Tuffaceous sandstone dissolution pore increment quantitative prediction method, device, equipment and medium

Abstract

The embodiment of the present application discloses a tuffaceous sandstone dissolution pore enlargement quantity quantitative prediction method, device, equipment and medium. The method comprises the following steps: collecting geological data of a research object; identifying tuff through thin section identification according to the geological data to determine the original content of tuff and the mineral index; simulating the thermal history according to the geological data to determine the formation temperature; determining the acid-base index according to the geological data based on the diagenetic evolution of tuff interstitial material; and substituting the original content of tuff, the mineral index, the formation temperature and the acid-base index into a preset tuffaceous sandstone dissolution pore enlargement model to determine the tuff dissolution pore enlargement quantity. By increasing the influence degree of the tuff component in the tuffaceous sandstone on the dissolution effect and using the previously constructed tuffaceous sandstone dissolution pore enlargement model to predict the pore enlargement quantity, the quantitative evaluation of the tuff dissolution pore enlargement size of the clastic rock reservoir is realized, thereby providing a basis for reservoir prediction.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of oil and gas exploration and development technology, and in particular to a method, apparatus, equipment and medium for quantitatively predicting the porosity increase caused by dissolution in tuffaceous sandstone. Background Technology

[0002] Against the backdrop of global oil and gas exploration continuously expanding into unconventional oil and gas sectors, tuffaceous sandstone has garnered widespread attention due to its rich oil and gas resources. Tuffaceous sandstone is rich in volcanic clastic material with a diameter of less than 2 mm, with rock fragments and interstitial material primarily composed of terrigenous sedimentary clastic material. In recent years, large-scale tight oil and gas reserves have been discovered in tuffaceous sandstone within numerous oil and gas basins, making tuffaceous sandstone reservoirs a new direction for ensuring oil and gas supply security. Due to the involvement of volcanic clastic components, compared to normal sedimentary sandstone, tuffaceous sandstone exhibits diverse grain origins, complex mineral composition, and decreased mineral stability in its rock fabric, inevitably resulting in multiple diagenetic stages, complex pore structures, and strong reservoir heterogeneity. To explore the geological conditions for the formation of tuffaceous sandstone reservoirs and the genetic mechanism of sweet spot reservoirs, previous studies have investigated the characteristics of tuff dissolution, the influence of tuff presence on sandstone properties and heterogeneity, the characteristics of clay minerals in tuffaceous sandstone, and their relationship with hydrocarbon reservoirs. As an important component of tuffaceous sandstone reservoirs, the secondary pores formed by tuff dissolution can increase the porosity and permeability of sandstone reservoirs, especially significantly contributing to the development of intergranular pores in tight sandstone reservoirs.

[0003] However, previous studies only considered the influence of single factors in tuff dissolution, such as simply establishing models based on temperature, pressure, or pH. However, due to the complexity of dissolution during diagenesis and the continuous cross-coupling of various diagenetic processes such as compaction, cementation, and dissolution throughout geological history, most geological models lack practicality and universality. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and medium for quantitatively predicting the porosity increase caused by dissolution in tuffaceous sandstone. This method considers the influence of tuffaceous components in tuffaceous sandstone on the dissolution process, thereby quantitatively evaluating the porosity increase caused by tuffaceous dissolution in clastic reservoirs and providing a basis for reservoir prediction.

[0005] In a first aspect, embodiments of the present invention provide a method for quantitatively predicting the porosity increase caused by dissolution in tuffaceous sandstone, the method comprising:

[0006] Collect geological data of the research subjects;

[0007] Thin section analysis was performed to identify tuff based on the geological data, in order to determine the original tuff content and mineral index.

[0008] Thermal history simulations were performed based on the geological data to determine the formation temperature.

[0009] Based on the diagenetic evolution of tuffaceous interstitial materials, the acid-base index was determined according to the aforementioned geological data;

[0010] The original tuff content, the mineral index, the formation temperature, and the acid-base index are substituted into a preset tuffaceous sandstone dissolution and porosification model to determine the amount of tuffaceous dissolution and porosification.

[0011] Optionally, the preset tuffaceous sandstone dissolution and pore-enhancing model is:

[0012]

[0013] Wherein, P represents the porosity increase from tuff dissolution, and S0 represents the original content of tuff. The mineral index is represented by C, the acid-base index by T, and the formation temperature by T.

