Hydrocarbon source rock sporopollen paleoclimate reconstruction method and device for neonatozoic basin

Abstract

The invention relates to the field of oil and gas exploration and development, and discloses a hydrocarbon source rock sporopollen paleoclimate reconstruction method and device for a neonatozoic basin. According to the method, sporopollen identification can be carried out on a plurality of hydrocarbon source rock samples, sporopollen identification data of each hydrocarbon source rock sample is determined, namely, a plurality of sporopollen categories in each hydrocarbon source rock sample and relative contents corresponding to different sporopollen categories are determined, and sporopollen identification is carried out on the basis of the sporopollen identification data of each hydrocarbon source rock sample and the created sporopollen paleoclimate database. The method comprises the following steps: determining qualitative paleoclimate parameter data and quantitative paleoclimate parameter data of each hydrocarbon source rock sample, and generating a TOC evolution chart based on the qualitative paleoclimate parameter data and the quantitative paleoclimate parameter data of each hydrocarbon source rock sample, thereby realizing intelligent paleoclimate reconstruction, reducing manpower resources consumed by paleoclimate reconstruction in related technologies, and improving the efficiency of paleoclimate reconstruction. And the paleoclimate reconstruction efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of oil and gas exploration and development, and in particular to a method and device for reconstructing paleoclimate of hydrocarbon source rock pollen in a Cenozoic basin. Background Art

[0002] Currently, hydrocarbon-rich sags exist in many offshore basins, with the majority of crude oil and natural gas resources coming from organic-rich source rocks from the Eocene-Miocene. The development of these source rocks and the concentration of organic matter in these rocks are influenced by paleoclimate changes.

[0003] Among the related technologies, paleoclimate reconstruction is used to study paleoclimate evolution and its impact on source rock development. This has important scientific value for understanding the paleoclimate evolution laws in key geological historical periods, and is also of great significance for studying the organic matter enrichment mechanism of source rocks and the development laws of high-quality source rocks.

[0004] Related technologies can be used by technicians to reconstruct paleoclimate through manual calculations, but this requires a lot of human resources and is inefficient. Summary of the Invention

[0005] The present invention provides a method and device for reconstructing paleoclimate from hydrocarbon source rock pollen in Cenozoic basins, which is used to solve the defects in related technologies that technicians use manual calculations to reconstruct paleoclimate, which requires a large amount of human resources and is inefficient. The method realizes intelligent paleoclimate reconstruction, reduces the human resources required for paleoclimate reconstruction by related technologies, and improves the efficiency of paleoclimate reconstruction.

[0006] In a first aspect, the present invention provides a method for reconstructing paleoclimate from source rock pollen in a Cenozoic basin, comprising: Performing pollen identification on multiple source rock samples corresponding to multiple depth intervals in a single well in a Cenozoic basin to determine multiple pollen categories in each source rock sample and the relative content of each pollen category; For any of the source rock samples, according to each of the pollen categories in the source rock sample, the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to each of the pollen categories are searched in the created pollen paleoclimate database, and the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to each of the pollen categories are mutually verified. If the mutual verification is passed, the total relative content value corresponding to the target qualitative parameter category is calculated according to the qualitative parameter category and relative content corresponding to each of the pollen categories in the source rock sample, and the corresponding coexistence parameter interval is calculated according to the quantitative parameter extreme value corresponding to each of the pollen categories in the source rock sample; A TOC evolution chart of a single well in the Cenozoic basin is generated based on the total organic carbon TOC of each source rock sample, each depth segment, each relative content total value, and each coexistence parameter interval.

[0007] Optionally, the pollen paleoclimate database includes a plurality of rows of data, each row of data including a qualitative parameter category and a quantitative parameter extreme value corresponding to the pollen category; wherein: The qualitative parameter categories corresponding to the pollen categories include humidity categories and temperature zone categories, the humidity categories are mesophytic, marshy, hygrophytic or xerophytic, and the temperature zone categories are tropical, subtropical, temperate or frigid; The quantitative parameter extreme values ​​corresponding to the pollen categories include temperature extreme values ​​and precipitation extreme values, and the coexistence parameter intervals include coexistence temperature intervals and coexistence precipitation intervals.

[0008] Optionally, when the target qualitative parameter category includes tropical, subtropical, marshland and wetland, the total relative content value corresponding to the target qualitative parameter category includes a first relative content total value and a second relative content total value; The method of calculating the total relative content value corresponding to the target qualitative parameter category according to the qualitative parameter category and relative content corresponding to each of the pollen categories in the source rock sample includes: In the qualitative parameter categories corresponding to each of the pollen categories of the source rock sample, each first qualitative parameter category is determined to be tropical or subtropical in the temperature zone category, and each second qualitative parameter category is determined to be marshy or hygrophytic in the humidity category; Determining the pollen category corresponding to each of the first qualitative parameter categories as a first category; and determining the pollen category corresponding to each of the second qualitative parameter categories as a second category; The relative contents corresponding to each of the first categories are added together to obtain the total value of the first relative contents; and the relative contents corresponding to each of the second categories are added together to obtain the total value of the second relative contents.

[0009] Optionally, when the temperature extremes include the minimum and maximum annual average temperature values, and the precipitation extremes include the minimum and maximum annual average precipitation values, the corresponding coexistence parameter intervals are calculated based on the quantitative parameter extremes corresponding to each of the pollen categories in the source rock sample, including: Determine the maximum annual average temperature minimum value and the maximum annual average precipitation minimum value among the minimum annual average temperature values ​​and the minimum annual average precipitation minimum values ​​corresponding to each of the pollen categories of the source rock sample; and determine the minimum annual average temperature maximum value and the minimum annual average precipitation maximum value among the maximum annual average temperature values ​​and the maximum annual average precipitation values ​​corresponding to each of the pollen categories of the source rock sample; Construct an interval from the maximum annual average temperature minimum value to the minimum annual average temperature maximum value, and use it as the coexistence temperature interval; and construct an interval from the maximum annual average precipitation minimum value to the minimum annual average precipitation minimum value, and use it as the coexistence precipitation interval.

[0010] Optionally, generating a TOC evolution chart of a single well in the Cenozoic basin based on the total organic carbon (TOC) of each source rock sample, each depth segment, each relative content total value, and each coexistence parameter interval includes: respectively determining a characteristic parameter value for each of the coexistence parameter intervals; Based on the TOC of each source rock sample and each depth segment, a first curve is constructed showing how the TOC of the source rock changes with the depth of the single well formation; based on each relative content total value and each depth segment, a second curve is constructed showing how the relative content total value changes with the depth of the single well formation; and based on the characteristic parameter value of each coexistence parameter interval and each depth segment, a third curve is constructed showing how the characteristic parameter value changes with the depth of the single well formation; Based on the first curve, the second curve and the third curve, a chart including the first curve, the second curve and the third curve is constructed and used as the TOC evolution chart.

[0011] Optionally, the pollen identification is performed on a plurality of source rock samples corresponding to a plurality of depth sections in a single well in a Cenozoic basin to determine a plurality of pollen categories in each source rock sample and the relative content of each pollen category, including: Sampling multiple depth intervals of a single well in the Cenozoic basin to obtain initial source rock samples corresponding to each depth interval; Preprocessing the initial source rock samples corresponding to each of the depth sections to obtain each of the source rock samples; Each of the source rock samples is subjected to pollen identification to determine the multiple pollen categories in each of the source rock samples and the relative content of each pollen category.

