Carbon sequestration site determination method and device, storage medium and electronic equipment

Abstract

The embodiment of the invention provides a carbon sequestration site determination method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining underground geophysical prospecting data of a target region, the underground geophysical prospecting data at least comprises geological structure information corresponding to the target area and seismic data corresponding to different geological structures of the target area; performing well connection contrastive analysis on the underground geophysical prospecting data to predict depth information corresponding to different geological structures in the target area; simulating the geological storage process of CO2 under different geological structures according to the depth information and the geological structure information so as to determine storage potentials corresponding to the different geological structures; and determining a target location for carbon sequestration in the target area according to the depth information and the sequestration potential. According to the method, the problem that the carbon sequestration site of the region under the complex geological condition is difficult to determine in the related technology can be solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon storage geologic body, preferably to the evaluation technology field, in particular to a carbon storage site determination method and device, a storage medium and an electronic device. BACKGROUND

[0002] Currently, the optimization and evaluation of carbon storage geologic bodies mainly use geophysical prospecting techniques such as seismic exploration to directly identify the three-dimensional structure, stratigraphic distribution and structural characteristics of the geologic body, or indirectly invert the physical properties, shale content and water saturation of the storage and cap rock of the geologic body, and comprehensively optimize the storage horizon and evaluate the storage feasibility.

[0003] Currently, the evaluation of storage mainly considers surface factors, and the resolution of underground geophysical prospecting data is low, which is difficult to meet the requirements of accurate evaluation. However, in areas such as the Ordos Basin, the landform is complex, with gullies crisscrossing, thick loess layers, and serious impact on the quality of geological data, which limits the accurate evaluation and optimization of carbon storage geologic bodies.

[0004] In view of the problem that it is difficult to determine the carbon storage site of the region under complex geological conditions in the related art, no effective solution has been proposed so far.

[0005] Therefore, it is necessary to improve the related art to overcome the defects in the related art. SUMMARY

[0006] The embodiments of the present application provide a carbon storage site determination method and device, a storage medium and an electronic device to at least solve the problem that it is difficult to determine the carbon storage site of the region under complex geological conditions in the related art.

[0007] According to an embodiment of the present application, a carbon storage site determination method is provided, comprising: obtaining underground geophysical prospecting data of a target region, wherein the underground geophysical prospecting data at least includes: geological structure information corresponding to the target region and seismic data corresponding to different geological structures of the target region; performing well correlation analysis on the underground geophysical prospecting data to predict depth information corresponding to different geological structures in the target region; simulating the geological storage process of CO2 under different geological structures according to the depth information and the geological structure information to determine the storage potential corresponding to different geological structures; and determining a target site for carbon storage in the target region according to the depth information and the storage potential.

[0008] In one example embodiment, the underground geophysical data of the target area is acquired, including: acquiring first geophysical data in the target area based on a target geophysical acquisition technology, wherein the target geophysical acquisition technology at least includes one of the following: a small bin acquisition technology, a large dose acquisition technology; performing static correction and denoising processing on the first geophysical data to determine second geophysical data; performing velocity analysis on the second geophysical data, and correcting the second geophysical data according to the velocity analysis result to acquire the underground geophysical data.

[0009] In one example embodiment, the underground geophysical data is subjected to well-to-well comparative analysis to predict the depth information corresponding to different geological structures in the target area, including: acquiring well data of a plurality of drillings in the target area, and determining a standard formation according to the well data, wherein the well data of the plurality of drillings is used to indicate the underground rock physical properties of the target area; performing well-to-well comparison based on the standard formation, and establishing a well-to-well comparison framework corresponding to the target area according to the comparison result of the well-to-well comparison, wherein the well-to-well comparison framework is a framework for comparing the geological structures of the plurality of drillings between the plurality of drillings based on the standard formation; converting the seismic data from the time domain to the depth domain according to the well-to-well comparison framework, and performing data comparison between the seismic data converted to the depth domain and the well data to acquire depth domain well-seismic comparison data, wherein the seismic data converted to the depth domain is used to indicate the seismic attributes of the target area, and the depth domain well-seismic comparison data is used to indicate the relationship between the seismic attributes of the target area and the underground rock physical properties; performing data fusion on the seismic data converted to the depth domain, the geophysical data, and the well data based on a data fusion technology, and processing the fused data through a multi-attribute parameter joint interpretation technology to acquire geological attribute data corresponding to different geological structures in the target area; predicting the depth information corresponding to different geological structures in the target area according to the geological attribute data and the depth domain well-seismic comparison data.

[0010] In one example embodiment, the depth information corresponding to different geological structures in the target area is predicted according to the geological attribute data and the depth domain well-seismic comparison data, including: establishing a depth model corresponding to the target area according to the depth domain well-seismic comparison data, and establishing an attribute model corresponding to the target area according to the geological attribute information; model integrating the depth model and the attribute model according to a fusion algorithm to determine the mapping relationship between the geological attributes and the depth in the target area; predicting the depth information corresponding to different geological structures in the target area according to the mapping relationship.

[0011] In an example embodiment, simulating the geological storage process of CO2 under different geological structures according to the depth information and the geological structure information comprises: constructing a three-dimensional geological model corresponding to the target region according to the depth information and the geological structure information; determining physical and chemical action parameters of CO2 in the underground environment of the target region according to the three-dimensional geological model; determining a state equation and a boundary condition of the target region according to the physical and chemical action parameters and a phase change of CO2, wherein the phase change is a phase change of CO2 under different temperatures and different pressures; inputting the state equation and the boundary condition into a numerical simulation model, so that the numerical simulation model simulates the geological storage process of CO2 under different geological structures.

