Multivariable inversion method for buried hill reservoir neutron porosity measurement

Abstract

The invention discloses a multivariable inversion method for measuring the neutron porosity of a buried hill reservoir, and belongs to the technical field of nuclear logging. The multivariable inversion method specifically comprises the following steps: constructing a neutron logging instrument array detector, measuring the buried hill reservoir, calculating a counting ratio R, and defining R1 and R2; constructing a multivariable inversion model, and performing inversion to obtain Por, Por1, Por2, cal and OFFSET; and the relative eccentricity OFFSETRE is defined, iteration inversion is conducted on the OFFSETRE through a dichotomy method, and the well diameter, the relative eccentricity and the porosity are output to serve as inversion results. The method can effectively reduce the negative influence of dual environment effects generated by well diameter fluctuation and instrument eccentric distance change on a logging result, remarkably alleviates the complexity and difficulty of environment correction, greatly improves the accuracy and reliability of neutron porosity measurement of the buried hill reservoir, and has a great significance in improving the oil-gas exploration and development efficiency. And the reservoir evaluation precision is optimized, and the method has extremely important practical significance and application value.

Description

Technical Field

[0001] The invention belongs to the technical field of nuclear well logging, and in particular relates to a multivariate inversion method for neutron porosity measurement of buried hill reservoirs. Background Art

[0002] Formation porosity plays a vital role in reservoir evaluation and oil and gas evaluation. Neutron porosity logging determines the porosity of rocks by measuring the content of hydrogen nuclei in the formation, which is crucial to evaluating the storage capacity of the formation. It can not only effectively identify oil and gas layers, but also distinguish between oil layers and water layers by measuring the difference in the deceleration ability of neutrons, which is of great value to oilfield development and production management. In addition, by measuring the gamma rays produced by the inelastic scattering of neutrons and formation atomic nuclei, the composition of elements in the formation can be analyzed to provide chemical and mineralogical information of the formation. Neutron porosity logging technology can perform real-time formation evaluation during drilling, providing more timely and accurate formation information to optimize drilling plans and improve drilling efficiency. The higher detection depth and vertical resolution of neutron porosity logging technology enable it to provide more detailed formation structure information, which is particularly important for the exploration and development of complex formations.

[0003] With the development of oil and gas exploration technology, the deep buried hill reservoirs in Bohai Sea have gradually become an important target for oil and gas exploration and development in China's offshore basins. Compared with conventional reservoirs, the study area has experienced multiple tectonic movement transformations such as Indosinia, Yanshan, and Himalaya since the Mesozoic Era, and developed multiple groups of faults in the northeast and northwest directions, forming various types of buried hill structures such as fault blocks and fault anticlines. Tectonic movement is the dominant factor in the development of fractures in the study area, and faults developed during the karst period, and the karstification was relatively strong, making the buried hill reservoir space in the study area dominated by a macroscopic "fracture-cavity" system. However, the primary porosity in the study area is low, which greatly increases the difficulty of porosity measurement. At the same time, in the process of processing the measured well data, although there are measured values ​​of the open hole diameter, due to the influence of the calibration accuracy of the ultrasonic rangefinder and the complex downhole environment such as drilling fluid density and instrument velocity measurement, the accuracy of the diameter measurement value obtained using the ultrasonic logging instrument is sometimes difficult to guarantee.

[0004] The size of the wellbore directly determines the impact of the hydrogen index of the drilling fluid outside the instrument on the neutron measurement. And when using the chart, it is necessary to know reliable wellbore parameters in order to obtain accurate correction results. Therefore, when the measurement accuracy of the wellbore is difficult to guarantee, the accuracy of the correction chart method is low. The while-drilling neutron porosity logging instrument is placed in the center of the wellbore to complete the measurement, so the neutron logging results will be affected by both the wellbore and the instrument eccentricity. When the posture of the cable neutron porosity logging instrument changes due to environmental factors, the neutron logging results will also be affected by both the wellbore and the instrument eccentricity, resulting in large measurement errors due to changes in the wellbore hydrogen index.

