A method, system, equipment and medium for logging identification of hydrogen-rich reservoirs in clastic rocks.

Abstract

This invention relates to the field of oil and gas field exploration and development, and discloses a logging identification method, system, equipment, and medium for hydrogen-rich reservoirs in clastic rocks. The method includes: identifying oil and gas reservoirs in clastic rock reservoirs based on differences in the conductivity of fluids within the reservoirs; identifying gas reservoirs in clastic rock reservoirs based on differences in the influence of oil and gas on the formation's elastic modulus; and identifying hydrogen-rich reservoirs based on differences in gas density within the gas reservoirs combined with differences in the gas's occurrence environment. The technical solution of this invention comprehensively utilizes logging methods such as shallow and deep resistivity logging, density logging, neutron logging, sonic logging, and natural gamma ray spectroscopy logging to identify hydrogen-rich reservoirs in clastic rock reservoirs, thereby improving the effectiveness and accuracy of hydrogen-rich reservoir identification.

Description

Technical Field

[0001] This disclosure relates to the field of oil and gas field exploration and development, and in particular to a logging identification method, system, equipment and medium for hydrogen-rich reservoirs in clastic rocks. Background Technology

[0002] Against the backdrop of global energy decarbonization, the global energy structure is transitioning from fossil fuels to non-fossil fuels. Hydrogen, as a clean, efficient, and zero-emission new energy source, has gained attention from many countries worldwide. Natural hydrogen is generated during underground geological processes. Under certain geological conditions, this hydrogen is generated, transported, and enriched in underground rock strata, forming natural hydrogen reservoirs. The development and utilization of natural hydrogen has attracted global attention in the past decade. With increasing emphasis on natural hydrogen and the commencement of related exploration work, research on relevant exploration technologies and methods has also been carried out.

[0003] However, the formation mechanism and occurrence environment of hydrogen-rich reservoirs are significantly different from those of oil and gas reservoirs. Therefore, the logging identification methods and evaluation factors for hydrogen-rich reservoirs are also inevitably different. Difficulties have arisen when using existing logging methods to evaluate hydrogen-rich reservoirs, mainly because:

[0004] (1) From the perspective of conductivity, hydrogen and petroleum or natural gas are both high-resistivity media that are close to insulators and are not easy to distinguish from conductivity.

[0005] (2) Hydrogen and natural gas have similar volume density and hydrogen content, making it difficult to distinguish them using only density logging and neutron logging.

[0006] (3) Hydrogen and natural gas are both gaseous and have almost the same effect on rock elastic parameters.

[0007] As can be seen from the above, it is quite difficult to identify hydrogen-rich reservoirs using the current conventional well logging methods for identifying oil and gas layers. Therefore, it is very necessary to develop a well logging method for identifying hydrogen-rich reservoirs to address the problems encountered in the exploration of natural hydrogen reservoirs. Summary of the Invention

[0008] To address the aforementioned issues, this invention provides a logging identification method, system, equipment, and medium for hydrogen-rich reservoirs in clastic rocks. This method comprehensively utilizes logging methods such as shallow and deep resistivity logging, density logging, neutron logging, sonic logging, and natural gamma ray spectroscopy logging to identify hydrogen-rich reservoirs in clastic rocks, thereby improving the effectiveness and accuracy of hydrogen-rich reservoir identification.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] In a first aspect, the present invention provides a well logging identification method for hydrogen-rich clastic rock reservoirs, comprising:

[0011] Oil and gas reservoirs in clastic rock reservoirs can be identified based on the differences in the conductivity of fluids in clastic rock reservoirs.

[0012] Based on the differences in the influence of oil and gas on the formation elastic modulus in oil and gas reservoirs, gas reservoirs in clastic rock reservoirs are identified.

[0013] Hydrogen-rich reservoirs were identified based on differences in gas density within the gas reservoir and differences in the gas occurrence environment.

[0014] Furthermore, based on the differences in conductivity of fluids in clastic rock reservoirs, oil and gas reservoirs within clastic rock reservoirs are identified, including:

[0015] Determine the apparent formation water resistivity based on formation resistivity and formation factors;

[0016] Oil and gas reservoirs in clastic rock reservoirs were identified based on the apparent formation water resistivity.