[0012] In an example embodiment, determining a target site for carbon storage in the target region according to the depth information and the storage potential comprises: performing multi-criteria decision analysis on different geological structures of the target region according to the depth information, the storage potential and the underground geophysical data, and determining a first site allowing storage of CO2 in the target region according to an analysis result of the multi-criteria decision analysis; performing risk assessment on the first site; and determining the first site as the target site in a case where the risk assessment result of the first site is determined as low risk.

[0013] According to another embodiment of the present application, a device for determining a carbon storage site is provided, comprising: an acquisition module configured to acquire underground geophysical data of a target region, wherein the underground geophysical data at least comprises geological structure information corresponding to the target region and seismic data corresponding to different geological structures of the target region; an analysis module configured to perform well-to-well correlation analysis on the underground geophysical data to predict depth information corresponding to different geological structures in the target region; a simulation module configured to simulate a geological storage process of CO2 under different geological structures according to the depth information and the geological structure information to determine storage potential corresponding to different geological structures; and a determination module configured to determine a target site for carbon storage in the target region according to the depth information and the storage potential.

[0014] According to yet another embodiment of the present application, a computer readable storage medium is also provided, and the computer readable storage medium stores a computer program, wherein the computer program is configured to perform the steps in any of the method embodiments described above when executed.

[0015] According to yet another embodiment of the present application, an electronic device is also provided, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to perform the steps in any of the method embodiments described above.

[0016] According to still another embodiment of the present application, a computer program product is also provided, comprising a computer program which, when executed by a processor, implements the steps of any of the above method embodiments.

[0017] By the embodiments of the present application, the underground geophysical prospecting data of the target region is acquired, the underground geophysical prospecting data at least including the geological structure information corresponding to the target region and the seismic data corresponding to different geological structures of the target region, the well-to-well comparative analysis is performed on the underground geophysical prospecting data to predict the depth information corresponding to different geological structures in the target region, the geological sequestration process of CO2 under different geological structures is simulated according to the depth information and the geological structure information to determine the sequestration potential corresponding to different geological structures, and then the target site for carbon sequestration in the target region is determined according to the depth information and the sequestration potential. That is, the embodiments of the present application predict the depth information of different geological structures by collecting the underground geophysical prospecting data of the target region, including the geological structure information and the seismic data, and using the well-to-well comparative analysis. The sequestration process of CO2 under different geological structures is evaluated by using the numerical simulation technology in combination with the depth information and the structure data, and the sequestration potential of each geological structure is quantified. Finally, the carbon sequestration site in the target region is accurately selected according to the depth information and the sequestration potential analysis. Through the embodiments of the present application, the problem that it is difficult to determine the carbon sequestration site of the region under complex geological conditions in the related art can be solved, and the effective carbon sequestration site under complex geological conditions can be optimized. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, those skilled in the art can obtain other drawings according to these drawings without any creative effort.

[0020] Figure 1 is a hardware structure block diagram of a computer terminal device of a carbon sequestration site determination method according to an embodiment of the present application;

[0021] Figure 2 is a flowchart of a carbon sequestration site determination method according to an embodiment of the present application;

[0022] Figure 3 is a structure block diagram of a carbon sequestration site determination device according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] The embodiments of this application will be described in detail below with reference to the accompanying drawings and examples.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0025] The methods and embodiments provided in this application can be executed on a computer terminal device or a similar computing device. Taking running on a computer terminal device as an example, Figure 1 This is a hardware structure block diagram of a computer terminal device for a method of determining a carbon sequestration location according to an embodiment of this application. Figure 1 As shown, a computer terminal device may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The computer terminal device may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal device described above. For example, the computer terminal device may also include components that are more complex than those described above. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0026] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the carbon sequestration location determination method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the aforementioned method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to computer terminal devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0027] The transmission device 106 is configured to receive or send data via a network. The network can include a wireless network provided by a communication service provider of a computer terminal device. In one example, the transmission device 106 includes a network interface controller (NIC) that can be connected to other network devices through a base station to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module configured to communicate with the Internet through a wireless manner.

[0028] The embodiment provides a method for determining a carbon storage site, Figure 2 is a flowchart of the method for determining a carbon storage site according to the embodiment of the present application, as shown in the figure, the flow includes the following steps: Figure 2

[0029] In step S202, underground geophysical prospecting data of a target area is acquired, wherein the underground geophysical prospecting data at least includes geological structure information corresponding to the target area and seismic data corresponding to different geological structures of the target area.

[0030] The underground geophysical prospecting data is a detection and description of underground geological features from different angles and scales. The underground geophysical prospecting data can include the geological structure information and the seismic data, and can also include underground fluid analysis data, core analysis data and other data. The seismic data can be obtained through seismic exploration technology, including seismic reflection, refraction and seismic tomography, etc. The seismic data can reveal information such as structure, depth, velocity and density of underground strata.

[0031] In step S204, well-to-well correlation analysis is performed on the underground geophysical prospecting data to predict depth information corresponding to different geological structures in the target area.

