Volcanic rock lithofacies logging identification method and device
By constructing a well logging identification pattern chart for volcanic rock facies and using the correlation of multiple well logging data, the problems of high cost and low timeliness in volcanic rock facies identification were solved, and rapid and accurate identification of facies and subfacies was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- PETROCHINA CO LTD
- Filing Date
- 2024-11-12
- Publication Date
- 2026-05-12
AI Technical Summary
Existing volcanic rock facies identification methods are costly, inefficient, and inaccurate, making it difficult to achieve a complete description of the formation cores of each well profile through core drilling and cuttings logging.
A well logging identification pattern chart for volcanic rock facies was constructed using well logging curve data. By utilizing well logging data such as natural gamma, density, compensated neutron, sonic transit time, and resistivity, the correlation between volcanic rock facies and well logging data was established, and the facies and subfacies were quickly and accurately identified through the pattern chart.
It enables simple, rapid, and accurate identification of volcanic rock facies, reducing identification costs and improving identification efficiency.
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Figure CN122018032A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of oil and gas exploration and development technology, specifically to a method for identifying volcanic rock facies logging and a device for identifying volcanic rock facies logging. Background Technology
[0002] Volcanic rocks are small hills of various shapes formed by the accumulation of hot gases, liquids, and solids ejected from a volcano during an eruption. Because the erupted magma contains gaseous debris and solid magma, its temperature and pressure drop rapidly, causing chemical and physical changes, thus transforming the magma into volcanic rock. These rocks, formed from hot magma erupting from deep within the Earth through a volcano and cooling at the surface, are divided into volcanic rocks in a narrow and broad sense. In a narrow sense, volcanic rocks refer to volcanic lava, which is formed when low-viscosity, low-volatile magma (such as basic magma) overflows from the volcano in melt form. High-viscosity, acidic magma can also infiltrate to the surface during the later stages of a volcanic eruption due to the escape of large amounts of volatiles from the magma chamber. In a broad sense, volcanic rocks, in addition to lava, also include pyroclastic rocks. Pyroclastic rocks are mainly formed when high-viscosity, high-volatile acidic rocks are erupted to the surface through explosive eruptions, often mixed with a certain amount of normal sediments or lava material. Volcanic rock facies mainly refers to the environment in which volcanic activity products are produced and their facies characteristics. Volcanic rock facies analysis is a very important issue in studying sedimentary environments, finding hidden oil reservoirs, and evaluating oil and gas.
[0003] Currently, the main method for identifying volcanic rock facies is to analyze drilling core and cuttings logging data to determine the facies of volcanic rocks. This method is not only costly and inefficient, but also difficult to achieve a complete description of the strata cores of each well profile due to the limited number of core wells, even fewer continuous cores, and inaccurate cuttings logging. Summary of the Invention
[0004] In view of this, the present invention proposes a method and device for identifying volcanic rock facies through well logging, which aims to utilize the advantages of continuous well logging curves, abundant information and the ability to reflect the lithology of volcanic rocks to establish a well logging identification pattern for identifying volcanic rock facies.
[0005] To achieve the above objectives, the present invention adopts the following technical solution: According to a first aspect of the present invention, a method for identifying volcanic rock facies through well logging is provided, comprising the following steps: Acquire multiple sets of volcanic rock sample data within the target area, including well logging data of the volcanic rock samples and the corresponding lithofacies types; Based on the acquired volcanic rock sample data, a well logging pattern identification map of volcanic rock facies within the target area was constructed; Based on the well logging identification pattern of volcanic rock facies within the target area, facies identification is performed on volcanic rock samples within the target area.
[0006] According to one embodiment of the present invention, the logging data of the volcanic rock sample includes natural gamma, density, compensated neutrons, sonic transit time, and resistivity.
[0007] According to one embodiment of the present invention, acquiring multiple sets of volcanic rock sample data within a target area includes: Analyze the lithofacies types of volcanic rocks within the target area; For each lithofacies type, multiple sets of volcanic rock sample data were obtained.
[0008] According to one embodiment of the present invention, the analysis of the lithofacies type of volcanic rocks in the target area includes: starting from the actual geological data of the target area, and based on the geological and petrological characteristics of the target area, conducting a lithofacies type analysis of the volcanic rocks in the target area.
[0009] According to one embodiment of the present invention, the geological features of the target area include the geological tectonic background, volcanic activity history and related sedimentary environment of the target area, and the petrological features include rock composition, structure and rock type. According to one embodiment of the present invention, based on the acquired multiple sets of volcanic rock sample data, a well logging identification pattern map of volcanic rock facies within a target area is constructed, including: Preprocessing was performed on the acquired data of multiple sets of volcanic rock samples of various lithofacies types; Based on preprocessed data from multiple volcanic rock samples, a well logging identification pattern chart of volcanic rock facies is constructed to characterize the correlation between various volcanic rock facies types and well logging data within the target area.
[0010] According to one embodiment of the present invention, preprocessing is performed on multiple sets of volcanic rock sample data of various lithofacies types, including: The acquired data of multiple sets of volcanic rock samples of various lithofacies types were sorted according to lithofacies type; The sorted volcanic rock sample data were sequentially numbered to obtain preprocessed volcanic rock sample data.
[0011] According to one embodiment of the present invention, based on preprocessed multi-set volcanic rock sample data, a volcanic rock facies logging identification pattern chart characterizing the correlation between various volcanic rock facies types and logging data within a target area is constructed, including: Based on preprocessed data from multiple volcanic rock samples, a volcanic rock lithofacies logging identification pattern is constructed. In the volcanic rock lithofacies logging identification pattern, the radius coordinate represents the size of the logging data and the angular coordinate represents the sample data number. Dividing lines are drawn between two adjacent facies types in the volcanic rock facies logging identification flower pattern to divide the volcanic rock facies logging identification flower pattern into multiple fan-shaped petals, each fan-shaped petal representing a facies type, thereby forming the volcanic rock facies logging identification pattern diagram.
[0012] According to one embodiment of the present invention, based on a well logging identification pattern chart of volcanic rock facies within a target area, lithofacies identification is performed on volcanic rock samples within the target area, including: Obtain well logging data from volcanic rock samples within the target area; The well logging data of the acquired volcanic rock sample is projected onto the volcanic rock lithofacies well logging identification pattern chart, and the lithofacies of the volcanic rock sample is determined by observing which fan-shaped petal the well logging data falls into.
[0013] According to one embodiment of the present invention, acquiring multiple sets of volcanic rock sample data within a target area includes: For each lithofacies type, analyze its subfacies type; For each subfacies type, multiple sets of volcanic rock sample data were obtained.
