Rock core homing method based on imaging logging and accurate matching of rock core phase modes

Abstract

The invention provides a rock core homing method based on accurate matching of imaging logging facies and rock core facies modes, which comprises the following steps: firstly, respectively extracting typical imaging logging lithofacies and rock core lithofacies types, and constructing an imaging logging lithofacies database and a rock core lithofacies database; constructing an imaging logging-rock core lithofacies identification mode based on bidirectional calibration according to the characteristics of the imaging logging and rock core lithofacies database; establishing a rock core lithofacies profile and an imaging logging lithofacies profile based on a bidirectionally calibrated imaging logging-rock core lithofacies identification mode; and finally, based on the imaging logging lithofacies identification precision and the coincidence rate threshold, quantitatively matching the imaging logging lithofacies profile and the rock core lithofacies profile to realize accurate homing of the rock core depth. The method has high generalization performance and practical value, and therefore a brand-new efficient solution is provided for development of rock core homing.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas exploration and development, and in particular relates to a core homing method based on imaging logging and precise matching of core phase patterns. Background Art

[0002] In the field of oil and gas exploration and development, core data is a physical sample that directly reflects the underground geological conditions. Its accuracy and reliability have a decisive impact on subsequent geological analysis, reservoir evaluation and exploration and development. However, in the process of drilling and coring, complex geological conditions, limitations of drilling equipment and technology, etc., often lead to deviations between the core samples and the actual formation depth after they are taken out. Therefore, the core retrieval technology needs to be used to return the core to its depth after it is taken out.

[0003] Traditional core retrieval technology mainly uses the correspondence between lithology and electrical properties, or logging technologies such as acoustic waves, natural gamma rays, and resistivity to determine the depth position of the core. However, in the face of complex geological conditions, the existing core retrieval technology has a relatively high error and is difficult to meet the application requirements of structural analysis of core-imaging logging.

[0004] Technical solution of prior art 1 "Ground Gamma Test System for Cores and Its Application in Core Relocation" [J]. Petroleum Instruments, 2003(02), author: Wang Yanqin, Yang Fuzhou, An Mingquan, etc. It uses the comparison between natural gamma curve and core scanning gamma curve to achieve core relocation. The core surface gamma measuring instrument is used to measure the surface of the cores arranged in sequence to generate the core surface gamma intensity (API) curve, which is then compared with the logging gamma curve to find out the similarities and differences between the trends of the two curves. By comparing the corresponding relationship between the peak value, valley value and other characteristic points, the position of the core in the formation is determined, and the core depth relocation is achieved.

[0005] Disadvantages of the prior art 1 Compared with the method of homing based on the correspondence between lithology and electrical properties, this method is less affected by human factors and improves the accuracy of core homing. The accuracy of this method is limited by the accuracy of the natural gamma logging response, and since the natural gamma core test increases the cost to a certain extent, its application scope is relatively limited.

[0006] Technical solution of prior art 2 "Spatial Relocation of Cores in the East Hole of Songke 2 Well in the Scientific Drilling Project of Songliao Basin". Geological Science and Technology Information, 201736(04), author Li Ning, Zou Changchun, Peng Cheng, etc. This article proposes a method: using the high resolution, strong continuity, intuitive and accurate characteristics of imaging logging data, the core depth relocation is achieved by comparing the core rolling image and the electrical imaging logging image characteristics. The core rolling image is formed by continuously rolling the core to obtain structural and structural characteristics such as fractures, faults, pores, etc. The electrical imaging logging image is obtained by scanning the surrounding area of ​​the wellbore with the electrical imaging logging instrument in all directions and undergoing a series of complex data processing and image generation processes. Ignoring the size difference between the wellbore diameter and the core diameter, the two images are flipped and adjusted to the same coordinate system, and then the typical geological features such as fractures, lithology mutations and bedding occurrence changes are identified on the core rolling image and the electrical imaging logging image according to the characteristics of color, texture and morphology, so as to achieve the core depth relocation.

[0007] Disadvantages of the second prior art This technology recognizes the high-resolution characteristics of electrical imaging logging images, clarifies the mirror image correspondence between them and core roll sweep images, and the possibility of matching the typical geological features of the two. However, in the technical process of the article, no specific methods and quantitative standards are proposed for implementation; the comparison of core roll sweep images and electrical imaging logging images often depends on the experience and subjective judgment of the interpreter, and different interpreters may come to different conclusions due to differences in experience, knowledge and opinions; at the same time, imaging logging images have multiple solutions, lack a set of quantitative matching models between imaging logging and core lithofacies, and have poor generalizability. Summary of the invention

[0008] The purpose of the present invention is to solve the defects of the above-mentioned prior art and provide a core homing method based on imaging logging and accurate matching of core phase patterns.

