A method for inverting the dynamic characteristics of seafloor sedimentary environments based on three-phase potential

Abstract

This application provides a method for inverting the dynamic changes of the seabed sedimentary environment based on three-phase potential, including in-situ data processing, electrical signal calibration, mathematical model establishment, and dynamic change analysis. By deploying a seabed electrode array, signals such as spontaneous potential, resistivity, and redox potential are acquired in real time. An inversion algorithm is used to deduce seabed sedimentary environment characteristics, such as seabed interface location, suspended particle concentration, sediment density, porosity, and water content. This method, combined with multi-frequency signal analysis, can monitor changes in the seabed sedimentary environment in real time and identify sediment movement. Compared with existing technologies such as CN118153411B and CN110411923B, this invention covers richer inversion content, and the complementarity of potential signals improves monitoring accuracy and efficiency, exhibiting stronger adaptability and reliability. This method has lower equipment and maintenance costs, is suitable for large-scale, long-term monitoring, and can provide innovative solutions in fields such as deep-sea monitoring, environmental assessment, and resource exploration.

Description

Technical Field

[0001] This application relates to the fields of seabed exploration technology and marine engineering geology technology, and more specifically, to a method for inverting the dynamic changes of seabed sedimentary environments based on three-phase potential. Background Technology

[0002] The development of seafloor mineral resources and the discharge of plumes have led to dynamic changes in the seafloor sedimentary environment. The seafloor sedimentary environment is a transitional zone between water and seafloor sediments; processes such as marine sediments and seawater flow in this layer have a significant impact on marine ecosystems, resource distribution, and the stability of engineering structures. However, traditional monitoring methods (such as acoustic, optical, and seismic detection) are often limited by signal attenuation and low resolution in turbid environments, especially in complex sedimentary structures where accurate data is difficult to obtain. In contrast, electrical detection methods (such as conductivity, resistivity, and natural electric field detection) can directly reflect changes in the electrical parameters of seafloor sediments and have strong penetrating power, enabling stable measurement results in high-turbidity and deep environments.

[0003] Currently, with the integrated development of ocean dynamics, sedimentology, and electromagnetic detection technologies, and the improvement of inversion algorithms (such as the introduction of machine learning and Kalman filtering), the application of electrical inversion in boundary layer monitoring has become more real-time and accurate. Therefore, inversion technology based on electrical methods for dynamic changes in the seabed sedimentary environment is becoming an important direction in the field of seabed environmental monitoring, promoting in-depth research on seabed sedimentary processes, material transport, and engineering geological conditions. However, current methods for inverting the seabed sedimentary environment based on electrical signals are limited by the uncertainties of multiple media. Single spontaneous potential signal processing cannot meet the needs of current inversion methods and cannot uniformly analyze seabed interface changes caused by mining disturbances. There is an urgent need for a unified method for inverting the seabed sedimentary environment, including suspended particulate matter concentration, seabed interface, and sediment properties. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, this application provides a method for inverting the dynamic changes of the seabed sedimentary environment based on three-phase potential.

[0005] The method for inverting the dynamic characteristics of the seafloor sedimentary environment based on three-phase potential provided in this application specifically includes:

[0006] Three-phase potential data acquisition and preprocessing, three-phase potential and suspended particle concentration data processing, interface processing, three-phase potential and sediment property processing;

[0007] Determination of seabed sedimentary environment data;

[0008] Finally, we need to achieve a dynamic description of the characteristics of the seabed sedimentary environment based on three-phase potential, and then implement real-time dynamic monitoring.

[0009] Optionally, the three-phase potential data acquisition and preprocessing mainly includes data acquisition and processing. Based on the natural potential difference, resistivity, and in-situ oxidation potential, the concentrations of seabed sediments, seabed interfaces, and suspended particulate matter are sequentially inverted and then processed as they change over time.

[0010] Data preprocessing involves using different value ranges for the features of the data. Therefore, it is necessary to preprocess the input data, process the data with a large value range, label each feature and perform further standardization processing, distinguish the data with large errors, and retain the data with good quality.

[0011] The dataset and measured data are analyzed and fitted, and further preprocessed using neural network learning, mainly by processing the three-phase potentials to make them conform to the in-situ monitoring.

[0012] Sedimentary environment dataset: First, establish an in-situ monitoring database dataset, including the acquisition of in-situ soil and water bodies in the deep sea, mainly including the concentration of suspended particulate matter in the water body, changes in the position of the seabed interface, and basic physical properties of seabed sediments, including basic parameters such as density, water content, and porosity.

[0013] Three-phase potential data calibration: Based on the obtained electrode parameters, the natural potential is first analyzed, and a system is established from the first electrode ring to the nth electrode ring (n≥30). The main electrode difference processing is performed to obtain the electrode difference value SPd between each electrode ring and the reference electrode. Each potential difference value represents the potential characteristic value relative to the reference electrode.

[0014]

[0015] In the formula, SPd is the potential difference, and X... i Xc represents the actual measured value, N represents the reference electrode value, and N represents the amplification of the electrode acquisition by a factor of n, which means reducing the original value by a factor of n to obtain the true potential difference value. This allows for the acquisition of the true potential difference value, making the monitoring differences in the in-situ process more obvious.

[0016] Submarine resistivity calibration: Based on the resistivity values ​​obtained from in-situ monitoring, interval division is performed to obtain the average apparent resistivity value that can represent a certain distance.

[0017]

[0018] In the formula, current I and voltage V, electrode constant K, are typically provided by the electrode manufacturer or obtained through calibration with a standard solution, ρ is the resistivity, and ε is the reference error resistivity. This formula allows for correction of resistivity values, especially relative to the initial resistivity value. Compared to traditional resistivity values, this formula incorporates error analysis, making the data more accurately reflect the true situation.

[0019] Processing of seabed redox potential: This is done based on the current temperature, as redox potential typically changes with temperature; temperature compensation is then performed.

[0020] ORP T =ORP T0 +α(T-T0)

[0021] ORP T This is the corrected redox potential; this is the corrected redox potential; ORP T0 It is the corrected redox potential; α is the temperature coefficient, which is usually a constant depending on the specific measurement system. It adds the calibration of the oxidation potential at the measured temperature and determines the in-situ oxidation potential at the stable monitoring temperature on the seabed.

[0022] Salinity has a relatively small impact on redox potential, but it still needs to be corrected in high-salinity water bodies. Salinity correction can be performed by consulting specific salinity-ORP relationships.

[0023] Optionally, three-phase potential and suspended particle concentration data processing: data calibration, firstly select monitoring data of the target area, and perform numerical fitting based on natural potential interpolation and suspended particle concentration. In the deep-sea mining process, the concentration of suspended particles in the plume changes significantly.

