Shale segment interlayer identification method and device based on hydrocarbon generation potential and lithology binarization

Abstract

The application discloses a shale segment interlayer identification method and device based on hydrocarbon generation potential and lithology binarization. The method comprises the following steps: inputting the sensitive curve of a target well in a shale layer into a lithology identification model, obtaining the depth range of the organic matter rich shale development segment and the binarized lithology data of the organic matter rich shale development segment according to the model output result; identifying the non-organic matter rich shale single layer according to the lithology data; and if the thickness of the non-organic matter rich shale single layer is greater than the lower limit of the single layer thickness serving as the interlayer of the pseudo-in-situ conversion segment, the non-organic matter rich shale single layer is identified as the interlayer. The method breaks the limitation of the traditional interlayer identification which simply relies on lithology, is more suitable for the geological evaluation and related research of the in-situ conversion of shale oil, and converts the lower limit value of the hydrocarbon generation potential of the interlayer into the lower limit value of the interlayer thickness which is more intuitive and easier to obtain, so that the requirement for data is reduced, and the identification of the interlayer of the pseudo-in-situ conversion segment of the shale oil can be realized only by using the lithology data.

Description

Technical Field

[0001] This invention relates to the fields of geophysical logging and in-situ shale oil extraction technology, and in particular to a method and apparatus for identifying shale interlayers based on hydrocarbon generation potential and lithological binarization. Background Technology

[0002] Studies have shown that my country's medium- and low-maturity shale oil resources have enormous potential. Breakthroughs in corresponding exploration and development technologies would be of great strategic significance in reducing my country's dependence on imported crude oil. Currently, theoretical and technological explorations in this field are in full swing both domestically and internationally. The organic matter contained in medium- and low-maturity shale mainly includes two categories: already formed residual oil and kerogen that has not been converted into hydrocarbons. Existing unconventional oil and gas development methods, such as horizontal wells with large-scale hydraulic fracturing, are generally ineffective in developing either type of organic matter. In-situ heating of the shale is necessary to convert the organic matter into more fluid, lighter oil and gas for extraction. In this process, detailed characterization of the organic-rich shale strata to be heated is required, especially identifying interlayers that affect heating and oil-gas conversion efficiency.

[0003] Currently, the technical methods for evaluating interlayers in shale formations mainly target simple lithological interlayers. For example, identifying and characterizing non-shale lithological interlayers such as sandstone, limestone, dolomite, and mixed sedimentary rocks within shale. In this classification scheme, studies have been reported on the thickness, proportion, and development degree of individual interlayers (Zhu Deshun, Wang Yong, Zhu Deyan, et al. Definition Criteria and Enrichment Controlling Factors of Interlayered Shale Oil in the First Member of the Bohai Bay Depression, 2015; Cheng Ming, Luo Xiaorong, Lei Yuhong, et al. Study on Distribution, Fractal Characteristics and Estimation Methods of Siltaceous Interlayers / Laminations in Zhangjiatan Shale, Ordos Basin, 2015; Liu Yali, Liu Peng. Characteristics and Role of Interlayers in Terrestrial Organic-Rich Mudstone and Shale—Taking the Jiyang Depression as an Example, 2019; Wang Baohua, Li Hao, Lu Jianlin. Quantitative Characterization of the Development Degree of Non-Mudstone and Shale Interlayers in Terrestrial Shale Formations, 2019). Previous studies have shown that the presence of interlayers primarily affects the accumulation, migration, and seepage of already generated oil and gas, as well as the effectiveness of hydraulic fracturing in subsequent development stages. Therefore, current research on interlayers mainly focuses on aspects such as porosity, permeability, oil and gas saturation, and mechanical properties.

[0004] In terms of patented technologies, the evaluation of interlayers in shale formations often focuses on their impact on the seepage and content of already generated oil and gas, or on subsequent reservoir stimulation. Examples include: a quantitative characterization method for the development degree of permeable interlayers in mudstone and shale (authorization publication number: CN 110569512B); a classification of lithofacies assemblages of sandstone interlayer development sections in shale formations (application publication number: CN115876974A); a calculation method and system for the oil-bearing index of sandstone interlayers in shale formations (application publication number: CN114894997A); and a method for evaluating the brittleness of continental shale gas reservoirs considering interlayer types (authorization publication number: CN115356772B). Summary of the Invention

[0005] The inventors discovered that for in-situ conversion of shale oil, the target development zone is an organic-rich shale section, and the extraction target is either non-flowing solid organic matter or non-flowing viscous, stagnant oil. Traditional lithological interlayer identification and evaluation are not significantly beneficial for the in-situ heating and development of low-maturity shale oil. In contrast, accurately identifying interlayers with poor hydrocarbon generation potential from the perspective of source rock quality is more practically significant for the efficient development of shale oil in-situ conversion. Currently, there are few studies on interlayer identification and evaluation based on differences in hydrocarbon generation potential for organic-rich shale formations. Furthermore, due to the characteristics of most continental shale formations, such as rapid lithological changes, numerous interlayers, and thin individual layers, achieving high-precision evaluation of interlayers with low hydrocarbon generation potential in organic-rich shale formations is quite challenging.

[0006] In order to at least partially solve the technical problems existing in the prior art, the inventors made this invention, which provides a method and device for identifying interlayers in shale sections based on hydrocarbon generation potential and lithological binarization through specific implementation methods. It can identify interlayers based on hydrocarbon generation potential on the basis of the binarization interpretation of organic-rich shale, and provide important data basis for realizing efficient in-situ conversion and development of shale oil.

[0007] In a first aspect, embodiments of the present invention provide a method for identifying interlayers in shale sections based on hydrocarbon generation potential and lithological binarization, including:

[0008] The sensitive curve of the target well within the shale layer is input into the lithology identification model. Based on the model output, the depth range of the organic-rich shale development section and the binary lithology data within the range are obtained. The binary lithology data includes organic-rich shale and non-organic-rich shale.

[0009] Based on the aforementioned binarized lithological data, identify single layers of non-organic shale;

[0010] If the thickness of the non-organic shale monolayer is greater than the lower limit of the monolayer thickness as a pseudo-in-situ transformation interlayer, the non-organic shale monolayer is identified as an interlayer. The lower limit of the monolayer thickness is predetermined based on the average value of the hydrocarbon generation potential of the organic shale monolayer within the shale layer and multiple data pairs containing the thickness of the non-organic shale monolayer and its hydrocarbon generation potential.

[0011] Secondly, embodiments of the present invention provide a shale interlayer identification device based on hydrocarbon generation potential and lithological binarization. The device includes a binarized lithological data acquisition module, a non-organic shale single-layer identification module, a single-layer thickness lower limit determination module for interlayers, and an interlayer identification module.

[0012] The binarized lithological data acquisition module is used to input the sensitive curve of the target well within the shale layer into the lithological identification model, and obtain the depth range of the organic-rich shale development section and the binarized lithological data within the range based on the model output results. The binarized lithological data includes organic-rich shale and non-organic-rich shale.

[0013] The non-organic shale monolayer identification module is used to identify non-organic shale monolayers based on the binarized lithology data.

