A method for determining a facies division scheme of a continental mixed sedimentary shale
By adopting an evaluation-then-classification method in the facies classification of mixed mudstone and shale, combining core observation and well logging curves, and using mineral triangular charts to distinguish the mineral components of small layers, the problem of insufficient accuracy in facies classification in existing technologies has been solved, and efficient and accurate facies type identification and evaluation have been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA PETROLEUM & CHEMICAL CORP
- Filing Date
- 2022-09-27
- Publication Date
- 2026-07-03
AI Technical Summary
Existing technologies lack accuracy in classifying the facies of mixed mudstone and shale, failing to effectively distinguish favorable facies, resulting in low work efficiency and failing to meet practical application needs.
The principle of evaluation before classification was adopted. Based on core observation and well logging curve identification, combined with sedimentary cycle characteristics, mineral composition analysis was carried out on different sub-layers. Evaluation was conducted by assigning key parameters, and different evaluation levels were distinguished by mineral triangle charts to determine the lithofacies classification scheme.
It improves the accuracy and effectiveness of lithofacies classification, increasing accuracy by 60% and work efficiency by 85%, providing a basis for selecting "sweet spot" layers and target windows, and achieving efficient lithofacies classification.
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Figure CN115542420B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of petroleum exploration, and specifically relates to a method for determining the lithofacies classification scheme of continental mixed sedimentary mudstone and shale. Background Technology
[0002] my country is rich in unconventional shale oil resources, especially in the eastern continental shale oil resources, including the Songliao Basin, Cangdong Depression, Jiyang Depression and Subei Basin. The continental mudstone and shale have complex mineral compositions and strong sedimentary heterogeneity. There are various lithofacies classification schemes and no unified standard. Many scholars have different opinions.
[0003] In their article "A Method for Lithofacies Classification of Shale Strata," published in the Journal of China University of Petroleum (Natural Science Edition) Vol. 39, No. 3, 2015, Dong Chunmei et al. pointed out that: "The composition of shale strata is complex, and the lithofacies classification schemes are not uniform. Through core observation, microscopic identification, whole-rock analysis, and organic geochemical data analysis, a comprehensive lithofacies classification scheme for shale strata is established by combining core macrostructure, organic matter content, and rock type, based on the principle of 'four-component, three-end-member' classification."
[0004] The article "Diversity of Lithofacies Assemblages in Marine and Continental Shale Systems in China and Their Significance for Unconventional Oil and Gas Exploration," published by Li Maowen et al. in the 2022 issue of *Petroleum and Natural Gas Geology* (Vol. 43, No. 1), points out that: "There is a strong correlation between organic-rich fine-grained sedimentary facies assemblages and organic facies. Carbonate-rich fine-grained sedimentary facies assemblages are dominated by type I-S or II-S organic facies, felsic shale facies assemblages are mostly type II organic facies, while clayey shale facies assemblages are mostly type III / IV organic matter. Therefore, whole-rock..." Mineral X-ray diffraction analysis can be used to study fine-grained sedimentary facies and sedimentary environments, and can also provide important reference information such as organic matter types, hydrocarbon product characteristics, rock mechanical properties, and compressibility. Based on the comparative analysis of marine shale in North America and the Sichuan Basin, this study focuses on major terrestrial shale strata in China. Using whole-rock mineral X-ray diffraction analysis, combined with core observation, thin section identification, and total organic carbon (TOC) analysis, this study identifies lithofacies and organic facies types, as well as lithofacies assemblage characteristics and differences among different shale strata. This study analyzes the characteristics of shale sediments and explores their guiding significance for unconventional shale oil and gas exploration. The results show that China's continental lacustrine basins exhibit diverse sedimentary types. During the subsidence period of continental basins, freshwater to slightly brackish lacustrine shale strata are dominated by a clayey-felsic shale facies assemblage rich in carbonate minerals. Conversely, during the rifting period of continental basins, salinized and alkalized lacustrine sediments are dominated by carbonate shale facies assemblages and carbonate-bearing clayey-felsic shale facies assemblages. All types of continental fine-grained sedimentary systems are characterized by rapid facies zoning, complex lithology and lithofacies, and diverse reservoir-seal combinations. The heterogeneity and diversity of lithofacies facies in China's continental fine-grained sedimentary rocks lead to a diversity of "sweet spot" types for continental shale oil and gas. Significant differences exist in the organic phases corresponding to different lithofacies assemblages, and the differential evolution of organic matter further results in differences in the hydrocarbon occurrence states within different lithofacies. These analytical results confirm that each continental shale system possesses its own unique geological characteristics. The diversity and differences in fine-grained sedimentary lithofacies and organic phase assemblages reveal the necessity for the classification and evaluation of continental shale oil and gas "sweet spots" and resources.
