Shale compressive strength evaluation method based on CO2 injection duration and mineral composition

Abstract

The present application relates to a kind of based on CO2 injection length and shale compressive strength evaluation method of mineral component, obtain multiple groups of different CO2 injection length gradient under the quartz content and uniaxial compressive strength data of shale sample, group is obtained according to injection length discrete length sample group;According to the evolution trend of uniaxial compressive strength, adjacent sample group with consistent evolution trend is merged, and multiple continuous injection length subinterval is divided, and the corresponding relationship between quartz content, injection length and uniaxial compressive strength is established in each subinterval;Smooth transition interval is set at the junction position of adjacent subinterval, and interpolation transition rule with CO2 injection length as input variable is constructed.The corresponding relationship formula or target relationship formula is constructed by interpolation rule according to target injection length during evaluation, and the uniaxial compressive strength prediction value is obtained by substituting parameters.The present application is in line with the characteristics of CO2-water rock interaction in stages, which ensures the fitting accuracy and eliminates the prediction mutation at the junction of subinterval.

Description

Technical Field

[0001] The embodiments in this specification relate to the fields of rock mechanics and unconventional oil and gas development, and in particular to a method for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition. Background Technology

[0002] Carbon Capture, Utilization and Storage (CCUS) has become one of the key technological pathways for reducing greenhouse gas emissions. Shale reservoirs, due to their widespread distribution and enormous storage potential, are considered important target formations for CO2 storage. Meanwhile, supercritical CO2 fracturing technology and CO2-enhanced shale gas extraction technology (CO2-ESGR) have received widespread attention in recent years.

[0003] In practical engineering, after CO2 is injected into shale reservoirs, it reacts with formation water to form carbonic acid (H2CO3), creating an acidic environment (pH value can drop to around 4.0). This leads to the chemical dissolution of carbonate minerals (such as calcite and dolomite) in the shale, as well as the hydration, swelling, and dissolution of clay minerals. These mineralogical changes significantly alter the mechanical properties of the shale, directly affecting wellbore stability, caprock sealing, and reservoir stimulation effectiveness. Therefore, accurately evaluating the degree of mechanical strength degradation of shale after CO2 immersion is of great significance for the safety design and effectiveness assessment of related projects. Summary of the Invention

[0004] To address the problems existing in the prior art, this specification provides a method for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition.

[0005] The specific technical solutions of the embodiments in this specification are as follows: On the one hand, the embodiments of this specification provide a method for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition, the method comprising: We acquired quartz content data and uniaxial compressive strength data of shale samples under different carbon dioxide (CO2) injection duration gradients to construct a sample dataset. The shale samples in the sample dataset are grouped according to the CO2 injection duration gradient of each shale sample in the sample dataset to obtain multiple discrete duration sample groups. Based on the evolution of uniaxial compressive strength under each discrete duration sample group, adjacent discrete duration sample groups with consistent evolution patterns are merged to obtain multiple continuous CO2 injection duration segment intervals. For each CO2 injection duration segment, the relationship between quartz content, CO2 injection duration and uniaxial compressive strength is established based on the quartz content data, CO2 injection duration and uniaxial compressive strength data of all discrete duration sample groups included in the CO2 injection duration segment. A smooth transition interval is set at the boundary of two adjacent CO2 injection duration segments, and an interpolation transition rule is constructed with CO2 injection duration as the input variable. The interpolation transition rule is used to calculate the relational parameters corresponding to any CO2 injection duration within the smooth transition interval. When evaluating the uniaxial compressive strength of the shale to be evaluated, the quartz content of the shale to be evaluated and the target CO2 injection time corresponding to the shale to be evaluated are obtained; Determine whether the target CO2 injection duration belongs to a segmented interval or a smooth transition interval, and obtain the target relational expression. Specifically: if the target CO2 injection duration falls within a segmented interval, the relational expression corresponding to that segmented interval is used as the target relational expression; if it falls within a smooth transition interval, the target CO2 injection duration is substituted into the target interpolation transition rule corresponding to that smooth transition interval to calculate the relational expression parameters corresponding to the target CO2 injection duration, and the target relational expression is constructed based on these parameters. The quartz content and CO2 injection duration of the shale to be evaluated are used as inputs to the target relational expression to calculate and output the predicted uniaxial compressive strength of the shale to be evaluated.

[0006] Furthermore, a smooth transition interval is set at the boundary between two adjacent CO2 injection duration segments, including: Determine the boundary time point between two adjacent CO2 injection duration segments; Centered on the boundary time point, a preset transition time is extended into the previous CO2 injection duration segment interval and the next CO2 injection duration segment interval, respectively, to form the smooth transition interval covering the boundary time point.

[0007] Furthermore, an interpolation transition rule is constructed with CO2 injection duration as the input variable, including: Extract the relational parameters corresponding to each of two adjacent CO2 injection duration segments; The relational parameters of two adjacent CO2 injection duration segments are used as the two endpoint values ​​of the interpolation; Using the CO2 injection duration as the interpolation independent variable, and based on the two endpoint values, a linear weighted interpolation rule is established within the smooth transition interval to determine the relationship between the parameters and the CO2 injection duration, thus obtaining the interpolation transition rule.

[0008] Furthermore, the shale samples in the sample dataset are grouped according to the CO2 injection duration gradient of each shale sample in the sample dataset to obtain multiple discrete duration sample groups, including: Based on the CO2 injection duration corresponding to each shale sample, the samples were classified into the same group, resulting in multiple discrete duration sample groups corresponding to fixed CO2 injection durations.

[0009] Furthermore, based on the evolution of uniaxial compressive strength under each discrete duration sample group, adjacent discrete duration sample groups with consistent evolution patterns are merged to obtain multiple continuous CO2 injection duration segment intervals, including: Based on the inflection point of the relative rate of change of uniaxial compressive strength, the injection duration is divided into at least two consecutive segments: the initial rapid response stage, the mid-term structural adjustment stage, and the late-term deterioration and evolution stage.

