A high-quality hydrocarbon source rock comprehensive prediction method based on automatic layering

Abstract

A high-quality hydrocarbon source rock comprehensive prediction method based on automatic layering relates to the technical field of oil and gas exploration, and solves the problem that the existing method is difficult to quickly and accurately predict the development area of high-quality hydrocarbon source rock in the study area. The method comprises the following steps: S1, using geochemical data, obtaining single well geology and geochemistry column, and performing single well geochemical evaluation; S2, calculating the TOC value of the single well by using the logging curve to obtain the continuous distribution TOC curve; S3, automatically layering the single well TOC to obtain the TOC hierarchical layering channel; S4, based on the obtained TOC hierarchical layering channel, drawing the TOC well-to-well profile map; S5, based on the obtained TOC well-to-well profile map, drawing the hydrocarbon source rock TOC plane map; S6, based on the obtained hydrocarbon source rock TOC plane map, delineating the development area of high-quality hydrocarbon source rock. The method can quickly and accurately predict the development area of high-quality hydrocarbon source rock by fully utilizing the drilling, logging, logging, seismic, geological data of the study area.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration technology, and in particular to a comprehensive prediction method for high-quality source rocks based on automatic stratification. Background Technology

[0002] Effective source rocks are a prerequisite for the formation of oil and gas reservoirs, and the development of high-quality source rocks directly controls whether large oil and gas fields can be formed. Evaluating, identifying, and tracking high-quality source rocks in the study area can clarify oil and gas generation conditions, assess resource potential, and quickly pinpoint favorable zones, contributing to new discoveries in oil and gas exploration in emerging fields. Traditional prediction of high-quality source rocks is mainly based on single-well geochemical evaluation. First, analytical and laboratory data are used to evaluate the source rocks in terms of organic matter abundance, type, and maturity. Then, inter-well interpolation is used to draw TOC contour maps of the source rocks. Due to the diverse sources and rapid facies changes in continental lacustrine basins, source rocks exhibit strong spatial heterogeneity, making it difficult to accurately characterize high-quality source rocks using only limited core analysis data. How to fully utilize drilling, logging, well logging, seismic, and geological data in the study area to quickly and accurately predict the development areas of high-quality source rocks is a pressing problem that exploration geological research needs to overcome. Summary of the Invention

[0003] This invention addresses the problem in the prior art where limited analytical and laboratory data and insufficient inter-well interpolation geological data make it difficult to quickly and accurately predict high-quality source rock development zones in a study area. Instead, it provides a comprehensive prediction method for high-quality source rocks based on automatic stratification. This method, by fully utilizing drilling, logging, well logging, seismic, and geological data from the study area, can quickly and accurately predict high-quality source rock development zones.

[0004] The present invention solves its problems through the following technical solution: This comprehensive prediction method for high-quality source rocks based on automatic stratification includes the following steps:

[0005] S1. Utilize geochemical data to obtain single-well geological and geochemical columns and conduct single-well geochemical evaluation;

[0006] S2. Based on the obtained single-well geological and geochemical columns, the TOC value of the single well is calculated using well logging curves to obtain continuously distributed TOC curves;

[0007] S3. Based on the obtained continuously distributed TOC curves, the TOC of a single well is automatically stratified to obtain the TOC stratification channels;

[0008] S4. Based on the obtained TOC classification and layering, draw the TOC well-connection profile.

[0009] S5. Based on the obtained TOC well profile, draw the source rock TOC plan view;

[0010] S6. Based on the obtained TOC plan of the source rock, delineate the development zone of high-quality source rock.

[0011] Furthermore, step S1 utilizes geochemical data to obtain single-well geological and geochemical columns for single-well geochemical evaluation; specific methods include:

[0012] Organic geochemical experiments were conducted using core sampling, wellbore coring, cuttings logging, and outcrop samples. The resulting geochemical data were added to the single-well comprehensive columnar section according to the corresponding depth of the samples, thus obtaining the single-well geological and geochemical column. The single-well geochemical evaluation was then carried out based on the obtained single-well geological and geochemical column.

[0013] Furthermore, the geochemical data includes: total organic carbon (TOC), hydrocarbon generation potential (S1+S2), hydrogen index (HI), oxygen index (OI), pyrolysis type index (S2 / S3), total hydrocarbon content (HC), chloroform bitumen (A'), type index (TI), hydrogen-to-carbon ratio (H / C), oxygen-to-carbon ratio (O / C), vitrinite reflectance (Ro), and pyrolysis peak temperature (Tmax).