[0032] ​Among them, the above-mentioned joint well contrast analysis is a comprehensive analysis method in geology and geophysics, mainly used to establish a unified geological horizon framework among multiple wells to improve the understanding of underground geological structure and lithological characteristics. Specifically, it can be realized by the following steps: data collection: collecting logging curves (such as natural gamma, resistivity, acoustic velocity, etc.), core description, formation thickness, depth data, etc. from multiple wells. Key horizon identification: identify geological interfaces or horizons with distinct characteristics in each well, which are usually defined by special rock types, colors, structures or logging responses, and are easy to compare between wells. Depth correction: due to the influence of topography and stratigraphic dip, the depth reference of different wells may not be consistent. Joint well contrast analysis requires depth correction to ensure that the depth contrast of horizons between wells is accurate. This is usually achieved by establishing the correspondence between seismic reflection layers and geological horizons in the depth domain. Horizon correlation: on the basis of depth correction, correlate the geological horizons of each well, identify and track the lateral variation of strata, establish the continuity and correspondence of horizons between wells, and form a unified geological sequence framework. Geological modeling: use the results of contrast analysis to establish a three-dimensional geological model to visually display the distribution and variation of underground geological structure, and provide a basis for resource assessment, carbon storage site selection, etc. Parameter interpretation and prediction: through joint well contrast, the geological parameters (such as rock type, porosity, permeability, etc.) can be associated with seismic attributes to predict the geological characteristics of un-drilled areas.

[0033] Step S206, simulating the geological storage process of CO2 under different geological structures according to the depth information and the geological structure information to determine the storage potential corresponding to different geological structures;

[0034] Among them, the above-mentioned geological storage process can include the migration, storage and leakage process of CO2 in the target area, etc.

[0035] The above-mentioned storage potential refers to the ability of a specific geological structure to safely and effectively store carbon dioxide (CO2). The assessment of this ability takes into account the physical properties of the geological body, such as porosity and permeability, which determine the space for CO2 and the flow resistance; the stability of the chemical environment, including the composition of underground fluids and the chemical reactivity of rocks, to ensure the long-term stability of CO2 in the geological body; and the integrity of the geological structure, such as the sealing of faults and the continuity of strata, to prevent CO2 leakage.

[0036] Step S208, determining the target site for carbon storage in the target area according to the depth information and the storage potential.

[0037] Through the above steps, the underground geophysical data of the target region is obtained, and the underground geophysical data at least includes the geological structure information corresponding to the target region and the seismic data corresponding to different geological structures of the target region. The well correlation analysis is performed on the underground geophysical data to predict the depth information corresponding to different geological structures in the target region. The geological sequestration process of CO2 in different geological structures is simulated according to the depth information and the geological structure information, so as to determine the sequestration potential corresponding to different geological structures. Then, the target location for carbon sequestration in the target region is determined according to the depth information and the sequestration potential. That is, the underground geophysical data of the target region is collected, including the geological structure information and the seismic data, the depth information of different geological structures is predicted by using the well correlation analysis, the depth information and the structure data are combined, and the numerical simulation technology is used to evaluate the sequestration process of CO2 in different geological structures, so as to quantify the sequestration potential of each geological structure. Finally, the carbon sequestration location in the target region is accurately selected according to the depth information and the sequestration potential analysis. Through the embodiments of the present application, the problem that it is difficult to determine the carbon sequestration location in the region under complex geological conditions in the related art can be solved, and the effective carbon sequestration location under complex geological conditions can be selected.

[0038] Optionally, the step S202 of obtaining the underground geophysical data of the target region includes: obtaining first geophysical data in the target region based on a target geophysical acquisition technology, wherein the target geophysical acquisition technology at least includes one of the following: a small bin acquisition technology and a large dose acquisition technology; performing static correction and denoising processing on the first geophysical data to determine second geophysical data; performing velocity analysis on the second geophysical data, and correcting the second geophysical data according to the velocity analysis result to obtain the underground geophysical data.

[0039] It can be understood that the above-mentioned small bin acquisition technology is a high-precision seismic exploration method, which can significantly improve the resolution of underground geological structure imaging by reducing the size of the seismic data acquisition unit (i.e., bin size). The small bin acquisition technology uses a dense array of seismic sources and receivers during acquisition to make multiple measurements with smaller coverage areas, thereby obtaining more detailed underground information. The small bin technology is particularly suitable for complex geological environments that require high-resolution imaging, such as fault identification, lithology differentiation, and small-scale geological body detection, and it can reveal smaller-scale geological heterogeneity and structural details to provide more accurate geological data for carbon sequestration projects and the like.

[0040] The large amount of acquisition technology refers to using a relatively large amount of explosives as a seismic source in seismic exploration to enhance the energy of seismic waves and improve the detection capability of deep underground information. By increasing the energy of the seismic source, the effects of surface noise and deep signal attenuation can be overcome, allowing seismic waves to penetrate deeper into the strata and obtain more distant and deeper geological information. Large amount technology is crucial for improving the signal-to-noise ratio of seismic data and enhancing the intensity of deep stratum reflection waves, especially in areas with thick overburden, complex terrain, or high penetration requirements. It can help researchers more accurately identify the three-dimensional structure and characteristics of geological bodies, providing key deep geological data support for carbon storage projects.

[0041] In the process of obtaining underground geophysical data in the target area, first, small bin acquisition technology or large amount acquisition technology is used to obtain the first geophysical data in the target area. Small bin acquisition technology can improve data resolution and accurately capture geological structure details by reducing the size of the acquisition unit and using a more dense source and receiver layout, making it particularly suitable for complex geological environments or areas requiring high-resolution imaging. Large amount acquisition technology increases the energy of the source to enhance the penetration of seismic waves and the intensity of deep signals.

[0042] After collecting the first geophysical data, data preprocessing is performed, including static correction and denoising. Static correction is used to eliminate differences in seismic wave propagation velocity caused by terrain, surface conditions, and other factors, ensuring that seismic data from different locations are compared under the same conditions. Denoising aims to remove random noise in seismic records, improving signal clarity and making geological features more apparent.

[0043] Velocity analysis is performed on the preprocessed second geophysical data to determine the wave velocity distribution of the underground medium. Through velocity analysis, an underground velocity model can be established to further correct seismic data to compensate for the time difference of seismic waves propagating in different depths and media, resulting in more accurate underground geophysical data.

