A method for supercritical carbon dioxide mineralization and storage in deep shale

Abstract

This invention relates to the field of carbon dioxide geological storage technology, and more particularly to a method for supercritical carbon dioxide mineralization and storage in deep shale. It includes: determining an initial injection parameter spectrum based on the geological characteristics of the target shale layer and the storage target, and evaluating the theoretical maximum mineralization and storage capacity; achieving primary regulation of the initial injection parameters through a phase proximity coefficient; performing advanced regulation of the initial injection parameters based on a comprehensive storage benefit index and predicting the relative benefit gain coefficient; evaluating the qualification of advanced regulation commands based on the deviation between actual and predicted benefit gains; and dynamically optimizing the advanced regulation commands based on the benefit change coefficient when commands are unqualified. This invention achieves intelligent control throughout the entire process, from parameter design and real-time regulation to system self-learning, effectively ensuring the safety and efficiency of the storage process.

Description

Technical Field

[0001] This invention relates to the field of carbon dioxide geological storage technology, and in particular to a method for supercritical carbon dioxide mineralization and storage in deep shale. Background Technology

[0002] With the advancement of carbon neutrality goals, carbon dioxide geological storage technology has become one of the key means to address climate change. Deep shale reservoirs, due to their widespread distribution and dual potential for adsorption and mineralization storage, are considered ideal storage sites. However, existing carbon dioxide storage methods still have significant shortcomings when applied to deep shale. First, traditional saline aquifer or oil and gas reservoir storage mainly relies on physical traps, which pose a long-term leakage risk and make it difficult to guarantee storage stability. Second, the low porosity and low permeability of shale reservoirs make it difficult for carbon dioxide to migrate and distribute effectively, and the natural rate of mineral carbonation reaction is extremely slow, resulting in a storage period of up to decades. Third, existing injection processes lack precise control over the supercritical carbon dioxide phase, which can easily lead to phase transitions and reduced storage efficiency. In addition, the lack of real-time monitoring and safety early warning mechanisms for the strain field in the near-wellbore zone during engineering implementation may induce formation instability or caprock damage. Finally, existing technologies mostly adopt static injection schemes, which cannot be adaptively adjusted according to the dynamic response of the reservoir, resulting in a serious lack of intelligence and optimization in the storage process. Therefore, there is an urgent need to develop a method for the efficient, safe, and intelligent control of carbon dioxide mineralization and storage in deep shale.

[0003] Chinese Patent Publication No. CN119321342A discloses a supercritical carbon dioxide mineralization and sequestration method based on paste filling technology, comprising the following steps: S1, preparation of paste filling material; S2, preparation of supercritical carbon dioxide; S3, mineralization and sequestration: to achieve large-scale mineralization and sequestration of CO2 in mines, the mineralization and sequestration steps include a mineralized filling slurry preparation process and a carbon injection mineralization process; the invention provides a supercritical carbon dioxide mineralization and sequestration method based on paste filling technology, which combines paste filling technology with supercritical carbon dioxide mineralization and sequestration, so that mine solid waste containing large amounts of calcium and magnesium resources is fully mineralized with supercritical carbon dioxide and prepared into a mineralized filling slurry, which is then filled into the underground goaf. This not only helps to improve the mechanical properties of the filling body and improve its pore structure, but also conforms to the concept of "using waste to treat waste" in mines, realizing green mining of metal mines.

[0004] Therefore, the supercritical carbon dioxide mineralization and storage method based on paste filling technology has the following drawbacks: the mineralization and storage steps of carbon dioxide are too complicated; the phase parameters of the prepared supercritical carbon dioxide cannot be strictly controlled during transportation; the geological characteristics of the underground goaf are not obtained; leakage is prone to occur during the carbon dioxide storage process, resulting in low safety of the carbon dioxide storage process; and the carbon dioxide mineralization and storage efficiency is low, making it impossible to achieve dynamic control of carbon dioxide mineralization and storage. Summary of the Invention

[0005] To address these issues, the present invention provides a method for supercritical carbon dioxide mineralization and storage in deep shale, which overcomes the problems of overly complex mineralization and storage steps, inability to strictly control the phase parameters of supercritical carbon dioxide, lack of acquisition of geological characteristics of underground goaf areas, and easy leakage during the injection of supercritical carbon dioxide into paste filling materials in the prior art.

[0006] To achieve the above objectives, this invention provides a method for supercritical carbon dioxide mineralization and storage in deep shale. It includes:

[0007] The geological characteristics of the target shale layer and the determination of the initial injection parameter spectrum based on the storage target were used to assess the theoretical maximum mineralization storage capacity of the reservoir.

[0008] Real-time monitoring of key parameters of the supercritical carbon dioxide phase state downhole is used to obtain the phase state proximity coefficient, in order to determine the pressure boosting priority, energy-saving pressure reduction, and dynamic fine-tuning steady state of the initial injection parameter spectrum.

[0009] Real-time monitoring of the strain field near the wellbore yields the maximum compressive principal strain value, and the comprehensive benefit index of the storage is obtained to determine whether the advanced control command for the initial injection parameter spectrum is a protective pulse injection command or an enhanced pulse injection command, and to predict the relative benefit gain coefficient.

[0010] After the advanced control command has been executed for one complete pulse cycle, the validity of the advanced control command for the initial injection parameter spectrum is determined based on the benefit gain deviation value, and the number of times it fails is recorded.

[0011] If the advanced control command for the initial injection parameter spectrum is determined to be unqualified, the cumulative injection time of supercritical carbon dioxide is monitored in real time, and the progressive optimization or reconfiguration optimization of the advanced control command is determined based on the benefit change coefficient.