[0014] According to one embodiment of the present invention, based on the acquired multiple sets of volcanic rock sample data, a well logging identification pattern map of volcanic rock facies within a target area is constructed, including: Preprocessing was performed on the acquired data of multiple sets of volcanic rock samples of various subfacies types; Based on preprocessed data from multiple volcanic rock samples, a well logging identification pattern chart of volcanic rock subfacies is constructed to characterize the correlation between various volcanic rock subfacies types and well logging data within the target area.
[0015] According to one embodiment of the present invention, preprocessing is performed on multiple sets of volcanic rock sample data of various subfacies types, including: The acquired data of multiple sets of volcanic rock samples of various subfacies types were sorted according to lithofacies type; The data of multiple volcanic rock samples for each lithofacies type were sorted according to subfacies type; The sorted volcanic rock sample data were sequentially numbered to obtain preprocessed volcanic rock sample data.
[0016] According to one embodiment of the present invention, based on preprocessed multi-set volcanic rock sample data, a volcanic rock subfacies logging identification pattern chart characterizing the correlation between various volcanic rock subfacies types and logging data within a target area is constructed, including: Based on preprocessed data from multiple volcanic rock samples, a subfacies logging identification pattern for volcanic rocks is constructed. In this pattern, the radius coordinate represents the size of the logging data, and the angular coordinate represents the sample data number. Dividing lines are drawn between two adjacent lithofacies types in the volcanic rock subfacies logging identification flower diagram to divide the volcanic rock lithofacies logging identification flower diagram into multiple fan-shaped petals, each fan-shaped petal representing a lithofacies type. Dividing lines are drawn between two adjacent subfacies types in each lithofacies type to divide each fan-shaped petal into sub-fan-shaped petals, each sub-fan-shaped petal representing a subfacies type, thereby forming the volcanic rock subfacies logging identification pattern diagram.
[0017] According to one embodiment of the present invention, based on a well logging identification pattern chart of volcanic rock facies within a target area, lithofacies identification is performed on volcanic rock samples within the target area, including: Obtain well logging data from volcanic rock samples within the target area; The well logging data of the acquired volcanic rock sample is projected onto the volcanic rock subfacies well logging identification pattern chart. The lithofacies and / or subfacies of the volcanic rock sample are determined by observing which fan-shaped petal and / or which sub-fan-shaped petal the well logging data falls into.
[0018] According to one embodiment of the present invention, the lithofacies types of volcanic rocks include eruptive facies, effusive facies, intrusive facies, and volcanic sedimentary facies.
[0019] According to one embodiment of the present invention, the lithofacies types of volcanic rocks include explosive facies, effusive facies, intrusive facies, and volcanic sedimentary facies. The explosive facies include pyroclastic flow subfacies, the effusive facies include composite lava flow subfacies, vitreous clastic rock subfacies, and platy lava flow subfacies, the intrusive facies include outer zone subfacies, middle zone subfacies, and inner zone subfacies, and the volcanic sedimentary facies include volcanic sedimentary subfacies containing outer clastic rocks and re-transported pyroclastic sedimentary subfacies.
[0020] According to a second aspect of the present invention, a volcanic rock facies logging identification device is provided, comprising: The sample data acquisition module is used to acquire multiple sets of volcanic rock sample data within the target area. The volcanic rock sample data includes well logging data of the volcanic rock samples and the corresponding lithofacies types. The chart construction module is used to construct a chart of volcanic rock lithofacies well logging identification patterns within the target area based on multiple sets of acquired volcanic rock sample data; The lithofacies identification module is used to identify the lithofacies of volcanic rock samples within the target area based on the lithofacies logging identification pattern chart of volcanic rocks within the target area.
[0021] According to one embodiment of the present invention, the map construction module includes a lithofacies identification map construction submodule, which is used to construct a volcanic rock lithofacies logging identification pattern map that characterizes the association between various volcanic rock lithofacies types and logging data within a target area based on multiple sets of acquired volcanic rock sample data.
[0022] According to one embodiment of the present invention, the chart construction module includes a subfacies identification chart construction submodule, which is used to construct a volcanic subfacies logging identification pattern chart based on the acquired multiple sets of volcanic rock sample data, which characterizes the correlation between various volcanic subfacies types and logging data within the target area.
[0023] According to one embodiment of the present invention, the logging data of the volcanic rock sample includes natural gamma, density, compensated neutrons, sonic transit time, and resistivity.
[0024] By adopting the above technical solution, the present invention has at least the following beneficial technical effects: The volcanic rock facies logging identification method and apparatus provided by the present invention first constructs a volcanic rock facies logging identification pattern map based on multiple sets of volcanic rock sample data in the target area. Then, based on the constructed volcanic rock facies logging identification pattern map, the facies of volcanic rock samples in the target area can be identified. The constructed volcanic rock facies logging identification pattern map can be used to identify the volcanic rock facies simply, quickly and accurately. Attached Figure Description
[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these drawings without creative effort.
[0026] Figure 1 A flowchart of the volcanic rock facies logging identification method provided by the present invention; Figure 2 A block diagram of the volcanic rock facies logging identification device provided by the present invention; Figure 3 This is a longitudinal distribution map of volcanic rocks; Figure 4 A diagram for classifying and naming volcanic rocks using the silica-alkali method; Figure 5 A diagram showing the variation of SiO2 and K2O in volcanic eruption rocks; Figure 6 This is a schematic diagram of the volcanic rock lithofacies well logging identification pattern constructed in the embodiment; Figure 7 This is a schematic diagram of the volcanic rock subfacies logging identification pattern constructed in the embodiment; Figure 8 The above is a diagram showing the distribution of volcanic eruptive facies in the Huangshatuo oilfield, as illustrated in the example. Figure 9 The above is a distribution map of the intrusive facies of volcanic rocks in the Huangshatuo oilfield, as shown in the example. Figure 10 The above is a diagram showing the distribution of volcanic rock overflow facies in the Huangshatuo oilfield, as illustrated in the example. Figure 11 The data shown is from volcanic rock samples from Well Xiao 22 in the Huangshatuo Oilfield, as presented in this example. Detailed Implementation
[0027] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to specific examples and the accompanying drawings.
[0028] It should be noted that all uses of "first" and "second" in the embodiments of the present invention are for the purpose of distinguishing two entities or parameters with the same name but different names. It is clear that "first" and "second" are only for the convenience of expression and should not be construed as limiting the embodiments of the present invention. Subsequent embodiments will not explain this in detail.