[0010] Furthermore, based on the quartz content data, CO2 injection duration, and uniaxial compressive strength data of all discrete duration sample groups included in the CO2 injection duration segment interval, a relationship between quartz content, CO2 injection duration, and uniaxial compressive strength under the CO2 injection duration segment interval is established, including: Within each CO2 injection duration segment, with quartz content and CO2 injection duration as independent variables and uniaxial compressive strength as the dependent variable, a mapping relationship between the independent and dependent variables is established through data fitting, thus obtaining the relationship formula for that CO2 injection duration segment.

[0011] On the other hand, embodiments of this specification also provide a device for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition, the device comprising: The sample dataset construction unit is used to acquire quartz content data and uniaxial compressive strength data of shale samples under different carbon dioxide (CO2) injection duration gradients to construct the sample dataset. The discrete duration sample group division unit is used to group the shale samples in the sample dataset according to the CO2 injection duration gradient of each shale sample in the sample dataset to obtain multiple discrete duration sample groups. The CO2 injection duration segmentation unit is used to merge adjacent discrete duration sample groups with consistent evolution patterns based on the evolution pattern of uniaxial compressive strength under each discrete duration sample group, thereby obtaining multiple continuous CO2 injection duration segmentation intervals. The relational fitting unit is used to establish the relational formula between quartz content, CO2 injection time and uniaxial compressive strength for each CO2 injection time segment interval, based on the quartz content data, CO2 injection time and uniaxial compressive strength data of all discrete time sample groups included in the CO2 injection time segment interval. An interpolation transition rule construction unit is used to set a smooth transition interval at the boundary of two adjacent CO2 injection duration segment intervals and construct an interpolation transition rule with CO2 injection duration as the input variable. The interpolation transition rule is used to calculate the relational parameters corresponding to any CO2 injection duration within the smooth transition interval. The data acquisition unit for shale to be evaluated is used to acquire the quartz content of the shale to be evaluated and the target CO2 injection duration corresponding to the shale to be evaluated when evaluating the uniaxial compressive strength of the shale to be evaluated. The target relation determination unit is used to determine whether the target CO2 injection duration belongs to a target CO2 injection duration segment interval or a target smooth transition interval, and to obtain a target relation. Specifically: if the target CO2 injection duration is located within a target CO2 injection duration segment interval, the relation corresponding to that segment interval is used as the target relation; if the target CO2 injection duration is located within a target smooth transition interval, the target CO2 injection duration is substituted into the target interpolation transition rule corresponding to that smooth transition interval to calculate the relation parameters corresponding to the target CO2 injection duration, and the target relation is constructed based on these parameters. The uniaxial compressive strength prediction calculation unit is used to take the quartz content and CO2 injection duration of the shale to be evaluated as inputs to the target relation, calculate the predicted uniaxial compressive strength of the shale to be evaluated, and output it.

[0012] On the other hand, embodiments of this specification also provide a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the above-described method.

[0013] On the other hand, embodiments of this specification also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0014] On the other hand, embodiments of this specification also provide a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method.

[0015] The methods described in this specification have at least the following technical effects: (1) Identify the modulating effect of CO2 injection state (i.e., after CO2 is injected into the shale reservoir, it reacts with formation water to form carbonic acid, and the state of carbonic acid immersion) on the mineral-strength relationship. The embodiments in this specification no longer presuppose that "high quartz necessarily corresponds to high strength", but instead characterize the relationship before and after immersion through interaction terms.

[0016] (2) The calculation process is transparent and reproducible. The methods in the embodiments of this specification clearly provide the input variables, group statistics, regression formulas, coefficient calculation methods and example coefficients, which are convenient for those skilled in the art to verify and regionalize.

[0017] (3) It can reduce the workload of repetitive mechanical testing. After the target area is calibrated, the mechanical parameters of similar shale can be quickly screened by X-ray diffraction (XRD) test using a small amount of quartz content data; the actual accuracy depends on the calibration sample size and the consistency of lithology, temperature and pressure and soaking time.

[0018] (4) It can be extended to multi-parameter evaluation. In addition to uniaxial compressive strength, when the corresponding calibration data is available, similar models can be established for Young's modulus and Poisson's ratio; other mineral components such as carbonate minerals, clay minerals and feldspar can be used as auxiliary explanatory variables or extended input variables to improve the applicability and interpretability of the model.

[0019] (5) Clear engineering output. The output includes predicted values, relative change rates, model errors and applicable range, which can be used as an auxiliary basis for screening caprock stability, wellbore stability and fracturing sections. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this specification 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 only some embodiments of the embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 The diagram shown is a flowchart illustrating a method for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition, as described in this specification. Figure 2 The diagram shown is a schematic representation of a process in which a smooth transition interval is set at the boundary between two adjacent CO2 injection duration segments in an embodiment of this specification. Figure 3 The diagram shown is a flowchart illustrating the process of constructing an interpolation transition rule with CO2 injection duration as the input variable in an embodiment of this specification. Figure 4 The diagram shown is a schematic of a standard core sample used in an embodiment of this specification. Figure 5 The diagram shown is a schematic representation of the powder sample in an embodiment of this specification. Figure 6 The figure shown is a graph showing the relationship between quartz content and UCS of the samples before and after immersion in the embodiments of this specification. Figure 7 The diagram shown is a schematic representation of a shale compressive strength evaluation device based on CO2 injection duration and mineral composition, as described in an embodiment of this specification. Figure 8 The diagram shown is a structural schematic of the computer device according to an embodiment of this specification.

[0022] [Explanation of Figure Markers]: 701. Sample Dataset Construction Unit; 702. Discrete duration sample group partitioning unit; 703. CO2 injection duration segmentation unit; 704. Relational fitting unit; 705. Interpolation Transition Rule Construction Unit; 706. Shale data acquisition unit to be evaluated; 707. Target Relationship Determination Unit; 708. Calculation unit for predicted uniaxial compressive strength; 802. Computer equipment; 804. Processing equipment; 806. Storage resources; 808. Drive mechanism; 810. Input / Output Module; 812. Input devices; 814. Output devices; 816. Presentation equipment; 818. Graphical User Interface; 820. Network interface; 822. Communication link; 824. Communication bus. Detailed Implementation

[0023] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the embodiments of this specification.