[0012] Furthermore, the process of primary regulation of the initial injection parameter spectrum includes,

[0013] Obtain downhole pressure and temperature of supercritical carbon dioxide;

[0014] The phase proximity coefficient is obtained by weighted summation;

[0015] The phase state proximity coefficient is compared with a preset first phase state proximity coefficient;

[0016] Based on the phase proximity coefficient being less than or equal to a preset first phase proximity coefficient, a pressurization priority control strategy is determined for the initial injection parameter spectrum.

[0017] Furthermore, the process of primary regulation of the initial injection parameter spectrum also includes,

[0018] The phase state proximity coefficient is compared with a preset second phase state proximity coefficient;

[0019] Based on the fact that the phase state proximity coefficient is greater than the preset first phase state proximity coefficient and less than or equal to the preset second phase state proximity coefficient, a dynamic fine-tuning steady-state strategy is determined for the initial injection parameter spectrum.

[0020] Based on the fact that the phase state proximity coefficient is greater than the preset second phase state proximity coefficient, an energy-saving and pressure-reducing control strategy is determined for the initial injection parameter spectrum.

[0021] Wherein, the preset first phase state proximity coefficient is less than the preset second phase state proximity coefficient.

[0022] Furthermore, the process of advanced manipulation of the initial injection parameter spectrum and prediction of relative benefit gain coefficients includes,

[0023] The maximum compressive principal strain value was obtained by acquiring the strain field in the near-wellbore zone.

[0024] The dynamic equivalent storage capacity is obtained by calculating the sum of adsorption storage capacity, mineralization storage capacity, and tectonic storage capacity.

[0025] The comprehensive benefit index of the storage is obtained by multiplying the standardization achievement rate and the safety factor.

[0026] The comprehensive benefit index of the sealed storage is compared with the first preset comprehensive benefit index of the sealed storage;

[0027] The protective pulse injection command is executed based on the fact that the comprehensive benefit index of the sealing is less than or equal to the first preset comprehensive benefit index of the sealing.

[0028] Furthermore, the process of advanced manipulation of the initial injection parameter spectrum and prediction of relative benefit gain coefficients also includes,

[0029] The comprehensive benefit index of the sealed storage is compared with the second preset comprehensive benefit index of the sealed storage;

[0030] Based on the fact that the comprehensive benefit index of the sealed storage is greater than the first preset comprehensive benefit index of the sealed storage and less than or equal to the second preset comprehensive benefit index of the sealed storage, a robust pulse injection command is determined to be executed.

[0031] Furthermore, the process of advanced manipulation of the initial injection parameter spectrum and prediction of relative benefit gain coefficients also includes,

[0032] The enhanced pulse injection command is executed based on the fact that the comprehensive benefit index of the sealed storage is greater than the second preset comprehensive benefit index of the sealed storage.

[0033] Among them, the first preset comprehensive benefit index of sealing is less than the second preset comprehensive benefit index of sealing.

[0034] Furthermore, the process of determining whether the advanced control instructions for the initial injection parameter spectrum are qualified based on the benefit gain deviation value includes,

[0035] Obtain the pre-regulation benefit index and the post-regulation benefit index;

[0036] The difference between the post-regulation benefit index and the pre-regulation benefit index is calculated to obtain the benefit index difference.

[0037] The actual relative benefit gain coefficient is obtained by calculating the ratio of the benefit index difference to the benefit index before regulation.

[0038] The difference between the actual relative benefit gain coefficient and the predicted relative benefit gain coefficient is used to obtain the benefit gain deviation value.

[0039] Based on the fact that the benefit gain deviation value is greater than the preset deviation value, the advanced control command is determined to be unqualified.

[0040] Furthermore, the process of determining whether to implement an incremental optimization strategy or a reconfiguration optimization strategy to dynamically optimize high-level control instructions based on the benefit change coefficient includes the following:

[0041] Set a statistical window that includes a period of several consecutive advanced control commands;

[0042] The comprehensive benefit index of the sealed-up area at the start time of the statistical window is recorded as the initial benefit index.

[0043] The current comprehensive benefit index of the storage is recorded as the current benefit index;

[0044] Calculate the difference between the current benefit index and the initial benefit index;

[0045] The ratio of the difference to the initial benefit index is used to obtain the benefit change coefficient;

[0046] The benefit change coefficient is compared with the first preset benefit change coefficient;

[0047] Based on the fact that the benefit change coefficient is less than or equal to the first preset benefit change coefficient, a gradual optimization strategy is adopted.

[0048] Furthermore, the process of determining whether to implement an incremental optimization strategy or a reconfiguration optimization strategy to dynamically optimize high-level control instructions based on the benefit change coefficient also includes,

[0049] The benefit change coefficient is compared with the second preset benefit change coefficient;

[0050] Based on the fact that the benefit change coefficient is greater than the first preset benefit change coefficient and less than or equal to the second preset benefit change coefficient, an adjustment optimization strategy is adopted.

[0051] Furthermore, the process of determining whether to implement an incremental optimization strategy or a reconfiguration optimization strategy to dynamically optimize high-level control instructions based on the benefit change coefficient also includes,

[0052] Based on the fact that the benefit change coefficient is greater than the second preset benefit change coefficient, a reconstructive optimization strategy is adopted.

[0053] Wherein, the first preset benefit change coefficient is less than the second preset benefit change coefficient.

[0054] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention determines the initial injection parameter spectrum by the geological characteristics of the target shale layer and the storage target, evaluates the theoretical maximum mineralization storage capacity of the reservoir, monitors the initial injection parameters in real time and performs primary and advanced dynamic regulation, determines whether the advanced regulation command is qualified based on the benefit gain deviation value, and optimizes the advanced regulation command based on the benefit change coefficient calculated based on continuous historical regulation data when it is unqualified. This realizes intelligent management of the entire process of supercritical carbon dioxide mineralization storage in deep shale, significantly improves storage efficiency, safety and system adaptability, effectively reduces energy consumption and operational risks, and ensures the long-term stability and reliability of storage operations.

