellbore and / or formation conditions that affect the neutron porosity logging response.

[0132] The apparent porosity calculation formula is obtained by module 702, which is used to fit the actual porosity of the formation based on the simulated neutron dataset to obtain the apparent porosity calculation formula.

[0133] The discrete correction formula generation module 703 is used to process the target environment parameters according to the apparent aperture calculation formula and generate a discrete correction formula. The discrete correction formula is used to describe the correspondence between the porosity correction and the apparent aperture under different target environment parameter values.

[0134] The continuous correction formula is obtained by module 704, which is used to obtain the continuous correction formula based on the discrete correction formula and the target environmental parameters. The continuous correction formula is used to complete the continuous correction of neutron porosity logging while drilling.

[0135] In one feasible approach, the continuous correction formula obtaining module 704 is further specifically used for:

[0136] Based on the discrete correction formula and the target environment parameters, determine the target discrete correction formula under the target environment parameters;

[0137] Determine the target discrete correction coefficients based on the target discrete correction formula;

[0138] By fitting the discrete correction coefficients of the target and the target environmental parameters, a continuous correction formula is obtained.

[0139] Wellbore and / or formation conditions include wellbore diameter, eccentricity, mud salinity, formation water salinity, temperature, and pressure.

[0140] In one feasible approach, the continuous correction formula obtaining module 704 is further specifically used for:

[0141] Regression analysis was performed on the values ​​of the target discrete correction coefficient and the target environmental parameters to obtain a polynomial function relationship, which is the relationship between the target discrete correction coefficient and the target environmental parameters.

[0142] By substituting the polynomial function relationship into the target discrete correction formula for fitting, a continuous correction formula is obtained.

[0143] In one implementable manner, the discrete correction formula generation module 703 is further specifically used for:

[0144] Determine the target environmental parameters and the actual porosity under the target environmental parameters;

[0145] Calculate the apparent aperture under the target environmental parameters according to the apparent aperture calculation formula;

[0146] The porosity correction amount is obtained by comparing the actual porosity with the apparent porosity under the target environmental parameters.

[0147] Using the apparent porosity under the target environmental parameters as the independent variable, a function fitting is performed on the porosity correction amount to obtain the discrete correction amount formula.

[0148] In one implementable manner, the discrete correction formula generation module 703 is further specifically used for:

[0149] Based on the target environmental parameters, determine the environmental parameter interaction terms;

[0150] Based on the interaction terms of environmental parameters, the dimensionality of the polynomial function relationship is expanded to obtain the updated polynomial function relationship;

[0151] The updated polynomial function relationship is substituted into the target discrete correction formula for fitting, resulting in a continuous correction formula.

[0152] In one feasible approach, the apparent porosity calculation formula obtaining module 702 is also specifically used for:

[0153] Based on the simulated neutron dataset, the near-far thermal neutron count ratio was determined under various target environmental parameters and under the actual porosity of various formations.

[0154] Based on the near-far thermal neutron count ratios, the actual porosity of each formation is fitted to obtain the apparent porosity calculation formula.

[0155] The calibration device for neutron porosity logging while drilling provided in this embodiment can perform the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0156] Figure 8 This is a schematic diagram of the structure of the controlled-source porosity logging instrument model proposed in this application. Figure 8 As shown, the controlled-source porosity logging instrument model 80 includes:

[0157] The shield is a pulsed neutron source made of tungsten metal;

[0158] The near-thermal neutron detector and the far-thermal neutron detector are both sensitive to He tubes.

[0159] Specifically, the near-ultrathermal neutron detector is used to detect neutron flux, along with a near-thermal neutron detector, a near-gamma detector, two far-thermal neutron detectors, and a far-gamma detector (the gamma detector is used for other logging methods in the logging-while-drilling instrument). The long and short source distances of the neutron detectors are 27.3 in (69.342 cm) and 11.3 in (28.702 cm), respectively. The detectors are wrapped with boron sleeves on the side facing the instrument to eliminate the influence of thermal neutrons generated inside the instrument.

[0160] The lithology is limestone, the pore fluid is water, the porosity range is 0-40%, and the step size is 5%. The well diameter D is set to five values: 8in, 8.5in, 10in, 11in, and 12in; the eccentricity e is set to five values: -0.5in, -0.25in, 0in, 0.25in, and 0.5in. Positive eccentricity indicates the instrument is offset to the same side of the formation being probed, while negative eccentricity indicates the opposite direction. Formation water salinity Cw is set to four values: 0 kppm, 10 kppm, 50 kppm, and 100 kppm; mud salinity Cm is set to four values: 0 kppm, 50 kppm, 150 kppm, and 200 kppm; pressure P is set to five values: 0.1 MPa, 100 MPa, 150 MPa, and 200 MPa; and temperature T is set to five values: 25℃, 50℃, 75℃, 125℃, and 175℃. Figure 2 The diagram shows the apparatus, wellbore, and formation model for controlled-source logging while drilling.

