A method, system, equipment, and medium for early warning of hydrogen sulfide concentration based on sedimentary thermal deviation.

Abstract

This invention discloses a method, system, device, and medium for early warning of hydrogen sulfide concentration based on sedimentary layer metabolic thermal deviation, belonging to the field of sedimentary layer gas monitoring technology. The method includes: sequentially applying a first thermal micro-perturbation and a second thermal micro-perturbation to the physical center of the interface to construct a nonlinear instability coefficient and record the critical deceleration determination time; latching a reference state in response to the physical center of the interface meeting preset evolution conditions and recording the interface structure triggering time; constructing a biological amplification factor based on the reference state by applying isoparametric thermal pulses to determine activity-enhanced interface erosion; applying controlled hydrodynamic pulses to diagnose the reservoir driving type using gradient peak migration characteristics; and outputting a graded early warning based on the reservoir driving type when the causal leading time sequence conditions are met. This invention eliminates pore structure interference through dual-amplitude thermal micro-perturbations, distinguishes the causes of interface erosion through self-referenced causal discrimination, and adaptively identifies the reservoir driving mechanism through dynamic thermal diffusion reference cycle number, thus achieving advanced graded early warning.

Description

Technical Field

[0001] This invention relates to the field of sedimentary gas monitoring technology, specifically to a method, system, device, and medium for early warning of hydrogen sulfide concentration based on sedimentary metabolic thermal deviation. Background Technology

[0002] The long-term accumulation of organic matter in the bottom sediments of lakes, reservoirs, and nearshore seas provides a continuous carbon source and an anaerobic metabolic environment for sulfate-reducing bacteria. These bacteria oxidize organic carbon using sulfate as an electron acceptor, continuously generating hydrogen sulfide. During seasonal thermostratification, the thermocline blocks vertical convection, causing hydrogen sulfide to accumulate in large quantities at the sedimentary interface. When external hydrodynamic disturbances disrupt the thermostratification structure, the accumulated hydrogen sulfide is released into the upper water layers in a sudden manner, posing a threat to the aquatic ecosystem and surrounding areas.

[0003] For monitoring hydrogen sulfide in sedimentary layers, existing technical solutions mainly fall into the following two categories: The first type is the direct electrochemical detection method, which involves deploying electrochemical sensors in the interstitial water of sedimentary layers to obtain real-time hydrogen sulfide concentration values. This method can only reflect the current hydrogen sulfide concentration at the sampling location, and the alarm will only be triggered when the concentration reaches the danger threshold, lacking the ability to provide early warning. Furthermore, the electrochemical sensors are immersed in the sulfide-rich interstitial water environment for a long time, and corrosion failure problems restrict their long-term stable operation.

[0004] The second category is the indirect indicator method based on redox potential. This method infers the overall metabolic activity of sulfur-reducing bacteria by monitoring the redox potential and sulfate concentration gradient of the sediment layer. However, the redox potential is influenced by multiple physicochemical processes, such as iron reduction, manganese reduction, and organic matter degradation in the sediment layer. This makes it difficult to effectively separate the metabolic heat production signal of sulfur-reducing bacteria from the background heat signal. Consequently, it is impossible to quantitatively characterize the spatial structural features and dynamic evolution trend of metabolic activity in the interface region, and therefore, it cannot achieve early identification and warning of dangerous hydrogen sulfide accumulation events. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention provides a method, system, device and medium for early warning of hydrogen sulfide concentration based on the metabolic thermal deviation of the deposition layer.

[0006] Therefore, the technical problem solved by the present invention is that the existing technology cannot adaptively separate metabolic heat signals under the interference of heterogeneous pore structure of the deposition layer, and lacks continuous monitoring means for the driving mechanical characteristics before interface instability, which makes it impossible to achieve early warning of dangerous hydrogen sulfide accumulation events before the concentration reaches the dangerous threshold.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for early warning of hydrogen sulfide concentration based on metabolic thermal deviation of sedimentary layers, comprising, Extract the metabolic thermal deviation field of the sedimentary layer, and determine the physical center of the interface using the sensing layer with the largest absolute value of the spatial gradient in the metabolic thermal deviation field of the sedimentary layer. A first thermal perturbation and a second thermal perturbation are sequentially applied to the sensing layer where the physical center of the interface is located. The amplitude of the second thermal perturbation is greater than that of the first thermal perturbation. A nonlinear instability coefficient is constructed based on the position recovery characteristics of the physical center of the interface. In response to the continuous monotonically increasing nonlinear instability coefficient exceeding a preset upper limit, the critical deceleration determination time is recorded. In response to the physical center of the interface satisfying the preset evolution conditions, the interface state is latched as a reference state, and the trigger time of the interface structure is recorded. Based on the reference state, the interface region sensing layer and the oxidation region sensing layer are determined. Equal-parameter thermal pulses are applied to the interface region sensing layer and the oxidation region sensing layer to construct a bio-amplification factor. After the metabolic thermal deviation response of the oxidation region sensing layer reaches its peak value, the bio-amplification factor monotonically increases, which is determined to be an activity-enhanced interface erosion. In response to the establishment of the activity-enhanced interface erosion judgment, a controlled hydrodynamic pulse is applied to diagnose the reservoir driving type based on the gradient peak migration characteristics of the unrecovered area, and the time of completion of the reservoir diagnosis is recorded. In response to the critical deceleration determination time, the interface structure trigger time, and the storage diagnosis completion time satisfying the causal leading timing condition, a graded early warning is output according to the storage driving type.

[0008] As a preferred embodiment of the hydrogen sulfide concentration advance warning method based on sedimentary thermal deviation of the present invention, wherein: the extraction of the sedimentary thermal deviation field includes: Substitute the measured temperature time sequence of each sensing layer into the thermal diffusion equation, and construct the deposition layer metabolic thermal deviation value of the sensing layer using the residual of the obtained thermal equation. The deposition layer metabolic heat deviation values ​​of all sensing layers are arranged along the vertical depth direction, forming the deposition layer metabolic heat deviation field; The candidate thermal diffusivity coefficient that minimizes the global spatial variation coefficient of the metabolic thermal deviation field of the deposition layer is used to determine the estimated value of the thermal diffusivity coefficient, and the reference thermal diffusivity reference period is determined based on the estimated value of the thermal diffusivity coefficient. The noise floor is defined by the root mean square of the deposition layer metabolic heat deviation values ​​of all sensing layers. The metabolic thermal deviation field of the sediment layer is subjected to morphological smoothing, and the inflection point is defined at the depth where the sign of the difference sequence changes and the absolute value reaches a local maximum.

[0009] As a preferred embodiment of the hydrogen sulfide concentration early warning method based on sedimentary thermal deviation described in this invention, wherein the preset evolution conditions satisfy one of the following conditions: The physical center of the interface monotonically migrates to the shallow layer within the interval where the number of consecutive sampling cycles is greater than or equal to the reference thermal diffusion reference cycle number, and the total migration amount is greater than or equal to the distance between adjacent sensing layers. Interface sharpness is defined as the number of sensing layers between the shallowest sensing layer of the noise substrate and the physical center of the interface, where the metabolic heat deviation value of the deposition layer is greater than that of the deposition layer. The interface sharpness decreases monotonically within the range where the number of consecutive sampling periods is greater than or equal to the reference thermal diffusion reference period, and the total decrease is greater than or equal to that of one sensing layer. The total number of inflection points in the metabolic thermal deviation field of the deposition layer changes from one to zero; The total number of inflection points in the metabolic thermal deviation field of the deposition layer is greater than or equal to two.