[0055] Furthermore, this invention monitors key phase parameters of supercritical carbon dioxide in real time and calculates the phase proximity coefficient. Based on the phase proximity coefficient and preset first and second phase proximity coefficients, a primary control strategy is implemented for the initial inlet and outlet parameter spectrum. When the phase proximity coefficient is less than or equal to the preset first phase proximity coefficient, a pressure-priority control strategy is implemented, and if the bottom hole temperature is still below the safety threshold during the pressure increase process, the bottom hole heating system is activated. When the phase proximity coefficient is greater than the preset first phase proximity coefficient and less than or equal to the preset second phase proximity coefficient, the current injection pressure benchmark value is maintained unchanged, allowing the pulse injection parameters to fluctuate normally within ±5% of the initial set value. When the phase proximity coefficient is greater than the preset second phase proximity coefficient, the injection pressure is reduced to 0.8-0.9 times the injection pressure benchmark value, while monitoring the change of the phase proximity coefficient to ensure that it is not lower than the second preset phase proximity coefficient. This ensures the stability of the supercritical carbon dioxide phase, prevents the decrease in storage efficiency or equipment damage caused by phase deviation, and improves the control accuracy and response speed of the injection process.

[0056] Furthermore, this invention monitors the strain field near the wellbore in real time and calculates the dynamic equivalent storage capacity and the comprehensive storage benefit index. Based on the comparison between the comprehensive storage benefit index and the first and second preset comprehensive storage benefit indices, it determines advanced control commands for the initial injection parameter spectrum. When the comprehensive storage benefit index is less than or equal to the first preset comprehensive storage benefit index, a protective pulse injection command is executed; when the comprehensive storage benefit index is greater than the first preset comprehensive storage benefit index but less than or equal to the second preset comprehensive storage benefit index, a robust pulse injection command is executed; and when the comprehensive storage benefit index is greater than the second preset comprehensive storage benefit index, an enhancing pulse injection command is executed. This achieves a dynamic balance between storage efficiency and formation safety, optimizes pulse injection parameters, and maximizes storage benefits while ensuring reservoir integrity.

[0057] Furthermore, this invention evaluates the eligibility of advanced control commands and calculates the benefit variation coefficient based on historical data of the comprehensive benefit index of the storage facility. It then determines a dynamic optimization strategy for the advanced control commands based on a comparison of the benefit variation coefficient with a first preset benefit variation coefficient and a second preset benefit variation coefficient. A progressive optimization strategy is implemented when the benefit variation coefficient is less than or equal to the first preset benefit variation coefficient; an adjustment optimization strategy is implemented when the benefit variation coefficient is greater than the first preset benefit variation coefficient but less than or equal to the second preset benefit variation coefficient; and a reconstruction optimization strategy is implemented when the benefit variation coefficient is greater than the second preset benefit variation coefficient. This tiered optimization approach enables timely identification and correction of control deviations, adapts to changes in formation conditions, enhances the system's adaptability and robustness, and ensures the continuous efficiency and controllable risks of the storage operation. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating the steps of the deep shale supercritical carbon dioxide mineralization and storage method according to an embodiment of the present invention.

[0059] Figure 2 This is a logic block diagram of an embodiment of the present invention for determining a primary control strategy for the initial injection parameter spectrum based on the phase proximity coefficient;

[0060] Figure 3 This is a logic block diagram of an embodiment of the present invention for determining advanced control instructions for the initial injection parameter spectrum based on the comprehensive benefit index of the storage.

[0061] Figure 4 This is a logic block diagram illustrating how an embodiment of the present invention determines whether an advanced control command for the injection parameters is qualified based on the benefit gain deviation between the actual relative benefit gain coefficient and the predicted relative benefit gain coefficient.

[0062] Figure 5 This is a logic block diagram illustrating how an embodiment of the present invention determines a dynamic optimization strategy for advanced control commands based on the benefit change coefficient. Detailed Implementation

[0063] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0064] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0065] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0066] Please see Figure 1 The diagram shown illustrates the steps of a deep shale supercritical carbon dioxide mineralization and storage method according to an embodiment of the present invention.

[0067] The present invention provides a method for supercritical carbon dioxide mineralization and storage in deep shale, comprising:

[0068] Step S1: Based on the geological characteristics and storage target of the target shale layer, determine the initial injection parameter spectrum and evaluate the maximum theoretical mineralization storage capacity of the reservoir;

[0069] Step S2: Real-time monitoring of key phase parameters of supercritical carbon dioxide downhole and calculation of phase proximity coefficient; determination of primary control strategy for initial injection parameter spectrum based on comparison of the phase proximity coefficient with preset first phase proximity coefficient and preset second phase proximity coefficient.

[0070] Step S3: Real-time monitoring of the strain field in the near-wellbore zone to obtain the maximum compressive principal strain value and calculate the dynamic equivalent storage capacity of the reservoir under the current injection conditions. Based on the comparison results of the comprehensive storage benefit index with the first preset comprehensive storage benefit index and the second preset comprehensive storage benefit index, determine the advanced control command for the initial injection parameter spectrum and predict the relative benefit gain coefficient.

[0071] Step S4: After the advanced control command has been executed for a complete pulse cycle, calculate the actual relative benefit gain coefficient, determine whether the advanced control command for the injection parameters is qualified based on the comparison result between the actual relative benefit gain coefficient after control and the predicted relative benefit gain coefficient, and record the number of times it is unqualified.

[0072] Step S5: Under the condition that the advanced control command for the injection parameters is unqualified, the cumulative injection time of supercritical carbon dioxide is monitored in real time, the benefit change coefficient is calculated based on the historical data of the comprehensive benefit index of storage, and the dynamic optimization strategy for the advanced control command is determined according to the comparison result of the benefit change coefficient with the first preset benefit change coefficient and the second preset benefit change coefficient.