[0009] The present invention proposes a core homing method based on accurate matching of imaging logging and core phase pattern, which is a set of construction rules of imaging logging and core lithofacies characteristic pattern, establishes core and imaging logging characteristic profiles, and uses the matching rate of core characteristic profiles and imaging logging profiles to quantify the reliability of core homing, thereby achieving high-precision core homing. The present invention effectively solves the problem of accurate core homing under complex geological conditions, and provides more accurate and reliable data support for oil and gas exploration and development.

[0010] The present invention adopts the following technical solution: A core tracing method based on imaging logging and accurate matching of core phase patterns comprises the following steps: Step 1. Extract typical imaging logging lithofacies and core lithofacies types respectively, and build imaging logging lithofacies database and core lithofacies database.

[0011] (1) Construct an imaging logging lithofacies database. Based on the imaging logging images and natural gamma while drilling, the typical lithofacies of imaging logging are identified and an imaging logging lithofacies database is established, which is denoted as .set up Include elements, Middle Elements ( ≤ ≤ ) is composed of imaging logging image features and while-drilling natural gamma curve features, and is not repeated with other elements.

[0012] (2) Construct a core lithofacies database. Based on core descriptions (color, grain size, lithology, etc.), core natural gamma curves and other data, identify typical core lithofacies and establish a core lithofacies database. .set up Include elements, is the number of core lithofacies types, Middle Elements ( ≤ ≤ ) is unique and does not repeat with other elements.

[0013] Step 2. Construct an imaging logging-core lithofacies identification model based on bidirectional calibration.

[0014] Database-based and database Establish a lithofacies database based on bidirectional calibration of imaging logging-core. . It has the following characteristics:

[0015] Include elements, is the number of imaging logging-core lithofacies recognition modes based on bidirectional calibration, Middle Elements ( ≤ ≤ ) does not repeat with other elements. for arrive The mapping relationship for Any element in , There is only one element in ( ≤ ≤ ) corresponds to it; for arrive The mapping relationship for Any element in , There is only one element in ( ≤ ≤ ) corresponds to it. In the mapping relationship and Down, and All elements in are covered, and each element can only appear once and cannot be repeated.

[0016] Step 3. Based on the bidirectionally calibrated imaging logging-core lithofacies identification mode, establish the core lithofacies profile and the imaging logging lithofacies profile.

[0017] (1) Establish core lithofacies profile. Image logging-core lithofacies identification mode based on bidirectional calibration , combined with the core segmentation characteristics, the core lithofacies profile is established. The core lithofacies profile is constructed in the following way:

[0018] ① For the same core, the core logging depth is [γ 1 ,γ 2 ],in is the starting depth of core sampling, is the end depth of core sampling, and the core drilling footage is The total length of the core is , the core is broken or the top and bottom wear points are The core is divided into sections from shallow to deep based on the core crushing or top and bottom wear. Segments are recorded as , , …, .

[0019] ② Set up core Block. The core blocks are recorded from shallow to deep. , , …, .

[0020] ③Based on database Based on the core lithofacies identification standard, the core arrive The lithofacies are identified and recorded as b 1 、b 2 …bλ , where 1≤λ≤m.

[0021] ④ Based on the core crushing, top and bottom wear points and core lithofacies discontinuity points, establish the core lithofacies profile PM5.

[0022] ⑤Based on the mapping relationship in step 2 , in the core lithofacies section Based on the database Core lithofacies profile based on medium elements .

[0023] (2) Establishing the lithofacies profile of imaging logging.

[0024] ① Assume the depth of the core after homing is [ , ], , Respectively represent the actual top depth, bottom depth, and homing offset of the core in the formation , according to the homing offset The maximum possible Determine the depth range of the imaging log lithofacies section , The starting depth for collecting formation images for imaging logging. is the end depth of the imaging logging data record, where μ 1 =β 1 -v max , μ 2 =β 2 +v max , establish the imaging logging lithofacies continuous profile PW5, denoted as a 1 、a 2 , …, a ω ,in ≤ ≤ .

[0025] ②Based on the mapping relationship in step 2 , in the imaging logging lithofacies section Based on the database Imaging logging profile based on medium element .