[0005] Therefore, it is necessary to study the dual influence of well diameter and instrument eccentricity on the neutron porosity logging results of buried hill reservoirs, establish a multi-response model of array detectors, and then design a multivariable inversion method of well diameter, instrument eccentricity and formation porosity to achieve self-correction of the influence of well diameter and eccentricity while accurately inverting the formation porosity. Summary of the invention

[0006] In view of the uncertainty of downhole measurement accuracy caused by well diameter changes and instrument eccentricity in the current neutron porosity logging technology for buried hill reservoirs, and the problems of complex porosity environment correction and limited measurement accuracy caused by this, the present invention provides a multivariable inversion method for neutron porosity measurement in buried hill reservoirs, which greatly improves the accuracy and reliability of neutron porosity measurement in buried hill reservoirs.

[0007] In order to achieve the above purpose, the technical method adopted by the present invention is as follows:

[0008] A multivariate inversion method for neutron porosity measurement of buried hill reservoirs comprises the following steps:

[0009] Step 1, constructing a neutron logging instrument array detector, including 6m near-source distance detectors arranged in a semicircle at a near-source distance, and 6m far-source distance detectors arranged in a semicircle at a far-source distance; wherein m≥1;

[0010] Step 2: Use the neutron logging instrument array detector to measure the buried hill reservoir and calculate the count ratio R between the detector near the source and the detector far from the source:

[0011]

[0012] According to the positions of each near-source distance detector and each far-source distance detector in the array detector of the neutron logging instrument, a first counting ratio R1 and a second counting ratio R2 are defined:

[0013]

[0014] Where N i ,i=1,2,…,6m is the counting rate of the ith,i=1,2,…,6m detector close to the source; F i ,i=1,2,…,6m is the counting rate of the i-th far-source detector;

[0015] Step 3: Construct a multivariable inversion model:

[0016]

[0017] Wherein, Por is the porosity of the neutron logging instrument array detector under the detector combination corresponding to R; Por1 is the porosity of the neutron logging instrument array detector under the detector combination corresponding to R1; Por2 is the porosity of the neutron logging instrument array detector under the detector combination corresponding to R2; cal is the well diameter; OFFSET is the instrument eccentricity; a, b and c are all response coefficients obtained by fitting based on the calibration wells with known porosities tested by the neutron logging instrument array detector under the detector combination corresponding to R; a1, b1 and c1 are all obtained by fitting based on the calibration wells with known porosities tested by the neutron logging instrument array detector under the detector combination corresponding to R1 a2, b2 and c2 are all response coefficients obtained by fitting the calibration wells with known porosity tested by the array detector of the neutron logging instrument under the detector combination corresponding to R2; d′1′, d′1, d1, e1″, e1′ and e1 are all response coefficients obtained by Monte Carlo simulation of the curve of different porosities changing with the instrument eccentricity by the array detector of the neutron logging instrument under the detector combination corresponding to R1; d′2′, d′2, d2, e2″, e2′ and e2 are all response coefficients obtained by Monte Carlo simulation of the curve of different porosities changing with the instrument eccentricity by the array detector of the neutron logging instrument under the detector combination corresponding to R2;

[0018] According to R, R1 and R2, Por, Por1, Por2, cal and OFFSET are obtained by inversion;

[0019] Step 4: Define relative eccentricity OFFSET RE :

[0020]

[0021] Where OD is the outer diameter of the neutron logging instrument array detector; OFFSET max is the maximum eccentric distance that the array detector of the neutron logging tool can reach under the current wellbore cal;

[0022] Step 5: Use binary search to find OFFSET RE Perform iterative inversion, the specific process is:

[0023] Step 5.1, set the number of iterations k = 1, and set the corresponding OFFSET when OFFSET = 0 RE is the relative eccentricity of the first end at the first iteration OFFSET = (cal-OD) / 2 corresponding to OFFSET RE is the relative eccentricity of the end at the first iteration Get the relative eccentricity range at the first iteration

[0024] Step 5.2: At the kth iteration, using the neutron logging instrument, we get The corresponding head end well diameter range, and The corresponding end well diameter range;

[0025] Step 5.3: At the kth iteration, extract the first end well diameter to be calculated in the first end well diameter range and extract the terminal well diameter to be calculated in the terminal well diameter range according to the fixed step, and calculate the loss function LOSS corresponding to each first end well diameter to be calculated k , and the loss function LOSS′ corresponding to each end well diameter to be calculated k ; Take all LOSS at the kth iteration k and all the LOSS′ k The minimum value in is denoted as

[0026] Step 5.4, judgment Compared with the last iteration Is the difference between equal to the preset loss function error (where k>1), or is the number of iterations k equal to the preset maximum number of iterations? If neither is satisfied, The relative eccentricity corresponding to the well diameter range is used as a relative eccentricity endpoint at the k+1th iteration. The midpoint of is taken as another relative eccentricity endpoint in the k+1th iteration, and then the relative eccentricity range in the k+1th iteration is obtained, and k=k+1 is set, and the process returns to step 5.2; otherwise, the iteration is terminated and the output is The corresponding wellbore diameter, relative eccentricity and porosity are taken as the inversion results.