[0014] Optionally, for volcanic glass, potassium feldspar, sodium feldspar, and calcium feldspar, the mineral index is set to 0.25, 0.5, 0.75, and 1.0, respectively.

[0015] Optionally, under weakly acidic conditions, the acid-base index is 1.2, and under weakly alkaline conditions, the acid-base index is 1.0.

[0016] Optionally, the step of identifying tuff based on the geological data includes:

[0017] Based on the pre-set tuff and clay identification table, the tuff is identified using a point counting method according to the geological data.

[0018] Optionally, the geological data includes: top depth of strata, bottom depth of strata, stratum thickness, erosion thickness, deposition time, and erosion time;

[0019] Accordingly, the step of performing thermal history simulation based on the geological data to determine the formation temperature includes:

[0020] Using Petrolmod 2016 geological software, thermal history simulations were performed based on the top depth of the stratum, the bottom depth of the stratum, the thickness of the stratum, the erosion thickness, the deposition time, and the erosion time to determine the temperature of the stratum.

[0021] Optionally, before substituting the original tuff content, the mineral index, the formation temperature, and the acid-base index into a preset tuffaceous sandstone dissolution and porosification model to determine the amount of tuffaceous dissolution and porosification, the method further includes:

[0022] A comprehensive evaluation of the factors influencing dissolution is conducted to establish the pre-defined tuffaceous sandstone dissolution porosity model; wherein, the factors influencing dissolution include tuffaceous composition, formation water pH, and formation temperature.

[0023] Secondly, embodiments of the present invention also provide a device for quantitatively predicting the porosity increase caused by dissolution in tuffaceous sandstone, the device comprising:

[0024] The data collection module is used to collect geological data of the research object;

[0025] The tuff identification module is used to identify tuff based on the geological data through thin section analysis, in order to determine the original tuff content and mineral index.

[0026] The formation temperature determination module is used to perform thermal history simulation based on the geological data in order to determine the formation temperature.

[0027] The acid-base index determination module is used to determine the acid-base index based on the diagenetic evolution of tuffaceous interstitial materials and the geological data.

[0028] The porosity determination module is used to substitute the original tuff content, the mineral index, the formation temperature, and the acid-base index into a preset tuff sandstone dissolution porosity model to determine the tuff dissolution porosity.

[0029] Thirdly, embodiments of the present invention also provide a computer device, the computer device comprising:

[0030] One or more processors;

[0031] Memory, used to store one or more programs;

[0032] When the one or more programs are executed by the one or more processors, the one or more processors implement the quantitative prediction method for porosity increase in tuffaceous sandstone provided in any embodiment of the present invention.

[0033] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the quantitative prediction method for porosity increase in tuffaceous sandstone by dissolution provided in any embodiment of the present invention.

[0034] This invention provides a method for quantitatively predicting the porosity increase caused by dissolution in tuffaceous sandstone. First, geological data of the study object is collected. Then, tuff is identified based on the geological data through thin section analysis to determine the original tuff content and mineral indices. Next, formation temperature and pH are determined through thermal history simulation and diagenetic evolution. Finally, the obtained original tuff content, mineral indices, formation temperature, and pH are substituted into a pre-constructed porosity increase model for tuffaceous sandstone dissolution to predict the amount of porosity increase caused by tuffaceous dissolution. This method, by considering the influence of tuffaceous components on dissolution and using a pre-constructed porosity increase model, achieves a quantitative evaluation of the porosity increase caused by tuffaceous dissolution in clastic reservoirs, thus providing a basis for reservoir prediction. Attached Figure Description

[0035] Figure 1 This is a flowchart of a method for quantitatively predicting the porosity increase of tuffaceous sandstone by dissolution, provided in Embodiment 1 of the present invention.