[0029] According to a first aspect of the present invention, a method for identifying volcanic rock facies logging is provided, such as... Figure 1 As shown, the volcanic rock facies logging identification method includes the following steps: S1: Acquire multiple sets of volcanic rock sample data within the target area. The volcanic rock sample data includes well logging data of the volcanic rock samples and the corresponding lithofacies types. S2: Based on the acquired data from multiple sets of volcanic rock samples, construct a well logging pattern map for identifying volcanic rock facies within the target area; S3: Based on the well logging identification pattern of volcanic rock facies within the target area, perform lithofacies identification on volcanic rock samples within the target area.
[0030] The volcanic rock facies logging identification method provided by this invention first constructs a volcanic rock facies logging identification pattern map based on multiple sets of volcanic rock sample data in the target area. Then, based on the constructed volcanic rock facies logging identification pattern map, the facies of volcanic rock samples in the target area can be identified. The constructed volcanic rock facies logging identification pattern map can easily, quickly and accurately identify the volcanic rock facies.
[0031] In some embodiments, logging data for volcanic rock samples includes natural gamma ray, density, compensated neutron, sonic transit time, and resistivity. To accurately identify volcanic rock facies, logging parameters reflecting key information such as lithology, pore structure, and fluid properties are selected to construct a volcanic rock facies logging identification model chart, based on the characteristics of the volcanic rock facies and research objectives. Among the various logging parameters, natural gamma ray (GR) reflects the radioactivity intensity of the rock and is related to the mineral composition; density (DEN) directly measures the rock's density and is related to its mineral composition and porosity; compensated neutron (CNL) indirectly reflects the rock's porosity by measuring the capture rate of thermal neutrons; sonic transit time (AC) reflects the rock's density and porosity; the faster the sound waves propagate in the rock, the denser the rock; and resistivity (Rt) reflects the rock's electrical conductivity and is affected by factors such as the rock's pore structure and fluid properties.
[0032] In some embodiments, acquiring multiple sets of volcanic rock sample data within a target area includes: analyzing the lithofacies types of volcanic rocks within the target area; and acquiring multiple sets of volcanic rock sample data for each lithofacies type. Acquiring multiple sets of volcanic rock sample data for each lithofacies type helps improve the accuracy of lithofacies identification.
[0033] In some embodiments, analyzing the lithofacies type of volcanic rocks within a target area includes: starting from the actual geological data of the target area, and based on the geological and petrological characteristics of the target area, conducting a lithofacies type analysis of the volcanic rocks within the target area. The geological characteristics of the target area include the geological tectonic background, volcanic activity history, and related sedimentary environments; the petrological characteristics include rock composition, structure, and rock type. Rock composition includes the mineral and chemical composition of volcanic rocks, especially the main mineral assemblage and elemental content; structure includes the grain size, shape, arrangement, and features such as vesicles and amygdalae, which reflect the formation environment and processes of volcanic rocks; rock types include basalt, andesite, and rhyolite, etc. In some embodiments, the lithofacies types of volcanic rocks include eruptive facies, effusive facies, intrusive facies, and volcanic sedimentary facies.
[0034] In some embodiments, based on the acquired multiple sets of volcanic rock sample data, a well logging identification pattern chart of volcanic rock facies within a target area is constructed, including: preprocessing the acquired multiple sets of volcanic rock sample data of various facies types; and based on the preprocessed multiple sets of volcanic rock sample data, constructing a well logging identification pattern chart of volcanic rock facies representing the correlation between each volcanic rock facies type and well logging data within the target area.
[0035] In some embodiments, preprocessing of multiple sets of volcanic rock sample data of various lithofacies types includes: sorting the multiple sets of volcanic rock sample data of various lithofacies types according to lithofacies type; and sequentially numbering the sorted multiple sets of volcanic rock sample data to obtain preprocessed multiple sets of volcanic rock sample data.
[0036] In some embodiments, based on preprocessed multiple sets of volcanic rock sample data, a volcanic rock facies logging identification pattern diagram is constructed to characterize the association between various volcanic rock facies types and logging data within the target area. This includes: constructing a volcanic rock facies logging identification flower diagram based on preprocessed multiple sets of volcanic rock sample data, wherein the radius coordinate in the volcanic rock facies logging identification flower diagram represents the logging data size, and the angular coordinate represents the sample data number; drawing dividing lines between two adjacent rock facies types in the volcanic rock facies logging identification flower diagram to divide the volcanic rock facies logging identification flower diagram into multiple fan-shaped petals, each fan-shaped petal representing a rock facies type, thereby forming a volcanic rock facies logging identification pattern diagram.
[0037] In some embodiments, based on a well logging identification pattern chart of volcanic rock facies within a target area, lithofacies identification of volcanic rock samples within the target area is performed, including: acquiring well logging data of volcanic rock samples within the target area; projecting the acquired well logging data of volcanic rock samples onto a well logging identification pattern chart of volcanic rock facies, and determining the lithofacies of volcanic rock samples by observing which fan-shaped petal the well logging data falls into.
[0038] In some embodiments, acquiring multiple sets of volcanic rock sample data within a target area further includes: analyzing the subfacies type for each lithofacies type; and acquiring multiple sets of volcanic rock sample data for each subfacies type.
[0039] In some embodiments, the eruptive facies includes a pyroclastic flow subfacies, the overflow facies includes a composite lava flow subfacies, a vitreous clastic rock subfacies, and a platy lava flow subfacies, the intrusive facies includes an outer zone subfacies, a middle zone subfacies, and an inner zone subfacies, and the volcanic sedimentary facies includes an outer clastic rock volcanic sedimentary subfacies and a retransported pyroclastic sedimentary subfacies.
[0040] In some embodiments, based on the acquired multiple sets of volcanic rock sample data, a well logging identification pattern chart of volcanic rock facies within a target area is constructed, including: preprocessing the acquired multiple sets of volcanic rock sample data of various subfacies types; and based on the preprocessed multiple sets of volcanic rock sample data, constructing a well logging identification pattern chart of volcanic rock subfacies that characterizes the correlation between each volcanic rock subfacies type and well logging data within the target area.
[0041] In some embodiments, preprocessing of the acquired volcanic rock sample data of multiple subfacies types includes: sorting the acquired volcanic rock sample data of multiple subfacies types according to lithofacies type; sorting the volcanic rock sample data of each lithofacies type according to subfacies type; and sequentially numbering the sorted volcanic rock sample data to obtain preprocessed volcanic rock sample data.