[0017] Furthermore, the formula for calculating the apparent formation water resistivity is as follows:

[0018]

[0019] Among them, R wa R represents the apparent formation water resistivity. t denoted as ρ, where ρ is the formation resistivity; F is the formation factor.

[0020] Furthermore, the formula for calculating the underlying factors is:

[0021]

[0022] Where F represents the formation factor, φ represents the porosity, a represents the lithology coefficient, and m represents the cementation index.

[0023] Furthermore, porosity can be calculated using density logging and neutron logging, including:

[0024] Density porosity is obtained through density logging calculations.

[0025] Neutron porosity was calculated using neutron logging.

[0026] The average value of density porosity and neutron porosity is defined as porosity.

[0027] Furthermore, based on the differences in the influence of oil and gas on the formation elastic modulus in oil and gas reservoirs, gas reservoirs in clastic rock reservoirs are identified, including:

[0028] Calculate the actual compressibility coefficient of the oil and gas reservoir and the compressibility coefficient of the saturated water reservoir;

[0029] Based on the relationship between the actual compressibility coefficient of the formation and the compressibility coefficient of the saturated water formation, gas reservoirs in clastic rock reservoirs are identified.

[0030] Furthermore, based on the differences in gas density within the gas reservoir and the differences in the gas occurrence environment, hydrogen-rich reservoirs were identified, including:

[0031] The gas density in the gas reservoir was calculated using neutron logging and density logging.

[0032] The total intensity of natural gamma rays in the gas-bearing environment was measured using the natural gamma spectroscopy logging method.

[0033] Based on the ratio of radioactive element content in clastic rock reservoirs, determine the ratio of the intensity of natural gamma rays produced by the corresponding radioactive elements.

[0034] Hydrogen-rich reservoirs are identified based on the ratio of gas density in the reservoir to the intensity of natural gamma rays produced by radioactive elements.

[0035] Secondly, the present invention also provides a logging identification system for hydrogen-rich clastic reservoirs, comprising:

[0036] The first identification module is used to identify oil and gas reservoirs in clastic rock reservoirs based on the differences in conductivity of fluids in clastic rock reservoirs.

[0037] The second identification module is used to identify gas reservoirs in clastic rock reservoirs based on the differences in the influence of oil and gas on the formation elastic modulus.

[0038] The third identification module is used to identify hydrogen-rich reservoirs based on differences in gas density within the gas reservoir and differences in the gas occurrence environment.

[0039] Thirdly, the present invention also provides an electronic device, comprising: a processor and a memory;

[0040] The processor is coupled with the memory;

[0041] The processor is used to read and execute programs or instructions stored in the memory, causing the device to perform the method as described in the first aspect.

[0042] Fourthly, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method as described in the first aspect.

[0043] In summary, the technical solution provided by this invention has at least the following technical effects or advantages:

[0044] The technical solution of this invention first identifies oil, natural gas, and hydrogen layers based on the differences in conductivity between oil, natural gas, hydrogen, and formation water using the apparent formation water resistivity. Then, it identifies natural gas and hydrogen reservoirs based on the different effects of natural gas or hydrogen on the formation's elastic modulus compared to oil, using the formation compressibility coefficient. Finally, it calculates the gas density using density logging, neutron logging, and the residual oil and gas saturation in the flushed zone, and identifies the redox environment by calculating the thorium-uranium ratio using natural gamma ray spectroscopy logging. Finally, it identifies hydrogen-rich reservoirs based on the density differences between hydrogen and natural gas combined with the different redox environments they occur in. This technical solution comprehensively utilizes various logging methods, including shallow and deep resistivity logging, density logging, neutron logging, sonic logging, and natural gamma ray spectroscopy logging, to identify hydrogen-rich reservoirs in clastic rock reservoirs, thus improving the effectiveness and accuracy of hydrogen-rich reservoir identification.

[0045] Other features and advantages of this disclosure will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the disclosure. The objects and other advantages of this disclosure may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating a method for identifying hydrogen-rich clastic reservoirs using well logging, as described in an embodiment of this disclosure.