[0014] The interlayer identification module is used to identify the non-organic shale monolayer as an interlayer if the thickness of the non-organic shale monolayer is greater than the lower limit of the monolayer thickness for a pseudo-in-situ transformation interlayer. The lower limit of the monolayer thickness is determined in advance by the interlayer monolayer thickness determination module based on the average value of the hydrocarbon generation potential of the organic shale monolayer within the shale layer and multiple data containing the thickness of the non-organic shale monolayer and its hydrocarbon generation potential value.

[0015] Thirdly, embodiments of the present invention provide a computer storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-mentioned method for identifying shale interlayers based on hydrocarbon generation potential and lithological binarization.

[0016] Fourthly, this disclosure provides a server, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method for identifying shale interlayers based on hydrocarbon generation potential and lithological binarization.

[0017] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0018] (1) The shale interlayer identification method based on hydrocarbon generation potential and lithological binarization provided in this embodiment of the invention, based on the average hydrocarbon generation potential value of a single organic-rich shale layer within the shale layer and multiple data pairs containing the thickness and hydrocarbon generation potential value of a single non-organic-rich shale layer, pre-determines the lower limit of the single-layer thickness of the non-organic-rich shale layer as an interlayer in the pseudo-in-situ conversion section; if the thickness of the non-organic-rich shale layer is determined to be greater than the lower limit of the single-layer thickness as an interlayer, it is determined to be an interlayer. First, this method is designed for specific application scenarios of organic-rich shale development sections, breaking the limitations of traditional methods that rely solely on lithology to identify interlayers, and is more suitable for geological evaluation and related research on in-situ conversion of shale oil; in addition, this method transforms the lower limit of the hydrocarbon generation potential of the interlayer into a more intuitive and easily obtainable lower limit of the interlayer thickness, reducing the data requirements, and only lithological data is needed to identify interlayers in the pseudo-in-situ conversion section of shale oil. The direct reason why the lower limit of hydrocarbon generation potential of interlayers can be converted into the lower limit of interlayer thickness in this way is that there is a relatively significant statistical relationship between interlayer thickness and hydrocarbon generation potential. The fundamental reason is that the enrichment of organic matter requires an extremely low deposition rate. The smaller the thickness of a single interlayer, the faster the deposition rate, the more difficult it is for organic matter to accumulate, and ultimately the worse the hydrocarbon generation potential.

[0019] (2) The shale interlayer identification method based on hydrocarbon generation potential and lithological binarization provided in this embodiment of the invention is designed for the specific scenario of thin interlayer lithology identification in organic-rich shale development sections. It abandons the pursuit of universality in conventional well logging lithology interpretation, which interprets and characterizes various lithologies developed in the study area separately. Instead, it limits the lithology interpretation objects to two types: organic-rich shale and non-organic-rich shale. This reduces the ambiguity of well logging lithology interpretation and improves interpretation accuracy. At the same time, it reduces the amount of computation and increases the identification speed of batch interpretation of multiple wells.

[0020] (3) The shale interlayer identification method based on hydrocarbon generation potential and lithological binarization provided in this embodiment of the invention determines the data on which the lower limit of the thickness of a single layer of non-organic-rich shale as a pseudo-in-situ transformation interlayer depends. This data consists of the average hydrocarbon generation potential value of a single layer of organic-rich shale within the shale layer and multiple data pairs containing the thickness of a single layer of non-organic-rich shale and its hydrocarbon generation potential value. This is obtained through the following method: based on the binarized lithological data of continuous core sections within the shale layer and the upper limit of the proportion of non-organic-rich shale in the in-situ transformation section, pseudo-in-situ transformation sections are identified from the core sections; according to sedimentary cycles... The identified pseudo-in-situ transformation segments were divided into multiple units. The type of each unit was determined by its proportion of the thickness within the corresponding pseudo-in-situ transformation segment, and at least one unit was selected from each type. Millimeter-level lithological descriptions were performed on the selected units. Based on the description results, the units were divided into multiple organic-rich shale monolayers and non-organic-rich shale monolayers. Rock samples were taken from each monolayer, and their hydrocarbon generation potential was determined through pyrolysis testing. The average hydrocarbon generation potential of the organic-rich shale monolayers and multiple data pairs containing the thickness and hydrocarbon generation potential of the non-organic-rich shale monolayers were statistically obtained. Taking into full account the geological characteristics of rapid lithological changes and thin monolayers in terrestrial shale formations, lithological combination division, multi-level core fine description, and multi-scale sampling segment selection significantly reduced the workload while ensuring the lithological representativeness and high sampling accuracy of the collected samples.

[0021] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0022] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0023] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0024] Figure 1 This is a flowchart illustrating the method for determining the lower limit of the thickness of a single layer of non-organic shale as an interlayer in Embodiment 1 of the present invention.

[0025] Figure 2 This is a flowchart of the method for establishing a lithological identification model for organic-rich shale development sections based on lithological binarization in Embodiment 2 of the present invention;

[0026] Figure 3 This is a flowchart of the shale interlayer identification method based on hydrocarbon generation potential and lithological binarization in Embodiment 3 of the present invention;

[0027] Figure 4 This is a flowchart of the multi-well, multi-curve, and multi-lithology sensitive curve synchronous screening method in Embodiment 4 of the present invention;

[0028] Figure 5 This is an example diagram of the synchronous comparison and screening of sensitivity curves for all sample points and the lithological distribution vein lines in Embodiment 4 of the present invention;

[0029] Figure 6 This is a typical wellbore column diagram and the distribution of three sampling points in Embodiment 5 of the present invention;

[0030] Figure 7 for Figure 6 The diagram showing the millimeter-level silty interlayer and shale single-layer division and sampling scheme of "Sampling Point 1";

[0031] Figure 8 for Figure 6 The diagram shows the millimeter-level silty interlayer and shale single-layer division and sampling scheme of "Sampling Point 2" and "Sampling Point 3";

[0032] Figure 9 This is a graph showing the relationship between the average ratio of the hydrocarbon generation potential values ​​of a single sandstone layer and the average value of the shale layer and the thickness of the single sandstone layer in Embodiment 5 of the present invention.

[0033] Figure 10 for Figure 6 The "Sampling Point 1" section compares the lithological profile evaluated in this embodiment with a conventional lithological profile.

[0034] Figure 11 This is a schematic diagram of the shale interlayer identification device based on hydrocarbon generation potential and lithological binarization in an embodiment of the present invention. Detailed Implementation

[0035] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0036] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Every smaller range between any stated value or intermediate value within a stated range, and any other stated value or intermediate value within said range, is also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0037] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention. All references to this specification are incorporated by way of citation to disclose and describe methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0038] In this application, the lower limit of TOC (total organic matter content) of organic-rich shale is used as the standard to classify organic-rich shale and non-organic-rich shale. Specifically, rocks with TOC greater than the lower limit are defined as organic-rich shale, and rocks with TOC not greater than the lower limit are defined as non-organic-rich shale.

[0039] The lower limit of TOC for organic-rich shale is set flexibly according to the actual geological conditions of the study area. It can usually be set to 2%, 3% or 5%, or other values ​​can be selected.