[0036] Figure 2 This is a schematic diagram of the structure of the quantitative prediction device for the porosity increase of tuffaceous sandstone by dissolution provided in Embodiment 2 of the present invention;

[0037] Figure 3 This is a schematic diagram of the structure of a computer device provided in Embodiment 3 of the present invention. Detailed Implementation

[0038] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0039] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processes, many of these steps can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the steps can be rearranged. The process can be terminated when its operation is complete, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0040] Example 1

[0041] Figure 1This is a flowchart illustrating a method for quantitatively predicting the porosity increase due to dissolution in tuffaceous sandstone, as provided in Embodiment 1 of the present invention. This embodiment is applicable to the quantitative evaluation of porosity increase due to dissolution in clastic rock reservoirs. The method can be executed by the quantitative prediction device for porosity increase due to dissolution in tuffaceous sandstone provided in this embodiment. This device can be implemented in hardware and / or software, and is generally integrated into a computer device. Figure 1 As shown, the specific steps include the following:

[0042] S11. Collect geological data of the research object.

[0043] Specifically, the geological data to be collected may include stratigraphic depth, thickness, depositional time, rock type, diagenesis, diagenetic minerals, tuff type, and formation water medium, etc. For example, taking the Wenchang Formation tuffaceous sandstone reservoir in the Baiyun Depression of the South China Sea as the research object, core and thin section observations show that the Wenchang Formation sandstone is mainly light gray feldspathic lithic sandstone. Quartz and feldspar account for 28%–52% of the clastic grains, and rock fragments account for 43%–70%. The grain size is mostly 0.35–0.86 mm, with moderate sorting (sorting coefficient 2.3), and poor rounding. The interstitial material has a high tuff content, consisting of andesitic and rhyolitic tuff. Dissolution pores generated by tuff dissolution account for 2.2% of the total porosity.

[0044] S12. Through thin section analysis, tuff is identified based on the geological data to determine the original tuff content and mineral index.

[0045] Specifically, by analyzing thin sections and referring to collected geological data, suitable types of sandstone can be selected to quantitatively characterize the original tuff content in the early stages of sedimentary deposition, and the tuff components can be identified to determine the corresponding mineral indices. These mineral indices can be directly selected from multiple preset values, each corresponding to a specific tuff component. The value closest to the corresponding component can be chosen as the mineral index for the research object. For example, in the case of the Wenchang Formation tuffaceous sandstone reservoir in the Baiyun Depression of the South China Sea, observation of rock thin sections can reveal that early calcite-cemented sandstone can be selected to quantitatively characterize the original percentage content of tuff in the early stages of sedimentary deposition.

[0046] Optionally, the step of identifying tuff based on the geological data includes: identifying tuff based on a pre-set tuff and clay identification table, using a point counting method (e.g., 300-350 points). The pre-set tuff and clay identification table can be as shown in Table 1.

[0047] Table 1. Pre-defined identification table for tuff and clay.

[0048]

[0049] S13. Perform thermal history simulation based on the geological data to determine the formation temperature.

[0050] Specifically, the paleotemperature, burial depth, and burial history of the strata of the research object can be determined based on geological data, and then the stratum temperature can be determined by simulating the thermal history of the strata. Optionally, the geological data includes: top depth of the stratum, bottom depth of the stratum, stratum thickness, erosion thickness, deposition time (including deposition start time and deposition end time), and erosion time (including erosion start time and erosion end time). Correspondingly, the step of simulating the thermal history based on the geological data to determine the stratum temperature includes: using Petrolmod 2016 geological software to simulate the thermal history based on the top depth of the stratum, the bottom depth of the stratum, the stratum thickness, the erosion thickness, the deposition time, and the erosion time to determine the stratum temperature. Specifically, the above geological data can be input into the third-party geological software Petrolmod 2016 to calculate the paleotemperature, burial depth, and burial history of the strata, thereby simulating the burial history and thermal history of the strata to determine the stratum temperature.

[0051] S14. Based on the diagenetic evolution of tuffaceous interstitial materials, determine the acid-base index according to the geological data.