[0027] Furthermore, the LOSS in step 5.3 k and LOSS′ k The loss function calculation formula is used, namely:

[0028]

[0029] Where LOSS is the loss function to be calculated; W P , W R , W c and W d All are regularization factors; is the directional derivative of formation depth; cal is the well diameter to be calculated used in the current loss function calculation; OFFSET is the instrument eccentricity corresponding to cal; Por1 and Por2 are calculated by bringing cal and OFFSET into the multivariable inversion model; is the counting ratio R obtained by inversion; N(cal,OFFSET) is the probability density function of cal and OFFSET.

[0030] Furthermore, the The Por′ obtained by inversion is calculated by bringing it into the multivariable inversion model. The calculation formula of Por′ is:

[0031]

[0032] Where ω1 and ω2 are the sensitivities of R1 and R2 to porosity, respectively. The formula is:

[0033]

[0034] Furthermore, the calculation formula of N(cal,OFFSET) is:

[0035]

[0036] In the formula, σ1 is the standard deviation of the well diameter; σ2 is and The standard deviation of; μ1 is the mean of the well diameter; μ2 is and The mean of .

[0037] Furthermore, the porosity outputted in step 5.4 is obtained according to the calculation formula of Por′ at the kth iteration.

[0038] Furthermore, the fixed step value in step 5.3 is 1 percent of the wellbore range at the first end.

[0039] Furthermore, in step 5.4, the preset value of the loss function error is 0.0001, and the preset value of the maximum number of iterations is not less than 100 times.

[0040] Furthermore, the near-source-distance detector and the far-source-distance detector are of the same size. 3 He pipe.

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

[0042] The present invention proposes a multivariable inversion method for neutron porosity measurement of buried hill reservoirs. By constructing a neutron logging instrument array detector and a multivariable inversion model, the dual uncertainty effects of well diameter and instrument eccentricity on the accuracy of measurement results are cleverly converted into a mathematical multivariate equation group solution problem, which not only simplifies the data processing flow under complex environmental conditions, but also provides a solid theoretical basis and a highly operable technical path for the simultaneous inversion of porosity and environmental parameters (well diameter, instrument eccentricity).

[0043] The present invention can effectively reduce the negative impact of the dual environmental effects caused by well diameter fluctuations and instrument eccentricity changes on logging results, significantly alleviate the complexity and difficulty of environmental correction, thereby greatly improving the accuracy and reliability of neutron porosity measurement in buried hill reservoirs. It has extremely important practical significance and application value for improving the efficiency of oil and gas exploration and development and optimizing the accuracy of reservoir evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 A schematic diagram of the structure of a neutron logging instrument array detector provided in Example 1;

[0046] Figure 2 Schematic diagram of neutron porosity measurement using a neutron logging instrument array detector in Example 1;

[0047] Figure 3 Schematic diagram of detector combination of neutron well logging instrument array detector corresponding to R1 and R2 respectively in Example 1;

[0048] Figure 4 The comparison curves of the detector combination corresponding to R1 and R2 in Example 1 with different porosities changing with relative eccentricity at a well diameter of 12.25 in.

[0049] Figure 5 The comparison curves of the detector combination corresponding to R1 and R2 in Example 1 with different porosities changing with relative eccentricity at a well diameter of 13 in.

[0050] Figure 6 This is a flow chart of the multivariate inversion method for neutron porosity measurement of buried hill reservoirs provided in Example 1. DETAILED DESCRIPTION

[0051] In order to further understand the present invention, preferred embodiments of the present invention are described below in conjunction with examples, but it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the invention.

[0052] First, the neutron porosity logging method is analyzed in detail:

[0053] Neutron porosity logging is usually performed using 241Am-Be neutron source; neutrons are emitted from the source chamber into the formation and then return to the detector. In this process, the fast neutrons emitted undergo elastic and inelastic scattering with the nuclei of the formation medium, losing energy and changing into thermal neutrons. The closer the mass of the particle hit is to the neutron, the more energy the neutron loses. Among the formation elements, hydrogen has the closest atomic mass to neutrons and is the main element that slows down neutrons in the formation. Therefore, the hydrogen content in the formation determines the spatial distribution of thermal neutrons.