[0012] Optionally, pre-processing the initial source rock sample corresponding to each depth segment to obtain each source rock sample includes: For the initial source rock sample corresponding to any of the depth segments, the initial source rock sample is crushed into sample particles with a set particle size, and the sample particles are acid-treated with high-temperature dilute hydrochloric acid and high-temperature hydrofluoric acid in sequence to obtain treated sample particles, the treated sample particles are washed with water until neutral, and placed in a centrifuge tube for centrifugal treatment to obtain centrifuged sample particles, heavy liquid and acetic acid aqueous solution are added to the centrifuged sample particles in the centrifuge tube, and after standing for a set period of time, the particles are washed with water until neutral to obtain neutral sample particles, a stainless steel sieve is used to remove impurities in the neutral sample particles to obtain sieved sample particles, the sieved sample particles are ultrasonically vibrated to obtain vibrated sample particles, the vibrated sample particles are washed and dried with a nylon sieve to obtain washed and dried sample particles, and the washed and dried sample particles are centrifugally dehydrated to obtain the source rock sample corresponding to the depth segment.

[0013] Optionally, performing pollen identification on each source rock sample to determine multiple pollen categories in each source rock sample and the relative content of each pollen category includes: For any of the source rock samples, a corresponding thin section is made according to the source rock sample, and the thin section is placed under a microscope for observation to determine all the pollen in the source rock sample and count the total number of pollen; if the total number of pollen is not greater than the preset threshold, it is determined that the source rock sample does not meet the requirements, and resampling is performed in the depth segment corresponding to the source rock sample to obtain a sample that meets the requirements; if the total number of pollen is greater than the preset threshold, it is determined that the source rock sample meets the requirements, and each pollen category in the source rock sample is determined according to each pollen in the source rock sample, and the number of pollen corresponding to each pollen category in the source rock sample is counted, and the ratio of the number of pollen corresponding to each pollen category in the source rock sample to the total number of pollen is determined as the relative content corresponding to each pollen category in the source rock sample.

[0014] Optionally, the pollen categories in the source rock sample include a first pollen category corresponding to lower plant pollen and a second pollen category corresponding to higher plant pollen; Alternatively, the pollen category in the source rock sample only refers to the second pollen category corresponding to higher plant pollen.

[0015] In a second aspect, the present invention provides a device for reconstructing paleoclimate from source rock pollen in a Cenozoic basin, comprising: An identification unit is used to perform pollen identification on a plurality of source rock samples corresponding to a plurality of depth sections in a single well in a Cenozoic basin, so as to determine a plurality of pollen categories in each source rock sample and the relative content of each pollen category; A search unit is used for searching, for any of the source rock samples, for each of the pollen categories in the source rock sample, in the created pollen paleoclimate database for the qualitative parameter category and the quantitative parameter extreme value corresponding to each of the pollen categories; A demonstration unit, for mutually demonstrating the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to each of the pollen categories; The first statistical unit is used for statistically analyzing the relative contents of target qualitative parameter categories according to the qualitative parameter categories and relative contents corresponding to each of the sporopollen categories in the source rock sample if the mutual demonstrations are passed; A second statistical unit is configured to calculate a corresponding coexistence parameter interval based on the extreme value of the quantitative parameter corresponding to each of the sporopollen categories in the source rock sample; A generating unit is used to generate a TOC evolution chart of a single well in the Cenozoic basin according to the total organic carbon TOC of each source rock sample, each depth segment, each relative content total value and each coexistence parameter interval.

[0016] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for reconstructing the paleoclimate of source rock pollen in the Cenozoic basin according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0017] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for reconstructing the paleoclimate of source rock pollen in a Cenozoic basin according to the first aspect or any corresponding embodiment thereof.

[0018] The pollen paleoclimate reconstruction method and device for hydrocarbon source rock in the Cenozoic basin provided by the present invention can perform pollen identification on multiple hydrocarbon source rock samples, determine the pollen identification data of each hydrocarbon source rock sample, that is, multiple pollen categories in each hydrocarbon source rock sample and the relative contents corresponding to different pollen categories, determine qualitative paleoclimate parameter data and quantitative paleoclimate parameter data of each hydrocarbon source rock sample based on the pollen identification data of each hydrocarbon source rock sample and the established pollen paleoclimate database, generate a TOC evolution map based on the qualitative paleoclimate parameter data and quantitative paleoclimate parameter data of each hydrocarbon source rock sample, realize intelligent paleoclimate reconstruction, reduce the human resources required for paleoclimate reconstruction using related technologies, reduce energy consumption, improve the efficiency of paleoclimate reconstruction, and reconstruct the paleoclimate evolution law during the sedimentary period of the hydrocarbon source rock, reveal the organic matter enrichment mechanism of the hydrocarbon source rock, and predict the favorable development layer section of relatively high-quality hydrocarbon source rock, providing assistance for the deployment and decision-making of the next step of oil and gas exploration. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or related technologies, the following is a brief introduction to the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flow chart of a method for reconstructing paleoclimate from source rock pollen in a Cenozoic basin provided in an embodiment of the present invention; Figure 2 A diagram showing paleoclimate data in a palynological paleoclimate database provided by an embodiment of the present invention; Figure 3 A TOC evolution chart provided by an embodiment of the present invention; Figure 4 A statistical diagram of the palynological families, genera, species, and their relative contents identified in 72 source rock samples from Well Y8 provided in an embodiment of the present invention; Figure 5 A qualitative and quantitative paleoclimate parameter map calculated from 72 source rocks in the Y8 well provided in an embodiment of the present invention; Figure 6 A schematic diagram of the structure of a device for reconstructing paleoclimate from source rock pollen in a Cenozoic basin provided by an embodiment of the present invention; Figure 7 A schematic structural diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0022] The following combination Figure 1-Figure 5 The present invention describes the method for paleoclimate reconstruction of source rocks and pollen in Cenozoic basins.

[0023] like Figure 1 As shown, this embodiment proposes a first method for reconstructing paleoclimate from source rock pollen in Cenozoic basins, which may include the following steps: S101. Perform pollen identification on multiple source rock samples corresponding to multiple depth sections in a single well in a Cenozoic basin to determine multiple pollen categories in each source rock sample and the relative content of each pollen category.

[0024] Among them, single well in Cenozoic basin refers to a single well in the Cenozoic basin.

[0025] Specifically, a depth segment refers to a layer segment within a certain depth range in a single well in a Cenozoic basin. Each depth segment can be a layer segment with a different depth range, and the depth range of each depth segment can be completely different and non-overlapping.

[0026] The source rock samples were collected from a single well in a Cenozoic basin at a single depth. Different source rock samples correspond to different depths.

[0027] The pollen category in a source rock sample refers to the pollen category corresponding to a pollen in the source rock sample, and specifically can be the family, genus, or species corresponding to the pollen. It should be noted that a source rock sample includes multiple pollen, each of which has a corresponding pollen category. A source rock sample contains multiple pollen categories corresponding to multiple pollen.

[0028] It should be noted that the relative content of a pollen type in a source rock sample refers to the ratio of the number of pollen corresponding to that type in the source rock sample to the total number of pollen in the source rock sample. This example can identify pollen of different families, genera, and species in multiple source rocks and calculate their relative content within the total pollen in a single source rock.

[0029] S102. For any source rock sample, according to each pollen category in the source rock sample, search the created pollen paleoclimate database for the qualitative parameter category and the quantitative parameter extreme value corresponding to each pollen category.

[0030] Optionally, the pollen paleoclimate database includes multiple rows of data, each row of data includes qualitative parameter categories and quantitative parameter extreme values ​​corresponding to the pollen categories; wherein: The qualitative parameter categories corresponding to the pollen categories include humidity category and temperature zone category. The humidity category is mesophytic, marshy, hygrophytic or xerophytic, and the temperature zone category is tropical, subtropical, temperate or frigid. The quantitative parameter extreme values ​​corresponding to the pollen categories include temperature extreme values ​​and precipitation extreme values, and the coexistence parameter intervals include coexistence temperature intervals and coexistence precipitation intervals.