[0052] Specifically, the diagenetic evolution of tuffaceous interstitial materials is closely related to the pH, ion content, and flowability of formation water in the burial environment. The pH of formation water is not constant but fluctuates with increasing burial depth and formation temperature. When the temperature reaches 80–120℃, the pH of formation water decreases significantly, and some acidic unstable minerals will dissolve, forming secondary pores. Therefore, the diagenetic evolution of tuffaceous interstitial materials can reflect the acidity or alkalinity of formation water, thereby determining the corresponding acid-base index. The acid-base index can be directly selected from multiple preset values, each corresponding to a certain acidity or alkalinity. Specifically, the value closest to the corresponding acidity or alkalinity can be selected as the acid-base index for the research object. For example, regarding the tuffaceous sandstone reservoir of the Wenchang Formation in the Baiyun Depression of the South China Sea, the lower section of the Wenchang Formation is an important coal-bearing stratum, with coal mainly containing three types of functional groups: aliphatic, aromatic, and oxygen-containing functional groups. During the burial and evolution process, as the reflectivity of vitrinite increases, oxygen-containing functional groups are successively released, and carbon dioxide and carboxylic acids cause the formation water to become acidic.

[0053] S15. Substitute the original tuff content, the mineral index, the formation temperature, and the acid-base index into the preset tuff sandstone dissolution and porosification model to determine the amount of tuff dissolution and porosification.

[0054] Specifically, after obtaining the original tuff content, mineral index, formation temperature, and acid-base index, these parameters can be used as model inputs and substituted into the preset tuff sandstone dissolution and porosity enhancement model to achieve quantitative prediction of the amount of tuff dissolution and porosity enhancement.

[0055] Optionally, the preset tuffaceous sandstone erosion porosity enhancement model is:

[0056]

[0057] Wherein, P represents the porosity increase from tuff dissolution, and S0 represents the original content of tuff. The mineral index is represented by C, the acid-base index by T, and the formation temperature by T.

[0058] Further optionally, the mineral indices for volcanic glass, potassium feldspar, sodium feldspar, and calcium feldspar are set to 0.25, 0.5, 0.75, and 1.0, respectively. Also optionally, the acid-base index is set to 1.2 under weakly acidic conditions and 1.0 under weakly alkaline conditions. As exemplified above, for the Wenchang Formation tuffaceous sandstone reservoir in the Baiyun Depression of the South China Sea, simulation parameters T = 144℃ and S0 = 12% can be selected. Substituting C=1.2 into the above-mentioned preset tuffaceous sandstone dissolution porosity model, we can predict that the tuffaceous dissolution porosity increase is P=3.2%.

[0059] Based on the above technical solution, optionally, before substituting the original tuff content, the mineral index, the formation temperature, and the acid-base index into the preset tuff sandstone dissolution and porosity enhancement model to determine the amount of tuff dissolution and porosity enhancement, the method further includes: comprehensively evaluating the dissolution influencing factors to establish the preset tuff sandstone dissolution and porosity enhancement model; wherein, the dissolution influencing factors include tuff composition, formation water acidity / alkalinity, and formation temperature.

[0060] Specifically, a pre-defined porosity-enhancing model for tuffaceous sandstone dissolution can be established through a comprehensive study of the dissolution mechanism and influencing factors of tuff. Regarding the dissolution mechanism of tuff, as an important component of tuffaceous sandstone, the secondary pores formed by its dissolution can significantly increase the porosity and permeability of tight sandstone reservoirs. The tuffaceous components in sandstone are controlled by volcanic rocks from the same depositional period and the lithology of the source area. Different types of tuff have drastically different effects on the formation of secondary pores in sandstone reservoirs. Generally, acidic tuff is relatively stable under surface and burial conditions, often transforming into components such as silica, phosphothrene, montmorillonite, and illite, and is less likely to form secondary pores. In contrast, intermediate-basic volcanogenic tuff components (mainly including volcanic glass and feldspar crystals) have poor chemical stability and are easily dissolved by organic acids during the mid-diagenetic stage (80℃~120℃) to form secondary pores. Regarding the evolution of volcanic glass, during burial, as the temperature and pressure of the strata increase, the volcanic glass undergoes hydration reactions, transforming into authigenic minerals such as clay minerals, zeolites, and quartz, ultimately forming zeolite cement and siliceous cement within tuffaceous sandstone. Since zeolites are aluminosilicate minerals, the Al content of aluminosilicates... 3+ Feldspar readily combines with the carboxyl groups of organic acids in formation water to form stable complexes, thus creating secondary porosity. Regarding the evolution of feldspar crystal fragments, feldspar, as an important component of intermediate-basic tuff, plays a crucial role in the development of sweet spot reservoirs, especially in deep and ultra-deep tight sandstone reservoirs. The chemical structures of potassium feldspar, sodium feldspar, and calcium feldspar, the three end-members of feldspar, are KAlSi3O8, NaAlSi3O8, and CaAl2Si2O8, respectively. Organic acid fluids, hydrothermal fluids, and atmospheric water leaching during diagenesis can all lead to the dissolution of feldspar minerals, as shown in the following reaction equations:

[0061] 2KAlSi3O8 (potassium feldspar) + 2H + +H₂O→Al₂Si₂O₅(OH)₄(kaolinite) + 4SiO₂(silicon) + 2K + ;

[0062] 2NaAlSi3O8 (albite) + 2H + +H₂O→Al₂Si₂O₅(OH)₄ (kaolinite) + 4SiO₂ (silicon) + 2Na + ;

[0063] CaAl2Si2O8 (calcium feldspar) + 2H + +H₂O→Al₂Si₂O₅(OH)₄(kaolinite) +Ca 2+ .

[0064] Regarding the evaluation of factors influencing dissolution, the tuffaceous components are considered first. Different types of feldspar exhibit varying resistance to physicochemical weathering. Potassium feldspar (KAlSi3O8) is more stable than plagioclase (NaAlSi3O8-CaAl2Si2O8), and among plagioclase, acidic plagioclase (such as albite) is more stable than basic plagioclase (such as calcium feldspar). Therefore, during diagenetic evolution, calcium feldspar forms the highest secondary porosity in tuffaceous components, potassium feldspar the lowest, while albite forms secondary porosity in between. Next, the formation water pH is considered. Under the same temperature and pressure conditions, the solubility of feldspar minerals follows a consistent trend with pH. Under neutral and weakly alkaline conditions, pH changes have little effect on the dissolution of tuffaceous components. Under strongly acidic conditions, with increasing acidity, low pH rapidly increases the dissolution rate of tuffaceous components, leading to a general increase in cation concentration and solubility. Under strongly alkaline conditions, increasing solution alkalinity significantly enhances the dissolution rate of tuffaceous components. Among the three feldspar minerals in tuff—potassium feldspar, sodium feldspar, and calcium feldspar—calcium feldspar exhibits the greatest variation in solubility, while potassium feldspar shows the least. Considering the influence of formation temperature, the dissolution of feldspar minerals in tuff requires relatively high pH levels. + / K + or H + / Na + Pore ​​fluid conditions, therefore H + Increased concentration and K + Na + Decreased ion concentrations are favorable conditions for dissolution. In terrestrial sedimentary basins, lake water is primarily composed of Mg... + Ca + Cl - In a predominantly saline environment, after the deposition of clastic sediments, the environment is characterized by low H2O. + / K + Pore ​​fluid conditions are unfavorable for the dissolution of feldspar minerals. As the burial depth increases and the formation temperature exceeds 80℃, the formation process introduces large amounts of organic acids and carbon dioxide into the reservoir, altering the properties of pore water. This promotes the dissolution of easily soluble components of clastic particles and the formation of secondary pores. Simultaneously, the illiteration of montmorillonite leads to the formation of K... + Further consumption enhances the dissolving power of pore fluids. When the formation temperature exceeds 120℃, organic acids begin to decarboxylate and decompose. Formation pore fluids are then primarily controlled by carbonic acid concentration. Simultaneously, a large amount of kaolinite formed from the early dissolution of feldspar begins illiteration, consuming significant amounts of potassium (K). + Ions, resulting in relatively high H + / K + Pore ​​fluid conditions are maintained, and feldspar dissolution can continue to occur. This is the main reason why dissolution pores are developed in large numbers under deep and ultra-deep burial conditions of tuffaceous sandstone.