[0024] Processing of spontaneous potential: Dynamic indoor data changes in the seabed sedimentary environment were analyzed. Based on the observation that the maximum suspended sediment concentration in still water estuaries is 30 mg / L, the maximum concentration during tides can reach 8.69 g / L, and the maximum near-bottom concentration during typhoons can reach 14.2 g / L, with a 30-fold increase during storm surges, this experiment configured a suspended sediment solution with a concentration range of 0-20 g / L. The test range was 0-20 g / L, with an accuracy of 1 g / L, and correlations were established.

[0025] c=f(SP)S,t,DO,Z-1.82275e-8.75061

[0026] Where c is the suspended sediment concentration in g / L, SP is the spontaneous potential in mV (for a saturated calomel electrode), Z is the test water level in cm, S is the salinity, t is the temperature in °C, and DO is the dissolved oxygen in mg / L.

[0027] SPM = 0.00315 * RR% + 0.5146

[0028] SPM represents the mass of suspended sediments on the seabed, and RR measures the decrease in sediment resistivity, expressed as a percentage. Further analysis can be performed based on the decrease in resistivity to obtain a baseline resistivity value.

[0029] Then, indoor resistivity correction was performed.

[0030] c=-4.30948ln(ρ-0.28402 / 0.05594)S,t

[0031] Where c is the suspended sediment concentration in g / L, ρ is the resistivity in Ω·m, S is the salinity, and t is the temperature in ℃. Resistivity has a certain logarithmic relationship with the identification of suspended particle concentration.

[0032] The relationship between redox potential and suspended particulate matter concentration was analyzed using the mass of suspended sediments from the South China Sea. The analysis of the redox potential relationship in the sediments was as follows:

[0033] TOC = 8.147TN + 0.0192

[0034] ORP = -f(pH)a + b

[0035] pH=f(C TOC C TN )

[0036] C SPM =f(C DO C OM (ORP)

[0037] Among them, C SPM This indicates the concentration of suspended particulate matter and the concentration of dissolved oxygen (C). DO Organic matter concentration C OM ORP represents redox potential, TOC is total organic carbon in sediments, TN is total organic nitrogen, and there is a correlation between redox potential and total organic carbon and total organic nitrogen in sediments. a and b are correlation coefficients, pH is the pH value of the solution, and C... TOC C TN The formula, compared to traditional laboratory experiments, indicates that the redox potential is mainly influenced by the sediment, and that there is a negative proportional relationship between the redox potential and the solution pH. This yields a nonlinear relationship between the redox potential and the solution, and can be analyzed based on specific laboratory experiments, especially for calibration of organic matter concentration.

[0038] Optionally, the three-phase potential and sediment property parameter data are processed to establish a mathematical relationship between sediment density, water content, porosity and spontaneous potential. The density of sediment is usually determined by the relative proportion of solid particles and pore water.

[0039] Spontaneous potential can be expressed by the following formula:

[0040]

[0041] Where, ρ s It is the density of solid particles, ρ w It is the density of pore water. It refers to porosity. It is primarily determined based on the pore water content in sediments.

[0042] Moisture content is

[0043]

[0044] Porosity is

[0045]

[0046] Among them, V w It is the density of solid particles, V p V is the density of solid particles, and V is the total volume. Compared to pore water between sediments, this method focuses more on the in-situ sediment pore density within the seabed sediment environment compared to traditional calculation methods.

[0047] Mathematical models can be established using sediment density, water content, and porosity:

[0048]

[0049] Resistivity can be used to establish mathematical models with sediment porosity and water content:

[0050]

[0051] R is the resistivity of the sediment (Ω·m), R W It is the resistivity of water (Ω·m). It refers to the porosity of sediments. It is the porosity of saturated water;

[0052]

[0053] R is the resistivity of the sediment (Ω·m), R0 is the resistivity of the dry sediment (Ω·m), ρ min The density of sediment minerals (2.5-3.0 g / cm³) 3 ), ρ bulk The total density of sediments (g / cm³) 3);

[0054] The following model can comprehensively consider the combined effects of porosity, water content, and density on resistivity. Compared with previous indoor test data, it can be used to perform sediment property and resistivity fitting calibration for clay properties in seabed mining areas:

[0055] R = 9.651ω -0.5711

[0056]

[0057] ρ=0.31R 2 +1.96R +1.50

[0058]

[0059] The above formula defines the laws governing the resistivity, density, water content, and porosity of seabed clay. Compared with existing patents, this formula more clearly indicates the influencing factors and is more consistent with the in-situ monitoring environment.

[0060] Redox potential (RPP) is a measure of the combined effects of porosity, water content, and density on resistivity. ρ represents the compactness of the sediment, typically related to the content of organic matter and minerals, as well as the degree of sediment compaction. Higher density may lead to lower porosity, thus affecting the diffusion rate of oxygen and other oxidants. Therefore, higher sediment density often corresponds to a lower RRP, especially under anaerobic conditions.

[0061] ORP = ab·ρ

[0062] a and b are empirical constants, and their specific values ​​depend on the environment and sediment type.

[0063] Water content (W) directly affects the availability and diffusion rate of oxygen in sediments. Higher water content generally indicates lower oxygen content, especially in anaerobic environments. Therefore, ORP tends to decrease with increasing water content. A common empirical formula is:

[0064] ORP = cd·W

[0065] This indicates the proportion of void volume to total volume in sediments. High porosity generally means faster oxygen diffusion and a higher ORP. Low porosity makes it difficult for oxygen to enter, resulting in a lower ORP and a tendency to create a reducing environment.

[0066]

[0067] Finally, the comprehensive model:

[0068]

[0069] Redox potential is related to sediment density, water content, and porosity, but the specific mathematical relationship is greatly affected by environmental and experimental conditions. This formula is more accurate than previous indoor test calibrations, more suitable for indoor tests and in-situ monitoring, and covers a more comprehensive range.

[0070] Optionally, the determination of seafloor sedimentary environment data involves identifying the dynamic characteristics of seafloor sedimentary environment changes based on known monitoring data.

[0071] The first step is to determine the interface location. This can be achieved by preprocessing the three-phase potential (spontaneous potential, resistivity, and redox potential) data. Based on the traditional variable point method model, an electrode direction determination can be added to determine the interface location. The spontaneous potential data is denoted as F(t, j). Assuming that at a certain time t, for the data F(t, j), the vertical distribution data of the three-phase potential F(t, j) is divided into two parts by the seabed interface location m.