[0010] As a preferred embodiment of the hydrogen sulfide concentration advance warning method based on the metabolic thermal deviation of the deposition layer described in this invention, wherein: the first thermal micro-perturbation and the second thermal micro-perturbation are applied to the same sensing layer where the physical center of the interface is located. The first thermal micro-perturbation causes the physical center of the interface to have a displacement equal to the distance between adjacent sensing layers. The second thermal micro-perturbation causes the displacement of the physical center of the interface to be equal to the distance between two adjacent sensing layers. Both the first thermal micro-perturbation and the second thermal micro-perturbation have an upper limit of not causing irreversible structural changes in the deposition layer; The nonlinear instability coefficient is constructed based on the nonlinear increasing characteristic of the recovery time of the physical center of the interface after the second thermal perturbation stops relative to the recovery time of the physical center of the interface after the first thermal perturbation stops.

[0011] As a preferred embodiment of the hydrogen sulfide concentration advance warning method based on sedimentary thermal deviation described in this invention, wherein the construction of the biomagnification factor includes: The interface region sensing layer is defined by the sensing layer where the physical center of the interface is located in the reference state, and the oxide region sensing layer is defined by the sensing layer in the reference state that is located above the physical center of the interface and whose distance from the physical center of the interface is greater than or equal to the distance between two sensing layers. The bio-amplification factor is defined by the gain characteristic of the metabolic thermal deviation response of the interface region sensing layer to the isoparametric thermal pulse relative to the metabolic thermal deviation response of the oxidation region sensing layer to the isoparametric thermal pulse. The peak time is defined as the sampling time at which the metabolic thermal deviation response of the oxidized region sensing layer reaches its peak value, and the post-peak segment is defined as the sampling interval after the peak time.

[0012] As a preferred embodiment of the hydrogen sulfide concentration early warning method based on sedimentary thermal deviation described in this invention, wherein: the diagnosis of reservoir-driven types based on gradient peak migration characteristics in unrecovered areas includes: The number of dynamic thermal diffusion reference cycles is determined by the recovery time of the physical center of the interface after the second thermal micro-disturbance stops; The unrecovered region is defined as the sensing layer region in the metabolic thermal deviation field of the sediment layer after the application of the controlled hydrodynamic pulse, where the deviation state has not yet recovered to the reference state. The recovery front is defined as the boundary sensing layer between the unrecovered region and the recovered region. When the number of consecutive sampling periods in which the gradient peak position persists in the unrecovered region is greater than or equal to the number of dynamic thermal diffusion reference periods, and the depth monotonically migrates to the shallow layer and merges with the recovery front, it is diagnosed as an interface self-organizing type. When the number of independently evolving gradient peaks in the unrecovered region is greater than or equal to two, it is diagnosed as a multi-domain splitting type; in response to the fact that after some gradient peaks in the multi-domain splitting type merge with the recovery front, the depth change of the gradient peaks that did not merge with the recovery front towards the shallow layer at each sampling time is greater than the depth change of the gradient peaks that did not merge with the recovery front towards the shallow layer at each sampling time before the partial gradient peaks were merged, a cascade activation risk marker is added; When the gradient peak migration characteristics in the unrecovered region do not meet the conditions for interface self-organization and the number of independently evolving gradient peaks is less than two, it is diagnosed as deep passive diffusion type.

[0013] As a preferred embodiment of the hydrogen sulfide concentration advance warning method based on sedimentary thermal deviation described in this invention, wherein the causal leader timing condition simultaneously satisfies the following two conditions: The critical deceleration determination time is earlier than the interface structure trigger time, and the interface structure trigger time is earlier than the storage capacity diagnosis completion time. The duration from the critical deceleration determination time to the interface structure trigger time is greater than or equal to the recovery time of the physical center of the interface after the second thermal micro-disturbance stops, as recorded at the critical deceleration determination time.

[0014] This invention provides an early warning system for hydrogen sulfide concentration based on the metabolic thermal deviation of the deposition layer.

[0015] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a hydrogen sulfide concentration early warning system based on sedimentary thermal deviation, comprising: a metabolic thermal deviation field extraction module, used to extract the sedimentary thermal deviation field and determine the physical center of the interface; The critical deceleration monitoring module is connected to the metabolic thermal deviation field extraction module and is used to construct a nonlinear instability coefficient based on the position recovery characteristics of the physical center of the interface and record the critical deceleration determination time. The reference state latching module is connected to the metabolic thermal deviation field extraction module and is used to latch the interface state as a reference state and record the interface structure trigger time. The cause determination module is connected to the reference state latching module and is used to construct a biological amplification factor based on the reference state and determine the activity-enhanced interface erosion. The reserve diagnosis module, connected to the cause discrimination module, is used to diagnose the reserve driving type and record the reserve diagnosis completion time; The early warning output module is connected to the critical deceleration monitoring module, the reference state latching module, and the reserve diagnosis module. It is used to output a graded early warning according to the reserve driving type in response to the critical deceleration determination time, the interface structure trigger time, and the reserve diagnosis completion time satisfying the causal leading timing condition.

[0016] The present invention provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the aforementioned method for early warning of hydrogen sulfide concentration based on deposition layer metabolic thermal deviation.

[0017] The present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the aforementioned method for early warning of hydrogen sulfide concentration based on deposition layer metabolic thermal deviation.

[0018] The beneficial effects of this invention are as follows: By sequentially applying a first thermal micro-perturbation and a second thermal micro-perturbation to the same sensing layer where the physical center of the interface is located, the position recovery process of the two perturbations follows the same pore structure path. The influence of the pore structure on the recovery time of the two positions cancels out when constructing the nonlinear instability coefficient. This invention achieves continuous monitoring of critical deceleration without relying on any external normalization parameters under the disturbance of heterogeneous pore structure in the deposition layer. It provides a driving force signal for interface instability before observable changes occur at the physical center of the interface, and records the critical deceleration determination time before the interface structure triggering time, thus ensuring the temporal leading nature of the early warning from a physical mechanism perspective.

[0019] This invention uses the sampling moment when the metabolic thermal deviation response of the sensing layer in the oxidation zone reaches its peak as the internal time reference for the reversal of the direction of the heat conduction driving force. The change trend of the biomagnification factor in the later stage of the peak is used to distinguish between activity-enhanced and load-driven interface erosion. This invention enables the differentiation between the endogenous and exogenous causes of enhanced metabolism of sulfur-reducing bacteria without relying on external model parameters, providing a causal basis for differentiated graded early warning.

