A method of formation density measurement, storage medium and apparatus

Abstract

The application discloses a formation density measurement method, a storage medium and equipment, and relates to the field of well logging technology. The method comprises the following steps: establishing a neutron logging model of formation density for representing the relationship between the formation density and the non-elastic gamma count ratio and the thermal neutron count ratio; and substituting the non-elastic scattering gamma ray count ratio, the thermal neutron count ratio and a plurality of calibration coefficients of a target formation of a well to be measured into the neutron logging model of formation density to obtain the formation density of the target formation of the well to be measured. According to the method, the final formation density can be obtained by using the thermal neutron and the non-elastic gamma count. The method has the characteristics of small influence of formation lithology, high measurement efficiency and simple design of related instruments.

Description

Technical Field

[0001] This invention relates to the field of well logging technology, and in particular to a formation density measurement method, storage medium, and device. Background Technology

[0002] Density measurement is a crucial part of open-hole logging. Traditional density measurement uses Cs-137 as the gamma-ray source, recording the Compton scattering between the gamma rays and the formation using a gamma detector to obtain formation density information. However, this method has drawbacks: firstly, the radioactive source needs to be manually added / unloaded before and after logging, posing a radiation hazard to operators; secondly, using chemical sources for logging carries the risk of source jamming downhole, which, if retrieval fails, can cause radiation damage to the environment.

[0003] With the development of controlled neutron source technology and increasing environmental protection requirements, more and more oil companies and researchers are beginning to study the use of controlled neutron sources to measure formation density, thereby avoiding the problems mentioned above. Existing neutron logging methods for measuring formation density using controlled neutron sources have the following shortcomings:

[0004] 1) The spatial correction using captured gamma rays makes the measurement results highly susceptible to the influence of stratigraphic lithology, resulting in a large measurement bias;

[0005] 2) Simultaneous introduction of thermal neutrons and ultrathermal neutrons for spatial correction increases the complexity of instrument design, and the low ultrathermal neutron count rate affects the logging speed.

[0006] 3) Due to the low efficiency of fast neutron counting, introducing fast neutrons for spatial correction will not only reduce the logging speed, but also affect the accuracy of the measurement results due to the instability of the neutron source.

[0007] Furthermore, because chemical source formation density logging tools have simple formulas, few calibration coefficients, and mature technology, existing calibrated well groups can already meet calibration requirements, based on a large amount of domestic and international measured data. However, controlled source formation density neutron logging tools have complex formulas, many calibration coefficients, immature domestic technology, and very little measured data. Existing standard calibrated well groups for formation density cannot meet the calibration requirements of formation density neutron logging instruments. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to provide a formation density measurement method, storage medium and device to address the shortcomings of the prior art.

[0009] The technical solution of the present invention to solve the above-mentioned technical problems is as follows:

[0010] A method for measuring formation density, comprising:

[0011] A neutron logging model for formation density was established to characterize the relationship between formation density and inelastic gamma count ratio and thermal neutron count ratio.

[0012] The formation density of the target formation is obtained by substituting the inelastic scattered gamma ray count ratio, the thermal neutron count ratio, and multiple calibration coefficients of the target formation into the neutron logging model for formation density.

[0013] The beneficial effects of this invention are: this method utilizes thermal neutrons and inelastic gamma counting to obtain the final formation density. This invention features minimal influence from formation lithology, high measurement efficiency, and simple instrument design.

[0014] Calculating formation density by thermal neutron counting is highly efficient and can improve the detection efficiency and logging speed of neutron logging instruments.

[0015] Since thermal neutron counts can be measured using formation porosity instruments, the instrument design based on this method only requires consideration of the gamma detector arrangement, simplifying the design process. Furthermore, the instruments used in this invention are all commonly used equipment in the field, facilitating operation, implementation, and testing.

[0016] By employing the correction relationship between experimental and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio, numerical simulation of calibrated wells can compensate for the current deficiency in the number of standard calibrated wells for formation density.

[0017] Furthermore, the neutron logging model for the formation density is as follows:

[0018] ρ=A*ln(f(R t )+BR in )+g(R t )+C,

[0019] in,

[0020] f(R t ) = DR t 2 +ER t +F,

[0021] g(R t )=ln(GR t 2 +HR t +I),

[0022] ρ represents the formation density, R t R represents the thermal neutron detector count ratio. in The gamma ray count ratio represents the inelastic scattering gamma rays, and A, B, C, D, E, F, G, H and I are scale coefficients.

