Formation density calculation method and device for variable energy window gamma density logging and storage medium
By using the variable energy window gamma density logging method, changing the energy window boundary and optimizing the combination, the problem of inaccurate density calculation in heavy mud cake environment was solved, and higher measurement accuracy and parameter adjustment capability were achieved.
Patent Information
- Application Number
- CN202410960297.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-17
- Publication Date
- 2026-01-20
- Estimated Expiration
- 2044-07-17
AI Technical Summary
In formations with heavy mud cake, existing technologies suffer from poor matching between the energy window and the peak fall edge of gamma density logging tools, leading to inaccurate formation density calculations.
The variable energy window gamma density logging method is adopted. By changing the energy window boundary through a traversal algorithm, a reasonable energy window range is obtained. The energy window boundary combination is optimized by using the compensation density calculation formula and data similarity comparison to improve the calculation accuracy.
In formation environments containing mud cake, the measurement accuracy of the density logging tool is significantly improved. It is applicable to both simulated and measured spectra and features adjustable parameters, further enhancing the accuracy of density calculation.
Smart Images
Figure CN121363413A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the technical field of nuclear logging formation density, and particularly relates to a formation density calculation method and device for variable energy window gamma density logging and a storage medium. BACKGROUND
[0002] In the field of nuclear logging, when logging is performed by using a gamma density logging instrument, gamma photons are emitted by a gamma source to a formation, and after scattering and absorption of the gamma photons by the formation, part of the scattered photons is received by two gamma ray detectors at different distances from the source. The density of the formation is different, the scattering and absorption capabilities of the gamma photons are different, and the readings recorded by the detectors are also different. The interaction of gamma rays with matter mainly includes Compton effect, photoelectric effect and electron pair effect. Only the Compton effect is proportional to the formation density. According to this principle, there is a compensated gamma density logging formula, and the formation density can be calculated by using the formula.
[0003] At present, a fixed energy window method is mainly used to obtain the formation density. In the formation environment without heavy mud cake, the fixed energy window method can better match the part of the energy spectrum reflecting the Compton effect, that is, the falling edge of the peak. However, when there is heavy mud cake in the formation, the peak of the energy spectrum will be greatly shifted, so that the energy window and the falling edge of the peak cannot be well matched, and therefore the formation density cannot be accurately calculated. SUMMARY
[0004] The application provides a formation density calculation method and device for variable energy window gamma density logging and a storage medium, which mainly changes the energy window boundary to obtain a reasonable energy window range in the energy spectrum of each formation, and then more accurate formation density is obtained.
[0005] The application is implemented by the following technical scheme:
[0006] On one hand, the application provides a formation density calculation method for variable energy window gamma density logging, which includes the following steps:
[0007] Step S1: Obtain the response energy spectrum of the gamma density logging instrument in different known formation environments, and record each formation environment and the response energy spectrum as a “formation environment-energy spectrum database”;
[0008] Step S2: Change the energy window boundary of the response energy spectrum by using a traversal algorithm, traverse the energy corresponding to the response energy spectrum channel, divide the response energy spectrum by energy channel, obtain different energy window boundary combinations and the density count under the combination;
[0009] Step S3: Use the compensated density calculation formula of the gamma density logging instrument to calculate the density of different energy window boundary combinations and the density count under the combination, and take the calculation result as the apparent density under different energy window boundary combinations;
[0010] Step S4: Based on the calculated apparent density and the true density of the formation, the screening is performed to exclude accidental results, and the energy window boundary combination meeting the conditions is screened out, and the energy window boundary combination with the minimum relative error is obtained by taking the minimum value, and is recorded as the optimal energy window boundary combination under the formation;
[0011] Step S5: The steps S1-S4 are applied to different known formation environments, and the optimal energy window boundary combination corresponding to each formation environment is stored in a "formation-optimal energy window combination database", and the "formation-optimal energy window combination database" is combined with the "formation environment-energy spectrum database" to obtain a "formation environment-energy spectrum-optimal energy window combination database";
[0012] Step S6: The response energy spectrum of the gamma density logging instrument in the formation environment to be measured is obtained as a to-be-measured response energy spectrum;
[0013] Step S7: The similarity between the to-be-measured response energy spectrum and the recorded response energy spectrum is compared by using a data similarity comparison method, and the recorded response energy spectrum with the highest similarity is selected;
[0014] Step S8: The "formation environment-energy spectrum-optimal energy window combination database" is queried to obtain the optimal energy window boundary combination corresponding to the recorded response energy spectrum with the highest similarity as a new energy window range, and the apparent density of the new energy window range is calculated by using a compensation density calculation formula to obtain a final calculation result.
