Quantitative characterization method for paleo-fluid migration in deep carbonate reservoir based on silicon-mercury isotope coupling

Abstract

The present application relates to oil and gas exploration and development technology field, it is a kind of based on silicon-mercury isotope coupling determination deep carbonate reservoir paleofluid migration quantitative characterization method, comprising: collecting the rock sample of deep carbonate reservoir research area reservoir;The rock sample is carried out silicon-mercury isotope integrated pretreatment, then high-precision isotope ratio analysis is carried out respectively, and the test result of silicon isotope and mercury isotope is obtained;Paleofluid migration path is quantitatively distinguished according to the test result of silicon isotope;According to the test result of mercury isotope, migration rate and migration distance are quantitatively obtained.The present application realizes the synchronous quantification and collaborative characterization of deep carbonate reservoir diagenetic paleofluid migration path, migration rate and migration distance, solves the technical bottleneck of qualitative ambiguity and strong multi-solution of existing method, and provides core technical support for deep oil and gas exploration.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and development technology, and is a quantitative characterization method for determining paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling. Background Technology

[0002] The diagenetic evolution of deep carbonate reservoirs is influenced by multiple phases of tectonic movement, hydrothermal activity, and water-rock interactions. Paleofluid migration characteristics (migration path, migration rate, and migration distance) directly control the formation and distribution of high-quality reservoirs. Accurately and quantitatively obtaining core parameters of paleofluid migration (migration path, migration rate, and migration distance) is a crucial prerequisite for understanding the diagenetic-accumulation coupling relationship of deep carbonate reservoirs and overcoming the "black box" problem of deep oil and gas exploration.

[0003] Current methods for paleofluid migration analysis in deep carbonate reservoirs suffer from problems such as high ambiguity, poor quantification, and fragmented parameters, failing to meet the needs of refined research on deep reservoirs. These problems are mainly manifested in the following ways: (1) Traditional geological analysis methods (such as core observation and well logging interpretation) can only qualitatively determine the direction of migration, but cannot quantitatively characterize the source of the migration path, the type of medium, and cannot calculate the migration rate and migration distance; (2) Single isotope techniques (such as carbon, oxygen and strontium isotopes) can only trace the source of fluids and cannot correlate with transport dynamic characteristics (such as transport rate and transport distance). Furthermore, they are subject to the influence of later modifications and have strong ambiguity. (3) Existing isotopic methods have not constructed quantitative models for the characteristics of deep reservoirs such as high temperature and pressure, strong water-rock interaction and complex migration channels, and cannot achieve simultaneous quantitative characterization of migration path and migration rate; (4) The sample pretreatment and testing methods for deep reservoirs are not adapted to the requirements of simultaneous analysis of silicon and mercury isotopes, which can easily lead to impurity interference and isotope fractionation, affecting the accuracy of data.

[0004] A search for relevant technologies yielded the following results: Patent application CN112069620A discloses a method and apparatus for determining the degree of particle migration in natural gas hydrate reservoirs, comprising the following steps: establishing a pore network model to simulate the flow of reservoir particles in the network model under phase equilibrium conditions; obtaining capillary forces based on reservoir particle migration condition parameters; and determining the throat through which the reservoir particles flow based on the capillary forces. When the reservoir particle concentration is less than a preset concentration, if the diameter of a single reservoir particle is less than the throat diameter, or the volume of all reservoir particles entering the throat is less than the throat volume, the throat radius is updated to a first throat radius. When the reservoir particle concentration is greater than or equal to a preset concentration, and the diameter of the reservoir particles is less than one-third of the throat diameter, if the volume of all reservoir particles entering the throat is less than the throat volume, the throat radius is updated to a first throat radius. Based on the first throat radius, the degree of reservoir particle migration is determined according to a first predetermined rule. This document reveals the influence of particle migration on fluid flow during hydrate decomposition.

[0005] Patent application CN115774294A discloses a method for identifying the migration direction of overpressured fluids using the pressure gradient evolution rate. The method includes: Step 1, calculating the duration of each key geological event based on its stage; Step 2, predicting the current formation pressure using the Eaton method; Step 3, performing paleopressure reconstruction; Step 4, dividing the pressure structure of each key geological event stage based on the paleopressure reconstruction results; Step 5, calculating the pressure gradient of the overpressure top sealing layer and the overpressure bottom sealing layer; Step 6, calculating the evolution rate of each pressure gradient; and Step 7, comparing the magnitudes of the evolution rates of each pressure gradient, with the direction of maximum pressure gradient evolution rate indicating the pressure migration direction. This document utilizes the pressure gradient evolution rate to identify the migration direction of overpressured fluids. Summary of the Invention

[0006] This invention provides a quantitative characterization method for determining paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling, which can effectively solve the problem that existing quantitative characterization methods for paleofluid migration in deep carbonate reservoirs cannot quantitatively characterize paleofluid migration.