[0005] The article "Geological Characteristics and Shale Oil Exploration Practice of the Third Member and First Sub-Member of the Shahejie Formation in the Qikou Depression of the Bohai Bay Basin" published by Zhou Lihong et al. in the 2021 issue of "Petroleum and Natural Gas Geology" (Volume 42, Issue 2) points out: "The third member and first sub-member of the Shahejie Formation in the Qikou Depression [Es]..." 3(1) High-yield and stable industrial oil flows have been obtained in shale oil exploration, confirming the significant exploration potential of lacustrine shale oil and establishing a market with reserves exceeding 100 million tons. This provides important reference for the exploration of shale oil in the widely distributed Shahejie Formation in the Bohai Bay Basin. A comprehensive study was conducted on the sedimentary environment, lithology, reservoir properties, brittleness, and oil-bearing characteristics of the three members of the Shahejie Formation in the Qikou Depression. 3(1)The semi-deep to deep lake region features well-developed pores and fractures in its mudstone and shale formations, high brittleness index, poor reservoir sensitivity, and good hydrocarbon potential. It possesses favorable conditions for hydrocarbon generation, reservoir development, oil production, and engineering stimulation, making its shale oil accumulation geological conditions excellent. Vertically, Es... 3(1) The area is divided into six sweet spots, numbered C1-C6 from top to bottom. The planar distribution is stable, with individual spot thicknesses ranging from 7 to 96 meters, a cumulative thickness of 434 meters, and a distribution area ranging from 87.4 to 194.3 km². 2 The stacked area of the planar dessert is 256 km². 2 Using the volumetric oil content method, the preliminary resource quantity is calculated to be 4.1 × 10⁻⁶. 8 Following the principle of "controlling the production area with old wells and increasing production with horizontal wells," industrial oil flow was obtained in two highly deviated wells, Bin60-56 and F38x1. Horizontal wells were deployed for exploration in the C1 sweet spot. Well QY10-1-1 obtained a high-yield oil and gas flow of 100 tons per day. After 206 days of self-flowing trial production, well Bin56-1H produced a cumulative oil production of 3043.11 tons, with a backflow rate of 7.77%. Significant breakthroughs have been achieved in the exploration of shale oil in the Sha-3 section of the Qikou Depression.
[0006] Although the above classification scheme solves some problems, its application to the classification of mixed sedimentary shale facies still has certain limitations as described in the background technology. Summary of the Invention
[0007] This invention provides a method for determining the lithofacies classification scheme of continental mixed sedimentary mudstone and shale, specifically a method for determining an effective lithofacies classification scheme for mudstone and shale. Unlike conventional classification schemes, this method adopts the principle of evaluation before classification. Based on core observation and well logging curve identification, it conducts sub-layer classification, evaluates different sub-layers using key parameter assignment, analyzes the distribution patterns of mineral components in different sub-layers within mineral triangular charts, and determines the lithofacies classification scheme based on effectively distinguishing different evaluation levels.
[0008] This application provides a method for determining the lithofacies classification scheme of terrestrial mixed sedimentary mudstone and shale, including:
[0009] Step 1, Core observation: Based on the sedimentary principles of strata, observe the cores in order of depth from deep to shallow.
[0010] Step 2, stratigraphic division: Using the results of core observation and combined with the characteristics of well logging curves, stratigraphic division is carried out;
[0011] Step 3, Layer Evaluation: Samples are taken from each layer, and pyrolysis and irregular sample property analysis are carried out. Layer evaluation is performed based on the analysis results.
[0012] Step 4, composition determination: X-ray diffraction whole-rock analysis was performed on the cores corresponding to each sub-layer to analyze the rock mineral composition;
[0013] Step 5, Scheme Determination: Based on the above analysis results, determine the target division scheme.
[0014] The first step, core observation, includes:
[0015] Based on the sedimentary principles of strata, observations are conducted in order from deep to shallow, observing the size of the sedimentary structures, the variation patterns of color, the relative content of ash and cloudiness in carbonate minerals, and the characteristics of tectonic changes, in order to determine the characteristics of sedimentary cycles.
[0016] Step 2, stratigraphic division, includes:
[0017] Based on the results of core observations and the characteristics of well logging curves (including resistivity curves, gamma curves, and sonic curves), strata with consistent curve variation patterns can be divided into the same set of sub-layers. Furthermore, considering sedimentary cycle characteristics, mudstone and shale formations with the same sedimentary cycle characteristics on the plane are divided into the same set of strata. Each segment is divided into at least 5 sub-segments, and each sub-segment is further divided into different sub-layers based on the thickness of the strata. Strata with a thickness of 90–130 m are divided into at least 10–12 sub-layers, strata with a thickness of 70–90 m are divided into at least 6–9 sub-layers, and strata with a thickness of 50–70 m are divided into at least 3–5 sub-layers.