[0048] Figure 2 This is a further flowchart illustrating a method for identifying hydrogen-rich clastic reservoirs using well logging in an embodiment of the present invention.

[0049] Figure 3 This is a diagram illustrating the gas layer intersection based on formation water resistivity and compressibility in this embodiment of the disclosure.

[0050] Figure 4 To determine the oil and gas density chart based on the neutron porosity to density porosity ratio and residual oil and gas saturation in the embodiments of this disclosure;

[0051] Figure 5 This is a cross-plot of gas density and identification of hydrogen-rich reservoirs in the embodiments of this disclosure;

[0052] Figure 6 This is a schematic diagram illustrating the logging identification and evaluation results and verification of hydrogen-rich reservoirs in typical wells in this embodiment of the present disclosure.

[0053] Figure 7 This is a schematic diagram of the structure of a logging identification system for hydrogen-rich clastic reservoirs in an embodiment of this disclosure;

[0054] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0056] Geophysical logging is a common method for classifying reservoir types, obtaining reservoir parameters, and identifying fluid properties. Reservoir fluid identification primarily targets water, oil, and natural gas. Geophysical logging can identify reservoir fluid properties mainly due to the differences in the physical properties of oil, gas, and water, the effectiveness of observing these differences, and the influence of reservoir lithology and pore structure. For oil and water in reservoirs, the most obvious difference in their physical properties is conductivity. While pure water is a weak insulator with low conductivity, naturally occurring water generally contains salts, resulting in higher conductivity and a much lower resistivity compared to oil and gas. Therefore, resistivity logging can be used to distinguish and identify oil and gas layers from water layers. Identifying reservoir fluids by drawing cross-plots based on tested reservoir (oil and water) logging data is a method that combines resistivity logging data with lithological and porosity logging data to create cross-plots for qualitative identification of reservoir fluid properties. The lateral resistivity difference method is also a commonly used method for identifying reservoir fluid properties. It utilizes the resistivity differences caused by the different resistivity logging effects of the invasion zone at different lateral probe depths to identify fluid properties. The method of identifying reservoir fluid properties based on Archie's formula to calculate water saturation uses the relationship between resistivity, porosity, and saturation established by Archie's formula to obtain water (oil and gas) saturation, and uses the volume of different types of fluids to identify oil, gas, and water layers.

[0057] This invention provides a logging identification method, system, equipment, and medium for hydrogen-rich reservoirs in clastic rocks. It comprehensively utilizes logging methods such as shallow and deep resistivity logging, density logging, neutron logging, and natural gamma ray spectroscopy logging to identify hydrogen-rich reservoirs in clastic rocks, thereby improving the effectiveness and accuracy of hydrogen-rich reservoir identification.

[0058] Figure 1 This is a flowchart illustrating a method for identifying hydrogen-rich clastic reservoirs using well logging, as described in an embodiment of the present invention. Figure 2 This is a further flowchart illustrating a well logging method for identifying hydrogen-rich clastic reservoirs according to an embodiment of the present invention. As shown in the figure, the method includes:

[0059] S101. Based on the differences in conductivity of fluids in clastic rock reservoirs, identify oil and gas reservoirs in clastic rock reservoirs.

[0060] Based on formation resistivity and formation factors, the apparent formation water resistivity is determined; based on the apparent formation water resistivity, oil and gas reservoirs in clastic rock reservoirs are identified.

[0061] For example, fluid types in clastic rock reservoirs include oil, natural gas, hydrogen, and formation water. The properties of reservoir fluids are identified based on the physical properties of oil, gas, and water, thereby identifying the reservoir category.

[0062] Based on the differences in conductivity of fluids in clastic rock reservoirs, oil and gas reservoirs (oil, natural gas, and hydrogen reservoirs) can be identified. The fluid types in the reservoirs are classified as oil, water, natural gas, and hydrogen. The most significant difference between oil / gas and water lies in their conductivity; therefore, apparent formation water resistivity can be used to identify oil and gas reservoirs. The formula for calculating apparent formation water resistivity is:

[0063]

[0064] Among them, R wa R represents the apparent formation water resistivity. t is the formation resistivity, which can be obtained through deep lateral or deep induction logging; F is the formation factor.