[0015] In step S1, the response energy spectrum of the gamma density logging instrument in different known formation environments is obtained by a scale well experiment or by a density logging model of different formation environments established on simulation software.
[0016] Further, the formation environment includes mud cake density, mud cake thickness, lithology, formation density, mud gap, and mud density; the response energy spectrum includes a long source distance detector energy spectrum and a short source distance detector energy spectrum; each formation environment and its long source distance detector energy spectrum and short source distance detector energy spectrum are recorded as a "formation environment-energy spectrum database".
[0017] Further, the long source distance detector energy spectrum and the short source distance detector energy spectrum each have different energy window intervals, and the energy window interval has a high-energy boundary E high and a low-energy boundary E low , wherein: in the energy window interval of the long source distance detector energy spectrum, the high-energy boundary is LE high , and the low-energy boundary is LE low ; in the energy window interval of the short source distance detector energy spectrum, the high-energy boundary is SE high , and the low-energy boundary is SE low .
[0018] wherein in step S2, the energy window boundary of the response energy spectrum is changed by a traversal algorithm, the traversal algorithm comprising the following steps:
[0019] S201: finding a peak value E of the response energy spectrum m , E m being the energy corresponding to the channel address with the highest count rate in the entire response energy spectrum;
[0020] S202: initializing a low-energy boundary E low , a high-energy boundary E high , E low =E m , E high =E low ;
[0021] S203: sliding E low , E high rightward by a step size each time, until E high is greater than 0.662 MeV;
[0022] S204: calculating the count sum, i.e. the density count N, within the current energy window range each time E high is slid, and recording the current energy window boundary combination and the density count, i.e. E low , E high and N;
[0023] S205: ending the traversal until E low is greater than 0.662 MeV.
[0024] Further, by performing the above traversal of the energy window boundary on the response energy spectrum of the long and short source-detector distance detectors respectively, different energy window boundary combinations of the long and short source-detector distance detectors and the density counts under such combinations can be obtained.
[0025] wherein in step S3, the compensation density calculation formula of the gamma density logging tool is specifically: wherein, p b is the calculated apparent density, A L , A s are known coefficients related to the long and short source-detector distance detectors and the formation environment respectively, B L , B S are known coefficients related to the long and short source-detector distance detectors and the formation environment respectively, N L , N S are the sums of the density count rates in the specific energy intervals of the long and short source-detector distance detectors respectively, and k is a fitting coefficient related to the long and short source-detector distance detectors and the formation environment.
[0026] The calculated apparent density p of each long and short source distance energy window boundary combination is calculated by the compensated density calculation formula of the density logging instrument b .
[0027] In step S4, the calculated apparent density is compared with the true density of the formation, and the comparison is screened according to the following steps:
[0028] Step S401: The energy window width is set to be greater than 10 channel widths, i.e., E high -E low > 10 x 0.003198 MeV;
[0029] Step S402: The relative error e between the true density and the energy window boundary combination meeting the conditions is calculated.
[0030] Step S403: The energy window boundary combination with the minimum relative error e is recorded as the optimal energy window boundary combination of the formation.
