Metamorphic rock buried hill hydrothermal flow capacity evaluation method based on spectral logging

Abstract

This invention discloses a method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy spectrum logging. The method includes: S1, using conventional cable logging with natural gamma ray as a benchmark, performing depth correction on acoustic remote sensing logging, natural gamma ray energy spectrum logging, and elemental trapping energy logging spectra; S2, qualitatively determining the influence of hydrothermal fluids on the changes in the buried hill; S3, obtaining the spatial distribution characteristics of hydrothermal fluids at the wellbore based on acoustic remote sensing and conventional cable logging; S4, obtaining the sensitive curves characterizing the influence of hydrothermal fluids and their regular relationships; S5, obtaining the hydrothermal flow capacity index (MI) of the buried hill based on the sensitive curves of the hydrothermal influence, and studying the hydrothermal flow capacity and reservoir parameters based on the comprehensive index MI. The beneficial effects of this invention are: establishing a method for evaluating the hydrothermal flow capacity of buried hills using logging data, ensuring the reliability of reserve calculations.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration technology, and in particular to a method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy spectrum logging. Background Technology

[0002] In recent years, with breakthroughs in the exploration and development of deep-buried metamorphic buried hills in the Bohai Oilfield, the reservoir effectiveness and reservoir parameter calculation of deep-buried metamorphic buried hills have received increasing attention from petroleum workers. Unlike shallow-buried metamorphic buried hills, deep-buried metamorphic buried hills are more strongly affected by magma intrusion and hydrothermal activity, with natural gamma values ​​reaching up to thousands of API, resulting in complex well logging responses that seriously affect subsequent reserve assessment work.

[0003] Currently, most published studies on hydrothermal changes, both domestically and internationally, determine the formation of certain mineral deposits by quantitatively measuring the contents of uranium, thorium, and potassium through field sampling, cuttings, and core data, or by measuring changes in fixed elements associated with the deposit. However, no literature reports on hydrothermal flow capacity evaluation techniques for buried metamorphic hills based on well logging data. In the field of oil and gas exploration, well logging technology is an important means of evaluating reservoir development and reserve scale, and abundant well logging data provides a foundation for studying the hydrothermal flow capacity of deeply buried metamorphic hills. Natural gamma-ray spectroscopy logging and elemental capture spectroscopy logging can measure the elemental content of formations and quantitatively evaluate the hydrothermal flow capacity of deeply buried metamorphic hills. Summary of the Invention

[0004] The purpose of this invention is to provide a method for evaluating the hydrothermal flow capacity of buried metamorphic hills based on energy-spectrum logging. This method utilizes natural gamma-ray spectral logging and elemental capture spectral logging, combined with core, wall core, and cuttings analysis, to provide a quantitative evaluation technique for the hydrothermal flow capacity of buried metamorphic hills based on energy-spectrum logging. This not only establishes a method for evaluating the hydrothermal flow capacity of buried hills using logging data, but also provides support for subsequent reservoir effectiveness evaluation and accurate calculation of reservoir parameters in deeply buried metamorphic hills, effectively ensuring the reliability of reserve calculations.

[0005] To achieve the above objectives, the present invention adopts the following technical solution, comprising the following steps:

[0006] S1. Using the natural gamma curve of conventional cables as a benchmark, depth correction is performed on acoustic remote detection logging, natural gamma spectral logging, and elemental trapping energy logging spectra.

[0007] S2. Based on the whole-rock analysis, trace element analysis, cast thin section, backscattering, and quantitative analysis of rock and minerals of core or wall core samples, combined with the regional logging response characteristics of metamorphic buried hills in oilfields, qualitatively determine the influence of hydrothermal fluids on the variation of metamorphic buried hills.

[0008] S3. Based on acoustic remote detection and conventional cable logging, obtain the spatial distribution characteristics of hydrothermal fluids above the well.

[0009] S310. By using acoustic remote logging, information on the geological structure around the well can be obtained, and the location of fractures around the well can be effectively identified.

[0010] S320. By using the combined characteristics of natural gamma, neutron, and density curves from conventional cable logging, the distribution of buried hill intrusions above the well is determined.