[0161] This application also provides a correction system for neutron porosity logging while drilling, including a computer program that, when executed by a processor, implements the above-described method.

[0162] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0163] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0164] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0165] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for correcting neutron porosity logging while drilling, characterized in that, include: Obtain a simulated neutron dataset, which is a dataset obtained by simulating and analyzing the near- and far-field thermal neutron count ratio response under different environmental parameters based on the controlled-source porosity logging instrument model while drilling. The environmental parameters are wellbore and / or formation conditions that affect the neutron porosity logging response. Based on the simulated neutron dataset, the actual porosity of the formation is fitted to obtain the apparent porosity calculation formula. Based on the apparent aperture calculation formula, the target environmental parameters are processed to generate a discrete correction formula. The discrete correction formula is used to describe the correspondence between the aperture correction amount and the apparent aperture for each value of the target environmental parameter. Based on the discrete correction formula and the target environmental parameters, a continuous correction formula is obtained, which is used to complete the continuous correction of the neutron porosity logging while drilling.

2. The correction method according to claim 1, characterized in that, Based on the discrete correction formula and the target environment parameters, a continuous correction formula is obtained, including: Based on the discrete correction formula and the target environment parameters, determine the target discrete correction formula under the target environment parameters; Determine the target discrete correction coefficients based on the target discrete correction formula; The discrete correction coefficients of the target and the target environmental parameters are fitted to obtain a continuous correction formula.

3. The correction method according to claim 2, characterized in that, The discrete correction coefficients of the target and the target environmental parameters are fitted to obtain a continuous correction formula, including: Regression analysis is performed on the values ​​of the target discrete correction coefficient and the target environmental parameter to obtain a polynomial function relationship, which is the relationship between the target discrete correction coefficient and the target environmental parameter. The polynomial function relationship is substituted into the target discrete correction formula for fitting to obtain the continuous correction formula.

4. The correction method according to claim 1, characterized in that, Based on the aforementioned aperture clearance calculation formula, the target environmental parameters are processed to generate a discrete correction formula, including: Determine the target environmental parameters and the actual porosity under the target environmental parameters; Calculate the aperture under the target environmental parameters according to the aperture calculation formula. The porosity is compared with the apparent porosity under the target environmental parameters to obtain the porosity correction amount. Using the apparent porosity under the target environmental parameters as the independent variable, the porosity correction amount is fitted by a function to obtain the discrete correction amount formula.

5. The correction method according to claim 3, characterized in that, After performing regression analysis on the values ​​of the target discrete correction coefficients and the target environmental parameters to obtain a polynomial function relationship, the method further includes: Based on the target environmental parameters, determine the environmental parameter cross terms; Based on the environmental parameter cross terms, the polynomial function relationship is subjected to dimensional expansion processing to obtain the updated polynomial function relationship; The updated polynomial function relationship is substituted into the target discrete correction formula for fitting to obtain the continuous correction formula.

6. The correction method according to any one of claims 1 to 3, characterized in that, Based on the simulated sub-dataset, the actual formation porosity is fitted to obtain the apparent porosity calculation formula, including: Based on the simulated neutron dataset, determine the near- and far-field thermal neutron count ratios under each of the target environmental parameters and under each of the actual porosities of the formation; Based on the near-far thermal neutron count ratios of each formation, the actual porosity of each formation is fitted to obtain the apparent porosity calculation formula.

7. The correction method according to any one of claims 1 to 3, characterized in that, The wellbore and / or formation conditions include wellbore diameter, eccentricity, mud salinity, formation water salinity, temperature, and pressure.

8. A calibration device for neutron porosity logging while drilling, characterized in that, include: The simulated neutron dataset acquisition module is used to acquire the simulated neutron dataset, which is a dataset obtained by simulating and analyzing the near- and far-field thermal neutron count ratio response under different environmental parameters based on the controllable source porosity logging instrument model while drilling. The environmental parameters are the wellbore and / or formation conditions that affect the neutron porosity logging response. The apparent porosity calculation formula acquisition module is used to fit the actual porosity of the formation based on the simulated sub-data set to obtain the apparent porosity calculation formula. The discrete correction formula generation module is used to process the target environment parameters according to the apparent aperture calculation formula and generate a discrete correction formula. The discrete correction formula is used to describe the correspondence between the aperture correction amount and the apparent aperture under different values ​​of the target environment parameters. The continuous correction formula generation module is used to obtain a continuous correction formula based on the discrete correction formula and the target environmental parameters. The continuous correction formula is used to complete the continuous correction of the neutron porosity logging while drilling.

9. A model for a controlled-source porosity logging instrument while drilling, characterized in that, include: The shield is a pulsed neutron source made of tungsten metal; The near-thermal neutron detector and the far-thermal neutron detector are provided, wherein the sensitive medium of the near-thermal neutron detector and the far-thermal neutron detector is a ³He tube.

10. A calibration system for neutron porosity logging while drilling, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

Images