[0014] The single-well geochemical evaluation specifically includes the following three aspects:

[0015] Regarding organic matter abundance: source rocks are classified into four levels based on TOC, S1+S2, chloroform bitumen A', and HC: non-source rocks, general source rocks, good source rocks, and high-quality source rocks.

[0016] Regarding organic matter type: source rocks are classified into four types using type indices (TI), H / C, O / C, HI, OI, and S2 / S3: Type I, Type II1, Type II2, and Type III;

[0017] Regarding the maturity of organic matter: the source rocks are divided into five evolutionary stages based on Ro and Tmax: immature stage, low maturity stage, mature stage, high maturity stage and over-mature stage.

[0018] Furthermore, step S2, based on the obtained single-well geological and geochemical column, calculates the single-well TOC value using well logging curves to obtain a continuously distributed TOC curve; the specific method is as follows:

[0019] Based on the identification of lithological profiles such as sandstone and mudstone, the single-well geological and geochemical column obtained in step S1 is used to calculate the organic matter abundance (TOC) using sonic transit time and resistivity curves, resulting in a continuously distributed TOC curve.

[0020] Furthermore, the method for calculating the total organic matter abundance (TOC) is as follows:

[0021] The TOC is calculated using the ΔlgR technique, and the formula is as follows:

[0022] TOC = a × △logR + b

[0023] △logR=log(R / Rbase)+K×(△T-△Tbase)

[0024] In the formula:

[0025] a: Coefficient, which can be adjusted based on the calculation results;

[0026] b: A constant representing the background value of TOC (Total Organic Carbon), typically 0.2-0.4;

[0027] △logR: The measured curve spacing on a logarithmic coordinate system;

[0028] R: Deep resistivity logging value (unit: Ω·m);

[0029] Rbase: The baseline value of the RT logging curve;

[0030] K: constant, default value 0.02;

[0031] △T: Sound wave propagation time (unit: μs / ft or μs / m);

[0032] △Tbase: Baseline value of the AC logging curve;

[0033] When performing TOC calculations, the coefficients a and b in the calculation formula are adjusted to ensure that the calculated TOC value matches the measured TOC value.

[0034] Furthermore, for the entire well section, methods to better match the calculated TOC value with the measured TOC value include:

[0035] ① For thin interbedded sections of source rocks, a segmented processing technique is used to improve the correlation between calculated and measured values;

[0036] ② For source rock sections with low total organic carbon abundance, the method of adjusting the baseline value is adopted to make the vertical profile characteristics more obvious and reduce the error;

[0037] ③ For the low-sonic section of the logging curve, the baseline should be lowered to avoid negative values ​​or inconsistencies in lithology and electrical properties.

[0038] ④ For well sections with strong heterogeneity, ensure that the calculated average TOC value and the measured average TOC value match for the entire well section.

[0039] Furthermore, step S3, based on the obtained continuously distributed TOC curves, automatically stratifies the TOC of a single well to obtain TOC graded stratification channels; the specific method is as follows:

[0040] Using the Resform geological research software platform, a TOC grading and layering channel is added to the single-well columnar chart of the continuously distributed TOC curve obtained in step 2), which is the single-well TOC grading and layering channel.

[0041] Furthermore, the method for adding a TOC (Total Occupation Code) grading and stratification channel to a single-well column chart using the Resform geological research software platform is as follows:

[0042] Based on the continuously distributed TOC curves, and relying on the Resform geological software platform, a script program (macro) suitable for the study area was written. At the same time, the classification symbols were configured. After running the macro, a TOC classification layer channel will be automatically added to the single-well column chart, which is the single-well TOC classification layer channel.

[0043] The process of writing a script suitable for the research area can be divided into the following 5 steps:

[0044] Create a layered channel and set its name;

[0045] Set the top and bottom depths for each layer of the TOC (Transmission of Cost) level;

[0046] Set up 3 TOC levels and determine the boundary values ​​for each level;

[0047] Set the colors for each TOC level;

[0048] Continue calculating until the bottom depth is reached, then terminate the operation.

[0049] The source code for the script program suitable for the research area is as follows:

[0050]

[0051] Furthermore, step S4 involves drawing a TOC well-connection profile based on the obtained TOC graded and layered channels; the specific method is as follows:

[0052] Based on the obtained TOC classification and layered channels, a framework of source rock TOC well-connected profiles is constructed according to the structural strike and dip of the study area. Within the framework, the connectivity and pinch-out locations of different sub-layers of source rocks are determined based on the mudstone thickness and TOC classification results, thus obtaining the TOC well-connected profile.