[0023] Furthermore, A, B, C, D, E, F, G, H, and I are the processes for obtaining the scale coefficients, including:

[0024] By using calibration experiments of standard calibration wells and numerical calculations of the corresponding Monte Carlo model, the correction relationships between experimental and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio were obtained.

[0025] Substituting formations of other densities into the Monte Carlo model yields calibrated simulation wells for those densities. Numerical simulations of these calibrated simulation wells are then used to obtain simulated values ​​for the inelastic gamma-ray count ratio and thermal neutron count ratio. Finally, the simulated values ​​are corrected using the correction relationship between experimental measurements and simulated values, resulting in the corrected inelastic scattered gamma-ray count ratio and thermal neutron count ratio.

[0026] The calibration coefficients are obtained by substituting the inelastic scattered gamma-ray count ratio, thermal neutron count ratio, and corresponding formation density of multiple standard calibration wells, as well as the simulated and corrected inelastic scattered gamma-ray count ratio, thermal neutron count ratio, and corresponding formation density of multiple calibration simulation wells, into the neutron logging model of formation density.

[0027] Furthermore, simulated values ​​of the inelastic gamma-ray count ratio and thermal neutron count ratio are obtained through numerical simulation of the calibrated simulation well; and the simulated values ​​of the calibrated simulation well are corrected using the correction relationship between experimental measurements and simulated values ​​to obtain the simulated corrected inelastic scattered gamma-ray count ratio and thermal neutron detector count ratio, specifically including:

[0028] A Monte Carlo transport model for the formation density of various materials in a standard calibrated well was constructed, and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio were obtained through numerical simulation.

[0029] Using experimental measurements of inelastic gamma count ratio and thermal neutron count ratio from standard calibration wells, the correction relationship between experimental measurements and simulated values ​​under different formation densities was obtained.

[0030] By selecting formation models with various lithologies and mixing them with pure water at different volume percentages, rock strata with different lithologies and formation densities were constructed. These strata were then substituted into the Monte Carlo model to obtain a calibrated simulation well. Through numerical simulation, the simulated values ​​of the non-elastic gamma count ratio and thermal neutron count ratio of the calibrated simulation well were obtained.

[0031] Using the correction relationship between the experimental measurements and the simulated values, the simulated values ​​of the inelastic gamma count ratio and thermal neutron count ratio of the calibrated simulation well are corrected to obtain the corrected inelastic gamma count ratio and thermal neutron count ratio of the calibrated simulation well.

[0032] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: a storage medium storing instructions, wherein when a computer reads the instructions, the computer executes a formation density measurement method as described in any of the above solutions.

[0033] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows:

[0034] An electronic device includes a processor and a storage medium as described above, wherein the processor executes instructions in the storage medium.

[0035] The advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0036] Figure 1 A schematic flowchart of a formation density measurement method provided for an embodiment of the present invention;

[0037] Figure 2 A schematic flowchart of a neutron logging method for measuring formation density, provided for other embodiments of the present invention;

[0038] Figure 3 A diagram showing the relationship between formation density and actual density is provided for other embodiments of the present invention;

[0039] Figure 4 A schematic diagram showing the relationship between the absolute error of the formation density and the true density and the true density, provided for other embodiments of the present invention;

[0040] Figure 5 A schematic diagram showing the relationship between the relative error of formation density and true density and the true density, provided for other embodiments of the present invention. Detailed Implementation

[0041] The principles and features of the present invention are described below with reference to the accompanying drawings. The embodiments described are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0042] like Figure 1 As shown, an embodiment of the present invention provides a method for measuring formation density, comprising:

[0043] S1, Establish a neutron logging model for formation density to characterize the relationship between formation density and inelastic gamma count ratio and thermal neutron count ratio;

[0044] S2, Substitute the inelastic scattered gamma ray count ratio, the thermal neutron count ratio, and multiple calibration coefficients of the target formation of the well to be logged into the neutron logging model of the formation density to obtain the formation density of the target formation of the well to be logged.