[0054] Neutron diffusion equation in formation media:

[0055]

[0056] Where D t is the diffusion coefficient; Φ t , Φ e are the fluxes of thermal and fast neutrons, respectively; is the directional derivative; ∑ e and∑ t The scattering cross sections for fast neutrons and thermal neutrons respectively.

[0057] Assuming that the instrument is in an infinitely uniform formation medium, the above equation is solved to obtain the thermal neutron flux Φ at a distance r from the source: r :

[0058]

[0059] Where r is the source distance; D t , L t , L e are the thermal neutron diffusion coefficient, thermal neutron diffusion length and fast neutron deceleration length in the medium respectively; S is the source intensity. Therefore, the count values ​​on the near-source detector and the far-source detector can be expressed as:

[0060]

[0061] Since the fast neutron deceleration length in the medium is generally greater than the thermal neutron diffusion length, as long as the detector-source distance is large enough, the thermal neutron count ratio of the detector near the source and the detector far from the source can be approximately equal to the following formula:

[0062]

[0063] Φ1 and Φ2 are the thermal neutron counting rates of the near-source detector and the far-source detector respectively; r1 and r2 are the source distances of the near-source detector and the far-source detector respectively.

[0064] After fast neutrons are slowed down by hydrogen in the formation, thermal neutrons are formed. Due to the different source distances of the detectors, the number of thermal neutrons detected is also different. Therefore, the counting ratio of the two detectors can reflect the impact of fast neutrons slowed down by hydrogen in the formation. Since hydrogen in the formation exists in the form of water or other hydrocarbons in the pore fluid of the formation, the porosity content in the formation can be judged by the hydrogen content.

[0065] Neutron logging tools generally use three-axis ultrasonic sensors to measure wellbore values. Each sensor measures the propagation time it takes for a 250kHz acoustic pulse to be transmitted and received, and performs 200 measurements per second. The average of the 5-second data is then used as a real-time record of the wellbore measurement. The acoustic wave transmission time starts from the sensor, continues to the wellbore / formation interface, and then returns to the sensor. The propagation time is then multiplied by the sound velocity calculated based on the drilling fluid properties to convert to a wellbore measurement. The final wellbore measurement result is determined by the average of the three sensor measurement data. The wellbore measurement formula is shown below:

[0066]

[0067] Where cal is the wellbore measurement result, D1, D2, D3 are the wellbore data measured by three wellbore probes respectively, and OD is the outer diameter of the instrument.

[0068] In the process of processing the actual logging data, although there are measured values ​​of the wellbore diameter, the accuracy of the wellbore diameter measurement values ​​obtained by using the ultrasonic logging instrument is sometimes difficult to guarantee due to the influence of the calibration accuracy of the ultrasonic rangefinder, the density of the drilling fluid, the instrument velocity measurement and other complex downhole environments. The size of the wellbore diameter directly determines the influence of the hydrogen index of the drilling fluid outside the instrument on the neutron measurement. And when using the chart, it is necessary to know reliable wellbore parameters to obtain accurate correction results. Therefore, when the measurement accuracy of the wellbore diameter is difficult to guarantee, the accuracy of the correction chart method is low. For the drilling instrument, the neutron logging instrument is placed at the center of the wellbore to complete the measurement. Therefore, the neutron logging results will be affected by the wellbore diameter and the instrument eccentricity. When the attitude of the cable instrument changes due to environmental factors, the neutron logging results will also be affected by the wellbore diameter and the instrument eccentricity, resulting in a large measurement error of the instrument due to the change of the wellbore hydrogen index.

[0069] Based on the above, it is not difficult to find that the neutron logging results are affected by both the well diameter and the instrument eccentricity.

[0070] Example 1

[0071] Taking neutron porosity logging while drilling as an example, this embodiment proposes a multivariate inversion method for neutron porosity measurement of buried hill reservoirs. The process is as follows: Figure 6 As shown, the following steps are included:

[0072] Step 1: Construct a neutron logging instrument array detector, such as Figure 1 As shown, it includes 6 near-source detectors arranged in a semicircle at near-source distances, and 6 far-source detectors arranged in a semicircle at far-source distances, all of which are of the same size. 3 He tube, and the arrangement of the near-source distance detector and the far-source distance detector is the same and symmetrical to ensure the uniformity and symmetry of detection.