[0053] Furthermore, the method for drawing the TOC plan of the source rock in step S5 includes the following steps:

[0054] Based on the obtained TOC well profile, and using all exploration well, logging, and lithological data, and referring to the formation thickness map, a thickness map of the source rocks in the study area was drawn.

[0055] The TOC results are calculated based on the well logging curves. The oil-based mud contamination section is removed from the calculated TOC results. The TOC planar map of the source rocks in the study area is drawn with reference to the sedimentary facies diagram trend and the thickness map of the source rocks in the study area.

[0056] Furthermore, the method for delineating the high-quality source rock development area in step S6 is as follows:

[0057] Based on the obtained TOC plan of the source rocks, the TOC boundaries of high-quality source rocks are determined according to the correlation between TOC and S1 / TOC and TOC and S2 in the study area, thereby delineating the development area of ​​high-quality source rocks.

[0058] Compared with the above-mentioned background technology, the present invention has the following beneficial effects:

[0059] This invention presents a comprehensive prediction method for high-quality source rocks based on automatic stratification. Compared with existing technologies, this innovative achievement offers a complete, advanced, and efficient technical solution.

[0060] Existing technologies only classify high-quality source rocks based on a few TOC measured data. The industry generally believes that high-quality source rocks have a TOC ≥ 2%. This method is limited to the field of petroleum geochemistry. This innovative achievement, based on the existing understanding in the industry, uses a comprehensive approach combining geology, seismology, well logging and other disciplines to predict high-quality source rocks in the study area.

[0061] Existing technologies only classify high-quality source rocks based on experimental analysis data. In exploration practice, there is very little core data and limited actual TOC measurement data. This innovative achievement uses logging curves to calculate TOC values. Logging data such as sonic resistivity are distributed throughout the entire well section, greatly expanding the spatial distribution of TOC evaluation data.

[0062] Existing technologies for vertically dividing high-quality source rocks in a single well typically involve manually adding small layers. For exploration wells with mudstone thicknesses of hundreds or even thousands of meters, hundreds of high-quality source rock layers may be developed. This method is inefficient, with a work cycle of one week or even more than one month. This innovative achievement utilizes programming scripts to automatically divide the formation, and the addition of all high-quality source rock layers can be completed within one second for formations of several thousand meters.

[0063] In terms of expected results, existing technologies are limited to vertically dividing high-quality source rocks into locally developed small layers in a single well. This innovative achievement can accurately identify and predict the spatial distribution of high-quality source rocks in any study area (single well, interconnected wells, planar, multi-layer).

[0064] By utilizing wells XS1 and DS17 in the deep Xujiaweizi fault depression, YS5, SX67, and SS2 in the Yingshan-Shuangcheng fault depression, GS1 and LS4 in the Gulong-Lindian fault depression, and BC1 in the Beian fault depression in the Daqing exploration area, the rapid identification and prediction of high-quality source rocks were completed. This invention effectively guided the exploration deployment in the Daqing exploration area and provided technical support for the discovery of the Shuangcheng oilfield and the submission of tight gas reserves in the Shahezi Formation. The research process and methods can be extended to other emerging fields, reducing exploration investment risks. Attached Figure Description

[0065] Figure 1 This is a geochemical composite columnar section based on well XS1 as an example in an embodiment of the present invention;

[0066] Figure 2 This is an embodiment of the invention using well SX67 as an example to calculate the TOC value from the logging curve, and then comparing it with the measured TOC value on the geochemical columnar section.

[0067] Figure 3 In this embodiment of the invention, the TOC automatic grading script program and running interface in the Resform software are automatically grading the XS1 well. After running the macro plugin, a new grading channel is added to the rightmost side of the single well column.

[0068] Figure 4 This is a comparison diagram of the TOC well profiles of wells DS3-SS6 in an embodiment of the present invention;

[0069] Figure 5 This is a TOC plan view drawn using the deep Shahezi Formation source rocks in Songbei as an example in an embodiment of the present invention;

[0070] Figure 6 This is a map showing the development area of ​​high-quality source rocks in the deep Shahezi Formation of Songbei, delineated by the method of this invention.

[0071] Figure 7 This is a flowchart of the comprehensive prediction method for high-quality source rocks based on automatic stratification, as presented in this invention. Detailed Implementation

[0072] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0073] Figure 7 This is a flowchart of a comprehensive prediction method for high-quality source rocks based on automatic stratification; for example... Figure 7 As shown, a comprehensive prediction method for high-quality hydrocarbon source rocks based on automatic stratification is presented. The specific method includes the following steps:

[0074] Step S1: Using geochemical data, obtain single-well geological and geochemical columns and conduct single-well geochemical evaluation;

[0075] The geochemical data include: total organic carbon (TOC), hydrocarbon generation potential (S1+S2), hydrogen index (HI), oxygen index (OI), pyrolysis type index (S2 / S3), total hydrocarbon content (HC), chloroform bitumen (A'), type index (TI), hydrogen-to-carbon ratio (H / C), oxygen-to-carbon ratio (O / C), vitrinite reflectance (Ro), and pyrolysis peak temperature (Tmax).