[0007] Key points of the invention: 1. Establish an integrated sample pretreatment process for silicon-mercury isotopes, simultaneously adapt to the testing requirements of the two isotopes, realize the simultaneous testing of dual isotopes on the same target rock sample, eliminate impurity interference and sample heterogeneity, and ensure data matching. 2. Construct a three-level quantitative discrimination system for silicon isotopes, based on silicon isotopes (δ¹²⁺). 30 Si) Fractionation characteristics, accurately defining the migration path from three dimensions: source of the sphere, migration medium, and migration direction. All discriminations are quantitative thresholds with no fuzzy intervals. 3. Establish a quantitative calculation model for mercury isotopes, based on the mass fractionation of mercury isotopes (δ¹⁸O). 202Hg) and non-mass fractionation (Δ 199 The Hg effect was used to quantitatively calculate the migration rate and distance of ancient fluids, achieving a breakthrough from "qualitative description" to "precise numerical values". 4. Construct a two-way coupling verification mechanism for silicon-mercury isotopes, constrain the migration rate calculation parameters by migration path characteristics, verify the rationality of the path with the rate results, and improve the accuracy of the characterization results.

[0008] The technical solution of this invention is achieved through the following measures: a quantitative characterization method for determining paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling, comprising: Collect rock samples from the reservoirs in the deep carbonate rock study area; After the rock sample was crushed, impurities removed and acid-free purified, rock sample powder was obtained. The rock sample powder was then subjected to mercury extraction and silicon extraction to obtain pure mercury vapor and pure silicon solution. High-precision isotope ratio analysis was performed on the pure mercury vapor and pure silicon solution to obtain the silicon isotope δ. 30 Si and mercury isotope δ 202 Hg, Δ 199 Hg test results; According to silicon isotope δ 30 The test results of Si can be used to quantitatively determine the ancient fluid migration path; Based on mercury isotope δ 202 Hg, Δ 199 The test results of Hg can be used to quantitatively obtain the migration rate and migration distance.

[0009] The following are further optimizations and / or improvements to the above-mentioned technical solution: Furthermore, the aforementioned rock samples are core samples or outcrop samples from deep carbonate reservoirs.

[0010] Furthermore, the aforementioned rock samples are preferably core samples or outcrop samples from the main reservoir sections of the Ordovician and Cambrian deep carbonate rock reservoirs.

[0011] Furthermore, the above rock samples meet the following conditions: (1) the rock samples are not subjected to later weathering and alteration and are not filled with secondary minerals; (2) the target mineral of the rock samples is primary calcite cement or dolomite cement; (3) the lattice integrity of the rock samples is ≥95%.

[0012] Further, after the rock sample is crushed, impurities removed, and acid-free purified, rock sample powder is obtained. The rock sample powder is then subjected to mercury extraction and silicon extraction to obtain pure mercury vapor and pure silicon solution, including: Crushing: Grind the rock sample and select mineral particles with a particle size of 100μm to 200μm; Impurity removal: Mineral particles with a particle size of 100μm to 200μm are added to a zinc bromide solution and centrifuged to obtain impurity-removed particles; Acid-free purification: The impurity-removed particles were purified by vacuum washing with anhydrous ethanol to obtain rock sample powder; Stepwise extraction and purification: Mercury extraction: The rock sample powder was pyrolyzed at a constant temperature of 250℃ for 2 hours. The released mercury vapor was adsorbed and enriched through a gold tube to obtain pure mercury vapor; Silicon extraction: Silicon was extracted from the rock sample powder by alkaline fusion. After cooling, it was dissolved in deionized water and treated with a cation exchange resin column to obtain a pure silicon solution.

[0013] Furthermore, the pure mercury vapor and pure silicon solution were subjected to high-precision isotope ratio analysis to obtain the silicon isotope δ-1. 30 Si and mercury isotope δ 202 Hg, Δ 199 The test results for Hg include: High-precision isotope ratio analysis was performed using a multi-receiver inductively coupled plasma mass spectrometer. The silicon isotope δ¹⁴ was obtained by performing silicon isotope analysis on the pure silicon solution using a multi-receiver inductively coupled plasma mass spectrometer. 30 The test results for Si were obtained under the following conditions: plasma power of 1300W, resolution of 4000, and injection rate of 0.5mL / min. The pure mercury vapor was analyzed using a multi-receiver inductively coupled plasma mass spectrometer to obtain the mercury isotope δ¹⁴. 202 Hg, Δ 199 The test results for Hg were obtained under the following conditions: plasma power of 1000W and resolution of 3000.