[0044] Optionally, the step S204 of comparing the underground geophysical data between wells to predict the depth information corresponding to different geological structures in the target area comprises: obtaining well data of multiple wells in the target area, wherein the well data of the multiple wells is used to indicate the underground rock physical properties of the target area; comparing the multiple wells based on the standard stratum to establish an inter-well comparison framework corresponding to the target area, wherein the inter-well comparison framework is a framework for comparing the geological structures of the multiple wells based on the standard stratum established between the multiple wells; converting the seismic data from the time domain to the depth domain according to the inter-well comparison framework, and comparing the seismic data converted from the time domain to the depth domain with the well data to obtain depth domain well-seismic comparison data, wherein the seismic data converted from the time domain to the depth domain is used to indicate the seismic attributes of the target area, and the depth domain well-seismic comparison data is used to indicate the relationship between the seismic attributes of the target area and the underground rock physical properties; performing data fusion on the seismic data converted from the time domain to the depth domain, the geophysical data and the well data based on a data fusion technology, and processing the fused data through a multi-attribute parameter joint interpretation technology to obtain geological attribute data corresponding to different geological structures in the target area; and predicting the depth information corresponding to different geological structures in the target area according to the geological attribute data and the depth domain well-seismic comparison data.

[0045] It can be understood that the well data mentioned above refers to underground geological information obtained through various logging methods and techniques during the drilling process, including but not limited to core analysis, logging curves (such as natural gamma, resistivity, acoustic velocity), downhole video, formation thickness and rock physical properties, etc. These data provide detailed information about underground rock types, porosity, permeability, and depth and stratigraphic continuity.

[0046] The inter-well comparison framework mentioned above is a set of systematic comparison methods and standards established between multiple wells, which is used to identify and track the lateral changes and continuity of strata. It is based on the comparison of key geological marker layers such as lithology changes, stratigraphic contact interfaces, etc., and uses depth correction technology to ensure the comparability of different well data, forming a unified three-dimensional geological sequence model, which provides a basis for regional geological research, resource assessment and engineering decision-making.

[0047] The above-mentioned standard stratigraphy refers to stratigraphic units widely recognized and used in geological research, which have specific lithological characteristics, sedimentary environments and age backgrounds. They usually have obvious stratigraphic boundaries and lithological markers, which can be used as a reference for regional geological correlation and age division, helping to establish a geological time framework and spatial distribution model, based on which the geological history, stratigraphic evolution and resource distribution can be understood and explained.

[0048] The above-mentioned depth domain well-seismic correlation data is information obtained by comparing and matching between well data and seismic data after depth correction. This data comparison is carried out in geological depth rather than seismic time, aiming to more accurately identify and locate the stratigraphic features recorded in well data on seismic profiles, thereby improving the accuracy and reliability of seismic interpretation.

[0049] The above-mentioned seismic attribute refers to a quantitative parameter that can reflect the physical properties of underground rocks and geological characteristics extracted through seismic data processing and interpretation. These attributes include but are not limited to amplitude, frequency, phase, waveform, polarization, etc., as well as parameters obtained through mathematical transformation or model interpretation, such as porosity, permeability, saturation, shale content, etc. Seismic attribute analysis is used to identify the lithology, fluid properties and structural characteristics of the strata.

[0050] In geological exploration and carbon storage assessment, the inter-well correlation analysis of geophysical data is a complex and meticulous process, aiming to predict and understand the depth information and physical properties of different geological structures in the target area through comprehensive analysis of seismic data and well data in the target area. Specifically:

[0051] The well data of multiple wells in the target area are collected, which contain detailed information on the physical properties of underground rocks, such as rock porosity and permeability.

[0052] Based on these standard stratigraphies, inter-well correlation is the process of finding and matching geological features between different wells. Through inter-well correlation, an inter-well correlation framework can be established, which clearly shows the lateral correlation relationship between geological structures in multiple wells under the guidance of standard stratigraphy.

[0053] Subsequently, using the inter-well correlation framework, seismic data is converted from time domain to depth domain, which is based on seismic wave velocity and depth information of standard stratigraphy, so that seismic data and well data can be compared on the same depth scale. Through depth domain well-seismic correlation, the relationship between seismic data attributes and rock physical properties becomes clear, and depth domain well-seismic correlation data can directly reflect the relationship between seismic attributes and underground rock physical properties in the target area.

[0054] Based on the above steps, data fusion technology is introduced to integrate the depth-converted seismic data, geophysical data (such as magnetic and gravity measurement data), and well data to form a unified data set. Then, multi-attribute parameter joint interpretation technology is applied to process the fused data, and through comprehensive analysis, the geological attribute data of different geological structures in the target area are obtained, including lithology, fluid properties, shale content, etc.

[0055] Finally, combined with the geological attribute data and the depth domain well-seismic correlation data, the depth information of different geological structures in the target area can be predicted, including the specific depth of each layer, the thickness and distribution of the strata.

[0056] Among them, predicting the depth information corresponding to different geological structures in the target area according to the geological attribute data and the depth domain well-seismic correlation data includes: establishing a depth model corresponding to the target area according to the depth domain well-seismic correlation data, and establishing an attribute model corresponding to the target area according to the geological attribute information; model integration of the depth model and the attribute model is performed according to the fusion algorithm to determine the mapping relationship between the geological attributes and the depth in the target area; the depth information corresponding to different geological structures in the target area is predicted according to the mapping relationship.