[0042] In some embodiments, based on preprocessed multiple sets of volcanic rock sample data, a volcanic rock subfacies logging identification pattern diagram is constructed to characterize the association between various volcanic rock subfacies types and logging data within a target area. This includes: constructing a volcanic rock subfacies logging identification flower diagram based on preprocessed multiple sets of volcanic rock sample data, where the radius coordinate represents the logging data size and the angular coordinate represents the sample data number; drawing dividing lines between two adjacent rock facies types in the volcanic rock subfacies logging identification flower diagram to divide the diagram into multiple fan-shaped petals, each representing a rock facies type; drawing dividing lines between two adjacent subfacies types within each rock facies type to divide each fan-shaped petal into sub-fan-shaped petals, each representing a subfacies type, thereby forming the volcanic rock subfacies logging identification pattern diagram.
[0043] In some embodiments, based on a well logging identification pattern chart of volcanic rock facies within a target area, lithofacies identification of volcanic rock samples within the target area is performed, including: acquiring well logging data of volcanic rock samples within the target area; projecting the acquired well logging data of volcanic rock samples onto a well logging identification pattern chart of volcanic rock subfacies, and determining the lithofacies and / or subfacies of volcanic rock samples by observing which fan-shaped petal and / or which sub-fan-shaped petal the well logging data falls into.
[0044] According to a second aspect of the present invention, a volcanic rock facies logging identification device is provided, which is used to implement the method described in the first aspect of the present invention, such as... Figure 2 As shown, the volcanic rock facies logging identification device includes: a sample data acquisition module 10, used to acquire multiple sets of volcanic rock sample data within the target area. The volcanic rock sample data includes logging data of the volcanic rock samples and the corresponding facies types. The logging data of the volcanic rock samples includes natural gamma, density, compensated neutron, sonic transit time, and resistivity; a map construction module 20, used to construct a volcanic rock facies logging identification pattern map within the target area based on the acquired multiple sets of volcanic rock sample data; and a facies identification module 30, used to identify the facies of volcanic rock samples within the target area based on the volcanic rock facies logging identification pattern map within the target area.
[0045] In some embodiments, the map construction module 20 includes a lithofacies identification map construction submodule 201, which is used to construct a volcanic rock lithofacies logging identification pattern map that characterizes the association between various volcanic rock lithofacies types and logging data in the target area based on the acquired multiple sets of volcanic rock sample data.
[0046] In some embodiments, the chart construction module 20 includes a subfacies identification chart construction submodule 202, which is used to construct a volcanic subfacies logging identification pattern chart that characterizes the association between various volcanic subfacies types and logging data within a target area based on the acquired multiple sets of volcanic rock sample data.
[0047] The following specific embodiments further illustrate the solution of the present invention: Example This section uses the identification of volcanic rock facies in the Huangshatuo oilfield in the eastern depression of Liaohe River as an example to provide a detailed description of the volcanic rock facies logging identification method provided by this invention.
[0048] Step 1: Based on the actual geological data of the Huangshatuo oilfield, and according to the geological characteristics of the block and the petrological characteristics of the volcanic rocks, conduct an analysis of the volcanic rock facies types: The Huangshatuo Oilfield is located approximately 3 kilometers northeast of Huangshatuo Town, Tai'an County, Liaoning Province. Structurally, it lies on the western side of the Tiejianlu Structure in the central section of the eastern Liaohe Basin, bordering the Oulituozi Oilfield to the south. The Huangshatuo Structure, situated in the central part of the eastern depression, is the downthrown block of the Jiexi Fault. It is a large, nose-shaped fault structure attached to the Jiexi Fault, with a westward-dipping axial direction. This structure is controlled by a northeast-trending main fault and dissected by later-developed near-east-west and northwest-trending secondary faults, dividing it into multiple fault blocks and further complicating the nose-shaped structure. The Shahekou Formation (Sha-3 Member), the center of Eocene volcanic eruptions in the eastern Liaohe Basin, erupted with abundant volcanic rocks. Drilling indicates that the Sha-3 Member contains well-developed volcanic reservoirs, primarily composed of trachyte, basalt, and transitional rocks, followed by tuff. The Huangshatuo Oilfield has already established oil and gas production blocks within the trachyte reservoirs.
[0049] Based on the vertical variation analysis of volcanic rock lithology revealed by drilling, the vertical variation of volcanic rock lithology in the Sha-3 Member of the Huangshatuo Oilfield can be roughly divided into three phases ( Figure 3 These groups correspond to the early middle, middle and late middle, and early upper phases of the Shahejie Formation (Shahejie Formation 3), with the top and bottom primarily consisting of basalt and basaltic tuff. The reservoirs in this area are mainly Shahejie volcanic rocks, with Phase II volcanic rocks forming the primary reservoir for volcanic oil and gas. The main oil-bearing part is the lower Shahejie Formation (Shahejie Formation 3), and the oil-bearing lithology is trachyte. The characteristics of each group are as follows: Phase I volcanic rocks (early stage of Sha-3): The lithology is mainly basalt and tuff formed by extrusive facies, with thin single-layer thickness, and interbedded with clastic sedimentary rocks.
[0050] Phase II volcanic rocks (late stage of Sha-3): The lithology is mainly trachyte formed by exudative facies. The eruption centers are located in the Oulituozi, Huangshatuo, and Rehetai areas, with the Huangshatuo area experiencing the most intense eruptions. The lithology is dominated by trachyte, and the volcanic rocks are continuous and thick, forming a banded pattern extending northeastward along the western boundary fault. The Huangshatuo oilfield's volcanic oil and gas reservoirs are mainly distributed in Group II volcanic rocks. Phase II volcanic rocks can be further subdivided into three phases: II-1, II-2, and II-3.
[0051] Phase III volcanic rocks (early stage of Sha-3): The lithology is mainly extrusive basalt. After diagenesis, it has undergone deep alteration, with many layers, thin thickness, and wide distribution. It often occurs interbedded with mudstone strata and overlies Phase II trachyte, serving as the caprock for Phase II volcanic oil reservoirs.
[0052] Volcanic rocks are complex in composition and diverse in type, with some exhibiting significant secondary alterations. Different types of volcanic rocks show great differences in reservoir characteristics, lithofacies, and hydrocarbon accumulation. The study of volcanic rock petrological characteristics is fundamental to volcanic rock research. A comprehensive study of volcanic rock lithology can be conducted using various methods, including chemical composition classification and mineral composition classification, while fully utilizing analytical and logging data. The main chemical components of volcanic rocks are SiO2, Al2O3, Fe2O3, FeO, MgO, CaO, Na2O, K2O, and TiO2, with SiO2 being the most abundant oxide. Based on SiO2 content, igneous rocks can be classified into ultrabasic, basic, intermediate, acidic, and alkaline rocks (belonging to the intermediate rock category, with SiO2 content similar to intermediate rocks, but K2O content higher than other rock types).