[0024] It should be noted that the terms "first," "second," etc., in the description, claims, and accompanying drawings of the embodiments in this specification are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data can be used interchangeably where appropriate so that the embodiments described herein can be implemented in an order different from that illustrated or described in the specification. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0025] It should be noted that the acquisition, storage, use, and processing of data in the technical solutions of the embodiments of this specification all comply with the relevant provisions of national laws and regulations.

[0026] It should be noted that in the embodiments of this specification, certain software, components, models, and other existing solutions in the industry may be mentioned. These should be considered as exemplary, and their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but does not mean that the applicant has already used or necessarily used such a solution. Similarly, the descriptions of prediction algorithms, table organization forms, and hardware structures are also exemplary.

[0027] The applicant compiled 12 shale samples from the supporting data, including two samples before soaking, and two samples each soaked in supercritical CO2 and formation water for 1 h, 3 h, 96 h, 192 h, and 288 h. The soaking temperature was 90 ℃ and the pressure was 40 MPa. XRD whole-rock mineral quantitative analysis was used to obtain the relative mass content of each mineral, in wt%. Preliminary results show that under the experimental conditions, the soaking state changes the relationship between quartz content and uniaxial compressive strength (UCS); Young's modulus and Poisson's ratio can be used as auxiliary mechanical response parameters obtained from the same uniaxial compression test, but the existing sample size is insufficient to establish an independent, stable, and significant correlation between these two parameters and the content of any single mineral.

[0028] Specifically: In the two samples before soaking, when the quartz content increased from 19.5 wt% to 33.2 wt%, the uniaxial compressive strength increased from 167.19 MPa to 184.39 MPa, showing a positive slope.

[0029] When the 10 samples were analyzed together after soaking, the Pearson correlation coefficient between quartz content and uniaxial compressive strength was -0.867 (p≈0.0012), showing a strong negative correlation; the slopes of both points for each soaking time group were also negative.

[0030] Based on this, the embodiments of this specification provide a method for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition. Figure 1 The diagram shown is a flowchart illustrating a method for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition, as described in this specification. The order of steps listed in the embodiment is merely one possible execution order among many and does not represent the only possible order. In actual system or device products, the methods shown in the embodiment or accompanying drawings can be executed sequentially or in parallel. Specifically, as shown... Figure 1 As shown, the method may include: Step 101: Obtain quartz content data and uniaxial compressive strength data of shale samples under different CO2 injection duration gradients, and construct a sample dataset; Step 102: Group the shale samples in the sample dataset according to the CO2 injection duration gradient of each shale sample in the sample dataset to obtain multiple discrete duration sample groups; Step 103: Based on the evolution of uniaxial compressive strength under each discrete duration sample group, merge adjacent discrete duration sample groups with consistent evolution patterns to obtain multiple continuous CO2 injection duration segment intervals. Step 104: For each CO2 injection duration segment, based on the quartz content data, CO2 injection duration and uniaxial compressive strength data of all discrete duration sample groups included in the CO2 injection duration segment, establish the relationship between quartz content, CO2 injection duration and uniaxial compressive strength in the CO2 injection duration segment. Step 105: Set a smooth transition interval at the boundary of two adjacent CO2 injection duration segments, and construct an interpolation transition rule with CO2 injection duration as the input variable. The interpolation transition rule is used to calculate the relational parameters corresponding to any CO2 injection duration within the smooth transition interval. Step 106: When evaluating the uniaxial compressive strength of the shale to be evaluated, obtain the quartz content of the shale to be evaluated and the target CO2 injection time corresponding to the shale to be evaluated; Step 107: Determine whether the target CO2 injection duration belongs to a segmented interval or a smooth transition interval, and obtain the target relational expression. Specifically: if the target CO2 injection duration is within a segmented interval, the relational expression corresponding to that segmented interval is used as the target relational expression; if the target CO2 injection duration is within a smooth transition interval, the target CO2 injection duration is substituted into the target interpolation transition rule corresponding to that smooth transition interval to calculate the relational expression parameters corresponding to the target CO2 injection duration, and the target relational expression is constructed based on these parameters. Step 108: Using the quartz content and CO2 injection duration of the shale to be evaluated as inputs to the target relation, calculate and output the predicted uniaxial compressive strength of the shale to be evaluated.

[0031] In the embodiments of this specification, firstly, quartz content data and uniaxial compressive strength data of shale samples under different CO2 injection duration gradients are obtained to construct a sample dataset.

[0032] In this embodiment, outcrop shale samples from the target reservoir were selected and processed into standard core columns with a diameter of 25 mm and a height of 50 mm. The bedding angle was controlled at 0° to eliminate heterogeneity interference. The experiment simulated the in-situ reservoir conditions, setting the soaking temperature at 90℃ and the pressure at 40 MPa. The real environment after CO2 injection into the reservoir was simulated by the combined action of supercritical CO2 and formation water from the target block. The formation water was of the NaHCO3 type with a total mineralization of 11368 mg / L. Six injection duration gradients were set up: no injection (0 h), 1 h, 3 h, 96 h, 192 h, and 288 h. Two parallel samples were set up for each group, for a total of 12 experimental samples.

[0033] XRD whole-rock mineral quantitative analysis yielded the following results: After mechanical experiments, the core was ground to 200-mesh powder, and whole-rock mineral testing was performed using XRD equipment to obtain the relative mass content of components such as quartz, carbonate minerals, and clay minerals. Quartz content data was extracted as the core input parameter.

[0034] Uniaxial compressive strength data are obtained through uniaxial compression tests: uniaxial compression tests are conducted on each group of core columns according to rock mechanics test standards, stress-strain curves are collected, and the peak strength is read as the uniaxial compressive strength of the corresponding sample. Auxiliary mechanical parameters such as Young's modulus and Poisson's ratio can be obtained simultaneously.

[0035] The CO2 injection time, quartz content, and uniaxial compressive strength of each sample were matched one-to-one to form a complete sample dataset.