[0065] The formula for calculating the underlying factors is:

[0066]

[0067] Where F represents the formation factor, φ represents the porosity, a represents the lithology coefficient, and m represents the cementation index, which can be obtained through rock electrical experiments.

[0068] Porosity φ can be calculated using density logging and neutron logging, including:

[0069] Density porosity is obtained through density logging calculations.

[0070] Neutron porosity was calculated using neutron logging.

[0071] The average value of density porosity and neutron porosity is defined as porosity.

[0072] The formula for calculating neutron porosity is:

[0073] φ N =(Φ N -Φ Nma) / (Φ Nf -Φ Nma )-V sh (Φ Nsh -Φ Nma ) / (Φ Nf -Φ Nma (3)

[0074] The formula for calculating density porosity is:

[0075] φ D =(ρ b -ρ ma ) / (ρ f -ρ ma )-V sh (ρ sh -ρ ma ) / (ρ f -ρ ma (4)

[0076] Among them, V sh The mud content can be obtained using natural gamma or spontaneous potential logging. Φ N For neutron logging porosity, Φ Nma Φ is the skeleton neutron response value. Nsh Φ is the neutron response value of mud. Nf ρ is the neutron response value of the mud filtrate. ma ρ is the density of the rock skeleton. f ρ is the density of the mud filtrate. b For density logging, the apparent volumetric density is ρ. sh This refers to the density of the clay.

[0077] To minimize the impact of residual gas within the intrusive zone on the porosity calculations of density and neutron logging, the effective porosity φ of the clastic rock is taken as the average of the neutron porosity and density porosity, as shown in the formula:

[0078]

[0079] in, Neutron porosity Density porosity.

[0080] Let R be the upper limit of the apparent formation water resistivity of the water layer. w0 The formula for identifying oil and gas (natural gas, hydrogen) reservoirs is:

[0081] R wa >R w0 (6)

[0082] Reservoirs whose apparent formation water resistivity is greater than the upper limit of the apparent formation water resistivity of the water layer are identified as oil and gas reservoirs in clastic rock reservoirs.

[0083] S102. Based on the differences in the influence of oil and gas on the formation elastic modulus in oil and gas reservoirs, gas reservoirs in clastic rock reservoirs are identified.

[0084] Calculate the actual compressibility coefficient of the formation and the compressibility coefficient of the water-saturated formation for oil and gas reservoirs; based on the relationship between the actual compressibility coefficient of the formation and the compressibility coefficient of the water-saturated formation, identify gas reservoirs in clastic rock reservoirs.

[0085] For example, since the compressibility coefficients of gas and liquid oil or water differ greatly, the compressibility coefficient of rocks in a reservoir is quite sensitive to changes in gas saturation. Therefore, gas reservoirs in clastic rock reservoirs can be identified based on the relationship between the actual compressibility coefficient of the formation and the compressibility coefficient of the apparent saturated water formation.

[0086] The formula for calculating the actual compressibility coefficient of a formation is:

[0087]

[0088] Among them, C t ρ is the formation compressibility coefficient. b The rock density can be obtained using compensated density logging; v p v s These are the longitudinal and transverse wave velocities, respectively, which can be obtained using array acoustic logging or long-spacing acoustic logging.

[0089] The compressibility coefficient C of the apparent saturated water formation sat The calculation formula is:

[0090]

[0091] Where: K ma The bulk modulus of the matrix is ​​K, which can be determined based on lithological data. w φ represents the bulk modulus of formation water; φ represents porosity.

[0092] Based on the relationship between the actual compressibility coefficient of the formation and the compressibility coefficient of the water-saturated formation, and combined with the apparent formation water resistivity, the formula for identifying gas (natural gas, hydrogen) reservoirs is as follows:

[0093]

[0094] Reservoirs whose actual formation compressibility is greater than that of saturated water formations and whose apparent formation water resistivity is greater than the upper limit of the apparent formation water resistivity of water layers are identified as gas reservoirs in clastic rock reservoirs.