[0014] Furthermore, the above is based on silicon isotope δ 30 The test results of Si quantitatively determine the paleofluid transport path, including: Based on silicon isotope δ 30 The Si test results yielded δ 30 Si value, δ 30 Si fractionation range, δ 30 Si spatial fractionation gradient, based on silicon isotope δ 30 A three-level quantitative discrimination system for silicon isotopes was constructed based on Si testing results. This system was used to determine paleofluid migration pathways. The three-level quantitative discrimination system includes a primary discrimination for determining the origin of migration layers, a secondary discrimination for determining the type of migration medium, and a tertiary discrimination for determining the migration direction. The primary discrimination is based on δ¹⁸O⁻. 30 The Si quantitative threshold defines the burial depth of different transport spheres and their corresponding paleofluid transport; the secondary discrimination is based on δ 30Si fractionation amplitude defines the migration characteristics of different transport media; the three-level discrimination is based on the reservoir structural background and δ 30 Si spatial fractionation gradient, quantitatively determining the transport direction.

[0015] Furthermore, the above is based on the mercury isotope δ 202 Hg, Δ 199 The test results for Hg quantitatively obtain the migration rate and migration distance, including: The migration distance and migration rate are obtained based on a quantitative calculation model of mercury isotopes. This model includes formulas for calculating the migration distance and migration rate. Specific steps are as follows: Formula for calculating transport distance: In the formula, D is the transport distance, in km; δ 202 Hg is the mercury isotope δ⁻ of pure mercury vapor. 202 Hg test value, ‰; The ancient fluid's primitive mercury isotope δ 202 Original Hg value, ‰; The mass fractionation coefficient; Formula for calculating transport rate: In the formula, V is the transport rate, m / yr; Δ 199 Hg is the mercury isotope Δ of pure mercury vapor. 199 Hg test value, ‰; The ancient fluid's primitive mercury isotope Δ 199 Original Hg value, ‰; This is the non-mass fractionation coefficient.

[0016] Furthermore, the aforementioned quantitative characterization method for determining paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling also includes verification using silicon-mercury isotope coupling: The results of paleofluid migration paths, migration rates, and migration distances are compared with the geological evolution patterns of the deep carbonate rock study area. If the consistency is ≥90%, the results are considered valid.

[0017] The present invention describes a quantitative characterization method for determining paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling. This method is a characterization method based on the coupling of the migration path tracing characteristics of silicon isotopes with the migration dynamics (migration rate and migration distance) of mercury isotopes. In essence, it is a quantitative characterization method with deep silicon-mercury isotope coupling. This method achieves simultaneous quantitative and coordinated characterization of the migration path, migration rate, and migration distance of diagenetic paleofluids in deep carbonate reservoirs, solving the technical bottlenecks of existing methods such as qualitative ambiguity and multiple solutions, and providing core technical support for deep oil and gas exploration.

[0018] This invention, based on silicon-mercury isotope coupling technology, constructs a quantitative characterization system for paleofluid migration in deep carbonate reservoirs. Compared with existing technologies, it has the following significant advantages: 1. Achieve simultaneous quantitative analysis of transport parameters: For the first time, the simultaneous quantitative characterization of paleofluid transport path (source layer, transport medium, transport direction), transport rate, and transport distance has been achieved. All results are precise numerical values ​​or quantitative classifications, completely solving the problem of qualitative ambiguity in traditional methods. 2. Dual isotope coupling reduces ambiguity: By linking silicon isotope path constraints with mercury isotope rate verification, the ambiguity of characterization results is reduced from 40% to below 10%, improving data reliability; 3. Strong adaptability to deep reservoirs: The customized sample pretreatment process (i.e., silicon-mercury isotope integrated pretreatment) and fractionation model (including mercury isotope mass fractionation and non-mass fractionation) are precisely suited to the characteristics of high temperature and high pressure and complex impurities in deep reservoirs. The test data has small deviation and its adaptability is far higher than that of conventional methods. 4. High operational repeatability: The entire process has established quantitative standards and parameter thresholds, with clear steps and strong operability, and the consistency of repeated test results from different laboratories is ≥95%; 5. Significant geological application value: The quantitative results can be directly used for the reconstruction of the diagenetic sequence of deep carbonate reservoirs, the identification of hydrothermal activity periods, and the selection of high-quality reservoir target areas, helping to overcome the "black box" problem of deep oil and gas exploration and improve the exploration success rate.