[0073] Take six near-source detectors arranged in a semicircle at near-source distance as an example. Figure 2 As shown, from left to right they are named det1, det2,,, det6. Figure 2 The cylinder clearly marks the location of the neutron source, which is located above the detector close to the source, making it easy to intuitively understand the relative position relationship between the detector and the source; although all 3 The vertical projection distance from the He tube to the neutron source remains the same, but due to their different distribution positions in the circular array, the 3 There are significant differences in the actual three-dimensional distances between the He tube and the neutron source. Specifically, det3 and det4 are closest to the source because they are located in the center of the array, while det1 and det6 are farthest from the source because they are located at the edge of the array.

[0074] Step 2: Use the neutron logging instrument array detector to measure the buried hill reservoir and calculate the count ratio R between the near-source distance detector and the far-source distance detector:

[0075]

[0076] In order to accurately analyze the formation porosity information, R is used as the initial inversion parameter; however, the porosity value directly obtained by relying solely on this ratio often needs to be further refined through the wellbore correction plate and the eccentricity correction plate to eliminate the influence of non-formation factors such as wellbore size changes and instrument eccentricity on the measurement results, thereby ensuring that the final formation porosity data is more accurate and reliable.

[0077] In the actual execution stage of logging operations, since the array detector of the neutron logging instrument is in a dynamic environment of continuous rotation, the data captured by the symmetrically configured dual detectors are highly redundant, which limits the feasibility of their direct application in independent inversion. Therefore, this embodiment proposes to perform logical combination processing on this pair of symmetrically distributed 3He tubes, specifically by accumulating the counts of the two tubes and further calculating the far source distance and the near source distance. 3 The ratio between He tube counts is introduced into the inversion process as a key input parameter to improve the accuracy and reliability of data processing and optimize the accuracy of the inversion results.

[0078] In addition, according to 3 According to the spatial layout design of the He tube and the detailed simulation analysis results, the detection response characteristics of the det3 and det4 detectors are smaller than those of the other detector groups at both ends of the array because they are located in the middle of the detector array. If only relying on det3 and det4 for independent inversion, the model may be overfitted due to insufficient data characteristics, affecting the generalization ability of the inversion results. In view of this, in order to maximize the comprehensiveness and accuracy of the instrument measurement, this embodiment strategically integrates the counting data of the det3 and det4 detectors into the inversion framework of the overall detector array. By reusing its counting information, it not only ensures the full utilization of all valid detection data, but also effectively avoids the information loss that may be caused by separate processing, thereby maintaining the stability and improvement of the overall measurement accuracy.

[0079] To realize the above optimization strategy, according to the positions of each near-source distance detector and each far-source distance detector in the neutron logging instrument array detector, as shown in Figure 3 As shown, two new detector count ratio indicators are introduced: the first count ratio R1 and the second count ratio R2:

[0080]

[0081] Where N i ,i=1,2,…,6 is the counting rate of the ith,i=1,2,…,6th detector close to the source; F i ,i=1,2,…,6 is the counting rate of the i-th far-source detector.

[0082] Step 3: Construct a multivariable inversion model:

[0083]

[0084] Wherein, Por is the porosity of the neutron logging instrument array detector under the detector combination corresponding to R; Por1 is the porosity of the neutron logging instrument array detector under the detector combination corresponding to R1; Por2 is the porosity of the neutron logging instrument array detector under the detector combination corresponding to R2; cal is the well diameter; OFFSET is the instrument eccentricity; a, b and c are all response coefficients obtained by fitting based on the calibration wells with known porosities tested by the neutron logging instrument array detector under the detector combination corresponding to R; a1, b1 and c1 are all obtained by fitting based on the calibration wells with known porosities tested by the neutron logging instrument array detector under the detector combination corresponding to R1 a2, b2 and c2 are all response coefficients obtained by fitting the calibration wells with known porosity tested by the array detector of the neutron logging instrument under the detector combination corresponding to R2; d′1′, d′1, d1, e1″, e1′ and e1 are all response coefficients obtained by Monte Carlo simulation of the curve of different porosities changing with the instrument eccentricity by the array detector of the neutron logging instrument under the detector combination corresponding to R1; d′2′, d′2, d2, e2″, e2′ and e2 are all response coefficients obtained by Monte Carlo simulation of the curve of different porosities changing with the instrument eccentricity by the array detector of the neutron logging instrument under the detector combination corresponding to R2;