[0031] Further, the calculation method of the relative error e is as follows: In the formula, p is the true density value of the formation, which is known, and p b is the apparent density. Whether the gamma density logging instrument response energy spectrum is obtained through the calibration experiment or the gamma density logging instrument response energy spectrum is obtained in the density logging model of different formation environments established on the simulation software, the true density value of the formation is known.
[0032] In step S7, the data similarity comparison method is to solve the norm, and specifically includes the following steps:
[0033] Step S701: The norm between the response energy spectrum of the unrecorded formation environment and all existing response energy spectrums is calculated.
[0034] Step S702: The response energy spectrum with the minimum norm between the response energy spectrum of the unrecorded formation environment and all existing response energy spectrums is found out as the response energy spectrum with the highest similarity.
[0035] Further, the calculation formula of the norm solving method is as follows: In the formula, d represents the norm between the response energy spectrum of the unrecorded formation environment and all existing response energy spectrums, N i represents the i-th channel density count of the existing energy spectrum, and n i represents the i-th channel density count of the obtained response energy spectrum to be measured.
[0036] In one aspect, the application provides a formation density calculation device of variable energy window gamma density logging, comprising: a data acquisition module, an energy window revision module, a density calculation module, an optimal energy window screening module, an optimal energy window storage module, a to-be-tested data acquisition module, a similarity judgment module, and a solving module.
[0037] The data acquisition module is configured to acquire response energy spectra of a gamma density logging instrument in different known formation environments, and record the response energy spectrum of each known formation environment as a "formation environment-energy spectrum database".
[0038] The energy window revision module is configured to change the energy window boundary of the response energy spectrum, divide the response energy spectrum by energy channel through an iteration algorithm, and acquire different energy window boundary combinations and density counts under the combinations.
[0039] The density calculation module is configured to calculate the density of different energy window boundary combinations and the density counts under the combinations, and take the calculation results as the apparent density under different energy window boundary combinations.
[0040] The optimal energy window screening module is configured to screen the calculated apparent density and the true density of the formation, exclude accidental results, screen out energy window boundary combinations meeting the conditions, and take the minimum value method to obtain the energy window boundary combination with the smallest relative error, which is recorded as the optimal energy window boundary combination under the formation.
[0041] The optimal energy window storage module is configured to store the optimal energy window boundary combination corresponding to each formation environment in different known formation environments into a "formation-optimal energy window combination database", and combine the "formation-optimal energy window combination database" with the "formation environment-energy spectrum database" to obtain a "formation environment-energy spectrum-optimal energy window combination database".
[0042] The to-be-tested data acquisition module is configured to acquire the response energy spectrum of the gamma density logging instrument in the to-be-tested formation environment.
[0043] The similarity judgment module is configured to compare the similarity between the to-be-tested response energy spectrum and the recorded response energy spectrum, and select the recorded response energy spectrum with the highest similarity.
[0044] The solving module is configured to query the "formation environment-energy spectrum-optimal energy window combination database", obtain the optimal energy window boundary combination corresponding to the recorded response energy spectrum with the highest similarity as a new energy window range, calculate the apparent density of the new energy window range using a compensation density calculation formula, and obtain the final calculation result.
[0045] In one aspect, the application also provides an electronic readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the method for calculating formation density of variable energy window gamma density logging.
[0046] Compared with the prior art, the application has the following advantages:
[0047] 1. The application adopts the method of variable energy window and the most similar calculation, so that the energy window interval can be changed when the mud cake existing in the logging environment causes the energy spectrum to deviate, and the measurement precision of the density logging instrument is improved.
[0048] 2. The application is suitable for analog spectrum and measured spectrum, and has an adjustable parameter function, so that targeted parameter adjustment can be implemented on different density logging instruments, and the density calculation precision is further improved.
[0049] Other features and advantages of the application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the application. The objects and other advantages of the application can be achieved and obtained by the structure indicated in the specification, claims and drawings. BRIEF DESCRIPTION OF DRAWINGS
[0050] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.