[0045] This method utilizes thermal neutron and inelastic gamma counting to obtain the final formation density. This invention features minimal influence from formation lithology, high measurement efficiency, and simple instrument design.

[0046] Formation density is calculated using thermal neutron counting and inelastic gamma counting, which is highly efficient and can improve the detection efficiency and logging speed of neutron logging instruments.

[0047] Since thermal neutron counts can be measured using formation porosity instruments, the instrument design based on this method only requires consideration of the gamma detector arrangement, simplifying the design process. Furthermore, the instruments used in this invention are all commonly used equipment in the field, facilitating operation, implementation, and testing.

[0048] By employing the correction relationship between experimental and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio, numerical simulation of calibrated wells can compensate for the current deficiency in the number of standard calibrated wells for formation density.

[0049] Optionally, in any of the above embodiments, the neutron logging model for formation density is:

[0050] ρ=A*ln(f(R t )+BR in )+g(R t )+C,

[0051] in,

[0052] f(R t ) = DR t 2 +ER t +F,

[0053] g(R t )=ln(GR t 2 +HR t +I),

[0054] ρ represents the formation density, R t R represents the thermal neutron detector count ratio. in The gamma ray count ratio represents the inelastic scattering gamma rays, and A, B, C, D, E, F, G, H and I are scale coefficients.

[0055] The formation density model formula of this scheme is simple and the measurement results are not sensitive to lithology, which can reduce the deviation of the measurement results and improve the measurement accuracy.

[0056] Optionally, in any of the above embodiments, A, B, C, D, E, F, G, H, and I represent the process of obtaining scale coefficients, including:

[0057] By using calibration experiments of standard calibration wells and numerical calculations of the corresponding Monte Carlo model, the correction relationships between experimental and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio were obtained.

[0058] Substituting formations of other densities into the Monte Carlo model yields calibrated simulation wells for those densities. Numerical simulations of these calibrated simulation wells are then used to obtain simulated values ​​for the inelastic gamma-ray count ratio and thermal neutron count ratio. Finally, the simulated values ​​are corrected using the correction relationship between experimental measurements and simulated values, resulting in the corrected inelastic scattered gamma-ray count ratio and thermal neutron count ratio.

[0059] The calibration coefficients are obtained by substituting the inelastic scattered gamma-ray count ratio, thermal neutron count ratio, and corresponding formation density of multiple standard calibration wells, as well as the simulated and corrected inelastic scattered gamma-ray count ratio, thermal neutron count ratio, and corresponding formation density of multiple calibration simulation wells, into the neutron logging model of formation density.

[0060] Optionally, in any of the above embodiments, simulated values ​​of the inelastic gamma-ray count ratio and the thermal neutron count ratio are obtained through numerical simulation of the calibrated simulation well; and the simulated values ​​of the calibrated simulation well are corrected using the correction relationship between the experimental measurements and the simulated values ​​to obtain the simulated corrected inelastic scattered gamma-ray count ratio and the thermal neutron detector count ratio, specifically including:

[0061] A Monte Carlo transport model for the formation density of various materials in a standard calibrated well was constructed, and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio were obtained through numerical simulation.

[0062] Using experimental measurements of inelastic gamma count ratio and thermal neutron count ratio from standard calibration wells, the correction relationship between experimental measurements and simulated values ​​under different formation densities was obtained.

[0063] By selecting formation models with various lithologies and mixing them with pure water at different volume percentages, rock strata with different lithologies and formation densities were constructed. These strata were then substituted into the Monte Carlo model to obtain a calibrated simulation well. Through numerical simulation, the simulated values ​​of the non-elastic gamma count ratio and thermal neutron count ratio of the calibrated simulation well were obtained.

[0064] Using the correction relationship between the experimental measurements and the simulated values, the simulated values ​​of the inelastic gamma count ratio and thermal neutron count ratio of the calibrated simulated well are corrected to obtain the corrected inelastic gamma count ratio and thermal neutron count ratio of the calibrated simulated well. It should be noted that, in one embodiment, the numerical simulation may include:

[0065] By using experiments with standard calibrated wells and numerical calculations with corresponding Monte Carlo models, the correction relationships between experimental and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio are obtained; or, by selecting formation models of various lithologies and mixing them with pure water at different volume percentages, calibrated simulation wells with different lithologies and formation densities are constructed for Monte Carlo numerical simulation.