[0036] Then, the samples were grouped according to the CO2 injection duration gradient of each shale sample in the sample dataset, resulting in multiple discrete duration sample groups. Specifically, based on the CO2 injection duration corresponding to each shale sample, shale samples with the same CO2 injection duration were grouped into the same group, resulting in multiple discrete duration sample groups corresponding to fixed CO2 injection durations. Finally, six discrete duration sample groups were obtained, each corresponding to a fixed injection duration point, including a baseline sample group without CO2 injection.

[0037] Then, based on the evolution law of uniaxial compressive strength corresponding to each discrete duration sample group, adjacent discrete duration sample groups with consistent evolution trends are merged to obtain multiple continuous CO2 injection duration segment intervals.

[0038] Specifically, this specification's embodiments, based on the inflection point of the relative change rate of uniaxial compressive strength, divide the injection duration into at least two consecutive segments: an initial rapid response stage, a mid-term structural adjustment stage, and a late-stage deterioration and evolution stage. First, the relative change rate of uniaxial compressive strength relative to the non-injected baseline group is calculated for each discrete duration sample group, with the inflection point of the relative change rate serving as the basis for stage division. The reason for using the inflection point of the relative change rate for division is that the interaction between CO2 and shale water has a staged characteristic; the dominant reaction mechanisms differ in different stages, and the corresponding strength evolution rate will show a clear inflection point. The inflection point position is the time node where the reaction mechanism changes. Segmentation based on this principle matches the actual physicochemical process, rather than being an arbitrary segmentation in a purely mathematical sense.

[0039] Based on the evolutionary characteristics of the experimental data, the injection duration can be divided into three continuous stages, and the characteristics of each stage are as follows: (1) Initial rapid reaction stage (0~1h): After CO2 injection, it quickly dissolves in the formation water to form carbonic acid. The carbonate cement undergoes rapid dissolution, the rock cement strength decreases rapidly, and the uniaxial compressive strength shows a rapid decreasing trend. During this stage, mineral dissolution is concentrated on the particle surface, and the strength change rate is fast.

[0040] (2) Mid-term structural adjustment stage (1~192h): As the reaction proceeds, clay minerals undergo hydration expansion and partial dissolution, the pore structure is reconstructed, the stress relationship of the rock's internal skeleton is redistributed, and the uniaxial compressive strength shows the characteristics of first fluctuating and rising and then stabilizing. Moreover, the correlation between quartz content and compressive strength changes. During this stage, the internal structure of the rock is in a dynamic adjustment process, and the reaction mechanism is complex.

[0041] (3) Later stage of deterioration and evolution (192~288h): The dissolution extends to the deep interior of the rock, the interparticle connection skeleton is continuously weakened, the uniaxial compressive strength shows a downward trend again, and the deterioration rate tends to stabilize.

[0042] Because the dominant reaction mechanisms differ across the three stages, the mapping relationships between quartz content, injection duration, and compressive strength exhibit significant differences. A single global formula cannot simultaneously ensure the fitting accuracy for each stage. Therefore, this embodiment employs a piecewise fitting approach, establishing intensity correlation formulas for each stage separately. Ultimately, three consecutive CO2 injection duration segments are obtained, corresponding to the initial rapid response stage, the mid-term structural adjustment stage, and the late-stage deterioration and evolution stage, respectively.

[0043] For each CO2 injection duration segment, the relationship between quartz content, CO2 injection duration and uniaxial compressive strength is established based on the quartz content data, CO2 injection duration and uniaxial compressive strength data of all discrete duration sample groups included in the segment.

[0044] Specifically, within each CO2 injection duration segment, quartz content and CO2 injection duration are used as independent variables, and uniaxial compressive strength is used as the dependent variable. A data regression fitting method is employed to establish the mapping relationship between the independent and dependent variables, yielding the corresponding formula for that segment. The specific functional form of the formula can be flexibly chosen based on the data distribution characteristics of that segment, including but not limited to multivariate linear functions, polynomial functions, etc. There is no need to limit the uniform form; the selection criterion is the best fit within that segment, ensuring the prediction accuracy at each stage.

[0045] Then, a smooth transition interval is set at the boundary of two adjacent CO2 injection duration segments, and an interpolation transition rule with CO2 injection duration as the input variable is constructed to calculate the relational parameters corresponding to any CO2 injection duration within the smooth transition interval.

[0046] The technical problem solved by setting a smooth transition interval is that if the two segments are hard switched directly with time points as the boundary, the intensity prediction value at the boundary will be discontinuous and abrupt. However, the water-rock reaction between CO2 and shale is a continuous and gradual physicochemical process. There is no abrupt point in the evolution of rock mechanical properties. The prediction results of hard segmentation do not conform to objective physical laws and will introduce prediction errors in the boundary area.

[0047] The principle of setting a smooth transition interval is as follows: in the transition area at the boundary of stages, the relationship between the previous stage and the relationship between the next stage is smoothly connected by continuous parameter interpolation, so as to ensure that the intensity prediction result changes continuously with the injection time.

[0048] Specifically, such as Figure 2 The diagram shown is a schematic representation of a process in this specification where a smooth transition interval is set at the boundary between two adjacent CO2 injection duration segments, including: Step 201: Determine the boundary time point between two adjacent CO2 injection duration segments; Step 202: Taking the boundary time point as the center, extend a preset transition time into the previous CO2 injection duration segment interval and the next CO2 injection duration segment interval respectively, to form the smooth transition interval covering the boundary time point.

[0049] For example, the boundary between the initial rapid response phase and the mid-term structural adjustment phase is 1 hour, which can be extended to both sides by 0.5 hours to form a smooth transition interval of 0.5 hours to 1.5 hours.

[0050] like Figure 3 The diagram shown is a flowchart illustrating the construction of an interpolation transition rule with CO2 injection duration as the input variable in an embodiment of this specification, including: Step 301: Extract the relational parameters corresponding to each of the two adjacent CO2 injection duration segments; Step 302: Use the relational parameters of two adjacent CO2 injection duration segment intervals as the two endpoint values ​​of the interpolation; Step 303: Using the CO2 injection duration as the interpolation independent variable, and based on the two endpoint values, establish a linear weighted interpolation rule in the smooth transition interval in which the relational parameters change with the CO2 injection duration, and obtain the interpolation transition rule.

