A method, system, device and storage medium for determining source distance of density logging

Abstract

The present invention discloses a method, system, device and storage medium for determining the source distance of density logging, which belongs to the technical field of pulsed radioactive source logging in oil and gas exploration. The method comprises: establishing a formation detection model using Monte Carlo simulation software; obtaining the relationship between the count rate and the long source distance and the short source distance from the formation detection model, and preliminarily screening the value ranges of the long source distance and the short source distance; further screening the value ranges of the long source distance and the short source distance based on the statistical error and measurement accuracy of the formation detection model; and determining the final value range of the short source distance using the short source distance compensation function and sensitivity requirements. The present invention can quickly determine the value ranges of the long source distance and the short source distance, and has higher accuracy. A reasonable source distance confirmation method for a density logging instrument can help improve the accuracy of density instrument data, obtain high-precision formation density parameters, make subsequent logging interpretation and analysis more accurate, and save a certain amount of logging costs.

Description

Technical Field

[0001] The present invention belongs to the technical field of pulsed radioactive source logging in oil and gas exploration, and relates to a source distance determination method, system, equipment and storage medium for density logging. Background Art

[0002] Density logging is an indispensable method in traditional well logging. It utilizes a gamma source to emit gamma rays, which react with formation material, causing them to attenuate or disappear. Long and short detectors record the gamma count rate, thereby analyzing formation density. Lithologic density logging is widely used in the oil well logging industry. It not only measures the photoelectric absorption cross-section index (PAC) but also accurately measures formation density, playing a significant role in analyzing porosity and lithology in different formations. The determination of the density logging instrument source distance directly impacts the accuracy of logging data. A reasonable density logging source distance is crucial for measuring complex structures, lithologies, and pore structures. A sound method for determining the source distance of density logging instruments can improve data accuracy, enhance subsequent logging interpretation and analysis, and reduce logging costs. Currently, the source distance for long detectors is primarily determined by the relationship between count rate and source distance and measurement error, while the source distance for short detectors is primarily determined by instrument sensitivity. However, source distance determination using a single method can result in significant errors. Summary of the Invention

[0003] The purpose of the present invention is to solve the technical problem of large error in source distance determined by a single method in the prior art, and to provide a method, system, device and storage medium for determining source distance for density logging.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] In a first aspect, the present invention provides a method for determining source distance of density logging, comprising the following steps:

[0006] Establishing a formation detection model using Monte Carlo simulation software;

[0007] The relationships between the count rate and the long and short source distances are obtained from the formation detection model, and the range of the long and short source distances is preliminarily selected.

[0008] The range of long source distance and short source distance is further screened based on the statistical error and measurement accuracy of the formation detection model;

[0009] The short source distance compensation function and sensitivity requirements are used to determine the final value range of the short source distance.

[0010] A further improvement of the present invention is:

[0011] The Monte Carlo simulation software is used to establish a stratum detection model, which includes the following steps:

[0012] A well logging instrument model was established; the well logging instrument included a radioactive source, a long-source-spacing detector, a short-source-spacing detector, an instrument housing, and a shield; the radioactive source was a 137Cs source; the well logging instrument housing was made of titanium alloy; the shield was made of tungsten-nickel-iron; the well logging instrument had a diameter of 42 mm and a length of 500 mm; the long-source-spacing detector was a cylindrical lanthanum bromide crystal with a radius of 14 mm and a length of 13 mm, and the short-source-spacing detector was a cylindrical lanthanum bromide crystal with a radius of 17 mm and a length of 20 mm;

[0013] A wellbore and formation model was established; the wellbore and formation were designed as a series of cylinders, with a wellbore radius of 10 cm, a formation radius ranging from 10 cm to 80 cm, and a height of 100 cm.