[0076] Organic geochemical experiments were conducted using core samples from drilling, wellbore, cuttings logging, and outcrop samples. The obtained geochemical data for TOC, S1+S2, HI, OI, S2 / S3, HC, chloroform bitumen A', type index (TI), H / C, O / C, Ro, and Tmax were added to the single-well comprehensive column chart according to the corresponding depth of the samples, thus obtaining the single-well geological and geochemical column. Based on the obtained single-well geological and geochemical column, single-well geochemical evaluation was performed according to the oil and gas industry standard "Methods for Geochemical Evaluation of Source Rocks".

[0077] In terms of organic matter abundance, source rocks are classified into four levels based on TOC, S1+S2, chloroform bitumen A', and HC: non-source rocks, general source rocks, good source rocks, and high-quality source rocks.

[0078] In terms of organic matter type, source rocks are classified into four types: Type I, Type II1, Type II2, and Type III using type indices (TI), H / C, O / C, HI, OI, and S2 / S3.

[0079] Regarding the maturity of organic matter, source rocks are divided into five evolutionary stages based on Ro and Tmax: immature stage, low maturity stage, mature stage, high maturity stage, and over-mature stage.

[0080] Step S2: Based on the obtained single-well geological and geochemical column, calculate the single-well TOC value using well logging curves to obtain a continuously distributed TOC curve; the specific method is as follows:

[0081] Based on the identification of lithological profiles such as sandstone and mudstone, the single-well geological and geochemical column obtained in step 1) is used to calculate the organic matter abundance (TOC) using sonic transit time and resistivity curves, resulting in a continuously distributed TOC curve.

[0082] This study uses the ΔlogR technique to calculate TOC, and the calculation formula is as follows:

[0083] TOC = a × △logR + b

[0084] △logR=log(R / Rbase)+K×(△T-△Tbase)

[0085] In the formula:

[0086] a: Coefficient, which can be adjusted based on the calculation results;

[0087] b: A constant representing the background value of TOC (Total Organic Carbon), typically 0.2-0.4;

[0088] △logR: The measured curve spacing on a logarithmic coordinate system;

[0089] R: Deep resistivity logging value (unit: Ω·m);

[0090] Rbase: The baseline value of the RT logging curve;

[0091] K: constant, default value 0.02;

[0092] △T: Sound wave propagation time (unit: μs / ft or μs / m);

[0093] △Tbase: Baseline value of the AC logging curve;

[0094] When performing specific TOC calculations, the values ​​of coefficients such as a and b are repeatedly adjusted in the calculation formula to ensure that the calculated TOC value matches the measured TOC value.

[0095] When establishing a well logging model for the electrical characteristics of source rocks, methods to make the calculated TOC value and the measured TOC value more consistent across the entire well section include:

[0096] S21. For thin interbedded sections of source rocks, a segmented processing technique is adopted to improve the correlation between calculated and measured values;

[0097] S22. For source rock sections with low total organic carbon abundance, the method of adjusting the baseline value is used to make the vertical profile characteristics more obvious and reduce the error.

[0098] S23. For the low-sonic section of the logging curve, the baseline should be lowered to avoid negative values ​​or inconsistencies in lithology and electrical properties.

[0099] S24. For well sections with strong heterogeneity, ensure that the calculated average TOC value and the measured average TOC value match for the entire well section.

[0100] Step S3: Based on the obtained continuously distributed TOC curves, automatically stratify the TOC of a single well to obtain TOC stratification channels; the specific method is as follows:

[0101] Using the continuously distributed TOC curves obtained in step 2), a script program (macro) suitable for the study area was written based on the Resform geological software platform. At the same time, the classification symbols were configured. After running the macro, a column of TOC classification and stratification channels will be automatically added to the single-well column chart.

[0102] Script writing can be divided into 5 processes:

[0103] Create a layered channel and set its name;

[0104] Set the top and bottom depths for the TOC (Transmission of Cost) level of the tiered road system;

[0105] Set up 3 TOC levels and determine the boundary values ​​for each level;

[0106] Set the colors for each TOC level;

[0107] Continue calculating until the bottom depth is reached, then end the operation.