[0065] In the early stages of deposition, the tuffaceous components in tuffaceous sandstone significantly degrade its physical properties. However, with increasing burial depth, the tuffaceous components undergo dehydration and shrinkage, developing numerous shrinkage fractures. These fractures create channels for communication between the tuffaceous interstitial material and the formation water medium. Unstable substances within the tuffaceous interstitial material then dissolve, thereby significantly improving the reservoir's storage capacity. Based on the above, and considering the influencing factors of the tuffaceous components in tuffaceous sandstone during the dissolution process, a pre-defined porosity-enhancing model for tuffaceous sandstone dissolution can be established from three aspects: tuffaceous components, formation water pH, and formation temperature. Specifically, it can be as described above:

[0066]

[0067] The technical solution provided in this invention first collects geological data of the research object, then identifies tuff based on the geological data through thin section analysis to determine the original tuff content and mineral index. Next, it determines the formation temperature and acid-base index through thermal history simulation and diagenetic evolution. Finally, it substitutes the obtained original tuff content, mineral index, formation temperature, and acid-base index into a pre-built tuffaceous sandstone dissolution and porosity enhancement model to predict the amount of tuffaceous dissolution and porosity enhancement. By considering the influence of tuffaceous components in tuffaceous sandstone on dissolution and using a pre-constructed tuffaceous sandstone dissolution and porosity enhancement model to predict the amount of porosity enhancement, it achieves a quantitative evaluation of the size of tuffaceous dissolution and porosity enhancement in clastic reservoirs, thus providing a basis for reservoir prediction.

[0068] Example 2

[0069] Figure 2 This is a schematic diagram of the device for quantitatively predicting the porosity increase of tuffaceous sandstone through dissolution, provided in Embodiment 2 of the present invention. This device can be implemented in hardware and / or software, and is generally integrated into a computer device to execute the method for quantitatively predicting the porosity increase of tuffaceous sandstone through dissolution provided in any embodiment of the present invention. Figure 2 As shown, the device includes:

[0070] Data collection module 21 is used to collect geological data of the research object;

[0071] The tuff identification module 22 is used to identify tuff based on the geological data through thin section analysis, so as to determine the original tuff content and mineral index.

[0072] Formation temperature determination module 23 is used to perform thermal history simulation based on the geological data in order to determine the formation temperature;

[0073] Acid-base index determination module 24 is used to determine the acid-base index based on the diagenetic evolution of tuffaceous interstitial materials and the geological data.

[0074] The porosity determination module 25 is used to substitute the original tuff content, the mineral index, the formation temperature, and the acid-base index into a preset tuff sandstone dissolution porosity model to determine the tuff dissolution porosity.

[0075] The technical solution provided in this invention first collects geological data of the research object, then identifies tuff based on the geological data through thin section analysis to determine the original tuff content and mineral index. Next, it determines the formation temperature and acid-base index through thermal history simulation and diagenetic evolution. Finally, it substitutes the obtained original tuff content, mineral index, formation temperature, and acid-base index into a pre-built tuffaceous sandstone dissolution and porosity enhancement model to predict the amount of tuffaceous dissolution and porosity enhancement. By considering the influence of tuffaceous components in tuffaceous sandstone on dissolution and using a pre-constructed tuffaceous sandstone dissolution and porosity enhancement model to predict the amount of porosity enhancement, it achieves a quantitative evaluation of the size of tuffaceous dissolution and porosity enhancement in clastic reservoirs, thus providing a basis for reservoir prediction.

[0076] Based on the above technical solution, optionally, the preset tuffaceous sandstone dissolution and pore-enhancing model is:

[0077]

[0078] Wherein, P represents the porosity increase from tuff dissolution, and S0 represents the original content of tuff. The mineral index is represented by C, the acid-base index by T, and the formation temperature by T.

[0079] Based on the above technical solution, optionally, for volcanic glass, potassium feldspar, sodium feldspar and calcium feldspar, the mineral index is taken as 0.25, 0.5, 0.75 and 1.0 respectively.

[0080] Based on the above technical solution, optionally, the acid-base index is 1.2 under weak acid conditions and 1.0 under weak base conditions.

[0081] Based on the above technical solution, optionally, the condensate identification module 22 is specifically used for:

[0082] Based on the pre-set tuff and clay identification table, the tuff is identified using a point counting method according to the geological data.

[0083] Based on the above technical solution, optionally, the geological data includes: top depth of strata, bottom depth of strata, stratum thickness, erosion thickness, deposition time, and erosion time;

[0084] Accordingly, the formation temperature determination module 23 is specifically used for:

[0085] Using Petrolmod 2016 geological software, thermal history simulations were performed based on the top depth of the stratum, the bottom depth of the stratum, the thickness of the stratum, the erosion thickness, the deposition time, and the erosion time to determine the temperature of the stratum.