[0014] The relationships between the count rate and the long source distance and the short source distance are obtained from the formation detection model, and the preliminary screening of the value ranges of the long source distance and the short source distance comprises the following steps:

[0015] estimating a maximum long source distance value range of a long source distance detector and a maximum short source distance value range of a short source distance detector of the well logging instrument;

[0016] uniformly selecting a number of point values ​​in the maximum long source distance value range and the maximum short source distance value range, respectively, and inputting the point values ​​into the formation detection model to obtain the counting rate corresponding to each point value, thereby obtaining the relationship between the counting rate and the long source distance and the short source distance;

[0017] Since the counting rate corresponding to the long source distance requires measuring deeper strata, the higher the counting rate received by the long source distance detector, the more conducive it is to analyzing the physical properties of the reservoir. Therefore, the long source distance detector requires a high counting rate, further screening the value range of the long source distance; while the short source distance mainly measures mud cake and plays a compensatory role, so the appropriate counting rate meets the demand, further screening the value range of the short source distance.

[0018] The further screening of the value ranges of the long source distance and the short source distance based on the statistical error and measurement accuracy of the formation detection model comprises the following steps:

[0019] Input different values ​​of long source distance and short source distance in the formation detection model to obtain the corresponding measurement results;

[0020] Performing error analysis on the measurement results to obtain relationships between long source distance, short source distance and error respectively;

[0021] The formation detection model simulation density logging requires that the measurement error is less than 1%. Based on this, the value ranges of long source distance and short source distance are further screened.

[0022] Determining the final value range of the short source distance by using the short source distance compensation function and the sensitivity requirement includes the following steps:

[0023] Evenly selecting a number of point values ​​within the short source distance value range after further screening, and inputting the point values ​​into the formation detection model to obtain the counting rate corresponding to each point value, and then calculating the relative sensitivity from the counting rate to obtain the relationship between the relative sensitivity and the short source distance;

[0024] Since the greater the relative sensitivity, the less favorable it is for short detectors to measure reservoirs, the range of values ​​for short source distances continues to narrow.

[0025] According to the compensation function of short source distance for long source distance, the relative sensitivities under several different combinations of long and short source distances are obtained. Based on the fact that a larger relative sensitivity is less conducive to reservoir measurement with a short detector, the final value range of the short source distance is determined.

[0026] The sensitivity A and relative sensitivity S are:

[0027] The sensitivity A is:

[0028]

[0029] In actual work, the sensitivity A is represented by relative sensitivity S, which is:

[0030]

[0031] Where N is the counting rate and ρ is the formation density.

[0032] The compensation function of the short source distance to the long source distance specifically includes:

[0033] When the long source distance is fixed and the short source distance increases, the distance between the long source distance detector and the short source distance detector decreases, and both the sensitivity and relative sensitivity decrease; when the density increases, the relative sensitivity decreases, while the sensitivity remains unchanged; therefore, the short source distance and the distance between the long source distance detector and the short source distance detector should be increased to improve the sensitivity, thereby determining the final value range of the short source distance.

[0034] In a second aspect, the present invention provides a source distance determination system for density logging, characterized by comprising:

[0035] Modeling unit, using Monte Carlo simulation software to establish a formation detection model;

[0036] Preliminary screening of units: using the formation detection model to obtain the relationship between the count rate and the long detector source distance and the short detector source distance, and preliminarily screening the value range of the long source distance and the short source distance;

[0037] The secondary screening unit further screens the range of long source distance and short source distance according to the statistical error and measurement accuracy of the formation detection model;

[0038] The final screening unit uses the short source distance compensation function and sensitivity requirements to determine the final value range of the short source distance.

[0039] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for determining the source distance of density logging according to any one of claims 1 to 7 when executing the computer program.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for determining the source distance of density logging according to any one of claims 1 to 7.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention discloses a method for determining source distance of density logging. The method determines the range of long source distance and short source distance by combining elements such as count rate, statistical error and measurement accuracy. First, the relationship between count rate and source distance is used to determine the reasonable range of long and short source distances. Then, the range of long and short source distances is narrowed based on the first step by using statistical error and measurement accuracy. Finally, the compensation function of short source distance for long source distance and the sensitivity of short source distance are used to determine the range of long and short source distances of density logging. The present invention can quickly determine the range of long and short source distances and has higher accuracy. The reasonable source distance confirmation method of density logging instrument can help improve the accuracy of density instrument data, obtain high-precision formation density parameters, make subsequent logging interpretation and analysis more accurate, and save certain logging costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 This is a flow chart of a method for determining source distance of density logging in the present invention;

[0045] Figure 2 A schematic diagram of a formation detection model in a method for determining source distance of density logging in the present invention;