[0108] The source code for the script program suitable for the research area is as follows:

[0109]

[0110] The method calculates TOC with an error of less than 10% compared to the measured TOC; TOC stratification is fast, completed within 1 second for a single well; a geochemical parameter planar map of source rocks is drawn using relevant gridding technology, and the trend is more consistent with the actual geology; the time to complete the TOC classification evaluation of source rocks in a region is within one week. The working efficiency data of the automatic TOC stratification technology are shown in Table 1.

[0111] Table 1. Efficiency Data of TOC Automatic Layering Technology

[0112] project TOC calculation error TOC layering speed Reliability of data extrapolation Completion Time parameter ≤10％ ﹤1s high ≤7 days

[0113] Step S4: Based on the obtained TOC classification and layering, draw the TOC well-connection profile; the specific method is as follows:

[0114] The TOC classification and layered channels obtained in step 3) are used to construct a large-scale framework for the source rock TOC well-connected profile according to the structural strike and dip of the study area. Within this framework, the connectivity and pinch-out locations of different sub-layers of source rocks are determined based on the mudstone thickness and the TOC classification results, thus obtaining the TOC well-connected profile.

[0115] Step S5: Based on the obtained TOC well profile, draw the source rock TOC plan view;

[0116] The method for drawing a TOC plan view of source rocks includes the following steps:

[0117] Using the TOC well profile obtained in step 4), and based on the logging lithology data of all exploration wells, and referring to the formation thickness map, draw the thickness map of the source rocks in the study area.

[0118] Based on the TOC results calculated from the well logging curves (excluding oil-based mud contamination data), and referring to the sedimentary facies diagram trend and the thickness map of the source rocks in the study area, a TOC planar map of the source rocks in the study area was drawn.

[0119] Step S6: Based on the obtained source rock TOC plan, delineate the high-quality source rock development area;

[0120] The method for delineating the high-quality source rock development zone is as follows:

[0121] Based on the TOC planar map of the source rocks obtained in step 5), and the correlation between TOC and S1 / TOC, and TOC and S2 of the analysis and testing data of the study area, the TOC boundary of high-quality source rocks is determined, thereby delineating the development area of ​​high-quality source rocks.

[0122] Example 1

[0123] To make the objectives, technical solutions, and advantages of this invention clearer, the following description, using the deep layers of the northern Songliao Basin as an example, will be further detailed with reference to the accompanying drawings.

[0124] Taking the deep strata in the northern Songliao Basin as an example, this paper illustrates the implementation process of a comprehensive prediction method for high-quality source rocks based on automatic stratification.

[0125] 1. Geological background and data selection

[0126] The deep strata in the northern Songliao Basin refer to the strata below the second member of the Quantou Formation, mainly consisting of the basement, Huoshiling Formation, Shahezi Formation, Yingcheng Formation, Denglouku Formation, and the first and second members of the Quantou Formation. The basement is composed of metamorphic rocks such as mudstone and phyllite, and intrusive rocks such as granite. The Huoshiling Formation formed in the early stage of the rift basin, with a suite of clastic rocks at the bottom and volcanic rocks and littoral-latitude sediments during the intermittent eruptions in the middle and upper parts. The Lower Cretaceous Shahezi Formation represents the peak period of rift basin development, forming the main source rocks and local caprocks during the rift period. It is widely developed within the rift basin, mainly composed of dark mudstone, interbedded with argillaceous sandstone and conglomerate, and is the main source rock in this area. High-quality source rocks were rapidly identified and predicted in single wells, in series of wells, and on the horizontal plane using wells such as XS1 and DS17 in Xujiaweizi Fault Depression, YS5, SX67, and SS2 in Yingshan-Shuangcheng Fault Depression, GS1 and LS4 in Gulong-Lindian Fault Depression, and BC1 in Beian Fault Depression.

[0127] 2. Identification and Prediction of High-Quality Hydrocarbon Source Rocks

[0128] The method described in step 1) of the invention is used to obtain single-well geological and geochemical columns, step 2) to obtain continuously distributed TOC curves, step 3) to automatically add a TOC classification and stratification channel to the single-well column chart, step 4) to perform a comparison of TOC profiles of consecutive wells, step 5) to draw a TOC planar map of source rocks in the study area, and step 6) to delineate the development area of ​​high-quality source rocks.