[0011] S4. By comparing the logging response characteristics of hydrothermal-affected and hydrothermal-unaffected sections, and combining natural gamma ray spectroscopy and elemental trapping spectroscopy logging, sensitive curves and regular relationships characterizing the hydrothermal influence are obtained.

[0012] S5. Obtain the hydrothermal flow capacity index MI of the buried hill based on the sensitivity curve of the hydrothermal influence, and study the hydrothermal flow capacity and reservoir parameters based on the comprehensive index MI.

[0013] Preferably, in step S2, the qualitative assessment of the influence of hydrothermal fluids on the variation of metamorphic buried hills includes the hydrothermal characteristics of the core or wall core samples and the regional logging response characteristics.

[0014] Preferably, the hydrothermal characteristics of the core or wall core sample include one or more of the following: mineral type, elemental content differences, and aggregation sites.

[0015] Preferably, this includes the numerical changes and combination patterns of the logging curves.

[0016] Preferably, in step S3, the formation hydrothermal fluid flow mainly accompanies faults or intrusive bodies into the metamorphic buried hill, and the logging methods for obtaining the spatial distribution characteristics of hydrothermal fluid in the metamorphic buried hill include sonic remote detection logging and wireline logging.

[0017] Preferably, the acoustic long-range detection identifies the distribution of faults and reflectors within tens of meters around the well using a dipole shear wave mode. When a fault around the well intersects with the wellbore, it indicates that the location can effectively communicate with the formation, which is conducive to forming a channel for hydrothermal flow.

[0018] Conventional cable logging uses the combination of natural gamma, neutron, and density curves to determine the distribution characteristics of intrusive bodies around the well. When the natural gamma is low and smooth, and the neutron and density values ​​are high, the intrusive body is mainly composed of intermediate-basic lithology. When the natural gamma is medium to high and smooth, and the neutron and density values ​​are low, the intrusive body is mainly composed of acidic lithology. Later intrusive bodies mainly penetrate the bedrock along the foliation, gneiss, and fault locations. Since the penetration of veins can extend far in Archean buried hills, this provides an effective pathway for hydrothermal fluids to migrate from deep layers to Archean buried hills, resulting in more complex and variable logging response characteristics in Archean buried hills.

[0019] Preferably, in step S4, based on acoustic remote detection logging and conventional wireline logging, a segment of the Archean buried hill without developed faults or intrusive bodies is selected as the standard logging response of the unaffected by hydrothermal fluids; and a segment of the Archean buried hill with developed faults or intrusive bodies is selected as the segment affected by hydrothermal fluids.

[0020] The conventional cable logging method obtains logging values ​​for natural gamma, neutron, density, and photoelectric absorption cross section exponent curves; based on the natural gamma energy spectrum logging method, it obtains logging values ​​for uranium, thorium, and potassium curves; based on the elemental capture energy spectrum logging method, it obtains the contents of silicon, calcium, aluminum, iron, magnesium, sulfur, titanium, and gadolinium.

[0021] The logging curves are used to obtain sensitive curves characterizing the hydrothermal influence. Based on the Archean buried hill section unaffected by hydrothermal influence, regression formulas are constructed between the sensitive curves and silicon, calcium, aluminum, and iron elements. According to the regression formulas, the original curve values ​​of the hydrothermal-affected section are quantitatively obtained.

[0022] Preferably, in step S5, the hydrothermal flow capacity index MI of the buried hill is calculated based on the sensitivity curve of the Archean buried hill hydrothermal fluid.

[0023] MI=(C-C')×f(m) Equation 1

[0024] Where MI is the hydrothermal flow capacity, C is the hydrothermal flow capacity sensitivity curve value, C' is the original sensitivity curve value reconstructed from the original curve value, and f(m) is the normalization function.

[0025] The formula for calculating the normalization function is as follows:

[0026] f(m) = 1 / ((C-C') max -(C-C') min Equation 2

[0027] The study of hydrothermal flow capacity and reservoir parameters in Archean buried hills was conducted based on the hydrothermal flow capacity index MI.