[0031] like Figure 2As shown, this embodiment can establish a database of paleoclimate qualitative and quantitative parameters of a total of 183 different families, genera, and species of pollen since the Paleogene, i.e., a pollen paleoclimate database. This embodiment can determine the paleoclimate parameters of each family, genera, and species of pollen by a large amount of research literature and a method of using the present to analyze the past. Among them, the qualitative parameters are the mesophytic, marshy, hygrophytic, and xerophytic categories that reflect humidity and the tropical, subtropical, temperate, and frigid categories that reflect temperature. The relative content changes of the pollen of each category reflect the changing patterns of temperature and humidity in the paleoclimate. Among them, the quantitative parameters are the average annual temperature and average annual precipitation that directly reflect temperature. The changes in temperature and humidity in the paleoclimate are reflected according to the height of their specific values.

[0032] It should be noted that most of the pollen species since the Paleogene can find corresponding species in the present plant pollen. According to the climatic zone where the pollen species correspond to the present plants, the method of using the present to explain the past is used, combined with previous studies, the pollen plants are divided into tropical-subtropical, temperate and cold zone categories reflecting temperature, and mesophytic, hygrophytic, marsh-like and xerophytic categories reflecting humidity, in order to establish the qualitative paleoclimate parameters of each family, genus and species of pollen: the percentage content reflecting the humidity and temperature categories. Most of the pollen plants earlier than the Paleogene cannot find corresponding genera and species in the present plant pollen, and therefore their paleoclimate parameters cannot be determined by the method of using the present to explain the past. Therefore, the database and this embodiment can only use the hydrocarbon source rock pollen since the Paleogene to reconstruct the qualitative and quantitative parameters of the paleoclimate.

[0033] The coexistence parameter range refers to the parameter range in which pollen corresponding to different pollen types in a source rock sample can adapt to survive together.

[0034] Specifically, the coexistence temperature range refers to the temperature range in which pollen corresponding to different pollen types in a source rock sample can adapt to survive together. The coexistence precipitation range refers to the precipitation range in which pollen corresponding to different pollen types in a source rock sample can adapt to survive together.

[0035] S103. Mutually verify the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to each pollen category.

[0036] Specifically, for any pollen category in the source rock sample, this embodiment can mutually verify the qualitative parameter category and quantitative parameter extreme value corresponding to the pollen category. If the qualitative parameter category and quantitative parameter extreme value corresponding to the pollen category pass the verification, it is determined that the qualitative parameter category and quantitative parameter extreme value corresponding to the pollen category are in line with reality and can be directly used for subsequent processing. If the qualitative parameter category and quantitative parameter extreme value corresponding to the pollen category fail to pass the verification, they can be corrected and used for subsequent processing after correction.

[0037] Specifically, in this embodiment, a technician can consult relevant knowledge to mutually verify the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to the pollen categories. A relevant artificial intelligence model can also be used to mutually verify the matching degree between the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to the pollen categories.

[0038] S104. If the mutual demonstrations are all passed, the total relative content value corresponding to the target qualitative parameter category is calculated based on the qualitative parameter category and relative content corresponding to each pollen category in the source rock sample.

[0039] It should be noted that, for any source rock sample, this embodiment calculates the total relative content corresponding to the target qualitative parameter category based on the qualitative parameter category and relative content corresponding to each pollen category in the source rock sample only when the qualitative parameter category and quantitative parameter extreme value corresponding to each pollen category in the source rock sample are mutually verified.

[0040] The target qualitative parameter category may include one or more qualitative parameter categories, which are used as representative qualitative parameter categories to further characterize the changing patterns of temperature and humidity.

[0041] Optionally, when the target qualitative parameter category includes tropical, subtropical, marshland, and hygrophila, the relative content total values ​​corresponding to the target qualitative parameter category include a first relative content total value and a second relative content total value. In this case, step S104 may include: In the qualitative parameter categories corresponding to each pollen category of the source rock sample, each first qualitative parameter category is determined to be tropical or subtropical for the temperature zone category, and each second qualitative parameter category is determined to be marshy or hygrophytic for the humidity category; Determining the pollen category corresponding to each first qualitative parameter category as the first category; and determining the pollen category corresponding to each second qualitative parameter category as the second category; The relative contents corresponding to each first category are summed to obtain a first relative content total value; and the relative contents corresponding to each second category are summed to obtain a second relative content total value.

[0042] Specifically, if the temperature zone category in the qualitative parameter category corresponding to a pollen category is tropical or subtropical, then the qualitative parameter category corresponding to the pollen category is the first qualitative parameter category. If the humidity zone category in the qualitative parameter category corresponding to a pollen category is marshy or hygrophytic, then the qualitative parameter category corresponding to the pollen category is the second qualitative parameter category.

[0043] It can be understood that if the temperature zone category in the qualitative parameter category corresponding to a certain pollen category is tropical or subtropical, and the humidity zone category in the qualitative parameter category corresponding to the pollen category is marshland or hygrophilic, then the qualitative parameter category corresponding to the pollen category is regarded as both the first qualitative parameter category and the second qualitative parameter category.

[0044] The first category is the pollen category corresponding to the first qualitative parameter category, and the second category is the pollen category corresponding to the second qualitative parameter category. For example, if the qualitative parameter category corresponding to a pollen category is the first qualitative parameter category, then the pollen category is the first category. For another example, if the qualitative parameter category corresponding to a pollen category is the second qualitative parameter category, then the pollen category is the second category. For another example, if the qualitative parameter category corresponding to a pollen category is considered both the first qualitative parameter category and the second qualitative parameter category, then the pollen category is considered both the first category and the second category.

[0045] Specifically, the relative content of the first category is the ratio of the number of pollen corresponding to the first category in a source rock sample to the total number of pollen in the source rock sample. The relative content of the second category is the ratio of the number of pollen corresponding to the second category in a source rock sample to the total number of pollen in the source rock sample. It should be noted that, for any source rock sample, this embodiment can add up the relative contents corresponding to each first category in the source rock sample to obtain a first relative content total value, and add up the relative contents corresponding to each second category in the source rock sample to obtain a second relative content total value.

[0046] It is understood that each source rock sample has a corresponding first relative content total value and a corresponding second relative content total value. For example, when there is a first source rock sample and a second source rock sample, the first source rock sample has a corresponding first relative content total value and a corresponding second relative content total value, and the second source rock sample also has a corresponding first relative content total value and a corresponding second relative content total value.

[0047] S105. Count the corresponding coexistence parameter intervals based on the extreme values ​​of the quantitative parameters corresponding to each pollen category in the source rock sample.

[0048] Specifically, for any source rock sample, this embodiment can calculate the corresponding coexistence parameter interval based on the extreme value of the quantitative parameter corresponding to each sporopollen category in the source rock sample.

[0049] Optionally, in the pollen paleoclimate reconstruction method for source rocks in other Cenozoic basins proposed in this embodiment, the quantitative parameter extremes corresponding to the pollen categories include temperature extremes and precipitation extremes, and the coexistence parameter intervals include coexistence temperature intervals and coexistence precipitation intervals. When the temperature extremes include the minimum and maximum annual average temperature values, and the precipitation extremes include the minimum and maximum annual average precipitation values, step S104 may include: Among the minimum annual average temperature values ​​and the minimum annual average precipitation values ​​corresponding to each pollen type of the source rock sample, determine the maximum minimum annual average temperature value and the maximum minimum annual average precipitation value; and among the maximum annual average temperature values ​​and the maximum annual average precipitation values ​​corresponding to each pollen type of the source rock sample, determine the minimum maximum annual average temperature value and the minimum maximum annual average precipitation value; An interval from the largest annual average temperature minimum to the smallest annual average temperature maximum is constructed as the coexistence temperature interval; and an interval from the largest annual average precipitation minimum to the smallest annual average precipitation minimum is constructed as the coexistence precipitation interval.