[0053] Statistical analysis of petrological rocks in the Huangshatuo oilfield volcanic rocks Figure 4 Basalt has a SiO2 content of 30%-53% and a K2O content of 0.5%-3%, belonging to the basic rock type; trachyte has a SiO2 content of 53%-60%, belonging to the intermediate rock type, but its K2O content is 4.0%-7.5%, and its Na2O+K2O content is above 9%. Due to the high K2O content, this type of rock has high radioactivity; and trachyandesite has a SiO2 content of 53%-60%, K2O is 3%-4%, and its K2O+Na2O content is above 9%, belonging to the intermediate rock type.
[0054] Based on the relationship between K2O content and SiO2 content in the petrological analysis of volcanic rocks in the Huangshatuo oilfield (Figure 1), Figure 5 As can be seen from the data, there are significant differences in K2O content among the three types of lithology: trachyte, andesite, and basalt. Specifically, from basic rocks to intermediate rocks to acidic rocks, the K2O content increases with the increase of SiO2 content, showing a positive correlation. Therefore, based on chemical composition, these three types of lithology can be distinguished relatively accurately.
[0055] Basaltic rocks: The basalts in this area are grayish-black, dark black, and blackish-green, turning grayish-green after weathering and purplish-red when strongly oxidized. The main mineral components are plagioclase and pyroxene, with olivine as a minor mineral. Alteration minerals include chlorite, analcime, and calcite. They are massive, dense, hard, and have high density, with whole-rock analysis showing SiO2 content ranging from 44% to 53%—basic lava. Thin-section analysis reveals a porphyritic texture, amygdaloidal structure, and a matrix with interstitial structure. Overall, the alteration is deep; plagioclase is easily sericitized and kaolinized by hydrothermal alteration, while pyroxene easily forms chlorite. Whole-rock X-ray diffraction analysis shows that the clay content can reach over 20%. Due to the predominantly altered mudstone and analcime filling, this type of rock has poor reservoir properties. Current oil testing and production have shown generally poor oil content, and it is not considered a primary reservoir rock for research.
[0056] Trachyte: This refers to rocks whose main component is trachyte, characterized by well-developed phenocrysts and a "rough" texture. The overall color is light gray, gray, dark gray, or grayish-green. The mineral composition is mainly alkali feldspar (primarily orthoclase), with plagioclase, pyroxene, and other dark minerals accounting for less than 5%. Based on thin section and scanning electron microscopy analysis of this area, the trachyte exhibits a porphyritic texture and massive structure. The matrix also has a rough texture, with phenocrysts accounting for 15%, ranging in size from 0.2 to 2.2 mm. The matrix grain size is 0.01 to 0.2 mm. Phenocrysts: Alkali feldspar is euhedral to subhedral, short columnar, moderately altered, accounting for 13%; plagioclase is euhedral, long tabular, with well-developed twinning, moderately altered, accounting for 1%; pyroxene shows a darkened rim, accounting for 1%. Matrix: Mainly microcrystalline alkali feldspar, with a small amount of microcrystalline plagioclase, tabular, long tabular, oriented, accounting for 80%, and glassy-cryptocrystalline content of 5%. In the eastern depression, the trachyte rocks underwent significant hydrothermal alteration, resulting in intense zeolization. The resulting analcime filled fractures and dissolution pores within the trachyte. Simultaneously, feldspar, through weathering or hydrothermal alteration, formed clay minerals such as kaolinite, deteriorating the reservoir's storage capacity. The main trachyte rock types include trachyte breccia, brecciated trachyte, and other types of trachyte. These rocks exhibit less alteration than basalts, and the reservoirs formed from them generally have better storage capacity, making them the primary reservoir rocks in this area.
[0057] Tuffaceous rocks: These are volcanic clastic rocks composed of volcanic ash with a grain size of less than 2 mm. They contain basaltic and trachytic particles, and are mostly grayish-green or black in color. They exhibit a vitreous tuffaceous texture with few crystal fragments. The rock is composed of volcanic glass and volcanic ash. Whole-rock analysis indicates that the tuff contains more than 20% clay and a relatively high amount of fluorite, exceeding 25%.
[0058] Volcanic lithofacies is the sum of studies on volcanic activity patterns, formation environments, and lithological characteristics. The lithofacies of the Huangshatuo oilfield can be divided into four facies and nine subfacies: eruptive facies, overflow facies, intrusive facies, and volcanic sedimentary facies. Figure 8 , Figure 9 , Figure 10 Distribution maps of the eruptive, intrusive, and overflow facies of volcanic rocks in the Huangshatuo oilfield are presented respectively.
[0059] Explosive facies: This facies can form at different stages of volcanic activity, but is most developed in the early stages and during the peak of eruption. Rock composition typically involves magma with low temperatures, high volatile content, and high viscosity; intermediate-acidic and alkaline magma are more conducive to eruption. Rocks include pyroclastic rocks, submerged pyroclastic rocks, welded breccia, and agglomerates. The closer to the crater, the coarser the rock grain; the farther from the crater, the finer the rock grain. Explosive facies includes the pyroclastic flow subfacies.
[0060] The pyroclastic flow subfacies is a type of rock formed by the rapid flow, migration, and localization of hot, high-density fluids rich in volcanic debris and gases. The eruptive facies of Huangshatuo is predominantly pyroclastic flow subfacies.
[0061] Volcanic sedimentary facies: Formed at different stages of volcanic activity, these facies consist of volcanic ash, dust, and volcanic rock breccia transported over a certain distance into normal sediments, often forming at the distal ends of volcanic bodies. The lithology is mainly tuffaceous breccia, tuffaceous shale, and tuffaceous sandstone, with some tuffaceous mudstone also present. The gravels are complex in composition and poorly sorted, mostly angular and sub-angular. The Huangshatuo trachyte can be divided into volcanic sediments containing exoclasts and re-transported volcanic clastic sediments.
[0062] Volcanic sedimentary subfacies containing exoclastic rocks are rocks formed by the short-distance transport or deposition of various clastic materials produced by volcanic eruptions. Volcanic clastic rocks are a transitional type of rocks between extrusive and sedimentary rocks.
[0063] Re-transported volcanic clastic sedimentary facies refers to the process where most of the weathering products of the parent rock are transported away, except for a few remnants that remain in situ and form the weathering crust. Due to the different properties of the weathering products, the modes of transportation and deposition also differ. One type involves the transportation and deposition of clastic materials, known as physical transportation and deposition; the other involves the transportation and deposition of dissolved materials, known as chemical and biochemical transportation and deposition. The main forces transporting sediments are water, gravity flows, wind, ice, and organisms.