[0086] Based on the above technical solution, optionally, the quantitative prediction device for the porosity increase of tuffaceous sandstone dissolution also includes:

[0087] The porosity enhancement model establishment module is used to comprehensively evaluate the influencing factors of dissolution before substituting the original tuff content, the mineral index, the formation temperature, and the acid-base index into the preset tuffaceous sandstone dissolution porosity enhancement model to determine the amount of tuffaceous dissolution porosity enhancement, so as to establish the preset tuffaceous sandstone dissolution porosity enhancement model; wherein, the influencing factors of dissolution include tuffaceous composition, formation water acidity-basement, and formation temperature.

[0088] The quantitative prediction device for the porosity increase of tuffaceous sandstone by dissolution provided in this embodiment of the invention can execute the quantitative prediction method for the porosity increase of tuffaceous sandstone by dissolution provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0089] It is worth noting that in the embodiments of the above-mentioned quantitative prediction device for the pore increase of tuffaceous sandstone erosion, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0090] Example 3

[0091] Figure 3 This is a schematic diagram of the structure of a computer device provided in Embodiment 3 of the present invention, showing a block diagram of an exemplary computer device suitable for implementing the embodiments of the present invention. Figure 3 The computer device shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments of the present invention. Figure 3 As shown, the computer device includes a processor 31, a memory 32, an input device 33, and an output device 34; the number of processors 31 in the computer device can be one or more. Figure 3 Taking a processor 31 as an example, the processor 31, memory 32, input device 33, and output device 34 in a computer device can be connected via a bus or other means. Figure 3 Taking the example of a connection between China and Israel via a bus.

[0092] The memory 32, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the quantitative prediction method for porosity increase in tuffaceous sandstone karstification in this embodiment of the invention (e.g., the data collection module 21, tuffaceous identification module 22, formation temperature determination module 23, acid-base index determination module 24, and porosity determination module 25 in the quantitative prediction device for porosity increase in tuffaceous sandstone karstification). The processor 31 executes various functional applications and data processing of the computer device by running the software programs, instructions, and modules stored in the memory 32, thereby realizing the aforementioned quantitative prediction method for porosity increase in tuffaceous sandstone karstification.

[0093] The memory 32 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 32 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory, or other non-volatile solid-state storage device. In some instances, the memory 32 may further include memory remotely located relative to the processor 31, which can be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0094] Input device 33 can be used to acquire geological data of the research object, and to generate key signal inputs related to user settings and function control of the computer equipment. Output device 34 may include a display screen, which can be used to display prediction results to the user, etc.

[0095] Example 4

[0096] Embodiment 4 of the present invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform a method for quantitatively predicting the porosity increase caused by dissolution in tuffaceous sandstone. The method includes:

[0097] Collect geological data of the research subjects;

[0098] Thin section analysis was performed to identify tuff based on the geological data, in order to determine the original tuff content and mineral index.

[0099] Thermal history simulations were performed based on the geological data to determine the formation temperature.

[0100] Based on the diagenetic evolution of tuffaceous interstitial materials, the acid-base index was determined according to the aforementioned geological data;

[0101] The original tuff content, the mineral index, the formation temperature, and the acid-base index are substituted into a preset tuffaceous sandstone dissolution and porosification model to determine the amount of tuffaceous dissolution and porosification.

[0102] Storage media can be any type of memory device or storage device. The term "storage media" is intended to include: mounting media, such as CD-ROMs, floppy disks, or magnetic tape devices; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (e.g., hard disks or optical storage); registers or other similar types of memory elements. Storage media may also include other types of memory or combinations thereof. Furthermore, storage media may reside in a computer system in which the program is executed, or may reside in a different second computer system connected to the computer system via a network (such as the Internet). The second computer system can provide program instructions to the computer for execution. The term "storage media" can include two or more storage media that may reside in different locations (e.g., in different computer systems connected via a network). Storage media may store program instructions (e.g., specifically implemented as a computer program) that can be executed by one or more processors.

[0103] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the method operations described above, but can also perform related operations in the quantitative prediction method for the amount of tuffaceous sandstone dissolution porosity provided in any embodiment of the present invention.