[0057] It can be understood that in geoscience and carbon storage assessment, the prediction of depth information is based on the comprehensive analysis of geological attribute data and depth domain well-seismic correlation data. This process first involves the construction of a depth model and an attribute model, then determines the mapping relationship between geological attributes and depth through model integration, and finally realizes the prediction of depth information of different geological structures in the target area.

[0058] Depth domain well-seismic correlation data provides a direct way to associate seismic attributes of seismic data with subsurface rock physical properties of well data. Based on these data, a depth model of the target area can be established through geological modeling technology, which is a three-dimensional model that describes the relationship between seismic attributes and stratum depth in detail.

[0059] Using geological attribute data, an attribute model of the target area is constructed. This model contains the physical properties of subsurface rocks such as lithology, porosity, permeability, and parameters closely related to storage potential such as fluid saturation.

[0060] Model integration of the depth model and the attribute model is performed through a fusion algorithm. Fusion algorithm is a data processing technology aimed at fusing data from different sources into a unified model to maximize information utilization and accuracy. In this process, the depth model and the attribute model are integrated together to determine the mapping relationship between geological attributes and depth, i.e., to determine the corresponding relationship between the physical properties of the strata and the seismic attributes at a specific depth.

[0061] Based on the determined mapping relationship, the depth information corresponding to different geological structures in the target area can be predicted. This step, through the prediction ability of the model, combined with the geological attribute data, can calculate the depth of the geological structure in the unexplored area, including the specific depth of each layer, the thickness of the stratum and its distribution characteristics.

[0062] Optionally, the step S206 of simulating the geological storage process of CO2 under different geological structures according to the depth information and the geological structure information comprises: constructing a three-dimensional geological model corresponding to the target area according to the depth information and the geological structure information; determining the physical and chemical action parameters of CO2 in the underground environment of the target area according to the three-dimensional geological model; determining the equation of state and the boundary conditions of the target area according to the physical and chemical action parameters and the phase change of CO2 corresponding to the phase change of CO2 under different temperatures and different pressures; inputting the equation of state and the boundary conditions into the numerical simulation model to make the numerical simulation model simulate the geological storage process of CO2 under different geological structures.

[0063] It can be understood that simulating the geological storage process of CO2 under different geological structures is a systematic engineering covering model construction, parameter determination and numerical simulation, and its purpose is to predict and evaluate the behavior and storage effect of CO2 in the underground environment. The specific steps include: based on the previously predicted depth information and the obtained geological structure information, a three-dimensional geological model of the target area is constructed. This model describes the spatial distribution of the underground geological body in detail, including the key parameters such as the sequence, thickness, lithology, porosity and permeability of the stratum.

[0064] Using the three-dimensional geological model, the physical and chemical action parameters of CO2 in the underground environment of the target area are determined. These parameters involve the interaction between CO2 and the surrounding rock and fluid, such as adsorption, dissolution, chemical reaction, etc.

[0065] Considering the phase change of CO2 under different temperatures and pressures, the equation of state is determined. The equation of state is a mathematical expression describing the state change of a substance under different conditions. For CO2, this involves the conversion between gaseous, liquid and supercritical states.

[0066] In addition, the boundary conditions of the target area also need to be determined, including the boundary properties of the geological body (such as sealing, permeability), initial pressure and temperature, injection rate and total amount of CO2, and other key parameters.

[0067] Finally, the state equation, physical and chemical action parameters, and boundary conditions are input into the numerical simulation model. The numerical simulation model is a computer model based on physical principles and geological conditions, which can simulate the storage process of CO2 in different geological structures, including CO2 injection, migration, diffusion, storage, and possible leakage, by solving complex mathematical equations.

[0068] Optionally, the step S208 of determining the target site for carbon storage in the target region according to the depth information and the storage potential comprises: performing multi-criteria decision analysis on different geological structures of the target region according to the depth information, the storage potential, and the underground geophysical data, and determining a first site allowing CO2 storage in the target region according to an analysis result of the multi-criteria decision analysis; performing risk assessment on the first site; and determining the first site as the target site in a case where a risk assessment result of the first site is determined to be low risk.

[0069] It can be understood that the process of determining the target site for carbon storage starts from the comprehensive consideration of the depth information and the storage potential of the target region. First, the depth information, the storage potential, and the underground geophysical data are fused by a multi-criteria decision analysis method to perform systematic evaluation on different geological structures in the target region. This analysis considers multiple key factors, including the physical properties of the geological body, the depth position, the seismic attribute, and a series of indicators related to CO2 storage, aiming to identify the most suitable geological structure for CO2 storage, i.e., the first site allowing CO2 storage. Then, detailed risk assessment is performed on the selected first site, which can include geological risk, environmental risk, and engineering implementation risk, etc., to ensure that the selected site meets the storage requirements in terms of safety and stability.

[0070] In a case where the risk assessment result of the first site is confirmed to be low risk, the site is formally determined as the target site, i.e., the most suitable implementation region for carbon storage.

[0071] In order to better understand the process of the above-mentioned method for determining the carbon storage site, the implementation method flow of the above-mentioned method for determining the carbon storage site will be described in combination with optional embodiments below, but not used to limit the technical solutions of the embodiments of the present application.

[0072] The optional embodiments of the present application provide a multi-parameter and multi-scale carbon storage geological body optimization and evaluation method, in particular:

[0073] 1) High-precision 3D geophysical acquisition, processing, and interpretation technology. Based on small bin and large amount of geophysical acquisition means, using static correction, stacking denoising, and fine velocity analysis processing technology, the data resolution is improved to ≤10m; 3D geological modeling and visualization: using 3D geological modeling technology to build a digital model of geological body, and through visualization means to show the internal structure and structural features of the geological body, providing intuitive basis for optimization and evaluation.