[0040] Example 1

[0041] Embodiment 1 of the present invention provides a method for determining the lower limit of the thickness of a single layer of non-organic-rich shale as an interlayer in a pseudo-in-situ transformation section of a shale layer. Specifically, it involves determining the lower limit of the thickness of non-organic-rich shale interlayers identified from pseudo-in-situ transformation sections within a shale layer, referring to... Figure 1 As shown, it includes the following steps:

[0042] Step S11: Based on the binary lithological data of the core section of the target layer in the sample well and the upper limit of the proportion of non-organic shale in the in-situ transformation section, identify the pseudo-in-situ transformation section from the core section, divide the identified pseudo-in-situ transformation section into multiple units, determine the type of each unit according to the thickness ratio of the pseudo-in-situ transformation section, and select at least one unit from each type of unit.

[0043] First, select typical dissected wells for identifying low hydrocarbon generation potential interlayers. Typically, typical dissected wells must meet the following requirements:

[0044] (1) The dissection well must be located within the shale oil in-situ conversion development block, or at least adjacent to the development block;

[0045] (2) At least one well;

[0046] (3) The shale section where shale oil is to be heated in situ has a continuous core sampling section.

[0047] Based on lithological description data, pseudo-in-situ transformation sections, i.e. organic-rich shale sections, were identified from the core sections of typical dissected wells.

[0048] The binary lithological data of the cored sections, including organic-rich shale and non-organic-rich shale, can be obtained from the core description data, thin section identification data and TOC detection data of the cored sections of the target layer in the sample well. The acquisition process includes the steps described in Example 2 below.

[0049] Here, we need to obtain the binary lithological data of the core segment in centimeter-level format.

[0050] The proportion of non-organic-rich shale in the identified pseudo-in-situ transformation zone shall not exceed the upper limit of the proportion of non-organic-rich shale in the in-situ transformation zone. The upper limit of the proportion of non-organic-rich shale in the in-situ transformation zone can usually be set to 20%, but it is optional and can be set to other values ​​according to relevant regulations or actual research needs.

[0051] In some embodiments, the pseudo-in-situ transformation segment can be divided into multiple units according to depositional cycles, that is, divided into multiple depositional cycles, with each depositional cycle being considered as a unit.

[0052] Based on the different proportions of the thickness of the pseudo-in-situ transformation section, each unit is divided into one of the following types:

[0053] (1) The thickness of the section to which it is located is less than 1%.

[0054] (2) The thickness of the section to which it is located shall be no less than 1% and no more than 5%.

[0055] (3) The thickness of the section to be transformed in situ is greater than 5% and not greater than 10%.

[0056] (4) The thickness of the section to which it is located is greater than 10%.

[0057] The basis for this classification is that the thickness of a single sedimentary cycle is affected by the combined influence of the sedimentary paleoenvironment, which in turn affects the organic matter abundance of the lithological assemblage.

[0058] Selecting the same number of units from each type of unit can be done by selecting one typical unit from each type of unit, or multiple units can be selected if research time and conditions permit.

[0059] Step S12: Perform millimeter-level binary lithological description on the selected units. Based on the description results, divide the units into multiple organic-rich shale monolayers and non-organic-rich shale monolayers. Take rock samples from the monolayers and determine the hydrocarbon generation potential of the rock samples through pyrolysis testing.

[0060] Thin section identification data can accurately identify lithology at the millimeter level, but thin section identification data cannot distinguish between organic-rich shale and non-organic-rich shale for mudstone and shale. In this case, it is also necessary to refer to the TOC value. Mudstone and shale with a TOC value not greater than the lower limit of the TOC value of organic-rich shale, as well as other lithologies other than mudstone and shale, are identified as non-organic-rich shale.

[0061] It can be seen that the organic-rich shale in this embodiment is defined based on the lower limit value of the TOC of organic-rich shale. Shale that meets this lower limit value is organic-rich shale. The organic-rich shale development section refers to the rock layer composed of organic-rich shale and its interlayers.

[0062] Based on the millimeter-level binarized lithological description of the selected units, the following steps are performed:

[0063] (1) Using wire cutting technology, each lithological monolayer of each unit (sampling section) is cut along the lithological monolayer bedding plane to prepare an independent sheet rock sample for each lithological monolayer. The thickness of the rock sample is the thickness of the monolayer. The volume of a single rock sample must meet the mass required for rock pyrolysis (preferably, not less than 5 grams); (2) Rock pyrolysis test is carried out on each rock sample; (3) The sum of free hydrocarbons (S1) (unit mg / g, amount of free hydrocarbons in a unit mass of rock) and pyrolysis hydrocarbons (S2) (unit mg / g, amount of hydrocarbons generated after pyrolysis of a unit mass of rock) of each pyrolysis rock sample is calculated as the hydrocarbon generation potential value of the rock sample.

[0064] Step S13: Statistically obtain the average value of hydrocarbon generation potential of organic-rich shale single layer, and multiple data pairs including the thickness of non-organic-rich shale single layer and its hydrocarbon generation potential value.

[0065] The determination of the lower limit of the thickness of a single layer of non-organic shale as a pseudo-in-situ transformation zone relies on the average hydrocarbon generation potential of organic shale single layers within the shale layer and multiple data pairs containing the thickness and hydrocarbon generation potential of non-organic shale single layers. This is achieved through the following methods: Based on the binary lithological data of continuous core sections within the shale layer and the upper limit of the proportion of non-organic shale in the in-situ transformation zone, pseudo-in-situ transformation zones are identified from the core sections; the identified pseudo-in-situ transformation zones are divided into multiple units according to sedimentary cycles, and the type of each unit is determined according to its thickness ratio within the corresponding pseudo-in-situ transformation zone; at least one unit is selected from each type of unit; millimeter-level lithological descriptions are performed on the selected units, and based on the description results, the units are divided into multiple organic shale single layers and non-organic shale single layers. Rock samples are taken from the single layers, and the hydrocarbon generation potential of the rock samples is determined through pyrolysis testing; the average hydrocarbon generation potential of organic shale single layers and multiple data pairs containing the thickness and hydrocarbon generation potential of non-organic shale single layers are statistically obtained. Taking into full account the geological characteristics of terrestrial shale strata, such as rapid lithological changes and thin single-layer thickness, the study significantly reduced the amount of basic work by using lithological combination division, multi-level core fine description, and multi-scale sampling segment screening, while also ensuring the lithological representativeness and high sampling accuracy of the collected samples.

[0066] Step S14: For each data pair, obtain a sample point, which includes the thickness of a single layer of non-organic shale and the ratio of its hydrocarbon generation potential value to the average hydrocarbon generation potential value of a single layer of organic shale.

[0067] Step S15: Project the sample points into a coordinate system, obtain a trend line by fitting, and determine the ratio of the hydrocarbon generation potential value to the average hydrocarbon generation potential value of the organic-rich shale single layer as the thickness of the non-organic-rich shale single layer corresponding to the set ratio based on the trend line. Determine this thickness as the lower limit of the single layer thickness of the non-organic-rich shale single layer as the interlayer of the pseudo-in-situ conversion section.

[0068] The coordinate system uses the thickness of a single layer of non-organic shale and the ratio of the hydrocarbon generation potential value of a single layer of non-organic shale to the average hydrocarbon generation potential value of a single layer of shale (hydrocarbon generation potential value of a single layer of non-organic shale / average hydrocarbon generation potential value of a single layer of shale) as coordinate axes.