[0066] The standard calibration wells are a group of calibration wells that conform to petroleum industry standards, and the size and materials of each well are fixed.

[0067] It should be noted that, in one embodiment, the measurement data of strata with different densities includes thermal neutron counts from near- and far-range thermal neutron detectors, and inelastic scattered gamma ray counts from near- and far-range gamma detectors; the thermal neutron count ratio R is obtained based on the thermal neutron counts. t The inelastically scattered gamma ray count ratio R is obtained from the inelastically scattered gamma ray count. in Numerical calculations were performed on the calibrated simulated well to obtain simulated values ​​of inelastic gamma ray count ratio and thermal neutron count ratio. The simulated values ​​were then corrected using the correction relationship between experimental measurements and simulated values ​​to obtain the corrected inelastic scattered gamma ray count ratio and thermal neutron count ratio.

[0068] In any embodiment, it may include obtaining formation inelastic scattered gamma ray count ratios R of different densities. in Thermal neutron detector count ratio R t Substituting the formation density ρ into the formation density model yields the scale coefficients A, B, C, D, E, F, G, H, and I.

[0069] This scheme uses a count ratio method, which can eliminate the influence of neutron source instability. Since the count is proportional to the intensity of the neutron source, the count ratio of the two detectors is independent of the intensity of the neutron source and therefore independent of the stability of the neutron source, thus eliminating the influence of neutron source instability.

[0070] By employing the correction relationship between experimental and simulated measurements of inelastic gamma count ratio and thermal neutron count ratio, numerical simulations of calibrated wells can compensate for the current shortage of standard calibrated wells for formation density.

[0071] In another embodiment, such as Figure 2 As shown, a neutron logging method for measuring formation density includes:

[0072] S11: Establishing a neutron logging model for formation density

[0073] ρ=A*ln(f(R t )+BR in )+g(R t )+C,

[0074] in,

[0075] f(R t ) = DR t 2 +ER t +F,

[0076] g(R t )=ln(GR t 2 +HR t +I),

[0077] R t R represents the count ratio between near-field and far-field thermal neutron detectors. in The ratio of inelastic scattering gamma counts for near-range and far-range gamma detectors, and A, B, C, D, E, F, G, H, and I are calibration coefficients.

[0078] S12: Construct Monte Carlo models of standard-calibrated wells for formation density under various materials and conduct numerical simulations. Alternatively, select formation models with multiple lithologies, mix them with pure water at different volume percentages, construct calibration simulation wells with different lithologies and formation densities, and conduct numerical simulations; use calibration experiments of standard-calibrated wells to measure inelastic gamma counts and thermal neutron counts;

[0079] S13: Based on the simulation method in S12, the measurement data of the standard calibrated well formation and the simulation data after correction of the calibrated simulation well were obtained, including the thermal neutron count ratio of near- and far-range thermal neutron detectors and the inelastic scattered gamma ray count ratio of near- and far-range gamma detectors.

[0080] S14: The inelastic scattered gamma-ray count ratio R obtained from S13 for strata of different densities in Thermal neutron detector count ratio R t Substituting the formation density into the neutron logging model of formation density in S11 yields calibration coefficients A, B, C, D, E, F, G, H, and I. The specific calibration coefficients are related to the structure of the logging instrument.

[0081] S15: Simulates the thermal neutron count ratio of near- and far-range thermal neutron detectors and the inelastic scattered gamma ray count ratio of near- and far-range gamma detectors for the target formation to be logged.

[0082] S16: Substitute the thermal neutron count ratio, inelastic gamma ray count ratio, and calibration coefficient from S15 into the neutron logging model for formation density in S11 to obtain the formation density of the target formation to be logged.

[0083] in, Figure 3The figure shows the relationship between the formation density values ​​obtained by this invention and the actual formation density values. As can be seen from the figure, the density values ​​obtained by this invention are all distributed around the 45-degree line (i.e., where the measured density and the actual density are completely consistent), and the correlation linearity reaches 95.6%. The relationship between the absolute error of the formation density obtained by this invention and the actual density is as follows: Figure 4 As shown, the deviation of the formation density obtained by this invention does not exceed 0.13 g / cm³. 3 The relationship between the relative error of formation density and true density and the true density is as follows: Figure 5 As shown, the relative deviation of the formation density obtained by the present invention does not exceed 7%.

