A waterflood identification method based on the dual physical processes of pulsed neutron slowdown and diffusion

Abstract

The present invention discloses a waterflood identification method based on the dual physical processes of pulsed neutron moderation and diffusion, belonging to the technical fields of geophysical logging and oilfield development. A pulsed neutron detection system composed of a D-T controllable neutron tube source and a dual-spacing thermal neutron detector is adopted to extract the thermal neutron count ratio and the macroscopic capture cross-section to quickly realize the evaluation of reservoir waterflooding. This method is based on the interaction processes such as inelastic scattering, elastic scattering, and radiative capture that occur between neutrons and the atomic nuclei of formation elements. By utilizing the characteristics that the moderation process of neutrons is closely related to the hydrogen content in the formation, while the diffusion process is mainly affected by the capture ability of the formation, new parameters are constructed by integrating the two physical processes, significantly improving the response degree to reservoir waterflooding. This method has a high interpretation coincidence rate, can eliminate the influence of formation water salinity and porosity on the evaluation of waterflooded layers, and can provide a theoretical basis and technical support for quickly and accurately identifying the waterflooding situation of reservoir by pulsed neutron lifetime logging.

Description

Technical Field

[0001] The present invention belongs to the technical fields of geophysical logging and oilfield development, and particularly relates to a waterflood identification method based on the dual physical processes of pulsed neutron moderation and diffusion. Background Art

[0002] The exploration and development of oil and gas resources are key factors driving national economic growth and maintaining energy security, and the oil and gas saturation parameter thereof is a key parameter for reserve estimation and development plan formulation. With the continuous deepening of exploration and development, most of the domestic main development oil reservoirs have entered the middle and late stages of development. After years of water injection development, the lithology, physical properties, oil-bearing property, electrical and acoustic properties of the oil and gas layers have changed greatly. The distribution law of remaining oil underground is complex, the waterflooded area of the reservoir is large, and the distribution of high water cut and low water cut areas is unbalanced. Therefore, how to optimize the oilfield development plan, control the water cut, stabilize the oil production, and tap the potential of old wells has become a key problem urgently to be solved in oilfield development.

[0003] As a conventional means for monitoring the remaining oil saturation through casing, pulsed neutron logging technology lays a foundation for the adjustment plans such as water flooding and gas flooding in oilfields. By measuring the gamma rays and thermal neutron information released by the inelastic scattering, radiation capture and other interactions between the 14MeV high-energy fast neutrons generated by a D-T controllable neutron source and the element nuclei in the formation, pore fluid, etc. through the media such as the instrument shell, well fluid, steel casing and cement sheath, the oil and gas saturation is determined. Carbon-oxygen ratio logging, neutron lifetime logging, fast neutron cross-section gas-bearing and chlorine energy spectrum logging, etc. are important methods for measuring the oil saturation through casing and evaluating waterflooded layers. The differences in the wellbore and annulus fluids will significantly affect the determination of the final oil saturation of the formation by these methods, resulting in difficulty in accurately identifying the waterflooded situation in low-porosity tight reservoirs.

[0004] In recent years, pulsed neutron-neutron logging technology has been widely used in determining the remaining oil saturation in medium- and high-salinity formations. This technology accurately evaluates the saturation of the reservoir by measuring the macroscopic capture cross-section of the formation and combining with the rock volume physical model, and has achieved remarkable application effects. This method not only improves the identification accuracy of remaining oil, but also provides more reliable data support in complex formation conditions, providing an important technical guarantee for oilfield development and optimization. However, the traditional method of qualitatively identifying waterflooded layers by neutron lifetime is to identify waterflooded layers through the overlap of the capture cross-section and resistivity logging curves, and its application effect is not ideal when the porosity and formation water salinity change. Therefore, there is an urgent need for a new method that can overcome the limitations of the existing technology. Summary of the Invention

[0005] In view of the above problems existing in the prior art, the present invention proposes a waterflood identification method based on the dual physical processes of pulsed neutron moderation and diffusion, with reasonable design, which solves the deficiencies of the prior art and has good effects.