[0095] Formula (9) can also be converted into a plot method, using intersection plots to identify gas reservoirs in clastic rock reservoirs (such as...). Figure 3 (As shown).

[0096] S103. Based on the differences in gas density in the gas reservoir and the differences in the gas occurrence environment, hydrogen-rich reservoirs are identified.

[0097] The gas density in the gas reservoir was calculated using neutron logging and density logging. The total intensity of natural gamma rays in the gas-bearing environment was measured using natural gamma ray spectroscopy logging. The intensity ratio of natural gamma rays produced by the corresponding radioactive elements was determined based on the ratio of the radioactive element content in the clastic rock reservoir. Hydrogen-rich reservoirs were identified based on the ratio of the gas density in the gas reservoir to the intensity of natural gamma rays produced by the radioactive elements.

[0098] For example, in terms of density, natural gas is denser than hydrogen. From the perspective of the occurrence environment, hydrogen has strong redox properties, and its occurrence environment is a strong redox environment. Therefore, based on the gas reservoirs identified in the clastic rock reservoirs in the above steps, hydrogen-rich reservoirs are identified according to the density differences of the gases (natural gas and hydrogen) in the gas reservoirs combined with the differences in the gas occurrence environment. Gas density ρ g The data was obtained using Frost E's (1979) calculation method through neutron logging and density logging, with the following formula:

[0099]

[0100] Among them, S hr The residual oil and gas (natural gas or hydrogen) saturation can be achieved by flushing the area with resistivity R. xo It is obtained by calculating using Archie's formula, which is as follows:

[0101]

[0102] Where b and n are both rock electrical parameters, which can be obtained through rock electrical experiments; a is the lithological additional conductivity correction coefficient, the value of which is closely related to the clay composition, content, and distribution of the target layer; R mf φ represents the formation water resistivity, in Ω·m; φ represents the target layer porosity, a decimal; and m represents the porosity index (cementation index), which measures the tortuosity of pores caused by the rock skeleton and pores. The higher the pore tortuosity, the larger the m value.

[0103] Formula (10) can also be converted into a graphical method, and the gas density can be calculated using the intersection plot method (e.g., Figure 4 (As shown).

[0104] Determining the gas occurrence environment, i.e., the gas redox environment, can be done using natural gamma ray spectroscopy logging. Natural gamma ray spectroscopy logging can detect uranium (U), thorium (Th), and other elements in formation rocks. 40The intensity of gamma rays produced by radioactive elements such as K, and the sum of the intensities of natural gamma rays produced by all radioactive elements in the strata, are considered. In oxidizing environments, low-valence uranium is easily oxidized to high-valence states and forms complex ions that dissolve in water. Therefore, the uranium content is lower in oxidizing environments, resulting in lower gamma ray production. In contrast, the thorium group content is relatively stable in clastic rocks, leading to a higher thorium-uranium ratio (Th / U) in hydrogen-rich reservoirs. This thorium-uranium ratio (Th / U) can be used to identify hydrogen-rich layers.

[0105] Let the intensities of gamma rays produced by the uranium series (U) and the thorium series (Th) be U and Th, respectively, then their ratio is:

[0106] P = Th / U (12)

[0107] Let the minimum limit for the thorium-uranium ratio of a hydrogen-rich gas layer be P0, and the maximum limit for the gas density be ρ. g0 Then, combining gas density, the relationship for identifying hydrogen-rich reservoirs is:

[0108]

[0109] Based on the identification of gas reservoirs in clastic rock reservoirs, reservoirs with a gamma-ray intensity ratio greater than the minimum thorium-uranium ratio limit for hydrogen-rich gas layers and a gas density less than the maximum gas density limit are identified as hydrogen-rich reservoirs.

[0110] According to formula (13), it can also be converted into a plot method, and the intersection plot method can be used to identify hydrogen-rich reservoirs (such as...). Figure 5 (As shown).