[0051] Figure 1 A flowchart of a method for calculating formation density of variable energy window gamma density logging is shown;
[0052] Figure 2 Another flowchart of a method for calculating formation density of variable energy window gamma density logging is shown;
[0053] Figure 3 A flowchart of a method for calculating formation density of variable energy window gamma density logging is shown;
[0054] Figure 4 A comparison chart of error effects of fixed energy window and sliding energy window simulation data is shown;
[0055] Figure 5 A comparison chart of error effects of fixed energy window and sliding energy window experimental data is shown. DETAILED DESCRIPTION
[0056] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of the present application.
[0057] Embodiment one.
[0058] In an embodiment, referring to Figure 1 , Figure 2 and Figure 3 , the present application provides a formation density calculation method of variable energy window gamma density logging, comprising the following steps:
[0059] Step S1: obtaining the response energy spectrum of the gamma density logging instrument in different known formation environments, and recording each formation environment and the response energy spectrum as a "formation environment-energy spectrum database";
[0060] Further, the obtaining method of the response energy spectrum of the gamma density logging instrument in different known formation environments comprises: obtaining through a calibration well experiment or obtaining through a density logging model of different formation environments established on simulation software.
[0061] Further, the formation environment comprises mud cake density, mud cake thickness, lithology, formation density, mud gap and mud density; the response energy spectrum comprises long source distance detector energy spectrum and short source distance detector energy spectrum; each formation environment and its long source distance detector energy spectrum and short source distance detector energy spectrum are recorded as a "formation environment-energy spectrum database".
[0062] Further, the long source distance detector energy spectrum and the short source distance detector energy spectrum both have different energy window intervals, and the energy window interval has a high energy boundary E high and a low energy boundary E low , wherein: in the energy window interval of the long source distance detector energy spectrum, the high energy boundary is LE high and the low energy boundary is LE low ; in the energy window interval of the short source distance detector energy spectrum, the high energy boundary is SE high and the low energy boundary is SE low .
[0063] Step S2: changing the energy window boundary of the response energy spectrum by using a traversal algorithm, traversing the energy corresponding to the response energy spectrum channel address and dividing the response energy spectrum by energy channel address to obtain different energy window boundary combinations and the density count under the combination;
[0064] Further, referring to Figure 3The traversal algorithm comprises the following steps:
[0065] S201: finding a peak value E in the response spectrum m m E is the energy corresponding to the channel address with the highest count rate in the entire response spectrum;
[0066] S202: initializing a low-energy boundary E low , a high-energy boundary E high , setting E low =E m , and E high =E low ;
[0067] S203: sliding E low , E high to the right several times each time E high is slid by one step to the right, until E high is greater than 0.662 MeV;
[0068] S204: calculating the sum of counts in the current energy window range, i.e., the density count N, each time E high is slid, recording the current energy window boundary combination and the density count, i.e., E low , E high , and N;
[0069] S205: ending the traversal until the energy E low is greater than 0.662 MeV.
[0070] Further, by performing the above traversal of the energy window boundary on the response spectra of the long and short source distance detectors respectively, different energy window boundary combinations of the long and short source distance detectors and the density counts under such combinations can be obtained.
[0071] Step S3: using a compensated density calculation formula of the gamma density logging instrument to calculate the density under different energy window boundary combinations and the density count under the combination, and taking the calculation result as the apparent density under different energy window boundary combinations;
[0072] Further, the compensated density calculation formula of the gamma density logging instrument is specifically as follows: In the formula, p b is the calculated apparent density, A L and A s are known coefficients related to the long and short source distance detectors and the formation environment respectively, B L and B S are known coefficients related to the long and short source distance detectors and the formation environment respectively, N L and N Srespectively, k is a fitting coefficient related to the formation environment of the long and short source distance detectors.
[0073] The calculated apparent density p of each long and short source distance energy window boundary combination is calculated by the compensated density calculation formula of the density logging tool b .