[0073] Specifically, this invention determines the initial injection parameter spectrum based on the geological characteristics of the target shale layer and the storage target, evaluates the theoretical maximum mineralization storage capacity of the reservoir, monitors the initial injection parameters in real time and performs primary and advanced dynamic regulation, determines whether the advanced regulation command is qualified based on the benefit gain deviation value, and optimizes the advanced regulation command based on the benefit change coefficient calculated from historical data of multiple consecutive regulation when it is unqualified. This realizes intelligent management of the entire process of supercritical carbon dioxide mineralization storage in deep shale, significantly improves storage efficiency, safety and system adaptability, effectively reduces energy consumption and operational risks, and ensures the long-term stability and reliability of storage operations.

[0074] In this embodiment of the invention, in step S1, the geological characteristics of the target shale layer and the sealing target are obtained, and the initial injection parameter spectrum is determined based on the multi-feature fusion method.

[0075] Specifically, the geological features include mineralogical features, physical structure features, and mechanical and geostress features, and the sequestration targets are the scale target of the total mass of carbon dioxide to be sequestered and the efficiency target of the mass of carbon dioxide fixed per unit time through mineralization reactions.

[0076] Specifically, the initial injection parameter spectrum includes, but is not limited to, the carbon dioxide injection pressure reference value, the injection temperature, and the pulse injection parameters, wherein the pulse injection parameters include the pulse pressure amplitude and the pulse period.

[0077] In this embodiment of the invention, after obtaining the geological characteristics of the target shale and the storage target, the initial injection parameter spectrum is obtained through a pre-constructed injection parameter decision model. In practical application, firstly, a training dataset for the model is constructed; each sample in the dataset contains an input feature vector and a corresponding target output label; the input feature vector consists of the geological characteristic quantification index of the target shale layer and the storage target quantification index, including: clay mineral mass fraction and carbonate mineral mass fraction characterizing mineralogical characteristics; porosity and permeability characterizing physical structural characteristics; Young's modulus and minimum horizontal principal stress characterizing mechanical and geostress characteristics; and scale target and efficiency target characterizing the storage target; the target output label is the injection parameter combination that has been verified as optimal under the input feature conditions through engineering or numerical simulation, specifically including but not limited to: carbon dioxide injection pressure baseline value, injection temperature, pulse pressure amplitude, and pulse period.

[0078] Secondly, based on the training dataset, the injection parameter decision model is trained using a multivariate regression algorithm. The input feature vector is used as the independent variable, and the target output label is used as the dependent variable. A nonlinear mapping relationship from multidimensional geological and target features to the optimal initial injection parameters is established through least squares fitting. The training objective of the model is to minimize the root mean square error between the predicted injection parameter combination and the label values ​​in the training samples.

[0079] Finally, in the model application stage, the specific geological feature quantification indicators of the target shale layer to be sealed and the sealing target quantification indicators are organized into an input feature vector according to the same format and dimensions as in the training stage, and input into the already trained injection parameter decision model; the model performs a forward calculation and directly outputs a set of specific numerical parameters, which constitute the initial injection parameter spectrum, including but not limited to the injection pressure benchmark value, injection temperature, pulse pressure amplitude and pulse period of carbon dioxide injection.

[0080] Specifically, after determining the initial injection parameter spectrum, the theoretical maximum mineralization and sequestration capacity of the reservoir is evaluated. In the actual evaluation process, the effective volume and shale density of the reservoir are first obtained. Then, the mass fractions of clay minerals and carbonate minerals in the shale are determined through mineral composition analysis. Based on indoor thermogravimetric analysis experimental data, the theoretical carbon dioxide sequestration capacity per unit mass of clay minerals and per unit mass of carbonate minerals is obtained. The effective volume is multiplied by the shale density to obtain the total mass of the reservoir. Then, it is multiplied by the product of the clay mineral mass fraction and the theoretical carbon dioxide sequestration capacity per unit mass of clay minerals, and the product of the carbonate mineral mass fraction and the theoretical carbon dioxide sequestration capacity per unit mass of carbonate minerals, respectively. Finally, the two product results are added together to obtain the theoretical maximum mineralization and sequestration capacity.

[0081] Please see Figure 2 As shown, it is a logic block diagram of the primary control strategy for determining the initial injection parameter spectrum based on the phase proximity coefficient in an embodiment of the present invention.

[0082] Specifically, under the condition of executing the initial injection parameter spectrum, the key parameters of the supercritical carbon dioxide phase state downhole are monitored in real time, the phase state proximity coefficient is calculated, and a primary control strategy for the initial injection parameter spectrum is determined based on the comparison results of the phase state proximity coefficient with preset first phase state proximity coefficients and preset second phase state proximity coefficients.

[0083] If the phase proximity coefficient is less than or equal to the preset first phase proximity coefficient, then it is determined that the first control strategy will be executed on the initial injection parameter spectrum.

[0084] If the phase proximity coefficient is greater than the preset first phase proximity coefficient and less than or equal to the preset second phase proximity coefficient, then it is determined that the second control strategy will be executed on the initial injection parameter spectrum.

[0085] If the phase proximity coefficient is greater than the preset second phase proximity coefficient, then the third control strategy is determined to be executed on the initial injection parameter spectrum.

[0086] In this embodiment of the invention, the key phase parameters include downhole pressure and downhole temperature.

[0087] In this embodiment of the invention, the phase proximity coefficient is obtained by first acquiring the bottom hole pressure and bottom hole temperature under real-time monitoring, then calculating the pressure ratio of the pressure difference between the bottom hole pressure and the critical carbon dioxide pressure relative to the critical carbon dioxide pressure, and the temperature ratio of the temperature difference between the bottom hole temperature and the critical carbon dioxide temperature relative to the critical carbon dioxide temperature, calculating the product of the pressure ratio and the pressure weighting coefficient to obtain the pressure factor, calculating the product of the temperature ratio and the temperature weighting coefficient to obtain the temperature factor, and finally calculating the sum of the pressure factor and the temperature factor to obtain the phase proximity coefficient.