[0026] Step 4. Quantitatively match the imaging logging lithofacies profile and the core lithofacies profile to achieve accurate core depth positioning.

[0027] After the core is returned to its original position, the threshold of the coincidence rate between the imaging logging lithofacies and the core lithofacies is ; Assume that the imaging logging image accuracy is . Set the top depth of the logging core As the starting point, is the moving step length, i is the number of moves, and the core lithofacies section Move up and down respectively When the core discontinuity point is taken as the boundary, at the depth [ , ]and[ , ], segmented matching of core lithofacies profiles and imaging logging lithofacies profile , record the maximum coincidence rate .

[0028] from Start by calculating the maximum matching rate , according to the maximum matching rate With minimum threshold The relationship between the core depth and the depth of the core is determined to determine whether the core depth is successful. The following relationship is satisfied:

[0029] (1) When hour, ≥ , the core was successfully returned to its original position, The corresponding core depth is the core retrieval depth.

[0030] (2) When and ≤ hour, ≥ , the core was successfully returned to its original position, The corresponding core depth is the core retrieval depth.

[0031] (3) When and < , then take The core depth corresponding to the maximum value is the core retrieval depth.

[0032] Beneficial effects of the present invention: 1. Parameters are easy to obtain. Various parameters required in the present invention can be directly measured by imaging logging images, core rolling sweep images and other methods, and the parameters are easy to obtain.

[0033] 2. High reliability of the homing results. Traditional core homing methods mainly use the correspondence between cores and electrical properties or logging technologies such as acoustic waves, natural gamma rays, and resistivity to achieve low accuracy of core homing results. The imaging logging and core phase pattern precise matching core homing method proposed in the present invention establishes a set of quantitative matching models between imaging logging and core lithofacies, and the reliability of core homing is high.

[0034] 3. Strong scalability. The core retrieval method proposed by the present invention has a clear principle, is easy to promote, and has strong scalability and practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is an imaging logging-core lithofacies identification mode based on bidirectional calibration; Figure 2 Based on Core lithofacies profile; Figure 3 Based on Imaging logging profile; Figure 4 It is an imaging logging-core lithofacies identification mode based on bidirectional calibration; Figure 5 Based on Core lithofacies section; Figure 6 Based on Imaging logging lithofacies profile; Figure 7 is the number of moves i and the matching rate Relationship scatter plot; Figure 8 This is the result of core retrieval. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention is described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] The present invention proposes to first extract typical imaging logging lithofacies and core lithofacies types respectively, and construct an imaging logging lithofacies database and a core lithofacies database; then, according to the characteristics of the imaging logging and core lithofacies databases, construct an imaging logging and core lithofacies identification mode based on bidirectional calibration, and then establish a core lithofacies profile and an imaging logging lithofacies profile based on the bidirectional calibration imaging logging-core lithofacies identification mode, and finally, based on the imaging logging lithofacies identification accuracy and the coincidence rate threshold, quantitatively match the imaging logging lithofacies profile and the core lithofacies profile to achieve accurate core depth homing. The present invention constructs a set of quantitative matching models between imaging logging and core lithofacies, which can obtain better core homing results.

[0038] like Figure 1 As shown, a core tracing method based on imaging logging and accurate matching of core phase patterns of the present invention comprises the following steps: Step 1. Extract typical imaging logging lithofacies and core lithofacies types respectively, and build imaging logging lithofacies database and core lithofacies database.

[0039] (1) Construct an imaging logging lithofacies database. Based on the imaging logging images and natural gamma while drilling, the typical lithofacies of imaging logging are identified and an imaging logging lithofacies database is established, which is denoted as .set up Include elements, The i-th element in ( ≤ ≤ ) is composed of imaging logging image features and while-drilling natural gamma curve features, and is not repeated with other elements.

[0040] (2) Construct a core lithofacies database. Based on core descriptions (color, grain size, lithology, etc.), core natural gamma curves and other data, identify typical core lithofacies and establish a core lithofacies database. .set up Include elements, is the number of core lithofacies types, Middle Elements ( ≤ ≤ ) is unique and does not repeat with other elements.

[0041] Step 2. Construct an imaging logging-core lithofacies identification model based on bidirectional calibration Database-based and database Establish a lithofacies database based on bidirectional calibration of imaging logging-core. . It has the following characteristics:

[0042] Include elements, is the number of imaging logging-core lithofacies recognition modes based on bidirectional calibration, Middle Elements Do not repeat with other elements. for arrive The mapping relationship for Any element in , There is only one element in Corresponding to this; for arrive The mapping relationship for Any element in , There is only one element in Correspondingly, in the mapping relationship and Down, and All elements in are covered, and each element can only appear once and cannot be repeated, such as Figure 1 shown.