[0104] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0105] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0106] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0107] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for quantitatively predicting the porosity increase due to dissolution in tuffaceous sandstone, characterized in that, include: Collect geological data of the research subjects; Thin section analysis was performed to identify tuff based on the geological data, in order to determine the original tuff content and mineral index. Thermal history simulations were performed based on the geological data to determine the formation temperature. Based on the diagenetic evolution of tuffaceous interstitial materials, the acid-base index was determined according to the aforementioned geological data; The original tuff content, the mineral index, the formation temperature, and the acid-base index are substituted into a preset tuff sandstone dissolution and porosification model to determine the amount of tuff dissolution and porosification. The preset tuffaceous sandstone dissolution and pore-enhancing model is as follows: ； Wherein, P represents the porosity increase from tuff dissolution, and S0 represents the original content of tuff. C represents the mineral index, C represents the acid-base index, and T represents the formation temperature; The mineral index is directly selected from a set of preset values, each value corresponding to a tuff component. Specifically, the value closest to the component is selected as the mineral index of the research object. For volcanic glass, potassium feldspar, sodium feldspar, and calcium feldspar, the mineral index is set to 0.25, 0.5, 0.75, and 1.0, respectively.

2. The method for quantitatively predicting the porosity increase due to dissolution in tuffaceous sandstone according to claim 1, characterized in that, Under weakly acidic conditions, the acid-base index is 1.2; under weakly alkaline conditions, the acid-base index is 1.

0.

3. The method for quantitatively predicting the porosity increase due to dissolution in tuffaceous sandstone according to claim 1, characterized in that, The identification of tuff based on the geological data includes: Based on the pre-set tuff and clay identification table, the tuff is identified using a point counting method according to the geological data.

4. The method for quantitatively predicting the porosity increase due to dissolution in tuffaceous sandstone according to claim 1, characterized in that, The geological data includes: top depth of strata, bottom depth of strata, stratum thickness, erosion thickness, deposition time, and erosion time; Accordingly, the step of performing thermal history simulation based on the geological data to determine the formation temperature includes: Using Petrolmod 2016 geological software, thermal history simulations were performed based on the top depth of the stratum, the bottom depth of the stratum, the thickness of the stratum, the erosion thickness, the deposition time, and the erosion time to determine the temperature of the stratum.

5. The method for quantitatively predicting the porosity increase due to dissolution in tuffaceous sandstone according to claim 1, characterized in that, Before substituting the original tuff content, the mineral index, the formation temperature, and the acid-base index into the preset tuffaceous sandstone dissolution and porosification model to determine the amount of tuffaceous dissolution and porosification, the method further includes: A comprehensive evaluation of the factors influencing dissolution is conducted to establish the pre-defined tuffaceous sandstone dissolution porosity model; wherein, the factors influencing dissolution include tuffaceous composition, formation water pH, and formation temperature.

6. A device for quantitatively predicting the porosity increase due to dissolution in tuffaceous sandstone, characterized in that, include: The data collection module is used to collect geological data of the research object; The tuff identification module is used to identify tuff based on the geological data through thin section analysis, in order to determine the original tuff content and mineral index. The formation temperature determination module is used to perform thermal history simulation based on the geological data in order to determine the formation temperature. The acid-base index determination module is used to determine the acid-base index based on the diagenetic evolution of tuffaceous interstitial materials and the geological data. The porosity determination module is used to substitute the original tuff content, the mineral index, the formation temperature and the acid-base index into a preset tuff sandstone dissolution porosity model to determine the tuff dissolution porosity. The preset tuffaceous sandstone dissolution and pore-enhancing model is as follows: ； Wherein, P represents the porosity increase from tuff dissolution, and S0 represents the original content of tuff. C represents the mineral index, C represents the acid-base index, and T represents the formation temperature; The mineral index is directly selected from a set of preset values, each value corresponding to a tuff component. Specifically, the value closest to the component is selected as the mineral index of the research object. For volcanic glass, potassium feldspar, sodium feldspar, and calcium feldspar, the mineral index is set to 0.25, 0.5, 0.75, and 1.0, respectively.

7. A computer device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the quantitative prediction method for porosity increase in tuffaceous sandstone as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the quantitative prediction method for porosity increase in tuffaceous sandstone as described in any of claims 1-5.

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