[0064] Intrusive facies: Geological bodies formed by the slow extrusion of viscous acidic, intermediate-acidic, and alkaline magma from the upper part of a volcanic conduit or fissures beside the crater, followed by deposition and cooling. They commonly form in terrestrial volcanoes and are also found in shallow marine volcanic deposits. Common forms include lava domes, lava needles, lava stelae, and lava ridges, varying in size, with steep dips, and a typical lava crust. Their planar shape is circular or elliptical, and some transitional to extrusive lava. When the magma viscosity is high and the gas supersaturation is low, the magma is not an extrusion but an intrusive facies. The intrusive facies of the Huangshatuo trachyte can generally be divided into three subfacies: The outer subfacies consists of porous trachyte with well-developed vesicles, a gas content of 10% to 25%, and well-developed fractures. Intermediate zone subfacies: composed of trachyte porphyry, with fewer vesicles, greater thickness, and underdeveloped fractures; Inner zone subfacies: The lithology is mainly clastic trachyte with well-developed fractures.
[0065] Overflow facies: This facies can form during various stages of volcanic activity, but it mainly appears during the intercritical period after a strong volcanic eruption. It consists of lava that overflows from the crater, ranging in composition from ultrabasic to acidic, but predominantly basic. It represents the lava that overflows and vents from volcanic eruptions. Lava with lower viscosity flows easily and often overflows after a strong eruption, forming lava flows or lava beds. The most common overflow facies rocks are basalt, followed by andesite. Overflow facies are relatively common in volcanic rocks in the Liaohe Basin. The Lower Tertiary Fangshanpao Formation and the Upper Basalt of the Shale Seminary are both overflow facies, exhibiting distinct vesicular and amygdaloidal structures. Basalt mostly erupts in an overflow manner, with eruption patterns primarily Hawaiian and Strongbolley. The overflow facies can be further divided into subfacies such as composite lava flows, vitreous clastic rocks, and platy lava flows.
[0066] Composite lava flows are lava flows composed of two different types of rock. The most common type is basaltic composite lava flows, which can be divided into basalt rich in phenocrysts and basalt without or with few phenocrysts. These composite lava flows form when magma rising from deep within the Earth's surface briefly lingers in volcanic conduits before reaching the surface. Phenocryst minerals crystallizing from this magma sink due to their higher density, while the upper magma contains no phenocrysts. When the magma flows to the surface through the volcanic conduit, the phenocryst-free magma flows out first, followed by the polycrystalline magma, which covers the phenocryst-free rock. The phenocryst-free magma cools faster upon contact with the surface, and its flow velocity decreases due to friction with the ground, while the polycrystalline magma flows faster and farther because it is on top of the surface.
[0067] Vitreous clastic rocks are formed when hot magma comes into contact with water during its flow, subsequently cooling and contracting, fracturing. Compared to lava, they typically have a volcanic clastic structure and a lower degree of crystallinity. The matrix is glassy or semi-crystalline, and a glassy outer shell is visible on the surface of the clastic rocks. Cementation is mainly hydrochemical. Based on composition, they can be classified into basaltic, rhyolitic, and andesitic rocks, among others. They can occupy a large volume in sedimentary basins with a volcanic rift background. Vitreous clastic rocks not only serve as an important indicator of underwater eruptions or emplacements of terrestrial volcanic rocks but can also exist as volcanic oil and gas reservoirs.
[0068] Slab lava flows refer to lava flows with numerous slab-like fragments on their surface. They result from the fracturing of a relatively smooth lava crust and belong to the category of crusted lava. The fracturing of the crust is often caused by an increase in the flow velocity of the lava still flowing beneath it. This fracturing of the crust causes the gas in the underlying lava to dissipate, making it more viscous and gradually transforming it into lava with characteristics of slag-like masses. However, these surface slab-like fragments still retain the properties of crusted lava.
[0069] Step 2: Obtain multiple sets of sample data for various lithofacies types from multiple wells in the Huangshatuo oilfield. Each set of sample data includes the well logging data of the sample and the corresponding lithofacies type. The well logging data includes natural gamma, density, compensated neutron, sonic transit time and resistivity. Figure 11 Data on volcanic rock samples from Well Xiao 22 in the Huangshatuo Oilfield are presented.
[0070] This study established a lithofacies and subfacies logging identification model chart using characteristic points from five logging curves (natural gamma, density, compensated neutron, sonic transit time, and resistivity) measured in multiple wells in the Huangshatuo oilfield. Figure 4 , Figure 5 ), to identify the lithofacies of this work area.
[0071] Step 3: Based on the acquired sample data, establish a lithofacies logging identification model chart adapted to the Huangshatuo oilfield: The logging response characteristics of volcanic rocks are mainly a comprehensive reflection of the rock's mineral composition, pore structure, fracture and pore development, and oil content. Each lithology has its inherent characteristic values, such as the level of radioactive elements and density. Therefore, the difference in the mineral composition of volcanic rocks (i.e., the difference in lithology) is an intrinsic factor in the logging response. Accurately identifying the lithofacies of volcanic rocks using logging data is an effective approach.
[0072] In the burst phase, the natural gamma is high, the resistivity characteristics are thin-layered, serrated, and of medium resistance; the acoustic transit time is medium-high, the density is medium-low, and the compensated neutrons are medium-low. (Floral diagram) Figure 6 The upper right petal in the image reflects the characteristics of this phase.
[0073] Logging response of pyroclastic flow subfacies: High natural gamma ray; thin, toothed resistivity characteristics; medium resistivity; medium-high sonic transit time; medium-low density; medium-low compensated neutron values. (Floral diagram) Figure 7 The petal number 1 on the upper right side of the image reflects the characteristics of this subphase.
[0074] The characteristics of volcanic sedimentary facies on well logging curves are as follows: natural gamma varies drastically with mineral composition, generally showing a moderate value; resistivity varies drastically, generally showing a low to medium value; sonic transit time is medium to high; density is generally high; and compensated neutrons are medium to high. (Floral diagram) Figure 6 The right petal in the image reflects the characteristics of this phase.
[0075] The characteristics of the volcanic sedimentary subfacies containing clastic rocks on well logging curves are: moderate natural gamma, low to medium resistivity, high sonic transit time, medium to high density, and high compensated neutron concentration. (Floral diagram) Figure 7 Petal 2 in the image reflects the characteristics of this subphase.
[0076] The characteristics of the re-transported volcanic clastic sedimentary subfacies on well logging curves are: moderate natural gamma, drastic resistivity variations, generally low to medium values, low sonic transit time, generally high density, and moderate compensated neutron values. (Floral diagram) Figure 7 Petal 3 in the image reflects the characteristics of this subphase.
