Resource quantity evaluation method for secondary burial depth hydrocarbon generation of high-maturity source rock

Abstract

The invention belongs to the technical field of oil and gas resource exploration, and provides a resource quantity evaluation method for secondary burial depth hydrocarbon generation of high-maturity source rocks. The method has a complete technical link of basic evaluation, parameter acquisition, model calibration, potential judgment, boundary definition, data quantification and resource accounting, the technical problem that the secondary hydrocarbon potential of the high-maturity source rock cannot be accurately judged is solved, and the precision of hydrocarbon generation history simulation is greatly improved by replacing sample thermal simulation and model calibration; the blank of no quantitative standard for the secondary hydrocarbon boundary of the high-maturity source rock is filled, and the defined depth and maturity range provides a clear reference basis for exploration; the accounting hydrocarbon generation amount can accurately distinguish the primary hydrocarbon amount from the secondary hydrocarbon amount, accurate resource amount data support is provided for oil-gas exploration deployment of high-maturity source rocks, and the practicability is high; the whole method is standardized in process, can be copied, can be popularized to secondary burial depth hydrocarbon generation evaluation scenes of all high-maturity source rocks, and is wide in application range.

Description

Technical Field

[0001] This disclosure relates to the field of oil and gas resource exploration technology, and in particular to a method for evaluating the resource quantity of hydrocarbon generation from secondary burial depth in highly mature source rocks. Background Technology

[0002] Resource assessment is a core component of source rock exploration, and its results directly guide the direction and deployment of oil and gas exploration. Currently, the mainstream oil and gas resource assessment methods in the industry can be summarized into three main categories: First, the analogy method, which mainly relies on basic geological parameters such as sedimentary rock volume, sedimentary velocity, basin area, and source rock volume for comparative estimation. This method is suitable for scenarios where early exploration data is scarce, but its accuracy and reliability are relatively low. Second, the statistical method, which encompasses various models such as the oil and gas field scale sequence method, oil and gas discovery process method, Pareto method, declining curve method, log-normal distribution method, Zibov method, and Ong's life cycle method. This is the main means for Western oil companies and governments to conduct resource assessments, and its core advantage lies in its emphasis on the economic, dynamic, and risk-related aspects of resources. Third, the genetic method, the most widely used assessment method in China, is based on the principle of material balance. It starts from basic parameters such as hydrocarbon generation (hydrocarbon expulsion, available accumulation), multiplying them by a certain coefficient (migration-accumulation, reservoir formation) for deterministic evaluation. Specific methods include the material balance method, natural profile evolution method, thermal simulation experiment method, and chemical kinetic method. The key feature of this method is that it fully considers a series of genetic parameters in the process of hydrocarbon generation, migration, accumulation and preservation, with clear geological significance and applicability to all exploration stages. However, the accuracy of the evaluation results is highly dependent on the degree of geological understanding of source rock characteristics, hydrocarbon migration and accumulation patterns and preservation conditions. Furthermore, the selection of some key parameters (such as the migration-accumulation coefficient) is somewhat based on human experience, which affects the accuracy of the evaluation results.

[0003] Oil and gas exploration in the Binbei area of ​​the Songliao Basin has long focused on shallow and medium-depth formations. However, with the declining production of shallow oil and gas and the increasing difficulty of exploration, the deep Carboniferous-Permian strata have gradually become an important potential target area for increasing oil and gas reserves and production. Exploration results show that the source rocks in this area are characterized by wide distribution, large thickness, and medium to high organic matter abundance. The kerogen type is mainly Type II, and the thermal evolution has entered the highly mature to over-mature stage (measured vitrinite reflectance Ro > 2.0%), possessing a good hydrocarbon generation foundation and huge exploration potential. However, resource assessment of these deep source rocks faces several unique challenges: Firstly, the study area has low exploration levels and deep burial depths, with few wells encountering Carboniferous-Permian strata. High maturity limits the research foundation for the distribution characteristics and organic geochemical features of source rocks. Secondly, the source rocks in this area have undergone uplift and erosion processes, resulting in the loss of a large amount of early-generated oil and gas, making it difficult to preserve and accumulate, directly affecting the accuracy of resource estimation. More importantly, current research on deep oil and gas resource assessment fails to fully recognize the core role of highly mature source rocks, especially lacking a resource assessment method for secondary hydrocarbon generation during the secondary burial process of highly mature source rocks, which cannot meet the actual needs of deep oil and gas exploration in the Carboniferous-Permian strata in the Binbei area of ​​the Songliao Basin. Therefore, providing a method for assessing hydrocarbon generation resources applicable to the secondary burial process of highly mature source rocks has become a pressing technical bottleneck in this field. Summary of the Invention

[0004] This disclosure provides a method for evaluating the resource quantity of hydrocarbon generation from secondary burial depth of highly mature source rocks, in order to at least solve the above-mentioned technical problems existing in the prior art.