[0020] This invention directly determines the dynamic thermal diffusion reference cycle number by using the recovery time of the physical center of the interface after the second thermal micro-disturbance stops. This allows the determination criteria for the persistence of the gradient peak position in the unrecovered area to be updated in real time with the current physical state of the sediment layer. This enables the adaptive identification of three types of reserve-driving mechanisms: interface self-organization, multi-domain splitting, and deep passive diffusion. Furthermore, it eliminates randomness in determinations by verifying causal leading time sequence conditions, ensuring that the graded early warning output is supported by physical causal direction. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 The above is a flowchart of an early warning method for hydrogen sulfide concentration based on the metabolic thermal deviation of the deposition layer, provided as an embodiment of the present invention.

[0023] Figure 2 The flowchart illustrates the extraction of the metabolic thermal deviation field of the sedimentary layer, as provided in one embodiment of the present invention, for a method of early warning of hydrogen sulfide concentration based on the metabolic thermal deviation of the sedimentary layer.

[0024] Figure 3 The flowchart illustrates the causal lead timing conditions for a method for predicting hydrogen sulfide concentration based on sedimentary thermal deviation, as provided in one embodiment of the present invention. Detailed Implementation

[0025] To make the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0026] Example 1 Reference Figures 1-3 This is one embodiment of the present invention, which provides a method for early warning of hydrogen sulfide concentration based on deposition layer metabolic thermal deviation, comprising: S1: Extract the metabolic thermal deviation field of the sedimentary layer, and determine the physical center of the interface by the sensing layer with the largest absolute value of the spatial gradient in the metabolic thermal deviation field of the sedimentary layer. S2: Apply a first thermal micro-perturbation and a second thermal micro-perturbation sequentially to the sensing layer where the physical center of the interface is located. The amplitude of the second thermal micro-perturbation is greater than that of the first thermal micro-perturbation. Construct a nonlinear instability coefficient based on the position recovery characteristics of the physical center of the interface. In response to the continuous monotonically increasing nonlinear instability coefficient exceeding the preset upper limit, record the critical deceleration determination time. S3: In response to the physical center of the interface meeting the preset evolution conditions, latch the interface state as a reference state and record the trigger time of the interface structure; S4: Based on the reference state, the interface region sensing layer and the oxidation region sensing layer are determined. Equal-parameter thermal pulses are applied to the interface region sensing layer and the oxidation region sensing layer to construct a bio-amplification factor. After the metabolic thermal deviation response of the oxidation region sensing layer reaches its peak, the bio-amplification factor monotonically increases, which is determined to be an activity-enhanced interface erosion. S5: In response to the establishment of the active-enhanced interface erosion judgment, a controlled hydrodynamic pulse is applied to diagnose the reservoir driving type based on the gradient peak migration characteristics of the unrecovered area, and the reservoir diagnosis completion time is recorded. S6: When the critical deceleration determination time, the interface structure trigger time, and the reserve diagnosis completion time meet the causal leader timing condition, a graded early warning is output according to the reserve driving type.

[0027] In some embodiments, the specific implementation of extracting the metabolic thermal deviation field of the deposition layer in step S1 includes steps S11 to S15: S11: Substitute the measured temperature time sequence of each sensing layer into the thermal diffusion equation, and construct the deposition layer metabolic thermal deviation value of the sensing layer using the residual of the obtained thermal equation.

[0028] It is understandable that the sedimentary layer is an organic-rich accumulation layer at the bottom of the water body. Sulfide-reducing bacteria form a redox gradient interface along the vertical depth direction within the sedimentary layer, and there are spatial differences in the intensity of metabolic activity on both sides of the interface. An array of sensing layers is deployed along the vertical depth direction, with each sensing layer recording the measured temperature time series at a fixed sampling period. Under conditions without biological metabolic heat production, the temperature distribution inside the sedimentary layer is governed solely by the physical process of heat conduction, satisfying the discrete one-dimensional heat diffusion equation. However, the metabolic activity of sulfur-reducing bacteria generates additional heat in local sensing layers, causing the measured temperature time series to deviate from the predicted values ​​of the discrete one-dimensional heat diffusion equation.

[0029] Furthermore, the thermal diffusivity is a physical parameter in the discrete one-dimensional thermal diffusivity equation that describes the rate of heat propagation in the deposition medium, and its value is directly related to the thermal properties of the deposition medium.

[0030] When executing S11, candidate thermal diffusivity values ​​must be preset. For the first... The first sensing layer is in the first At each sampling time, the residual of the thermal equation is calculated and expressed as: ; in, Number the sensing layer; Number the sampling time; For the first The first sensing layer is in the first The measured temperature at each sampling time. Indicates the first The first sensing layer is in the first The measured temperature at each sampling time. Indicates the first The first sensing layer is in the first The measured temperature at each sampling time; The duration of a single sampling period; The distance between adjacent sensing layers; For the first There are 10 candidate thermal diffusivity values, among which This serves as the index for the candidate thermal diffusivity values, with the range of values ​​determined by a preset grid of candidate thermal diffusivity values. For candidate thermal diffusivity values Next The first sensing layer is in the first The residuals of the thermal equation at each sampling time point approach zero when there is no biological metabolic heat production, and show positive values ​​when sulfur-reducing bacteria are metabolically active.

[0031] Understandably, the preset candidate thermal diffusivity value grid is set to 1×10. -8 m 2 / s is the initial value, 1×10 -6 m 2 / s is the termination value, 1×10 -8 m 2 / s is the step size, forming a set of uniformly distributed discrete candidate values ​​that cover the typical property range of the thermal diffusivity coefficient of the deposited medium; the preset candidate thermal diffusivity coefficient value grid remains unchanged during the operation of this method.

[0032] S12: The deposition layer metabolic heat deviation values ​​of all sensing layers are arranged along the vertical depth direction, forming the deposition layer metabolic heat deviation field.

[0033] Understandably, by arranging the sedimentary metabolic thermal deviation values ​​of all sensing layers at the same sampling time in ascending order of vertical depth, a sedimentary metabolic thermal deviation field is formed, reflecting the spatial distribution of metabolic activity within the sedimentary layer at the current moment. This field presents the metabolic thermal deviation intensity of each sensing layer at different depths as a discrete spatial sequence, thus characterizing the location and extent of the metabolically active regions of sulfur-reducing bacteria in vertical space.

[0034] S13: Determine the estimated value of the thermal diffusivity by selecting the candidate thermal diffusivity that minimizes the global spatial variation coefficient of the metabolic thermal deviation field of the sedimentary layer, and determine the reference number of thermal diffusivity cycles based on the estimated value of the thermal diffusivity.

[0035] Understandably, the calculated residuals of the thermal equation in S11 vary with the candidate thermal diffusivity value. The value varies depending on the candidate thermal diffusivity value. When consistent with the actual thermal properties of the sedimentary layer, the residuals of the thermal equations in the non-biological metabolic heat-generating region approach zero, and the spatial variation coefficient of the sedimentary metabolic heat deviation field composed of the residuals of all sensing layer thermal equations takes the global minimum value; when the candidate thermal diffusivity value When deviating from the true thermal properties of the sedimentary layer, the residuals of the thermal equations in the non-biological metabolic heat-generating region exhibit systematic spatial variation, and the spatial variation coefficient of the sedimentary layer metabolic heat deviation field is greater than the spatial variation coefficient corresponding to the estimated value of the thermal diffusivity coefficient.