[0018] Step 3, the sub-level evaluation, includes:
[0019] At least one sample was taken from each meter of different sublayers to conduct pyrolysis and physical property analysis of irregular samples, and key parameters such as organic carbon (TOC), free hydrocarbons (S1), saturation index (S1 / TOC), and porosity were obtained. Parameters are assigned values, categorized as follows: TOC ≥ 1.8% is category one, 0.9% ≤ TOC < 1.8% is category two, and TOC < 0.9% is category three; S1 ≥ 3 mg / g is category one, 2 mg / g ≤ S1 < 3 mg / g is category two, and S1 < 2 mg / g is category three; S1 / TOC ≥ 150 mg / g is category one, 100 mg / g ≤ S1 / TOC < 150 mg / g is category two, and S1 / TOC < 100 mg / g is category three. As one category, Classified into two categories, It is classified into three categories: organic carbon (TOC), free hydrocarbons (S1), oil saturation index (S1 / TOC), and porosity. The parameter assignment ranges for categories one, two, and three are the same: category one is assigned a range of 0.8-1.0, category two a range of 0.6-0.8, and category three a range of 0.5-0.6. The weights for the organic carbon (TOC) parameter are 0.3, the free hydrocarbon (S1) parameter is 0.3, the oil saturation index (S1 / TOC) parameter is 0.1, and porosity... With a parameter weight of 0.3, the comprehensive evaluation results of each sub-layer are obtained and sorted according to the scores. The top 30% of the comprehensive evaluation scores are classified as Class I, 30% to 60% as Class II, and the rest as Class III.
[0020] Step 4, component determination, includes:
[0021] At least one core sample was taken from each meter of the corresponding sublayer for whole-rock X-ray diffraction analysis to analyze the mineral composition of the rock, including quartz, calcite, dolomite, ferrodolomite, plagioclase, potassium feldspar, siderite, pyrite, halite, anhydrite, gypsum, gypsum, anhydrous mirabilite, barite, calcium mirabilite, zeolite, analcime, and clay. Quartz, plagioclase, and potassium feldspar were classified as feldspar-quartz terrigenous clastic minerals, calcite, dolomite, and ferrodolomite as carbonate minerals, and clay as clay minerals. The sum of the three minerals (feldspar-quartz, carbonate minerals, and clay minerals) was less than or equal to 100. Feldspar-quartz, carbonate minerals, and clay minerals were used as the three end-members of the mineral composition triangle plate.
[0022] In step 5, the scheme is determined as follows: Based on the compositional characteristics of feldspar, quartz, carbonate minerals, and clay minerals in different sub-layers, their distribution patterns are represented by mineral triangle maps. The distribution points of whole-rock mineral components in different sub-layers are located at different points within the triangle map. The evaluation results of different sub-layers have already been clarified in step 3. With these two conditions met, the choice of which triangle map to use is then determined. The internal division scheme of each triangle map is different. The map that can distinguish between Class I, Class II, and Class III layers is selected. Different points within the triangle map represent different mineral compositions. It is required that when projecting points for the same sub-layer, at least 90% of the sample points in all measured samples are projected within the same area, and the projected areas for different sub-layers with similar evaluation results should be the same. This is considered a feasible division scheme.
[0023] The method for determining the lithofacies classification scheme of terrestrial mixed sedimentary mudstone and shale in this application has the following beneficial effects:
[0024] This invention provides a method for determining the lithofacies classification scheme of terrestrial mixed sedimentary mudstone and shale, which is an effective method for classifying mudstone and shale lithofacies. Unlike conventional classification schemes, this method adopts the principle of evaluation before classification. Based on core observation and well logging curve identification, combined with sedimentary cycle characteristics, it conducts sub-layer classification, evaluates different sub-layers using key parameter assignment, analyzes the distribution patterns of mineral components in different sub-layers on mineral triangular charts, and determines the lithofacies classification scheme based on effectively distinguishing different evaluation levels.
[0025] The method employed in this invention improves the accuracy and effectiveness of lithofacies classification schemes, increases work efficiency, and avoids the inability of lithofacies classification methods to effectively distinguish favorable lithofacies. Accuracy is improved by 60 percentage points, reaching 98.2%. It avoids repetitive work, reducing the workload of 3 people for 15 days to 1 person for 5 days, increasing work efficiency by over 85%. Accurate and efficient lithofacies classification lays the foundation for further evaluation of favorable lithofacies and provides a basis for selecting "sweet spots" and target windows, effectively meeting the needs of practical applications. After application in a well in a basin depression, the single well produced 45 tons of oil per day, reaching industrial oil flow. Attached Figure Description
[0026] Figure 1 A flowchart illustrating the method for determining the lithofacies classification scheme of terrestrial mixed mudstone and shale in this application;
[0027] Figure 2 This is a comprehensive columnar section diagram of a certain well section 2 in this application;
[0028] Figure 3 A triangular diagram of whole-rock mineral composition of the V sub-member of the second section of a certain well.