[0005] According to the first aspect of this disclosure, a method for evaluating the resource quantity of hydrocarbon generation at secondary burial depth in highly mature source rocks is provided, comprising the following steps: S1: Statistically analyze the organic matter abundance, organic matter type, and organic matter maturity data of the target wells in the study area, and combine them with the corresponding geochemical characteristic analysis charts to comprehensively analyze the hydrocarbon generation potential of the highly mature source rocks in the study area. S2: Select substitute samples that are similar in depositional period and kerogen type to the high-maturity source rocks in the study area, and use hydrocarbon generation thermal simulation experiments to perform qualitative and quantitative analysis on each component of the product, and obtain the yield-temperature curves and hydrocarbon generation kinetic parameters of each component. S3: Using a parallel first-order reaction model (MFF model) with different pre-exponential factors and discrete distribution activation energies, and based on the hydrocarbon generation kinetic parameters and conversion rates of each component described in step S2, the kinetic models of gaseous hydrocarbons, total oil, and total hydrocarbons of the substitute sample are calibrated. S4: Combining the sedimentary burial history-thermal history data of the target well in the study area with the kinetic parameters calibrated in step S3, conduct hydrocarbon generation history simulation of the bottom and top layers of the source rock basement of the target well, clarify the hydrocarbon generation evolution characteristics and determine the secondary hydrocarbon generation potential. S5: For the target well with the secondary hydrocarbon generation potential, simulate the hydrocarbon generation history of its full thickness layer to determine the depth range of the secondary hydrocarbon generation limit and the range of the equivalent vitrinite reflectance (EasyRo%) before the secondary erosion and when the conversion rate is 100%. S6: The total organic carbon (TOC) content of the high-mature source rocks in the study area is predicted and calculated. Combined with well logging data, sedimentary facies diagrams and previous exploration results, the original TOC contour map and source rock thickness contour map are drawn. S7: Based on the genetic method, using the original TOC contour map and the source rock thickness contour map, combined with the set original hydrogen index, organic matter conversion rate and source rock density parameters, the total hydrocarbon generation and secondary hydrocarbon generation of the high-mature source rock in the study area are calculated by grid division and accumulation.

[0006] Specifically, this disclosure addresses the technical challenge of directly conducting thermal simulation experiments on highly mature source rocks. It innovatively selects substitute samples with similar depositional periods and matching kerogen types, and uses hydrocarbon generation thermal simulation experiments to obtain hydrocarbon generation kinetic parameters. This solves the industry pain point of inaccurately obtaining hydrocarbon generation parameters from highly mature source rocks. The selection principle of substitute samples is a core innovation, differing from the random sampling method in existing technologies. Secondly, this disclosure innovatively combines MFF models with different pre-exponential factors and discrete activation energies with the kinetic parameters from thermal simulation for precise calibration, resulting in a gaseous hydrocarbon / total oil / total hydrocarbon kinetic model suitable for highly mature source rocks. Furthermore, it specifically simulates the hydrocarbon generation history of the bottom and top layers of the source rock basement separately, rather than simulating the entire basement, enabling accurate identification of the impact of erosion on hydrocarbon generation and thus determining the secondary hydrocarbon generation potential. This simulation method is original. Furthermore, for target wells with secondary hydrocarbon generation potential, a full-thickness stratigraphic hydrocarbon generation history simulation is used, with a 100% organic matter conversion rate before secondary erosion as the threshold, to determine the boundary depth + EasyRo% maturity range for secondary hydrocarbon generation. This definition standard and method are the core innovations of this disclosure. In addition, based on the genetic method and combined with source rock TOC contour maps and thickness contour maps, this disclosure innovatively splits hydrocarbon generation into total hydrocarbon generation and secondary hydrocarbon generation for separate calculation, rather than only calculating the total hydrocarbon generation. At the same time, by combining the set hydrogen index, conversion rate, and density parameters and performing cumulative calculation through grid division, the accuracy of hydrocarbon generation calculation in highly mature source rocks is significantly improved, fully adapting to actual exploration needs.

[0007] The above seven steps form a complete technical chain of basic evaluation, parameter acquisition, model calibration, potential assessment, boundary definition, data quantification, and resource accounting. The steps are progressive and interconnected, forming an inseparable whole.

[0008] Specifically, the target well and the highly mature source rock mentioned in step S1 are not specifically limited.

[0009] In one embodiment, the highly mature source rock in step S1 is a hydrocarbon source rock of the Linxi Formation of the Carboniferous-Permian system in the Binbei area of ​​the Songliao Basin, and the maturity of the highly mature source rock is Ro > 2.0%.

[0010] Specifically, the Songliao Basin contains multiple source rock strata, including the Nenjiang Formation, Qingshankou Formation, Yingcheng Formation, Shahezi Formation, and the Carboniferous-Permian Linxi Formation, encompassing Type I, Type II1, Type II2, and Type III kerogen and coal-bearing source rocks. Except for the Nenjiang Formation, all strata have entered the gas generation stage, with other strata exhibiting high burial depth and maturity. In particular, the Carboniferous-Permian strata, limited by their high maturity, have relatively scarce organic geochemical data. Therefore, data from four wells (4S1, Mg1, Du101, and Zs1) during this period were analyzed to assess the abundance, type, and maturity of organic matter in the source rocks of this region.

[0011] In one embodiment, the geochemical characteristic analysis chart in step S1 includes a cross-plot of organic matter maturity versus burial depth, a frequency distribution plot of TOC, and a micro-component discrimination plot.

[0012] Specifically, step S1 involves comparing and analyzing the measured geochemical data of the target well with the aforementioned chart, which allows for a rapid and accurate evaluation of the hydrocarbon generation potential of highly mature source rocks.

[0013] Specifically, the cross-plot of organic matter maturity and burial depth (Ro-depth cross-plot) is used to determine the variation of organic matter maturity with burial depth and identify the distribution strata of highly mature source rocks; the frequency distribution plot of TOC is used to statistically analyze the distribution range of TOC values ​​in the target well and determine the degree of organic matter enrichment in the source rock; the micro-component discrimination plot is used to distinguish kerogen types and determine the hydrocarbon generation tendency (oil generation / gas generation) of the source rock.

[0014] In one possible implementation, given that organic geochemical characteristics indicate that the Carboniferous-Permian source rocks in the Binbei area of ​​the Songliao Basin possess hydrocarbon generation potential, but due to their generally high maturity, δ 13 The heavier the carbon content, the more likely the kerogen is to be Type III. Drilling into the Carboniferous-Permian system is less frequent, resulting in even less relevant organic geochemical analysis data. Therefore, in step S2, a Permian Fengcheng Formation shale sample from the Mahu Depression, which has a similar depositional period to the Linxi Formation of the Carboniferous-Permian system in the Binbei area of ​​the Songliao Basin and matches the kerogen type, was selected as a substitute sample to conduct a hydrocarbon generation thermal simulation experiment.