[0074] Step S4: Based on the calculated apparent density and the true density of the formation, the screening is performed, the accidental results are excluded, the energy window boundary combination meeting the conditions is screened out, the energy window boundary combination with the minimum relative error is obtained by taking the minimum value, and is recorded as the optimal energy window boundary combination under the formation;
[0075] Further, the screening based on the calculated apparent density and the true density of the formation includes the following steps:
[0076] Step S401: The energy window width is set to be greater than 10 channel widths, i.e., E high -E low > 10 x 0.003198 MeV;
[0077] Step S402: The relative error e between the energy window boundary combination meeting the conditions and the true density is obtained.
[0078] Step S403: The energy window boundary combination with the minimum relative error e is recorded as the optimal energy window boundary combination under the formation.
[0079] Further, the calculation method of the relative error e is as follows: In the formula, p is the true density value of the formation, which is known, and p b is the apparent density. Whether the gamma density logging tool response energy spectrum is obtained through the calibration experiment or the density logging model of different formation environments is established on the simulation software, the true density value of the formation is known.
[0080] Step S5: The steps S1 to S4 are applied to different formation environments, the optimal energy window boundary combination corresponding to each formation environment is stored in the “formation-optimal energy window combination database”, the “formation-optimal energy window combination database” is combined with the “formation environment-energy spectrum database”, and the “formation environment-energy spectrum-optimal energy window combination database” is obtained.
[0081] Step S6: The response energy spectrum under the formation environment of the to-be-measured gamma density logging tool is obtained as the to-be-measured response energy spectrum.
[0082] Step S7: using the data similarity comparison method, comparing the similarity between the to-be-tested response spectrum and the recorded response spectrum, and selecting the recorded response spectrum with the highest similarity;
[0083] Further, the data similarity comparison method uses a norm solving method, specifically including:
[0084] Step S701: calculating the norm between the response spectrum of the unrecorded formation environment and all existing response spectrums;
[0085] Step S702: finding the spectrum with the smallest norm between the response spectrum of the unrecorded formation environment and the response spectrum obtained this time as the recorded response spectrum with the highest similarity through the calculated norm.
[0086] Further, the specific calculation formula of the norm solving method is: In the formula, d represents the norm between the response spectrum of the unrecorded formation environment and all existing response spectrums, N i represents the i-th channel density count of the existing spectrum, n i represents the i-th channel density count of the to-be-tested response spectrum obtained this time.
[0087] Step S8: querying the "formation environment-spectrum-optimal energy window combination database" to obtain the optimal energy window boundary combination corresponding to the recorded response spectrum with the highest similarity as a new energy window range, using the compensated density calculation formula to calculate the apparent density of the new energy window range to obtain the final calculation result.
[0088] Embodiment two.
[0089] In an embodiment, please refer to Figure 4 and Figure 5 .
[0090] Figure 4 The fixed energy window and sliding energy window simulation data error effect comparison chart is the energy spectrum of the logging instrument in different formation environments obtained in the density logging model of the Monte Carlo simulation software, and the experimental data obtained by the method used in the present application;
[0091] Figure 5 The fixed energy window and sliding energy window experimental data error effect comparison chart is the energy spectrum of the logging instrument in different formation environments obtained in the calibration well experiment, and the experimental data obtained by the method used in the present application;
[0092] Further, whether the energy spectrum of the logging instrument in different formation environments is obtained in the simulation software or in the calibration well experiment, the experimental operation process after obtaining the energy spectrum is the same, and the specific implementation operation is as follows:
[0093] obtaining the response spectrum of the litho-density logging tool LDLT1550 under different mud cake thickness and mud cake density, the response spectrum including the short source distance detector spectrum and the long source distance detector spectrum; and recording each formation environment and its short source distance detector spectrum and long source distance detector spectrum as the "formation environment-spectrum database" of the litho-density logging tool LDLT1550;
[0094] changing the energy window boundary of the short and long source distance by using the traversal algorithm, dividing the energy spectrum into 207 channels by traversing the energy channel corresponding to the short source distance detector spectrum and the long source distance detector spectrum, and dividing 0-0.662 MeV; the short and long source distance detectors have different energy window intervals, the energy window interval has a high energy boundary E high and a low energy boundary E low ; the long source distance energy window high energy boundary is LE high , the long source distance energy window low energy boundary is LE low , the short source distance energy window high energy boundary is SE high , and the short source distance energy window low energy boundary is SE low ; the above operation of changing the energy window boundary is performed on the long and short source distance detector response spectrum respectively, so that the different energy window boundary combinations of the long and short source distance detectors of the litho-density logging tool LDLT1550 and the density count under the combination are obtained;