[0019] This invention is applicable to carbonate reservoirs with a burial depth greater than 5000m, especially to deep carbonate oil and gas reservoirs such as the Ordovician, Cambrian, and Carboniferous systems in Xinjiang; it can also be extended to shallow and medium-depth carbonate reservoirs, other sedimentary rock reservoirs containing carbonate minerals, and the field of quantitative analysis of fluid migration in paleoclimate and paleomarine environment research. Attached Figure Description

[0020] Appendix Figure 1 This is a graph showing the relationship between burial depth and silicon isotopes.

[0021] Appendix Figure 2 For δ 202 Hg-Δ 199 Fitting plot of burial depth of Hg. Detailed Implementation

[0022] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0023] Unless otherwise specified, all chemical reagents and chemical products mentioned in this invention are known and commonly used chemical reagents and chemical products in the prior art; unless otherwise specified, all percentages in this invention are mass percentages; unless otherwise specified, all solutions in this invention are aqueous solutions with water as the solvent, for example, hydrochloric acid solution is an aqueous solution of hydrochloric acid; room temperature in this invention generally refers to a temperature between 15°C and 25°C, and is generally defined as 25°C.

[0024] Unless otherwise specified, all instruments and devices mentioned in this invention are instruments and devices that are known and commonly used in the prior art. For example, a mercury vapor generator is a device used to generate mercury vapor, such as a mercury vapor generator.

[0025] δ 30 The fractionation rate of Si is the δ¹⁸O of the silicon isotope in the rock sample. 30 The difference between Si and the standard value of the same period.

[0026] δ 30 Si spatial fractionation gradient: Using the least squares method to apply δ 30 By linearly fitting Si with the spatial coordinate z, the following relationship is obtained: Where, δ 30 Si is δ 30 Si value, ‰; slope a is δ 30 Si represents the spatial fractionation gradient (‰ / km or ‰ / m); b is the intercept of the linear fit; z is the spatial coordinate.

[0027] In this invention, deep or ultra-deep refers to a depth > 5000m.

[0028] δ 202 Hg, Δ 199 Hg is one of the two key parameters of mercury isotopes, reflecting mass fractionation (MDF) and massless fractionation (MIF) processes, respectively.

[0029] δ 202 Hg represents the degree of mass fractionation of mercury isotopes, calculated as a deviation of parts per thousand relative to the standard NIST SRM 3133, in units of ‰.

[0030] Δ 199 Hg indicates odd-numbered isotopes. 199 The non-mass fractionation signal of Hg is expressed in ‰.

[0031] This method constructs a silicon-mercury isotope integrated sample pretreatment process specific to deep carbonate reservoirs, an isotope coupled quantitative model (a three-level quantitative discrimination system for silicon isotopes and a quantitative calculation model for mercury isotopes), and a collaborative characterization system for migration path, migration rate, and migration distance. This enables the quantitative discrimination of paleofluid migration paths (layer origin, migration medium, and migration direction) and the accurate calculation of migration rate and migration distance. It forms a two-way linkage mechanism of "migration path constraining migration rate calculation and migration rate verifying the rationality of migration path," solving the problem that existing methods are mainly qualitative and have multiple solutions. This provides complete quantitative data support for the analysis of diagenetic evolution of deep carbonate reservoirs.

[0032] This invention provides a quantitative characterization method for determining paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling, comprising: S1, Sample Collection: Collect rock samples from the reservoirs in the deep carbonate rock study area; The rock samples are core samples or outcrop samples from deep carbonate reservoirs.

[0033] When core samples are taken from reservoirs in deep carbonate rock research areas, diamond drill bits are used to drill the samples, remove the surface oxide layer and surrounding rock impurities, and obtain pure rock blocks of 2cm×2cm×2cm, which are the core samples. The burial depth (accurate to 0.5m), lithology, reservoir section, hydrothermal alteration index (Tsi, value from 0 to 1) of the core samples are marked to ensure that the core samples were formed in the same diagenetic period.

[0034] The rock samples are preferably core samples or outcrop samples from the main reservoir sections of the Ordovician and Cambrian deep carbonate rock reservoirs.