[0029] Figure 4 This is a triangular diagram of the mineral composition of the V-1 sublayer in the second section of a certain well.
[0030] Figure 5 This is a triangular diagram of the mineral composition of the V-2 sublayer in the second section of a certain well.
[0031] Figure 6 This is a triangular diagram of the mineral composition of the V-3 sublayer in the second section of a certain well.
[0032] Figure 7 This is a triangular diagram of the mineral composition of the V-4 sublayer in the second section of a certain well.
[0033] Figure 8 This is a triangular diagram of the mineral composition of the V-5 sublayer in the second section of a certain well.
[0034] Figure 9 This is a triangular diagram of the mineral composition of the V-6 sublayer in the second section of a certain well.
[0035] Figure 10 This is a triangular diagram of the mineral composition of the V-7 sublayer in the second section of a certain well.
[0036] Figure 11 This is a triangular diagram of the mineral composition of the V-8 sublayer in the second section of a certain well.
[0037] Figure 12 This is a triangular diagram of the mineral composition of the V-9 sublayer in the second section of a certain well.
[0038] Figure 13 This is a triangular diagram of the mineral composition of the V-10 sublayer in the second section of a certain well.
[0039] Figure 14 A triangular diagram showing the mineral composition of the V-1 sublayer in the second section of a certain well.
[0040] Figure 15 A triangular diagram showing the mineral composition correlation of the V-2 sublayer in the second section of a certain well.
[0041] Figure 16 A triangular diagram showing the mineral composition correlation of the V-3 sublayer in the second section of a certain well.
[0042] Figure 17 A triangular diagram showing the mineral composition correlation of the V-4 sublayer in the second section of a certain well.
[0043] Figure 18 A triangular diagram showing the mineral composition correlation of the V-5 sublayer in the second section of a certain well.
[0044] Figure 19 A triangular diagram showing the mineral composition correlation of the V-6 sublayer in the second section of a certain well.
[0045] Figure 20 A triangular diagram showing the mineral composition of the V-7 sublayer in the second section of a certain well.
[0046] Figure 21 A triangular diagram showing the mineral composition correlation of the V-8 sublayer in the second section of a certain well.
[0047] Figure 22 A triangular diagram showing the mineral composition of the V-9 sublayer in the second section of a certain well.
[0048] Figure 23 This is a triangular diagram showing the mineral composition of the V-10 sublayer in the second section of a certain well. Detailed Implementation
[0049] The present application will be further described below with reference to the accompanying drawings and embodiments.
[0050] In the following description, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The following description provides multiple embodiments of the invention, which can be substituted or combined with each other. Therefore, this application can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more other possible combinations of A, B, C, and D, even if such embodiments are not explicitly described in the following text.
[0051] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this application. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
[0052] Example 1
[0053] like Figure 1 As shown, the method for determining the facies classification scheme of terrestrial mixed sedimentary mudstone and shale in this application includes the following steps: S101, core observation: observation is conducted according to the sedimentary principles of strata, following a depth-to-shallow order; S103, stratigraphic division: stratigraphic division is performed using the results of core observation combined with well logging curve characteristics; S105, sub-layer evaluation: samples are taken from each sub-layer, and pyrolysis and irregular sample property analysis are conducted, with sub-layer evaluation based on the analysis results; S107, composition determination: X-ray diffraction whole-rock analysis is performed on the cores corresponding to each sub-layer to analyze the rock mineral composition; S109, scheme determination: the target classification scheme is determined based on the above analysis results. The final determined scheme is the target sought, i.e., the optimal classification scheme.
[0054] The method used in this invention improves the accuracy and effectiveness of lithofacies classification schemes, and the lithofacies classification method can effectively distinguish favorable lithofacies.
[0055] Example 2
[0056] The method used in this application to determine the lithofacies classification scheme for terrestrial mixed sedimentary mudstone and shale includes:
[0057] Step 1, Core observation: Based on the sedimentary principles of strata, observe in order from deep to shallow to preliminarily observe the size of the sedimentary structure, the color variation pattern, the relative content of ash (calcium carbonate CaCO3) and cloud (magnesium carbonate MgCO3) in carbonate minerals, and the structural variation characteristics to determine the characteristics of sedimentary cycles.