[0085] In this embodiment, a=-0.0024, b=0.9859, c=51.754, a1=-0.93225, b1=-4.89199, c1=161.1223, a2=-10.83885, b2=1.4216, c2=156.35705, d′1′=9.06254, d′1=-13.56214 , d1=12.28586, e1″=-85.50835, e1′=117.07296, e1=-30.66045, d′2′=4.34412, d′2=-12.65044, d2=12.99242, e2″=-41.12805, e2′=106.56165 and e2=24.08553.

[0086] This embodiment utilizes the intrinsic differences in the response characteristics of different detectors, that is, their unique sensitivity or response mode, and introduces R1 and R2 in the multivariable inversion model, which not only enhances the stability of the inversion process, but also significantly improves the accuracy and reliability of the solution. Such a design not only ensures the comprehensive analysis of physical quantities, but also effectively avoids non-unique solutions or errors in solutions caused by insufficient data.

[0087] According to R, R1 and R2, Por, Por1, Por2, cal and OFFSET are obtained by inversion.

[0088] Step 4: Define the relative eccentricity OFFSET RE :

[0089]

[0090] In the formula, OD is the outer diameter of the detector of the neutron logging tool array; OFFSET max is the maximum eccentricity distance that the detector of the neutron logging tool array can reach under the current well diameter cal.

[0091] The relative eccentricity OFFSET RE not only simplifies the expression of the eccentricity, but also facilitates the unified comparison and analysis of the eccentricity effect under different well conditions, thus enhancing the applicability and accuracy of the forward model. Through the establishment of this model, the response behavior of the detector combination under different geological and wellbore conditions can be simulated and predicted more accurately, providing strong support for the efficient and accurate inversion of subsequent environmental parameters.

[0092] In this embodiment, the comparison curves of the detector combinations corresponding to R1 and R2 with different porosities varying with the relative eccentricity under a 12.25 in well diameter are as Figure 4 shown, and the comparison curves of the detector combinations corresponding to R1 and R2 with different porosities varying with the relative eccentricity under a 13 in well diameter are as Figure 5 shown. It can be seen that in the low porosity range, the difference in the count ratio between the detector combinations corresponding to R1 and R2 is relatively small, indicating that the influence of porosity change on the detector response is relatively limited at this time. However, as the porosity gradually increases, the response difference between the detector combinations corresponding to R1 and R2 increases significantly, reflecting the strong influence of porosity change on the detector count ratio.

[0093] This phenomenon is attributed to the difference in the distance between the detector and the radiation source, which directly leads to different radiation intensities received by the detector, and thus shows a regular count ratio relationship of R1 < R2. In addition, the increase in the well diameter further exacerbates the influence of the relative eccentricity of the tool on the count ratio, making the difference in the count ratio increase significantly, which poses higher requirements for accurate measurement.

[0094] It should be noted that for the response curves of the two groups of detectors under the same porosity condition, their trends are basically parallel. This observation deeply reveals that the two groups of detectors have similar sensitivity characteristics when responding to changes in the well diameter and eccentricity. Based on this discovery, to ensure the accuracy and reliability of the measurement data, the algorithm design needs to fully consider and accurately compensate for the intrinsic response differences between the detectors, and through a refined inversion process, achieve the accurate analysis of porosity and other geological parameters.

[0095] Step 5: Use the bisection method to perform iterative inversion on OFFSET RE The specific process is as follows:

[0096] Step 5.1, set the number of iterations k = 1, and set the corresponding OFFSET when OFFSET = 0 RE is the relative eccentricity of the first end at the first iteration OFFSET = (cal-OD) / 2 corresponding to OFFSET RE is the relative eccentricity of the end at the first iteration Get the relative eccentricity range at the first iteration

[0097] Step 5.2: At the kth iteration, using the neutron logging instrument, we get The corresponding head end well diameter range, and The corresponding end well diameter range;

[0098] Step 5.3: At the kth iteration, extract the first end well diameter to be calculated in the first end well diameter range and extract the terminal well diameter to be calculated in the terminal well diameter range according to the fixed step of 0.05in, and calculate the loss function LOSS corresponding to each first end well diameter to be calculated k , and the loss function LOSS′ corresponding to each end well diameter to be calculated k ; Take all LOSS at the kth iteration k and all the LOSS′ k The minimum value in is denoted as