[0072]

[0073] Where, β i The errors are independent random errors with an expected value of 0 and a common variance σ², where 0 < σ² < ∞. Here, m, α₁, α₂, and σ² are unknown. Corresponding to the resistivity observation process near the seabed interface, α₁ is the natural potential difference of the sediment, α₂ is the natural potential difference of the seawater, n is the total number of natural potential electrodes, and m is the location of the abrupt change in the natural potential difference. The mean change at position j is...

[0074]

[0075] Where d+1≤j≤n-d+1, obviously, when j is in the seawater layer or sediment layer, since the potential difference of spontaneous potential is similar, G j The potential difference between seawater and sediment is relatively small or even tends to be 0; when j is in the transition zone, especially at the seabed, the difference in spontaneous potential between seawater and sediment will be G. j Larger, therefore,

[0076] |G m |=max|G j |=γ

[0077] At this point, m is the mutation point, i.e., the location of the seabed interface, and γ is the test level. The critical value E can be taken empirically, when |G m If |>E, the change point exists; otherwise, it is assumed that all the spontaneous potential electrodes are in seawater or sediment (depending on the expected value of the spontaneous potential difference).

[0078] Secondly, the concentration of suspended particulate matter is determined based on in-situ monitoring data.

[0079] Spontaneous potential: After filtering the three-phase potential interpolation from top to bottom and removing half of the duplicate values, the spontaneous potential inversion model shows a strong correlation with suspended sediment concentration, and both conform to the Gaussian Amp function model. Based on this, an empirical formula can be derived:

[0080]

[0081] Where x represents the potential difference at the reference electrode, in mV, y represents the concentration of suspended particulate matter, in g / L, and y0, A, x c Both ω and ω are variables that are described based on the range of potential difference. They can be assigned values ​​in intervals. Based on long-term monitoring data of natural potential, the concentration of suspended particulate matter can be determined and identified, and the entire suspended sediment concentration profile structure can be obtained.

[0082] Resistivity inversion:

[0083] c=-4.30948ln(ρ-0.28402 / 0.05594)S,t

[0084] Redox potential inversion:

[0085] TOC = 8.147TN + 0.0192

[0086] ORP = -f(pH)a + b

[0087] pH=f(C TOC C TN )

[0088] C SPM =f(C DO C OM (ORP)

[0089] Based on the sediment type, the most suitable method for retrieving suspended particulate matter concentration is selected after in-situ test data and sediment property calibration.

[0090] Finally, the basic properties of the sediments were analyzed, and a multiple regression model was established based on the previously correlated data:

[0091]

[0092] Where a is a constant term, b1, b2, and b3 are coefficients to be determined, and ε is an error term.

[0093] Modeling of spontaneous potential difference:

[0094]

[0095] Inversion equations:

[0096]

[0097] Optimization algorithms (such as least squares or other optimization techniques) are used to solve these equations to determine the unknown sediment density, water content, and porosity. Combining the above equations, the final model can be expressed as follows:

[0098]

[0099] Resistivity inversion of sediment relationships: The resistivity relationship between density, water content, and porosity is indirect. It can be comprehensively represented by combining various models and considering the interaction of these factors. Resistivity can be mathematically modeled with sediment porosity and water content.

[0100]

[0101] The relationship between redox potential and sediments: Redox potential is related to sediment density, water content, and porosity, but the specific mathematical relationship is greatly affected by environmental and experimental conditions. This formula is more accurate than previous indoor experimental calibrations, more suitable for indoor experiments and in-situ monitoring, and covers a more comprehensive range.

[0102] ORP = ab·ρ

[0103] ORP = cd·W

[0104]

[0105] Based on the three-phase potential values, the advantages of the three-phase potential are first analyzed. The interface is determined based on the spontaneous potential and redox potential. The concentration of suspended particulate matter is determined based on the spontaneous potential and resistivity. The properties of sediments are then inverted based on the spontaneous potential and resistivity. First, the seabed water-soil interface is determined. Then, the concentration of suspended particulate matter can be obtained. Finally, the properties of sediments can be obtained, revealing the main effects of dynamic changes in the seabed interface from top to bottom.

[0106] Optionally, the implementation method includes:

[0107] (1) Electrical signals such as natural potential, resistivity, and redox potential are collected in real time by an electrode array deployed on the seabed.

[0108] (2) The above inversion algorithm is used to process the electrical signal, and the seabed interface of the sedimentary environment is derived. The seabed interface is determined based on the combination of three potentials.

[0109] (3) Based on the location of the seabed interface, the concentration of suspended particulate matter in the sedimentary environment above the seabed interface is determined by combining spontaneous potential, resistivity and redox potential.

[0110] (4) Below the seabed interface, physical parameters of the seabed sedimentary environment, such as sediment density, porosity, and water content, are derived based on the three-phase potential.

[0111] (5) Combine three-phase potential noise reduction filtering and other multi-frequency signal analysis methods to improve the resolution and accuracy of inversion.

[0112] (6) Dynamic monitoring: Based on changes in electrical signals, monitor the dynamic changes in the seabed sedimentary environment in real time and identify environmental changes, sediment movement, etc.

[0113] Because this application adopts the above technical solution, it has the following beneficial effects compared with the prior art:

[0114] 1. This application provides higher spatial and temporal resolution. Compared with the prior art, CN118153411B, "A Deep Learning-Based Electrical Monitoring and Inversion Method for Deep-Sea Mining Plume Concentration Profiles," the inversion method proposed in this patent covers the concentration of suspended particulate matter on the seabed, seabed interface changes, and the physical and mechanical properties of seabed sediments. Its content is richer and more advanced, and it inverts more data information in one interpretation method. The potential is not only taken from the natural potential, but also resistivity and redox potential are added. The three-phase potentials complement and correct each other, resulting in higher monitoring accuracy, richer inversion content, higher efficiency, and the ability to monitor and warn. The prior art, CN118425241A, "A Method for Electrical Testing of Seawater Suspended Particulate Matter Concentration," is not only applicable to seawater, but also to sea surface and seabed sediments, which is more advanced than the existing technology.

[0115] 2. This application presents a method for inverting the dynamic changes of the seabed sedimentary environment under the influence of deep-sea mining. It can simultaneously invert multiple physical parameters (such as density, porosity, and water content), providing more comprehensive seabed environmental information and enhancing the understanding of the seabed sedimentary environment. It is applicable to complex marine environments, including different sediment types and hydrological conditions, and exhibits good adaptability and reliability. Compared to traditional monitoring methods (such as sonar and sampling), this method has lower equipment and maintenance costs, making it suitable for large-scale, long-term monitoring. Compared to the prior art document CN110411923B – In-situ Real-time Monitoring Device and Method for Seabed Sedimentary Environment Based on Spontaneous Potential Measurement – ​​this method not only focuses on the design of in-situ devices but also provides monitoring and early warning capabilities. It incorporates a more complex, convenient, and effective interpretation algorithm, making it more advanced than existing technologies.