[0069] The aforementioned ratio is typically between 38% and 42%; preferably, it is 40%.

[0070] Taking a set ratio of 40% as an example, 40% of the average hydrocarbon generation potential of all organic-rich shale monolayers in the pseudo-in-situ conversion section is taken as the lower limit of hydrocarbon generation potential of the interlayer in the pseudo-in-situ conversion section; then, through the above-mentioned thickness conversion, the lower limit of the single-layer thickness of non-organic-rich shale monolayers as the interlayer of the pseudo-in-situ conversion section is obtained.

[0071] The direct reason why the lower limit of the hydrocarbon generation potential of the interlayer can be converted into the lower limit of the interlayer thickness in Embodiment 1 of this application is that there is a relatively significant statistical relationship between the interlayer thickness and the hydrocarbon generation potential of the interlayer; the fundamental reason is that the enrichment of organic matter requires an extremely low deposition rate, and the smaller the thickness of the single layer of the interlayer, the faster the deposition rate, the more difficult it is for organic matter to be enriched, and the worse the hydrocarbon generation potential is in the end.

[0072] Example 2

[0073] Embodiment 2 of the present invention provides a method for establishing a lithological identification model for organic-rich shale development sections based on lithological binarization, the process of which is as follows: Figure 2 As shown, it includes the following steps:

[0074] Step S21: Determine the lower limit of GR value for organic-rich shale based on the binarized lithological data of the cored section of the target layer in the sample well.

[0075] Wells cored within the target layer of the study area are selected as sample wells; alternatively, the selected wells can be divided into sample wells and validation wells. The data from the validation wells are not used in the model training but only for the later validation of the model.

[0076] Specifically, the binarized lithological data of the cored sections, including organic-rich shale and non-organic-rich shale (i.e., interlayers), are obtained through the following steps:

[0077] (1) Based on the thin section identification data of the core section of the target layer of the sample well, the lithological description data in its core description data is corrected to obtain preliminary lithological data, which includes mudstone and shale.

[0078] The lithological descriptions in core description data are merely lithological descriptions made by geologists based on visual observation and experience. Due to the limitations of visual observation and the influence of subjective factors, the accuracy of these lithological descriptions needs further refinement. Thin section identification data can accurately determine lithology, but the sampling for thin section identification data is limited. Therefore, preliminary lithological data is obtained by using the lithological descriptions in core description data as a basis and verifying them with thin section identification data.

[0079] The preliminary descriptive data obtained may include clastic rocks such as mudstone, shale, coarse sandstone, medium sandstone, fine sandstone and siltstone, as well as carbonate rocks or other types of rocks.

[0080] (2) Based on the TOC detection data, mudstone and shale with TOC values ​​greater than the preset lower limit of TOC for organic-rich shale in the preliminary lithological data are identified as organic-rich shale, and the binarized lithological data of the core section is obtained.

[0081] Thin section identification data can accurately identify lithology at the millimeter level, but thin section identification data cannot distinguish between organic-rich shale and non-organic-rich shale for mudstone and shale. In this case, it is also necessary to refer to the TOC value. Mudstone and shale with a TOC value not greater than the lower limit of the TOC value of organic-rich shale, as well as other lithologies other than mudstone and shale, are identified as non-organic-rich shale.

[0082] It can be seen that the organic-rich shale in this embodiment is defined based on the lower limit value of the TOC of organic-rich shale. Shale that meets this lower limit value is organic-rich shale. The organic-rich shale development section refers to the rock layer composed of organic-rich shale and its interlayers.

[0083] The lower limit of TOC for organic-rich shale is set flexibly according to the actual geological conditions of the study area. It can usually be set to 2%, 3% or 5%, or other values ​​can be selected.

[0084] Mudstone and shale with a TOC value not greater than the lower limit of the TOC value of organic-rich shale, as well as other lithologies other than mudstone and shale, are all classified as non-organic-rich shale.

[0085] Determining the lower limit of GR value for organic-rich shale can include extracting lithology and GR values ​​from sampling points with thin section identification data and TOC detection data based on lithological data and GR curves from sample wells; and statistically obtaining the lower limit of GR value for organic-rich shale based on the lithology and GR values ​​of multiple sampling points.

[0086] Since the interlayer identification in this embodiment is based on well logging curves, the well logging curves of the sample wells must first be standardized. After obtaining the preliminary lithological data or binarized lithological data of the core section, the standardized well logging curves are then repositioned to the correct depth.

[0087] The GR values ​​of the above sampling points were extracted from the GR curve after standardization and depth realignment.

[0088] Step S22: Use the binarized lithological data of the cored section and the curve segment of the selected sensitive curve as a sample to establish a sample set.

[0089] In some embodiments, after obtaining the binary lithological data of the cored section, the method further includes screening sensitive curves for organic-rich shale and non-organic-rich shale from all types of logging curves of the sample well.

[0090] Step S23: Train the selected neural network model using the sample set to establish a lithology identification model, and input the lower limit of the GR value into the lithology identification model.

[0091] The lower limit of the GR value is used to locate organic-rich shale development sections.

[0092] Example 3

[0093] Embodiment 3 of this invention provides a method for identifying shale interlayers based on hydrocarbon generation potential and lithological binarization. This method identifies non-organic-rich shale interlayers from pseudo-in-situ transformation sections (i.e., organic-rich shale sections) within shale layers. The procedure is as follows: Figure 3 As shown, it includes the following steps:

[0094] Step S31: Input the sensitive curve of the target well within the shale layer into the lithology identification model. Based on the model output, obtain the depth range of the organic-rich shale development section and the binary lithology data within the range.

[0095] Binarized lithological data include organic-rich shale and non-organic-rich shale.

[0096] The lithology identification model is pre-established using the method described in Example 2 above.

[0097] The working principle of the lithology identification model is to initially locate the development section of organic-rich shale based on the lower limit of the GR value of organic-rich shale and the GR curve of the target well. Based on the neural network learning results of the corresponding sensitive curve segment of the organic-rich shale development section, the binary lithology data is determined to obtain the output result.

[0098] In some embodiments, before inputting the sensitivity curve of the target well within the shale formation into the lithology identification model, the following may also be included:

[0099] Using cuttings logging data, anomalies in high GR values ​​of non-organic-rich shale were removed from the sensitivity curves of target wells within shale formations. For example, interference from special high-GR rocks, such as high-uranium-content sandstone, was eliminated.

[0100] Step S32: Identify non-organic shale single layers based on binarized lithological data.

[0101] Step S33: If the thickness of a non-organic shale monolayer is greater than the lower limit of the thickness of a monolayer that is a pseudo-in-situ transformation interlayer, the non-organic shale monolayer is identified as an interlayer.

[0102] The lower limit of the thickness of the non-organic shale monolayer as an interlayer is determined in advance based on the average value of the hydrocarbon generation potential of the organic shale monolayer within the shale layer and multiple data pairs containing the thickness of the non-organic shale monolayer and its hydrocarbon generation potential value. The specific determination method is described in the previous Example 1 and will not be repeated here.