[0046] Figure 3 Schematic diagram of the relationship between long source distance and count rate after simulation using the formation detection model of the present invention;

[0047] Figure 4 Schematic diagram of the relationship between short source distance and count rate after simulation using the formation detection model of the present invention;

[0048] Figure 5 Schematic diagram of the relationship between long source distance and error after simulation using the formation detection model of the present invention;

[0049] Figure 6 Schematic diagram of the relationship between short source distance and error after simulation using the formation detection model of the present invention;

[0050] Figure 7 A graph showing the relationship between the error of the density measurement value and the count rate when the formation detection model of the present invention is used;

[0051] Figure 8 Schematic diagram of the relationship between long source distance and counting rate;

[0052] Figure 9 Schematic diagram of the relationship between short source distance and relative sensitivity;

[0053] Figure 10 A system diagram of a method for determining source distance of density logging in the present invention;

[0054] Figure 11 This is a diagram of an electronic device module for a method for determining source distance for density logging in the present invention. DETAILED DESCRIPTION

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0056] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0057] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0058] In the description of the embodiments of the present invention, it should be noted that if the terms "upper," "lower," "horizontal," "inner," etc. appear, the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the inventive product is typically placed when in use. These terms are merely for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. In addition, the terms "first," "second," etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0059] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0060] In the description of the embodiments of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0061] The present invention is described in further detail below with reference to the accompanying drawings:

[0062] See also Figure 1 The embodiment of the present invention provides a method for determining the source distance of density logging, comprising the following steps:

[0063] S1, using Monte Carlo simulation software to establish a formation detection model;

[0064] S2, the relationship between the count rate and the long source distance and the short source distance is obtained from the formation detection model, and the value range of the long source distance and the short source distance is preliminarily screened;

[0065] S3, further screening the value range of long source distance and short source distance according to the statistical error and measurement accuracy of the formation detection model;

[0066] S4, use the short source distance compensation function and sensitivity requirements to determine the final value range of the short source distance.

[0067] The present invention discloses a method for determining source distance of density logging. The method determines the range of long source distance and short source distance by combining elements such as count rate, statistical error and measurement accuracy. First, the relationship between count rate and source distance is used to determine the reasonable range of long and short source distances. Then, the range of long and short source distances is narrowed based on the first step by using statistical error and measurement accuracy. Finally, the compensation function of short source distance for long source distance and the sensitivity of short source distance are used to determine the range of long and short source distances of density logging. The present invention can quickly determine the range of long and short source distances and has higher accuracy. The reasonable source distance confirmation method of density logging instrument can help improve the accuracy of density instrument data, obtain high-precision formation density parameters, make subsequent logging interpretation and analysis more accurate, and save certain logging costs.

[0068] The present invention is described in detail below with reference to specific embodiments:

[0069] Step 1: Use Monte Carlo simulation software to establish a formation detection model.

[0070] See also Figure 2 Monte Carlo numerical simulations were performed using a formation detection model. The instrument structure primarily consists of a radioactive source, detector, instrument housing, and shielding. The radioactive source is a 137Cs source, the instrument housing is constructed of titanium alloy, the shield is made of tungsten-nickel-iron, and the lower portion of the instrument is wrapped in a boron sheath. The main dimensions of the logging instrument are: the instrument has a diameter of 42 mm and a length of 500 mm. The long-source-standoff detector is a cylindrical lanthanum bromide crystal with a radius of 14 mm and a length of 13 mm. The short-source-standoff detector is a cylindrical lanthanum bromide crystal with a radius of 17 mm and a length of 20 mm. The wellbore and formation are designed as a series of cylinders, with a wellbore radius of 10 cm, a formation radius ranging from 10 cm to 80 cm, and a height of 100 cm.

[0071] This example uses Monte Carlo (MCNP) numerical simulation to establish Figure 2 In the formation detection model shown, the formation material to be measured is set to be a pure sandstone formation with a porosity of 10% and 100% saturation with water. The long detector and the short detector are simulated respectively by changing the source distance.

[0072] Step 2: Obtain the relationship between the count rate and the long source distance and the short source distance from the formation detection model, and preliminarily screen the value range of the long source distance and the short source distance.