[0058] Step 2, Stratigraphic Division: Utilizing core observation results and combining well logging curve characteristics (including but not limited to resistivity series curves, gamma curves, and sonic curves), based on the relative high and low variation patterns of the curves, strata with consistent curve variation patterns can be divided into the same set of sub-layers. Combining with drilling curves within the area, further stratigraphic division is carried out. Mudstone and shale with the same sedimentary cycle characteristics on the plane are ultimately divided into the same strata. Each segment (generally defined stratigraphic name; the same set of strata is named segment-sub-layer in descending order of thickness) is divided into at least 5 sub-segments. Each sub-segment is divided into different sub-layers according to the different thicknesses of the strata. Strata with a thickness of 90–130 m are divided into at least 10–12 sub-layers, strata with a thickness of 70–90 m are divided into at least 6–9 sub-layers, and strata with a thickness of 50–70 m are divided into at least 3–5 sub-layers.
[0059] Step 3, Sublayer Evaluation: Take at least one sample per meter from different sublayers, conduct pyrolysis and irregular sample property analysis, and obtain key parameters such as organic carbon (TOC), free hydrocarbons (S1), oil saturation index (S1 / TOC), and porosity. Parameters are assigned values, categorized as follows: TOC ≥ 1.8% is category one, 0.9% ≤ TOC < 1.8% is category two, and TOC < 0.9% is category three; S1 ≥ 3 mg / g is category one, 2 mg / g ≤ S1 < 3 mg / g is category two, and S1 < 2 mg / g is category three; S1 / TOC ≥ 150 mg / g is category one, 100 mg / g ≤ S1 / TOC < 150 mg / g is category two, and S1 / TOC < 100 mg / g is category three. As one category, Classified into two categories, It is classified into three categories: organic carbon (TOC), free hydrocarbons (S1), oil saturation index (S1 / TOC), and porosity. The parameter assignment ranges for categories one, two, and three are the same: category one is assigned a range of 0.8-1.0, category two a range of 0.6-0.8, and category three a range of 0.5-0.6. The weights for the organic carbon (TOC) parameter are 0.3, the free hydrocarbon (S1) parameter is 0.3, the oil saturation index (S1 / TOC) parameter is 0.1, and porosity... With a parameter weight of 0.3, the comprehensive evaluation results of each sub-layer are obtained and sorted according to the scores. The top 30% of the comprehensive evaluation scores are classified as Class I, 30% to 60% as Class II, and the rest as Class III.
[0060] Step 4, Component Determination: For each sublayer, at least one core sample should be taken per meter to address the strong heterogeneity of terrestrial mudstone and shale facies. Whole-rock X-ray diffraction (XRD) analysis should be performed to determine the rock mineral composition, including quartz, calcite, dolomite, ferrodolomite, plagioclase, potassium feldspar, siderite, pyrite, halite, anhydrite, gypsum, gypsum, anhydrous mirabilite, barite, calcium mirabilite, zeolite, analgesic, and clay. Quartz, plagioclase, and potassium feldspar are considered terrestrial clastic feldspar minerals; calcite, dolomite, and ferrodolomite are considered carbonate minerals; and clay is considered a clay mineral. The sum of the values of feldspar, carbonate, and clay minerals must be less than or equal to 100. Feldspar, carbonate, and clay minerals are then used as the three end-members of the mineral composition triangle diagram.
[0061] Step 5, Scheme Determination: Based on the compositional characteristics of feldspar, quartz, carbonate minerals, and clay minerals in different sub-layers, their distribution patterns are represented by mineral triangular diagrams. The distribution points of whole-rock mineral components in different sub-layers differ within the triangular diagrams, as the evaluation results for different sub-layers were already clarified in Step 3. With these two conditions met (first, mineral components are represented by points in the triangular diagram according to different sub-layers; second, the evaluation level of different sub-layers has been determined—Class I, Class II, or Class III), the choice of which triangular diagram to use is then determined. Each triangular diagram has a different internal division scheme. The selected diagram distinguishes between Class I, Class II, and Class III layers, with different points representing different mineral compositions. A feasible division scheme requires that over 90% of the points within the same sub-layer are in the same area, and that the point areas for the same evaluation results across different sub-layers are identical. In existing technologies, a triangular diagram is selected first; however, this invention meticulously evaluates each sub-layer before dividing the internal structure of the triangular diagram, thus improving efficiency and accuracy through targeted approach.
[0062] This invention provides a method for determining the lithofacies classification scheme of terrestrial mixed sedimentary mudstone and shale, which is an effective method for classifying mudstone and shale lithofacies. Unlike conventional classification schemes, this method adopts the principle of evaluation before classification. Based on core observation and well logging curve identification, combined with sedimentary cycle characteristics, it conducts sub-layer classification, evaluates different sub-layers using key parameter assignment, analyzes the distribution patterns of mineral components in different sub-layers on mineral triangular charts, and determines the lithofacies classification scheme based on effectively distinguishing different evaluation levels.
[0063] Example 3
[0064] The following section uses the HY1 well in a certain depression as an example to introduce each step.