[0050] Specifically, for any source rock sample, this embodiment can determine the maximum annual average temperature minimum value among the annual average temperature minimum values ​​corresponding to each pollen category of the source rock sample, and determine the maximum annual average precipitation minimum value among the annual average precipitation minimum values ​​corresponding to each pollen category of the source rock sample. This embodiment can determine the minimum annual average temperature maximum value among the annual average temperature maximum values ​​corresponding to each pollen category of the source rock sample, and determine the minimum annual average precipitation maximum value among the annual average precipitation maximum values ​​corresponding to each pollen category of the source rock sample. Afterwards, this embodiment can determine the interval from the maximum annual average temperature minimum value to the minimum annual average temperature maximum value as the coexisting temperature interval. The interval from the maximum annual average precipitation minimum value to the minimum annual average precipitation maximum value can be determined as the coexisting precipitation interval.

[0051] S106. Generate a TOC evolution chart for a single well in a Cenozoic basin based on the total organic carbon (TOC) of each source rock sample, each depth interval, each relative content value, and each coexistence parameter interval.

[0052] It should be noted that the TOC evolution chart can include the correspondence between depth segments, TOC, total relative content values ​​and coexistence parameter intervals.

[0053] Specifically, this embodiment can first detect the TOC of each source rock sample, and construct a TOC evolution chart based on the TOC of each source rock sample, the depth segment, the total relative content value and the coexistence parameter interval corresponding to each source rock sample. The TOC evolution chart can show the changing trends of TOC, the total relative content value and the coexistence parameter interval with the depth segment.

[0054] Optionally, step S106 may include: Determine the characteristic parameter value of each coexistence parameter interval respectively; Based on the TOC of each source rock sample and each depth segment, a first curve is constructed showing how the TOC of the source rock changes with the formation depth of the single well; based on each total relative content value and each depth segment, a second curve is constructed showing how the total relative content value changes with the formation depth of the single well; and based on the characteristic parameter value of each coexistence parameter interval and each depth segment, a third curve is constructed showing how the characteristic parameter value changes with the formation depth of the single well; Based on the first curve, the second curve and the third curve, a plate including the first curve, the second curve and the third curve is constructed and used as the TOC evolution plate.

[0055] Optionally, for any coexistence parameter interval, this embodiment may determine an average value of two endpoint values ​​in the coexistence parameter interval as the characteristic parameter value.

[0056] Optionally, in this embodiment, after the coexisting temperature interval and coexisting precipitation interval corresponding to the source rock sample are obtained, the average temperature of the two endpoint temperatures in the coexisting temperature interval can be calculated, and the average precipitation of the two endpoint precipitations in the coexisting precipitation interval can be used as the characteristic parameter value of the coexisting temperature interval, and the average precipitation can be used as the characteristic parameter value of the coexisting precipitation interval. The average temperature and average precipitation are used to represent the coexisting temperature interval and the coexisting precipitation interval. Figure 3 The TOC evolution chart shown includes the TOC of the source rock, the total relative content, the average temperature and the average precipitation variation range with the formation depth of a single well. Figure 3 In the first row of data, the tropical / subtropical component (%) represents the total value of the first relative content, the marsh-wetland component (%) represents the total value of the second relative content, T_average represents the average temperature, and P_average represents the average precipitation.

[0057] like Figure 3As shown, this embodiment can perform a linear fit on the TOC of the source rock corresponding to multiple consecutive depth segments to obtain a TOC variation curve of the source rock TOC as the depth of a single well changes. This curve is the first curve. A linear fit is performed on the total relative content values ​​corresponding to multiple consecutive depth segments to obtain a variation curve of the total relative content values ​​corresponding to tropical / subtropical components, i.e., the second curve. The average temperature and average precipitation are determined in the coexisting temperature interval and coexisting precipitation interval corresponding to each source rock sample, respectively. Based on the depth segment corresponding to each source rock sample, a linear fit is performed on the average temperature corresponding to each source rock sample, and a linear fit is performed on the average precipitation corresponding to each source rock sample to obtain the corresponding parameter variation curve, i.e., the third curve.

[0058] Specifically, paleoclimate controls paleovegetation, thereby controlling the input of organic matter into source rocks. The TOC chart of this example helps reveal the relationship between source rock quality and paleoclimate change, thereby clarifying the climatic conditions conducive to source rock development and providing data support for source rock genetic mechanism research and distribution prediction.

[0059] It should be noted that this embodiment can be based on a rapid reconstruction method of source rock pollen paleoclimate that combines qualitative and quantitative methods. It can quickly and reasonably reconstruct the paleoclimate evolution laws during the source rock deposition period and reveal the influence of paleoclimate factors on the enrichment of organic matter in source rocks, predict favorable source rock development layers, serve oil and gas exploration and development decision-making, and has great promotion and application value.

[0060] The pollen paleoclimate reconstruction method for hydrocarbon source rocks in Cenozoic basins proposed in this embodiment can perform pollen identification on multiple hydrocarbon source rock samples, determine the pollen identification data of each hydrocarbon source rock sample, that is, the multiple pollen categories in each hydrocarbon source rock sample and the relative contents of different pollen categories. Based on the pollen identification data of each hydrocarbon source rock sample and the established pollen paleoclimate database, qualitative paleoclimate parameter data and quantitative paleoclimate parameter data of each hydrocarbon source rock sample are determined. Based on the qualitative paleoclimate parameter data and quantitative paleoclimate parameter data of each hydrocarbon source rock sample, a TOC evolution map is generated, realizing intelligent paleoclimate reconstruction, reducing the human resources required for paleoclimate reconstruction using related technologies, reducing energy consumption, and improving the efficiency of paleoclimate reconstruction. It can also reconstruct the paleoclimate evolution laws during the hydrocarbon source rock deposition period, reveal the organic matter enrichment mechanism of hydrocarbon source rocks, and predict favorable development intervals of high-quality hydrocarbon source rocks, providing assistance for the deployment and decision-making of the next step of oil and gas exploration.

[0061] based on Figure 1 This embodiment proposes a second method for reconstructing paleoclimate from source rock pollen in Cenozoic basins. In this method, step S101 may include: Sampling was performed at multiple depth intervals in a single well in a Cenozoic basin to obtain initial source rock samples corresponding to each depth interval; Pre-processing the initial source rock samples corresponding to each depth section to obtain each source rock sample; Each source rock sample was subjected to pollen identification to determine the multiple pollen categories in each source rock sample and the relative content of each pollen category.

[0062] Optionally, the above-mentioned pre-processing of the initial source rock samples corresponding to each depth section to obtain each source rock sample includes: For the initial source rock sample corresponding to any depth segment, the initial source rock sample is crushed into sample particles with a set particle size, and the sample particles are acid-treated with high-temperature dilute hydrochloric acid and high-temperature hydrofluoric acid in sequence to obtain treated sample particles, the treated sample particles are washed with water until neutral, and placed in a centrifuge tube for centrifugal treatment to obtain centrifuged sample particles, heavy liquid and acetic acid aqueous solution are added to the centrifuged sample particles in the centrifuge tube, and after standing for a set time, they are washed with water until neutral to obtain neutral sample particles, a stainless steel sieve is used to remove impurities in the neutral sample particles to obtain sieved sample particles, the sieved sample particles are ultrasonically vibrated to obtain vibrated sample particles, the vibrated sample particles are washed and dried with a nylon sieve to obtain washed and dried sample particles, the washed and dried sample particles are centrifuged and dehydrated to obtain the source rock sample corresponding to the depth segment.

[0063] Specifically, in this embodiment, the source rock sample can be crushed to a particle size of 0.5 mm. The sample particles are then treated with dilute hydrochloric acid (20% concentration) and hydrofluoric acid heated to 80°C. After treatment, the sample is washed with water until neutral. Heavy liquid flotation is then performed: the neutralized sample is transferred to a centrifuge tube and centrifuged for 5-10 minutes. A heavy liquid (relative density 2.0-2.25) is added, followed by a 1% aqueous acetic acid solution. The sample is allowed to stand for 12 hours and then washed with water until neutral. The sample is then sieved and washed using a stainless steel sieve with a pore size of 200 μm to remove impurities, followed by ultrasonic vibration. The sample is then washed and dried using a nylon sieve with a pore size of less than 10 μm, and then centrifuged for dehydration.