[0036] Furthermore, the spatial variation coefficient of the metabolic thermal deviation field of the sedimentary layer and the candidate thermal diffusivity values ​​were used as the basis for further analysis. The correspondence is used as the discrimination criterion. On the preset candidate thermal diffusivity value grid, the candidate thermal diffusivity value that makes the spatial variation coefficient take the global minimum value is searched. The thermal diffusivity estimate is determined adaptively only by the measured temperature time series of the sensing layer.

[0037] The quotient obtained by dividing the standard deviation of the residuals of all sensing layer thermal equations at the same sampling time by the absolute value of the mean of the residuals of all sensing layer thermal equations at the same sampling time is defined as the metabolic thermal deviation field of the deposition layer in the candidate thermal diffusivity value. The spatial variation coefficient under the given conditions is expressed as: ; in, For candidate thermal diffusivity values Next The spatial variation coefficient of the metabolic thermal deviation field of the sediment layer at each sampling time; For candidate thermal diffusivity values Next Standard deviation of the residuals of all sensor layer thermal equations at each sampling time; For candidate thermal diffusivity values Next The mean of the residuals of the thermal equations of all sensing layers at each sampling time; , The meaning is consistent with the definition in S11.

[0038] Furthermore, on the preset candidate thermal diffusivity value grid, for each candidate thermal diffusivity value... Substituting into formula S11, the thermal equation residuals of all sensing layers are calculated one by one, and then the corresponding spatial variation coefficients are calculated. ; take Candidate thermal diffusivity value with global minimum As an estimate of the thermal diffusivity, it is denoted as

[0039] Furthermore, based on the estimated thermal diffusivity... The reference thermal diffusion period number is determined as follows: ; in, The reference number of thermal diffusion cycles; This is an estimate of the thermal diffusivity; this is the rounding up operation. and The meaning is consistent with the definition in S11. Reference thermal diffusion reference period number. This reflects the minimum number of sampling cycles required for thermal disturbances to be homogenized between adjacent sensing layers. With the estimated value of thermal diffusivity Each update will recalculate synchronously.

[0040] Furthermore, after the estimated value of the thermal diffusivity is determined, it is calculated every [number] reference thermal diffusivity cycles. For each sampling period, the spatial variation coefficient of the residual field is recalculated for all candidate thermal diffusivity values ​​using the latest measured temperature data for the current time period. The candidate thermal diffusivity value corresponding to the global minimum of the recalculated spatial variation coefficient is compared with the current thermal diffusivity estimate. If they differ, update the thermal diffusivity estimate with the candidate thermal diffusivity value. Simultaneously recalculate the reference thermal diffusion period number. and noise floor; the candidate thermal diffusivity value corresponding to the global minimum of the recalculated spatial variability coefficient and the current thermal diffusivity estimate. At the same time, keep the estimated value of thermal diffusivity. No change, only update the noise base.

[0041] Furthermore, using the estimated value of the thermal diffusivity The result obtained by substituting into the residual calculation formula of the S11 thermal equation is defined as the deposition layer metabolic heat deviation value of the sensing layer.

[0042] S14: Define the noise floor using the root mean square of the deposition layer metabolic heat deviation values ​​of all sensing layers.

[0043] Understandably, the metabolic heat deviation values ​​of each sensing layer's deposition layer are affected by sensor measurement noise, thermal diffusivity estimation errors, and microscopic heterogeneity of the deposition layer, exhibiting random fluctuations centered at zero under background conditions without biological metabolic heat generation. The noise floor is defined as the root mean square value of the metabolic heat deviation values ​​of all sensing layers' deposition layers at the same sampling time.

[0044] Furthermore, the noise substrate is estimated with respect to the thermal diffusivity. The updates are synchronized to ensure that the noise substrate matches the current thermal properties of the deposited layer.

[0045] S15: Perform morphological smoothing on the metabolic thermal deviation field of the sediment layer, and define the inflection point at the depth where the sign of the difference sequence changes and the absolute value reaches a local maximum.

[0046] It should be noted that the depth position where the absolute value is a local maximum refers to the depth position in the smoothed difference sequence where the absolute value of the difference at that depth position is greater than the absolute value of the difference between the two adjacent depth positions in the shallow direction and the two adjacent depth positions in the deep direction.

[0047] It is understandable that the metabolic thermal deviation field of the sedimentary layer may experience local fluctuations in the vertical space due to sensor noise, with amplitudes lower than the differences in metabolic thermal deviation values ​​between adjacent sensing layers. The morphology-preserving smoothing process only suppresses these local fluctuations with amplitudes lower than the differences in metabolic thermal deviation values ​​between adjacent sensing layers, without changing the number and relative arrangement of extreme points, thus completely preserving the spatial structural characteristics of the metabolic thermal deviation field of the sedimentary layer.

[0048] Furthermore, a difference sequence is calculated along the vertical depth direction for the smoothed sedimentary layer metabolic thermal deviation field; inflection points are defined at depths where the sign of the difference sequence changes and the absolute value of the difference reaches a local maximum. When the total number of inflection points is zero, the spatial distribution of the sedimentary layer metabolic thermal deviation field exhibits a monotonic structure; when the total number of inflection points is greater than or equal to two, multiple gradient reversal positions exist within the sedimentary layer metabolic thermal deviation field. The total number of inflection points and the depth position of each inflection point are recorded at each sampling time.

[0049] Furthermore, the anchoring region is defined by a set of sensor layers within a distance of at least two sensor layers above the physical center of the interface. In the first sampling period of this method, when the depth of the physical center of the interface is not yet determined, the two shallowest sensor layers are used as the default range of the anchoring region. The anchoring region range is updated synchronously as the depth of the sensor layer containing the physical center of the interface is determined at the current sampling time. The root mean square of the metabolic heat deviation value of the deposition layer of each sensor layer within the anchoring region is determined when the number of consecutive sampling periods is greater than or equal to the reference thermal diffusion reference period. When the temperature remains consistently higher than the noise floor within the specified range, the spatial variation coefficient minimization search is re-executed using the measured temperature data of the anchoring area to obtain the local thermal diffusion coefficient correction value. The deposition layer metabolic thermal deviation value of all sensing layers within one sensing layer spacing above and below the physical center of the interface is then recalculated using the local thermal diffusion coefficient correction value. This recalculates the initial value of the corresponding sensing layer in the deposition layer metabolic thermal deviation field, outputting the refined deposition layer metabolic thermal deviation field. The root mean square of the deposition layer metabolic thermal deviation value of each sensing layer within the anchoring area must not exceed or be equal to the reference thermal diffusion reference period number within the consecutive sampling period. When the value is continuously greater than the noise floor within the range, the metabolic thermal deviation field of the initial deposition layer is directly output.

[0050] In some embodiments, the specific implementation of applying the first thermal micro-perturbation and the second thermal micro-perturbation and constructing the nonlinear instability coefficient in step S2 includes steps S21 to S25: S21: The first thermal micro-perturbation and the second thermal micro-perturbation are applied to the same sensing layer at the physical center of the interface.