[0015] In one embodiment, the hydrocarbon generation thermal simulation experiment in step S2 adopts a closed system gold tube hydrocarbon generation thermal simulation experiment, wherein the pressure is 10~150MPa, the heating rate is 2~20℃ / h, and the temperature after heating is 300~600℃.

[0016] In one embodiment, the product of step S2 includes at least one of gaseous product and liquid product; the components of the liquid product include at least one of light components and heavy components.

[0017] In one embodiment, the formula for calculating the total hydrocarbon generation in the MFF model described in step S3 is: XKH= = ( XKH i (1-exp( - ))); where XKH is the total amount of hydrocarbons generated from organic matter; NKH is the number of parallel first-order reactions in the process of hydrocarbon generation from organic matter; XKH i Let ρ be the hydrocarbon generation potential of kerogen corresponding to the i-th reaction, i = 1 ~ NKH; T is the absolute temperature, T0 is the reference temperature; AKH i is the pre-exponential factor for the i-th reaction; D is the heating rate; EKH i Let be the activation energy of the i-th reaction; R is the gas constant.

[0018] Specifically, the basic idea of ​​the above model calibration is as follows: First, construct the objective function from the sum of squares of the differences between the calculated values ​​and the experimental values; construct the constraints from the physical meaning of the chemical kinetic parameters; then construct the penalty function from the objective function and the constraints, transforming the solution of the constrained extremum problem into the solution of the unconstrained extremum problem; finally, use the variable-scale optimization algorithm to solve the minimum point, thereby achieving the purpose of calibrating the model.

[0019] In one embodiment, in the hydrocarbon generation history simulation described in step S4, the factors affecting the hydrocarbon generation process include the burial depth, temperature difference, and erosion of the bottom and top layers of the source rock basement of the target well.

[0020] Specifically, since the source rock basement of the target well is thick and the amount of hydrocarbon generation at the bottom and top boundaries of the basement differs, the situation at the bottom and top layers must be considered separately during the hydrocarbon generation history simulation.

[0021] Specifically, the hydrocarbon generation capacity of source rocks is a key factor in determining the exploration potential of a region, and the study of the sedimentary burial-thermal evolution history of source rocks plays a crucial role in assessing hydrocarbon generation potential. It reflects the changes in the maturity of source rocks in the study area at different historical periods, providing important evidence for the migration, accumulation, and hydrocarbon accumulation processes. Hydrocarbon generation history analysis simulates the thermal evolution process of source rocks under different burial depths and temperature conditions to infer their hydrocarbon generation potential and hydrocarbon generation time. This process analysis can reveal the hydrocarbon generation periods of different source rocks, helping to assess oil and gas resource potential and guide exploration and development.

[0022] In one embodiment, the depth range of the secondary hydrocarbon generation limit in step S5 is 3479.3~4173.0m, and the corresponding EasyRo% range is 0.78~1.26%.

[0023] In one possible implementation, in step S6, given that the Carboniferous-Permian source rocks have a high degree of maturity, in order to accurately assess the hydrocarbon generation intensity of the source rocks, the characteristics of the source rocks are further quantitatively characterized according to the genetic method. Since the original hydrogen index is difficult to recover, in order to directly calculate the hydrocarbon generation of the source rocks, it is necessary to rely on reliable original TOC contour maps, source rock thickness contour maps, and other maps for analysis.

[0024] In one possible implementation, the formula for calculating the amount of hydrocarbons generated in step S7 is: Q=S i ·H i ·ρ i TOC 0 ·HI 0 · X 0; where Q is the amount of hydrocarbons generated, in tons; S i The area of ​​the source rock is expressed in km². 2 H i ρ represents the thickness of the source rock, in meters (m). i The density of the source rock is expressed in kg / m³. 3 TOC0 is the original organic carbon content of the source rock, TOC0 = TOC × recovery coefficient; HI0 is the original hydrocarbon generation potential per unit mass of organic matter, in mg / g TOC; X0 is the hydrocarbon conversion rate of organic matter. The corresponding formula for calculating hydrocarbon generation intensity is: Hydrocarbon generation intensity = Q / S i = H i ·ρ i TOC 0 ·HI 0 ·X 0.

[0025] Specifically, the hydrocarbon generation mentioned above refers to the hydrocarbon generation of a single grid.

[0026] Specifically, the aforementioned TOC0 is obtained by restoring the current TOC.

[0027] In one embodiment, in step S7, the total hydrocarbon generation is obtained by summing the Q values ​​of each grid through grid division; based on the depth range and maturity interval corresponding to the secondary hydrocarbon generation bottom layer, the effective source rock distribution range of secondary hydrocarbon generation is defined, and the secondary hydrocarbon generation is calculated by summing the formulas for hydrocarbon generation and hydrocarbon generation intensity.

[0028] Specifically, each grid has a uniform source rock volume, organic matter abundance, hydrogen index, hydrocarbon generation conversion rate, and density.

[0029] Specifically, when calculating the amount of secondary hydrocarbon generation, the above formulas for hydrocarbon generation amount and hydrocarbon generation intensity are used, and X0 is replaced by the organic matter conversion rate of the secondary hydrocarbon generation stage.