[0064] Optionally, the pollen identification is performed on each source rock sample to determine multiple pollen categories and the relative content of each pollen category in each source rock sample, including: For any source rock sample, a corresponding thin section is made according to the source rock sample, and the thin section is placed under a microscope for observation to determine all the pollen in the source rock sample and count the total number of pollen; if the total number of pollen is not greater than the preset threshold, the source rock sample is determined to be unqualified, and resampling is performed in the depth section corresponding to the source rock sample to obtain a sample that meets the requirements; if the total number of pollen is greater than the preset threshold, the source rock sample is determined to be qualified, and each pollen category in the source rock sample is determined based on each pollen in the source rock sample, and the number of pollen corresponding to each pollen category in the source rock sample is counted, and the ratio of the number of pollen corresponding to each pollen category in the source rock sample to the total number of pollen is determined as the relative content corresponding to each pollen category in the source rock sample.

[0065] It should be noted that this embodiment allows for the preparation of thin sections corresponding to source rock samples for microscopic observation, identification, and statistics. If the number of pollen grains identified in a single source rock sample exceeds 60, the percentage of pollen belonging to each family, genus, and species is calculated. Source rock samples with fewer than 60 pollen grains are not used due to significant systematic errors.

[0066] Optionally, the pollen categories in the source rock sample include a first pollen category corresponding to lower plant pollen and a second pollen category corresponding to higher plant pollen; Alternatively, the pollen category in source rock samples refers only to the second pollen category corresponding to higher plant pollen.

[0067] Among them, higher plants refer to ferns, gymnosperms, and angiosperms, and higher plant pollen refers to the pollen of higher plants. The second pollen category is the pollen category corresponding to the higher plant pollen.

[0068] Among them, lower plants refer to algae and other related plants. Lower plant pollen refers to the pollen of lower plants. The first pollen category is the pollen category corresponding to lower plant pollen.

[0069] Specifically, each pollen category in the source rock sample of this embodiment may include a first pollen category corresponding to lower plant pollen and a second pollen category corresponding to higher plant pollen.

[0070] Specifically, each pollen category in the source rock sample of this embodiment may also refer only to the second pollen category corresponding to the higher plant pollen. In this case, when performing pollen identification on the source rock sample of this embodiment, each pollen in the source rock sample may be first identified, each higher plant pollen may be screened out, and then the second pollen category corresponding to each higher plant pollen may be determined.

[0071] The inventors of the present invention have found through research that the influence of lower plant pollen on source rock formation and paleoclimate reconstruction is relatively small, and the processing accuracy of qualitative paleoclimate data and quantitative paleoclimate data of lower plant pollen is relatively low. Therefore, in the process of paleoclimate reconstruction based on pollen identification data of source rock samples, this embodiment does not need to consider the first pollen category corresponding to lower plant pollen in the source rock sample, but only considers the second pollen category corresponding to higher plant pollen in the source rock sample, effectively reducing the amount of calculation for qualitative paleoclimate parameter data and quantitative paleoclimate parameter data, and can effectively improve data processing efficiency and reduce computing resource consumption while ensuring accuracy.

[0072] The pollen paleoclimate reconstruction method for source rock in the Cenozoic basin proposed in this embodiment can realize the pretreatment and pollen identification of source rock samples, determine the relative content of each pollen category and different pollen categories in the source rock samples, effectively ensure the subsequent determination of qualitative and quantitative paleoclimate parameter data, and ensure the construction and accuracy of the TOC evolution map.

[0073] To better illustrate the process of the embodiment of the present invention, Example 1 is provided for introduction. Example 1 includes the following steps: Step 1): Establish a database of qualitative and quantitative climate parameters for different families, genera, and species of pollen in offshore basins since the Paleogene.

[0074] S1.1: If Figure 2 As shown in the figure, qualitative paleoclimate parameters were established for a total of 183 different families, genera, and species of pollen. After extensive literature research, all pollen plants surveyed were divided into tropical-subtropical, temperate, and boreal categories reflecting temperature, and mesophytic, hygrophytic, marshy, and xerophytic categories reflecting humidity, in order to establish qualitative humidity and temperature categories for each family, genera, and species of pollen.

[0075] S1.2: If Figure 2 As shown in the figure, a total of 183 quantitative paleoclimate parameters were established for pollen from different families, genera, and species. Based on the current average annual temperature and average annual precipitation ranges of the corresponding pollen plant families, genera, and species, the quantitative humidity (precipitation) and temperature data ranges for each family, genus, and species were established.

[0076] Among them, due to the limitations of literature data, the database can be further expanded to cover more qualitative and quantitative paleoclimate parameters of palynaceae, genera, and species.

[0077] Among them, due to different research purposes, quantitative paleoclimate parameters can be further expanded to cover monthly average temperature / precipitation, coldest monthly average temperature / precipitation, hottest monthly average temperature / precipitation, etc.

[0078] Step 2) Identify the pollen of different families, genera, and species in the Paleocene-Pliocene source rocks of multiple offshore basins and calculate their relative abundance.

[0079] S2.1: Pre-process source rock samples.

[0080] S2.2: Identify and count the pollen of source rocks. For example, among the 72 source rock samples from the typical well Y8 in the Qiongdongnan Basin, 22 pollen of different families, species and genera were identified and their relative contents were counted. Some of the statistical results are as follows: Figure 4 shown.

[0081] Step 3): Calculate the paleoclimate qualitative and quantitative parameters of single well source rock samples.

[0082] S3.1: A tool has been independently developed to automatically identify paleoclimate parameters for plant pollen. For example, by inputting a database of qualitative and quantitative climatic parameters for pollen from various families, genera, and species in the offshore basin since the Paleogene, and the relative abundance data for 22 different families, genera, and species identified from 72 source rocks in the basin's representative well, Well Y8, into the tool, the tool can automatically match and output qualitative and quantitative paleoclimate parameters for all source rock samples from a single well. For example, pollen from 21 different families, genera, and species identified from the 72 source rocks is summed according to the database's tropical-subtropical, temperate, frigid, mesophytic, hygrophytic-swampy, and xerophytic categories. The percentage of the tropical-subtropical sum (Ai) is used to reflect temperature; a higher percentage of the tropical-subtropical sum indicates higher temperature; and the percentage of the hygrophytic-swampy sum (Bi) is used to reflect humidity; a higher percentage of the hygrophytic-swampy sum indicates higher humidity.

[0083] The total percentage of tropical-subtropical categories = sum(A1+A2+...+A21).

[0084] The percentage of the sum of the hygrophytic and marshy categories = sum(B1+B2+...+B21).

[0085] A1-A21 represents the percentage of pollen from each family, genera, and species classified as tropical-subtropical; B1-B21 represents the percentage of pollen from each family, genera, and species classified as hygrophytic-marsh-like. A higher percentage of the sum of tropical-subtropical types indicates a higher temperature; a higher percentage of the sum of hygrophytic-marsh-like types indicates a higher humidity (precipitation).

[0086] S3.2: The pollen samples from 21 different families, genera, and species identified in the 72 source rocks of Well Y8 were automatically matched to the annual average temperature and precipitation data ranges determined in the database using the "Automatic Identification Tool for Plant Pollen Paleoclimate Parameters." The coexistence factor analysis method for different pollen plants from 21 different families, genera, and species was used to determine the annual average temperature and precipitation ranges for each of the 72 source rock samples. The annual average temperature and precipitation for a single source rock sample were calculated as follows: Average annual temperature range = (T min ~T max ); Average annual precipitation range = (P min ~P max ).

[0087] Among them, T min = Max(Min t1, Min t2,...,Min t 21 ), i is the annual average temperature range of each family, genus, and species of pollen plants, Min t1~t 21 The minimum annual temperature range of each family, genus, and species of palynological plants was identified for a single source rock sample; T max =Min (Max t1, Max t2,..., Max t 21 ), i is the annual average temperature range of each family, genus, and species of palynological plants in a single source rock, Max t1~t 21 The maximum value of the annual average temperature range of each family, genus, and species of palynological plants was identified for a single source rock sample.