[0065] Step 1, Core observation of Well HY1: Based on the sedimentary principles of strata, observations are conducted in order of depth from deep to shallow. Preliminary observations are made of the size of the sedimentary structures, the color variation patterns, the relative content of ash (calcium carbonate, CaCO3) and globin (magnesium carbonate, MgCO3) in the carbonate minerals, and the structural variation characteristics to determine the sedimentary cycle characteristics. An equilateral triangle "△" represents a positive cycle. From the base to the top of the triangle, the basic sedimentary characteristics are a finer sedimentary structure, a darker color, and a change in structure from thick to thin layers. The sedimentary division scheme is as follows: Figure 2 As shown.
[0066] Step 2, HY1 well stratigraphic division: Utilizing the results of core observations and combining the characteristics of the HY1 well logging curves, including resistivity curves RS and RD and gamma curve GR, the stratigraphic layers with consistent curve variation patterns were divided into the same sub-layers based on the relative high and low variation patterns of the curves. Combining the drilling curves in the area, further stratigraphic division was carried out, and mudstone and shale with the same sedimentary cycle characteristics on the plane were finally divided into the same stratigraphic layers. The E1f2 section of the Fu-2 member of the HY1 well was divided into 5 sub-sections from bottom to top, namely V to I. Among them, the thickness of sub-section V is 103m, and it is divided into 10 sub-layers from bottom to top, namely V-10 to V-1. The curves are divided into five sub-segments: Sub-segment I, with low resistivity (RS and RD) of 2.1-5.0 Ω·m, is flat with little variation; Sub-segment II, with median resistivity of 3.5-20.1 Ω·m, is a low-amplitude arc-shaped curve; Sub-segment III, with resistivity of 4.2-182.9 Ω·m, is sawtooth-shaped with 7-8 sawtooth cycles; Sub-segment IV, with resistivity of 4.4-99.7 Ω·m, has 4 sets of high-resistivity peaks within the curve; and Sub-segment V, with resistivity of 4.8-82.0 Ω, has a flat upper curve and 5 high-resistivity peaks in the middle and lower parts.
[0067] Step 3, Evaluation of sub-layers in sub-section V of well HY1: 1-2 core samples were taken per meter from different sub-layers in sub-section V of well HY1. Sub-layer V-1, 14m thick, 17 samples were taken; sub-layer V-2, 7.5m thick, 11 samples were taken; sub-layer V-3, 13.5m thick, 14 samples were taken; sub-layer V-4, 10m thick, 15 samples were taken; sub-layer V-5, 8m thick, 20 samples were taken; sub-layer V-6, 15m thick, 23 samples were taken; sub-layer V-7, 13m thick, 22 samples were taken; sub-layer V-8, 5m thick, 8 samples were taken; sub-layer V-9, 14m thick, 20 samples were taken; sub-layer V-10, 3m thick, 6 samples were taken. All samples met the sampling requirements. Pyrolysis and irregular sample physical property analysis were conducted to obtain key parameters of the well, including total organic carbon (TOC), free hydrocarbons (S1), oil saturation index (S1 / TOC), and porosity. The parameters are categorized as follows: TOC ≥ 1.8% is Category 1, 0.9% ≤ TOC < 1.8% is Category 2, and TOC < 0.9% is Category 3; S1 ≥ 3 mg / g is Category 1, 2 mg / g ≤ S1 < 3 mg / g is Category 2, and S1 < 2 mg / g is Category 3; S1 / TOC ≥ 150 mg / g is Category 1, 100 mg / g ≤ S1 / TOC < 150 mg / g is Category 2, and S1 / TOC < 100 mg / g is Category 3. As one category, Classified into two categories, It is classified into three categories: organic carbon (TOC), free hydrocarbons (S1), oil saturation index (S1 / TOC), and porosity. The parameter assignment ranges for categories one, two, and three are the same: category one is assigned a range of 0.8-1.0, category two a range of 0.6-0.8, and category three a range of 0.5-0.6. The weights for the organic carbon (TOC) parameter are 0.3, the free hydrocarbon (S1) parameter is 0.3, the oil saturation index (S1 / TOC) parameter is 0.1, and porosity... With a parameter weight of 0.3, the comprehensive evaluation results of each sub-layer are obtained. The sub-layers are sorted according to their scores. V-8, V-6, and V-10 are classified as Class I, V-7, V-5, and V-9 as Class II, and V-3, V-1, V-4, and V-2 as Class III. Table 1 shows the classification evaluation table of different sub-layers in the V sub-section of the second section of a certain well. The parameter values are assigned as shown in Table 1.
[0068] Table 1
[0069]
[0070] V-8, V-6, and V-10 are classified as Class 1, V-7, V-5, and V-9 as Class 2, and V-3, V-1, V-4, and V-2 as Class 3.