[0051] It is understandable that the depositional medium possesses a microscopic heterogeneous pore structure in vertical space, and the pore structure characteristics differ at different sensing layers. The position recovery time obtained by applying perturbations to different sensing layers will be affected by the pore structure at their respective locations, making the position recovery times between different sensing layers incomparable. The first thermal micro-perturbation and the second thermal micro-perturbation are applied sequentially to the same sensing layer where the physical center of the interface is located. This ensures that the position recovery processes of the first and second thermal micro-perturbations both traverse the exact same pore structure path at the sensing layer where the physical center of the interface is located. The influence of the pore structure on the two position recovery times acts on both measurements in the same way, causing the influence of the pore structure on the two position recovery times to cancel each other out when constructing the nonlinear instability coefficient.

[0052] S22: The first thermal micro-perturbation causes the displacement of the physical center of the interface to be equal to the distance between adjacent sensing layers.

[0053] Understandably, after the first thermal perturbation is applied to the sensing layer where the physical center of the interface is located, the physical center of the interface will displace in the vertical depth direction. The amplitude constraint of the first thermal perturbation is that the displacement generated by the physical center of the interface is equal to the distance between one adjacent sensing layer. After the first thermal perturbation stops, the difference between the metabolic thermal deviation value of the deposition layer of the sensing layer where the physical center of the interface is located and the metabolic thermal deviation value of the deposition layer of the sensing layer where the physical center of the interface is located before the perturbation is applied is less than the number of sampling cycles experienced by the noise substrate. This difference is defined as the position recovery time of the physical center of the interface after the first thermal perturbation stops, denoted as . ,in The unit is the number of sampling periods.

[0054] S23: The second thermal micro-perturbation causes the displacement of the physical center of the interface to be equal to the distance between two adjacent sensing layers.

[0055] Understandably, after the second thermal micro-perturbation is applied to the sensing layer where the interface physical center is located, the interface physical center will displace in the vertical depth direction. The amplitude constraint of the second thermal micro-perturbation is: the displacement generated by the interface physical center is equal to the distance between two adjacent sensing layers, making the perturbation amplitude of the second thermal micro-perturbation greater than that of the first thermal micro-perturbation, and causing a difference in position recovery time between the second and first thermal micro-perturbations. After the second thermal micro-perturbation stops, the difference between the metabolic thermal deviation value of the deposition layer of the sensing layer where the interface physical center is located and the metabolic thermal deviation value of the deposition layer of the sensing layer where the interface physical center is located before the perturbation is applied is less than the number of sampling cycles experienced by the noise substrate. This difference is defined as the position recovery time of the interface physical center after the second thermal micro-perturbation stops, denoted as . ,in The unit is the number of sampling periods. Furthermore, the first and second thermal micro-perturbations are applied sequentially. During the first execution in the initial phase of this method, the interval between the two perturbations is taken as the reference number of thermal diffusion periods. Duration of a single sampling period The product is used as the initial default interval; in subsequent executions, the recovery time of the physical center of the interface after the second thermal perturbation stopped, as recorded in the previous execution, is used. Update interval.

[0056] Furthermore, the duration of the second thermal perturbation is the time elapsed from the start to the stop of each application of the second thermal perturbation.

[0057] S24: Both the first and second thermal micro-perturbations are limited to not causing irreversible structural changes in the sediment layer.

[0058] Understandably, the application of thermal micro-perturbations will cause changes in the metabolic thermal deviation value of the deposition layer in the local sensing layer, thereby causing a shift in the physical center position of the interface. When the application of thermal micro-perturbations causes irreversible changes in the pore structure of the deposition layer, the position recovery time of subsequent measurements becomes meaningless. The absolute upper limit of the amplitudes of the first and second thermal micro-perturbations is set at not causing irreversible structural changes in the deposition layer, ensuring the comparability of each measurement value in the nonlinear instability coefficient sequence.

[0059] S25: The nonlinear instability coefficient is constructed based on the nonlinear increase characteristic of the recovery time of the physical center of the interface after the second thermal perturbation stops relative to the recovery time of the physical center of the interface after the first thermal perturbation stops.

[0060] It is understandable that the recovery time of the physical center of the interface after the second thermal perturbation stops is considered. Time to recover the position of the physical center of the interface after the first thermal perturbation stops The nonlinear increasing characteristics are used to construct nonlinear instability coefficients, which are updated after each first thermal micro-perturbation and second thermal micro-perturbation are executed and recorded in the nonlinear instability coefficient sequence.

[0061] Furthermore, prior to recording the interface structure triggering time in step S3, the continuously valid nonlinear instability coefficient measurements constitute a reference period sequence. The number of valid measurements in the reference period sequence reaches the reference thermal diffusion reference cycle number. When the number of measurements is doubled, the baseline mean and standard deviation of the nonlinear instability coefficient are calculated using the baseline period sequence. The upper limit of the nonlinear instability coefficient detection is defined as the baseline mean plus three times the baseline standard deviation. If the number of valid measurements in the baseline period sequence does not reach the baseline thermal diffusion reference period, the upper limit of the nonlinear instability coefficient detection is determined. At twice the speed, continue accumulating baseline sequence data, without performing critical deceleration determination.

[0062] It should be noted that the number of valid measurements in the baseline sequence refers to the number of nonlinear instability coefficient measurements that have been completed and recorded in the baseline sequence before the interface structure triggering time in step S3. After each first thermal micro-perturbation and second thermal micro-perturbation are executed sequentially and the position recovery time is effectively recorded, the number of valid measurements in the baseline sequence increases once. Measurements that are terminated due to insufficient number of valid sampling points caused by the change in the metabolic thermal deviation response of the oxide zone sensing layer relative to the moment before the application of the equal-parameter thermal pulse are less than the change in the number of valid sampling points caused by the noise substrate are not included in the number of valid measurements in the baseline sequence.

[0063] It should be noted that not performing the critical deceleration determination means that the number of valid measurements in the reference period sequence has not reached the reference number of thermal diffusion reference cycles. At twice the speed, the baseline mean and standard deviation of the nonlinear instability coefficient have not yet been determined, and the upper limit for the detection of the nonlinear instability coefficient has not yet been established. Therefore, no judgment is made on whether the measured value of the nonlinear instability coefficient meets the critical deceleration judgment condition. The determination will be made once the number of valid measured values ​​in the baseline sequence reaches the baseline thermal diffusion reference period. After doubling the number of times, the upper limit of the nonlinear instability coefficient detection is determined, and then the critical deceleration judgment is performed on the subsequent nonlinear instability coefficient measurements.

[0064] Furthermore, when the metabolic activity of sulfur-reducing bacteria in the sedimentary interface region increases, the recovery time of the physical center of the interface after the second thermal micro-disturbance ceases... The increase is greater than the recovery time of the physical center of the interface after the first thermal perturbation stops. As the magnitude of the increase increases, the nonlinear instability coefficient increases monotonically.

[0065] Furthermore, the number of valid measurements in the baseline period sequence reaches the number of baseline thermal diffusion reference cycles. After doubling the response, the nonlinear instability coefficient is continuously greater than or equal to During the measurement, the nonlinear instability coefficient increases monotonically and exceeds the upper limit of the nonlinear instability coefficient detection limit. The critical deceleration determination time is recorded.

[0066] Understandably, before executing step S3, the upper boundary and interface sharpness of the interface must first be determined. The upper boundary of the interface is defined as the shallowest sensing layer in the sedimentary thermal deviation field where the sedimentary thermal deviation value is greater than that of the noisy substrate; the interface sharpness is defined as the number of sensing layers between the upper boundary and the physical center of the interface. The upper boundary and interface sharpness are recorded at each sampling time.