[0095] based on the density count, calculating the apparent density in different energy window ranges; the mud cake compensated density calculation formula of the litho-density logging tool LDLT1550 is: in the formula, ρ b is the calculated density, N L and N S are the sum of the density count rate in the specific energy interval in the long and short source distance detector spectrum respectively; the calculated density ρ b under each long and short source distance energy window boundary combination is calculated by using the compensated density calculation formula;
[0096] based on the apparent density, calculating the relative error between the apparent density and the true density, and screening the optimal energy window combination;
[0097] applying the above operation steps to different formation environments, recording the optimal energy window boundary combination corresponding to each formation environment as the "formation-optimal energy window combination database", and combining the "formation environment-spectrum database" to obtain the "formation environment-spectrum-optimal energy window combination database";
[0098] Obtain 9 formation density + 8 kinds of light and heavy mud cake density measured spectrum data as measured spectrum data, the measured spectrum data is based on the 'formation environment-spectrum-optimal energy window combination database' obtained in the density logging model of different formation environments established on the Monte Carlo simulation software, and is based on the 'formation environment-spectrum-optimal energy window combination database' obtained in the calibration well experiment; the following operations are performed respectively:
[0099] Compare the similarity between the measured spectrum data and the recorded response spectrum, and select the highest similarity of the existing response spectrum;
[0100] Query the 'formation environment-spectrum-optimal energy window combination database' to obtain the optimal energy window boundary combination corresponding to the highest similarity of the existing response spectrum as a new energy window range, and use the compensated density calculation formula to calculate the apparent density of the new energy window range to obtain the final calculation result.
[0101] The results are shown in the data comparison graphs of Figure 4 and Figure 5 .
[0102] From the data comparison in Figure 4 and Figure 5 , it can be seen that the measurement accuracy of the present application is improved by one order of magnitude.
[0103] Example Three.
[0104] In an embodiment, a variable energy window gamma density logging formation density calculation device is provided, comprising: a data acquisition module, an energy window revision module, a density calculation module, an optimal energy window screening module, a best energy window storage module, a measured data acquisition module, a similarity judgment module, and a solving module.
[0105] The data acquisition module is used to obtain the response spectrum of the gamma density logging instrument in different known formation environments, and record the response spectrum of each known formation environment as 'formation environment-spectrum database'
[0106] The energy window revision module is used to change the energy window boundary of the response spectrum, and the energy channel of the response spectrum is divided by traversing the energy corresponding to the response spectrum channel through a traversal algorithm, to obtain different energy window boundary combinations and the density count under the combination.
[0107] The density calculation module is used to calculate the density of different energy window boundary combinations and the density count under the combination, and the calculation result is used as the apparent density under different energy window boundary combinations.
[0108] The optimal energy window screening module screens based on the calculated apparent density and the true density of the formation, excludes accidental results, screens out energy window boundary combinations meeting the conditions, and uses the minimum value method to obtain the energy window boundary combination with the smallest relative error, which is recorded as the optimal energy window boundary combination under the formation;
[0109] The optimal energy window storage module is used for storing the optimal energy window boundary combination corresponding to each formation environment in different known formation environments in a "formation-optimal energy window combination database", and connecting the "formation-optimal energy window combination database" with the "formation environment-energy spectrum database" to obtain a "formation environment-energy spectrum-optimal energy window combination database";
[0110] The to-be-tested data acquisition module is used for acquiring the response energy spectrum of the gamma density logging instrument under the formation environment to be tested;
[0111] The similarity judgment module is used for comparing the similarity between the to-be-tested response energy spectrum and the recorded response energy spectrum, and selecting the recorded response energy spectrum with the highest similarity;
[0112] The solving module is used for querying the "formation environment-energy spectrum-optimal energy window combination database", obtaining the optimal energy window boundary combination corresponding to the recorded response energy spectrum with the highest similarity as a new energy window range, calculating the apparent density of the new energy window range using the compensated density calculation formula, and obtaining the final calculation result.