[0111] The effectiveness of the above-mentioned logging method for identifying hydrogen-rich clastic reservoirs is further illustrated below with specific examples. Figure 6 This is a verification diagram of the evaluation results of a hydrogen-rich reservoir in a well in the Qaidam Basin. As shown in the figure, the well logging data includes compensated neutron, compensated density, sonic transit time, wellbore, spontaneous potential, spontaneous gamma, microresistivity, shallow and deep seven-lateral, spontaneous gamma spectral logging, and long-spacing sonic full-wavelength logging data. Additionally, there are well logging data and gas testing data. These are processed according to the technical solution adopted in this invention:

[0112] (1) The effective porosity of the formation was calculated using density logging and neutron logging;

[0113] (2) The residual oil and gas saturation was calculated using microresistivity logging and effective porosity;

[0114] (3) The apparent formation water resistivity was calculated using deep lateral resistivity and effective porosity;

[0115] (4) Formation P-wave and S-wave velocities were obtained using long-spacing acoustic full-wave logging data, and the formation compressibility coefficient was obtained based on the P-wave and S-wave velocities. The apparent saturated water formation compressibility coefficient was then calculated using the lithological skeleton bulk modulus and the water bulk modulus.

[0116] (5) The uranium-thorium ratio was calculated using natural gamma ray spectroscopy logging;

[0117] (6) The gas density was calculated using density porosity, neutron porosity and residual oil and gas saturation;

[0118] (7) The uranium-thorium ratio was calculated using natural gamma ray spectroscopy logging;

[0119] (8) Four gas layers, namely 1, 2, 3 and 4, were identified by using the apparent formation water resistivity, formation compression modulus and apparent saturated water formation compression modulus.

[0120] (9) Layers 3 and 4 were identified as hydrogen-rich gas layers using gas density and uranium-thorium ratio. ⑩ Gas testing verified that layers 3 and 4 were indeed hydrogen-rich gas layers.

[0121] In summary, the technical solution provided by this invention has at least the following technical effects or advantages:

[0122] The technical solution of this invention first identifies oil, natural gas, and hydrogen layers based on the differences in conductivity between oil, natural gas, hydrogen, and formation water using the apparent formation water resistivity. Then, it identifies natural gas and hydrogen reservoirs based on the different effects of natural gas or hydrogen on the formation's elastic modulus compared to oil, using the formation compressibility coefficient. Finally, it calculates the gas density using density logging, neutron logging, and the residual oil and gas saturation in the flushed zone, and identifies the redox environment by calculating the thorium-uranium ratio using natural gamma ray spectroscopy logging. Finally, it identifies hydrogen-rich reservoirs based on the density differences between hydrogen and natural gas combined with the different redox environments they occur in. This technical solution comprehensively utilizes various logging methods, including shallow and deep resistivity logging, density logging, neutron logging, sonic logging, and natural gamma ray spectroscopy logging, to identify hydrogen-rich reservoirs in clastic rock reservoirs, thus improving the effectiveness and accuracy of hydrogen-rich reservoir identification.

[0123] Figure 7 This is a schematic diagram of a logging identification system for hydrogen-rich clastic reservoirs provided in this embodiment of the disclosure. As shown in the figure, the system includes:

[0124] The first identification module is used to identify oil and gas reservoirs in clastic rock reservoirs based on the differences in conductivity of fluids in clastic rock reservoirs.

[0125] The second identification module is used to identify gas reservoirs in clastic rock reservoirs based on the differences in the influence of oil and gas on the formation elastic modulus.

[0126] The third identification module is used to identify hydrogen-rich reservoirs based on differences in gas density within the gas reservoir and differences in the gas occurrence environment.

[0127] It should be noted that, for ease of explanation, Figure 7 This example only illustrates the main modules of a logging identification system for hydrogen-rich clastic reservoirs. In practical applications, the system may also include modules or components not shown in the figure; the system is not limited to the above-described module structure, but may also be other module structures that implement the above method embodiments.

[0128] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0129] like Figure 8 As shown, the electronic device includes: a processor and a memory;

[0130] The processor is used to read and execute programs and instructions stored in the memory, causing the electronic device to perform the above-described method embodiments.

[0131] It should be noted that, for ease of explanation, Figure 8 Only the main components of the electronic device are shown. In actual applications, the electronic device may also include components or assemblies not shown in the figure.