[0088] Among them, P min = Max(Min p1, Min p2,..., Min p 21 ), i is the range of annual average precipitation of each family, genus, and species of palynological plants in a single source rock, Min p1~p 21 The minimum value of the annual average precipitation range of each family, genus, and species of palynological plants was identified for a single source rock sample. max =Min (Max p1, Max p2,..., Max p 21 ), i is the range of annual average precipitation of each family, genus, and species of palynological plants in a single source rock, Max p1~p 21 The maximum value of the annual average precipitation range of each family, genus, and species of palynological plants in a single source rock was identified for the source rock samples.

[0089] The average annual temperature range and average annual precipitation of a single source rock sample can also be used to represent the average annual temperature T average and the average annual precipitation P average .in: Average annual temperature T average =(T min +T max ) / 2; Average annual precipitation average =(P min +P max ) / 2.

[0090] The calculated annual average temperature range (T min ~T max ) and average value T average , annual average precipitation range (P min ~P max ) and the average value P average like Figure 5 shown. Figure 5 The data for the tropical-subtropical component column represents the number of pollen from all source rock samples with a tropical or subtropical temperature zone. The data for the temperate component represents the number of pollen from all source rock samples with a temperate temperature zone. The data for the marsh-hygrophyte component column represents the number of pollen from all source rock samples with a marsh-hygrophyte humidity zone. It should be noted that some higher plants prefer humidity while others tolerate drought. Those that prefer humidity are classified as marsh-hygrophytes, those that tolerate drought are classified as xerophytes, and those in between are classified as mesophytes. Figure 5 The Mesozoic component sequence data is the number of pollen with Mesozoic drought and wet preference among all the pollen in the source rock samples. Figure 5 The data of the xerophytic group are the number of xerophytic pollen in all the pollen of the source rock samples, and the degree of drought-wet preference is the number of xerophytic pollen.

[0091] Step 4): Establish paleoclimate and TOC evolution profiles of source rocks to reveal paleoclimate factors that are conducive to the enrichment of organic matter in source rocks.

[0092] S3.1: The percentage of tropical-subtropical categories reflecting temperature, the percentage of hygrophytic-marsh categories reflecting humidity, and the quantitative annual temperature range (T) were calculated using spores of 21 different families, genera, and species from 72 source rock samples from Well Y8. min ~T max ) or the average annual temperature T average , annual average precipitation range (P min ~P max ) or average annual precipitation P average , we can establish the paleoclimate evolution profile of the Oligocene-Miocene source rocks in Well Y8, such as Figure 3 shown.

[0093] S3.2: Using the TOC values ​​measured from multiple source rock samples from a single well, we established TOC evolution profiles for source rocks at different depths and geological ages. The results indicate that during the deposition of the source rocks in the Lower Oligocene Yacheng Formation 2 and Lower Miocene Sanya Formation 2, the temperature and humidity were relatively high. Among the quantitative climate parameters, the average annual temperature (T average Average 20.0℃), high annual precipitation (P average In conclusion, at least in the northern South China Sea climate zone, the relatively high temperature (>19°C) and high precipitation (>1900) are conducive to the development of source rocks and the accumulation of organic matter.

[0094] Specifically, this embodiment can use the percentage of tropical-subtropical categories that qualitatively reflect temperature, the percentage of hygrophytic-marsh categories that reflect humidity, and the quantitative annual average temperature range (T min ~T max ) or the average annual temperature T average , annual average precipitation range (P min ~P max ) or average annual precipitation P average , it is possible to establish paleoclimate evolution profiles of source rocks at different depths and geological ages in a single well.

[0095] Using TOC values ​​measured from a series of source rock samples from a single well, we established TOC profiles of source rock at different depths and geological ages. Source rock TOC values ​​were obtained by testing source rock samples crushed to 200 mesh using a Leco CS-344 carbon-sulfur analyzer.

[0096] It should be noted that in many hydrocarbon-rich sags in offshore basins, the majority of crude oil and natural gas resources come from organic-rich source rocks from the Eocene-Miocene. The development of source rocks and the enrichment of organic matter are influenced by multiple factors, including paleoclimate, paleobiology, paleoenvironment, and paleotectonics.

[0097] Research has shown that algal development is significantly influenced by paleoclimatic factors such as temperature. The evolution of paleotemperature and paleoprecipitation in source rocks and their impact on source rock development are not only of great scientific value for studying paleoclimatic evolution during the critical Eocene-Miocene geological period, but also crucial for understanding the mechanisms of organic matter enrichment in source rocks and the development of high-quality source rocks.

[0098] Related technologies for paleoclimate reconstruction during the source rock deposition period primarily employ qualitative methods. Qualitative paleoclimate reconstruction involves using major element and clay mineral indices to reflect the physical and chemical strength of the provenance area, and thus the paleoclimate. Qualitative paleoclimate reconstruction also involves classifying pollen plants based on their dry-wet and cold-heat preferences, and using changes in the relative abundance of these ecological habit classifications to reflect paleoclimate.

[0099] However, these qualitative paleoclimate reconstruction methods can only reflect paleoclimate trends based on relative changes in temperature and precipitation, hindering inter-well and inter-basin paleoclimate comparisons. With the advancement of source rock paleoclimate research, relevant technologies have enabled quantitative paleoclimate reconstruction, but this is labor-intensive and prone to errors due to manual calculations.

[0100] This embodiment addresses the problems existing in both qualitative and quantitative paleoclimate reconstruction methods. Based on the relative content of all species and pollen in all hydrocarbon source samples from a single well, quantitative paleoclimate parameters such as the average annual temperature and average annual precipitation, as well as qualitative paleoclimate parameters such as the content of hygrophilic / xerophilic components and the content of tropical-subtropical / temperate components, can be determined for all hydrocarbon source rock samples from a single well. This solves the problem of the lack of horizontal comparison in qualitative methods and the high workload of quantitative methods. It also allows the climate evolution results output by the two methods to be mutually verified, thereby improving the reliability of paleoclimate reconstruction results. This method will provide assistance for paleoclimate research during the sedimentary period of hydrocarbon source rocks and the study of the mechanism of organic matter enrichment in hydrocarbon source rocks.

[0101] In this embodiment, the established source rock paleoclimate profile and TOC profile can be coupled for analysis to reveal the favorable temperature and humidity ranges for source rock sections with higher TOC. In addition, based on the specific values ​​of qualitative climate parameters such as annual temperature and precipitation, paleoclimate comparisons of different sags and basins can be achieved.

[0102] like Figure 6 As shown, this embodiment proposes a device for reconstructing paleoclimate from source rock pollen in a Cenozoic basin, which may include: Identification unit 601 is used to perform pollen identification on multiple source rock samples corresponding to multiple depth sections in a single well in a Cenozoic basin, so as to determine multiple pollen categories in each source rock sample and the relative content of each pollen category; A search unit 602 is configured to search, for any source rock sample, for each pollen category in the source rock sample, in the created pollen paleoclimate database for the qualitative parameter category and the quantitative parameter extreme value corresponding to each pollen category; The demonstration unit 603 is used to mutually demonstrate the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to each pollen category; The first statistical unit 604 is used to calculate the total relative content value corresponding to the target qualitative parameter category based on the qualitative parameter category and relative content corresponding to each sporopollen category in the source rock sample if the mutual demonstration is passed; The second statistical unit 605 is used to count the corresponding coexistence parameter interval according to the extreme value of the quantitative parameter corresponding to each sporopollen category in the source rock sample; The generating unit 606 is used to generate a TOC evolution chart of a single well in the Cenozoic basin based on the total organic carbon TOC of each source rock sample, each depth segment, each relative content total value and each coexistence parameter interval.