[0073] According to the actual density logging instrument, the simulated porosity φ is 0%, 10%, 20%, 30%, and 40% respectively for pure sandstone formations with water content. The long source distance of the long detector is 37cm-41cm, and the short source distance of the short detector is 16cm-20cm. The relationship between the counting rate and the long source distance and the short source distance is obtained, as shown in the following figure: Figure 3 and Figure 4As shown. The longer the source distance, the deeper the formation needs to be measured. The higher the count rate received by the detector, the more conducive it is to analyzing the physical properties of the reservoir. Therefore, the longer the source distance, the higher the count rate is. Figure 3 After analysis, we found that the range of the long source distance is 37-40cm. The short source distance mainly measures the mud cake and plays a compensation role, so the appropriate counting rate can meet the needs. Figure 4 After analysis, it was found that the range of short source distance is 16cm-20cm.

[0074] Step three: further screen the value ranges of long source distance and short source distance based on the statistical error and measurement accuracy of the formation detection model.

[0075] By analyzing the errors corresponding to the measurement results obtained by Monte Carlo numerical simulation, we can get the relationship between source distance and error. As the source distance increases, the measurement error becomes larger, such as Figure 5 and Figure 6 As shown. Monte Carlo numerical simulation density logging requires the measurement error to be less than 1%. Figure 5 and Figure 6 The relationship shown in the figure shows that for long source distances, when the source distance is 41 cm, the measurement error is greater than 1%, resulting in a measurement range of 37-40 cm for long source distances. For short source distances, due to the closer distance to the source, the count rate is higher, and the measurement accuracy is higher, so the requirement of a measurement error less than 1% is met for source distances of 16-20 cm.

[0076] According to the measurement accuracy analysis of the EILog instrument (source is 1.5Ci), we can get Figure 7 The relationship between the density measurement error and the count rate. As can be seen from the figure, when the density error is below 0.01g / cm3, the minimum count rate required is 3070cps. Since the density error is mainly determined by the long source distance, the relationship between the long source distance count rate and the long source distance is calculated here, as shown in the figure. Figure 8 As shown in the figure, when the density error is below 0.01g / cm³, the required minimum count rate is 3070cps, and the maximum source distance should be below 39cm. Taking all factors into consideration, the optimal maximum source distance is between 37-39cm.

[0077] Step 4: Use the short source distance compensation function and sensitivity requirements to determine the final value range of the short source distance.

[0078] In density logging, short detectors need to measure the physical properties of the near-surface formation, so the sensitivity requirements for short detectors are relatively high. The sensitivity definition formula is:

[0079]

[0080] In actual work, relative sensitivity S is often used to express the sensitivity of the instrument, and its definition formula is:

[0081]

[0082] The relationship between relative sensitivity and short source distance is as follows: Figure 9 As shown in Figure 1, the relative sensitivity increases with the increase of the short source distance. High sensitivity is not conducive to the measurement of near-ground layers at short source distances, so the value of the short source distance can be shortened to less than 19 cm.

[0083] Based on the compensation function of short source distance for long source distance, this paper further determines the value range of short source distance by comparing the sensitivity under different source distance combinations, as shown in the following table:

[0084] Table 1 Sensitivity analysis of different source distance combinations

[0085]

[0086] Table 1 shows that for a fixed long source distance, increasing the short source distance and decreasing the distance between near and far detectors decreases both the absolute and relative sensitivity of density measurements. Greater density decreases relative sensitivity, while absolute sensitivity remains constant. Therefore, to improve density measurement sensitivity, increasing both the source distance and detector spacing as much as possible is recommended. Therefore, from the perspective of combined sensitivity of short and long source distances, the short source distance can be between 16 and 18 cm.

[0087] See also Figure 10 The embodiment of the present invention provides a source distance determination system for density logging, comprising:

[0088] Modeling unit, using Monte Carlo simulation software to establish a formation detection model;

[0089] Preliminary screening of units: using the formation detection model to obtain the relationship between the count rate and the long detector source distance and the short detector source distance, and preliminarily screening the value range of the long source distance and the short source distance;

[0090] The secondary screening unit further screens the range of long source distance and short source distance according to the statistical error and measurement accuracy of the formation detection model;

[0091] The final screening unit uses the short source distance compensation function and sensitivity requirements to determine the final value range of the short source distance.