[0035] The rock sample meets the following conditions: (1) The rock sample has not been weathered or altered by later weathering and has no secondary mineral filling; (2) The target mineral of the rock sample is primary calcite cement or dolomite cement (direct carrier of diagenetic fluid); (3) The lattice integrity of the rock sample is ≥95%.

[0036] To address the complex coexistence of mineral impurities in deep carbonate rocks, an integrated pretreatment process was established that is simultaneously compatible with silicon and mercury isotope testing, eliminating impurity interference and isotope fractionation.

[0037] S2, Integrated silicon-mercury isotope pretreatment: After the rock sample was crushed, impurities removed and acid-free purified, rock sample powder was obtained. The rock sample powder was then subjected to mercury extraction and silicon extraction to obtain pure mercury vapor and pure silicon solution. Specifically, it includes: 1. Grinding and grading (crushing): The rock sample is ground to 200 to 300 mesh in an agate mortar and then graded by a laser particle size analyzer to select mineral particles with a particle size of 100 μm to 200 μm. 2. Density gradient centrifugation (impurity removal): Mineral particles with a diameter of 100μm to 200μm are added to a zinc bromide solution (density of 2.70g / cm³ to 2.87g / cm³) and centrifuged (centrifuged at 3000r / min for 30min) to remove impurities such as carbonate minerals, silica, clay, and volcanic debris. The impurity removal rate is ≥99.5% as detected by EDS energy dispersive spectroscopy, yielding impurity-removed particles. 3. Acid-free purification: The impurity-removed particles are purified by vacuum washing with anhydrous ethanol (washing pressure -0.08MPa, washing times 3 times) instead of traditional acid washing to obtain rock sample powder, avoiding the fractionation of silicon and mercury isotopes and element loss caused by acid dissolution in traditional acid washing; 4. Stepwise extraction and purification: (1) Mercury extraction: Weigh 50mg of rock sample powder, use water bath pyrolysis-gold amalgam enrichment method, pyrolyze at 250℃ for 2h, release mercury vapor through gold tube adsorption enrichment to obtain pure mercury vapor for mercury isotope testing; (2) Silicon extraction: Weigh 20mg of rock sample powder, use alkaline fusion method (NaOH and Na2CO3 are mixed at a mass ratio of 1:1 and melted at 600℃ for 30min) to extract silicon, cool and dissolve in deionized water, treat with cation exchange resin column to remove interfering ions such as Ca, Mg, and Fe to obtain pure silicon solution for silicon isotope testing; 5. Drying and storage: The treated pure mercury vapor and pure silicon solution are placed in clean containers and vacuum dried at 60°C for 12 hours to avoid contamination.

[0038] S3, High-precision quantitative analysis of silicon-mercury isotopes: High-precision isotope ratio analysis was performed on the pure mercury vapor and pure silicon solution to obtain the silicon isotope δ. 30 Si and mercury isotope δ 202 Hg, Δ 199 The test results for Hg include: Silicon isotope analysis of the pure silicon solution was performed using a multi-receiver inductively coupled plasma mass spectrometer (MC-ICP-MS). The test conditions were as follows: 1. Silicon isotopes (δ) 30Si) Testing: ① Instrument parameters: plasma power 1300W, resolution 4000, injection rate 0.5mL / min, Si-29 / Si-28 internal standard calibration; ② Standard material: NBS-28 was used as the standard material, and one standard sample was inserted for calibration for every 10 samples (pure silicon solution, concentration 5μg / mL to 10μg / mL); ③ Accuracy requirements: three parallel tests, test accuracy ±0.05‰, relative standard deviation (RSD) ≤0.1%; The silicon isotope δ¹⁴ was obtained. 30 Test results for Si; The pure mercury vapor was tested using a multi-receiver inductively coupled plasma mass spectrometer (MC-ICP-MS) under the following conditions: 2. Mercury isotopes (δ) 202 Hg, Δ 199 Hg) Test: ① Sample introduction mode: After the pure mercury vapor is preserved as described above, it becomes liquid. The liquid mercury is heated to form mercury vapor, and then the mercury vapor sample introduction mode is used; ② Instrument parameters: plasma power 1000W, resolution 3000, detection δ 202 Hg (mass fractionation) and Δ 199 Hg (non-mass fractionation); ③ Standard material: NIST-SRM-3133 is used as the standard material, and mass fractionation and non-mass fractionation calibration are performed simultaneously; ④ Accuracy requirements: Parallel tests are performed 3 times, δ 202 Hg test accuracy ±0.02‰, Δ 199 Hg testing accuracy ±0.01‰, RSD ≤0.2%; mercury isotope δ 202 Hg, Δ 199 Test results for Hg.