[0103] It should be noted that the processing of the identification unit 601, the search unit 602, the demonstration unit 603, the first statistical unit 604, the second statistical unit 605 and the generation unit 606 and the beneficial effects thereof can be referred to in detail. Figure 1 Steps S101 to S105 in the above are not described in detail.

[0104] Optionally, the pollen paleoclimate database includes multiple rows of data, each row of data includes qualitative parameter categories and quantitative parameter extreme values ​​corresponding to the pollen categories; wherein: The qualitative parameter categories corresponding to the pollen categories include humidity category and temperature zone category. The humidity category is mesophytic, marshy, hygrophytic or xerophytic, and the temperature zone category is tropical, subtropical, temperate or frigid. The quantitative parameter extreme values ​​corresponding to the pollen categories include temperature extreme values ​​and precipitation extreme values, and the coexistence parameter intervals include coexistence temperature intervals and coexistence precipitation intervals.

[0105] Optionally, when the target qualitative parameter category includes tropical, subtropical, marshland and hygrophila, the total relative content value corresponding to the target qualitative parameter category includes a first relative content total value and a second relative content total value; The first statistical unit 604 is further configured to: In the qualitative parameter categories corresponding to each pollen category of the source rock sample, each first qualitative parameter category is determined to be tropical or subtropical for the temperature zone category, and each second qualitative parameter category is determined to be marshy or hygrophytic for the humidity category; Determining the pollen category corresponding to each first qualitative parameter category as the first category; and determining the pollen category corresponding to each second qualitative parameter category as the second category; The relative contents corresponding to each first category are summed to obtain a first relative content total value; and the relative contents corresponding to each second category are summed to obtain a second relative content total value.

[0106] Optionally, when the temperature extremes include the annual average temperature minimum and the annual average temperature maximum, and the precipitation extremes include the annual average precipitation minimum and the annual average precipitation maximum, the second statistical unit 605 is further configured to: Among the minimum annual average temperature values ​​and the minimum annual average precipitation values ​​corresponding to each pollen type of the source rock sample, determine the maximum minimum annual average temperature value and the maximum minimum annual average precipitation value; and among the maximum annual average temperature values ​​and the maximum annual average precipitation values ​​corresponding to each pollen type of the source rock sample, determine the minimum maximum annual average temperature value and the minimum maximum annual average precipitation value; An interval from the largest annual average temperature minimum to the smallest annual average temperature maximum is constructed as the coexistence temperature interval; and an interval from the largest annual average precipitation minimum to the smallest annual average precipitation minimum is constructed as the coexistence precipitation interval.

[0107] Optionally, the generating unit 606 is further configured to: Determine the characteristic parameter value of each coexistence parameter interval respectively; Based on the TOC of each source rock sample and each depth segment, a first curve is constructed showing how the TOC of the source rock changes with the formation depth of the single well; based on each total relative content value and each depth segment, a second curve is constructed showing how the total relative content value changes with the formation depth of the single well; and based on the characteristic parameter value of each coexistence parameter interval and each depth segment, a third curve is constructed showing how the characteristic parameter value changes with the formation depth of the single well; Based on the first curve, the second curve and the third curve, a plate including the first curve, the second curve and the third curve is constructed and used as the TOC evolution plate.

[0108] Optionally, the identification unit 601 is further configured to: Sampling was performed at multiple depth intervals in a single well in a Cenozoic basin to obtain initial source rock samples corresponding to each depth interval; Pre-processing the initial source rock samples corresponding to each depth section to obtain each source rock sample; Each source rock sample was subjected to pollen identification to determine the multiple pollen categories in each source rock sample and the relative content of each pollen category.

[0109] Optionally, the identification unit 601 is further configured to: For the initial source rock sample corresponding to any depth segment, the initial source rock sample is crushed into sample particles with a set particle size, and the sample particles are acid-treated with high-temperature dilute hydrochloric acid and high-temperature hydrofluoric acid in sequence to obtain treated sample particles, the treated sample particles are washed with water until neutral, and placed in a centrifuge tube for centrifugal treatment to obtain centrifuged sample particles, heavy liquid and acetic acid aqueous solution are added to the centrifuged sample particles in the centrifuge tube, and after standing for a set time, they are washed with water until neutral to obtain neutral sample particles, a stainless steel sieve is used to remove impurities in the neutral sample particles to obtain sieved sample particles, the sieved sample particles are ultrasonically vibrated to obtain vibrated sample particles, the vibrated sample particles are washed and dried with a nylon sieve to obtain washed and dried sample particles, the washed and dried sample particles are centrifuged and dehydrated to obtain the source rock sample corresponding to the depth segment.

[0110] Optionally, the identification unit 601 is further configured to: For any source rock sample, a corresponding thin section is made according to the source rock sample, and the thin section is placed under a microscope for observation to determine all the pollen in the source rock sample and count the total number of pollen; if the total number of pollen is not greater than the preset threshold, the source rock sample is determined to be unqualified, and resampling is performed in the depth section corresponding to the source rock sample to obtain a sample that meets the requirements; if the total number of pollen is greater than the preset threshold, the source rock sample is determined to be qualified, and each pollen category in the source rock sample is determined based on each pollen in the source rock sample, and the number of pollen corresponding to each pollen category in the source rock sample is counted, and the ratio of the number of pollen corresponding to each pollen category in the source rock sample to the total number of pollen is determined as the relative content corresponding to each pollen category in the source rock sample.

[0111] Optionally, the pollen categories in the source rock sample include a first pollen category corresponding to lower plant pollen and a second pollen category corresponding to higher plant pollen; Alternatively, the pollen category in source rock samples refers only to the second pollen category corresponding to higher plant pollen.

[0112] The pollen paleoclimate reconstruction device for hydrocarbon source rocks in Cenozoic basins proposed in this embodiment can perform pollen identification on multiple hydrocarbon source rock samples, determine the pollen identification data of each hydrocarbon source rock sample, that is, the multiple pollen categories in each hydrocarbon source rock sample and the relative contents of different pollen categories. Based on the pollen identification data of each hydrocarbon source rock sample and the established pollen paleoclimate database, qualitative paleoclimate parameter data and quantitative paleoclimate parameter data of each hydrocarbon source rock sample are determined. Based on the qualitative paleoclimate parameter data and quantitative paleoclimate parameter data of each hydrocarbon source rock sample, a TOC evolution map is generated, thereby reconstructing the paleoclimate evolution law during the hydrocarbon source rock deposition period, revealing the organic matter enrichment mechanism of the hydrocarbon source rock, and predicting the favorable development intervals of relatively high-quality hydrocarbon source rocks, providing assistance for the deployment and decision-making of the next step of oil and gas exploration.

[0113] The source rock pollen paleoclimate reconstruction device of the Cenozoic basin in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0114] The embodiment of the present invention also provides a computer device having the above Figure 6 Source rock palynological paleoclimate reconstruction apparatus for the Cenozoic basin shown.

[0115] See also Figure 7 , a structural diagram of a computer device provided by an optional embodiment of the present invention, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0116] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0117] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0118] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function. The data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0119] The memory 20 may include volatile memory, such as random access memory. The memory may also include non-volatile memory, such as flash memory, a hard disk, or a solid-state drive. The memory 20 may also include a combination of the above types of memory.

[0120] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0121] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for reconstructing paleoclimate from source rock pollen in a Cenozoic basin, characterized in that: include: Performing pollen identification on multiple source rock samples corresponding to multiple depth intervals in a single well in a Cenozoic basin to determine multiple pollen categories in each source rock sample and the relative content of each pollen category; For any of the source rock samples, according to each of the pollen categories in the source rock sample, the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to each of the pollen categories are searched in the created pollen paleoclimate database, and the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to each of the pollen categories are mutually verified. If the mutual verification is passed, the total relative content value corresponding to the target qualitative parameter category is calculated according to the qualitative parameter category and relative content corresponding to each of the pollen categories in the source rock sample, and the corresponding coexistence parameter interval is calculated according to the quantitative parameter extreme value corresponding to each of the pollen categories in the source rock sample; A TOC evolution chart of a single well in the Cenozoic basin is generated based on the total organic carbon TOC of each source rock sample, each depth segment, each relative content total value, and each coexistence parameter interval.