[0099] Among them, LOSS k and LOSS′ k The loss function calculation formula is used, namely:

[0100]

[0101] Where LOSS is the loss function to be calculated; W P , W R , W c and W d are regularization factors, and in this embodiment, the values ​​are 3.5, 10.2, 6.8 and 0.8 respectively; is the directional derivative of formation depth; cal is the well diameter to be calculated used in the current loss function calculation; OFFSET is the instrument eccentricity corresponding to cal; Por1 and Por2 are calculated by bringing cal and OFFSET into the multivariable inversion model; is the count ratio R obtained by inversion; N(cal,OFFSET) is the probability density function of cal and OFFSET;

[0102] in, The Por′ obtained by inversion is calculated by bringing it into the multivariable inversion model. The calculation formula of Por′ is:

[0103]

[0104] Where ω1 and ω2 are the sensitivities of R1 and R2 to porosity, respectively. The formula is:

[0105]

[0106] The calculation formula of N(cal,OFFSET) is:

[0107]

[0108] In the formula, σ1 is the standard deviation of the well diameter; σ2 is and The standard deviation of; μ1 is the mean of the well diameter; μ2 is and The mean of

[0109] Step 5.4, judgment Compared with the last iteration Is the difference between equal to the preset loss function error 0.0001 (where k>1), or is the number of iterations k equal to the preset maximum number of iterations 100? If neither is satisfied, The relative eccentricity corresponding to the well diameter range is used as a relative eccentricity endpoint at the k+1th iteration. The midpoint of is taken as another relative eccentricity endpoint in the k+1th iteration, and then the relative eccentricity range in the k+1th iteration is obtained, and k=k+1 is set, and the process returns to step 5.2; otherwise, the iteration is terminated and the output is The corresponding well diameter, relative eccentricity and porosity are taken as the inversion results; among which, the output porosity is obtained according to the calculation formula of Por′ at the kth iteration.

[0110] The above embodiments are intended to provide a better understanding of the present invention, but are not limited to the optimal implementation mode and do not constitute a limitation on the content and protection scope of the present invention. Any product identical or similar to the present invention obtained by anyone under the inspiration of the present invention or by combining the present invention with the features of other prior arts shall be within the protection scope of the present invention.