[0028] The beneficial effects of this invention are: it establishes a method for evaluating the hydrothermal flow capacity of buried hills using well logging data, and also provides support for the subsequent evaluation of reservoir effectiveness and accurate calculation of reservoir parameters in deeply buried metamorphic rock buried hills, effectively ensuring the reliability of reserve calculation. Attached Figure Description

[0029] Figure 1 This is a schematic flowchart of a method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy spectrum logging according to the present invention.

[0030] Figure 2 These are analytical images of the cast thin sections from Embodiment 1 of the present invention;

[0031] Figure 3 This is the backscattered image in Embodiment 1 of the present invention;

[0032] Figure 4 This is a quantitative energy dispersive spectroscopy (EDS) image of rock minerals from Example 1 of the present invention;

[0033] Figure 5 This is a well logging response characteristic diagram of a metamorphic rock buried hill area in Embodiment 1 of the present invention;

[0034] Figure 6 This is a well logging feature diagram of dipole shear wave remote detection of metamorphic rock buried hills in Embodiment 1 of the present invention;

[0035] Figure 7 This is a conventional cable logging feature diagram of a metamorphic buried hill in Embodiment 1 of the present invention;

[0036] Figure 8 This is the energy dispersive spectral logging diagram of the unaffected hydrothermal section in Embodiment 1 of the present invention;

[0037] Figure 9 This is the energy dispersive spectral logging diagram of the section affected by the thermal fluid in Embodiment 1 of the present invention;

[0038] Figure 10 This is a correlation diagram between the hydrothermal sensing curve and the elemental trapping energy spectrum curve in Example 1 of the present invention;

[0039] Figure 11 This is a comparison chart of the hydrothermal sensing curve measurement and reconstruction curve in Embodiment 1 of the present invention;

[0040] Figure 12 This is a graph showing the analysis results of hydrothermal flow capacity and reservoir parameters in Embodiment 1 of the present invention. Detailed Implementation

[0041] The invention will now be described in further detail with reference to the accompanying drawings, so that those skilled in the art can implement it based on the description.

[0042] It should be understood that terms such as “having,” “comprising,” and “including” as used herein do not exclude the presence or addition of one or more other elements or combinations thereof.

[0043] Example 1

[0044] S100 uses the natural gamma ray curve of a conventional cable as a benchmark to perform depth correction on different logging operations using sonic remote detection logging, natural gamma ray spectral logging, and elemental trapping energy logging. During the logging process, considering the influence of well conditions, operation time, and research and production objectives, different series of logging parameters are collected multiple times. However, due to cable tension and wellhead pulley slippage, depth deviations occur in the logging responses of the same formation in different wells. Therefore, natural gamma ray logging is included in each logging operation, and depth realignment is performed based on the matching characteristics of the natural gamma ray curve, thus laying the foundation for subsequent research and reservoir parameter calculation.

[0045] S200. Based on whole-rock analysis, trace element analysis, cast thin section, backscattering, and quantitative analysis of rock minerals from core or wall core samples, combined with the regional logging response characteristics of metamorphic buried hills in oilfields, the influence of hydrothermal activity on the variation of metamorphic buried hills is qualitatively determined.

[0046] Hydrothermal fluids, also known as steam-water hydrothermal fluids, are high-temperature hot gas solutions formed at certain depths, using water as a carrier and containing various volatile components and ore-forming elements. Under different geological conditions, hydrothermal fluids with different compositions and origins can form. The main components are H₂O, HCl, HF, H₂S, CO₂, K, Na, Ca, Mg, Fe, Mn, Th, and U. Because hydrothermal fluids are rich in radioactive elements, rock and mineral analysis and well logging data can effectively determine the radioactive elements and their content in the formation.

[0047] The qualitative assessment of the influence of hydrothermal fluids on the variation of metamorphic buried hills includes the hydrothermal characteristics of core or wall core samples and the regional logging response characteristics. The hydrothermal characteristics of core or wall core samples include mineral type, differences in element content, and characteristics of accumulation layers. The regional logging response characteristics include numerical changes in logging curves and combination morphology characteristics.