[0088] In this embodiment of the invention, the pressure weighting coefficient ranges from 0.5 to 0.7, and is preferably 0.6. The product of the temperature weighting coefficients ranges from 0.3 to 0.5, and is preferably 0.4. The sum of the pressure weighting coefficient and the temperature weighting coefficient is 1. The preferred range and preferred value of the temperature weighting coefficient and the pressure weighting coefficient can be determined according to the actual situation, and are not specifically limited here.

[0089] In this embodiment of the invention, the value range of the first preset phase state proximity coefficient is 0.1 to 0.2, and the preferred value is 0.15. The value range of the preset second phase state proximity coefficient is 0.2 to 0.3, and the preferred value is 0.25. The preferred value range and preferred value of the preset first phase state proximity coefficient and the second phase state proximity coefficient can be determined according to the actual situation, and are not specifically limited here.

[0090] In this embodiment of the invention, the first control strategy is a pressure-priority control strategy, which uses the difference between the current bottom hole pressure and the target lower limit of safety pressure as the adjustment amount, and increases the output pressure of the surface injection pump at a rate of 0.5 MPa / min to 1.0 MPa / min. If the bottom hole temperature is still lower than the safety threshold during the pressure increase process, the bottom hole heating system is activated to maintain the bottom hole temperature in the range of 5°C to 10°C above the critical temperature of carbon dioxide. The target lower limit of safety pressure is a pressure value that is 0.5 MPa to 1.0 MPa higher than the critical pressure of carbon dioxide.

[0091] In this embodiment of the invention, the second control strategy is a dynamic fine-tuning steady-state strategy, which maintains the current injection pressure reference value unchanged, allows the pulse injection parameters to fluctuate normally within ±5% of the initial set value, and performs closed-loop fine-tuning through the feedback of the phase proximity coefficient to ensure that it is stable within the optimal range between the first preset phase proximity coefficient and the second preset phase proximity coefficient. The injection pressure reference value is the carbon dioxide injection pressure reference value in the initial injection parameter spectrum.

[0092] In this embodiment of the invention, the third control strategy is an energy-saving and pressure-reducing control strategy, which aims to reduce energy consumption by reducing the injection pressure to 0.8 to 0.9 times the injection pressure benchmark value, while monitoring the change of the phase state proximity coefficient to ensure that it is not lower than the second preset phase state proximity coefficient.

[0093] Specifically, this invention monitors key phase parameters of supercritical carbon dioxide in real time and calculates the phase proximity coefficient. Based on the phase proximity coefficient and preset first and second phase proximity coefficients, a primary control strategy is implemented for the initial inlet and outlet parameter spectrum. When the phase proximity coefficient is less than or equal to the preset first phase proximity coefficient, a pressure-priority control strategy is implemented, and if the bottom hole temperature remains below the safety threshold during pressure increase, the bottom hole heating system is activated. When the phase proximity coefficient is greater than the preset first phase proximity coefficient and less than or equal to the preset second phase proximity coefficient, the current injection pressure benchmark value is maintained unchanged, allowing the pulse injection parameters to fluctuate normally within ±5% of the initial set value. When the phase proximity coefficient is greater than the preset second phase proximity coefficient, the injection pressure is reduced to 0.8 to 0.9 times the injection pressure benchmark value, while monitoring changes in the phase proximity coefficient to ensure it is not lower than the second preset phase proximity coefficient. This ensures the stability of the supercritical carbon dioxide phase, prevents a decrease in storage efficiency or equipment damage due to phase deviation, and improves the control accuracy and response speed of the injection process.

[0094] Please see Figure 3 As shown, it is a logic block diagram of an embodiment of the present invention for determining advanced control instructions for the initial injection parameter spectrum based on the comprehensive benefit index of the storage.

[0095] Specifically, under the condition of implementing the primary control strategy, the maximum compressive principal strain value is obtained by real-time monitoring of the strain field in the near-wellbore zone, and the dynamic equivalent storage capacity of the reservoir under the current injection conditions is calculated. Based on the comparison result between the storage comprehensive benefit index and the first and second preset storage comprehensive benefit indices, advanced control instructions for the initial injection parameter spectrum are determined, wherein...

[0096] If the comprehensive benefit index of the sealing is less than or equal to the first preset comprehensive benefit index of the sealing, then the protective pulse injection command is executed.

[0097] If the comprehensive benefit index of the storage is greater than the first preset comprehensive benefit index of the storage and less than or equal to the second preset comprehensive benefit index of the storage, then the robust pulse injection command is executed.

[0098] If the overall storage benefit index is greater than the second preset overall storage benefit index, then the enhanced pulse injection command is executed.

[0099] In this embodiment of the invention, the dynamic equivalent storage capacity is first calculated by real-time monitoring of bottom hole pressure and temperature, and based on a pre-determined shale adsorption isotherm model for carbon dioxide. Then, the amount of carbon dioxide fixed by the mineralization reaction is calculated based on the total amount of injected carbon dioxide, reaction time, and mineralization reaction rate constant determined by core experiments, to obtain the amount of mineralization storage. Next, the mass of supercritical carbon dioxide stored in the effective fracture volume obtained by inversion from microseismic monitoring data is calculated to obtain the tectonic storage capacity. Finally, the sum of the adsorption storage capacity, the mineralization storage capacity, and the tectonic storage capacity is calculated to obtain the dynamic equivalent storage capacity.