[0084] Readers should understand that in the description of this specification, the references to "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0085] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the method embodiments described above are merely illustrative. For instance, the division of steps is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple steps may be combined or integrated into another step, or some features may be ignored or not executed.

[0086] If the above methods are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or 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.

[0087] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for measuring formation density, characterized in that, include: A neutron logging model for formation density was established to characterize the relationship between formation density and inelastic scattered gamma-ray count ratio and thermal neutron count ratio. Substitute the inelastic scattered gamma ray count ratio, the thermal neutron count ratio, and multiple calibration coefficients of the target formation in the well to be logged into the neutron logging model of the formation density to obtain the formation density of the target formation in the well to be logged. The neutron logging model for the formation density is as follows: ρ=A*ln(f(R t )+BR in )+g(R t )+C, in, f(R t )=DR t 2 +IS t +F, g(R t )=ln(GR t 2 +HR t +I), ρ represents the formation density, R t R represents the thermal neutron detector count ratio. in The inelastic scattered gamma ray count ratio is represented by A, B, C, D, E, F, G, H, and I, which are calibration coefficients. The process of obtaining A, B, C, D, E, F, G, H, and I as scale coefficients includes: By using calibration experiments of standard calibration wells and numerical calculations of the corresponding Monte Carlo model, the correction relationships between experimental and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio were obtained. Substituting formations of other densities into the Monte Carlo model yields calibrated simulation wells for those densities. Numerical simulations of these calibrated simulation wells are then used to obtain simulated values ​​for the inelastic gamma-ray count ratio and thermal neutron count ratio. The simulated values ​​are then corrected using the correction relationship between experimental measurements and simulated values, resulting in corrected simulated values ​​for the inelastic scattered gamma-ray count ratio and thermal neutron count ratio. Substituting the inelastic scattered gamma-ray count ratio, thermal neutron count ratio, and corresponding formation density of multiple standard calibration wells, along with the simulated and corrected inelastic scattered gamma-ray count ratio, thermal neutron count ratio, and corresponding formation density of multiple calibration simulation wells, into the neutron logging model of formation density, the calibration coefficients A, B, C, D, E, F, G, H, and I are solved to obtain the calibration coefficients.

2. The method for measuring formation density according to claim 1, characterized in that, The simulated values ​​of the inelastic gamma-ray count ratio and the thermal neutron count ratio are obtained through numerical simulation of the calibrated simulation well. Then, using the correction relationship between the experimental measurements and the simulated values, the simulated values ​​of the calibrated simulation well are corrected to obtain the simulated corrected inelastic scattered gamma-ray count ratio and the thermal neutron detector count ratio, specifically including: A Monte Carlo transport model for the formation density of various materials in a standard calibrated well was constructed, and simulated values ​​of inelastic gamma count ratio and thermal neutron count ratio were obtained through numerical simulation. Using experimental measurements of inelastic gamma count ratio and thermal neutron count ratio from standard calibration wells, the correction relationship between experimental measurements and simulated values ​​under different formation densities was obtained. By selecting formation models with various lithologies and mixing them with pure water at different volume percentages, rock strata with different lithologies and formation densities were constructed. These strata were then substituted into the Monte Carlo model to obtain a calibrated simulation well. Through numerical simulation, the simulated values ​​of the non-elastic gamma count ratio and thermal neutron count ratio of the calibrated simulation well were obtained. Using the correction relationship between the experimental measurements and the simulated values, the simulated values ​​of the non-elastic gamma count ratio and thermal neutron count ratio of the calibrated simulated well are corrected to obtain the corrected non-elastic gamma count ratio and thermal neutron count ratio of the calibrated simulated well.

3. A storage medium, characterized in that, The storage medium stores instructions that, when read by a computer, cause the computer to execute a formation density measurement method as described in claim 1 or 2.

4. An electronic device, characterized in that, It includes a processor and the storage medium of claim 3, wherein the processor executes instructions in the storage medium.

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