[0132] This disclosure also provides a computer-readable storage medium storing a program or instructions that, when read and executed by a computer, cause the computer to perform the above-described method embodiments.

[0133] Although the present disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A well logging method for identifying hydrogen-rich clastic rock reservoirs, characterized in that, include: Oil and gas reservoirs in clastic rock reservoirs can be identified based on the differences in the conductivity of fluids in clastic rock reservoirs. Based on the differences in the influence of oil and gas on the formation elastic modulus in oil and gas reservoirs, gas reservoirs in clastic rock reservoirs are identified. Based on the differences in gas density within the gas reservoir and the differences in the gas occurrence environment, hydrogen-rich reservoirs were identified, including: The gas density in the gas reservoir was calculated using neutron logging and density logging. The total intensity of natural gamma rays in the gas-bearing environment was measured using the natural gamma spectroscopy logging method. Based on the ratio of radioactive element content in clastic rock reservoirs, determine the ratio of the intensity of natural gamma rays produced by the corresponding radioactive elements. Hydrogen-rich reservoirs are identified based on the ratio of the gas density in the gas reservoir to the intensity of the natural gamma rays produced by the radioactive element.

2. The logging identification method for hydrogen-rich clastic reservoirs according to claim 1, characterized in that, The method of identifying oil and gas reservoirs in clastic rock reservoirs based on differences in the conductivity of fluids in clastic rock reservoirs includes: Determine the apparent formation water resistivity based on formation resistivity and formation factors; Oil and gas reservoirs in clastic rock reservoirs were identified based on the apparent formation water resistivity.

3. The logging identification method for hydrogen-rich clastic reservoirs according to claim 2, characterized in that, The formula for calculating the apparent formation water resistivity is as follows: in, The apparent formation water resistivity; Formation resistivity; This is due to stratigraphic factors.

4. The logging identification method for hydrogen-rich clastic reservoirs according to claim 2, characterized in that, The formula for calculating the formation factors is as follows: in, Due to stratigraphic factors, Porosity Lithology coefficient, This represents the cementation index.

5. The logging identification method for hydrogen-rich clastic reservoirs according to claim 4, characterized in that, porosity It can be calculated using density logging and neutron logging, including: Density porosity is obtained through density logging calculations. Neutron porosity was calculated using neutron logging. The average value of the density porosity and the neutron porosity is determined as the porosity. .

6. The logging identification method for hydrogen-rich clastic reservoirs according to claim 1, characterized in that, The method of identifying gas reservoirs in clastic rock reservoirs based on the differences in the influence of oil and gas on the formation elastic modulus includes: Calculate the actual compressibility coefficient of the oil and gas reservoir and the compressibility coefficient of the saturated water reservoir; Based on the relationship between the actual compressibility coefficient of the formation and the compressibility coefficient of the saturated water formation, gas reservoirs in clastic rock reservoirs are identified.

7. A logging identification system for hydrogen-rich clastic rock reservoirs, characterized in that, include: The first identification module is used to identify oil and gas reservoirs in clastic rock reservoirs based on the differences in conductivity of fluids in clastic rock reservoirs. The second identification module is used to identify gas reservoirs in clastic rock reservoirs based on the differences in the influence of oil and gas on the formation elastic modulus. The third identification module is used to identify hydrogen-rich reservoirs based on differences in gas density within the gas reservoir and differences in the gas occurrence environment, including: The gas density in the gas reservoir was calculated using neutron logging and density logging. The total intensity of natural gamma rays in the gas-bearing environment was measured using the natural gamma spectroscopy logging method. Based on the ratio of radioactive element content in clastic rock reservoirs, determine the ratio of the intensity of natural gamma rays produced by the corresponding radioactive elements. Hydrogen-rich reservoirs are identified based on the ratio of the gas density in the gas reservoir to the intensity of the natural gamma rays produced by the radioactive element.

8. An electronic device, characterized in that, include: Processor and memory; The processor is coupled to the memory; The processor is configured to read and execute the program or instructions stored in the memory, causing the device to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the method as described in any one of claims 1-6.

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