[0039] S4, Quantitative identification of ancient fluid migration pathways using silicon isotopes: According to silicon isotope δ 30 The test results of Si quantitatively determine the paleofluid transport path, including: Based on silicon isotope δ 30 The Si test results yielded δ 30 Si value, δ 30 Si fractionation range, δ 30 Based on the spatial fractionation gradient of Si and combined with a database of silicon isotope fractionation characteristics in deep carbonate reservoirs, a three-level quantitative discrimination system for silicon isotopes was constructed. This system was used to determine paleofluid migration pathways. The three-level quantitative discrimination system includes a primary discrimination for determining the origin of migration layers, a secondary discrimination for determining the type of migration medium, and a tertiary discrimination for determining the migration direction. The primary discrimination is based on δ¹⁸O⁻. 30 The Si quantitative threshold defines the burial depth of different transport spheres and their corresponding paleofluid transport; the secondary discrimination is based on δ 30Si fractionation amplitude defines the migration characteristics of different transport media; the three-level discrimination is based on the reservoir structural background and δ 30 The spatial fractionation gradient of Si is used to quantitatively determine the migration direction; the paleofluid migration path is determined based on the three-level quantitative discrimination system of silicon isotopes.

[0040] (1) First-level discrimination (origin of transport sphere): based on δ 30 The Si quantitative threshold is used to define the burial depth of paleofluid migration in different migration spheres. The discrimination criteria are shown in Table 1. Table 1. Silicon isotope δ 30 Table of Si quantitative threshold and migration spheres .

[0041] (2) Secondary discrimination (transport medium type): based on δ 30 The fractionation range of Si defines the transport characteristics of different transport media, and the discrimination criteria are shown in Table 2: Table 2 Correspondence between silicon isotope fractionation amplitude and transport medium .

[0042] (3) Three-level discrimination (migration direction): combining reservoir structural background and δ 30 Si spatial fractionation gradient, quantitatively determining the transport direction: 1) Vertical transport: δ in the vertical direction 30 Si increases linearly with increasing burial depth, δ 30 Si spatial fractionation gradient > 0.5‰ / km; 2) Lateral transport: δ on the plane 30 Si increases unidirectionally along the structural trend, δ 30 Si spatial fractionation gradient < 0.3‰ / km; 3) Oblique movement: The vertical and planar directions both show an increasing trend, δ 30 The spatial fractionation gradient of Si is 0.3‰ / km to 0.5‰ / km; 4) Migration path integration: Integrate the discrimination results of the three-level quantitative discrimination system of silicon isotopes to form a quantitative description of the migration path (e.g., burial depth of 5km ~ 8km, migration layer: deep layer, corresponding fluid type is crustal hydrothermal fluid, vertical upward migration along hydrothermal channel).

[0043] S5, quantitative calculation of mercury isotope migration rate and migration distance: Based on mercury isotope δ 202 Hg, Δ 199 The test results for Hg quantitatively obtain the migration rate and migration distance, including: The migration distance and migration rate are obtained based on a quantitative calculation model of mercury isotopes. This model includes formulas for calculating the migration distance and migration rate. Specific steps are as follows: (1) Determination of basic parameters: ① Original isotopic composition: The original mercury isotopic composition of the paleofluid was obtained by field measurement of unmigrated primary fluid inclusions in the reservoir of the deep carbonate rock study area. -1.5‰ to -1.0‰; ① 0.10‰ to 0.15‰; ② Mass fractionation coefficient: The mercury isotope mass fractionation coefficient of the reservoir in the deep carbonate rock study area was obtained by fitting the simulation of water-rock interaction under high temperature and high pressure (80℃ to 200℃, 50MPa to 150MPa). =0.002‰ / km, =0.0015‰・yr / m).

[0044] (2) Formula for calculating transport distance: In the formula, D is the transport distance (km); δ 202 Hg is the mercury isotope δ⁻ of pure mercury vapor. 202 Hg test value (‰); The ancient fluid's primitive mercury isotope δ 202 Original Hg value (‰); The mass fractionation coefficient is 0.002‰ / km, and the calculation result is rounded to one decimal place. (3) Formula for calculating transport rate: In the formula, V is the transport rate (m / yr); Δ 199 Hg is the mercury isotope Δ of pure mercury vapor. 199 Hg test value (‰); The ancient fluid's primitive mercury isotope Δ 199 Original Hg value (‰); The non-mass fractionation coefficient is 0.0015‰・yr / m, and the calculation result is rounded to two decimal places.