[0116] 3. This application is rationally designed, enabling data integration and intelligent analysis: by combining machine learning and data mining techniques, the collected data can be intelligently analyzed to automatically identify potential dynamic change patterns, providing decision support for environmental management and scientific research. The electrical-based inversion method for dynamic changes in the seabed sedimentary environment has significant advantages, providing innovative solutions in deep-sea monitoring, environmental assessment, and resource exploration. Its high precision, real-time performance, and non-invasive nature effectively supplement and enhance the performance of existing monitoring technologies.

[0117] Additional aspects and advantages of this application will become apparent in the following description or may be learned by practice of this application. Attached Figure Description

[0118] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0119] Figure 1 The data processing flow for the inversion method of dynamic change characteristics of seafloor sedimentary environment based on three-phase potential provided in this application Figure 1 ;

[0120] Figure 2 The data processing flow for the inversion method of dynamic change characteristics of seafloor sedimentary environment based on three-phase potential provided in this application Figure 2 ;

[0121] Figure 3 A diagram illustrating the seabed interface identification effect of the three-phase potential-based inversion method for retrieving dynamic changes in the seabed sedimentary environment provided in this application.

[0122] Figure 4 The inversion effect of suspended particulate matter for implementing the three-phase potential-based inversion method for dynamic changes in the seabed sedimentary environment provided in this application;

[0123] Figure 5 A diagram illustrating the sediment property identification effect of the three-phase potential-based inversion method for dynamic changes in the seafloor sedimentary environment provided in this application.

[0124] Figure 6 The flowchart illustrates the implementation of the method for inverting the dynamic changes of the seafloor sedimentary environment based on three-phase potential, as provided in this application. Detailed Implementation

[0125] To better understand the above-mentioned objectives, features, and advantages of this application, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0126] Many specific details are set forth in the following description in order to provide a full understanding of this application. However, this application may also be implemented in other ways different from those described herein. Therefore, the scope of protection of this application is not limited to the specific embodiments disclosed below.

[0127] The following is combined Figures 1 to 5 This application provides a detailed description of a method for inverting the dynamic changes of the seafloor sedimentary environment based on three-phase potential.

[0128] Combination Figure 1-2 The dynamic variation characteristics of the seafloor sedimentary environment based on three-phase potential provided in this application

[0129] Inversion methods specifically include:

[0130] S1, three-phase potential data acquisition and preprocessing, three-phase potential and suspended particle concentration data processing, interface processing, three-phase potential and sediment property processing;

[0131] S2, Determination of seabed sedimentary environment data;

[0132] S3. Finally, it is necessary to realize the dynamic description of the characteristics of the seabed sedimentary environment based on three-phase potential, and then implement real-time dynamic monitoring.

[0133] like Figure 1 , Figure 2 As shown, the three-phase potential data acquisition and preprocessing of long-term in-situ monitoring data of the seabed sedimentary environment involves processing spontaneous potential, resistivity, and redox potential, followed by processing of seabed interface, suspended solids concentration, sediment density, water content, and porosity data. Furthermore, a relationship is established between spontaneous potential, resistivity, redox potential, and sediment interface. Figure 1 S1 section;

[0134] Relationships were established between spontaneous potential, resistivity, redox potential, and suspended matter concentration; relationships were also established between spontaneous potential, resistivity, redox potential, and sediment density, water content, and porosity; by processing spontaneous potential, resistivity, and redox potential, sediment interface, suspended matter concentration, and sediment properties were retrieved, corresponding to... Figure 1 Part S2;

[0135] Finally, a model was established based on the three-phase potential and the changing characteristics of the seabed sedimentary environment; the dynamic changes in the seabed sedimentary environment caused by mining disturbances were elucidated. Figure 1 S3 section;

[0136] Three-phase potential data acquisition and preprocessing of long-term in-situ monitoring data of the seabed sedimentary environment: processing of spontaneous potential, resistivity, and redox potential, followed by processing of seabed interface, suspended matter concentration, sediment density, water content, and porosity data. These data are preprocessed.

[0137] Data preprocessing involves using different value ranges for the features of the data. Therefore, it is necessary to preprocess the input data, process the data with a large value range, label each feature and perform further standardization processing, distinguish the data with large errors, and retain the data with good quality.

[0138] The dataset and measured data are analyzed and fitted, and further preprocessed using neural network learning, mainly by processing the three-phase potentials to make them conform to the in-situ monitoring.

[0139] Sedimentary environment dataset: First, establish an in-situ monitoring database dataset, including the acquisition of in-situ soil and water bodies in the deep sea, mainly including the concentration of suspended particulate matter in the water body, changes in the position of the seabed interface, and basic physical properties of seabed sediments, including basic parameters such as density, water content, and porosity.

[0140] Three-phase potential data calibration: Based on the obtained electrode parameters, the natural potential is first analyzed, and a system is established from the first electrode ring to the nth electrode ring (n≥30). The main electrode difference processing is performed to obtain the electrode difference value SPd between each electrode ring and the reference electrode. Each potential difference value represents the potential characteristic value relative to the reference electrode.

[0141]

[0142] In the formula, SPd is the potential difference, and X... i Xc represents the actual measured value, N represents the reference electrode value, and N represents the amplification of the electrode acquisition by a factor of n, which means reducing the original value by a factor of n to obtain the true potential difference value. This allows for the acquisition of the true potential difference value, making the monitoring differences in the in-situ process more obvious.

[0143] Submarine resistivity calibration: Based on the resistivity values ​​obtained from in-situ monitoring, interval division is performed to obtain the average apparent resistivity value that can represent a certain distance.

[0144]

[0145] In the formula, current I and voltage V, electrode constant K, are typically provided by the electrode manufacturer or obtained through calibration with a standard solution, ρ is the resistivity, and ε is the reference error resistivity. This formula allows for correction of resistivity values, especially relative to the initial resistivity value. Compared to traditional resistivity values, this formula incorporates error analysis, making the data more accurately reflect the true situation.

[0146] Processing of seabed redox potential: This is done based on the current temperature, as redox potential typically changes with temperature; temperature compensation is then performed.

[0147] ORP T =ORP T0 +α(T-T0)

[0148] ORP T This is the corrected redox potential; this is the corrected redox potential; ORP T0 It is the corrected redox potential; α is the temperature coefficient, which is usually a constant depending on the specific measurement system. It adds the calibration of the oxidation potential at the measured temperature and determines the in-situ oxidation potential at the stable monitoring temperature on the seabed.