[0048] The hydrothermal characteristics of the aforementioned core or wall core samples were obtained using experimental methods including whole-rock analysis, trace element analysis, thin section analysis, backscattered electron microscopy (BSEM), and quantitative analysis of rock and mineral energy dispersive spectroscopy (EDS). For example, whole-rock analysis allows for quantitative analysis of the variations in the content of various minerals in different stratigraphic layers; trace element analysis allows for quantitative analysis of the variations in elemental content at the surface; and thin section analysis allows for qualitative observation of mineral differences in sample sections and the determination of mineral content. Figure 2 The thin-film analysis images of the castings provided by this invention, such as Figure 2 As shown, the sample is a fractured monzogranite, mainly composed of granite blocks, with sericitization of plagioclase and kaolinization of potassium feldspar. The rock composition includes quartz, plagioclase, potassium feldspar, igneous rock blocks, and metamorphic rock blocks. The igneous rock blocks are granite blocks, and the metamorphic rock blocks are quartzite blocks. Backscattering analysis allows for quantitative analysis of the rock's mineralogical characteristics. Figure 3The backscattered image provided by this invention, such as Figure 3 As shown, the rock composition is mainly composed of potassium feldspar (Or) and quartz (Q), with pyrite (Pr) and siderite (Ic) filling along the fractures. Quantitative energy dispersive spectroscopy (EDS) analysis of the rock minerals allows for the quantitative analysis of the types and contents of elements in the formation. Figure 4 The rock and mineral energy dispersive spectroscopy images provided by this invention, such as Figure 4 As shown in Table 1, the types and amounts of the elements contained are as follows:

[0049] Table 1. Results of quantitative energy dispersive spectroscopy analysis of rocks and minerals

[0050]

[0051] The regional logging response characteristics affected by the above-mentioned hydrothermal fluids were obtained using the numerical and amplitude variation analysis method of natural gamma curves. Figure 5 The conventional well logging response diagram provided by this invention, such as Figure 5 As shown, the natural gamma ray (GR) logging values ​​for regionally stable metamorphic buried hills range from 0 to 230 GAPI. For example, in the sections of 5275–5290 m and 5325–5350 m, the natural gamma ray (GR) is between 147 and 225 GAPI, consistent with the regional response pattern. However, in the section from 5290 to 5325 m, the natural gamma ray (GR) is between 232 and 561 GAPI, which differs significantly from the regional pattern. Based on the analysis of core and wall core samples, the abnormal increase in the natural gamma ray curve is mainly due to the influence of hydrothermal fluids.

[0052] S300. Based on acoustic remote sensing and conventional wireline logging, the spatial distribution characteristics of hydrothermal fluids are obtained from the wellbore. Hydrothermal fluids migrate primarily through fractures and fracture zones of various sizes, moving from high-pressure areas deep within the formation towards decompression directions. Formation hydrothermal fluid flow mainly accompanies faults or intrusive bodies into metamorphic buried hills. Logging methods for obtaining the spatial distribution characteristics of hydrothermal fluids in metamorphic buried hills include acoustic remote sensing logging and wireline logging.

[0053] S310. By using acoustic remote logging, information on the geological structure around the well is obtained, and the location of fractures around the well is effectively identified. According to the acoustic remote logging, the distribution of faults and reflectors within tens of meters around the well can be clearly identified through the dipole shear wave mode. When a fault around the well intersects with the wellbore, it indicates that the location can effectively communicate with the formation, which is conducive to the formation of a channel for hydrothermal flow. Figure 6 The well logging feature map of dipole shear wave remote detection for metamorphic buried hills provided by this invention, such as... Figure 6As shown in the figure, the first line is the north-south long-range logging curve, and the second line is the northeast-southeast long-range logging curve. It can be seen from the figure that there are two obvious fracture structures near the well, which intersect the wellbore at 4260m and 4350m respectively. The fracture effectively connects the wellbore and the formation, and is a favorable channel for hydrothermal flow. In conventional logging, the natural gamma curve value is high and the "spiculated" feature is obvious. Combined with the analysis of core and wall core samples, it is mainly due to the influence of hydrothermal fluids that the natural gamma curve is abnormally large.