[0006] A waterflood identification method based on the dual physical processes of pulsed neutron moderation and diffusion, which adopts a dual-detector pulsed neutron detection system composed of a D-T controllable neutron tube source and a dual-spacing thermal neutron detector, and extracts the thermal neutron count ratio and the macroscopic capture cross section to quickly realize the evaluation of reservoir waterflooding. The specific steps are as follows:

[0007] Step 1: Based on the existing detection system composed of a D-T controllable neutron tube source and a dual-spacing thermal neutron detector, use the Monte Carlo method to carry out numerical simulations on formations with different oil saturations, porosities and salinities, record the time spectrum information of the near and far-spacing thermal neutron detectors, and extract the thermal neutron count ratio and the macroscopic capture cross section information;

[0008] Step 2: According to the measurement responses of the thermal neutron count ratio and the macroscopic capture cross section in formations with different porosities, different salinities and different oil saturations, obtain the variation relationship of the combined parameters that comprehensively consider the dual physical processes of neutron moderation and diffusion with the formation porosity under theoretical conditions, and form a theoretical chart for identifying waterflood levels with the thermal neutron count ratio and the macroscopic capture cross section;

[0009] Step 3: Perform spectral data preprocessing on the actually detected thermal neutron time spectrum, adopt a filtering algorithm to reduce the error caused by low-statistics data, improve the accuracy of the data, and accurately extract the true capture cross section of the formation by using an adaptive single-exponential fitting algorithm to avoid the influence of the borehole, and calculate the near and far thermal neutron count ratios;

[0010] Step 4: Select a water layer section with relatively pure lithology and low shale content through conventional curves, calculate the regression formula of the water line, and combine the theoretical chart to obtain the actual oil line regression formula under the formation salinity conditions;

[0011] Step 5: Establish a qualitative waterflood identification chart, place the combined parameter values of the reservoir calculated in Step 3 in the qualitative identification chart for display, and quickly identify the waterflood situation of the reservoir.

[0012] Further, in the above Step 1, the thermal neutron count expression is:

[0013] (1);

[0014] Wherein, T 1, T 2 are respectively the neutron lifetimes of thermal neutrons in the borehole and the formation; N 1 and N 2 respectively represent the initial number of neutrons in the attenuation processes in the borehole and the formation;

[0015] Calculate the near-thermal neutron count and the far-thermal neutron count respectively according to formula (1), and the thermal neutron count ratio Ratio is the ratio of the near-thermal neutron count to the far-thermal neutron count;

[0016] Formation macroscopic capture cross section Σ has the following relationship with the thermal neutron lifetime:

[0017] (3).

[0018] Furthermore, in the step 2, the formation salinity includes five kinds of 0 ppm, 20000 ppm, 50000 ppm, 100000 ppm and 150000 ppm, the porosity includes eight kinds of 1%, 3%, 5%, 8%, 10%, 12%, 15% and 20%, and the oil saturation includes five kinds of 0%, 25%, 50%, 75% and 100%;

[0019] Combined parameter of the comprehensive neutron slowdown and diffusion dual physical processes DRS is expressed as:

[0020] (4);

[0021] where a and b are constant coefficients, Sigma is the formation macroscopic capture cross section, L e is the fast neutron slowdown length, Ratio is the thermal neutron count ratio;

[0022] Establish the regression formula of the combined parameter DRS with the formation porosity, salinity and oil saturation under theoretical conditions, and form a theoretical chart for identifying the water flooding level of the combined parameter of the comprehensive neutron slowdown and diffusion dual physical processes.