[0051] This can be understood as follows: by using this rule, any CO2 injection duration within the transition interval can be input, and the corresponding relational parameters under the injection duration can be output. Moreover, the parameters change continuously and gradually with the injection duration, which is different from the relational parameters that remain unchanged within each segment interval.

[0052] The technical effect of this smooth transition design is that it retains the advantage of high accuracy of segmented fitting while eliminating abrupt changes in prediction at the segment boundary, making the intensity prediction results continuous and smooth throughout the entire time range, which is more in line with the real law of shale mechanical property deterioration and effectively improves the evaluation accuracy of the boundary area.

[0053] When evaluating the uniaxial compressive strength of the shale to be evaluated, the quartz content of the shale and the corresponding target CO2 injection duration are obtained. For example, for the caprock of a target well, the quartz content is obtained through XRD testing, and the CO2 sequestration duration designed for the engineering project is used as the target CO2 injection duration.

[0054] Then, the interval to which the target CO2 injection duration belongs is determined, and the target relation is obtained: if the target CO2 injection duration is within a certain CO2 injection duration segment interval, the relation corresponding to that segment interval is directly used as the target relation; if the target CO2 injection duration is within a certain smooth transition interval, the target CO2 injection duration is substituted into the interpolation transition rule corresponding to that smooth transition interval to calculate the relation parameters corresponding to the target injection duration, and then the corresponding target relation is constructed based on the relation parameters.

[0055] Finally, the quartz content of the shale to be evaluated and the target CO2 injection duration are substituted into the target relationship to calculate and output the predicted uniaxial compressive strength of the shale. The output can also include information such as the applicable conditions corresponding to the predicted value and the model fitting error range, ensuring the rigor of engineering applications.

[0056] The uniaxial compressive strength prediction value obtained in this embodiment can directly support decision-making applications in various engineering scenarios. For example, in the CO2 geological storage scenario, it can be used to assess the mechanical stability of caprock shale under long-term CO2 injection, determine the safety of caprock sealing, and provide a basis for safety evaluation of storage sites. In the CO2 fracturing scenario, it can be used to calculate the degree of strength degradation of shale in different layers under the designed soaking time, and select layers with moderate strength degradation for fracturing, taking into account both fracture propagation effect and wellbore stability. In the CO2-enhanced shale gas extraction scenario, it can be used to assess the proppant embedding risk and changes in fracture conductivity after reservoir stimulation, providing a reference for optimizing development schemes.

[0057] In some other embodiments of this specification, a relationship between quartz content and uniaxial compressive strength can also be established. For example, using quartz content x and immersion state (i.e., CO2 injection) indicator variable I as input, where I=0 when not immersed and I=1 after immersion, the following formula can be established: y = β0 + β1x + β2I + β3xI In the formula, y represents the uniaxial compressive strength; when the target area has corresponding calibration data, y can also be Young's modulus E or Poisson's ratio ν. β0-β3 are all fitting parameters, where β1 can be defined as the slope of quartz content before soaking; β1+β3 can be defined as the slope of quartz content in the combined samples after soaking; β3 can be defined as the modulation of the direction and amplitude of the mineral-mechanical relationship by the soaking state.

[0058] In some other embodiments of this specification, the univariate linear relationship for a single time group can be: y=c(t)x+d(t) The slope c(t) and intercept d(t) are obtained by the following formulas: c(t)=Σ(x i - )(y i - ) / Σ(x i - ) 2 d(t)= -c(t)

[0059] Where t represents time, x i This indicates the quartz content at time t. y represents the average quartz content across the CO2 injection duration segments. i This represents the uniaxial compressive strength at time t. This represents the mean uniaxial compressive strength of the CO2 injection duration segment.

[0060] Goodness of fit according to R 2=1-Σ(y i - i ) 2 / Σ(y i - ) 2 calculate, i This represents the predicted uniaxial compressive strength. Regression results for each soaking time group are used to characterize the relationship between quartz content and uniaxial compressive strength under different soaking conditions, with soaking time serving as the grouping condition. The comprehensive evaluation model uses soaking state I, quartz content x, and the interaction term xI as core variables. Based on calibration data from the target area, total carbonate mineral content, total clay mineral content, feldspar content, and other XRD mineral components can be introduced as auxiliary explanatory variables or extended model variables to improve the model's applicability and interpretability. Model coefficients and their applicable scope are calibrated based on the lithology of the target shale and the experimental conditions.

[0061] It should be noted that the embodiments in this specification utilize the observable characteristic of "the statistical relationship between changes in immersion state and mineral composition and mechanical parameters." Based on existing supporting data, the following interpretations can be made, but mechanisms that have not been verified by microscopic experiments are not considered essential technical features, nor are mineral variables that have not undergone significance verification considered independent causal conclusions: (1) Before soaking, quartz can be used as a rigid skeleton component, and its content and uniaxial compressive strength show a positive slope in the two existing samples.

[0062] (2) After soaking, the mineral particles, cement and pore structure may be affected by CO2-water-rock interaction. The relative content and structural contribution of components such as carbonate minerals, clay minerals and feldspar may change. Therefore, the relative content of quartz is no longer necessarily equal to the effective load-bearing skeleton ratio. The quartz content in the combined sample after soaking is negatively correlated with the uniaxial compressive strength.

[0063] (3) The given content is a relative mass percentage, which is closed composition data. The change in the relative content of a certain mineral between different samples cannot prove that the mineral has undergone absolute dissolution or formation. Mechanism judgment also needs to be combined with mass change, solution ions, pore structure or microscopic characterization.

[0064] Example 1: Coefficient calculation based on existing experimental support data: Step 1: Sample preparation: Experimental samples such as Figure 4 and Figure 5 As shown, it contains a total of 12 standard core columns, among which, Figure 4 The diagram shown is a schematic representation of a standard core sample used in an embodiment of this specification. Figure 4As shown, the sample diameter was 25 mm and the height was 50 mm. Based on different processing conditions, the samples were divided into 6 groups, each containing 2 standard core samples: the sample before soaking, and samples soaked for 1 h, 3 h, 96 h, 192 h, and 288 h under the combined action of supercritical CO2 and formation water. After the uniaxial compression experiment, the corresponding cores were ground to 200 mesh, resulting in 12 powder samples. Figure 5 The diagram shown is a schematic representation of the powder sample in an embodiment of this specification.