[0043] Step 3. Establish core lithofacies profile and imaging logging lithofacies profile based on bidirectional calibration imaging logging-core lithofacies identification mode (1) Establish core lithofacies profile. Image logging-core lithofacies identification mode based on bidirectional calibration , combined with the core segmentation characteristics, the core lithofacies profile is established. The core lithofacies profile is constructed in the following way (such as Figure 2 as shown).

[0044] ① For the same core, the core logging depth is ,in is the starting depth of core sampling, is the end depth of core sampling, and the core drilling footage is The total length of the core is , the core is broken or the top and bottom wear points are The core is divided into sections from shallow to deep, with the core broken or the top and bottom worn as the segmentation boundaries. Segments are recorded as , , …, ,like Figure 2 As shown in (b).

[0045] ② Set up core Block. The core blocks are recorded from shallow to deep. , , …, ,like Figure 2 As shown in (c).

[0046] ③Based on database Based on the core lithofacies identification standard, the core arrive The lithofacies are identified and recorded as b 1 、b 2 …b λ , is a constant, the recognition result is Figure 2As shown in (d), ≤ ≤ .

[0047] ④ Based on the core crushing, top and bottom wear points and core lithofacies discontinuity points, establish the core lithofacies profile PM5, such as Figure 2 As shown in (e).

[0048] ⑤Based on the mapping relationship in step 2 , in the core lithofacies section Based on the database Core lithofacies profile based on medium elements ,like Figure 2 As shown in (f).

[0049] (2) Establishing the lithofacies profile of imaging logging, such as Figure 3 shown.

[0050] ① Assume that the depth of the core after homing is , , Respectively represent the actual top depth, bottom depth, and homing offset of the core in the formation , according to the homing offset The maximum possible Determine the depth range of the imaging log lithofacies section , The starting depth for collecting formation images for imaging logging. is the end depth of the imaging logging data record, where μ 1 =β 1 -v max , μ 2 =β 2 +v max , establish the imaging logging lithofacies continuous profile PW5, denoted as a 1 、a 2 , …, a ω , where 1≤ ≤ ,like Figure 3 As shown in (d).

[0051] ②Based on the mapping relationship in step 2 , in the imaging logging lithofacies section Based on the database Imaging logging profile based on medium element ,like Figure 3 As shown in (e).

[0052] Step 4. Quantitatively match the imaging logging lithofacies profile and the core lithofacies profile to achieve accurate core depth positioning.

[0053] After the core is returned to its original position, the threshold of the coincidence rate between the imaging logging lithofacies and the core lithofacies is ; Assume that the imaging logging image accuracy is . Set the top depth of the logging core As the starting point, is the moving step length, i is the number of moves, and the core lithofacies section Move up and down respectively When the core discontinuity point is taken as the boundary, at the depth and Internal, segmented matching of core lithofacies profiles and imaging logging lithofacies profile , record the maximum coincidence rate .

[0054] from Start by calculating the maximum matching rate , according to the maximum matching rate With minimum threshold The relationship between the core depth and the depth of the core is determined to determine whether the core depth is successful. The following relationship is satisfied:

[0055] (1) When hour, , the core was successfully returned to its original position, The corresponding core depth is the core retrieval depth.

[0056] (2) When and hour, , the core was successfully returned to its original position, The corresponding core depth is the core retrieval depth.

[0057] (3) When and , then take The core depth corresponding to the maximum value is the core retrieval depth.

[0058] Example The sample area analyzed in this embodiment is a tight sandstone oil and gas reservoir block in the Bozi area of ​​the Kuche Depression in the Tarim Basin. The core homing method based on the precise matching of imaging logging and core phase pattern is used to achieve precise core homing, including the following steps: Step 1. Extract typical imaging logging lithofacies and core lithofacies types respectively, and build imaging logging lithofacies database and core lithofacies database.