[0103] The shale interlayer identification method based on hydrocarbon generation potential and lithological binarization provided in Embodiment 3 of this invention uses the average hydrocarbon generation potential value of a single organic-rich shale layer within the shale layer and multiple data pairs containing the thickness and hydrocarbon generation potential value of a single non-organic-rich shale layer. It pre-determines the lower limit of the single-layer thickness of the non-organic-rich shale layer as an interlayer in the pseudo-in-situ conversion section. If the thickness of the non-organic-rich shale layer is greater than the lower limit of the single-layer thickness for interlayer identification, it is identified as an interlayer; otherwise, even if the lithology is non-organic-rich shale, it is not determined to be an interlayer. Firstly, this method, targeting the specific application scenario of organic-rich shale sections, breaks through the limitations of traditional methods that rely solely on lithology to identify interlayers, making it more suitable for geological evaluation and related research on in-situ shale oil conversion. Secondly, this method transforms the lower limit of the hydrocarbon generation potential of interlayers into a more intuitive and easily obtainable lower limit of the interlayer thickness, reducing the data requirements; only lithological data is needed to identify interlayers in the pseudo-in-situ conversion section of shale oil. The direct reason why the lower limit of hydrocarbon generation potential of interlayers can be converted into the lower limit of interlayer thickness in this way is that there is a relatively significant statistical relationship between interlayer thickness and hydrocarbon generation potential. The fundamental reason is that the enrichment of organic matter requires an extremely low deposition rate. The smaller the thickness of a single interlayer, the faster the deposition rate, the more difficult it is for organic matter to accumulate, and ultimately the worse the hydrocarbon generation potential.

[0104] The shale interlayer identification method based on hydrocarbon generation potential and lithological binarization provided in Embodiment 3 of this invention is designed for the specific scenario of identifying thin interlayer lithology in organic-rich shale sections. It abandons the pursuit of universality in conventional well logging lithological interpretation, which separately interprets and characterizes various lithologies developed in the study area. Instead, it limits the lithological interpretation objects to two types: organic-rich shale and non-organic-rich shale. This reduces the ambiguity of well logging lithological interpretation and improves interpretation accuracy. At the same time, it reduces the amount of computation and increases the identification speed of batch interpretation of multiple wells.

[0105] The sensitive curves in Examples 2 and 3 above are sensitive curves for organic-rich shale. They can be determined using conventional sensitive curve screening methods. For example, sensitivity analysis can be used to optimize the lithological sensitive curves for organic-rich shale sections, selecting the curves most sensitive to the response of organic-rich shale and its interlayers. The lithological sensitivity analysis method automatically calculates the correlation between each curve and the lithology, directly selecting the curve with the best correlation.

[0106] Alternatively, the sensitive curve can be screened using the method described in Example 4 below.

[0107] Example 4

[0108] Embodiment 4 of the present invention provides a method for simultaneous screening of multiple wells, multiple curves, and multiple lithology-sensitive curves, the process of which is as follows: Figure 4 As shown, it includes the following steps:

[0109] Step S41: Obtain multiple sample points of the target layer.

[0110] Each sample point includes the binarized lithology type and the values ​​of each curve to be screened.

[0111] Based on the lithological data of the sample well rich in organic shale in Example 1, the curve to be screened is depth-calibrated, and a matching relationship between the lithological data and the curve to be screened is established in depth to obtain the well logging lithological calibration chart.

[0112] Sample points can be extracted based on the sampling points of the logging curve. For example, if the logging curve is sampled at 0.125m intervals, the sample points can also be sampled at 0.125m intervals, or the samples can be extracted after dilution.

[0113] The sampling method for the above-mentioned sample points differs from the traditional method of using rock sample collection points as calibration points. This improvement will greatly enhance the richness of sample data and the continuity in the longitudinal direction.

[0114] Multiple wells with continuous coring samples in the target layer of the study area can be identified as sample wells. The sample wells are representative and comprehensive, which greatly reduces the impact of geological heterogeneity on the accuracy of lithology sensitive curve screening.

[0115] Step S42: Project each sample point onto a coordinate system containing multiple parallel number axes, each number axis corresponding to a different curve to be screened.

[0116] Based on the well logging lithology calibration chart, the numerical distribution range of each type of curve to be screened was statistically analyzed.

[0117] Establish a coordinate system containing multiple parallel number axes, with the two ends of the number axes aligned and their values ​​matching the corresponding numerical distribution ranges. This can be achieved by the two ends of the numerical distribution range being identical to their respective endpoints, or by the minimum value at one end being less than the minimum value in the numerical distribution range, and the maximum value at the other end being greater than the maximum value in the numerical distribution range.

[0118] Taking the logging curve GR as an example, if the numerical distribution range of GR in the target layer is 200API to 500API, then the two endpoints of the number axis corresponding to the logging curve GR can be set to 200API and 500API respectively.

[0119] In some embodiments, the numerical values ​​of each number axis in the established coordinate system change in the same direction.

[0120] Taking a vertically distributed number line as an example, the values ​​on each number line either gradually increase from top to bottom or gradually decrease from top to bottom.

[0121] Step S43: Connect the projection points of the same sample point on different number axes to obtain a ridge line.

[0122] Use lines or colors to distinguish types of lithology.

[0123] Step S44: Based on the distribution characteristics of the vein lines, select at least one type of lithology-sensitive curve.

[0124] In some embodiments, at least one type of lithological sensitivity curve may be selected based on the distribution characteristics of the vein lines on the number axis, according to the following understanding:

[0125] The more convergent the vein lines of organic-rich shale on a certain number axis, and the more obvious the difference between them and the vein lines of non-organic-rich shale, the stronger the sensitivity of the screening curve corresponding to that number axis to organic-rich shale, and vice versa.

[0126] See Figure 5 As shown in the embodiment, the lithological interpretation sensitivity curves for the organic-rich shale section were determined through lithological sensitivity analysis as GR, CNL, and AC. Among the five curves, GR, CNL, and AC curves clearly distinguished the organic-rich shale from the sandstone interlayer.

[0127] The method for simultaneous screening of multi-well, multi-curve, and multi-lithology sensitive curves provided in Embodiment 4 of this invention transforms the correlation between logging curves and lithology into more intuitive line convergence and differentiation, thereby reducing the influence of subjective human factors in the sensitive curve selection process and improving the objectivity of the selection results.

[0128] The method for synchronous screening of multi-well, multi-curve, and multi-lithological sensitive curves provided in Embodiment 4 of this invention establishes a coordinate system containing multiple parallel number axes, each corresponding to a different curve to be screened. The method draws the vein lines corresponding to different sample points in the coordinate system, realizing the synchronous comparison of curves of different types in the same coordinate system, improving the accuracy of sensitive curve selection, reducing the likelihood of missing sensitive curves, and greatly improving screening efficiency.

[0129] The method for simultaneous screening of multiple wells, multiple curves, and multiple lithology-sensitive curves provided in Embodiment 4 of this invention connects the projection points of the same sample point on different number axes to obtain a vein line. One sample point corresponds to one vein line, and the possibility of two vein lines completely overlapping is very small. This avoids the situation of a large number of overlapping projection points caused by the simple projection method, making the final lithology distribution vein line map more complete and representative.