[0149] Salinity has a relatively small impact on redox potential, but it still needs to be corrected in high-salinity water bodies. Salinity correction can be performed by consulting specific salinity-ORP relationships.

[0150] Relationships between spontaneous potential, resistivity, redox potential, and sediment interfaces:

[0151] Combination Figure 2 As shown, the sediment interface property determination method of this application can preprocess the three-phase potential data. Based on the traditional variable point method model, an electrode determination direction is added to determine the interface position. The spontaneous potential data is denoted as F(t,j). It is assumed that at a certain time t, for the data F(t,j), the vertical distribution data of spontaneous potential F(t,j) is divided into two parts with the seabed interface position m.

[0152]

[0153] Where, β i The errors are independent random errors with an expected value of 0 and a common variance σ², where 0 < σ² < ∞. Here, m, α₁, α₂, and σ² are unknown. Corresponding to the resistivity observation process near the seabed interface, α₁ is the natural potential difference of the sediment, α₂ is the natural potential difference of the seawater, n is the total number of natural potential electrodes, and m is the location of the abrupt change in the natural potential difference. The mean change at position j is...

[0154]

[0155] Where d+1≤j≤n-d+1, obviously, when j is in the seawater layer or sediment layer, since the potential difference of spontaneous potential is similar, G j The potential difference between seawater and sediment is relatively small or even tends to be 0; when j is in the transition zone, especially at the seabed, the difference in spontaneous potential between seawater and sediment will be G. j Larger, therefore,

[0156] |G m |=max|G j |=γ

[0157] At this point, m is the mutation point, i.e., the location of the seabed interface, and γ is the test level. The critical value E can be taken empirically, when |G m If |>E, the change point exists; otherwise, it is assumed that all the spontaneous potential electrodes are in seawater or sediment (depending on the expected value of the spontaneous potential difference).

[0158] Relationships were established between spontaneous potential, resistivity, redox potential, and suspended particulate matter concentration:

[0159] Three-phase potential and suspended particle concentration data processing: Data calibration. First, the monitoring data of the target area is selected, and numerical fitting is performed based on the natural potential interpolation and suspended particle concentration. In the deep-sea mining process, the concentration of suspended particles in the plume changes significantly.

[0160] Processing of spontaneous potential: Dynamic indoor data changes in the seabed sedimentary environment were analyzed. Based on the observation that the maximum suspended sediment concentration in still water estuaries is 30 mg / L, the maximum concentration during tides can reach 8.69 g / L, and the maximum near-bottom concentration during typhoons can reach 14.2 g / L, with a 30-fold increase during storm surges, this experiment configured a suspended sediment solution with a concentration range of 0-20 g / L. The test range was 0-20 g / L, with an accuracy of 1 g / L, and correlations were established.

[0161] c=f(SP)S,t,DO,Z-1.82275e-8.75061

[0162] Where c is the suspended sediment concentration in g / L, SP is the spontaneous potential in mV (for a saturated calomel electrode), Z is the test water level in cm, S is the salinity, t is the temperature in °C, and DO is the dissolved oxygen in mg / L.

[0163] SPM = 0.00315 * RR% + 0.5146

[0164] SPM represents the mass of suspended sediment on the seabed, and RR measures the decrease in sediment resistivity, expressed as a percentage (%). Further analysis can be performed based on this decrease in resistivity to derive a baseline resistivity value.

[0165] Then, indoor resistivity correction was performed.

[0166] c=-4.30948ln(ρ-0.28402 / 0.05594)S,t

[0167] Where c is the suspended sediment concentration in g / L, ρ is the resistivity in Ω·m, S is the salinity, and t is the temperature in ℃. Resistivity has a certain logarithmic relationship with the identification of suspended particle concentration.

[0168] The relationship between redox potential and suspended particulate matter concentration was analyzed using the mass of suspended sediments from the South China Sea. The analysis of the redox potential relationship in the sediments was as follows:

[0169] TOC = 8.147TN + 0.0192

[0170] ORP = -f(pH)a + b

[0171] pH=f(C TOC C TN )

[0172] C SPM =f(C DO C OM (ORP)

[0173] Among them, C SPM This indicates the concentration of suspended particulate matter and the concentration of dissolved oxygen (C). DO Organic matter concentration C OM ORP represents redox potential, TOC is total organic carbon in sediments, TN is total organic nitrogen, and there is a correlation between redox potential and total organic carbon and total organic nitrogen in sediments. a and b are correlation coefficients, pH is the pH value of the solution, and C... TOC C TN The formula, compared to traditional laboratory experiments, indicates that the redox potential is mainly influenced by the sediment, and that there is a negative proportional relationship between the redox potential and the solution pH. This yields a nonlinear relationship between the redox potential and the solution, and can be analyzed based on specific laboratory experiments, especially for calibration of organic matter concentration.

[0174] Relationships were established between spontaneous potential, resistivity, redox potential, and sediment density, water content, and porosity:

[0175] Three-phase potential and sediment property parameter data processing establish mathematical relationships between sediment density, water content, porosity and spontaneous potential. Sediment density is usually determined by the relative proportion of solid particles and pore water.

[0176] Spontaneous potential can be expressed by the following formula:

[0177]

[0178] Where, ρ s It is the density of solid particles, ρ w It is the density of pore water. It refers to porosity. It is primarily determined based on the pore water content in sediments.

[0179] Moisture content is

[0180]

[0181] Porosity is

[0182]

[0183] Among them, V w It is the density of solid particles, V p V is the density of solid particles, and V is the total volume. Compared to pore water between sediments, this method focuses more on the in-situ sediment pore density within the seabed sediment environment compared to traditional calculation methods.

[0184] Mathematical models can be established using sediment density, water content, and porosity:

[0185]

[0186] Resistivity can be used to establish mathematical models with sediment porosity and water content:

[0187]

[0188] R is the resistivity of the sediment (Ω·m), R W It is the resistivity of water (Ω·m). It refers to the porosity of sediments. It is the porosity of saturated water;

[0189]

[0190] R is the resistivity of the sediment (Ω·m), R0 is the resistivity of the dry sediment (Ω·m), ρ min The density of sediment minerals (2.5-3.0 g / cm³) 3 ), ρ bulk The total density of sediments (g / cm³) 3 );

[0191] The following model can comprehensively consider the combined effects of porosity, water content, and density on resistivity. Compared with previous indoor test data, it can be used to perform sediment property and resistivity fitting calibration for clay properties in seabed mining areas:

[0192] R = 9.651ω -0.5711

[0193]

[0194] ρ=0.31R 2 +1.96R +1.50

[0195]

[0196] The above formula defines the laws governing the resistivity, density, water content, and porosity of seabed clay. Compared with existing patents, this formula more clearly indicates the influencing factors and is more consistent with the in-situ monitoring environment.