[0030] According to one possible implementation of this disclosure, at least the following beneficial effects are achieved: This disclosure addresses the challenge of directly conducting thermal simulation experiments on highly mature source rocks with high organic matter evolution. It innovatively selects substitute samples with similar depositional periods and matching kerogen types, and combines this with closed-system gold tube thermal simulation experiments to obtain hydrocarbon generation kinetic parameters. This approach avoids the problems of depletion of hydrocarbon generation potential and parameter distortion caused by directly using highly mature samples, making the calibration of the kinetic model more closely match actual geological conditions and reducing the simulation error of the hydrocarbon generation history. Secondly, for the first time, it uses a 100% organic matter conversion rate before secondary erosion as a threshold, and combines hydrocarbon generation history simulation to determine the depth range of secondary hydrocarbon generation and the EasyRo% maturity range, solving the pain point of existing technologies that rely heavily on qualitative descriptions of secondary hydrocarbon generation boundaries but lack quantitative standards. This quantitative standard can directly guide the selection of exploration target strata, avoid ineffective drilling, and significantly improve exploration efficiency. Furthermore, based on the genetic formula, and combined with source rock TOC contour maps, thickness contour maps, and grid-based cumulative calculations, it innovatively separates hydrocarbon generation into total hydrocarbon generation and secondary hydrocarbon generation for separate calculation. By distinguishing between primary cracking conversion rate and secondary hydrocarbon generation conversion rate, the shortcomings of traditional methods that only calculate total hydrocarbon generation and cannot distinguish secondary contributions are solved. The calculation results are more consistent with the hydrocarbon generation patterns of highly mature source rocks, providing accurate data support for resource quantity classification and evaluation.

[0031] The basic data used in this disclosure (well logging TOC data, well logging data, sedimentary facies maps) are all conventional data for oil and gas exploration. The steps such as sample selection, thermal simulation experiments, and model calibration are all industry-standard techniques, requiring no additional development of specialized equipment. The operation is low-barrier and can be quickly extended to similar high-mature source rock exploration areas such as the Songliao Basin and Mahu Depression. Furthermore, the calculated secondary hydrocarbon generation can be directly used to guide exploration deployment and development plan optimization in high-mature source rock areas, achieving integrated exploration-development.

[0032] This disclosure demonstrates, through precise evaluation of secondary hydrocarbon generation, that some highly mature source rocks that have undergone secondary burial still possess effective hydrocarbon generation capacity. This provides a theoretical basis for tapping the potential of old oilfields and new exploration in highly mature areas, expanding the exploration scope of oil and gas resources. The constructed technical framework of alternative sample simulation + kinetic model calibration + boundary quantification + resource accounting can serve as a reference standard for evaluating secondary hydrocarbon generation in highly mature source rocks within the industry, promoting the technological upgrade of this field from empirical judgment to quantitative evaluation.

[0033] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0034] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which: In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0035] Figure 1 This shows the Ro-depth cross plot of the Carboniferous-Permian source rocks in the Binbei area in Embodiment 1 of this disclosure; Figure 2 The TOC frequency distribution histogram of the Carboniferous-Permian source rocks in the Binbei area in Embodiment 1 of this disclosure is shown; Figure 3 This shows a ternary diagram of the microstructure composition of the Carboniferous-Permian source rocks in the Binbei area in Embodiment 1 of this disclosure; Figure 4 The δ-kerogen of the Carboniferous-Permian source rocks in the Binbei area in Embodiment 1 of this disclosure is shown. 13 C-frequency distribution histogram; Figure 5 The Pr-nC of the Carboniferous-Permian source rocks in the Binbei area in Embodiment 1 of this disclosure is shown. 17 Ph-nC 18 Intersection diagram; Figure 6The graphs showing the generation yield of each component of the YF1 source rock thermal simulation experimental sample in Example 1 of this disclosure as a function of temperature are shown; wherein, (a) the heating rate is 20℃ / h, and (b) the heating rate is 2℃ / h. Figure 7 This paper presents a comparison chart of the kinetic parameters and conversion rates of each component generated in the YF1 source rock sample in Example 1 of this disclosure. Figure 8 The diagram shows the hydrocarbon generation history of the CP Linxi Formation in Embodiment 1 of this disclosure; the left column represents well 4S1, and the right column represents well Du101. Figure 9 The diagram shows the relevant results of the secondary burial hydrocarbon generation conversion rate of well 4S1 in Embodiment 1 of this disclosure; Figure 10 The evaluation results of the source rock characteristics of the CP Linxi Formation in Embodiment 1 of this disclosure are shown in the figure; wherein, (a) is the original TOC contour map; and (b) is the source rock thickness contour map. Figure 11 This shows a contour map of hydrocarbon generation intensity in the Linxi Formation (CP) in the northern Songliao Basin of this disclosure, as shown in Embodiment 1. Figure 12 The diagram shows the contour map of secondary hydrocarbon generation intensity in the Linxi Formation (CP) of the northern Songliao Basin in Embodiment 1 of this disclosure. Detailed Implementation

[0036] To make the objectives, features, and advantages of this disclosure more apparent and understandable, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0037] Example 1 This embodiment evaluates the resource quantity of hydrocarbon generation from secondary burial depths of highly mature source rocks, as detailed below: (1) Evaluation of basic geochemical characteristics. The Songliao Basin contains multiple source rock strata, including the Nenjiang Formation, Qingshankou Formation, Yingcheng Formation, Shahezi Formation, and Linxi Formation of the Carboniferous-Permian System, involving Type I, Type II1, Type II2, and Type III kerogen and coal-bearing source rocks. Except for the Nenjiang Formation, all of them have entered the gas generation stage. The source rocks in other strata are buried at great depths and have high maturity. In particular, the Carboniferous-Permian (CP) system is limited by high maturity, and there is relatively little organic geochemical data. Therefore, data from four wells, 4S1, Mg1, Du101, and Zs1, during this period were analyzed to assess the abundance, type, and maturity of organic matter in the source rocks of this region.