[0100] In this embodiment of the invention, the comprehensive storage benefit index is obtained by first calculating the ratio of the dynamic equivalent storage capacity to the theoretical maximum mineralization storage capacity to obtain the dynamic equivalent storage capacity achievement rate, then calculating the ratio of the dynamic equivalent storage capacity achievement rate to the target achievement rate to obtain the standardized achievement rate, then obtaining the maximum compressive principal strain value of the near-wellbore zone obtained through real-time monitoring, then calculating the ratio of the maximum compressive principal strain value to the safety threshold to obtain the relative strain ratio value, squaring the relative strain ratio value to obtain the relative strain square value, then calculating the difference between the numerical value 1 and the relative strain square value to obtain the safety factor, and finally calculating the product of the standardized achievement rate and the safety factor to obtain the comprehensive storage benefit index.

[0101] Specifically, the target achievement rate is set to 0.8, and the safety threshold is set to 1000 microstrain.

[0102] In this embodiment of the invention, the value range of the first preset comprehensive benefit index for sealing is 0.3 to 0.4, and the preferred value is 0.35. The value range of the second preset comprehensive benefit index for sealing is 0.6 to 0.7, and the preferred value is 0.65. The preferred value range and the preferred value can be determined according to the actual situation, and are not specifically limited here.

[0103] In this embodiment of the invention, the protective pulse injection command is to reduce the current injection pressure reference value to 0.7 to 0.8 times it, maintain the current pulse pressure amplitude unchanged, extend the pulse period to 1.5 to 2.0 times the pulse period in the initial injection parameter spectrum, and suspend any operation that increases the injection intensity.

[0104] In this embodiment of the invention, the robust pulse injection command is to maintain the current injection pressure reference value, setting the pulse pressure amplitude to 10% to 15% of the pulse pressure amplitude in the initial injection parameter spectrum, and setting the pulse period to 4 to 6 hours.

[0105] In this embodiment of the invention, the enhanced pulse injection command is to increase the current injection pressure reference value to 1.1 to 1.2 times, increase the pulse pressure amplitude to 20% to 25% of the pulse pressure amplitude in the initial injection parameter spectrum, and shorten the pulse period to 2 to 3 hours.

[0106] Specifically, this invention monitors the strain field near the wellbore in real time and calculates the dynamic equivalent storage capacity and the comprehensive storage benefit index. Based on the comparison between the comprehensive storage benefit index and the first and second preset comprehensive storage benefit indices, it determines advanced control commands for the initial injection parameter spectrum. When the comprehensive storage benefit index is less than or equal to the first preset comprehensive storage benefit index, a protective pulse injection command is executed; when the comprehensive storage benefit index is greater than the first preset comprehensive storage benefit index but less than or equal to the second preset comprehensive storage benefit index, a robust pulse injection command is executed; and when the comprehensive storage benefit index is greater than the second preset comprehensive storage benefit index, an enhancing pulse injection command is executed. This achieves a dynamic balance between storage efficiency and formation safety, optimizes pulse injection parameters, and maximizes storage benefits while ensuring reservoir integrity.

[0107] Please see Figure 4 As shown, it is a logic block diagram of an embodiment of the present invention for determining whether the advanced control command for the injection parameter is qualified based on the benefit gain deviation value between the actual relative benefit gain coefficient and the predicted relative benefit gain coefficient.

[0108] Specifically, after a complete pulse cycle of advanced control is executed, the actual relative benefit gain coefficient is calculated. Based on the comparison between the actual relative benefit gain coefficient after control and the predicted relative benefit gain coefficient, and a preset deviation value, the adequacy of the advanced control command for the injected parameters is determined.

[0109] If the benefit gain deviation value is less than or equal to the preset deviation value, then the advanced control instruction is determined to be qualified, and subsequent sealing operations are performed based on the current advanced control instruction.

[0110] If the benefit gain deviation value is greater than the preset deviation value, then the next high-level control instruction is determined to be unqualified.

[0111] In this embodiment of the invention, the actual relative benefit gain coefficient is obtained by first acquiring the comprehensive storage benefit index at the moment before the execution of the advanced control command, which is recorded as the pre-control benefit index; then acquiring the comprehensive storage benefit index after the execution of the advanced control command for one complete pulse cycle, which is recorded as the post-control benefit index; calculating the difference between the post-control benefit index and the pre-control benefit index to obtain the benefit index difference; and finally calculating the ratio of the benefit index difference to the pre-control benefit index to obtain the actual relative benefit gain coefficient.

[0112] Specifically, the pre-control benefit index is the comprehensive sealing benefit index determined in step S3, and the post-control benefit index is obtained by real-time monitoring and calculation using the same method after executing a complete pulse cycle through the advanced control command.

[0113] In this embodiment of the invention, the predicted relative benefit gain coefficient is predicted by constructing a regulation effect prediction model. The specific process of constructing the prediction model is as follows: First, a training dataset for the model is constructed. Each sample in the dataset corresponds to a historical advanced regulation event. The data comes from numerical simulation results of pilot tests in this well and operation data from neighboring wells with similar geological conditions, and includes an input feature vector and a corresponding true output label. The input feature vector includes the comprehensive benefit index of the sealing system at the moment before regulation, and the type of advanced regulation command used. It is worth noting that the type of advanced regulation command needs to be numerically encoded. For example, the protective pulse injection command is encoded as 1, the robust pulse injection command is encoded as 2, the enhancing pulse injection command is encoded as 3, and the adjustment ratio of the corresponding parameter in the initial injection parameter spectrum used when executing the advanced regulation command is specifically the adjustment ratio of the injection pressure benchmark value and the pulse period adjustment ratio. The true output label is the relative benefit gain coefficient actually calculated after the regulation has been executed for one complete pulse cycle.

[0114] Secondly, based on the training dataset, the regulation effect prediction model is trained using a multiple linear regression algorithm; the input feature vector is used as the independent variable, and the real output label is used as the dependent variable. By fitting with the least squares method, a linear mapping relationship from "current state - regulation action" to "expected effect gain" is established.