[0065] Supercritical CO2 + formation water was used as the soaking medium in each soaking group. The formation water was based on a real formula from a certain region, and its specific composition is shown in Table 1. The water type was NaHCO3, the total mineralization was 11368 mg / L, the soaking temperature was 90 ℃, and the pressure was 40 MPa.

[0066] Table 1 Formation water formulation

[0067] Step 2: Processing mechanical parameters and XRD data

[0068] Uniaxial compressive strength (UCS), Young's modulus (E), and Poisson's ratio (ν) of each standard core sample were obtained through uniaxial compression tests. The cores were then ground, and XRD analysis was used to determine the mineral composition of the corresponding samples. The mechanical test data of the cores and the XRD test data of the powder samples corresponded one-to-one according to sample number, as shown in Table 2. Table 2 lists the soaking conditions, UCS, E, ν, and the contents of quartz, carbonate minerals, and clay minerals for each sample. UCS and quartz content were used to establish the core interaction model of this embodiment; E and ν were used as auxiliary mechanical response parameters; and other mineral components were used as auxiliary explanatory variables or extended model variables. As can be seen from Table 2, the mechanical parameters and mineral compositions of the samples differed under different soaking conditions; therefore, the model coefficients should be calibrated using representative samples from the target area.

[0069] Table 2 Key XRD Components and Uniaxial Compressive Mechanical Parameters of Samples

[0070] Step 3: Group Statistics and Relative Changes

[0071] The mean and sample standard deviation of UCS, E and ν for each time group were calculated, and the relative rate of change was calculated with the mean of the unsoaked group as the benchmark. The results are shown in Table 3.

[0072] Table 3. Statistics and relative changes of mechanical parameters for each time group

[0073] Note: The rate of change is based on the mean of the unsoaked group. Positive values ​​indicate an increase in the group mean, and negative values ​​indicate a decrease in the group mean. Since the samples in each group are not paired before and after testing, the rate of change also includes the effect of sample heterogeneity.

[0074] Step 5: Regression and Interaction Models

[0075] An evaluation model was constructed using quartz content x, immersion state I, and their interaction term xI. Model parameters and fitting results are shown in Table 4. This embodiment uses uniaxial compressive strength (UCS) as the core evaluation index. The model's coefficient of determination R0 is also shown. 2 The coefficient of variation was 0.7636, the interaction term coefficient β3 was -3.3470, and the significance test result p was approximately 0.0158. Before soaking, the regression slope between quartz content and UCS was +1.2555; after soaking, the regression slope of the combined samples was -2.0915, indicating that the soaking state changes the direction of the statistical relationship between quartz content and UCS.

[0076] Table 4. Model parameters and fitting results before and after soaking.

[0077] Step 6: Result Interpretation and Verification Requirements

[0078] To further compare the relationship between quartz content and UCS under different soaking conditions, descriptive linear fitting was performed on each soaking time group. The resulting slopes, intercepts, and relationship directions are shown in Table 5. Table 5 shows that the regression slope of the unsoaked group is positive, while the regression slopes of all soaking time groups are negative, consistent with the overall regression direction of the merged samples after soaking. This further indicates that the soaking state may alter the direction of the statistical relationship between quartz content and UCS. Since each group contains only two samples, the coefficients in the table are mainly used to describe the relationship direction and are not used as a basis for independent prediction or extrapolation.

[0079] The results of this embodiment show that under the experimental conditions, the immersion state can modulate the statistical relationship between quartz content and UCS, causing the regression slopes before and after immersion to exhibit different directions. Given the small sample size of each immersion time group, the regression results for each time group are mainly used to characterize the direction of the relationship; the comprehensive interaction model is suitable for shale evaluation matching the lithology and experimental conditions of this embodiment. For evaluation objects with different lithologies, or those exceeding the range of supercritical CO2 and formation water combination media, 90 ℃, 40 MPa, and 1-288h conditions, the model coefficients should be recalibrated using representative samples from the target area. Young's modulus E and Poisson's ratio ν are used as auxiliary mechanical response parameters and evaluated after obtaining the corresponding calibration data.

[0080] Table 5 Quartz Content—Example Coefficients of UCS by Time Group

[0081] Note: The grouping coefficients listed in Table 5 are mainly used to characterize the direction of the relationship; when used for specific evaluation, the model should be calibrated using representative samples from the target area.

[0082] like Figure 6 The figure shows the quartz content-UCS relationship between the samples before and after immersion in this embodiment of the specification. The fitted lines of the unimmersed samples and the combined samples after immersion show different slope directions, which is consistent with the group analysis results shown in Table 5. Under the experimental conditions of this embodiment, the immersion state can modulate the statistical relationship between quartz content and UCS.

[0083] Example 2: Engineering Application – Stability Assessment of CO2 Storage Cap Layer

[0084] In CO2 geological storage projects, a long-term stability evaluation of the caprock shale of the target storage layer is required. The specific steps are as follows: (1) Take 5-10 representative samples of caprock shale and perform XRD whole-rock mineral analysis to obtain the original quartz content of each sample; (2) The longest time value in this embodiment should not be directly extrapolated to 100 years or 1000 years; long-term evaluation should be supplemented with long-term immersion data or a validated time scale conversion model; (3) Using the prediction model established in Example 1, calculate the strength degradation rate of each sample under the target immersion time; (4) The thresholds for the stable zone, transition zone and risk zone should be determined in combination with the allowable strength of the target project, in-situ stress and model error, and a fixed 20% / 40% threshold that has not been verified by project data should not be used.