[0130] Example 5

[0131] Embodiment 5 of the present invention provides a specific application of a method for identifying interlayers in shale oil in-situ conversion sections based on hydrocarbon generation potential. This method identifies sandstone interlayers within pseudo-in-situ conversion sections (i.e., organic-rich shale sections) of shale formations, and includes the following steps:

[0132] S1: Select a well with continuous coring in an organic-rich shale section as a typical dissection well. Figure 6 ).

[0133] S2: Based on centimeter-level core description, the organic-rich shale section was divided into 10 sedimentary cycles. Each sedimentary cycle exhibits a positive rhythm, meaning the basal layer consists of a set of siltstone or silty mudstone and shale, with the sediment grain size gradually decreasing to shale as it ascends. Genetically, the siltstone or silty mudstone and shale at the bottom of each cycle in this embodiment represents primary gravity flow deposition. Based on the different ratios of the thickness of a single sedimentary cycle to the total thickness of the proposed heating section, this embodiment defines four lithological assemblage types with ratios below 1%, 1% (inclusive) to 5% (inclusive), 5% to 10% (inclusive), and greater than 10% as Type I (0 cycles), Type II (1 cycle), Type III (4 cycles), and Type IV (5 cycles), respectively. Specific details are as follows... Figure 6 As shown in the figure. In this embodiment, lithological assemblages No. 1, No. 5, and No. 9 were selected as sample collection sections.

[0134] S3: Select millimeter-level core description and sample collection points for the Type II, Type III, and Type IV lithological assemblages developed in this embodiment, respectively. Figure 6 Specifically, in lithological section 1, a sample collection point was selected and designated as "Sampling Point 1" (…). Figure 6 (as shown in Figure 1); in lithological assemblages No. 5 and No. 9, one sample collection point was selected in each, and designated as "Sampling Point 2" (as shown in Figure 1). Figure 6 (as shown in point 2) and "sampling point 3" Figure 6 (As shown in Figure 3). Thin sections were prepared from samples collected at the three sampling points. These thin sections were used to perform millimeter-level core characterization of the lithology at these three sampling points. A total of 24 lithological monolayers were identified at "Sampling Point 1" (e.g., ...). Figure 7 (as shown), Figure 7 The numbers 1-24 represent lithological monolayers, with 12 and 4 lithological monolayers respectively identified in "Sampling Point 2" and "Sampling Point 3" (e.g.) Figure 8 As shown in the figure, the lithological monolayers of "Sampling Point 2" include ① to ③ of "Sampling Point 2-1", ① and ② of "Sampling Point 2-2", ① to ③ of "Sampling Point 2-3", and ① to ④ of "Sampling Point 2-4", totaling 12; the lithological monolayers of "Sampling Point 3" include ① to ④, totaling 4. In this embodiment, the lithological types of all lithological monolayers include shale and silty interlayers.

[0135] S4: All monolayers are sampled using wire cutting technology. After the sample of each monolayer is prepared, a pyrolysis experiment is performed, and the sum of the pyrolyzed free hydrocarbons S1 and pyrolyzed hydrocarbons S2 is taken as the hydrocarbon generation potential value of that monolayer.

[0136] S5: Calculate the hydrocarbon generation potential of all shale layers and their average value. Take 40% of the average hydrocarbon generation potential of all shale layers as the lower limit of the hydrocarbon generation potential for the interlayer of the shale oil in-situ conversion and heating section. The remaining layers are considered silty interlayers.

[0137] S6: Plot the ratio of the hydrocarbon generation potential of 15 silty interlayers at three sampling points to the average hydrocarbon generation potential of a single shale layer, along with the thickness of each interlayer, into a scatter plot on the same coordinate system. Since the only lithology of non-shale interlayers in this embodiment is silty interlayers, only one scatter plot needs to be created. In this embodiment, the vertical axis represents the ratio of the hydrocarbon generation potential of the silty interlayers to the average hydrocarbon generation potential of a single shale layer, and the horizontal axis represents the thickness of each interlayer. A trend line is set for the 15 data points, and the thickness corresponding to the intersection of the trend line and the horizontal line with a vertical axis value of 40% is taken as the lower limit of the thickness of interlayers with low hydrocarbon generation potential. That is, in this embodiment, siltstone and silty mudstone shale with a single layer thickness not exceeding 10 mm are all considered to have high hydrocarbon generation potential and are not considered interlayers; siltstone and silty mudstone shale with a single layer thickness exceeding 10 mm are all considered interlayers. Figure 9 ).

[0138] S7: For organic-rich shale sections, a multi-dimensional screening method for sensitive curves is used to select lithology-sensitive curves. This includes: screening sample wells for selecting lithology-sensitive curves; preparing data based on the sample wells, including well logging curve data and lithology data; establishing a well logging lithology calibration chart containing a standard lithology column and all curves; using all well logging curves from the sample wells as candidates for lithology-sensitive curves to avoid missing any, and statistically analyzing the numerical distribution range of each curve; setting a one-dimensional vertical axis for each curve, and arranging all corresponding axes horizontally; ensuring that the top scale of all axes is greater than the maximum value of the corresponding curve, and the bottom scale is less than the minimum value of the corresponding curve, ensuring that all curve values ​​are distributed on the axes; and standardizing the dimensions of all axes. Longitudinal length; connecting the numerical projections of the same logging curve data acquisition point on each number axis from left to right; the lithology of each logging curve data acquisition point is determined according to the logging lithology calibration chart; each lithology is marked with a unique color; connecting the numerical projections of all logging curve data acquisition points on different logging curve number axes one by one to form a lithology distribution vein line; statistically analyzing the distribution pattern of different lithologies on each number axis in the lithology sensitive curve synchronous comparison and screening coordinate system; the more convergent the vein line of a certain lithology on a certain number axis, the more obvious the difference between the vein lines of other lithologies, the stronger the sensitivity of the logging curve corresponding to that number axis to that lithology, and vice versa. After screening, GR, CNL, and AC were determined as the sensitive curves in this embodiment, such as... Figure 5 As shown.

[0139] S8: In this embodiment, the lithology interpretation sensitive curves GR, CNL, and AC are used as input curves to establish a well logging lithology identification model based on the three sensitive curves, and the interpretation model is further used to establish a lithology profile. Figure 10 ).

[0140] S9: Identify and determine the interlayers in the shale section for in-situ conversion and heating of shale oil according to the lower limit of the interlayer thickness described in step S6. Taking the core section of "Sampling Point 1" in this embodiment as an example, the lithological profile is reconstructed. Silty interlayers with a thickness of less than 10 mm are considered as shale. Finally, a lithological profile of the shale section for in-situ conversion of shale oil based on hydrocarbon generation potential is established, as follows: Figure 10 As shown. By Figure 10 and Figure 6 The comparison shows that Figure 6 Many silty interlayers Figure 10 The shale is considered to be shale. This practice of ignoring lithological interlayers is precisely what is needed for the in-situ transformation of shale oil, because these ignored interlayers can also generate hydrocarbons and do not need to be considered as interlayers.

[0141] Based on the inventive concept of this invention, embodiments of this invention also provide a shale interlayer identification device based on hydrocarbon generation potential and lithological binarization, see [link to relevant documentation]. Figure 11 As shown, the device includes a binary lithology data acquisition module 111, a non-organic shale single-layer identification module 112, an interlayer identification module 113, and an interlayer single-layer thickness lower limit determination module 114.