[0197] Redox potential (RPP) is a measure of the combined effects of porosity, water content, and density on resistivity. ρ represents the compactness of the sediment, typically related to the content of organic matter and minerals, as well as the degree of sediment compaction. Higher density may lead to lower porosity, thus affecting the diffusion rate of oxygen and other oxidants. Therefore, higher sediment density often corresponds to a lower RRP, especially under anaerobic conditions.

[0198] ORP = ab·ρ

[0199] a and b are empirical constants, and their specific values ​​depend on the environment and sediment type.

[0200] Water content (W) directly affects the availability and diffusion rate of oxygen in sediments. Higher water content generally indicates lower oxygen content, especially in anaerobic environments. Therefore, ORP tends to decrease with increasing water content. A common empirical formula is:

[0201] ORP = cd·W

[0202] This indicates the proportion of void volume to total volume in sediments. High porosity generally means faster oxygen diffusion and a higher ORP. Low porosity makes it difficult for oxygen to enter, resulting in a lower ORP and a tendency to create a reducing environment.

[0203]

[0204] Finally, the comprehensive model:

[0205]

[0206] Redox potential is related to sediment density, water content, and porosity, but the specific mathematical relationship is greatly affected by environmental and experimental conditions. This formula is more accurate than previous indoor test calibrations, more suitable for indoor tests and in-situ monitoring, and covers a more comprehensive range.

[0207] Finally, by processing the spontaneous potential, resistivity, and redox potential, the sediment interface, suspended matter concentration, and sediment properties are inverted to further elucidate the dynamic changes in the seabed sedimentary environment caused by mining disturbances and establish a three-phase potential and seabed sedimentary environment change characteristic model.

[0208] Figure 3The diagram shows the effect of using the above formula criteria. The horizontal axis represents the potential difference of the natural potential, and the vertical axis represents the observation electrode ring number. It can be clearly seen from the figure that there is a sudden change in the potential difference at the sediment-water interface from +20mV to -60mV. The difference at the sediment-water interface is huge. Above the interface is water, and below is sediment.

[0209] Combination Figure 4 As shown, correlation analysis was performed between seawater suspended particle concentration and resistivity, including sand and clay; regression analysis was performed between spontaneous potential and seawater suspended particle concentration, including sand and clay; and regression analysis was performed between redox potential and seawater suspended particle concentration, including sand and clay.

[0210] This application requires filtering of three-phase potential interpolation from top to bottom. After filtering out half of the duplicate values, the spontaneous potential inversion model has a strong correlation with the suspended sediment concentration, and both conform to the Gaussian Amp function model. Based on this, an empirical formula can be derived:

[0211]

[0212] Where x represents the potential difference at the reference electrode, in mV, y represents the concentration of suspended particulate matter, in g / L, and y0, A, x c Both ω and ω are variables that are described based on the range of potential difference. They can be assigned values ​​in intervals. Based on long-term monitoring data of natural potential, the concentration of suspended particulate matter can be determined and identified, and the entire suspended sediment concentration profile structure can be obtained.

[0213] Resistivity inversion:

[0214] c=-4.30948ln(ρ-0.28402 / 0.05594)S,t

[0215] Redox potential inversion:

[0216] TOC = 8.147TN + 0.0192

[0217] ORP = -f(pH)a + b

[0218] pH=f(C TOC C TN )

[0219] C SPM =f(C DO C OM (ORP)

[0220] Based on the sediment type, the most suitable method for retrieving suspended particulate matter concentration is selected after in-situ test data and sediment property calibration.

[0221] Figure 4 The analysis is based on the above formula. All six graphs show the concentration of suspended particulate matter in seawater on the horizontal axis and the values ​​of the three-phase points on the vertical axis, thus establishing a correlation analysis. 'a' and 'd' represent the correlation analysis between the concentration of suspended particulate matter in seawater and resistivity, including sand and clay. 'b' and 'e' represent the regression analysis between spontaneous potential and the concentration of suspended particulate matter in seawater, including sand and clay. 'c' and 'f' represent the regression analysis between redox potential and the concentration of suspended particulate matter in seawater, including sand and clay.

[0222] Combination Figure 5 , Figure 6 This application also requires analysis of the basic properties of the sediments. Figure 5 The main focus was on the schematic diagram showing the correlation between resistivity and sediment density, porosity, and water content in the three-phase potential.

[0223] Figure 5 Resistivity is selected as the pivot, with the horizontal axis representing resistivity values ​​and the vertical axis representing sediment density, porosity, and water content. Based on the previously correlated data, a multiple regression model is then established.

[0224]

[0225] Where a is a constant term, b1, b2, and b3 are coefficients to be determined, and ε is an error term.

[0226] Modeling of spontaneous potential difference:

[0227]

[0228] Inversion equations:

[0229]

[0230] Optimization algorithms (such as least squares or other optimization techniques) are used to solve these equations to determine the unknown sediment density, water content, and porosity. Combining the above equations, the final model can be expressed as follows:

[0231]

[0232] Resistivity inversion of sediment relationships: The resistivity relationship between density, water content, and porosity is indirect. It can be comprehensively represented by combining various models and considering the interaction of these factors. Resistivity can be mathematically modeled with sediment porosity and water content.

[0233]

[0234] The relationship between redox potential and sediments: Redox potential is related to sediment density, water content, and porosity, but the specific mathematical relationship is greatly affected by environmental and experimental conditions. This formula is more accurate than previous indoor experimental calibrations, more suitable for indoor experiments and in-situ monitoring, and covers a more comprehensive range.

[0235] ORP = ab·ρ

[0236] ORP = cd·W

[0237]

[0238] Combination Figure 6 As shown, the application of the method of this application also includes:

[0239] (1) Deployment of electrode arrays. Electrode arrays deployed on the seabed are used to collect electrical signals such as natural potential, resistivity, and redox potential in real time.

[0240] (2) Inversion of electrical signals. The electrical signals are processed using the above inversion algorithm to deduce the seabed interface of the sedimentary environment, and the seabed interface is determined based on the combined potential of the three types of potentials;

[0241] The concentration of suspended particulate matter in the sedimentary environment is determined by combining the seabed interface of the sedimentary environment with spontaneous potential, resistivity, and redox potential.