[0113] Embodiment Four.
[0114] In an embodiment, an electronic readable storage medium is provided, and a computer program is stored on the electronic readable storage medium, the computer program being executed by a processor to implement the steps of the formation density calculation method of the variable energy window gamma density logging as described above.
[0115] Although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalent features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims
1. A method for calculating formation density of variable energy window gamma density logging, characterized in that: obtaining the response energy spectrum of a gamma density logging instrument in different known formation environments, and recording the response energy spectrum of each formation environment as a "formation environment-energy spectrum database"; changing the energy window boundary of the response energy spectrum by using a traversal algorithm, traversing the energy of the response energy spectrum channel and dividing the response energy spectrum by energy channel, obtaining different energy window boundary combinations and the density count under the combination; calculating the density of different energy window boundary combinations and the density count under the combination by using the compensation density calculation formula of the gamma density logging instrument, and taking the calculation result as the apparent density under different energy window boundary combinations; screening the calculated apparent density and the true density of the formation based on the calculated apparent density and the true density of the formation, excluding accidental results, screening the energy window boundary combinations that meet the conditions, and taking the minimum value to obtain the energy window boundary combination with the minimum relative error, which is recorded as the optimal energy window boundary combination under the formation; applying the above four steps to different known formation environments, storing the optimal energy window boundary combination corresponding to each formation environment in a "formation-optimal energy window combination database", and combining the "formation-optimal energy window combination database" with the "formation environment-energy spectrum database" to obtain a "formation environment-energy spectrum-optimal energy window combination database"; obtaining the response energy spectrum of the formation environment of the gamma density logging instrument to be measured as the measured response energy spectrum; comparing the similarity between the measured response energy spectrum and the recorded response energy spectrum by using a data similarity comparison method, and selecting the response energy spectrum with the highest similarity; querying the "formation environment-energy spectrum-optimal energy window combination database" to obtain the optimal energy window boundary combination corresponding to the response energy spectrum with the highest similarity as the new energy window range, calculating the apparent density of the new energy window range by using the compensation density calculation formula to obtain the final calculation result. The response energy spectrum of the gamma density logging instrument in different known formation environments is obtained by: Through a calibration well experiment; Through a density logging model of different formation environments established on simulation software. 3.The method according to claim 1, characterized in that: The formation environment includes mud cake density, mud cake thickness, lithology, formation density, mud gap, and mud density. The response energy spectrum includes long source distance detector energy spectrum and short source distance detector energy spectrum. 4.The method according to claim 3, characterized in that: The traversal algorithm specifically includes:
2. A method for formation density calculation for a variable energy window gamma density log according to claim 1 wherein, The apparent density is calculated by: The screening condition based on the calculated apparent density and the true density of the formation includes: The relative error e between the energy window boundary combination that meets the condition and the true density is obtained. The energy window boundary combination with the minimum relative error e is recorded as the optimal energy window boundary combination under the formation. 8.The method according to claim 7, characterized in that: 9.The method according to claim 4, characterized in that: The long source-detector spacing spectrometer and the short source-detector spacing spectrometer each have different energy window intervals, the energy window intervals having a high energy boundary E high and a low energy boundary E low wherein: In the energy window interval of the long source distance detector energy spectrum, the high energy boundary is LE high , and the low energy boundary is LE low ; in the energy window interval of the short source distance detector energy spectrum, the high energy boundary is SE high , and the low energy boundary is SE low .