[0085] Example 3: Engineering Application – Optimal Selection of CO2 Fracturing Sections

[0086] In CO2 fracturing design, it is necessary to select a section that balances fracturing effectiveness with wellbore stability. The specific steps are as follows: (1) XRD mineral analysis was performed on the candidate shale to obtain the quartz content distribution profile; (2) Calculate the strength degradation rate at each depth point under the design soaking time (fracturing fluid flowback cycle) using the prediction model; (3) The segment ordering is carried out in combination with the predicted UCS, E, ν and their uncertainties; the specific preferred threshold should be determined by the target area fracturing test and wellbore stability constraints, and the fixed 30% to 50% range is not preset.

[0087] Based on the same inventive concept, embodiments of this specification also provide a device for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition, such as... Figure 7The diagram shown is a structural schematic of a shale compressive strength evaluation device based on CO2 injection duration and mineral composition, as described in an embodiment of this specification. The device includes: Sample dataset construction unit 701 is used to acquire quartz content data and uniaxial compressive strength data of shale samples under different carbon dioxide (CO2) injection duration gradients to construct sample datasets; The discrete duration sample grouping unit 702 is used to group the shale samples in the sample dataset according to the CO2 injection duration gradient of each shale sample in the sample dataset to obtain multiple discrete duration sample groups. CO2 injection duration segmentation unit 703 is used to merge adjacent discrete duration sample groups with consistent evolution patterns according to the evolution pattern of uniaxial compressive strength under each discrete duration sample group, so as to obtain multiple continuous CO2 injection duration segmentation intervals. The relational fitting unit 704 is used to establish the relational formula between quartz content, CO2 injection time and uniaxial compressive strength for each CO2 injection time segment interval, based on the quartz content data, CO2 injection time and uniaxial compressive strength data of all discrete time sample groups included in the CO2 injection time segment interval. The interpolation transition rule construction unit 705 is used to set a smooth transition interval at the boundary of two adjacent CO2 injection duration segment intervals and construct an interpolation transition rule with CO2 injection duration as the input variable. The interpolation transition rule is used to calculate the relational parameters corresponding to any CO2 injection duration within the smooth transition interval. The data acquisition unit 706 for the shale to be evaluated is used to acquire the quartz content of the shale to be evaluated and the target CO2 injection time corresponding to the shale to be evaluated when evaluating the uniaxial compressive strength of the shale to be evaluated. The target relation determination unit 707 is used to determine whether the target CO2 injection duration belongs to a target CO2 injection duration segment interval or a target smooth transition interval, and to obtain a target relation. Specifically: if the target CO2 injection duration is located within a target CO2 injection duration segment interval, the relation corresponding to that segment interval is used as the target relation. If the target CO2 injection duration is located within a target smooth transition interval, the target CO2 injection duration is substituted into the target interpolation transition rule corresponding to that smooth transition interval to calculate the relation parameters corresponding to the target CO2 injection duration, and the target relation is constructed based on these parameters. The uniaxial compressive strength prediction calculation unit 708 is used to take the quartz content and CO2 injection duration of the shale to be evaluated as inputs to the target relation, calculate the predicted value of the uniaxial compressive strength of the shale to be evaluated, and output it.

[0088] The beneficial effects obtained by the above-described device are the same as those obtained by the above-described method, and will not be described in detail in the embodiments of this specification.

[0089] like Figure 8 The diagram shown is a structural schematic of a computer device according to an embodiment of this specification. The methods described in this specification can be applied to the computer device of this embodiment.

[0090] Computer device 802 may include one or more processing devices 804, such as one or more central processing units (CPUs), each of which may implement one or more hardware threads.

[0091] The computer device 802 may also include any storage resource 806 for storing any kind of information such as code, settings, data, etc.

[0092] Non-limiting, for example, storage resource 806 may include any one or more of the following: any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc.

[0093] More generally, any storage resource can use any technology to store information.

[0094] Furthermore, any storage resource can provide volatile or non-volatile retention of information.

[0095] Furthermore, any storage resource can represent a fixed or removable component of the computer device 802.

[0096] In one scenario, when processing device 804 executes associated instructions stored in any storage resource or combination of storage resources, computer device 802 can perform any operation of the associated instructions. Computer device 802 also includes one or more drive mechanisms 808 for interacting with any storage resource, such as hard disk drive mechanisms, optical disk drive mechanisms, etc.

[0097] Computer device 802 may also include an input / output module 810 (I / O) for receiving various inputs (via input device 812) and providing various outputs (via output device 814). A specific output mechanism may include a presentation device 816 and an associated graphical user interface (GUI) 818. In other embodiments, the input / output module 810 (I / O), input device 812, and output device 814 may be omitted, and the device may function solely as a computer device within a network. Computer device 802 may also include one or more network interfaces 820 for exchanging data with other devices via one or more communication links 822. One or more communication buses 824 couple the components described above together.

[0098] Communication link 822 can be implemented in any way, such as via a local area network, a wide area network (e.g., the Internet), a point-to-point connection, or any combination thereof. Communication link 822 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

[0099] This specification also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0100] This specification also provides computer-readable instructions, wherein when a processor executes the instructions, the program therein causes the processor to perform the above-described method.

[0101] It should be understood that in the various embodiments of this specification, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this specification.

[0102] It should also be understood that, in the embodiments of this specification, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the embodiments of this specification, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0103] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this specification can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of the embodiments in this specification.

[0104] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0105] In the embodiments provided in this specification, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, devices, or units, or they may be electrical, mechanical, or other forms of connection.

[0106] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments described in this specification, depending on actual needs.

[0107] Furthermore, the functional units in the various embodiments of this specification can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0108] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this specification, in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this specification. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0109] This specification describes the principles and implementation methods of the embodiments using specific examples. The above descriptions of the embodiments are only for the purpose of helping to understand the methods and core ideas of the embodiments in this specification. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the embodiments in this specification. Therefore, the content of this specification should not be construed as a limitation on the embodiments in this specification.