[0038] Combined with corresponding geochemical characteristic analysis charts (cross-plot of organic matter maturity and burial depth, frequency distribution map of TOC, and micro-component discrimination map), Figure 1 The Ro-depth cross plot shows that the maturity is generally greater than 2, and according to the hydrocarbon source rock organic matter maturity evaluation index, the Carboniferous-Permian system in the Binbei area of ​​the Songliao Basin is currently in a high-overmature stage. Figure 2 The TOC frequency distribution histogram shows that the majority of TOC is between 1% and 2%. Referring to the SY / T5735-1995 source rock organic matter abundance index, the source rocks have high organic matter abundance, indicating they are primarily good source rocks. Microscopic component discrimination chart ( Figure 3 The data shows that the kerogen types are mainly type II1 and type III; due to the high maturity of the source rocks, the carbon isotopes are also affected, leading to... 12 C- 12 C breaks first. 13 C- 13 C fractures later, therefore δ 13 C-frequency distribution histogram ( Figure 4 The results show that kerogen δ 13 C > -25‰, belonging to Type III according to organic matter classification; for Carboniferous-Permian source rocks with high evolutionary degree, conventional methods cannot effectively reflect the type of organic matter kerogen, while the method of comparing biomarker compound parameters can effectively classify organic matter types, pterostilbene / nC 17 With phytane / nC 18 Relationship diagram ( Figure 5 The results show that the organic kerogen types are type II1 and type II2.

[0039] It is evident that the source rocks in this region have high organic matter abundance, deep thickness, high maturity, and good organic matter type. In summary, the Carboniferous-Permian basement layer in the study area has good hydrocarbon generation potential.

[0040] (2) Experimental Samples and Contents. Given that the organic geochemical characteristics indicate that the Carboniferous-Permian source rocks in the Binbei area of ​​the Songliao Basin possess hydrocarbon generation potential, but due to their generally high maturity, the δ¹⁴ ... 13 The heavier the carbon content, the more likely the kerogen is to be Type III. Drilling into the Carboniferous-Permian system is less frequent, resulting in even less relevant organic geochemical analysis data. Therefore, shale samples from the Permian Fengcheng Formation in the Mahu Depression, which are deposited at a similar time to the Linxi Formation of the Carboniferous-Permian system in the Binbei area of ​​the Songliao Basin and share the same kerogen type, were selected as substitute samples to conduct hydrocarbon generation simulation experiments.

[0041] The use of thermal simulation experiments to study the hydrocarbon generation characteristics of source rocks and to provide reliable parameters for calculating hydrocarbon resources has become an indispensable technique and means in oil and gas resource evaluation. To accurately evaluate the secondary hydrocarbon generation resources of the CP Linxi Formation, a closed-system gold tube thermal simulation experiment was conducted on substitute samples. This further clarified the component yield-temperature curves and hydrocarbon generation kinetic parameters during the formation of kerogen in the substitute samples.

[0042] One argillaceous dolomite sample from well FN7 was selected. Arylized dolomite is widely distributed in this study area, has great hydrocarbon generation potential, and is the main source rock of the Fengcheng Formation. The YF1 source rock sample has low maturity, with an Ro value of 0.6%, high organic matter abundance, and a TOC value of 0.8563% (see Table 1).

[0043] Table 1

[0044] The experimental apparatus used was a hydrocarbon generation kinetic thermal simulation experimental device developed by the Guangzhou Institute of Geochemistry, Chinese Academy of Sciences. The experimental process and standards followed the petroleum and natural gas industry standard "Golden Tube Hydrocarbon Generation Thermal Simulation Experimental Method". The thermal simulation experimental process was as follows: a. Under a pressure of 50 MPa, each sample was heated from room temperature to 600℃ at heating rates of 2℃ / h and 20℃ / h, respectively. b. From 336℃ to 600℃, every 24℃, the gaseous products of the samples were qualitatively and quantitatively analyzed; the light components (C6~C6) of the liquid products were analyzed. 14 Gas chromatography (GC) was used for qualitative and quantitative analysis of the liquid product; heavy components (C6000 GC) were analyzed. 14+ Organic extraction and weighing analysis were performed; yield quantification and hydrocarbon generation kinetic parameters were calculated for thermally simulated gaseous hydrocarbon products.

[0045] In the process of hydrocarbon generation from source rocks, heavy oil is generated earlier than light oil. Taking the YF1 rock sample with a heating rate of 20℃ / h as an example... Figure 6 (a) shows that heavy oil (i.e., C) 14+ ) and light oils (i.e., C 6-14 The temperatures corresponding to the maximum yield are approximately 408℃ and 456℃, respectively. When the pyrolysis temperature exceeds 408℃, the yield of heavy oil decreases rapidly, while the yield of light oil continues to increase. In fact, liquid hydrocarbons or light oils mainly originate from the thermal decomposition of the early-stage heavy components. The pyrolysis of type I organic matter mainly produces oil, but after reaching the high-temperature stage of 504℃, the yield of methane (i.e., C1) in the closed system increases rapidly, which is due to the cracking of early-stage liquid products and moisture.

[0046] Throughout the entire thermal simulation experiment of YF1 source rock, the gaseous products were mainly methane. Figure 6 of (a) Figure 6(b) shows that the methane yield gradually increases with increasing temperature, reaching a peak of 260.51 mg / (g·TOC) at a heating rate of 20 °C / h and a simulated temperature of 600 °C; and a peak of 299.26 mg / (g·TOC) at a heating rate of 2 °C / h and a simulated temperature of 600 °C. Total gas (i.e., C...) 1-5 The yield peaked at a heating rate of 20℃ / h and a simulated temperature of approximately 528℃, reaching 317.04 mg / (g·TOC); and at a heating rate of 2℃ / h and a simulated temperature of approximately 504℃, reaching 324.62 mg / (g·TOC). Total hydrocarbons (i.e., C...) 1+ The production rate peaked at a simulated temperature of approximately 432℃ and a heating rate of 20℃ / h, reaching 481.4 mg / (g·TOC); while at a simulated temperature of approximately 385℃ and a heating rate of 2℃ / h, it peaked at 503.08 mg / (g·TOC). The comparison of these two heating rates shows that different heating rates have some impact on natural gas production, but the differences are not significant; the lower the heating rate, the lower the corresponding gas production temperature.