[0142] The binarized lithology data acquisition module 111 is used to input the sensitive curve of the target well in the shale layer into the lithology identification model, and obtain the depth range of the organic-rich shale development section and the binarized lithology data within the range based on the model output results. The binarized lithology data includes organic-rich shale and non-organic-rich shale.

[0143] The non-organic shale single-layer identification module 112 is used to identify non-organic shale single layers based on the binarized lithology data.

[0144] The interlayer identification module 113 is used to identify the non-organic shale monolayer as an interlayer if the thickness of the non-organic shale monolayer is greater than the lower limit of the monolayer thickness as a pseudo-in-situ transformation interlayer; the lower limit of the monolayer thickness is determined in advance by the interlayer monolayer thickness determination module 114 based on the average value of the hydrocarbon generation potential value of the organic shale monolayer in the shale layer and multiple data containing the thickness of the non-organic shale monolayer and its hydrocarbon generation potential value.

[0145] In some embodiments, the above-described apparatus further includes a lithology identification model building module 115, for pre-building a lithology identification model in the following manner:

[0146] Based on the binarized lithological data of the target layer core section of the sample well, the lower limit of the GR value for organic-rich shale is determined; the binarized lithological data of the core section and the curve segment of the selected sensitive curve are used as a sample to establish a sample set; the selected neural network model is trained using the sample set to establish a lithological identification model, and the lower limit of the GR value is input into the lithological identification model. The lower limit of the GR value is used to locate the development section of organic-rich shale.

[0147] In some embodiments, the lithology identification model building module 115 is used to obtain binary lithology data of organic-rich shale from the target layer core section of the sample well in the following manner:

[0148] Based on the thin section identification data of the core section of the target layer in the sample well, the lithological description data in its core description data is corrected to obtain preliminary lithological data, which includes mudstone and shale. Based on the TOC detection data, mudstone and shale with TOC values ​​greater than the preset lower limit of TOC for organic-rich shale in the preliminary lithological data are identified as organic-rich shale, thus obtaining the binary lithological data of the organic-rich shale in the core section.

[0149] In some embodiments, the lithology identification model building module 115 is used for:

[0150] Based on the binary lithological data and GR curves of the sample wells, the lithology and GR values ​​of the sampling points with thin section identification data and TOC detection data were extracted; based on the lithology and GR values ​​of multiple sampling points, the lower limit of GR values ​​for organic-rich shale was statistically obtained.

[0151] In some embodiments, before inputting the sensitive curve of the target well within the shale layer into the lithology identification model, the binarized lithology data acquisition module 111 is further configured to:

[0152] Using cuttings logging data, anomalies with high GR values ​​in non-organic shale were removed from the sensitivity curves of target wells within shale formations.

[0153] In some embodiments, the interlayer single-layer thickness lower limit determination module 114 is used to pre-determine the single-layer thickness lower limit of the interlayer serving as the pseudo-in-situ transformation segment interlayer in the following manner:

[0154] For each data pair, a sample point is obtained, containing the thickness of the non-organic shale monolayer and the ratio of its hydrocarbon generation potential value to the average hydrocarbon generation potential value of the organic shale monolayer. The sample point is projected into a coordinate system, and a trend line is obtained through fitting. Based on the trend line, the ratio of the hydrocarbon generation potential value to the average hydrocarbon generation potential value of the organic shale monolayer is determined as the thickness of the non-organic shale monolayer corresponding to the set ratio. This thickness is determined as the lower limit of the thickness of the non-organic shale monolayer as the interlayer of the pseudo-in-situ transformation section.

[0155] In some embodiments, the interlayer single-layer thickness lower limit determination module 114 is used to obtain the average value of the hydrocarbon generation potential of the organic-rich shale single layer within the shale layer and multiple data pairs containing the thickness of the non-organic-rich shale single layer and its hydrocarbon generation potential value in the following manner:

[0156] Based on the binarized lithological data of the cored section of the target layer in the sample well and the upper limit of the proportion of non-organic shale in the in-situ transformation section, pseudo-in-situ transformation sections are identified from the cored section. The identified pseudo-in-situ transformation sections are divided into multiple units according to sedimentary cycles. The type of each unit is determined according to its thickness ratio to the pseudo-in-situ transformation section. At least one unit is selected from each type of unit. Millimeter-level binarized lithological description is carried out on the selected units. Based on the description results, the units are divided into multiple organic shale monolayers and non-organic shale monolayers. Rock samples are cut from the monolayers, and the hydrocarbon generation potential value of the rock samples is determined by pyrolysis testing. The average value of the hydrocarbon generation potential value of the organic shale monolayer and multiple data pairs containing the thickness and hydrocarbon generation potential value of the non-organic shale monolayer are obtained.

[0157] In some embodiments, the sandwich layer single-layer thickness lower limit determination module 114 is used for:

[0158] Each unit is classified into one of the following types:

[0159] The thickness of the quasi-in-situ transformation segment is less than 1%, the thickness of the quasi-in-situ transformation segment is not less than 1% and not more than 5%, the thickness of the quasi-in-situ transformation segment is greater than 5% and not more than 10%, and the thickness of the quasi-in-situ transformation segment is greater than 10%.

[0160] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0161] Based on the inventive concept of this invention, this embodiment of the invention also provides a computer storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-mentioned method for identifying shale interlayers based on hydrocarbon generation potential and lithological binarization.

[0162] Based on the inventive concept of this invention, this embodiment of the invention also provides a server, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-mentioned method for identifying shale interlayers based on hydrocarbon generation potential and lithological binarization.

[0163] Unless otherwise specifically stated, terms such as processing, calculation, operation, determination, display, etc., may refer to the actions and / or processes of one or more processing or computing systems or similar devices that represent the manipulation and conversion of data representing physical (e.g., electronic) quantities within the registers or memory of the processing system into other data similarly representing physical quantities within the memory, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals can be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0164] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0165] In the detailed description above, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than those stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features in a single disclosed embodiment. Therefore, the appended claims are hereby clearly incorporated into the detailed description, wherein each claim stands alone as a preferred embodiment of the invention.

[0166] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0167] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0168] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0169] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term “comprising” as used in the specification or claims is interpreted in a manner similar to the term “including,” as it is understood when used as a conjunction in the claims. Additionally, the use of any term “or” in the specification of the claims is intended to mean “non-exclusive or.” The terms “first” and “second” are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