[0092] See also Figure 11 The third object of the present invention is to provide an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for determining the source distance of density logging when executing the computer program.

[0093] Establishing a formation detection model using Monte Carlo simulation software;

[0094] The relationships between the count rate and the long and short source distances are obtained from the formation detection model, and the range of the long and short source distances is preliminarily selected.

[0095] The range of long source distance and short source distance is further screened based on the statistical error and measurement accuracy of the formation detection model;

[0096] The short source distance compensation function and sensitivity requirements are used to determine the final value range of the short source distance.

[0097] A fourth object of the present invention is to provide a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for determining source distance of density logging.

[0098] Establishing a formation detection model using Monte Carlo simulation software;

[0099] The relationships between the count rate and the long and short source distances are obtained from the formation detection model, and the range of the long and short source distances is preliminarily selected.

[0100] The range of long source distance and short source distance is further screened based on the statistical error and measurement accuracy of the formation detection model;

[0101] The short source distance compensation function and sensitivity requirements are used to determine the final value range of the short source distance.

[0102] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0104] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps of the function specified in one or more boxes, such as Figure 8 shown.

[0106] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for determining source distance of density logging, characterized in that: The following steps are involved: Establishing a formation detection model using Monte Carlo simulation software; The relationships between the count rate and the long and short source distances are obtained from the formation detection model, and the range of the long and short source distances is preliminarily selected. The relationships between the count rate and the long source distance and the short source distance are obtained from the formation detection model, and the preliminary screening of the value ranges of the long source distance and the short source distance comprises the following steps: Estimate the maximum long source distance value range of the long source distance detector and the maximum short source distance value range of the short source distance detector of the logging instrument; uniformly selecting a number of point values ​​in the maximum long source distance value range and the maximum short source distance value range, respectively, and inputting the point values ​​into the formation detection model to obtain the counting rate corresponding to each point value, thereby obtaining the relationship between the counting rate and the long source distance and the short source distance; Since the counting rate corresponding to the long source distance requires measuring deeper strata, the higher the counting rate received by the long source distance detector, the more conducive it is to analyzing the physical properties of the reservoir. Therefore, the long source distance detector requires a high counting rate, further screening the value range of the long source distance; while the short source distance measures the mud cake, which plays a compensatory role. Therefore, the appropriate counting rate meets the requirements, further screening the value range of the short source distance; The range of long source distance and short source distance is further screened based on the statistical error and measurement accuracy of the formation detection model; The further screening of the value ranges of the long source distance and the short source distance based on the statistical error and measurement accuracy of the formation detection model comprises the following steps: Input different values ​​of long source distance and short source distance in the formation detection model to obtain the corresponding measurement results; Performing error analysis on the measurement results to obtain relationships between long source distance, short source distance and error respectively; The formation detection model simulates density logging and requires the measurement error to be less than 1%. Based on this, the value ranges of long source distance and short source distance are further selected; The short source distance compensation function and the sensitivity A requirement are used to determine the final value range of the short source distance. Determining the final value range of the short source distance by using the short source distance compensation function and the sensitivity A requirement includes the following steps: Evenly selecting a number of point values ​​within the short source distance value range after further screening, and inputting the point values ​​into the formation detection model, obtaining the counting rate corresponding to each point value, and then calculating the relative sensitivity S from the counting rate, and obtaining the relationship between the relative sensitivity S and the short source distance; Since the larger the relative sensitivity S is, the less favorable it is for a short detector to measure the reservoir, the range of the value of the short source distance is further narrowed. According to the compensation function of short source distance for long source distance, the relative sensitivity S under several different combinations of long and short source distances is obtained. As the larger the relative sensitivity S, the less favorable it is for short detectors to measure reservoirs, the final value range of the short source distance is determined.