[0059] Based on imaging logging images and natural gamma while drilling, typical lithofacies of imaging logging were identified, and an imaging logging lithofacies database was established. Based on the core description (color, grain size, lithology, etc.), core natural gamma curve and other data, typical core lithofacies were identified and a core lithofacies database was established .database and Features are as follows:

[0060] (1) Database Include Elements, by It is a high gamma-ray bright blocky rock phase. It is a medium gamma massive bright-dark lithofacies. and It is a low-gamma dark massive rock phase. It is a high-low variation gamma-ray band lithofacies. and It is a high-low gamma porphyritic lithofacies. Each element is composed of imaging logging image characteristics and natural gamma curve characteristics while drilling, and does not repeat with other elements.

[0061] (2) Database Contains 11 elements, It is muddy sandstone. It is muddy fine sandstone. It's coarse sandstone. It is muddy sandstone. It's mudstone. It is sandy mudstone. It is sandy mudstone. It is sandstone intercalated with mudstone. It is a mud-gravel sandstone. It is fine sandstone, It is a medium conglomerate. Each element is unique and does not repeat with other elements.

[0062] Step 2. Construct an imaging logging-core lithofacies identification model based on bidirectional calibration Database-based and Based on the lithofacies characteristics of the well, a database of imaging logging-core lithofacies recognition patterns was constructed based on bidirectional calibration. , It has the following characteristics: Contains 5 elements, namely , , …, , and any element is unique. , , …, for arrive The mapping relationship for Any element of There is a unique element corresponding to it; , , …, for arrive The mapping relationship for Any element in There is a unique element corresponding to it. and All elements in are covered, and each element appears only once, such as Figure 4 shown.

[0063] The element characteristics are as follows: ①Element : High-density formations with high resistivity such as tight sandstone; ②Element : The color pattern of the image changes evenly, which represents the change of the combination characteristics of the grain sequence of a single well; ③Element : Lower resistivity and low density formations such as mudstone; ④Element : interbedded sandstone and mudstone; ⑤Element : High-resistance calcium and gravel appear in relatively dark images, or low-resistance gravel and nodules appear in relatively bright images; Step 3. Based on the bidirectionally calibrated imaging logging-core lithofacies identification mode, the core lithofacies profile and the imaging logging lithofacies profile were established.

[0064] (1) Establish core lithofacies profile.

[0065] Imaging logging-core lithofacies identification mode based on bidirectional calibration , combined with the core segmentation characteristics, the core lithofacies profile is established. The core lithofacies profile is constructed in the following way (such as Figure 5 shown):

[0066] ①. Known core logging depth is [ ], coring footage The total length of the core is , the core is broken or the top and bottom wear points are The core is divided into sections from shallow to deep, with the core broken or the top and bottom worn as the segmentation boundaries. Segments are recorded as , , …, ,like Figure 5 middle and shown.

[0067] ②Core total Blocks, from shallow to deep, are recorded as , , …, ,like Figure 5 middle shown.

[0068] ③Based on database Based on the core lithofacies identification standard, the core arrive The lithofacies are identified, and the identification results are as follows Figure 5 middle shown.

[0069] ④ Based on the core crushing and top and bottom wear points, establish the core lithofacies profile, such as Figure 5 middle shown.

[0070] ⑤ In the core lithofacies section Based on the database The core lithofacies section based on the medium element, such as Figure 5 middle shown.

[0071] (2) Establishing the lithofacies profile of imaging logging, such as Figure 6 shown.

[0072] ①Homing offset , determine the range of the imaging logging lithofacies section based on the return offset [ ], establish the continuous lithofacies profile of imaging logging, such as Figure 6 middle shown.

[0073] ②Based on The mapping relationship in the step , in the imaging logging lithofacies section Based on the database Imaging logging profile based on medium element ,like Figure 6 middle shown.

[0074] Step 4. Quantitatively match the imaging logging lithofacies profile and the core lithofacies profile to achieve accurate core depth positioning.

[0075] The threshold value of the coincidence rate between the imaging logging lithofacies and the core lithofacies in the study area is 95%. The top depth of the logging core is 6795.2m as the starting point, 0.05m as the moving step, i as the number of moves, at the depth Internal, core lithofacies section Move upward and downward by 0.05 im respectively, and use the continuous points of the core as the boundary to match the core lithofacies profile in sections. and imaging logging lithofacies profile .