Claims

1. A method for identifying interlayers in shale sections based on hydrocarbon generation potential and lithological binarization, characterized in that, include: The sensitive curve of the target well within the shale layer is input into the lithology identification model. Based on the model output, the depth range of the organic-rich shale development section and the binary lithology data within the range are obtained. The binary lithology data includes organic-rich shale and non-organic-rich shale. Based on the aforementioned binarized lithological data, identify single layers of non-organic shale; If the thickness of the non-organic shale monolayer is greater than the lower limit of the monolayer thickness as a pseudo-in-situ transformation interlayer, the non-organic shale monolayer is identified as an interlayer. The lower limit of the monolayer thickness is predetermined based on the average value of the hydrocarbon generation potential of the organic shale monolayer within the shale layer and multiple data containing the thickness of the non-organic shale monolayer and its hydrocarbon generation potential. The lithology identification model is pre-established in the following manner: based on the binarized lithology data of the target layer core section of the sample well, the lower limit of the GR value of organic-rich shale is determined; the binarized lithology data of the core section and the curve segment of the selected sensitive curve are used as a sample to establish a sample set; the selected neural network model is trained using the sample set to establish the lithology identification model, and the lower limit of the GR value is input into the lithology identification model. The lower limit of the GR value is used to locate the organic-rich shale development section. The lower limit of the single-layer thickness of the pseudo-in-situ transformation interlayer is determined in advance by the following method: For each data pair, a sample point is obtained, containing the single-layer thickness of the non-organic shale and the ratio of its hydrocarbon generation potential value to the average hydrocarbon generation potential value of the organic shale single layer; the sample point is projected into a coordinate system, and a trend line is obtained through fitting; based on the trend line, the ratio of the hydrocarbon generation potential value to the average hydrocarbon generation potential value of the organic shale single layer is determined as the corresponding non-organic shale single-layer thickness at the set ratio, and this thickness is determined as the lower limit of the single-layer thickness of the non-organic shale single layer as the pseudo-in-situ transformation interlayer.

2. The method according to claim 1, characterized in that, The model output is obtained from the lithology identification model in the following manner: Based on the lower limit of the GR value and the GR curve of the target well, locate the organic-rich shale development section; Based on the neural network learning results of the corresponding sensitive curve segments of the organic-rich shale development section, the binarized lithological data is determined, and the results used for output are obtained.

3. The method according to claim 1, characterized in that, The binary lithological data of the target layer core section of the sample well were obtained based on the core description data, thin section identification data and TOC detection data of the target layer core section of the sample well.

4. The method according to claim 3, characterized in that, The binarized lithological data of the target layer core section of the sample well were obtained in the following manner: Based on the thin section identification data of the cored section of the target layer in the sample well, the lithological description data in its core description data is corrected to obtain preliminary lithological data, which includes mudstone and shale; Based on the TOC detection data, mudstone and shale with TOC values ​​greater than the preset lower limit of TOC for organic-rich shale in the preliminary lithological data are identified as organic-rich shale, and the binary lithological data of the organic-rich shale in the core section is obtained.

5. The method according to claim 4, characterized in that, The determination of the lower limit of GR value for organic-rich shale includes: Based on the binary lithological data and GR curves of the sample wells, the lithology and GR values ​​of the sampling points with thin section identification data and TOC detection data were extracted. Based on the lithology and GR values ​​of multiple sampling points, the lower limit of GR values ​​for organic-rich shale was statistically determined.

6. The method according to claim 1, characterized in that, Before inputting the sensitive curve of the target well within the shale layer into the lithology identification model, the method further includes: Using cuttings logging data, anomalies with high GR values ​​in non-organic shale were removed from the sensitivity curves of target wells within shale formations.

7. The method according to claim 1, characterized in that, The average hydrocarbon generation potential of organic-rich shale monolayers and multiple data pairs containing the thickness and hydrocarbon generation potential of non-organic-rich shale monolayers were obtained in the following manner: Based on the binary lithological data of the core section of the target layer in the sample well and the upper limit of the proportion of non-organic shale in the in-situ transformation section, pseudo-in-situ transformation sections are identified from the core section. The identified pseudo-in-situ transformation sections are divided into multiple units according to sedimentary cycles. The type of each unit is determined according to the thickness ratio of the pseudo-in-situ transformation section. At least one unit is selected from each type of unit. Millimeter-level binary lithological descriptions were performed on the selected units. Based on the description results, the units were divided into multiple organic-rich shale monolayers and non-organic-rich shale monolayers. Rock samples were cut from the monolayers, and the hydrocarbon generation potential of the rock samples was determined by pyrolysis testing. The average value of hydrocarbon generation potential of organic-rich shale single layers was obtained statistically, along with multiple data pairs including the thickness of non-organic-rich shale single layers and their hydrocarbon generation potential values.

8. The method according to claim 7, characterized in that, The method of determining the type of each unit based on its thickness ratio within the pseudo-in-situ transformation section includes: Each unit is classified into one of the following types: The thickness of the quasi-in-situ transformation segment is less than 1%, the thickness of the quasi-in-situ transformation segment is not less than 1% and not more than 5%, the thickness of the quasi-in-situ transformation segment is greater than 5% and not more than 10%, and the thickness of the quasi-in-situ transformation segment is greater than 10%.

9. The method according to claim 1, characterized in that, The hydrocarbon generation potential is the sum of free hydrocarbons S1 and pyrolytic hydrocarbons S2 per unit mass of rock.

10. A shale interlayer identification device based on hydrocarbon generation potential and lithological binarization, characterized in that, The device includes a binary lithology data acquisition module, a non-organic shale single-layer identification module, a single-layer thickness lower limit determination module for interlayers, an interlayer identification module, and a lithology identification model establishment module. The binarized lithological data acquisition module is used to input the sensitive curve of the target well within the shale layer into the lithological identification model, and obtain the depth range of the organic-rich shale development section and the binarized lithological data within the range based on the model output results. The binarized lithological data includes organic-rich shale and non-organic-rich shale. The non-organic shale monolayer identification module is used to identify non-organic shale monolayers based on the binarized lithology data. The interlayer identification module is used to identify the non-organic shale monolayer as an interlayer if the thickness of the non-organic shale monolayer is greater than the lower limit of the monolayer thickness for a pseudo-in-situ transformation interlayer; the lower limit of the monolayer thickness is determined in advance by the interlayer monolayer thickness lower limit determination module based on the average value of the hydrocarbon generation potential of the organic shale monolayer within the shale layer and multiple data containing the thickness of the non-organic shale monolayer and its hydrocarbon generation potential value; The lithology identification model building module is used to pre-build a lithology identification model in the following manner: based on the binarized lithology data of the target layer core section of the sample well, determine the lower limit of the GR value of organic-rich shale; take the binarized lithology data of the core section and the curve segment of the selected sensitive curve as a sample to build a sample set; use the sample set to train the selected neural network model to build a lithology identification model, and input the lower limit of the GR value into the lithology identification model, wherein the lower limit of the GR value is used to locate the organic-rich shale development section; The interlayer single-layer thickness lower limit determination module is used to pre-determine the single-layer thickness lower limit of the interlayer serving as the pseudo-in-situ conversion section interlayer in the following manner: Based on each data pair, a sample point is obtained, containing the non-organic shale single-layer thickness and the ratio of its hydrocarbon generation potential value to the average hydrocarbon generation potential value of the organic shale single-layer; the sample point is projected into a coordinate system, and a trend line is obtained through fitting; based on the trend line, the ratio of the hydrocarbon generation potential value to the average hydrocarbon generation potential value of the organic shale single-layer is determined as the non-organic shale single-layer thickness corresponding to the set ratio; this thickness is determined as the single-layer thickness lower limit of the non-organic shale single-layer serving as the pseudo-in-situ conversion section interlayer.

11. A computer storage medium, characterized in that, The computer storage medium stores computer-executable instructions, which, when executed by a processor, implement the shale interlayer identification method based on hydrocarbon generation potential and lithological binarization as described in any one of claims 1 to 9.

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