[0023] Furthermore, in the step 3, first perform combined filtering in the depth domain and time domain on the measured thermal neutron time spectrum to reduce the error caused by low statistical data; then apply the constraints of formula (5) and formula (6) to the actual time spectrum, so as to adaptively select the formation area for calculating the macroscopic capture cross section;

[0024] (5);

[0025] (6);

[0026] where, k ( t ) is t the curvature of the thermal neutron time spectrum at time t n andt n+1 They are two adjacent moments respectively. Starting from the 0 moment for iteration, a threshold ε1 is set to control the fluctuation at the tail end not exceeding ε1, and at the same time ensure that the thermal neutron count at the tail end is greater than ε2;

[0027] Use the single exponential fitting algorithm to calculate the ratio of the capture cross section to the thermal neutron count.

[0028] Furthermore, in step 4, from the comprehensive analysis of the natural gamma ray, spontaneous potential, resistivity, and three porosity curves measured conventionally, a water layer section with relatively pure lithology and low shale content is determined;

[0029] Combined with the water analysis data of the area to be identified, determine the salinity of the water layer section, and calculate the water line combination parameters DRS The expression varying with porosity, and determine the oil line combination parameters under the condition of the corresponding formation water salinity according to the theoretical chart DRS The expression varying with porosity;

[0030] The formation oil saturation is given by the following formula:

[0031] (7);

[0032] Wherein, S o is the formation oil saturation, DRS is the ratio of the macroscopic capture cross section of the formation to the thermal neutron count under a certain porosity condition, DRS oil and DRS water are the ratios of the macroscopic capture cross sections of the oil layer and water layer formations to the thermal neutron count under the corresponding porosity conditions.

[0033] Furthermore, through the combination parameter DRS expressions of the oil line and water line established in step 4 and formula (7), obtain the corresponding DRS regression formula varying with porosity under different formation conditions of oil saturation, and combine with the evaluation standard of water flooded layers in the oilfield block to establish a qualitative identification chart for water flooding; Place the combination parameter DRS of the reservoir calculated in step 3 in the qualitative identification chart for display, DRS The interpretation conclusion corresponding to the value will indicate the water flooding degree of the reservoir, and can visually display the water flooding situation of the formation.

[0034] The beneficial technical effects brought by the present invention:

[0035] The present invention can eliminate the influence of formation water salinity and porosity on the evaluation of water-flooded layers, providing a new theoretical method for quickly and accurately identifying the water-flooded situation of formations by pulsed neutron lifetime logging. The interpretation coincidence rate in practical applications is as high as 90%, providing an important technical guarantee for oilfield development and optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic structural diagram of a dual-detector pulsed neutron detection system in the present invention.

[0037] Figure 2 It is the thermal neutron time spectrum of sandstone formations with different formation water salinities and oil saturations under the condition of 10% porosity.

[0038] Figure 3 Under different salinity conditions DRS The relationship diagram with formation porosity.

[0039] Figure 4 Under the condition that the formation water salinity is 20000 ppm, under different oil saturation formation conditions DRS The relationship diagram with formation porosity.

[0040] Figure 5 It is the application effect diagram of the measured well chart.

[0041] Among them, 1 - D - T controllable neutron source; 2 - first composite material shield; 3 - near-source thermal neutron detector; 4 - second composite material shield; 5 - far-source thermal neutron detector; 6 - instrument housing; 7 - borehole environment; 8 - casing; 9 - formation. DETAILED DESCRIPTION OF THE INVENTION

[0042] The following further describes the specific implementation manners of the present invention in combination with specific embodiments:

[0043] A water-flood identification method based on the dual physical processes of pulsed neutron deceleration and diffusion. Based on the processes of inelastic scattering, elastic scattering, and radiative capture of neutrons with the atomic nuclei of formation elements, a dual-detector pulsed neutron detection system composed of a D - T controllable neutron tube source and a dual-source thermal neutron detector is adopted, as Figure 1As shown in the figure, inside the instrument housing 6, from bottom to top, there are successively arranged a D-T controllable neutron source 1, a first composite material shield 2, a near-source thermal neutron detector 3, a second composite material shield 4, and a far-source thermal neutron detector 5. A first composite material shield 2 is filled between the D-T controllable neutron source 1 and the near-source thermal neutron detector 3, with a length set to 4 - 6 cm and a diameter set to 40 mm. The near-source thermal neutron detector 3 has a diameter of 12 mm and a length of 80 mm, and the distance between it and the D-T controllable neutron source 1 is set to 42 cm, and it is filled with He-3 gas at 4 atmospheric pressures inside. A second composite material shield 4 is filled between the near-source thermal neutron detector 3 and the far-source thermal neutron detector 5. The second composite material shield 4 has a length set to 5 - 7 cm and a diameter set to 100 mm. The far-source thermal neutron detector 5 has a diameter of 12 mm and a length of 100 mm, and the distance between it and the D-T controllable neutron source 1 is set to 72 cm, and it is filled with He-3 gas at 6 atmospheric pressures inside. The dual-detector pulsed neutron detection system is set to conduct detection in a measurement environment composed of a wellbore environment 7, a casing 8, and a formation 9.

[0044] A waterflood identification method based on the dual physical processes of pulsed neutron deceleration and diffusion. Using the above-mentioned dual-detector pulsed neutron detection system, it records the thermal neutron time spectra of the near and far thermal neutron detectors. Based on the processes of inelastic scattering, elastic scattering, and radiative capture of neutrons with the atomic nuclei of formation elements, it extracts the information of macroscopic capture cross-section and thermal neutron count ratio, realizes the evaluation of formation saturation and the elimination of environmental impacts such as salinity and porosity, and can quickly identify the waterflood situation of the reservoir. Specifically, it includes the following steps:

[0045] Step 1: Based on the existing D-T controllable neutron tube source and dual-source distance thermal neutron detectors, using the Monte Carlo method, conduct numerical simulations on formations with different oil saturations, porosities, and salinities, record the thermal neutron time spectrum information of the near and far detectors, and extract the thermal neutron count ratio and macroscopic capture cross-section information;

[0046] Step 2: According to the measurement responses of the thermal neutron count ratio and macroscopic capture cross-section in formations with different porosities, different salinities, and different oil saturations, obtain the regression formula of the combined parameters of the comprehensive neutron deceleration and diffusion dual physical processes changing with formation porosity under theoretical conditions, and form a theoretical chart for identifying waterflood levels with the combination of thermal neutron count ratio and macroscopic capture cross-section;

[0047] Step 3: Conduct spectral data preprocessing on the actually detected thermal neutron time spectrum, use a suitable filtering algorithm to reduce the error caused by low statistical data, improve the accuracy of the data, and accurately extract the true capture cross-section of the formation by avoiding the wellbore influence through an adaptive single-exponential fitting algorithm, and calculate the near and far thermal neutron count ratios;

[0048] Step 4: Select water layer sections with relatively pure lithology and low shale content through a conventional curve, calculate the regression formula of the water line, and obtain the actual oil line fitting formula under the corresponding formation salinity conditions by combining with the theoretical chart.

[0049] Step 5: Introduce the calculation results of the open-hole porosity and combine with the regional water analysis data to analyze and study the reservoir section; establish a qualitative identification chart for water flooding, place the combined parameter values of the reservoir calculated in Step 3 in the qualitative identification chart for display, and quickly identify the water flooding situation of the reservoir.

[0050] In Step 1, when the instrument works, 14 MeV high-energy fast neutrons are released. The fast neutrons interact with the atomic nuclei of formation elements through inelastic scattering and elastic scattering interactions, and are decelerated to thermal neutrons, which then interact with the atomic nuclei of formation elements through capture and disappear. The macroscopic capture ability of the formation is reflected by recording the change of thermal neutrons over time. The hydrogen content of the formation is reflected by the count ratio of the near and far detectors. The macroscopic capture cross-section of the formation is extracted using the time spectrum information of the near-detected thermal neutrons, and the thermal neutron count ratio is calculated.