[0054] S320. The distribution of buried hill intrusive bodies above the well is determined by the combined characteristics of natural gamma, neutron, and density curves obtained through conventional well logging. According to the conventional wireline logging, the distribution characteristics of intrusive bodies around the well can be determined by the combined morphology of natural gamma, neutron, and density curves. When the natural gamma value is low and smooth, the neutron value is high, and the density value is high, the intrusive body is mainly composed of intermediate-basic lithology; when the natural gamma value is medium to high and smooth, the neutron value is low, and the density value is low, the intrusive body is mainly composed of acidic lithology. Later intrusive bodies mainly penetrate the bedrock along the foliation, gneiss, and fault locations. Since the penetration of veins can extend far in Archean buried hills, this provides an effective pathway for hydrothermal fluids to migrate from deep layers to Archean buried hills, resulting in more complex and variable logging response characteristics of Archean buried hills. Figure 7 The conventional cable logging feature map of the metamorphic buried hill provided by this invention, such as Figure 7 As shown in the figure, the three segments of natural gamma (GR) at 4658.6–4662.5 m, 4665.7–4680.0 m, and 4698.1–4701.7 m exhibit low and smooth natural gamma values, high neutron (CNCF) values, high density (ZDEN) values, and high photoelectric absorption cross section (PE) values. Combined with the rock and mineral analysis data of the core samples, these three segments are mainly basic intrusive bodies. At the same time, the figure shows that the natural gamma values ​​between the intrusive bodies increase significantly, far exceeding the range of natural gamma values ​​of regional metamorphic rocks. The curve features a "spiky" characteristic. However, the values ​​and combination characteristics of the neutron and density curves, as well as the photoelectric absorption cross section value, are consistent with the characteristics of regional metamorphic rocks, indicating that the influence of later hydrothermal fluids on the logging response is mainly reflected in the natural gamma curve.

[0055] S400: By comparing the logging response characteristics of the hydrothermal and non-hydrothermal zones, and combining energy dispersive spectroscopy logging, sensitive curves and regular relationships characterizing the hydrothermal influence are obtained.

[0056] The logging response characteristics include conventional wireline logging and energy spectrum logging. Conventional wireline logging mainly includes logging values ​​for natural gamma, neutron, density, and photoelectric absorption cross section exponent curves. Energy spectrum logging mainly includes natural gamma spectral logging and element capture spectral logging. Natural gamma spectral logging can not only determine the total effect of all radioactive elements in the formation, but also quantitatively determine the content of uranium, thorium, and potassium; element capture spectral logging determines the content of various elements by measuring the gamma ray energy spectrum, and quantitatively obtains the content of silicon, calcium, aluminum, iron, magnesium, sulfur, titanium, and gadolinium.

[0057] The logging response characteristics of hydrothermal and non-hydrothermal-affected sections were compared. Based on sonic remote sensing logging and conventional wireline logging, a section without developed faults or intrusions was selected as the standard logging response for Archean buried hills unaffected by hydrothermal fluids; a section with developed faults and intrusions was selected as the section affected by hydrothermal fluids. Natural gamma ray, neutron, density, and photoelectric absorption cross-section index curves were obtained using conventional wireline logging; uranium, thorium, and potassium curves were obtained using natural gamma ray spectroscopy logging; and the contents of silicon, calcium, aluminum, iron, magnesium, sulfur, titanium, and gadolinium were obtained using elemental capture spectroscopy logging. Figure 8 This invention provides an energy dispersive spectral logging chart of a section unaffected by hydrothermal fluids. Figure 9 The energy dispersive spectral logging diagram of the hydrothermal-affected section provided by this invention, such as Figure 8 and Figure 9 As shown, through comparison Figure 8 and Figure 9 It can be seen that in the hydrothermal-affected sections, the natural gamma (GR) curve measured by conventional wireline logging is significantly increased, but the neutron (CNCF), density (ZDEN), and photoelectric absorption cross section (PE) curves do not change, indicating that the hydrothermal fluid carries a large amount of radioactive elements, causing changes in the natural gamma (GR) curve. From the uranium (URAN), thorium (TH), and potassium (K) curves measured by natural gamma spectroscopy logging, it can be seen that in the hydrothermal-affected sections, the thorium (TH) curve is significantly increased, while the uranium (URAN) and potassium (K) curves do not show significant changes. Quantitative analysis of silicon, calcium, aluminum, iron, magnesium, sulfur, titanium, and gadolinium contents obtained from elemental capture energy spectrum logging shows that in the hydrothermal-affected sections, the contents of silicon (WFSI), calcium (WFCA), aluminum (WFAL), iron (WFFE), sulfur (WFS), titanium (WFTI), and gadolinium (WFGD) did not change significantly. The change in magnesium (WFMG) content was mainly due to a significant change in the location of the intrusive body, indicating a higher content of dark minerals and that the lithology of the intrusive body was mainly intermediate to basic. In contrast, the magnesium (WFMG) content in the high-gamma-ray sections affected by hydrothermal fluids did not change significantly.