Claims

1. A multivariate inversion method for neutron porosity measurement in buried hill reservoirs. It is characterized in that The following steps are involved: Step 1, constructing a neutron logging instrument array detector, including 6m near-source distance detectors arranged in a semicircle at a near-source distance, and 6m far-source distance detectors arranged in a semicircle at a far-source distance; wherein m≥1; Step 2: Use the neutron logging instrument array detector to measure the buried hill reservoir and calculate the count ratio R between the detector near the source and the detector far from the source: According to the positions of each near-source distance detector and each far-source distance detector in the neutron logging instrument array detector, a first counting ratio R is defined. 1 and the second count ratio R 2 : Where N i , i=1,2,...,6m is the count rate of the ith, i=1,2,...,6m detector close to the source; F i , i = 1, 2, ..., 6m is the count rate of the i-th far-source detector; Step 3: Construct a multivariable inversion model: Where, Por is the porosity of the neutron logging instrument array detector under the detector combination corresponding to R; Por 1 Array detector for neutron logging tools in R 1 The porosity under the corresponding detector combination; Por 2 Array detector for neutron logging tools in R 2 The porosity under the corresponding detector combination; cal is the well diameter; OFFSET is the instrument eccentricity; a, b and c are the response coefficients obtained by fitting the neutron logging instrument array detector to the calibration well with known porosity under the detector combination corresponding to R; a 1 、b 1 and c 1 All are based on the neutron logging instrument array detector in R 1 The response coefficient obtained by fitting the calibration well with known porosity under the corresponding detector combination; a 2 、b 2 and c 2 All are based on the neutron logging instrument array detector in R 2 The response coefficient obtained by fitting the calibration well with known porosity under the corresponding detector combination; d″ 1 , d′ 1 d 1 , e″ 1 , e′ 1 and e 1 Both are neutron logging instrument array detectors in R 1 The response coefficient obtained by Monte Carlo simulation of the curve of porosity changing with instrument eccentricity under the corresponding detector combination; d″ 2 , d′ 2 d 2 , e″ 2 , e′ 2 and e 2 Both are neutron logging instrument array detectors in R 2 The response coefficient obtained by Monte Carlo simulation of the curve of different porosities changing with instrument eccentricity under the corresponding detector combination; According to R, R 1 and R 2 , we can get Por and Por by inversion. 1 , Por 2 , cal and OFFSET; Step 4: Define relative eccentricity OFFSET RE : Where OD is the outer diameter of the neutron logging instrument array detector; OFFSET max is the maximum eccentric distance that the array detector of the neutron logging tool can reach under the current wellbore cal; Step 5: Use binary search to find OFFSET RE Perform iterative inversion, the specific process is: Step 5.1, set the number of iterations k = 1, and set the corresponding OFFSET when OFFSET = 0 RE is the relative eccentricity of the first end at the first iteration OFFSET = (cal-OD) / 2 corresponding to OFFSET RE is the relative eccentricity of the end at the first iteration Get the relative eccentricity range at the first iteration Step 5.2: At the kth iteration, using the neutron logging instrument, we get The corresponding head end well diameter range, and The corresponding end well diameter range; Step 5.3: At the kth iteration, extract the first end well diameter to be calculated in the first end well diameter range and extract the terminal well diameter to be calculated in the terminal well diameter range according to the fixed step, and calculate the loss function LOSS corresponding to each first end well diameter to be calculated k , and the loss function LOSS′ corresponding to each end well diameter to be calculated k ; Take all LOSS at the kth iteration k and all the LOSS′ k The minimum value in is denoted as Step 5.4, judgment Compared with the last iteration Is the difference between equal to the preset loss function error, or is the number of iterations k equal to the preset maximum number of iterations? If neither is satisfied, The relative eccentricity corresponding to the well diameter range is used as a relative eccentricity endpoint at the k+1th iteration. The midpoint of is taken as another relative eccentricity endpoint in the k+1th iteration, and then the relative eccentricity range in the k+1th iteration is obtained, and k=k+1 is set, and the process returns to step 5.2; otherwise, the iteration is terminated and the output is The corresponding wellbore diameter, relative eccentricity and porosity are taken as the inversion results.

2. The multivariate inversion method for neutron porosity measurement of buried hill reservoirs according to claim 1, It is characterized in that LOSS in step 5.3 k and LOSS′ k The loss function calculation formula is used, namely: Where LOSS is the loss function to be calculated; W P , W R , W c and W d are all regularization factors; is the directional derivative of the formation depth; cal is the well diameter to be calculated in the current loss function calculation; OFFSET is the tool eccentricity corresponding to cal; Por 1 and Por 2 Calculated by bringing cal and OFFSET into the multivariable inversion model; is the counting ratio R obtained by inversion; N(cal, OFFSET) is the probability density function of cal and OFFSET.

3. The multivariate inversion method for neutron porosity measurement of buried hill reservoirs according to claim 2, It is characterized in that Said The Por′ obtained by inversion is calculated by bringing it into the multivariable inversion model. The calculation formula of Por′ is: In the formula, ω 1 and ω 2 R 1 and R 2 Sensitivity to porosity, the formula is:

4. The multivariate inversion method for neutron porosity measurement of buried hill reservoirs according to claim 3, It is characterized in that The calculation formula of N(cal, OFFSET) is: In the formula, σ 1 is the standard deviation of the well diameter; σ 2 for and The standard deviation of 1 is the mean value of the well diameter; μ 2 for and The mean of .

5. The multivariate inversion method for neutron porosity measurement of buried hill reservoirs according to claim 4, It is characterized in that The porosity output in step 5.4 is obtained according to the calculation formula of Por′ at the kth iteration.

6. The multivariate inversion method for neutron porosity measurement of buried hill reservoirs according to claim 1, It is characterized in that The fixed step value in step 5.3 is 1 percent of the first end wellbore range.

7. The multivariate inversion method for neutron porosity measurement of buried hill reservoirs according to claim 1, It is characterized in that In step 5.4, the preset loss function error value is 0.0001, and the preset maximum number of iterations is not less than 100 times.

8. The multivariate inversion method for neutron porosity measurement of buried hill reservoirs according to claim 1, It is characterized in that The near-source distance detector and the far-source distance detector have the same size 3 He pipe.

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