[0071] Step 4: Determination of the composition of sub-section V of well HY1: Take 1-2 samples per meter from different sub-layers of sub-section V of well HY1 and perform whole-rock X-ray diffraction (XRD) analysis to analyze the mineral composition of the rock, including quartz, calcite, dolomite, ferrodolomite, plagioclase, potassium feldspar, siderite, pyrite, halite, anhydrite, gypsum, gypsum, anhydrous mirabilite, barite, calcium mirabilite, zeolite, analcime, and clay. Quartz, plagioclase, and potassium feldspar are considered as feldspar terrigenous clastic minerals, calcite, dolomite, and ferrodolomite are considered as carbonate minerals, and clay is considered as clay minerals. The sum of feldspar quartz, carbonate minerals, and clay minerals is less than or equal to 100. Feldspar quartz, carbonate minerals, and clay minerals are used as the three end-members of the mineral composition triangle plate.
[0072] Step 5, as follows Figure 3-13As shown, the scheme for subsection V of well HY1 is determined as follows: Based on the compositional characteristics of feldspar, quartz, carbonate minerals, and clay minerals in different sub-layers, their distribution patterns are represented by mineral triangle diagrams. The characteristics of the point distribution differ among different sub-layers. The distribution patterns of the first-class layers (sub-layers V-8, V-6, and V-10) are the same: II2: felsic shale containing dolomitic mudstone and IV1: felsic-mudstone mixed shale. The distribution patterns of the second-class layers (sub-layers V-7, V-5, and V-9) are the same: IV1: felsic-mudstone mixed shale and IV2: felsic-dolomitic mixed shale. Shale: The three types of layers (V-3, V-1, V-4, and V-2 sublayers) have the same distribution pattern. IV2: Felsic-dolitic mixed shale, the whole-rock mineral distribution locations differ in different sublayers. The triangular plot internal division scheme is selected, and within the same sublayer, at least 90% of the data points are in the same area. For example, in the V-1 sublayer test analysis, 16 out of 17 data points are in the same area, accounting for 94.1% of the data points. The same applies to the other sublayers. This indicates that the first, second, and third types of sublayers can be distinguished relatively well, and the target division scheme can be determined. (Wherein: I1 is tuff shale, I2 is felsic tuff shale, I3 is felsic argillaceous tuff shale, II1 is felsic shale, II2 is tuff argillaceous felsic shale, II3 is argillaceous tuff shale, III1 is shale, III2 is tuff tuff felsic shale, III3 is tuff tuff shale, IV1 is felsic-argillaceous mixed sedimentary shale, IV2 is felsic-tuff tuff mixed sedimentary shale, IV3 is argillaceous-tuff mixed sedimentary shale)
[0073] If the internal partitioning scheme of the triangle diagram is changed, for layers V-6, V-8, and V-10 evaluated as Class 1, such as... Figure 19 , Figure 21 and Figure 23 The test analysis data points are located in II1 and / or IV2 and / or IV3; for V-5, V-7, and V-9, which are evaluated as Class II layers, such as Figure 18 , Figure 20 and Figure 22 The test analysis data points are located in IV1 and / or IV2 and / or IV3; for V-1, V-2, V-3 and V-4, which are evaluated as three-level layers, such as Figure 14 , Figure 15 , Figure 16 and Figure 17 The test and analysis points are located at I1 and / or IV1 and / or IV2; this classification scheme cannot clearly and accurately show the relationship between the mineral distribution patterns and evaluation grades of different sub-layers, and it does not have good operability in subsequent scientific research and production processes.
[0074] This invention provides a method for determining the lithofacies classification scheme of terrestrial mixed sedimentary mudstone and shale, which is an effective method for classifying mudstone and shale lithofacies. Unlike conventional classification schemes, this method adopts the principle of evaluation before classification. Based on core observation and well logging curve identification, combined with sedimentary cycle characteristics, it conducts sub-layer classification, evaluates different sub-layers using key parameter assignment, analyzes the distribution patterns of mineral components in different sub-layers on mineral triangular charts, and determines the lithofacies classification scheme based on effectively distinguishing different evaluation levels.
[0075] This invention improves the accuracy and effectiveness of lithofacies classification schemes, avoiding the inability of traditional lithofacies classification methods to effectively distinguish favorable lithofacies. Accuracy is increased by 60 percentage points, reaching 98%. It avoids repetitive work, reducing the workload of 3 people for 15 days to 1 person for 5 days, increasing work efficiency by over 85%. Accurate and efficient lithofacies classification lays the foundation for further evaluation of favorable lithofacies and provides a basis for selecting "sweet spot" layers and target windows, effectively meeting the needs of practical applications. After application in a certain well, the single-well daily oil production reached 45 tons, achieving industrial oil flow.