[0058] Based on the logging curves obtained from conventional cable logging, natural gamma ray spectroscopy logging, and elemental trapping spectroscopy logging, sensitive curves characterizing the hydrothermal influence are obtained. Based on the Archean buried hill section unaffected by hydrothermal activity, a correlation analysis is established between the hydrothermal sensitive curves and silicon, calcium, aluminum, and iron elements. Regression relationships conforming to metamorphic rock patterns are selected. The regression formula generally adopts a statistical regression method, as shown in Equation 3.

[0059] C'=f(w) Equation 3

[0060] In Equation 3, C' is the parameter variable of the regression, w is the selected element variable, and f is the regression function, which can be a linear or exponential expression.

[0061] like Figure 9 As shown, the sensitive curves affected by hydrothermal fluids are mainly the natural gamma curve and the thorium element curve. Figure 10 The correlation diagram between the hydrothermal sensing curve and the elemental trapping energy spectrum provided by this invention is shown in the figure below. Figure 10 As shown, A is the correlation graph between thorium content and aluminum element, C' is the sensitive curve characterizing the hydrothermal influence of thorium content, and w is the aluminum element content measured by elemental trapping energy spectroscopy. Correlation analysis shows a significant correlation between the two, with the regression formula C' = 376.36w. 1.1051 Correlation coefficient R 2 The value is 0.9967; B is the correlation graph between thorium content and silicon, C' is the thorium content, and w is the silicon content, with no correlation between the two; C is the correlation graph between thorium content and magnesium, C' is the thorium content, and w is the magnesium content, with no correlation between the two. Based on the above analysis, the selected element capture energy spectrum curve is determined to be aluminum (WFAL), and the regression relationship C' = 376.36w is used. 1.1051 Reconstruct the hydrothermal sensitive thorium element curve for the entire well section. Since natural gamma ray spectroscopy logging determines the content of uranium, thorium, and potassium by interpreting the spectrum after measuring all radionuclides, the relationship is GR=a×TH+b×URAN+c×K, where GR is the measured total gamma ray intensity, TH, URAN, and K are the thorium, uranium, and potassium element contents, respectively, and a, b, and c are calibration coefficients for the total intensity. Different instruments and different measurement processes may result in different calibration coefficients. The calibration coefficients determined by the parameters acquired by the field instruments are 2.32, 6.04, and 14.04, respectively. When the uranium and potassium curves remain unchanged, but the thorium element curve is abnormal, the natural gamma ray curve will change accordingly. Figure 11 The comparison chart of hydrothermal sensing curve measurement and reconstruction curve provided by the present invention is as follows: Figure 11As shown, in the sections unaffected by hydrothermal fluids, the measured thorium (TH) and natural gamma (GR) curves coincide with the reconstructed curves; in the sections affected by hydrothermal fluids, the measured thorium (TH) and natural gamma (GR) curves show significant differences from the reconstructed curves.