[0129] Organic geochemical experiments were conducted using samples from drilling cores, wellbore cores, and cuttings logging. The obtained geochemical data, including TOC, S1+S2, HI, chloroform bitumen A', and Ro, along with their corresponding depths, were added to a single-well comprehensive columnar section to obtain a single-well geological and geochemical column. Figure 1As shown, the organic carbon content of the mudstone in the Shahezi Formation of Well XS1 is as high as 6% to 15%, the organic carbon content of the coal is 35% to 62%, the hydrocarbon generation potential is 0.52 mg / g to 4.08 mg / g, and the hydrogen index is 100-400 mg / g TOC, reaching the standard of medium to good source rock; the Ro is above 2.0%, reaching the high to over-mature stage.

[0130] This study utilized well logging to calculate TOC (Total Hydrocarbon Concentration) in five deep fault depressions in the northern Songliao Basin (Xujiaweizi Fault Depression, Gulong-Lindian Fault Depression, Yingshan-Shuangcheng Fault Depression, Suihua Fault Depression, and Bei'an Fault Depression). Taking well SX67 as an example, the average measured TOC of the Shahezi Formation was 2.49%, while the average calculated TOC was 2.55%. High-abundance source rocks are developed in the lower part of the first stratum of the Shahezi Formation. The Shahezi source rocks are considered good source rocks, with a thickness of 96m containing source rocks with TOC > 1%. The TOC value calculated from the well logging curves of well SX67 was compared with the measured TOC value on a geochemical columnar section, as shown in the figure below. Figure 2 As shown.

[0131] Based on the Resform geological software platform, a script (macro) suitable for the study area was written, and classification symbols were configured. After running the macro, automatic TOC classification can be achieved, and a TOC classification stratification channel will be automatically added to the single-well column chart, such as... Figure 3 As shown.

[0132] To facilitate detailed research and evaluation of source rock characteristics, this study conducted a detailed correlation of the source rocks of the Shahezi Formation in Xujiaweizi. Six TOC (Total Organic Criterion) well profiles of the Shahezi Formation were established in the Xujiaweizi area, spanning two horizontal and four vertical lines. Simultaneously, two TOC well profiles of the Shahezi Formation were also established in the Yingshan-Shuangcheng fault depression. Figure 4 A comparison diagram of the TOC well profiles of wells DS3-SS6. Figure 4 It can be seen that the abundance and thickness of the source rocks in the Shahezi Formation in the northern part of the Xujiaweizi fault depression increase from north to south. High-quality source rocks are mainly distributed in the Anda area, and the overall structure shows high abundance and good continuity in the Shahezi Formation No. 4 Member. Fine TOC correlation shows that three cycles of high-quality source rocks can be developed within each sequence group of the Shahezi Formation. The TOC values ​​of the source rocks in the Shahezi Formation in the northern part of the Xujiaweizi fault depression are mainly between 1% and 3%, with some wells showing TOC values ​​greater than 3%.

[0133] The distribution characteristics of organic matter abundance in the Shahezi Formation mudstone are basically consistent with those of mudstone thickness distribution. The range of TOC values ​​greater than 1.0% is quite large, reaching over 4% in the central Xujiaweizi area. Based on the superposition of mudstone thickness and organic matter abundance, the effective source rock area of ​​the Shahezi Formation in the entire region is 2800.7 km². 2The source rocks of the Shahezi Formation in the Xujiaweizi fault depression have high organic matter abundance, with TOC values ​​generally exceeding 1.6%, and the highest TOC value near well XS401 exceeding 4.0%. The Shahezi Formation is the main source rock in this area. Figure 5 This is a TOC plan diagram drawn using the deep Shahezi Formation source rocks in Songbei as an example. Statistical analysis shows that the agreement rate between the well point values ​​on the TOC plan diagram and the measured values ​​is over 90% for each layer. Table 2 is a statistical table showing the agreement rate between the well point values ​​on the TOC plan diagram calculated using well logging curves and the measured values.

[0134] Table 2. Statistical table of the consistency rate between TOC planar well point values ​​calculated using well logging curves and measured values.

[0135] Layer TOC (single well) Number of samples Number of wells Compliance rate (%) Denglouku Group 0.2-5.25 / 0.49 402 83 90.12 Yingcheng Group 0.2-8.29 / 1.58 652 107 92.36 Shahezi Group 0.2-9.86 / 1.64 1036 91 95.99 Huoshiling Group 0.25-7.44 / 1.46 52 33 94.81