[0076] When the number of moves i=40, the logging core depth shifts downward by 1m, the coincidence rate reaches the threshold of 95%, and the core is successfully returned to the original position. Figure 7 The core return results are shown in Figure 8 shown.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A core tracing method based on imaging logging and accurate matching of core phase patterns, characterized in that: The following steps are involved: Step 1. Extract typical imaging logging lithofacies and core lithofacies types respectively, and build imaging logging lithofacies database and core lithofacies database (1) Construction of imaging logging lithofacies database: Based on the imaging logging images and natural gamma while drilling, the typical lithofacies of imaging logging are identified, and the imaging logging lithofacies database is established, which is recorded as ,set up Include elements, Middle Elements , ≤ ≤ , which is composed of imaging logging image features and natural gamma curve features while drilling, and does not repeat with other elements; (2) Construction of core lithofacies database: Based on the core description and core natural gamma curve data, typical core lithofacies are identified and a core lithofacies database is established. ,set up Include elements, is the number of core lithofacies types, Middle Elements , ≤ ≤ , is unique and does not repeat with other elements; Step 2. Construct an imaging logging-core lithofacies identification model based on bidirectional calibration Based on imaging logging lithofacies database Core Facies Database The lithofacies characteristics of the imaging logging-core lithofacies recognition model are constructed, and the imaging logging-core lithofacies database based on bidirectional calibration is established. , It has the following characteristics: Include elements, is the number of imaging logging-core lithofacies recognition modes based on bidirectional calibration, Middle Elements , ≤ ≤ , does not repeat with other elements; for arrive The mapping relationship for Any element in , There is only one element in , ≤ ≤ , corresponding to it; for arrive The mapping relationship for Any element in , There is only one element in , ≤ ≤ , correspondingly, in the mapping relationship and Down, and All elements in are covered, and each element can only appear once and cannot be repeated; Step 3. Establish core lithofacies profile and imaging logging lithofacies profile based on bidirectional calibration imaging logging-core lithofacies identification mode (1) Establishing core lithofacies profile: imaging logging-core lithofacies identification mode based on bidirectional calibration , combined with the core segmentation characteristics, the core lithofacies profile is established. The core lithofacies profile is constructed in the following way: ① For the same core, the core logging depth is set to [γ1,γ2], where is the starting depth of core sampling, is the end depth of core sampling, and the core drilling footage is The total length of the core is , the core is broken or the top and bottom wear points are The core is divided into sections from shallow to deep, with the core broken or the top and bottom worn as the segmentation boundaries. Segments are recorded as , , …, ; ② Set up core Block, for The core blocks are recorded from shallow to deep. , , …, ; ③ Core lithofacies database Based on the core lithofacies identification standard, the core arrive The lithofacies are identified and recorded as b1, b2…b λ , where 1≤λ≤m; ④ Based on the core crushing, top and bottom wear points and core lithofacies discontinuity points, establish the core lithofacies profile PM5; ⑤Based on the mapping relationship in step 2 , in the core lithofacies section Based on the bidirectional calibration of imaging logging-core lithofacies database, Core lithofacies profile based on medium elements ; (2) Establishing the lithofacies profile of imaging logging: ① Assume that the depth of the core after homing is , , Respectively represent the actual top depth, bottom depth, and homing offset of the core in the formation , according to the homing offset Get the maximum value , determine the depth range of the imaging logging lithofacies profile , The starting depth for collecting formation images for imaging logging. is the end depth of the imaging logging data record, where , , establish the imaging logging lithofacies continuous profile PW5, denoted as a1, a2…a ω ,in ≤ ≤ ; ②Based on the mapping relationship in step 2 , in the imaging logging lithofacies section Based on the database Imaging logging profile based on medium element ; Step 4. Quantitatively match the imaging logging lithofacies profile and the core lithofacies profile to achieve accurate core depth homing After the core is returned to its original position, the threshold of the coincidence rate between the imaging logging lithofacies and the core lithofacies is ; Assume that the imaging logging image accuracy is , set the top depth of the logging core As the starting point, is the moving step length, i is the number of moves, and the core lithofacies section Move up and down respectively When the core discontinuity point is taken as the boundary, at the depth [ , ]and[ , ], segmented matching of core lithofacies profiles and imaging logging lithofacies profile , record the maximum matching rate ; from Start by calculating the maximum matching rate , according to the maximum matching rate With minimum threshold To determine whether the core depth return is successful, the following relationship is satisfied: (1) When hour, ≥ , the core was successfully returned to its original position, The corresponding core depth is the core homing depth; (2) When and ≤ hour, ≥ , the core was successfully returned to its original position, The corresponding core depth is the core homing depth; (3) When and < , then take The core depth corresponding to the maximum value is the core retrieval depth.

2. The method according to claim 1, characterized in that The core description in step 1 (2) includes: color, grain size, and lithology category.

Images