[0047] Liquid hydrocarbon yield initially increases and then decreases with increasing temperature, as does total hydrocarbon yield, although the decrease is relatively small. This indicates that after the liquid hydrocarbon yield begins to decline, the gaseous hydrocarbon yield increases, slowing the rate of decline in total hydrocarbon yield. Figure 6 It can be seen that the YF1 source rock sample contains liquid hydrocarbons (i.e., C24H2O) 6-14 Only one hydrocarbon generation peak was observed. The sample reached its peak liquid hydrocarbon yield of 174.61 mg / (g·TOC) at a heating rate of 2℃ / h and a simulated temperature of approximately 431.5℃; the peak yield of 178.53 mg / (g·TOC) was reached at a heating rate of 20℃ / h and a simulated temperature of approximately 456℃. The hydrocarbon yield of the source rock varied with different heating rates. During the experiment, when the source rock was heated at heating rates of 2℃ / h and 20℃ / h, it was found that when the yields were the same, heating at a rate of 2℃ / h resulted in a lower hydrocarbon generation temperature. This phenomenon is consistent with the principle of time-temperature complementarity.

[0048] (3) Calibration of the kinetic model. Various reaction rate models describe the chemical kinetics of hydrocarbon formation from organic matter, including total reaction, series reaction, parallel reaction, and chain reaction. This embodiment uses a parallel first-order reaction model with different pre-exponential factors and a discrete activation energy distribution, referred to as the MFF model. Assume the process of hydrocarbon formation from organic matter consists of a series (NKH) of parallel first-order reactions, with each reaction having an activation energy of EKH. i The pre-exponential factor is AKH i Let the hydrocarbon generation potential of kerogen corresponding to each reaction be XKH.i Let i = 1, 2, ..., NKH. From the first-order reaction rate equation and the Arrhenius equation, it is easy to deduce that the total hydrocarbon generation of the NKH parallel reactions is: XKH= = ( XKH i (1-exp( - Where XKH is the total hydrocarbon generation; T is the absolute temperature, T0 is the reference temperature; D is the heating rate; and R is the gas constant. The basic idea for model calibration is as follows: First, construct the objective function from the sum of squares of the differences between the calculated and experimental values; construct the constraints from the physical meaning of the chemical kinetic parameters; then construct the penalty function from the objective function and the constraints, transforming the solution of the constrained extremum problem into the solution of the unconstrained extremum problem; finally, use a variable-scale optimization algorithm to solve for the minimum point, thus achieving the purpose of model calibration.

[0049] Based on the conversion rates of each component obtained from the thermal simulation experiment in step (2), the kinetic models of gaseous hydrocarbons, total oil, and total hydrocarbons in sample YF1 were calibrated using kinetic parameter calibration software. Figure 7 It can be seen that YF1 produces gaseous hydrocarbons (i.e., C2O3). 1-5 The pre-exponential factor of ) is 6.8 × 10. 14 S -1 The activation energy of the main frequency is 240 kJ / mol. Figure 7 (a)); the pre-exponential factor for the production of whole oil is 3.59 × 10⁻⁶. 15 S -1 The activation energy of the main frequency is 220 kJ / mol. Figure 7 (b)); the pre-exponential factor for total hydrocarbon production is 3.71 × 10⁻⁶. 15 S -1 The activation energy of the main frequency is 220 kJ / mol. Figure 7 (c) It can be seen that the overall activation energy distribution of gaseous hydrocarbons, total oil and total hydrocarbons in the YF1 sample is relatively high, indicating that it has certain late-stage gas generation potential. This suggests that the CP Linxi Formation has secondary hydrocarbon generation and has high oil and gas exploration prospects.

[0050] (4) Constructing sedimentary burial history-thermal history for hydrocarbon generation history evaluation. The hydrocarbon generation capacity of source rocks is a key factor in determining the exploration potential of a region, and the study of the sedimentary burial-thermal evolution history of source rocks occupies a crucial position in assessing hydrocarbon generation potential. It can reflect the changes in the maturity of source rocks in different historical periods in the study area, providing important evidence for the migration, accumulation, and hydrocarbon accumulation processes. Hydrocarbon generation history analysis is conducted by simulating the thermal evolution process of source rocks under different burial depths and temperature conditions to infer their hydrocarbon generation potential and hydrocarbon generation time. This process analysis can reveal the hydrocarbon generation period of different source rocks, help assess the potential of oil and gas resources, and guide exploration and development.

[0051] Because the CP Linxi Formation has a wide depositional range and thick depositional thickness, the hydrocarbon generation history experienced in different areas may not be consistent. Therefore, hydrocarbon generation history evaluation was carried out in wells 4S1 and Du101 for different areas.

[0052] First, based on the collected sedimentary and thermal histories of the target wells in the study area, combined with kinetic parameters, the evolutionary characteristics of hydrocarbon generation history in wells 4S1 and Du101 were clarified. Considering the thick basement of the CP Linxi Formation and the difference in hydrocarbon generation at the bottom and top boundaries, hydrocarbon generation history simulations were then performed on both the bottom and top layers of the basement. The results are as follows: Figure 8 As shown.

[0053] Based on the hydrocarbon generation history simulation results, for well Du101, during the primary hydrocarbon generation, the burial depth was large, and the temperature reached over 280℃. The entire kerogen was completely converted, and all hydrocarbon components were generated. However, due to erosion, almost all of these components were lost. Therefore, in the hydrocarbon generation history, before erosion occurred during the kerogen pyrolysis stage, the EasyRo% of the bottom strata had already reached 4%, indicating complete kerogen pyrolysis. The EasyRo% of the top strata was less than 4%, indicating the end of hydrocarbon generation due to kerogen pyrolysis. There was no secondary hydrocarbon generation, therefore, there is no exploration potential (e.g., ...). Figure 8 (b) and Figure 8 (d)). In contrast, for well 4S1, the bottom formation temperature reached 180℃ at the initial burial depth, and the top formation temperature was even lower than 180℃. Therefore, the primary hydrocarbon generation stage is reflected in the hydrocarbon generation history. Before the erosion occurs during the initial cracking stage, when the EasyRo% of the bottom formation is close to 2%, the kerogen conversion ends, but the top formation is less than 1%. Therefore, the top kerogen is not completely converted. In the later secondary burial stage, the kerogen continues to convert and generate hydrocarbons, so some formations still have hydrocarbon generation potential (such as...). Figure 8 (a) and Figure 8 (c) Therefore, the boundary of secondary hydrocarbon generation is determined based on the above factors.