[0051] Using the Monte Carlo method, in the established formation model, the formation salinity includes five types: 0 ppm, 20000 ppm, 50000 ppm, 100000 ppm, and 150000 ppm; the porosity includes eight types: 1%, 3%, 5%, 8%, 10%, 12%, 15%, and 20%; the oil saturation includes five types: 0%, 25%, 50%, 75%, and 100%; simulate the thermal neutron time spectrum of the pulsed neutron lifetime logging tool in formations with different oil saturations, porosities, and salinities, and record the near-detected thermal neutron time spectrum as Figure 2 shown, according to Figure 2 the recorded thermal neutron time spectrum, use the single exponential fitting algorithm to extract the macroscopic capture cross-section of the formation and the information of the thermal neutron count ratio of the near and far detectors.

[0052] Thermal neutron count N ( t ) The expression is:

[0053] (1);

[0054] Where T 1, T 2 are respectively the neutron lifetimes of thermal neutrons in the borehole and the formation; N 1 and N 2 respectively represent the initial number of neutrons during the attenuation processes in the borehole and the formation;

[0055] The thermal neutron distributions of the near and far detectors can be expressed as:

[0056] (2);

[0057] In the formula, D is the thermal neutron diffusion coefficient, L e is the fast neutron slowing-down length, L t is the thermal neutron diffusion length. The ability of the formation to slow down fast neutrons is reflected by the ratio of near and far thermal neutron counts, and the water flooding situation of the formation is jointly evaluated by combining the capture and absorption ability of the formation for thermal neutrons.

[0058] The macroscopic capture cross-section of the formation Σ has the following relationship with the thermal neutron lifetime:

[0059] (3).

[0060] In step 2, the combined parameter DRS that comprehensively considers the two physical processes of neutron slowing down and diffusion

[0061] (4);

[0062] where a and b are constant coefficients, Sigma is the macroscopic capture cross-section of the formation, L e is the fast neutron slowing-down length, Ratio is the thermal neutron count ratio;

[0063] Under theoretical conditions, a regression formula for the variation of the combined parameter DRS with formation porosity under different salinities and different oil saturations is established, and its variation relationship is as Figure 3 and Figure 4 shown, forming a theoretical chart for identifying water flooding levels with the combined parameter that comprehensively considers the two physical processes of neutron slowing down and diffusion.

[0064] In step 3, the thermal neutron count in the thermal neutron time spectrum of pulsed neutron lifetime logging is low and the statistical fluctuation is large. First, a combined filter in the depth domain and time domain is performed on the measured thermal neutron time spectrum to reduce the error caused by low statistical data. There will be differences in the transition section from the borehole area to the formation area of the filtered time spectrum under different formation conditions. To accurately extract the macroscopic capture cross-section of the formation, the time period for single exponential fitting should be strictly selected;

[0065] (5);

[0066] In k ( t ) is the curvature of the thermal neutron time spectrum at time t , t n and t n+1They are two adjacent moments respectively, and iteration starts from moment 0;

[0067] As shown in formula (5), first roughly find the transition section by using the curvature change of the thermal neutron time spectrum, and then use the Newton iteration algorithm to accurately determine the moment of transition from the borehole area to the formation area. Performing single-exponential fitting from this moment backward can minimize the influence of the wellbore environment on the extraction of the formation macroscopic capture cross-section and achieve the effect of accurately extracting the formation macroscopic capture cross-section. At the same time, certain limiting conditions are also required to constrain the statistical fluctuations at the tail end of the thermal neutron time spectrum, otherwise errors in parameter extraction will be caused by low thermal neutron counts.

[0068] (6);

[0069] Set a threshold ε1 to control the fluctuation at the tail end not to exceed ε1, and at the same time ensure that the thermal neutron count at the tail end is greater than ε2;

[0070] By applying the constraints of formula (5) and formula (6) to the actual time spectrum, the formation area for calculating the macroscopic capture cross-section is adaptively selected; this method not only avoids the statistical fluctuations caused by low counts at the tail end but also effectively avoids the wellbore area, thus accurately obtaining the true capture cross-section of the formation.