Claims

1. A method for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition, characterized in that, The method includes: We acquired quartz content data and uniaxial compressive strength data of shale samples under different carbon dioxide (CO2) injection duration gradients to construct a sample dataset. The shale samples in the sample dataset are grouped according to the CO2 injection duration gradient of each shale sample in the sample dataset to obtain multiple discrete duration sample groups. Based on the evolution of uniaxial compressive strength under each discrete duration sample group, adjacent discrete duration sample groups with consistent evolution patterns are merged to obtain multiple continuous CO2 injection duration segment intervals. For each CO2 injection duration segment, the relationship between quartz content, CO2 injection duration and uniaxial compressive strength is established based on the quartz content data, CO2 injection duration and uniaxial compressive strength data of all discrete duration sample groups included in the CO2 injection duration segment. A smooth transition interval is set at the boundary of two adjacent CO2 injection duration segments, and an interpolation transition rule is constructed with CO2 injection duration as the input variable. The interpolation transition rule is used to calculate the relational parameters corresponding to any CO2 injection duration within the smooth transition interval. When evaluating the uniaxial compressive strength of the shale to be evaluated, the quartz content of the shale to be evaluated and the target CO2 injection time corresponding to the shale to be evaluated are obtained; Determine whether the target CO2 injection duration belongs to a segmented interval or a smooth transition interval, and obtain the target relational expression. Specifically: if the target CO2 injection duration falls within a segmented interval, the relational expression corresponding to that segmented interval is used as the target relational expression; if it falls within a smooth transition interval, the target CO2 injection duration is substituted into the target interpolation transition rule corresponding to that smooth transition interval to calculate the relational expression parameters corresponding to the target CO2 injection duration, and the target relational expression is constructed based on these parameters. The quartz content and CO2 injection duration of the shale to be evaluated are used as inputs to the target relational expression to calculate and output the predicted uniaxial compressive strength of the shale to be evaluated.

2. The method according to claim 1, characterized in that, A smooth transition interval is set at the boundary between two adjacent CO2 injection duration segments, including: Determine the boundary time point between two adjacent CO2 injection duration segments; Centered on the boundary time point, a preset transition time is extended into the previous CO2 injection duration segment interval and the next CO2 injection duration segment interval, respectively, to form the smooth transition interval covering the boundary time point.

3. The method according to claim 1, characterized in that, Construct interpolation transition rules with CO2 injection duration as the input variable, including: Extract the relational parameters corresponding to each of two adjacent CO2 injection duration segments; The relational parameters of two adjacent CO2 injection duration segments are used as the two endpoint values ​​of the interpolation; Using the CO2 injection duration as the interpolation independent variable, and based on the two endpoint values, a linear weighted interpolation rule is established within the smooth transition interval to determine the relationship between the parameters and the CO2 injection duration, thus obtaining the interpolation transition rule.

4. The method according to claim 1, characterized in that, The shale samples in the sample dataset are grouped according to the CO2 injection duration gradient of each shale sample in the sample dataset to obtain multiple discrete duration sample groups, including: Based on the CO2 injection duration corresponding to each shale sample, the samples were classified into the same group, resulting in multiple discrete duration sample groups corresponding to fixed CO2 injection durations.

5. The method according to claim 1, characterized in that, Based on the evolution of uniaxial compressive strength under each discrete duration sample group, adjacent discrete duration sample groups with consistent evolution patterns are merged to obtain multiple continuous CO2 injection duration segment intervals, including: Based on the inflection point of the relative rate of change of uniaxial compressive strength, the injection duration is divided into at least two consecutive segments: the initial rapid response stage, the mid-term structural adjustment stage, and the late-term deterioration and evolution stage.

6. The method according to claim 1, characterized in that, Based on the data of quartz content, CO2 injection duration, and uniaxial compressive strength of all discrete time sample groups included in the CO2 injection duration segment interval, a relationship between quartz content, CO2 injection duration, and uniaxial compressive strength is established within this CO2 injection duration segment interval, including: Within each CO2 injection duration segment, with quartz content and CO2 injection duration as independent variables and uniaxial compressive strength as the dependent variable, a mapping relationship between the independent and dependent variables is established through data fitting, thus obtaining the relationship formula for that CO2 injection duration segment.

7. A device for evaluating the compressive strength of shale based on CO2 injection duration and mineral composition, characterized in that, The device includes: The sample dataset construction unit is used to acquire quartz content data and uniaxial compressive strength data of shale samples under different carbon dioxide (CO2) injection duration gradients to construct the sample dataset. The discrete duration sample group division unit is used to group the shale samples in the sample dataset according to the CO2 injection duration gradient of each shale sample in the sample dataset to obtain multiple discrete duration sample groups. The CO2 injection duration segmentation unit is used to merge adjacent discrete duration sample groups with consistent evolution patterns based on the evolution pattern of uniaxial compressive strength under each discrete duration sample group, thereby obtaining multiple continuous CO2 injection duration segmentation intervals. The relational fitting unit is used to establish the relational formula between quartz content, CO2 injection time and uniaxial compressive strength for each CO2 injection time segment interval, based on the quartz content data, CO2 injection time and uniaxial compressive strength data of all discrete time sample groups included in the CO2 injection time segment interval. An interpolation transition rule construction unit is used to set a smooth transition interval at the boundary of two adjacent CO2 injection duration segment intervals and construct an interpolation transition rule with CO2 injection duration as the input variable. The interpolation transition rule is used to calculate the relational parameters corresponding to any CO2 injection duration within the smooth transition interval. The data acquisition unit for shale to be evaluated is used to acquire the quartz content of the shale to be evaluated and the target CO2 injection duration corresponding to the shale to be evaluated when evaluating the uniaxial compressive strength of the shale to be evaluated. The target relation determination unit is used to determine whether the target CO2 injection duration belongs to a target CO2 injection duration segment interval or a target smooth transition interval, and to obtain a target relation. Specifically: if the target CO2 injection duration is located within a target CO2 injection duration segment interval, the relation corresponding to that segment interval is used as the target relation; if the target CO2 injection duration is located within a target smooth transition interval, the target CO2 injection duration is substituted into the target interpolation transition rule corresponding to that smooth transition interval to calculate the relation parameters corresponding to the target CO2 injection duration, and the target relation is constructed based on these parameters. The uniaxial compressive strength prediction calculation unit is used to take the quartz content and CO2 injection duration of the shale to be evaluated as inputs to the target relation, calculate the predicted uniaxial compressive strength of the shale to be evaluated, and output it.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1 to 6.

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

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

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