[0062] S500. Based on the sensitivity curve of the influence of buried hill hydrothermal fluids, the hydrothermal fluid flow capacity index MI of the buried hill is obtained, and the hydrothermal fluid flow capacity and reservoir parameters are studied based on the comprehensive index MI. The specific steps include the following:

[0063] S510, Calculation of the hydrothermal fluid flowability index MI of buried hills:

[0064] The flowability index of Archean buried hill hydrothermal fluids is obtained by calculating it using the formula shown in Equation 1:

[0065] MI=(C-C')×f(m) Equation 1

[0066] Where MI is the hydrothermal flow capacity, C is the hydrothermal flow capacity sensitivity curve value, C' is the original sensitivity curve value reconstructed from the original curve value, and f(m) is the normalization function.

[0067] The formula for calculating the normalization function is shown in Equation 2:

[0068] f(m) = 1 / ((C-C') max -(C-C') min Equation 2

[0069] The study of hydrothermal flow capacity and reservoir parameters in Archean buried hills was conducted based on the hydrothermal flow capacity index MI.

[0070] For example, Figure 12 The hydrothermal flow capacity and reservoir parameter analysis results provided by this invention are shown in the figure below. Figure 12 As shown in the figure, the measured thorium (TH) content and the reconstructed thorium (TH_C) content are consistent between 4325.0 and 4351.7 m, and the calculated hydrothermal flow index MI is 0.000, indicating that it is not affected by hydrothermal fluids. However, the measured thorium (TH) content and the reconstructed thorium (TH_C) content differ significantly between 4351.7 and 4366.3 m, and the (C-C') in the normalization function... max and (C-C') minThe values ​​were 85.5 and -0.96, respectively. The calculated hydrothermal flow index MI in this segment ranged from 0.043 to 1.000, indicating strong hydrothermal flow capacity. The measured natural gamma curve (GR) value was high. The feldspar (VOL_ORTHOCL) content calculated using the multi-mineral model based on the measured curve was significantly higher than the feldspar content obtained from the whole-rock analysis of the wall core. The calculated porosity (PHIE) value differed greatly from the porosity (POR) result obtained from the wall core analysis. The feldspar (VO) content calculated using the multi-mineral model based on the reconstructed curve was significantly higher. The L_ORTHOCL content showed high agreement with the feldspar content from the whole-rock analysis of the wall core, and the calculated porosity (PHIE_C) value was in good agreement with the porosity (POR) results from the wall core analysis. The measured thorium (TH) content and the reconstructed thorium (TH_C) content in the 4366.3–4390.0 m range showed slight differences. The calculated hydrothermal flow index MI in this segment ranged from 0.000 to 0.124, indicating weak hydrothermal flow capacity. The results calculated using the multi-mineral model through the measured and reconstructed curves showed minimal differences.