5. A method of formation density calculation for a variable energy window gamma density log according to claim 4, wherein, Finding the peak E in the response spectrum m , E m is the energy corresponding to the channel address with the highest count rate in the entire response spectrum; Initialize low energy boundary E low , high energy boundary E high , let E low = E m , E high = E low ; Each step E slides to the right low E high You need to slide to the right several times until you reach E. high Greater than 0.662 MeV; E high , the density count N in the current energy window range is calculated, and the current energy window boundary combination and the density count, i.e. E low , E high and N are recorded. Until E low Energy greater than 0.662 MeV, end traversal.
6. A method of formation density calculation for a variable energy window gamma density log according to claim 4, wherein, where p b is the calculated apparent density, A L , A s are known coefficients related to the long and short source spacing detectors and the formation environment, B L , b S are known coefficients related to the long and short source spacing detectors and the formation environment, N L , N S are the sums of the density count rates in specific energy intervals for the long and short source spacing detectors, and k is a fitting coefficient related to the long and short source spacing detectors and the formation environment.
7. A method of formation density calculation for a variable energy window gamma density log according to claim 4 wherein, The energy window width is set to be greater than 10 channel widths, i.e. E high -E low > 10 x 0.003198 MeV; The relative error e is calculated as follows: where p is the real density value of the formation, which is known, and p b is the apparent density. The data similarity comparison method is to solve a norm, and specifically comprises the following steps: Calculate the norm between the response spectrum of the unrecorded formation environment and all existing response spectra; Find the spectrum with the smallest norm between the response spectrum of the unrecorded formation environment and all existing response spectra, as the highest similarity existing response spectrum.
10. A method of formation density calculation for a variable energy window gamma density log according to claim 9, wherein, The calculation formula for solving the norm is: where d represents the norm between the response spectrum of the unrecorded formation environment and all existing response spectra, N i represents the i-th channel density count of the existing spectrum, n i represents the i-th channel density count of the measured response spectrum obtained this time.
11. A formation density calculation device for a variable energy window gamma density log, characterized by, Comprise: A data acquisition module is configured to acquire response spectra of a gamma density logging instrument in different known formation environments, and record the response spectrum of each known formation environment as a "formation environment-spectrum database"; an energy window revision module is configured to change the energy window boundary of the response spectrum, traverse the energy corresponding to the response spectrum channel by a traversal algorithm, and divide the response spectrum by energy channel to acquire different energy window boundary combinations and the density count under the combination; A density calculation module is configured to calculate the density of different energy window boundary combinations and the density count under the combination, and take the calculation result as the apparent density under different energy window boundary combinations; An optimal energy window screening module is configured to screen the calculated apparent density and the true density of the formation, exclude accidental results, screen out energy window boundary combinations meeting the conditions, and take the minimum value method to obtain the energy window boundary combination with the smallest relative error, which is recorded as the optimal energy window boundary combination under the formation; An optimal energy window storage module is configured to store the optimal energy window boundary combination corresponding to each formation environment in different known formation environments into a "formation-optimal energy window combination database", and combine the "formation-optimal energy window combination database" with the "formation environment-spectrum database" to obtain a "formation environment-spectrum-optimal energy window combination database"; A to-be-measured data acquisition module is configured to acquire the response spectrum of the gamma density logging instrument in the formation environment to be measured; A similarity judgment module is configured to compare the similarity between the to-be-measured response spectrum and the existing recorded response spectrum, and select the highest similarity existing response spectrum; A solving module is configured to query the "formation environment-spectrum-optimal energy window combination database", obtain the optimal energy window boundary combination corresponding to the highest similarity existing response spectrum, as a new energy window range, calculate the apparent density of the new energy window range using a compensation density calculation formula, and obtain the final calculation result.
12. An electronically readable storage medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to implement the steps of the formation density calculation method of the variable energy window gamma density logging according to any one of claims 1 to 10.