[0074] That is, to solve the problem of low resolution of underground geophysical data, small bin and large amount of geophysical acquisition means are used to ensure that high-precision geophysical data can still be obtained under complex topographic conditions. Through static correction, stacking denoising, and fine velocity analysis processing technology, the resolution of geophysical data is further improved to 10 meters or less, which means that the underground geological structure and anomalies can be identified more carefully, providing more accurate basic data for subsequent geological modeling and carbon storage evaluation.

[0075] 2) Multi-geological condition and multi-parameter geological body analysis technology. Based on well correlation, the drilling depth and sedimentary facies are finely described and predicted, and the difference between the actual drilling depth and the predicted depth is less than 50m; through multi-attribute parameter joint interpretation based on geophysical data, the interpretation accuracy is improved from "group" (hundred-meter level) to "layer" (ten-meter level), meeting the needs of fine evaluation of carbon storage.

[0076] That is, based on the fine description and prediction technology of well correlation, the depth and sedimentary facies of the well can be more accurately predicted, and the difference between the actual drilling depth and the predicted depth is controlled within 50 meters, which is of great significance for precise drilling in complex topographic conditions. In addition, through multi-attribute parameter joint interpretation of geophysical data, the interpretation accuracy is improved from group level to layer level, greatly improving the fineness of interpretation, meeting the needs of fine division of geological horizon in carbon storage evaluation.

[0077] 3) Numerical simulation: Through numerical simulation method, the migration, storage and leakage process of carbon dioxide in geological body are simulated, and the storage capacity and safety of geological body are evaluated.

[0078] That is, through numerical simulation method, the migration, storage and leakage process of carbon dioxide in geological body are simulated, which not only can evaluate the storage capacity and safety of geological body, but also can predict the behavior of carbon dioxide under different geological conditions, providing scientific basis for carbon storage site selection. For areas like Ordos Basin, numerical simulation can help overcome the limitations of thick loess layer and complex topography, providing more comprehensive dynamic prediction and risk assessment of storage.

[0079] 4) Comprehensive evaluation: Based on the results of multiple parameters and scales, the potential carbon storage geological body is comprehensively evaluated to determine the optimal storage site and scheme.

[0080] The comprehensive evaluation is performed by combining three-dimensional geophysical prospecting data, multi-parameter geological body analysis results, numerical simulation prediction and other multi-scale and multi-source information. The evaluation method can comprehensively consider factors such as geology, topography, geophysical prospecting and engineering implementation, effectively evaluate the comprehensive storage potential of the geological body, and determine the optimal carbon storage site and implementation scheme. This is crucial for overcoming the limitations of surface factors and realizing accurate carbon storage evaluation under complex underground geological conditions.

[0081] Through the optional embodiments of the present application, not only the resolution and accuracy of underground geophysical prospecting data under the condition of complex topography in the Ordos Basin and other similar conditions can be significantly improved, but also fine evaluation and optimization of carbon storage geological bodies can be realized, effectively solving the problems of surface factor limitations and low resolution of underground geophysical prospecting data in current storage evaluation.

[0082] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be realized by means of software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases the former is a better implementation. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes a plurality of instructions for causing a terminal device (which can be a mobile phone, computer, server or network device) to execute the method described in each embodiment of the present application.

[0083] In the present embodiment, a carbon storage site determination device is also provided, which is used to implement the above embodiments and preferred embodiments, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware or a combination of software and hardware is also possible and is contemplated.

[0084] Figure 3 is a structural block diagram of the carbon storage site determination device according to the embodiments of the present application, as shown in Figure 3 , the device comprises:

[0085] The acquisition module 32 is configured to acquire underground geophysical prospecting data of a target area, wherein the underground geophysical prospecting data at least includes geological structure information corresponding to the target area and seismic data corresponding to different geological structures of the target area.

[0086] The analysis module 34 is configured to perform well-to-well correlation analysis on the underground geophysical prospecting data to predict depth information corresponding to different geological structures in the target area.

[0087] The simulation module 36 is configured to simulate the geological storage process of CO2 under different geological structures according to the depth information and the geological structure information, to determine the storage potential corresponding to different geological structures.

[0088] The determination module 38 is configured to determine a target site for carbon storage in the target region according to the depth information and the storage potential.

[0089] With the above device, the underground geophysical prospecting data of the target region is acquired, and the underground geophysical prospecting data at least includes the geological structure information corresponding to the target region and the seismic data corresponding to different geological structures of the target region. The underground geophysical prospecting data is subjected to well correlation analysis to predict the depth information corresponding to different geological structures in the target region. The storage process of CO2 under different geological structures is simulated according to the depth information and the geological structure information, to determine the storage potential corresponding to different geological structures. Then, the target site for carbon storage in the target region is determined according to the depth information and the storage potential. That is, the embodiment of the present application collects the underground geophysical prospecting data of the target region, including the geological structure information and the seismic data, and predicts the depth information of different geological structures by using well correlation analysis. The storage process of CO2 under different geological structures is evaluated by using numerical simulation technology in combination with the depth information and the structure data, to quantify the storage potential of each geological structure. Finally, the carbon storage site in the target region is accurately selected according to the depth information and the storage potential analysis. Through the embodiment of the present application, the problem that it is difficult to determine the carbon storage site of the region under complex geological conditions in the related art can be solved, and the effective carbon storage site under complex geological conditions can be selected.

[0090] In an example embodiment, the acquisition module 32 is further configured to acquire first geophysical prospecting data in the target region based on a target geophysical prospecting acquisition technique, wherein the target geophysical prospecting acquisition technique at least includes one of the following: a small bin acquisition technique, a large dose acquisition technique; the first geophysical prospecting data is subjected to static correction and denoising processing to determine second geophysical prospecting data; the second geophysical prospecting data is subjected to velocity analysis, and the second geophysical prospecting data is corrected according to the velocity analysis result to acquire the underground geophysical prospecting data.