[0067] Furthermore, the depth position of the physical center of the interface is determined by step S1 at each sampling time, and the total number of inflection points and the depth position of each inflection point are recorded by step S15 at each sampling time. The interface sharpness, the depth position of the physical center of the interface, the total number of inflection points and the depth position of each inflection point together constitute the basis for determining the preset evolution conditions.

[0068] In some embodiments, the preset evolution conditions in step S3 satisfy one of the following conditions, including steps S31 to S34: S31: The physical center of the interface monotonically migrates to the shallow layer within the interval where the number of consecutive sampling cycles is greater than or equal to the reference thermal diffusion reference cycle number, and the total migration amount is greater than or equal to the distance between one adjacent sensing layer.

[0069] It is understandable that when the physical center of the interface is within the range of consecutive sampling periods greater than or equal to the reference thermal diffusion period, Within the interval, the depth of each adjacent sampling time changes towards the shallower layer, and the total change in the depth of the physical center of the interface from the start sampling time to the end sampling time within the interval is greater than or equal to the distance between an adjacent sensing layer, thus satisfying the preset evolution condition S31.

[0070] Furthermore, the reference thermal diffusion period number As a time benchmark for continuous determination, it ensures that the migration characteristics of the physical center of the interface to the shallow layer remain valid for a time scale longer than the thermal diffusion homogenization time, thus eliminating the interference of position fluctuations caused by short-term noise on the determination results.

[0071] S32: Interface sharpness is defined as the number of sensing layers between the shallowest sensing layer with a deposition layer metabolic heat deviation value greater than that of the noise substrate and the physical center of the interface. Interface sharpness decreases monotonically within the range where the number of consecutive sampling periods is greater than or equal to the reference thermal diffusion reference period, and the total decrease is greater than or equal to that of one sensing layer.

[0072] It is understandable that interface sharpness reflects the spatial range between the upper boundary of the interface and the physical center of the interface. When the interface sharpness is greater than or equal to the reference thermal diffusion reference number of consecutive sampling periods, it is considered to be sharp. Within the interval, if the interface sharpness decreases at each adjacent sampling time, and the total decrease in interface sharpness within the interval is greater than or equal to that of a sensing layer, then the S32 preset evolution condition is met.

[0073] Furthermore, the decrease in interface sharpness indicates a reduction in the number of sensing layers between the physical center of the interface and the upper boundary of the interface, corresponding to a narrowing of the spatial distribution of the redox gradient interface of the deposition layer.

[0074] S33: The total number of inflection points in the metabolic thermal deviation field of the sedimentary layer changes from one to zero.

[0075] It is understandable that the total number of inflection points changes from one to zero, indicating that the original depth position in the differential sequence after the smoothing of the metabolic thermal deviation field of the sedimentary layer has disappeared where the sign changes and the absolute value reaches a local maximum. The position of gradient direction reversal inside the metabolic thermal deviation field of the sedimentary layer is reduced from one to zero, which corresponds to the original spatial distribution structure of metabolic activity inside the sedimentary layer becoming more uniform, satisfying the S33 preset evolution condition.

[0076] S34: The total number of inflection points in the metabolic thermal deviation field of the sedimentary layer is greater than or equal to two.

[0077] It is understandable that if the total number of inflection points is greater than or equal to two, it indicates that there are multiple gradient direction reversal positions within the metabolic thermal deviation field of the sedimentary layer, corresponding to multiple metabolically active regions within the sedimentary layer, which satisfies the S34 preset evolution condition.

[0078] In response to the interface physical center satisfying any of the preset evolution conditions S31, S32, S33, and S34 at the current sampling time, the entire layer distribution of the sedimentary metabolic thermal deviation field, which consists of the depth position of the interface physical center at the current sampling time, the interface sharpness, the total number of inflection points in the sedimentary metabolic thermal deviation field and the depth position of each inflection point, and the sedimentary metabolic thermal deviation values ​​of all sensing layers, is latched as a reference state, and the current sampling time number is recorded as the interface structure trigger time.

[0079] It is understandable that step S4 is executed based on the reference state latched in step S3, and equal-parameter thermal pulses are applied synchronously to the interface region sensing layer and the oxide region sensing layer. The duration of the equal-parameter thermal pulses is the same and the heating power density is the same.

[0080] In some embodiments, the specific implementation of constructing the bio-amplification factor in step S4 includes steps S41 to S43: S41: Define the interface region sensing layer as the sensing layer where the physical center of the interface is located in the reference state, and define the oxide region sensing layer as the sensing layer located above the physical center of the interface in the reference state and whose distance from the physical center of the interface is greater than or equal to the distance between two sensing layers.

[0081] Understandably, the interface region sensing layer is the sensing layer located at the physical center of the interface in the reference state, and its depth corresponds to the region where the redox gradient interface metabolic activity is most active in the sedimentary layer. The oxidation region sensing layer is the sensing layer located above the physical center of the interface in the reference state, with a distance from the physical center greater than or equal to the distance between two sensing layers. Its depth corresponds to the oxidation region of the sedimentary layer. Under conditions without sulfur-reducing bacterial metabolic activity, the sedimentary metabolic thermal deviation value of the oxidation region sensing layer is driven by external heat conduction.

[0082] S42: Define the bio-amplification factor based on the gain characteristics of the metabolic thermal deviation response of the interface region sensing layer to an equivalent thermal pulse relative to the metabolic thermal deviation response of the oxidation region sensing layer to an equivalent thermal pulse.

[0083] It is understandable that the change in the metabolic thermal deviation response of the interface region sensing layer relative to the moment before the application of the equal-parameter thermal pulse is used as the numerator, and the change in the metabolic thermal deviation response of the oxidation region sensing layer relative to the moment before the application of the equal-parameter thermal pulse is used as the denominator. The quotient of the two is defined as the biomagnification factor corresponding to the sampling moment of the effective sampling point.

[0084] Furthermore, if the change in the metabolic thermal deviation response of the oxide zone sensing layer relative to the moment before the application of the equal-parameter thermal pulse is less than that of the noise substrate, the sampling point is discarded; if the number of valid sampling points is less than 8, the execution of step S4 is terminated, a data insufficiency marker is recorded, and the lower limit of the number of valid sampling points for the next execution is raised to 12; if the number of valid sampling points is greater than or equal to 8, step S43 is continued.

[0085] S43: The peak time is defined by the sampling time at which the metabolic thermal deviation response of the sensing layer in the oxidation zone reaches its peak value, and the post-peak segment is defined by the sampling interval after the peak time.

[0086] It is understandable that the metabolic thermal deviation response of the oxidized zone sensing layer changes at each sampling time after the application of the equal-parameter thermal pulse. The sampling time at which the metabolic thermal deviation response of the oxidized zone sensing layer first decreases after reaching its maximum value is defined as the peak time; the sampling interval consisting of all effective sampling points after the peak time is defined as the post-peak segment.