[0045] (4) Result verification: The migration rate must match the migration medium for silicon isotope discrimination (migration medium: hydrothermal channel, V>0.5m / yr; migration medium: pore water, V<0.1m / yr). If they do not match, return to step S2 to reprocess the rock sample.

[0046] S6, Verification of silicon-mercury isotope coupling: The results of paleofluid migration paths, migration rates, and migration distances are compared with the geological evolution patterns (tectonic movement periods and hydrothermal activity intensity) of the deep carbonate rock study area. If the consistency is ≥90%, the results are considered valid.

[0047] The present invention will be further described below with reference to embodiments: Example: Taking a typical deep carbonate reservoir block of the Yijianfang Formation (Block A) in the Ordovician system as an example, the method of this invention is applied to quantitatively characterize paleofluid migration. The detailed process is as follows: 1. Rock samples were collected according to step S1 above. The target rock samples were from the Yijianfang Formation, buried at a depth of 7800m~8350m. A total of 3 rock samples (A-01, A-02, A-03) were collected. The target minerals of the rock samples were calcite and dolomite cement. The basic characteristic information of the obtained rock samples (lattice integrity, uniformity of silicon / mercury mineral occurrence, thermal alteration index and diagenetic temperature) are shown in Table 3.

[0048] Table 3 Basic Information of Rock Samples from Block A .

[0049] 2. The rock sample is processed according to the silicon-mercury isotope integrated pretreatment process described in step S2 above. Then, according to the silicon-mercury isotope high-precision quantitative testing process described in step S3 above, high-precision isotope ratio analysis is performed on the obtained pure mercury vapor and pure silicon solution to obtain silicon isotope δ¹⁴. 30 Si and mercury isotope δ 202 Hg, Δ 199 The test results for Hg (including calibration of parallel and standard samples) are shown in Table 4.

[0050] Table 4. Biisotope test data of samples from Block A .

[0051] 3. Based on the criteria listed in step S4 above, the quantitative determination results of the migration path are shown in Table 5.

[0052] Table 5. Results of Level III Discrimination of Rock Samples from Block A .

[0053] 4. Following step S5 above, calculate the transport rate and transport distance: ①Original mercury isotopic composition of block A (measured primary fluid inclusions): =-1.20‰, =0.12‰; ② Mass fractionation coefficient: = 0.002‰ / km, =0.0015‰・yr / m.

[0054] The quantitative calculation results of fluid transport in block A are as follows: Table 6 Quantitative Calculation Results of Fluid Transport in Block A .

[0055] 5. By fitting the burial depth with silicon isotopes, it can be seen that the slope is (i.e., δ) 30 Si spatial fractionation gradient) 0.66‰ / km ( Figure 1 ), intuitively demonstrating the characteristics of vertical transport; at the same time, δ 202 Hg-Δ 199 Hg-burial depth fitting indicates that ( Figure 2 ), fitting R 2 All values ​​were above 0.95, indicating that the quantitative calculation results were reliable.

[0056] The above technical features constitute various embodiments of the present invention, which have strong adaptability and implementation effect. Unnecessary technical features can be added or removed according to actual needs to meet the needs of different situations.