[0091] In one example embodiment, the analysis module 34 is further configured to obtain well data of a plurality of drilled wells in the target region, wherein the well data of the plurality of drilled wells is indicative of subsurface petrophysical properties of the target region; perform interwell correlation of the plurality of drilled wells based on the standard formation, wherein the interwell correlation framework is a framework for correlating geological structures of the plurality of drilled wells based on the standard formation; convert the seismic data from time domain to depth domain based on the interwell correlation framework, and perform data correlation between the converted seismic data and the well data to obtain depth domain well-seismic correlation data, wherein the converted seismic data is indicative of seismic attributes of the target region, and the depth domain well-seismic correlation data is indicative of a relationship between the seismic attributes and the subsurface petrophysical properties; perform data fusion of the converted seismic data, the geophysical data, and the well data based on a data fusion technique, and process the fused data based on a multi-attribute parameter joint interpretation technique to obtain geological attribute data corresponding to different geological structures in the target region; and predict depth information corresponding to the different geological structures in the target region based on the geological attribute data and the depth domain well-seismic correlation data.

[0092] In one example embodiment, the analysis module 34 is further configured to establish a depth model corresponding to the target region based on the depth domain well-seismic correlation data, and establish an attribute model corresponding to the target region based on the geological attribute information; perform model integration of the depth model and the attribute model based on a fusion algorithm to determine a mapping relationship between geological attributes and depth in the target region; and predict depth information corresponding to different geological structures in the target region based on the mapping relationship.

[0093] In one example embodiment, the simulation module 36 is further configured to construct a three-dimensional geological model corresponding to the target region based on the depth information and the geological structure information; determine physical and chemical action parameters of CO2 in a subsurface environment of the target region based on the three-dimensional geological model; determine a state equation and boundary conditions of the target region based on the physical and chemical action parameters and a phase change of CO2, wherein the phase change is a phase change of CO2 under different temperatures and different pressures; and input the state equation and the boundary conditions into a numerical simulation model to simulate a geological storage process of CO2 under different geological structures.

[0094] In an example embodiment, the determining module 38 is further configured to perform a multi-criteria decision analysis on different geological structures of the target region according to the depth information, the storage potential and the subsurface geophysical data, and determine a first site allowing storage of CO2 in the target region according to an analysis result of the multi-criteria decision analysis; perform a risk assessment on the first site; and determine the first site as the target site if the risk assessment result of the first site is low risk.

[0095] It should be noted that the above modules can be implemented by software or hardware, and the hardware can be implemented in the following manner, but is not limited thereto: all the modules are located in the same processor; or the modules are located in different processors in any combination.

[0096] Embodiments of the present application also provide a computer readable storage medium, which stores a computer program. The computer program is configured to execute the steps in any of the above method embodiments when running.

[0097] Optionally, in the present embodiment, the storage medium is configured to store program code for executing the following steps:

[0098] S1, obtaining subsurface geophysical data of a target region, wherein the subsurface geophysical data at least includes geological structure information corresponding to the target region and seismic data corresponding to different geological structures of the target region;

[0099] S2, performing well-to-well comparative analysis on the subsurface geophysical data to predict depth information corresponding to different geological structures in the target region;

[0100] S3, simulating a geological storage process of CO2 in different geological structures according to the depth information and the geological structure information to determine storage potential corresponding to different geological structures;

[0101] S4, determining a target site for carbon storage in the target region according to the depth information and the storage potential.

[0102] In an example embodiment, the computer readable storage medium can include, but is not limited to, a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store computer programs.

[0103] The embodiment of the present application further provides an electronic device, comprising a memory and a processor, the memory storing a computer program, and the processor being configured to execute the computer program to perform the steps in any of the method embodiments.

[0104] In an example embodiment, the electronic device further comprises a transmission device connected to the processor and an input / output device connected to the processor.

[0105] Optionally, in the embodiment, the processor can be configured to perform the following steps by the computer program:

[0106] S1, obtaining underground geophysical exploration data of a target area, wherein the underground geophysical exploration data at least comprises geological structure information corresponding to the target area and seismic data corresponding to different geological structures of the target area;

[0107] S2, performing well-to-well comparative analysis on the underground geophysical exploration data to predict depth information corresponding to different geological structures in the target area;

[0108] S3, simulating a geological storage process of CO2 under different geological structures according to the depth information and the geological structure information to determine storage potential corresponding to different geological structures;

[0109] S4, determining a target site for carbon storage in the target area according to the depth information and the storage potential.

[0110] The embodiment of the present application further provides a computer program product, wherein the computer program product comprises a computer program, and the computer program is executed by a processor to implement the steps in any of the method embodiments.

[0111] The embodiment of the present application further provides another computer program product, comprising a non-volatile computer readable storage medium, wherein the non-volatile computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps in any of the method embodiments.

[0112] The embodiment of the present application further provides a computer program, comprising computer instructions stored in a computer readable storage medium; a processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to perform the steps in any of the method embodiments.

[0113] Optionally, in the embodiment, the processor can be configured to perform the following steps by the computer program:

[0114] S1, obtaining underground geophysical data of a target area, wherein the underground geophysical data at least comprises geological structure information corresponding to the target area and seismic data corresponding to different geological structures in the target area;

[0115] S2, performing well-to-well comparative analysis on the underground geophysical data to predict depth information corresponding to different geological structures in the target area;

[0116] S3, simulating geological sequestration process of CO2 under different geological structures according to the depth information and the geological structure information to determine sequestration potential corresponding to different geological structures;

[0117] S4, determining a target site for carbon sequestration in the target area according to the depth information and the sequestration potential.