[0054] (5) Determine the bottom boundary of secondary hydrocarbon generation. The so-called secondary hydrocarbon generation threshold refers to the burial depth at which secondary hydrocarbon generation begins in the source rock, and determining the bottom boundary depth at which secondary hydrocarbon generation begins is crucial when calculating the amount of secondary hydrocarbon generation.

[0055] Due to the thick CP Linxi Formation, during the primary hydrocarbon generation in well 4S1, the kerogen conversion at the bottom layer ended before the erosion period. At this point, the top layer kerogen was not fully converted and continued to generate hydrocarbons during the later secondary burial stage. Further simulations of the hydrocarbon generation history of all layers of thickness in well 4S1 revealed that the depth range of the secondary hydrocarbon generation boundary with a 100% conversion rate before the second erosion occurred was 3479.2–4173.0 m, with a thickness of 693.7 m. The EasyRo% of the kerogen during the secondary hydrocarbon generation stage was 0.78–1.26% (e.g., ...). Figure 9 As shown in the figure, this provides a data foundation for the next step of calculating secondary hydrocarbon generation.

[0056] (6) Evaluation of the characteristics of the source rocks of the CP Linxi Formation. Given the high maturity of the Carboniferous-Permian source rocks, in order to accurately evaluate the hydrocarbon generation intensity of the source rocks, it is necessary to further quantitatively characterize the characteristics of the source rocks based on the genetic method. Since the original hydrogen index is difficult to recover, in order to directly calculate the hydrocarbon generation of the source rocks, it is necessary to rely on reliable original TOC contour maps, source rock thickness contour maps and other maps for analysis.

[0057] Therefore, the TOC data identified by well logging in the northern part of the Songliao Basin (Carboniferous-Permian) were used for prediction and calculation. The calculated TOC values ​​of 59 wells in the target area were obtained, and the TOC distribution of the northern part of the Songliao Basin (e.g., the Carboniferous-Permian) was analyzed. Figure 10 As shown in (a). The development of source rocks in the work area was obtained by statistically analyzing the logging data of the target area. Combined with the Carboniferous-Permian sedimentary facies map and previous exploration results, the thickness contour map of the Carboniferous-Permian source rocks in the northern part of the Songliao Basin was finally obtained (as shown in (a)). Figure 10 (as shown in (b)).

[0058] (7) Hydrocarbon generation calculation. The hydrocarbon generation intensity of the source rocks was evaluated using the genetic method. In order to accurately evaluate the hydrocarbon generation intensity of the source rocks, the analysis was based on the restored original TOC contour map and the source rock thickness contour map.

[0059] The formula for calculating hydrocarbon generation is: Q=S i ·H i ·ρ i TOC 0 ·HI 0 ·X 0; where Q is the amount of hydrocarbons generated, in tons; S i The area of ​​the source rock is expressed in km². 2 Hi ρ represents the thickness of the source rock, in meters (m). i The density of the source rock is expressed in kg / m³. 3 TOC0 represents the original organic carbon content of the source rock, TOC0 = TOC × recovery coefficient, and TOC0 is recovered from the current TOC; HI0 represents the original hydrocarbon generation potential per unit mass of organic matter, in mg / g TOC; X0 represents the hydrocarbon conversion rate of organic matter. The corresponding formula for calculating hydrocarbon generation intensity is: Hydrocarbon generation intensity = Q / S i = H i ·ρ i TOC 0 ·HI 0 ·X 0.

[0060] The northern part of the Songliao Basin is divided into m×n identical grids. Each grid has a uniform source rock volume, organic matter abundance, hydrogen index, hydrocarbon generation conversion rate, and density. The total hydrocarbon generation amount is obtained by summing the Q values ​​of each cell.

[0061] The hydrocarbon generation intensity of the CP Linxi Formation was calculated based on the above calculation method. The CP Linxi Formation is currently at a high maturity level, and rock pyrolysis data can no longer characterize its hydrocarbon generation potential. Based on the previously classified Type II1 and Type II2 kerogen, the original hydrogen index (HI0) was set to a constant value of 500 mg / g TOC. For the initial pyrolysis, the organic matter conversion rate is approximately 1. Based on the restored original TOC and thickness contour maps, a contour map depicting the hydrocarbon generation intensity of the Linxi Formation in the Binbei area was constructed. Figure 11 The Linxi Formation is thick and mature, and calculations show that its hydrocarbon generation intensity is between 10,000 and 30,000 kt / km. 2 Based on the established isopleth map of hydrocarbon generation intensity in the CP Linxi Formation, the total hydrocarbon generation of the CP Linxi Formation in the Binbei area is calculated to be 824.383 billion tons, with a natural gas density of 0.72 kg / m³. 3 This is equivalent to a gas volume of 1144.976 trillion cubic meters.

[0062] Based on the restored original TOC and thickness contour maps, a contour map of secondary hydrocarbon generation intensity in the Linxi Formation of the Binbei area was constructed. The secondary hydrocarbon generation thickness of the Linxi Formation is 693.7 m, with a maturity of 0.78–1.26% and an average conversion rate of 35%. Calculation results show that the hydrocarbon generation intensity ranges from 0 to 5500 kt / km². 2 Between; based on the already characterized CP Linxi Formation secondary hydrocarbon generation intensity contour map ( Figure 12The secondary hydrocarbon generation of the CP Linxi Formation in the Binbei area was calculated to be 22.326 billion tons, with a natural gas density of 0.72 kg / m³. 3 This is equivalent to a gas volume of 31 trillion cubic meters.