[0077] The characteristics of the invasive phase on the logging curve are: thick layer, micro-tooth pattern, high natural gamma value, significant variations in resistivity and density due to subphase reactions, low to medium sonic transit time, and low to medium compensated neutron values. (Floral diagram) Figure 6 The lower petals in the middle reflect the characteristics of this phase.
[0078] The characteristics of the outer zone subphase on the logging curve are: low density, high natural gamma, medium to low resistivity, moderate sonic transit time, and medium to low compensated neutron values. (Floral diagram) Figure 7 Petal 4 in the image reflects the characteristics of this subphase.
[0079] The characteristics of the middle zone subphase on the logging curve are: medium to high density, high natural gamma, high resistivity, medium to low sonic transit time, and medium to low compensated neutron values. (Floral diagram) Figure 7 Petal 5 in the image reflects the characteristics of this subphase.
[0080] The characteristics of the inner zone subphase on the logging curve are: medium to high density, high natural gamma, high resistivity, low sonic transit time, and low compensated neutron values. (Floral diagram) Figure 7 Petal 6 in the image reflects the characteristics of this subphase.
[0081] The characteristics of the overflow phase on the logging curve are as follows: natural gamma ray is thick and slightly toothed under the same lithological conditions, and is generally low. Resistivity is massive, slightly toothed, and low-resistivity, with a relatively high density value. Acoustic transit time varies significantly with subphase, natural gamma ray is low, and compensated neutron values are medium to high. (Floral diagram) Figure 6 The left petal in the image reflects the characteristics of this phase.
[0082] The characteristics of composite lava flows on well logging curves are as follows: high density values; thick, serrated natural gamma ray under the same lithological conditions, generally low values; massive, serrated, and low resistivity; moderate sonic transit time; low natural gamma ray; and high compensated neutron values. (Floral diagram) Figure 7 Petal 7 in the image reflects the characteristics of this subphase.
[0083] The characteristics of vitreous clastic rocks on well logging curves are: high density, low resistivity, high sonic transit time, low natural gamma, and high compensated neutron values. (Floral diagram) Figure 7 Petal 8 in the image reflects the characteristics of this subphase.
[0084] The characteristics of plate-like lava flows on well logging curves are: high density, low resistivity, low sonic transit time, low natural gamma, and medium compensated neutron. (Floral pattern) Figure 7 Petal 9 in the image reflects the characteristics of this subphase.
[0085] according to Figure 6 The characteristics of each petal can be summarized in Table 1 for the volcanic rock facies curve response: Table 1. Well logging response characteristics of Huangshatuo volcanic rocks
[0086] according to Figure 7 The characteristics of each petal can be summarized in Table 2 for the response curves of volcanic rock subfacies: Table 2. Well logging response characteristics of subfacies in Huangshatuo volcanic rocks.
[0087] Traditional lithofacies classification relies on core sampling or cuttings logging. Core sampling is costly, resulting in very few cored wells, and even fewer wells capable of continuous core sampling. Cuttings logging also suffers from low accuracy. The flower-shaped diagram provided by this invention highlights the characteristics of various logging curves at the lithofacies and subfacies levels. Using this method, volcanic lithofacies and subfacies classifications were performed on 93 wells in the Huangshatuo area, providing rich geological data for geological modeling and remaining oil distribution studies in this block. Compared to traditional lithofacies classification, the lithofacies classification provided by this invention is more economical and practical.
[0088] In practice, if you want to determine which phase / subphase a certain layer belongs to, you can read the natural gamma, density, neutron, time difference and resistivity logging curve values of that layer, put the values into a flower diagram, and see which petal it falls into to intuitively determine the volcanic rock phase / subphase.
[0089] If you want to create a flower pattern to classify lithofacies / subfacies, you can read the curve values of different wells in the block and import them into drawing software or vector graphics software to draw. Note that you should look for curves that can highlight geological information, use different colors to distinguish different curves, and combine them with existing geological knowledge to find the final lobing method.
[0090] The above are exemplary embodiments disclosed in this invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments of this invention as defined by the claims. The functions, steps, and / or actions of the methods according to the disclosed embodiments described herein do not need to be performed in any particular order. The sequence numbers of the disclosed embodiments of this invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. Furthermore, although the elements disclosed in the embodiments of this invention may be described or claimed individually, they may be understood as multiple unless explicitly limited to a singular number.
[0091] It should be understood that, as used herein, the singular form “a” is intended to include the plural form as well, unless the context clearly supports an exception. It should also be understood that, as used herein, “and / or” refers to any and all possible combinations of one or more of the associated listed items.
[0092] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the invention (including the claims) is limited to these examples. Within the framework of the invention, technical features of the above embodiments or different embodiments can be combined, and many other variations of different aspects of the invention exist, which are not provided in the details for the sake of brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the protection scope of the invention.
Claims
1. A method for identifying volcanic rock facies through well logging, characterized in that, Includes the following steps: Acquire multiple sets of volcanic rock sample data within the target area, including well logging data of the volcanic rock samples and the corresponding lithofacies types; Based on the acquired volcanic rock sample data, a well logging pattern identification map of volcanic rock facies within the target area was constructed; Based on the well logging identification pattern of volcanic rock facies within the target area, facies identification is performed on volcanic rock samples within the target area.
2. The method for identifying volcanic rock facies through logging according to claim 1, characterized in that, The logging data for the volcanic rock samples include natural gamma, density, compensated neutrons, sonic transit time, and resistivity.
3. The method for identifying volcanic rock facies through logging according to claim 1, characterized in that, Obtain multiple sets of volcanic rock sample data within the target area, including: Analyze the lithofacies types of volcanic rocks within the target area; For each lithofacies type, multiple sets of volcanic rock sample data were obtained.
4. The method for identifying volcanic rock facies through logging according to claim 3, characterized in that, The analysis of lithofacies types of volcanic rocks in the target area includes: starting from the actual geological data of the target area, and based on the geological and petrological characteristics of the target area, conducting an analysis of the lithofacies types of volcanic rocks in the target area.
5. The method for identifying volcanic rock facies through well logging according to claim 4, characterized in that, The geological features of the target area include its geological tectonic background, volcanic activity history, and related sedimentary environment. The petrological features include rock composition, structure, and rock type.
6. The method for identifying volcanic rock facies through well logging according to claim 3, characterized in that, Based on the acquired volcanic rock sample data, a well logging identification pattern map of volcanic rock facies in the target area was constructed, including: Preprocessing was performed on the acquired data of multiple sets of volcanic rock samples of various lithofacies types; Based on preprocessed data from multiple volcanic rock samples, a well logging identification pattern chart of volcanic rock facies is constructed to characterize the correlation between various volcanic rock facies types and well logging data within the target area.