[0136] According to data, the hydrocarbon generation conditions in China's large and medium-sized gas fields are characterized by a hydrocarbon generation intensity greater than 20 × 10⁻⁶. 8 m 3 / km 2 Theoretical calculations yielded a theoretical curve showing the relationship between the thickness of the mudstone in the Shahezi Formation of Xujiaweizi and its total organic carbon (TOC). Wells DS12, XS1, and ZS32 were selected to measure the mudstone thickness and TOC of the Shahezi Formation. The measured values ​​were compared with the theoretical curve. Analysis showed that a TOC of 1% for the mudstone in the Shahezi Formation can be considered as the lower limit for high-quality source rocks. Figure 6 Map showing the delineated high-quality source rock development area of ​​the deep Shahezi Formation in Songbei; Figure 6 The base map is a plan view of the thickness of the dark mudstone in the Shahezi Formation, with the boundary of high-quality source rocks within the black dashed line. The thickness of the dark mudstone in the central Xujiaweizi, western Yingshan, southern Gulong, central Lindian, and eastern Bei'an all exceed 300m. Overall, the Shahezi Formation has a large stratum thickness and good source rock conditions, providing favorable conditions for near-source hydrocarbon accumulation. Five potential exploration areas in the peripheral fault depressions were identified in this stratum: the high-quality source rock area in the YS5 well area covers 245 km². 2 The thickest layer is ≥600m. The source-reservoir matching relationship in the Yingshan-Shuangcheng fault depression is relatively good, and the oil test result of well YS5 is low-yield; the area of ​​high-quality source rocks in the SS2 well area is 79km². 2 The thickest layer is ≥800m, and a gas-poor layer is observed in the comprehensive interpretation; the area of ​​high-quality source rock in the GS1 well area is 380km². 2 The area of ​​high-quality source rocks in the LS4 well area is 415 km². 2 Drilling at LS4 revealed a suspected gas layer; the area of ​​high-quality source rock in the eastern part of BC1 well is 52 km². 2 Although the area is relatively small, the mudstone thickness can reach more than 500m, which can be regarded as a favorable area for the next exploration.

[0137] Using this invention, the development area of ​​high-quality source rocks in the deep Shahezi Formation in the northern Songliao Basin was accurately delineated. Four risk exploration wells were drilled in the ancient central uplift zone, of which two wells achieved high production during gas testing and two wells showed oil and gas. In Anda, Xingshan, Xunan and other areas, multiple exploration wells (DS28, DS34, ZS32) have well-developed source rocks and have obtained industrial gas flow, demonstrating good exploration prospects.

[0138] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the implementation methods of the present invention, and should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of the present invention.

Claims

1. A comprehensive prediction method for high-quality source rocks based on automatic stratification, characterized in that: Includes the following steps: S1. Utilize geochemical data to obtain single-well geological and geochemical columns and conduct single-well geochemical evaluation; S2. Based on the obtained single-well geological and geochemical columns, the TOC value of the single well is calculated using well logging curves to obtain continuously distributed TOC curves; S3. Based on the obtained continuously distributed TOC curves, the TOC of a single well is automatically stratified to obtain the TOC stratification channels; S4. Based on the obtained TOC classification and layering, draw the TOC well-connection profile. S5. Based on the obtained TOC well profile, draw the source rock TOC plan view; S6. Based on the obtained TOC plan of the source rock, delineate the development zone of high-quality source rock.

2. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 1, characterized in that: Step S1 utilizes geochemical data to obtain single-well geological and geochemical columns for single-well geochemical evaluation; specific methods include: Organic geochemical experiments were conducted using core sampling, wellbore coring, cuttings logging, and outcrop samples. The resulting geochemical data were added to the single-well comprehensive columnar section according to the corresponding depth of the samples, thus obtaining the single-well geological and geochemical column. The single-well geochemical evaluation was then carried out based on the obtained single-well geological and geochemical column.

3. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 2, characterized in that: The geochemical data include: total organic carbon (TOC), hydrocarbon generation potential (S1+S2), hydrogen index (HI), oxygen index (OI), pyrolysis type index (S2 / S3), total hydrocarbon content (HC), chloroform bitumen (A'), type index (TI), hydrogen-to-carbon ratio (H / C), oxygen-to-carbon ratio (O / C), vitrinite reflectance (Ro), and pyrolysis peak temperature (Tmax).

4. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 3, characterized in that: The single-well geochemical evaluation specifically includes the following three aspects: Regarding organic matter abundance: source rocks are classified into four levels based on TOC, S1+S2, chloroform bitumen A', and HC: non-source rocks, general source rocks, good source rocks, and high-quality source rocks. Regarding organic matter type: source rocks are classified into four types using type indices TI, H / C, O / C, HI, OI, and S2 / S3: Type I, Type II1, Type II2, and Type III; Regarding the maturity of organic matter: the source rocks are divided into five evolutionary stages based on Ro and Tmax: immature stage, low maturity stage, mature stage, high maturity stage and over-mature stage.

5. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 1, characterized in that: Step S2, based on the obtained single-well geological and geochemical column, calculates the single-well TOC value using well logging curves to obtain a continuously distributed TOC curve; the specific method is as follows: Based on the identification of lithological profiles such as sandstone and mudstone, the single-well geological and geochemical column obtained in step S1 is used to calculate the organic matter abundance (TOC) using sonic transit time and resistivity curves, resulting in a continuously distributed TOC curve.

6. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 5, characterized in that: The method for calculating the total organic matter abundance (TOC) is as follows: The TOC is calculated using the ΔlgR technique, and the formula is as follows: TOC = a × △logR + b △logR=log(R / Rbase)+K×(△T-△Tbase) In the formula: a: Coefficient, which can be adjusted based on the calculation results; b: A constant representing the background value of TOC (Total Organic Carbon), typically 0.2-0.4; △logR: The measured curve spacing on a logarithmic coordinate system; R: Deep resistivity logging value (unit: Ω·m); Rbase: The baseline value of the RT logging curve; K: constant, default value 0.02; △T: Sound wave propagation time (unit: μs / ft or μs / m); △Tbase: Baseline value of the AC logging curve; When performing TOC calculations, the coefficients a and b in the calculation formula are adjusted to ensure that the calculated TOC value matches the measured TOC value.

7. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 6, characterized in that: For the entire well section, methods to better match the calculated TOC value with the measured TOC value include: ① For thin interbedded sections of source rocks, a segmented processing technique is used to improve the correlation between calculated and measured values; ② For source rock sections with low total organic carbon abundance, the method of adjusting the baseline value is adopted to make the vertical profile characteristics more obvious and reduce the error; ③ For the low-sonic section of the logging curve, the baseline should be lowered to avoid negative values ​​or inconsistencies in lithology and electrical properties. ④ For well sections with strong heterogeneity, ensure that the calculated average TOC value and the measured average TOC value match for the entire well section.

8. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 1, characterized in that: Step S3, based on the obtained continuously distributed TOC curves, automatically stratifies the TOC of a single well to obtain TOC stratification channels; the specific method is as follows: Using the Resform geological research software platform, a TOC grading and layering channel is added to the single-well columnar chart of the continuously distributed TOC curve obtained in step 2), which is the single-well TOC grading and layering channel.

9. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 8, characterized in that: The method for adding a TOC (Total Occupation Code) grading and layering channel to a single-well column chart, based on the Resform geological research software platform, is as follows: Based on the continuously distributed TOC curves, and relying on the Resform geological software platform, a script program suitable for the study area was written. At the same time, the classification symbols were configured. After running the macro, a TOC classification layered channel will be automatically added to the single-well column chart, which is the single-well TOC classification layered channel. The process of writing a script suitable for the research area can be divided into the following 5 steps: Create a layered channel and set its name; Set the top and bottom depths for each layer of the TOC (Transmission of Cost) level; Set up 3 TOC levels and determine the boundary values ​​for each level; Set the colors for each TOC level; Continue calculating until the bottom depth is reached, then terminate the operation.

10. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 1, characterized in that: Step S4 involves drawing a TOC well-connection profile based on the obtained TOC graded and layered channels; the specific method is as follows: Based on the obtained TOC classification and layered channels, a framework of source rock TOC well-connected profiles is constructed according to the structural strike and dip of the study area. Within the framework, the connectivity and pinch-out locations of different sub-layers of source rocks are determined based on the mudstone thickness and TOC classification results, thus obtaining the TOC well-connected profile.

11. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 1, characterized in that: The method for drawing the TOC plan of the source rock in step S5 includes the following steps: Based on the obtained TOC well profile, and using all exploration well, logging, and lithological data, and referring to the formation thickness map, a thickness map of the source rocks in the study area was drawn. The TOC results are calculated based on the well logging curves. The oil-based mud contamination section is removed from the calculated TOC results. The TOC planar map of the source rocks in the study area is drawn with reference to the sedimentary facies diagram trend and the thickness map of the source rocks in the study area.

12. The comprehensive prediction method for high-quality source rocks based on automatic stratification according to claim 1, characterized in that: The method for delineating the high-quality source rock development area in step S6 is as follows: Based on the obtained TOC plan of the source rocks, the TOC boundaries of high-quality source rocks are determined according to the correlation between TOC and S1 / TOC and TOC and S2 in the study area; and the development area of ​​high-quality source rocks is delineated based on the determined TOC boundaries of high-quality source rocks.

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