2. The method for determining source distance of density logging according to claim 1, characterized in that: The Monte Carlo simulation software is used to establish a stratum detection model, which includes the following steps: A well logging instrument model was established; the well logging instrument included a radioactive source, a long-source-spacing detector, a short-source-spacing detector, an instrument housing, and a shield; the radioactive source was a 137Cs source; the well logging instrument housing was made of titanium alloy; the shield was made of tungsten-nickel-iron; the well logging instrument had a diameter of 42 mm and a length of 500 mm; the long-source-spacing detector was a cylindrical lanthanum bromide crystal with a radius of 14 mm and a length of 13 mm, and the short-source-spacing detector was a cylindrical lanthanum bromide crystal with a radius of 17 mm and a length of 20 mm; A wellbore and formation model was established; the wellbore and formation were designed as a series of cylinders, with a wellbore radius of 10 cm, a formation radius ranging from 10 cm to 80 cm, and a height of 100 cm.

3. The method for determining source distance of density logging according to claim 1, characterized in that: The sensitivity A and relative sensitivity S are: The sensitivity A is: In actual work, the sensitivity A is represented by relative sensitivity S, which is: in, N represents the counting rate; ρ represents the formation density.

4. The method for determining source distance of density logging according to claim 1, characterized in that: The compensation function of the short source distance to the long source distance specifically includes: When the long source distance is fixed and the short source distance increases, the distance between the long source distance detector and the short source distance detector decreases, and both the sensitivity A and the relative sensitivity S decrease. When the density increases, the relative sensitivity S decreases, while the sensitivity A remains unchanged. Therefore, the short source distance and the distance between the long source distance detector and the short source distance detector should be increased to improve the sensitivity A, thereby determining the final value range of the short source distance.

5. A density logging source distance determination system, characterized in that: include: Modeling unit, using Monte Carlo simulation software to establish a formation detection model; Preliminary screening of units: using the formation detection model to obtain the relationship between the count rate and the long detector source distance and the short detector source distance, and preliminarily screening the value range of the long source distance and the short source distance; The relationships between the count rate and the long source distance and the short source distance are obtained from the formation detection model, and the preliminary screening of the value ranges of the long source distance and the short source distance comprises the following steps: Estimate the maximum long source distance value range of the long source distance detector and the maximum short source distance value range of the short source distance detector of the logging instrument; uniformly selecting a number of point values ​​in the maximum long source distance value range and the maximum short source distance value range, respectively, and inputting the point values ​​into the formation detection model to obtain the counting rate corresponding to each point value, thereby obtaining the relationship between the counting rate and the long source distance and the short source distance; Since the counting rate corresponding to the long source distance requires measuring deeper strata, the higher the counting rate received by the long source distance detector, the more conducive it is to analyzing the physical properties of the reservoir. Therefore, the long source distance detector requires a high counting rate, further screening the value range of the long source distance; while the short source distance measures the mud cake, which plays a compensatory role. Therefore, the appropriate counting rate meets the requirements, further screening the value range of the short source distance; The secondary screening unit further screens the range of long source distance and short source distance according to the statistical error and measurement accuracy of the formation detection model; The further screening of the value ranges of the long source distance and the short source distance based on the statistical error and measurement accuracy of the formation detection model comprises the following steps: Input different values ​​of long source distance and short source distance in the formation detection model to obtain the corresponding measurement results; Performing error analysis on the measurement results to obtain relationships between long source distance, short source distance and error respectively; The formation detection model simulates density logging and requires the measurement error to be less than 1%. Based on this, the value ranges of long source distance and short source distance are further selected; The final screening unit uses the short source distance compensation function and the sensitivity A requirement to determine the final value range of the short source distance; Determining the final value range of the short source distance by using the short source distance compensation function and the sensitivity A requirement includes the following steps: Evenly selecting a number of point values ​​within the short source distance value range after further screening, and inputting the point values ​​into the formation detection model, obtaining the counting rate corresponding to each point value, and then calculating the relative sensitivity S from the counting rate, and obtaining the relationship between the relative sensitivity S and the short source distance; Since the larger the relative sensitivity S is, the less favorable it is for a short detector to measure the reservoir, the range of the value of the short source distance is further narrowed. According to the compensation function of short source distance for long source distance, the relative sensitivity S under several different combinations of long and short source distances is obtained. As the larger the relative sensitivity S, the less favorable it is for short detectors to measure reservoirs, the final value range of the short source distance is determined.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for determining source distance of density logging according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for determining source distance of density logging according to any one of claims 1 to 4.

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