[0115] Finally, in the model application stage, the currently calculated comprehensive benefit index of storage, the type of advanced control command to be executed, and the corresponding baseline pressure and pulse cycle adjustment ratio are organized into an input feature vector in the same format as in the training stage, and input into the trained control effect prediction model; the model performs a forward calculation and directly outputs a specific value, namely the predicted relative benefit gain coefficient.

[0116] In this embodiment of the invention, the benefit gain deviation value is obtained by calculating the difference between the actual relative benefit gain coefficient and the predicted relative benefit gain coefficient.

[0117] In this embodiment of the invention, the preset deviation value ranges from 0.07 to 0.09, and the value in this invention is 0.08. The preferred range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0118] In this embodiment of the invention, the advanced control executes a complete pulse cycle by controlling the downhole injection pressure according to the injection pressure reference value and pulse injection parameters set by the currently effective advanced control command, thereby completing a complete and periodic pressure modulation process.

[0119] Specifically, within one pulse cycle, the downhole injection pressure changes in the following pattern: centered on the currently effective injection pressure reference value, with the pulse pressure amplitude as the fluctuation range, periodically increasing and decreasing pressure; a typical complete cycle includes: the pressure rising from the reference value to the peak value of the sum of the reference value and the amplitude and maintaining it for about 1 / 4 of the pulse cycle duration, then decreasing to the trough value of the difference between the reference value and the amplitude and maintaining it for about 1 / 4 of the pulse cycle duration, and finally returning to the reference value in about half a pulse cycle, thus constituting a complete pressure fluctuation cycle; the duration of the pulse cycle is the total time required to complete one pressure fluctuation cycle.

[0120] Please see Figure 5 As shown, it is a logic block diagram of the dynamic optimization strategy for determining advanced control instructions based on the benefit change coefficient in an embodiment of the present invention.

[0121] Specifically, when it is determined that the advanced control command for the injection parameters is unqualified, the cumulative injection time of supercritical carbon dioxide is monitored in real time. Based on historical data of the comprehensive storage benefit index, the benefit change coefficient is calculated. Then, based on the comparison of the benefit change coefficient with the first and second preset benefit change coefficients, a dynamic optimization strategy for the advanced control command is determined.

[0122] If the benefit change coefficient is less than or equal to the first preset benefit change coefficient, then a gradual optimization strategy is adopted.

[0123] If the benefit change coefficient is greater than the first preset benefit change coefficient and less than or equal to the second preset benefit change coefficient, then an adjustment optimization strategy is adopted.

[0124] If the benefit change coefficient is greater than the second preset benefit change coefficient, then a reconfiguration optimization strategy is adopted.

[0125] In this embodiment of the invention, the benefit change coefficient is obtained by first setting a statistical window containing five consecutive high-level control commands, and obtaining the comprehensive benefit index of the storage at the beginning of the statistical window as the initial benefit index; then, obtaining the comprehensive benefit index of the storage at the current time as the current benefit index, calculating the difference between the current benefit index and the initial benefit index, and finally calculating the ratio of the difference to the initial benefit index to obtain the benefit change coefficient used to evaluate the overall trend of the system in the near future.

[0126] In this embodiment of the invention, the value range of the first preset benefit change coefficient is -0.05 to -0.02, and the preferred value is -0.03. The value range of the second preset benefit change coefficient is 0.02 to 0.05, and the preferred value is 0.03. The preferred value range and preferred value can be determined according to the actual situation, and are not specifically limited here.

[0127] In this embodiment of the invention, the progressive optimization strategy is to reduce the injection pressure benchmark value by 3% to 5% on the existing basis, preferably by 4%, and to extend the pulse period by 10% to 15%, preferably by 13%.

[0128] In this embodiment of the invention, the adjustment optimization strategy is to switch the currently executed advanced control instruction. That is, if the currently executed advanced control instruction is an enhancing pulse instruction, it is switched to a robust pulse instruction; if the currently executed advanced control instruction is a robust pulse instruction, it is switched to a protective pulse instruction.

[0129] In this embodiment of the invention, the reconfigurable optimization strategy is to increase the injection pressure reference value by 3% to 5% on the existing basis, increase the pulse pressure amplitude by 2 MPa to 3 MPa (preferably 2.5 MPa), and shorten the pulse period by 10% to 15% (preferably 12%).

[0130] Specifically, this invention assesses the eligibility of advanced control commands and calculates the benefit variation coefficient based on historical data of the comprehensive benefit index of the storage facility. It then determines a dynamic optimization strategy for the advanced control commands based on a comparison of the benefit variation coefficient with a first preset benefit variation coefficient and a second preset benefit variation coefficient. A progressive optimization strategy is implemented when the benefit variation coefficient is less than or equal to the first preset benefit variation coefficient; an adjustment optimization strategy is implemented when the benefit variation coefficient is greater than the first preset benefit variation coefficient but less than or equal to the second preset benefit variation coefficient; and a reconstructive optimization strategy is implemented when the benefit variation coefficient is greater than the second preset benefit variation coefficient. This tiered optimization approach enables timely identification and correction of control deviations, adapts to changes in formation conditions, enhances the system's adaptability and robustness, and ensures the continuous efficiency and controllable risks of the storage operation.