[0087] Furthermore, if the bio-amplification factor monotonically increases at each sampling time within the post-peak segment, it is determined to be activity-enhanced interface erosion. In response to the determination of activity-enhanced interface erosion, step S5 is activated when the difference between two adjacent sampling times for all sensor layer deposition layer metabolic thermal deviation values ​​within the current sampling period after step S4 is completed is less than the noise substrate value. If the bio-amplification factor decreases synchronously with the metabolic thermal deviation response of the oxidized sensor layer within the post-peak segment, it is determined to be load-driven interface erosion, and step S5 is not activated.

[0088] Understandably, the intensity of the controlled hydrodynamic pulse needs to be constrained before executing step S5. The intensity of the controlled hydrodynamic pulse satisfies the following two constraints: Constraint 1, after the controlled hydrodynamic pulse is applied, the change in the metabolic thermal deviation value of the shallowest sensing layer relative to the corresponding layer in the reference state is greater than or equal to the noise substrate; Constraint 2, when the total number of inflection points in the reference state is not zero, all sensing layers below the deepest inflection point in the reference state are used as the reference layer, and the change in the metabolic thermal deviation value of each sensing layer in the reference layer is less than the noise substrate; when the total number of inflection points in the reference state is zero, all sensing layers below the physical center of the interface in the reference state are used as the reference layer, and the change in the metabolic thermal deviation value of each sensing layer in the reference layer is less than the noise substrate.

[0089] Furthermore, when the controlled hydrodynamic pulse is applied for the first time, the minimum intensity that satisfies constraint one is taken; if the change in the metabolic thermal deviation value of any sensing layer deposition layer in the reference layer is greater than or equal to the noise substrate, the current application is terminated and reapplied with a lower intensity until both constraints are satisfied at the same time.

[0090] In some embodiments, the specific implementation of diagnosing the reservoir-driven type using the gradient peak migration characteristics of the unrecovered region in step S5 includes steps S51 to S55: S51: The number of reference cycles for dynamic thermal diffusion is determined by the recovery time of the physical center of the interface after the second thermal micro-perturbation stops.

[0091] It is understandable that the recovery time of the physical center of the interface after the second thermal micro-perturbation stopped, as recorded in step S23, is considered. The number of sampling periods is directly used as the reference number for dynamic thermal diffusion, denoted as . Dynamic thermal diffusion reference period number Reflecting the actual recovery capability of the sedimentary layer interface region to disturbances at the current moment, and the recovery time of the physical center of the interface after the second thermal micro-disturbance stops. The update is synchronized to ensure that the gradient peak persistence determination criteria in step S53 match the current physical state of the sediment layer.

[0092] Furthermore, when step S51 is executed and step S2 has not yet completed any valid measurement, the dynamic thermal diffusion reference cycle number is... Take the reference number of thermal diffusion cycles As the initial default value; Step S2 first completes the effective measurement and transmits the recovery time of the physical center of the interface position after the second thermal micro-perturbation stops. After that, with Update dynamic thermal diffusion reference period number .

[0093] S52: The unrecovered region is defined as the sensing layer region in the metabolic thermal deviation field of the sediment layer after the application of a controlled hydrodynamic pulse, where the deviation state has not yet recovered to the reference state. The recovery front is defined as the boundary sensing layer between the unrecovered region and the recovered region.

[0094] Understandably, after the controlled hydrodynamic pulse is applied, the following recording operation is performed at each sampling time: the unrecovered region is defined as the sensing layer region where the difference between the metabolic thermal deviation value of the sedimentary layer of each sensing layer at the current sampling time and the metabolic thermal deviation value of the corresponding depth sensing layer in the reference state is greater than the noise substrate; the recovery front is defined as the boundary sensing layer where the difference between the metabolic thermal deviation value of the sedimentary layer between the unrecovered region and the recovered region and the metabolic thermal deviation value of the corresponding layer of the reference state changes from being greater than the noise substrate to being less than or equal to the noise substrate.

[0095] It should be noted that the recovered area is the sensor layer region where the difference between the metabolic thermal deviation value of the deposition layer of each sensing layer at the current sampling time and the metabolic thermal deviation value of the corresponding depth sensing layer in the reference state is less than or equal to the noise substrate. The recovered area and the unrecovered area are complementary to each other with the noise substrate as the discrimination threshold. They jointly cover the entire sensing layer at each sampling time. As the deviation state of each sensing layer gradually recovers after the application of the controlled hydrodynamic pulse, the range of the recovered area dynamically expands at each sampling time, while the range of the corresponding unrecovered area dynamically shrinks at each sampling time. The recovery front then migrates to the deeper layers until the entire sensing layer belongs to the recovered area, at which point the recovery process is complete.

[0096] Furthermore, the spatial gradient of the sedimentary thermal deviation field is calculated for the unrecovered area. The depth position where the absolute value of the gradient in the unrecovered area is locally maximized and the gradient sign changes is extracted as the gradient peak position. When there are multiple gradient peak positions, they are distinguished by the gradient peak position number, and the depth of each gradient peak position and the depth change of each gradient peak position between adjacent sampling times are recorded respectively.

[0097] Furthermore, the recording operation at each sampling moment continues until the difference between the metabolic thermal deviation values ​​of all sensing layer deposits and the metabolic thermal deviation values ​​of the corresponding layer in the reference state is less than the noise substrate. The current sampling moment number is then recorded as the time when the reserve diagnosis is completed.

[0098] S53: When the number of consecutive sampling periods in which the gradient peak position persists in the unrecovered region is greater than or equal to the number of dynamic thermal diffusion reference periods, and the depth monotonically migrates to the shallow layer and merges with the recovery front, it is diagnosed as an interface self-organizing type.

[0099] It is understandable that the number of consecutive sampling periods in which the gradient peak persists is greater than or equal to the number of dynamic thermal diffusion reference periods. This indicates that the gradient peak persists within the timescale corresponding to the current recovery capacity of the sedimentary layer; the gradient peak depth changes towards the shallower layer at each adjacent sampling time during its persistence, indicating that the gradient peak actively migrates towards the recovery front; the gradient peak eventually merges with the recovery front, indicating that the metabolic thermal deviation gradient structure within the unrecovered zone propagates to the shallower layer and merges with the recovery front. When all three conditions are met, the diagnosis is a self-organized interface type, indicating that the metabolic activity of sulfur-reducing bacteria in the sedimentary layer interface region is the main source of hydrogen sulfide production in the sedimentary layer.

[0100] S54: When the number of independently evolving gradient peaks in the unrecovered region is greater than or equal to two, it is diagnosed as a multi-domain splitting type; in response to the fact that after some gradient peaks in the multi-domain splitting type merge with the recovery front, the depth change of the gradient peaks that did not merge with the recovery front towards the shallow layer at each sampling time is greater than the depth change of the gradient peaks that did not merge with the recovery front towards the shallow layer at each sampling time before some gradient peaks were merged, a cascade activation risk marker is added.

[0101] It is understandable that when the number of independently evolving gradient peaks in the unrecovered zone is greater than or equal to two, it indicates that there are multiple independent metabolic thermal deviation gradient reversal positions in the unrecovered zone. Each gradient peak records depth changes, which is diagnosed as a multi-domain splitting type, indicating that there are multiple independent metabolically active regions of sulfur-reducing bacteria inside the sedimentary layer.