[0118] The specific examples in the embodiments can refer to the examples described in the above embodiments and exemplary embodiments, and will not be repeated here.

[0119] Obviously, those skilled in the art should understand that the modules or steps of the present application described above can be realized by general computing devices, which can be concentrated on a single computing device or distributed on a network composed of multiple computing devices, and can be realized by program codes executable by the computing devices, so that they can be stored in storage devices and executed by the computing devices, and in some cases, the steps shown or described can be executed in different order, or they can be manufactured into individual integrated circuit modules, or multiple modules or steps can be manufactured into a single integrated circuit module. Thus, the present application is not limited to any specific combination of hardware and software.

[0120] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining a carbon sequestration location, characterized in that, include: Obtain subsurface geophysical data for the target area, wherein the subsurface geophysical data includes at least: geological structure information corresponding to the target area and seismic data corresponding to different geological structures in the target area; The underground geophysical data is subjected to well-to-well comparative analysis to predict the depth information corresponding to different geological structures within the target area; Based on the depth information and the geological structure information, the geological storage process of CO2 under different geological structures is simulated to determine the storage potential corresponding to different geological structures. Based on the depth information and the storage potential, target locations for carbon sequestration are determined within the target area.

2. The method according to claim 1, characterized in that, Acquire subsurface geophysical data for the target area, including: The first geophysical data within the target area is obtained based on the target geophysical acquisition technology, wherein the target geophysical acquisition technology includes at least one of the following: small-area acquisition technology and large-dose acquisition technology; The first geophysical data is subjected to static correction and noise reduction to determine the second geophysical data; the second geophysical data is subjected to velocity analysis, and the second geophysical data is corrected according to the velocity analysis results to obtain the underground geophysical data.

3. The method according to claim 1, characterized in that, The underground geophysical data is subjected to well-to-well comparison analysis to predict the depth information corresponding to different geological structures within the target area, including: Acquire well data from multiple wells within the target area, and determine standard formations based on the well data, wherein the well data from the multiple wells are used to indicate the underground rock physical properties of the target area; Based on the standard formation, the multiple wells are compared between wells, and an inter-well comparison framework corresponding to the target area is established based on the comparison results. The inter-well comparison framework is used to establish a framework for comparing the geological structure of the multiple wells based on the standard formation. According to the well-to-well comparison framework, the seismic data is converted from the time domain to the depth domain, and the seismic data converted to the depth domain is compared with the well data to obtain depth domain well-seismic comparison data. The seismic data converted to the depth domain is used to indicate the seismic properties of the target area, and the depth domain well-seismic comparison data is used to indicate the relationship between the seismic properties of the target area and the physical properties of the underground rocks. Based on data fusion technology, the seismic data, geophysical data and well data converted to the depth domain are fused together, and the fused data is processed by multi-attribute parameter joint interpretation technology to obtain geological attribute data corresponding to different geological structures in the target area. Based on the geological attribute data and the depth domain well-seismic comparison data, predict the depth information corresponding to different geological structures within the target area.

4. The method according to claim 3, characterized in that, Based on the geological attribute data and the depth-domain well-seismic comparison data, predict the depth information corresponding to different geological structures within the target area, including: A depth model corresponding to the target area is established based on the depth domain well-seismic comparison data, and an attribute model corresponding to the target area is established based on the geological attribute information. The depth model and the attribute model are integrated using a fusion algorithm to determine the mapping relationship between geological attributes and depth within the target area; Based on the mapping relationship, predict the depth information corresponding to different geological structures within the target area.

5. The method according to claim 1, characterized in that, Simulate the geological sequestration process of CO2 under different geological structures based on the depth information and the geological structure information, including: A three-dimensional geological model corresponding to the target area is constructed based on the depth information and the geological structure information. The physicochemical parameters of CO2 in the underground environment of the target area were determined based on the three-dimensional geological model. The equation of state is determined based on the physicochemical parameters and the phase changes of CO2, and the boundary conditions of the target region are determined, wherein the phase changes are the phase changes of CO2 under different temperatures and pressures; The state equation and the boundary conditions are input into the numerical simulation model so that the numerical simulation model can simulate the geological storage process of CO2 under different geological structures.

6. The method according to claim 1, characterized in that, Based on the depth information and the storage potential, target locations for carbon sequestration are determined within the target area, including: Based on the depth information, the sequestration potential, and the underground geophysical data, a multi-criteria decision analysis is performed on different geological structures in the target area, and based on the analysis results of the multi-criteria decision analysis, a first location within the target area where CO2 sequestration is permitted is determined; A risk assessment was conducted at the first location; If the risk assessment result of the first location is determined to be low risk, the first location will be designated as the target location.

7. A device for determining the location of carbon sequestration, characterized in that, include: The acquisition module is used to acquire underground geophysical data of the target area, wherein the underground geophysical data includes at least: geological structure information corresponding to the target area and seismic data corresponding to different geological structures of the target area; The analysis module is used to perform well-to-well comparison analysis on the underground geophysical data in order to predict the depth information corresponding to different geological structures in the target area; The simulation module is used to simulate the geological sequestration process of CO2 under different geological structures based on the depth information and the geological structure information, so as to determine the sequestration potential corresponding to different geological structures; the determination module is used to determine the target location for carbon sequestration in the target area based on the depth information and the sequestration potential.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 6.

9. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method of any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that, The computer program is executed by a processor using the steps of the method described in any one of claims 1 to 6.

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