[0131] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for supercritical carbon dioxide mineralization and storage in deep shale, characterized in that, include: The geological characteristics of the target shale layer and the determination of the initial injection parameter spectrum based on the storage target were used to assess the theoretical maximum mineralization storage capacity of the reservoir. Real-time monitoring of key parameters of the supercritical carbon dioxide phase state downhole is used to obtain the phase state proximity coefficient, in order to determine the pressure-prioritizing and energy-saving pressure reduction, as well as the dynamic fine-tuning steady state of the initial injection parameter spectrum. Real-time monitoring of the strain field near the wellbore yields the maximum compressive principal strain value, and the comprehensive benefit index of the storage is obtained to determine whether the advanced control command for the initial injection parameter spectrum is a protective pulse injection command or an enhanced pulse injection command, and to predict the relative benefit gain coefficient. The process of advanced manipulation of the initial injection parameter spectrum and prediction of the relative benefit gain coefficient includes, The maximum compressive principal strain value was obtained by acquiring the strain field in the near-wellbore zone. The dynamic equivalent storage capacity is obtained by calculating the sum of adsorption storage capacity, mineralization storage capacity, and tectonic storage capacity. The comprehensive benefit index of the storage is obtained by multiplying the standardization achievement rate and the safety factor. The comprehensive benefit index of the sealed storage is compared with the first preset comprehensive benefit index of the sealed storage; The protective pulse injection command is executed based on the fact that the comprehensive benefit index of the sealing is less than or equal to the first preset comprehensive benefit index of the sealing. The comprehensive benefit index of the sealed storage is compared with the second preset comprehensive benefit index of the sealed storage; Based on the fact that the comprehensive benefit index of the sealed storage is greater than the first preset comprehensive benefit index of the sealed storage and less than or equal to the second preset comprehensive benefit index of the sealed storage, a robust pulse injection command is determined to be executed. The enhanced pulse injection command is executed based on the fact that the comprehensive benefit index of the sealed storage is greater than the second preset comprehensive benefit index of the sealed storage. Wherein, the first preset comprehensive benefit index for sealing is less than the second preset comprehensive benefit index for sealing; After the advanced control command has been executed for one complete pulse cycle, the validity of the advanced control command for the initial injection parameter spectrum is determined based on the benefit gain deviation value. If the advanced control command for the initial injection parameter spectrum is determined to be unqualified, the cumulative injection time of supercritical carbon dioxide is monitored in real time, and the progressive optimization or reconfiguration optimization of the advanced control command is determined based on the benefit change coefficient.

2. The method for supercritical carbon dioxide mineralization and storage in deep shale according to claim 1, characterized in that, The process of initial regulation of the initial injection parameter spectrum includes, Obtain downhole pressure and temperature of supercritical carbon dioxide; The phase proximity coefficient is obtained by weighted summation; The phase state proximity coefficient is compared with a preset first phase state proximity coefficient; Based on the phase proximity coefficient being less than or equal to a preset first phase proximity coefficient, a pressurization priority control strategy is determined for the initial injection parameter spectrum.

3. The method for supercritical carbon dioxide mineralization and storage in deep shale according to claim 2, characterized in that, The process of initial regulation of the initial injection parameter spectrum also includes, The phase state proximity coefficient is compared with a preset second phase state proximity coefficient; Based on the fact that the phase state proximity coefficient is greater than the preset first phase state proximity coefficient and less than or equal to the preset second phase state proximity coefficient, a dynamic fine-tuning steady-state strategy is determined for the initial injection parameter spectrum. Based on the fact that the phase state proximity coefficient is greater than the preset second phase state proximity coefficient, an energy-saving and pressure-reducing control strategy is determined for the initial injection parameter spectrum. Wherein, the preset first phase state proximity coefficient is less than the preset second phase state proximity coefficient.

4. The method for supercritical carbon dioxide mineralization and storage of deep shale according to claim 3, characterized in that, The process of determining whether the advanced control instructions for the initial injection parameter spectrum are qualified based on the benefit gain deviation value includes: Obtain the pre-regulation benefit index and the post-regulation benefit index; The difference between the post-regulation benefit index and the pre-regulation benefit index is calculated to obtain the benefit index difference. The actual relative benefit gain coefficient is obtained by calculating the ratio of the benefit index difference to the benefit index before regulation. The difference between the actual relative benefit gain coefficient and the predicted relative benefit gain coefficient is used to obtain the benefit gain deviation value. Based on the fact that the benefit gain deviation value is greater than the preset deviation value, the advanced control command is determined to be unqualified.

5. The method for supercritical carbon dioxide mineralization and storage in deep shale according to claim 4, characterized in that, The process of determining whether to implement an incremental or refactoring optimization strategy to dynamically optimize high-level control instructions based on the benefit variation coefficient includes the following steps. Set a statistical window that includes a period of several consecutive advanced control commands; The comprehensive benefit index of the sealed-up area at the start time of the statistical window is recorded as the initial benefit index. The current comprehensive benefit index of the storage is recorded as the current benefit index; Calculate the difference between the current benefit index and the initial benefit index; The ratio of the difference to the initial benefit index is used to obtain the benefit change coefficient; The benefit change coefficient is compared with the first preset benefit change coefficient; Based on the fact that the benefit change coefficient is less than or equal to the first preset benefit change coefficient, a gradual optimization strategy is adopted.

6. The method for supercritical carbon dioxide mineralization and storage of deep shale according to claim 5, characterized in that, The process of determining whether to implement an incremental or refactoring optimization strategy to dynamically optimize high-level control instructions based on the benefit change coefficient also includes... The benefit change coefficient is compared with the second preset benefit change coefficient; Based on the fact that the benefit change coefficient is greater than the first preset benefit change coefficient and less than or equal to the second preset benefit change coefficient, an adjustment optimization strategy is adopted.

7. The method for supercritical carbon dioxide mineralization and storage in deep shale according to claim 6, characterized in that, The process of determining whether to implement an incremental or refactoring optimization strategy to dynamically optimize high-level control instructions based on the benefit change coefficient also includes... Based on the fact that the benefit change coefficient is greater than the second preset benefit change coefficient, a reconstructive optimization strategy is adopted. Wherein, the first preset benefit change coefficient is less than the second preset benefit change coefficient.

Images