[0076] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A method of determining a facies division scheme for a continental turbidite shale, characterized by, include: Step 1, Core observation: Based on the sedimentary principles of strata, observe in order from deep to shallow depth; including: based on the sedimentary principles of strata, observe in order from deep to shallow depth, observe the size of the sedimentary structure, the color variation pattern, the relative content of ash and cloud in carbonate minerals, the tectonic variation characteristics, and determine the sedimentary cycle variation characteristics. Step 2, Stratigraphic Division: Using the results of core observations and well logging curve characteristics, stratigraphic division is carried out. This includes: using the results of core observations and well logging curve characteristics, including resistivity series curves, gamma curves, and sonic curves, stratigraphic layers with consistent curve variation patterns are divided into the same set of sub-layers based on the relative height variation patterns of the curves. On this basis, combined with sedimentary cycle characteristics, mudstone and shale with the same sedimentary cycle characteristics on the plane are divided into the same set of stratigraphic layers. Each segment is divided into at least 5 sub-segments. Each sub-segment is divided into different sub-layers according to the thickness of the stratigraphic layer. Stratigraphic layers with a thickness of 90-130m are divided into at least 10-12 sub-layers, stratigraphic layers with a thickness of 70-90m are divided into at least 6-9 sub-layers, and stratigraphic layers with a thickness of 50-70m are divided into at least 3-5 sub-layers. Step 3, Sublayer Evaluation: Samples are taken from each sublayer for pyrolysis and irregular sample property analysis. Sublayer evaluation is conducted based on the analysis results. This includes: taking at least one sample per meter from each sublayer for pyrolysis and irregular sample property analysis to obtain key parameters such as total organic carbon (TOC), free hydrocarbons (S1), saturation index (S1 / TOC), and porosity (φ). Parameters are assigned values, categorized as follows: TOC ≥ 1.8% (Class 1), 0.9% ≤ TOC < 1.8% (Class 2), TOC < 0.9% (Class 3); S1 ≥ 3 mg / g (Class 1), 2 mg / g ≤ S1 < 3 mg / g (Class 2), S1 < 2 mg / g (Class 3); S1 / TOC ≥ 150 mg / g (Class 1), 100 mg / g ≤ S1 / TOC < 150 mg / g (Class 2). S1 / TOC < 100 mg / g is classified as Category 3, φ ≥ 6% as Category 1, 4% ≤ φ < 6% as Category 2, and φ < 4% as Category 3. The assigned value ranges for organic carbon (TOC), free hydrocarbons (S1), oil saturation index (S1 / TOC), and porosity (φ) are the same for all three categories: Category 1 (0.8-1.0), Category 2 (0.6-0.8), and Category 3 (0.5-0.6). The weights for organic carbon (TOC), free hydrocarbons (S1), oil saturation index (S1 / TOC), and porosity (φ) are 0.3 each. The comprehensive evaluation results for each sublayer are calculated, and layers are ranked according to their scores. The top 30% of the comprehensive evaluation scores are classified as Category 1, 30%–60% as Category 2, and the rest as Category 3. Step 4, Component Determination: For the core samples corresponding to each sublayer, perform X-ray diffraction whole-rock analysis to analyze the rock mineral composition; including: at least one sample per meter of the core sample corresponding to each sublayer, perform X-ray diffraction whole-rock analysis to analyze the rock mineral composition, including quartz, calcite, dolomite, ferrodolomite, plagioclase, potassium feldspar, siderite, pyrite, halite, anhydrite, gypsum, gypsum, anhydrous mirabilite, barite, calcium mirabilite, zeolite, analgesic, and clay; quartz, plagioclase, and potassium feldspar are considered feldspar terrigenous clastic minerals, calcite, dolomite, and ferrodolomite are considered carbonate minerals, and clay is considered clay minerals. The sum of the three minerals (feldspar, carbonate, and clay) is less than or equal to 100, and the three minerals (feldspar, carbonate, and clay) are used as the three end-members of the mineral composition triangle plate; Step 5, Scheme Determination: Based on the above analysis results, determine the target classification scheme; according to the compositional characteristics of feldspar, quartz, carbonate minerals, and clay minerals in different sub-layers, represent their distribution patterns in the form of mineral triangle maps. The distribution points of whole-rock mineral components in different sub-layers are different within the triangle map, and the evaluation results of different sub-layers have been clarified in Step 3; with these two conditions met, then select which triangle map to use. The internal classification scheme of each triangle map is different. Select a map that distinguishes between Class I, Class II, and Class III layers. Different points within the triangle map represent different mineral compositions. It is required that when projecting points for the same sub-layer, at least 90% of the sample points in all measured sample points are projected within the same area, and the projected areas for different sub-layers with similar evaluation results should be the same. This is considered a feasible classification scheme.