7. The method for identifying volcanic rock facies through logging according to claim 6, characterized in that, Preprocessing was performed on the acquired volcanic rock sample data of various lithofacies types, including: The acquired data of multiple sets of volcanic rock samples of various lithofacies types were sorted according to lithofacies type; The sorted volcanic rock sample data were sequentially numbered to obtain preprocessed volcanic rock sample data.
8. The method for identifying volcanic rock facies through logging according to claim 7, characterized in that, Based on preprocessed data from multiple volcanic rock samples, a volcanic rock facies logging identification pattern chart is constructed to characterize the correlation between various volcanic rock facies types and logging data within the target area, including: Based on preprocessed data from multiple volcanic rock samples, a volcanic rock lithofacies logging identification pattern is constructed. In the volcanic rock lithofacies logging identification pattern, the radius coordinate represents the size of the logging data and the angular coordinate represents the sample data number. Dividing lines are drawn between two adjacent facies types in the volcanic rock facies logging identification flower pattern to divide the volcanic rock facies logging identification flower pattern into multiple fan-shaped petals, each fan-shaped petal representing a facies type, thereby forming the volcanic rock facies logging identification pattern diagram.
9. The method for identifying volcanic rock facies through well logging according to claim 8, characterized in that, Based on the well logging identification pattern chart of volcanic rocks within the target area, lithofacies identification is performed on volcanic rock samples within the target area, including: Obtain well logging data from volcanic rock samples within the target area; The well logging data of the acquired volcanic rock sample is projected onto the volcanic rock lithofacies well logging identification pattern chart, and the lithofacies of the volcanic rock sample is determined by observing which fan-shaped petal the well logging data falls into.
10. The method for identifying volcanic rock facies through well logging according to claim 3, characterized in that, Obtain multiple sets of volcanic rock sample data within the target area, including: For each lithofacies type, analyze its subfacies type; For each subfacies type, multiple sets of volcanic rock sample data were obtained.
11. The method for identifying volcanic rock facies through well logging according to claim 10, characterized in that, Based on the acquired volcanic rock sample data, a well logging identification pattern map of volcanic rock facies in the target area was constructed, including: Preprocessing was performed on the acquired data of multiple sets of volcanic rock samples of various subfacies types; Based on preprocessed data from multiple volcanic rock samples, a well logging identification pattern chart of volcanic rock subfacies is constructed to characterize the correlation between various volcanic rock subfacies types and well logging data within the target area.
12. The method for identifying volcanic rock facies through well logging according to claim 11, characterized in that, Preprocessing was performed on the acquired volcanic rock sample data of various subfacies types, including: The acquired data of multiple sets of volcanic rock samples of various subfacies types were sorted according to lithofacies type; The data of multiple volcanic rock samples for each lithofacies type were sorted according to subfacies type; The sorted volcanic rock sample data were sequentially numbered to obtain preprocessed volcanic rock sample data.
13. The method for identifying volcanic rock facies through well logging according to claim 12, characterized in that, Based on preprocessed data from multiple volcanic rock samples, a well logging identification pattern chart representing the correlation between various volcanic subfacies types and well logging data within the target area is constructed, including: Based on preprocessed data from multiple volcanic rock samples, a subfacies logging identification pattern for volcanic rocks is constructed. In this pattern, the radius coordinate represents the size of the logging data, and the angular coordinate represents the sample data number. Dividing lines are drawn between two adjacent lithofacies types in the volcanic rock subfacies logging identification flower diagram to divide the volcanic rock lithofacies logging identification flower diagram into multiple fan-shaped petals, each fan-shaped petal representing a lithofacies type. Dividing lines are drawn between two adjacent subfacies types in each lithofacies type to divide each fan-shaped petal into sub-fan-shaped petals, each sub-fan-shaped petal representing a subfacies type, thereby forming the volcanic rock subfacies logging identification pattern diagram.
14. The method for identifying volcanic rock facies through well logging according to claim 13, characterized in that, Based on the well logging identification pattern chart of volcanic rocks within the target area, lithofacies identification is performed on volcanic rock samples within the target area, including: Obtain well logging data from volcanic rock samples within the target area; The well logging data of the acquired volcanic rock sample is projected onto the volcanic rock subfacies well logging identification pattern chart. The lithofacies and / or subfacies of the volcanic rock sample are determined by observing which fan-shaped petal and / or which sub-fan-shaped petal the well logging data falls into.
15. The method for identifying volcanic rock facies through well logging according to claim 3, characterized in that, Volcanic rocks have the following lithofacies types: eruptive facies, effusive facies, intrusive facies, and volcanic sedimentary facies.
16. The method for identifying volcanic rock facies through well logging according to claim 10, characterized in that, The lithofacies types of volcanic rocks include explosive facies, effusive facies, intrusive facies, and volcanic sedimentary facies. The explosive facies include pyroclastic flow subfacies, the effusive facies include composite lava flow subfacies, vitreous clastic rock subfacies, and platy lava flow subfacies, the intrusive facies include outer zone subfacies, middle zone subfacies, and inner zone subfacies, and the volcanic sedimentary facies include volcanic sedimentary subfacies containing outer clastic rocks and re-transported pyroclastic sedimentary subfacies.
17. A volcanic rock facies logging identification device, characterized in that, include: The sample data acquisition module is used to acquire multiple sets of volcanic rock sample data within the target area. The volcanic rock sample data includes well logging data of the volcanic rock samples and the corresponding lithofacies types. The chart construction module is used to construct a chart of volcanic rock lithofacies well logging identification patterns within the target area based on multiple sets of acquired volcanic rock sample data; The lithofacies identification module is used to identify the lithofacies of volcanic rock samples within the target area based on the lithofacies logging identification pattern chart of volcanic rocks within the target area.
18. The volcanic rock facies logging identification device according to claim 17, characterized in that, The chart construction module includes a lithofacies identification chart construction submodule, which is used to construct a volcanic rock lithofacies logging identification pattern chart based on the acquired multiple sets of volcanic rock sample data, representing the correlation between various volcanic rock lithofacies types and logging data in the target area.
19. The volcanic rock facies logging identification device according to claim 17, characterized in that, The chart construction module includes a sub-module for subfacies identification chart construction. This sub-module is used to construct a volcanic subfacies logging identification pattern chart based on the acquired multiple sets of volcanic rock sample data. The chart chart characterizes the relationship between various volcanic subfacies types and logging data within the target area.
20. The volcanic rock facies logging identification device according to claim 17, characterized in that, The logging data for the volcanic rock samples include natural gamma, density, compensated neutrons, sonic transit time, and resistivity.