[0063] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0064] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise explicitly specified.

[0065] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for evaluating the resource quantity of hydrocarbon generation from secondary burial depth in highly mature source rocks, characterized in that, Includes the following steps: S1: Statistically analyze the organic matter abundance, organic matter type, and organic matter maturity data of the target wells in the study area, and combine them with the corresponding geochemical characteristic analysis charts to comprehensively analyze the hydrocarbon generation potential of the highly mature source rocks in the study area. S2: Select substitute samples that are similar in depositional period and kerogen type to the high-maturity source rocks in the study area, and use hydrocarbon generation thermal simulation experiments to perform qualitative and quantitative analysis on each component of the product, and obtain the yield-temperature curves and hydrocarbon generation kinetic parameters of each component. S3: Using the MFF model, based on the hydrocarbon generation kinetic parameters and conversion rates of each component described in step S2, the kinetic models of gaseous hydrocarbons, total oil, and total hydrocarbons of the substitute sample are calibrated. S4: Combining the sedimentary burial history-thermal history data of the target well in the study area with the kinetic parameters calibrated in step S3, conduct hydrocarbon generation history simulation of the bottom and top layers of the source rock basement of the target well, clarify the hydrocarbon generation evolution characteristics and determine the secondary hydrocarbon generation potential. S5: For target wells with the aforementioned secondary hydrocarbon generation potential, simulate the hydrocarbon generation history of its full-thickness layers to determine the depth range and EasyRo% range of the secondary hydrocarbon generation limit before secondary erosion and when the conversion rate is 100%. S6: Predict and calculate the TOC data of the high-mature source rocks in the study area, and draw the original TOC contour map and source rock thickness contour map by combining the well logging data, sedimentary facies map and previous exploration results. S7: Based on the genetic method, using the original TOC contour map and the source rock thickness contour map, combined with the set original hydrogen index, organic matter conversion rate and source rock density parameters, the total hydrocarbon generation and secondary hydrocarbon generation of the high-mature source rock in the study area are calculated by grid division and accumulation.

2. The resource quantity evaluation method according to claim 1, characterized in that, The highly mature source rock mentioned in step S1 is a hydrocarbon source rock of the Linxi Formation of the Carboniferous-Permian system in the Binbei area of ​​the Songliao Basin, and the maturity of the highly mature source rock is Ro > 2.0%.

3. The resource quantity evaluation method according to claim 1, characterized in that, The geochemical characteristic analysis charts mentioned in step S1 include a cross-plot of organic matter maturity versus burial depth, a frequency distribution plot of TOC, and a micro-component discrimination plot.

4. The resource quantity evaluation method according to claim 1, characterized in that, The hydrocarbon generation thermal simulation experiment described in step S2 adopts a closed system gold tube hydrocarbon generation thermal simulation experiment, wherein the pressure is 10~150MPa, the heating rate is 2~20℃ / h, and the temperature after heating is 300~600℃.

5. The resource quantity evaluation method according to claim 1, characterized in that, The product of step S2 includes at least one of gaseous product and liquid product; the components of the liquid product include at least one of light components and heavy components.

6. The resource quantity evaluation method according to claim 1, characterized in that, The formula for calculating the total hydrocarbon generation in the MFF model described in step S3 is as follows: XKH= = ( XKH i (1-exp( - ))); where XKH is the total amount of hydrocarbons generated from organic matter; NKH is the number of parallel first-order reactions in the process of hydrocarbon generation from organic matter; XKH i Let ρ be the hydrocarbon generation potential of kerogen corresponding to the i-th reaction, i = 1 ~ NKH; T is the absolute temperature, T0 is the reference temperature; AKH i is the pre-exponential factor for the i-th reaction; D is the heating rate; EKH i Let be the activation energy of the i-th reaction; R is the gas constant.

7. The resource quantity evaluation method according to claim 1, characterized in that, In the hydrocarbon generation history simulation described in step S4, the factors affecting the hydrocarbon generation process include the burial depth, temperature difference, and erosion of the bottom and top layers of the source rock basement of the target well.

8. The resource quantity evaluation method according to claim 2, characterized in that, The depth range of the secondary hydrocarbon generation limit mentioned in step S5 is 3479.3~4173.0m, and the corresponding EasyRo% range is 0.78~1.26%.

9. The resource quantity evaluation method according to claim 1, characterized in that, The formula for calculating the amount of hydrocarbons generated in step S7 is as follows: Q=S i ·H i ·ρ i TOC 0 ·HI 0 ·X 0; where Q is the amount of hydrocarbons generated, in tons; S i The area of ​​the source rock is expressed in km². 2 H i ρ represents the thickness of the source rock, in meters (m). i The density of the source rock is expressed in kg / m³. 3 TOC0 is the original organic carbon content of the source rock, TOC0 = TOC × recovery coefficient; HI0 is the original hydrocarbon generation potential per unit mass of organic matter, in mg / g TOC; X0 is the hydrocarbon conversion rate of organic matter. The corresponding formula for calculating hydrocarbon generation intensity is: Hydrocarbon generation intensity = Q / S i = H i ·ρ i TOC 0 ·HI 0 ·X 0.

10. The resource quantity evaluation method according to claim 9, characterized in that, In step S7, the total hydrocarbon generation is obtained by summing the Q values ​​of each grid through grid division; based on the depth range and maturity interval corresponding to the secondary hydrocarbon generation bottom layer, the effective source rock distribution range of secondary hydrocarbon generation is defined, and the secondary hydrocarbon generation is calculated by summing the formulas for hydrocarbon generation and hydrocarbon generation intensity.

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