[0071] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. A method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy dispersive spectroscopy logging, characterized in that, Includes the following steps: S1. Using the natural gamma curve of conventional cables as a benchmark, depth correction is performed on acoustic remote detection logging, natural gamma spectral logging, and elemental trapping energy logging spectra. S2. Based on the whole-rock analysis, trace element analysis, cast thin section, backscattering, and quantitative analysis of rock and minerals of core or wall core samples, combined with the regional logging response characteristics of metamorphic buried hills in oilfields, qualitatively determine the influence of hydrothermal fluids on the variation of metamorphic buried hills. S3. Based on acoustic remote detection and conventional cable logging, obtain the spatial distribution characteristics of hydrothermal fluids above the well. S310. By using acoustic remote logging, information on the geological structure around the well can be obtained, and the location of fractures around the well can be effectively identified. S320. By using the combined characteristics of natural gamma, neutron, and density curves from conventional cable logging, the distribution of buried hill intrusions above the well is determined. S4. By comparing the logging response characteristics of hydrothermal-affected and hydrothermal-unaffected sections, and combining natural gamma ray spectroscopy and elemental trapping spectroscopy logging, sensitive curves and regular relationships characterizing the hydrothermal influence are obtained. S5. Obtain the hydrothermal flow capacity index MI of the buried hill based on the sensitivity curve of the hydrothermal influence, and study the hydrothermal flow capacity and reservoir parameters based on the hydrothermal flow capacity index MI. In step S4, based on acoustic remote detection logging and conventional wireline logging, a section of the Archean buried hill without developed faults or intrusive bodies is selected as the standard logging response for the unaffected area by hydrothermal fluids; a section of the hill with developed faults or intrusive bodies is selected as the section affected by hydrothermal fluids. Based on conventional cable logging, obtain logging values ​​for natural gamma, neutron, density, and photoelectric absorption cross section exponent curves; based on the natural gamma spectral logging, obtain logging values ​​for uranium, thorium, and potassium curves; based on the elemental capture spectral logging, obtain the contents of silicon, calcium, aluminum, iron, magnesium, sulfur, titanium, and gadolinium. Based on the logging curves, sensitive curves characterizing the hydrothermal influence are obtained. Based on the Archean buried hill section unaffected by hydrothermal influence, a correlation analysis is constructed between the sensitive curves and silicon, calcium, aluminum, and iron elements. Those that conform to the metamorphic rock pattern are screened out, and regression formulas are obtained. Based on the regression formulas, the original curve values ​​of the hydrothermal-affected section are quantitatively obtained. The regression formula is shown in Equation 3: Formula 3 In Equation 3, C' is the parameter variable of the regression, w is the selected element variable, and f is the regression function; In step S5, the hydrothermal flow capacity index MI of the buried hill is calculated based on the sensitivity curve of the Archean buried hill hydrothermal fluid. Formula 1 Where MI is the hydrothermal flow capacity, C is the hydrothermal flow capacity sensitivity curve value, C' is the original sensitivity curve value reconstructed from the original curve value, and f(m) is the normalization function. The formula for calculating the normalization function is as follows: Formula 2 The study of hydrothermal flow capacity and reservoir parameters in Archean buried hills was conducted based on the hydrothermal flow capacity index MI.

2. The method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy dispersive spectroscopy logging as described in claim 1, characterized in that: In step S2, the qualitative assessment of the influence of hydrothermal fluids on the changes in metamorphic buried hills includes the hydrothermal characteristics of the core or wall core samples and the regional logging response characteristics.

3. The method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy dispersive spectroscopy logging as described in claim 2, characterized in that: The hydrothermal characteristics of the core or wall core samples include one or more of the following: mineral type, differences in elemental content, and aggregation sites.

4. The method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy dispersive spectroscopy logging as described in claim 2, characterized in that: This includes the numerical changes and combination patterns of well logging curves.

5. The method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy dispersive spectroscopy logging as described in claim 1 or 2, characterized in that: In step S3, the formation hydrothermal fluid flow mainly accompanies faults or intrusive bodies into the metamorphic buried hill. Logging methods for obtaining the spatial distribution characteristics of hydrothermal fluids in the metamorphic buried hill include sonic remote detection logging and wireline logging.

6. The method for evaluating the hydrothermal flow capacity of buried hills in metamorphic rocks based on energy dispersive spectroscopy logging as described in claim 1 or 2, characterized in that: In step S3, the acoustic long-range detection is to identify the distribution of faults and reflectors within tens of meters around the well using a dipole shear wave mode. When a fault around the well intersects with the wellbore, it indicates that the location can effectively communicate with the formation, which is conducive to forming a channel for hydrothermal flow. Conventional cable logging uses the combination of natural gamma, neutron, and density curves to determine the distribution characteristics of intrusive bodies around the well. When the natural gamma is low and smooth, and the neutron and density values ​​are high, the intrusive body is mainly composed of intermediate-basic lithology. When the natural gamma is medium to high and smooth, and the neutron and density values ​​are low, the intrusive body is mainly composed of acidic lithology. Later intrusive bodies mainly penetrate the bedrock along the foliation, gneiss, and fault locations. Since the penetration of veins can extend far in Archean buried hills, this provides an effective pathway for hydrothermal fluids to migrate from deep layers to Archean buried hills, resulting in more complex and variable logging response characteristics in Archean buried hills.

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