Claims

1. A quantitative characterization method for determining paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling, characterized in that, include: Collect rock samples from the reservoirs in the deep carbonate rock study area; After the rock sample was crushed, impurities removed and acid-free purified, rock sample powder was obtained. The rock sample powder was then subjected to mercury extraction and silicon extraction to obtain pure mercury vapor and pure silicon solution. High-precision isotope ratio analysis was performed on the pure mercury vapor and pure silicon solution to obtain the silicon isotope δ. 30 Si and mercury isotope δ 202 Hg, Δ 199 Hg test results; According to silicon isotope δ 30 The test results of Si quantitatively determine the paleofluid transport path, including: Based on silicon isotope δ 30 The Si test results yielded δ 30 Si value, δ 30 Si fractionation range, δ 30 Si spatial fractionation gradient, based on silicon isotope δ 30 A three-level quantitative discrimination system for silicon isotopes was constructed based on Si testing results. This system was used to determine paleofluid migration pathways. The system includes a primary discrimination level for identifying the origin of migration layers, a secondary discrimination level for identifying the type of migration medium, and a tertiary discrimination level for identifying the migration direction. The primary discrimination level is based on δ¹⁸O⁻. 30 The Si quantitative threshold defines the burial depth of different transport spheres and their corresponding paleofluid transport; the secondary discrimination is based on δ 30 Si fractionation amplitude defines the migration characteristics of different transport media; the three-level discrimination is based on the reservoir structural background and δ 30 Si spatial fractionation gradient, quantitatively determining the transport direction; Based on mercury isotope δ 202 Hg, Δ 199 The test results for Hg quantitatively obtain the migration rate and migration distance, including: The migration distance and migration rate are obtained based on a quantitative calculation model of mercury isotopes. This model includes formulas for calculating the migration distance and migration rate. Specific steps are as follows: Formula for calculating transport distance: D=(δ) 202 Hg-d 202 Hg0) / k1 In the formula, D is the transport distance, in km; δ 202 Hg is the mercury isotope δ⁻ of pure mercury vapor. 202 Hg test value, ‰; δ 202 Hg0 is the primitive mercury isotope δ in ancient fluids. 202 Original value of Hg, ‰; k1 is the mass fractionation coefficient; Formula for calculating transport rate: V=(D 199 Hg0-D 199 Hg) / k2 In the formula, V is the transport rate, m / yr; Δ 199 Hg is the mercury isotope Δ of pure mercury vapor. 199 Hg test value, ‰; Δ 199 Hg0 is the ancient fluid's primitive mercury isotope Δ. 199 Hg original value, ‰; k2 is the non-mass fractionation coefficient.

2. The method for quantitative characterization of paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling according to claim 1, characterized in that, The rock samples are core samples or outcrop samples from deep carbonate reservoirs.

3. The method for quantitative characterization of paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling according to claim 2, characterized in that, The rock samples are core samples or outcrop samples from the main reservoir sections of the Ordovician and Cambrian deep carbonate rock reservoirs; the rock samples meet the following conditions: (1) the rock samples have not been subjected to later weathering and alteration and have no secondary mineral filling; (2) the target mineral of the rock samples is primary calcite cement or dolomite cement; (3) the lattice integrity of the rock samples is ≥95%.

4. The method for quantitative characterization of paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling according to claim 3, characterized in that, The rock sample was pulverized, impurities removed, and purified without acid to obtain rock powder. The rock powder was then subjected to mercury extraction and silicon extraction to obtain pure mercury vapor and pure silicon solution, comprising: Crushing: Grind the rock sample and select mineral particles with a particle size of 100μm to 200μm; Impurity removal: Mineral particles with a particle size of 100μm to 200μm are added to a zinc bromide solution and centrifuged to obtain impurity-removed particles; Acid-free purification: The impurity-removed particles were purified by vacuum washing with anhydrous ethanol to obtain rock sample powder; Stepwise extraction and purification: Mercury extraction: The rock sample powder was pyrolyzed at a constant temperature of 250℃ for 2 hours. The released mercury vapor was adsorbed and enriched through a gold tube to obtain pure mercury vapor; Silicon extraction: Silicon was extracted from the rock sample powder by alkaline fusion. After cooling, it was dissolved in deionized water and finally treated with a cation exchange resin column to obtain a pure silicon solution.

5. The method for quantitative characterization of paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling according to any one of claims 1 to 4, characterized in that, High-precision isotope ratio analysis was performed on the pure mercury vapor and pure silicon solution to obtain the silicon isotope δ. 30 Si and mercury isotope δ 202 Hg, Δ 199 The test results for Hg include: High-precision isotope ratio analysis was performed using a multi-receiver inductively coupled plasma mass spectrometer. The silicon isotope δ¹⁴ was obtained by performing silicon isotope analysis on the pure silicon solution using a multi-receiver inductively coupled plasma mass spectrometer. 30 The test results for Si were obtained under the following conditions: plasma power of 1300W, resolution of 4000, and injection rate of 0.5mL / min. The pure mercury vapor was analyzed using a multi-receiver inductively coupled plasma mass spectrometer to obtain the mercury isotope δ¹⁴. 202 Hg, Δ 199 The test results for Hg were obtained under the following conditions: plasma power of 1000W and resolution of 3000.

6. The method for quantitative characterization of paleofluid migration in deep carbonate reservoirs based on silicon-mercury isotope coupling according to any one of claims 1 to 4, characterized in that, It also includes verification of silicon-mercury isotope coupling: The results of paleofluid migration paths, migration rates, and migration distances are compared with the geological evolution patterns of the deep carbonate rock study area. If the consistency is ≥90%, the results are considered valid.

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