[0071] Use the single-exponential fitting algorithm to calculate the capture cross-section, and obtain the near and far thermal neutron counts according to the dual-spacing thermal neutron detector, thereby calculating the thermal neutron count ratio.

[0072] In step 4, determine the water layer section with relatively pure lithology and low shale content through comprehensive analysis of the natural gamma ray, spontaneous potential, resistivity, and triple porosity curves measured conventionally;

[0073] Combined with the water analysis data of the area to be identified, determine the salinity of the water layer section, calculate the expression of the water line combination parameter varying with porosity, and determine the expression of the oil line combination parameter varying with porosity under the condition of the corresponding formation water salinity according to the theoretical chart;

[0074] The formation oil saturation is given by the following formula:

[0075] (7);

[0076] Where, S o is the formation oil saturation, DRS is the ratio of the formation macroscopic capture cross-section to the thermal neutron count ratio under a certain porosity condition, DRS oil 、 DRS water are the ratios of the formation macroscopic capture cross-section to the thermal neutron count ratio of the oil layer and water layer under the corresponding porosity condition.

[0077] Based on the combined parameters of the measured oil line and water line established in Step 4 DRS expression and Formula (7), calculate the corresponding DRS regression formula varying with porosity. Combining with the evaluation criteria for water-flooded layers in the oilfield block, establish a qualitative identification chart for water flooding; place the combined parameters of the reservoir calculated in Step 3 DRS in the qualitative identification chart for display, DRS and the corresponding interpretation conclusion of the value will indicate the water-flooding degree of the reservoir, which can visually display the water-flooding situation of the formation.

[0078] If the formation is water-flooded, it shows a DRS tendency to be larger; on the contrary, if the formation has not been exploited, DRS the value is smaller and closer to the oil line. Figure 5 It shows the application effect diagram of the chart obtained by using the combined parameters of pulsed neutron logging data under the condition that the formation water salinity is 150 g / L and the formation porosity is medium. Practice has proved that the coincidence rate between the actual projection point interpretation result of this chart and the perforation production is as high as 90%, and it can quickly and accurately evaluate the water-flooded layer.

[0079] Certainly, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by those skilled in the art within the scope of the essence of the present invention should also fall within the protection scope of the present invention.

Claims

1. A flooding identification method based on the dual physical processes of pulsed neutron deceleration and diffusion, characterized in that: A dual-detector pulsed neutron detection system consisting of a DT controllable neutron tube source and a dual-source distance thermal neutron detector is used to extract the thermal neutron count ratio and macroscopic capture cross section to quickly evaluate reservoir flooding. The specific steps include: Step 1: Based on the existing detection system consisting of DT controllable neutron tube source and dual-source distance thermal neutron detector, the Monte Carlo method is used to carry out numerical simulation of formations with different oil saturation, porosity and salinity, record the time spectrum information of near and far source distance thermal neutron detectors, and extract the thermal neutron counting ratio and macro capture cross section information; Step 2: Based on the measured responses of thermal neutron count ratio and macroscopic capture cross section in formations with different porosities, different salinities and different oil saturations, the relationship between the combined parameters of the dual physical processes of neutron deceleration and diffusion under theoretical conditions and the formation porosity is obtained, forming a theoretical chart for identifying the flooding level by combining thermal neutron count ratio and macroscopic capture cross section; Step 3: Preprocess the spectral data of the actually detected thermal neutron time spectrum, use a filtering algorithm to reduce the error caused by low statistical data, improve the accuracy of the data, and use an adaptive single exponential fitting algorithm to avoid the influence of the wellbore to accurately extract the true capture cross section of the formation and calculate the near and far thermal neutron count ratios; Step 4: Select the water layer section with purer lithology and lower mud content through the conventional curve, calculate the regression formula of the water line, and combine the theoretical chart to obtain the actual oil line regression formula under the corresponding formation mineralization conditions; Step 5: Establish a qualitative identification chart for flooding, and display the combined parameter values ​​of the reservoir calculated in step 3 on the qualitative identification chart to quickly identify the flooding of the reservoir; In step 2, the formation mineralization includes five types: 0ppm, 20000ppm, 50000ppm, 100000ppm and 150000ppm, the porosity includes eight types: 1%, 3%, 5%, 8%, 10%, 12%, 15% and 20%, and the oil saturation includes five types: 0%, 25%, 50%, 75% and 100%; The combined parameter DRS of the dual physical processes of neutron deceleration and diffusion is expressed as: Among them, a and b are constant coefficients, Sigma is the macroscopic capture cross section of the formation, and L e is the fast neutron deceleration length, Ratio is the thermal neutron counting ratio; Under theoretical conditions, a regression formula for the combined parameter DRS with formation porosity, salinity and oil saturation is established to form a theoretical chart for identifying water flooding levels using the combined parameters of the dual physical processes of neutron deceleration and diffusion.