[0242] Below the seabed interface, physical parameters of the seafloor sedimentary environment, such as sediment density, porosity, and water content, are derived based on the three-phase potential. The above two steps correspond to... Figure 1 S1 in the middle.

[0243] (3) Multi-frequency signal analysis. Combining three-phase potential noise reduction and filtering with multi-frequency signal analysis improves the resolution and accuracy of the inversion. Figure 1 S2 in the middle.

[0244] (4) Dynamic monitoring and identification: Based on changes in electrical signals, the dynamic characteristics of the seabed sedimentary environment are monitored in real time to identify environmental changes and sediment movement. Figure 1 S3 in the middle.

[0245] Figure 5 Using resistivity as the pivot, with the horizontal axis representing resistivity values ​​and the vertical axis representing sediment density, porosity, and water content, a relevant model is established. Figure 6 It is a fairly detailed overall rendering. Figure 6 Data judgment and model building correspondence Figure 1 S1 in the equation corresponds to the inversion law. Figure 1 S2 in the context refers to the application implementation. Figure 1 S3 in the middle.

[0246] In the description of this application, the term "multiple" refers to two or more. Unless otherwise expressly defined, the terms "upper," "lower," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. The terms "connection," "installation," "fixing," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific circumstances.

[0247] In the description of this specification, the terms "one embodiment," "some embodiments," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0248] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for inverting the dynamic changes of seafloor sedimentary environments based on three-phase potential, characterized in that, include: Three-phase potential data acquisition and preprocessing, three-phase potential and suspended particle concentration data processing, interface processing, three-phase potential and sediment property processing; Determination of seabed sedimentary environment data; Finally, we need to achieve a dynamic description of the characteristics of the seabed sedimentary environment based on three-phase potential, and then implement real-time dynamic monitoring. Determining seafloor sedimentary environment data includes: determining the dynamic characteristics of seafloor sedimentary environment changes based on known monitoring data. First, interface location is determined. The natural potential, resistivity, and redox potential data are preprocessed. Based on the traditional variable point method model, an electrode direction determination is added to determine the interface location. The natural potential data is set as follows: Assuming at a certain moment For data The vertical distribution data of the three-phase potentials were obtained by using the seabed interface position m. Divided into two parts; ; in, The errors are independent random errors with an expected value of 0 and a common variance. Here, m, α1, α2, and σ2 are unknown; corresponding to the resistivity observation process near the seabed interface, α1 is the natural potential difference of the sediment, and α2 is the natural potential difference of the seawater. This represents the total number of electrodes at their natural potential. The location of the abrupt change in the potential difference of the natural potential, in The mean change in position is ; in, Obviously, when When in the seawater layer or sediment layer, the potential difference is similar. It is relatively small or even tends to 0; when When located in the transition zone, at the seabed position, the difference in natural potential between seawater and sediments will... Larger, therefore, ; At this time The point of sudden change, i.e., the location of the seabed interface. To test the level, a critical value can be taken based on experience. If the point of change exists, then it is assumed that the spontaneous potential electrodes are all located in seawater or sediment. Secondly, the concentration of suspended particulate matter is determined based on in-situ monitoring data. Spontaneous potential: After filtering the three-phase potential interpolation from top to bottom and removing half of the duplicate values, the spontaneous potential inversion model shows a strong correlation with suspended sediment concentration, and both conform to the Gaussian Amp function model. Based on this, an empirical formula can be derived: ; in, This represents the potential difference at the reference electrode, in units of... , Represents the concentration of suspended particulate matter, in g / L, y0, A, x c , ω These are all quantities of change described based on the range of potential difference. Values ​​can be assigned to intervals. Based on long-term monitoring data of natural potential, the concentration of suspended particulate matter can be determined and identified, thus obtaining the overall suspended sediment concentration profile structure. Resistivity inversion: ; Redox potential inversion: ; ; ; ; Based on the sediment type, and after in-situ experimental data and sediment property calibration, the most suitable method for retrieving suspended particulate matter concentration is selected. Finally, the basic properties of the sediments were analyzed, and a multiple regression model was established based on the previously correlated data: ; in, a It is a constant term. b 1. b 2. b 3 is the coefficient to be determined. It is an error term; Modeling of spontaneous potential difference: ; ; ; Inversion equations: ; ; ; Optimization algorithms are used to solve these equations, determining the unknown sediment density, water content, and porosity. Combining these equations, the final model is expressed as: ; ; ; The relationship between redox potential and sediments: Redox potential is related to sediment density, water content, and porosity, but the specific mathematical relationship is greatly affected by environmental and experimental conditions. This formula is more accurate than the previous indoor test calibration, more suitable for indoor tests and in-situ monitoring, and has a more comprehensive coverage. ; ; ; 。 2. The method for inverting the dynamic changes of the seafloor sedimentary environment based on three-phase potential according to claim 1, characterized in that, The three-phase potential data acquisition and preprocessing includes: data acquisition and processing, based on the natural potential difference, resistivity, and in-situ oxidation potential, sequentially retrieving the concentrations of seabed sediments, seabed interfaces, and suspended particulate matter, and then processing them over time; data preprocessing, using different value ranges for data features, therefore requiring preprocessing of the input data, labeling each feature and further standardizing it, distinguishing data with large errors, retaining high-quality data, analyzing and fitting the dataset and measured data, and further preprocessing using neural network learning, mainly processing the three-phase potential to make it conform to the correspondence with in-situ monitoring; Sedimentary environment dataset: First, establish an in-situ monitoring database dataset, including the acquisition of in-situ soil and water bodies in the deep sea, mainly including the concentration of suspended particulate matter in the water body, changes in the position of the seabed interface, and the basic physical properties of seabed sediments, including basic parameters such as density, water content, and porosity. Three-phase potential data calibration: Natural potential processing Based on the obtained electrode parameters, the natural potential is first analyzed, and a system is established from the first electrode ring to the nth electrode ring, n≥30. The main electrode difference processing is performed to obtain the electrode difference value SPd between each electrode ring and the reference electrode. Each potential difference value represents the potential characteristic value relative to the reference electrode. ； In the formula, SPd represents the potential difference. These are actual measured values. The reference electrode value, Amplification for electrode acquisition A multiple, meaning reducing the original value. This allows us to obtain the true potential difference value, making the monitoring differences in in-situ processes more obvious. Seabed resistivity calibration: Based on the resistivity values ​​obtained from in-situ monitoring, interval division is performed to obtain the average apparent resistivity value representing a certain distance. ； In the formula, current and voltage Electrode constant Provided by the electrode manufacturer or obtained through calibration with standard solutions. resistivity Reference error resistivity; This formula allows for the correction of resistivity values. Compared to traditional resistivity values, this formula incorporates error analysis, making the data more accurately reflect the true state of the seabed redox potential. The processing of the redox potential is based on the prevailing temperature, as the redox potential changes with temperature; temperature compensation is then applied. ; ORP T This is the corrected redox potential; this is the corrected redox potential; ORP T0 This is the corrected redox potential; α It is a temperature coefficient, which depends on the specific measurement system. It adds the calibration of oxidation potential at the measured temperature and measures the in-situ oxidation potential at the stable monitoring temperature on the seabed. Salinity has a relatively small effect on oxidation-reduction potential, but it also needs to be corrected in high salinity waters. Salinity correction is done by consulting the specific salinity-ORP relationship.