2. The method according to claim 1, characterized in that The pollen paleoclimate database includes a plurality of rows of data, each row of data including a qualitative parameter category and a quantitative parameter extreme value corresponding to the pollen category; wherein: The qualitative parameter categories corresponding to the pollen categories include humidity categories and temperature zone categories, the humidity categories are mesophytic, marshy, hygrophytic or xerophytic, and the temperature zone categories are tropical, subtropical, temperate or frigid; The quantitative parameter extreme values ​​corresponding to the pollen categories include temperature extreme values ​​and precipitation extreme values, and the coexistence parameter intervals include coexistence temperature intervals and coexistence precipitation intervals.

3. The method according to claim 2, characterized in that When the target qualitative parameter category includes tropical, subtropical, marsh and wet, the total relative content value corresponding to the target qualitative parameter category includes a first relative content total value and a second relative content total value; The method of calculating the total relative content value corresponding to the target qualitative parameter category according to the qualitative parameter category and relative content corresponding to each of the pollen categories in the source rock sample includes: In the qualitative parameter categories corresponding to each of the pollen categories of the source rock sample, each first qualitative parameter category is determined to be tropical or subtropical in the temperature zone category, and each second qualitative parameter category is determined to be marshy or hygrophytic in the humidity category; Determining the pollen category corresponding to each of the first qualitative parameter categories as a first category; and determining the pollen category corresponding to each of the second qualitative parameter categories as a second category; The relative contents corresponding to each of the first categories are added together to obtain the total value of the first relative contents; and the relative contents corresponding to each of the second categories are added together to obtain the total value of the second relative contents.

4. The method according to claim 2, characterized in that When the temperature extremes include the minimum and maximum annual average temperature values, and the precipitation extremes include the minimum and maximum annual average precipitation values, the corresponding coexistence parameter intervals are calculated based on the quantitative parameter extremes corresponding to each of the pollen categories in the source rock sample, including: Determine the maximum annual average temperature minimum value and the maximum annual average precipitation minimum value among the minimum annual average temperature values ​​and the minimum annual average precipitation minimum values ​​corresponding to each of the pollen categories of the source rock sample; and determine the minimum annual average temperature maximum value and the minimum annual average precipitation maximum value among the maximum annual average temperature values ​​and the maximum annual average precipitation values ​​corresponding to each of the pollen categories of the source rock sample; Construct an interval from the maximum annual average temperature minimum value to the minimum annual average temperature maximum value, and use it as the coexistence temperature interval; and construct an interval from the maximum annual average precipitation minimum value to the minimum annual average precipitation minimum value, and use it as the coexistence precipitation interval.

5. The method according to claim 1, wherein Generating a TOC evolution chart of a single well in the Cenozoic basin based on the total organic carbon TOC of each source rock sample, each depth segment, each relative content total value, and each coexistence parameter interval includes: respectively determining a characteristic parameter value for each of the coexistence parameter intervals; Based on the TOC of each source rock sample and each depth segment, a first curve is constructed showing how the TOC of the source rock changes with the depth of the single well formation; based on each relative content total value and each depth segment, a second curve is constructed showing how the relative content total value changes with the depth of the single well formation; and based on the characteristic parameter value of each coexistence parameter interval and each depth segment, a third curve is constructed showing how the characteristic parameter value changes with the depth of the single well formation; Based on the first curve, the second curve and the third curve, a chart including the first curve, the second curve and the third curve is constructed and used as the TOC evolution chart.

6. The method according to claim 1, characterized in that The pollen identification is performed on a plurality of source rock samples corresponding to a plurality of depth sections in a single well in a Cenozoic basin to determine a plurality of pollen categories in each source rock sample and the relative content of each pollen category, including: Sampling multiple depth intervals of a single well in the Cenozoic basin to obtain initial source rock samples corresponding to each depth interval; Preprocessing the initial source rock samples corresponding to each of the depth sections to obtain each of the source rock samples; Each of the source rock samples is subjected to pollen identification to determine the multiple pollen categories in each of the source rock samples and the relative content of each pollen category.

7. The method according to claim 6, characterized in that The pre-processing of the initial source rock samples corresponding to each of the depth sections to obtain each of the source rock samples comprises: For the initial source rock sample corresponding to any of the depth segments, the initial source rock sample is crushed into sample particles with a set particle size, and the sample particles are acid-treated with high-temperature dilute hydrochloric acid and high-temperature hydrofluoric acid in sequence to obtain treated sample particles, the treated sample particles are washed with water until neutral, and placed in a centrifuge tube for centrifugal treatment to obtain centrifuged sample particles, heavy liquid and acetic acid aqueous solution are added to the centrifuged sample particles in the centrifuge tube, and after standing for a set period of time, the particles are washed with water until neutral to obtain neutral sample particles, a stainless steel sieve is used to remove impurities in the neutral sample particles to obtain sieved sample particles, the sieved sample particles are ultrasonically vibrated to obtain vibrated sample particles, the vibrated sample particles are washed and dried with a nylon sieve to obtain washed and dried sample particles, and the washed and dried sample particles are centrifugally dehydrated to obtain the source rock sample corresponding to the depth segment.

8. The method according to claim 6, characterized in that The pollen identification is performed on each source rock sample to determine the multiple pollen categories in each source rock sample and the relative content of each pollen category, including: For any of the source rock samples, a corresponding thin section is made according to the source rock sample, and the thin section is placed under a microscope for observation to determine all the pollen in the source rock sample and count the total number of pollen; if the total number of pollen is not greater than the preset threshold, it is determined that the source rock sample does not meet the requirements, and resampling is performed in the depth segment corresponding to the source rock sample to obtain a sample that meets the requirements; if the total number of pollen is greater than the preset threshold, it is determined that the source rock sample meets the requirements, and each pollen category in the source rock sample is determined according to each pollen in the source rock sample, and the number of pollen corresponding to each pollen category in the source rock sample is counted, and the ratio of the number of pollen corresponding to each pollen category in the source rock sample to the total number of pollen is determined as the relative content corresponding to each pollen category in the source rock sample.

9. The method according to any one of claims 1 to 8, characterized in that The pollen categories in the source rock sample include a first pollen category corresponding to lower plant pollen and a second pollen category corresponding to higher plant pollen; Alternatively, the pollen category in the source rock sample only refers to the second pollen category corresponding to higher plant pollen.

10. A device for reconstructing paleoclimate from source rock pollen in a Cenozoic basin, characterized in that: include: An identification unit is used to perform pollen identification on a plurality of source rock samples corresponding to a plurality of depth sections in a single well in a Cenozoic basin, so as to determine a plurality of pollen categories in each source rock sample and the relative content of each pollen category; A search unit is used for searching, for any of the source rock samples, for each of the pollen categories in the source rock sample, in the created pollen paleoclimate database for the qualitative parameter category and the quantitative parameter extreme value corresponding to each of the pollen categories; A demonstration unit, for mutually demonstrating the qualitative parameter categories and quantitative parameter extreme values ​​corresponding to each of the pollen categories; The first statistical unit is used for statistically analyzing the relative contents of target qualitative parameter categories according to the qualitative parameter categories and relative contents corresponding to each of the sporopollen categories in the source rock sample if the mutual demonstrations are passed; A second statistical unit is configured to calculate a corresponding coexistence parameter interval based on the extreme value of the quantitative parameter corresponding to each of the sporopollen categories in the source rock sample; A generating unit is used to generate a TOC evolution chart of a single well in the Cenozoic basin according to the total organic carbon TOC of each source rock sample, each depth segment, each relative content total value and each coexistence parameter interval.

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