2. The flooding identification method based on the dual physical process of pulsed neutron deceleration and diffusion according to claim 1 is characterized in that: In step 1, the thermal neutron count expression is: Among them, T1 and T2 are the neutron lifetimes of thermal neutrons in the wellbore and formation, respectively; N1 and N2 represent the initial neutron numbers in the attenuation process in the wellbore and formation, respectively; According to formula (1), the near thermal neutron count and the far thermal neutron count are calculated respectively, and the thermal neutron count ratio Ratio is the ratio of the near thermal neutron count to the far thermal neutron count; The relationship between the formation macroscopic capture cross section Σ and the thermal neutron lifetime is as follows:

3. The flooding identification method based on the dual physical process of pulse neutron deceleration and diffusion according to claim 2 is characterized in that: In step 3, the measured thermal neutron time spectrum is first subjected to combined filtering in the depth domain and the time domain to reduce the error caused by low statistical data; then the constraints of formula (5) and formula (6) are applied to the actual time spectrum, so as to adaptively select the formation region for calculating the macro capture cross section; Where k(t) is the curvature of the thermal neutron time spectrum at time t, t n , t n+1 They are two adjacent moments, starting from moment 0, and the iteration is performed. The threshold ∈1 is set to control the fluctuation of the tail end not to exceed ε1, while ensuring that the thermal neutron count at the tail end is greater than ε2; The capture cross section and thermal neutron count ratio were calculated using a single exponential fitting algorithm.

4. The flooding identification method based on the dual physical process of pulsed neutron deceleration and diffusion according to claim 3 is characterized in that: In step 4, the water layer section with relatively pure lithology and low mud content is determined by comprehensive analysis of conventionally measured natural gamma, natural potential, resistivity and three-porosity curves; Combined with the water analysis data of the area to be identified, determine the salinity of the water layer, calculate the expression of the water line combination parameter DRS changing with porosity, and determine the expression of the oil line combination parameter DRS changing with porosity under the corresponding formation water salinity conditions according to the theoretical plate; The formation oil saturation is given by the following formula: Among them, S o is the oil saturation of the formation, DRS is the ratio of the formation macroscopic capture cross section to the thermal neutron count ratio under a certain porosity condition, and DRS oil , DRS water It is the ratio of the macroscopic capture cross section of the oil layer and water layer to the thermal neutron count ratio under the corresponding porosity conditions.

5. The flooding identification method based on the dual physical process of pulsed neutron deceleration and diffusion according to claim 4 is characterized in that: Through the DRS expression of the combined parameters of the oil line and the water line in the measured well established in step 4 and formula (7), the regression formula of the DRS change with porosity under different oil saturation formation conditions is obtained, and combined with the evaluation standard of water-flooded layers in oilfield blocks, a water-flooded qualitative identification chart is established; The combined parameter DRS of the reservoir calculated in step 3 is displayed in the qualitative identification plate. The interpretation conclusion corresponding to the DRS value will indicate the degree of water flooding of the reservoir and can intuitively show the water flooding situation of the formation.

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