3. The method for inverting the dynamic changes of the seafloor sedimentary environment based on three-phase potential according to claim 1, characterized in that, Three-phase potential and suspended particulate concentration data processing, including: data calibration, firstly selecting monitoring data of the target area, and then performing numerical fitting based on natural potential interpolation and suspended particulate concentration. In the deep-sea mining process, the concentration of suspended particulate matter in the plume changes significantly. Processing of spontaneous potential: Dynamic indoor data changes in the seabed sedimentary environment. Based on the fact that the maximum suspended sediment concentration in still water estuaries is 30 mg / L, the maximum concentration of suspended sediment on the seabed during tides can reach 8.69 g / L, and the maximum concentration near the bottom during typhoons can reach 14.2 g / L. During storm surges, the concentration can increase 30 times. Based on the suspended sediment solution concentration range of 0-20 g / L; and with a test range of 0-20 g / L and an accuracy of 1 g / L, a correlation was established: ； in Suspended sediment concentration, in g / L; SP, spontaneous potential, in g / L. , To measure water level height, the unit is cm. Salinity Temperature is expressed in °C, and dissolved oxygen (DO) is expressed in mg / L. ； SPM represents the mass of suspended sediments on the seabed, and RR measures the reduction in sediment resistivity, expressed as a percentage. Further analysis is performed based on the reduction in resistivity to derive a baseline resistivity value. Then, indoor resistivity correction was performed. ； in This refers to the suspended sediment concentration, expressed in g / L. Resistivity, in units of , Salinity Temperature is expressed in °C. Resistivity has a logarithmic relationship with the identification of suspended particulate concentration. The relationship between redox potential and suspended particulate matter concentration was analyzed using the mass of suspended sediments from the South China Sea. The analysis of the redox potential relationship in the sediments was as follows: ； ； ； ； in, This indicates the concentration of suspended particulate matter and the concentration of dissolved oxygen (C). DO Organic matter concentration C OM ORP represents redox potential, TOC is total organic carbon in sediments, TN is total organic nitrogen, and there is a correlation between redox potential and total organic carbon and total organic nitrogen in sediments. a and b are correlation coefficients, pH is the pH value of the solution, and C... TOC C TN The formula, compared to traditional indoor experiments, indicates that the redox potential is mainly affected by the sediment, and that there is a negative proportional relationship between the redox potential and the solution pH, thus revealing a nonlinear relationship between the redox potential and the solution.

4. The method for inverting the dynamic changes of the seafloor sedimentary environment based on three-phase potential according to claim 1, characterized in that, Data processing of three-phase potential and sediment property parameters, including: establishing the mathematical relationship between sediment density, water content, porosity and spontaneous potential, where the density of sediment is determined by the relative proportion of solid particles and pore water; Spontaneous potential is expressed by the following formula: ； in, It is the density of solid particles. It is the density of pore water. It refers to porosity; it is mainly determined based on the pore water content in sediments. Moisture content is ； Porosity is ； in ， It is the density of solid particles. It is the density of solid particles. It is the total volume, which focuses more on the pore density of sediments in situ within the seabed sedimentary environment than on the pore water between sediments, compared to traditional calculation methods. Establish a mathematical model with sediment density, water content, and porosity: ； A mathematical model was established based on resistivity, sediment porosity, and water content. ； It is the resistivity of the sediment. , It is the resistivity of water , It refers to the porosity of sediments. It is the porosity of saturated water. ； It is the resistivity of the sediment. , The resistivity of dry sediments , The density of sediment minerals (g / cm³) 3 , The total density of sediments is g / cm³ 3 ; The following model comprehensively considers the combined effects of porosity, water content, and density on resistivity. Compared with previous indoor test data, it is used to calibrate the sediment properties and resistivity of clay in seabed mining areas: ； ； ； ； Redox potential, taking into account the combined effects of porosity, water content, and density on resistivity. The density of sediments indicates their compactness and is related to the content of organic matter and minerals, as well as the degree of compaction. Higher density may lead to lower porosity, which in turn affects the diffusion rate of oxygen and other oxidants. Therefore, higher sediment density often corresponds to a lower redox potential. ； a and b are empirical constants, and their specific values ​​depend on the environment and sediment type; Moisture content Water content directly affects the availability and diffusion rate of oxygen in sediments; higher water content indicates lower oxygen content, therefore, ORP tends to decrease with increasing water content. A common empirical formula is: ； ORP (Organic Porosity) represents the proportion of void volume to total volume in sediments. High porosity means faster oxygen diffusion and a higher ORP, while low porosity makes it difficult for oxygen to enter, resulting in a lower ORP and a tendency to create a reducing environment. ； Finally, the comprehensive model ； The redox potential is related to the density, water content and porosity of sediments, but the specific mathematical relationship is greatly affected by the environment and experimental conditions. This formula is more accurate than the previous indoor test calibration, more suitable for indoor tests and in-situ monitoring, and has a more comprehensive coverage.

5. The method for inverting the dynamic changes of the seafloor sedimentary environment based on three-phase potential according to claim 1, characterized in that, Implementation methods include: (1) Deploy an electrode array to collect electrical signals of natural potential, resistivity and redox potential in real time by deploying an electrode array on the seabed; (2) Invert electrical signals. Use the above inversion algorithm to process electrical signals, deduce the seabed interface of the sedimentary environment, and determine the seabed interface based on the combination of three potentials. The concentration of suspended particulate matter in the sedimentary environment is determined by combining the seabed interface of the sedimentary environment with spontaneous potential, resistivity, and redox potential. (3) Multi-frequency signal analysis, combined with the noise reduction and filtering multi-frequency signal analysis method of three-phase potential, improves the resolution and accuracy of inversion; (4) Dynamic monitoring and identification: Based on changes in electrical signals, the dynamic characteristics of the seabed sedimentary environment are monitored in real time to identify environmental changes and sediment movement.

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