[0102] Furthermore, in response to the merging of some gradient peaks with the recovery front in the multi-domain splitting pattern, the depth change of gradient peaks that have not merged with the recovery front is continuously tracked at each sampling time. When the depth change of gradient peaks that have not merged with the recovery front towards the shallow layer at each sampling time is greater than the depth change of gradient peaks that have not merged with the recovery front towards the shallow layer at each sampling time before the merging of some gradient peaks, a cascade activation risk marker is added, indicating that the migration rate of residual gradient peaks in the unrecovered region increases after the merging of other gradient peaks, and there is a risk of chain triggering.

[0103] S55: When the gradient peak migration characteristics in the unrecovered region do not meet the conditions for interface self-organization and the number of independently evolving gradient peaks is less than two, it is diagnosed as deep passive diffusion type.

[0104] It is understandable that the number of consecutive sampling periods in which the gradient peak position persists within the unrecovered region is less than the number of dynamic thermal diffusion reference periods. Sampling moments where the gradient peak depth increases during its continuous existence do not meet the criteria for interface self-organization; when the number of independently evolving gradient peaks is less than two, the criteria for multi-domain splitting are not met. When both of the above conditions are met, the diagnosis is deep passive diffusion type, indicating that hydrogen sulfide in the sedimentary layer passively diffuses from deep to shallow layers, while the metabolic activity of sulfur-reducing bacteria in the non-sedimentary layer interface region actively generates it.

[0105] Understandably, step S6 continuously records the following three sampling time numbers: the critical deceleration determination time recorded in step S2, the interface structure trigger time recorded in step S3, and the reserve diagnosis completion time recorded in step S5. After the reserve diagnosis completion time is recorded, a causal precedent timing condition verification is performed, and conditions S61 and S62 must be satisfied simultaneously.

[0106] In some embodiments, the specific implementation of the causal leading timing condition in step S6 includes steps S61 to S62: S61: The critical deceleration determination time is earlier than the interface structure trigger time, and the interface structure trigger time is earlier than the storage diagnosis completion time.

[0107] It is understandable that the critical deceleration determination time is earlier than the interface structure triggering time, indicating that the precursor signal of sedimentary interface instability evolves before the interface structure, which is consistent with the physical causal direction of the early warning of hydrogen sulfide concentration. The interface structure triggering time is earlier than the reservoir diagnosis completion time, indicating that the interface structure evolution is identified before the reservoir driving mechanism is identified. The timing of the three is consistent with the physical causal order of critical deceleration determination, interface structure triggering, and reservoir diagnosis completion, which satisfies condition S61.

[0108] S62: The duration from the critical deceleration determination time to the interface structure trigger time is greater than or equal to the recovery time of the physical center of the interface after the second thermal micro-disturbance recorded at the critical deceleration determination time stops.

[0109] It is understandable that the duration between the critical deceleration determination time and the interface structure trigger time is determined by the number of sampling periods between the critical deceleration determination time and the interface structure trigger time, and the duration of a single sampling period. The product is determined. The recovery time of the physical center of the interface after the second thermal micro-perturbation stops, recorded at the critical deceleration determination moment, is the same as that recorded in step S23. Corresponding duration. The duration between the critical deceleration determination moment and the interface structure trigger moment is greater than or equal to... The corresponding duration indicates that at least one sedimentation layer relaxation time has elapsed between the critical deceleration determination and the interface structure triggering, thus excluding the randomness determination and satisfying condition S62.

[0110] In response to the simultaneous fulfillment of conditions S61 and S62, a graded early warning is output based on the reserve-driven type diagnosed in step S5, as follows: When the storage-driven type is interface self-organizing and there is no cascade activation risk marker, a first-level warning is output, along with the depth position where the gradient peak finally merges with the recovery front. When the reserve-driven type is interface self-organizing and has a cascade activation risk marker, the output is a first-level warning enhancement, with the gradient peak number and depth position of the triggering cascade activation risk marker. When the reserve-driven type is multi-domain splitting and has cascade activation risk markers, the output is a first-level warning enhancement, with the final depth of each gradient peak and the gradient peak number corresponding to the cascade activation risk markers. When the reserve-driven type is multi-domain splitting and there is no cascade activation risk marker, output a first-level warning and attach the final depth sequence of each gradient peak. When the reserve-driven type is deep passive diffusion, a level 2 early warning is output.

[0111] Furthermore, if conditions S61 and S62 are not simultaneously met, it is determined that the causal precursor duration is insufficient, a level 3 warning is output, the nonlinear instability coefficient sequence is re-accumulated, and the level warning output is re-executed after the next verification that conditions S61 and S62 are simultaneously met.

[0112] Furthermore, in response to the nonlinear instability coefficient being continuously greater than or equal to the reference thermal diffusion reference number of cycles... If the measurement shows a monotonically increasing amount and the interface structure trigger time has not yet been recorded, an early warning is output. In response to the early warning output, if the migration amount of the interface physical center to the shallow layer is greater than or equal to the distance between an adjacent sensing layer, an S3 reference state latching operation is performed, the current sampling time number is recorded as the interface structure trigger time, and the causal leader timing condition verification is re-executed.

[0113] Furthermore, the interval between each execution of the first and second thermal micro-perturbations is defined as the background monitoring interval. An incremental sequence is constructed using the adjacent differences of three consecutive nonlinear instability coefficients. When all differences in the incremental sequence are positive, the background monitoring interval is shortened, and the recording interval for the interface physical center depth in step S1 is updated to not exceed the current background monitoring interval. The shortened background monitoring interval must not be less than the duration of a single second thermal micro-perturbation and the time recorded at the critical deceleration determination moment. The sum of the corresponding durations; when the current background monitoring interval is equal to the lower limit, the intensity of the first thermal micro-disturbance and the second thermal micro-disturbance will be increased by one level each, and the amplitude constraints of the first thermal micro-disturbance and the second thermal micro-disturbance must still meet the upper limit amplitude constraints specified in S22 and S23.

[0114] Furthermore, after the critical deceleration determination time is recorded, the background monitoring interval continues to run at the current duration, continuously updating the nonlinear instability coefficient sequence and the recovery time of the physical center of the interface after the latest second thermal micro-perturbation stops. .

[0115] Example 2 As one embodiment of the present invention, this embodiment provides a hydrogen sulfide concentration advance warning system based on deposition layer metabolic thermal deviation, comprising: The metabolic thermal deviation field extraction module is used to extract the metabolic thermal deviation field of the sediment layer and determine the physical center of the interface; The critical deceleration monitoring module is connected to the metabolic thermal deviation field extraction module and is used to construct a nonlinear instability coefficient based on the position recovery characteristics of the physical center of the interface and record the critical deceleration determination time. The reference state latching module is connected to the metabolic thermal deviation field extraction module and is used to latch the interface state as a reference state and record the interface structure trigger time. The cause determination module is connected to the reference state latching module and is used to construct a biological amplification factor based on the reference state and determine the activity-enhanced interface erosion. The reserve diagnosis module, connected to the cause discrimination module, is used to diagnose the reserve driving type and record the reserve diagnosis completion time; The early warning output module is connected to the critical deceleration monitoring module, the reference state latching module, and the reserve diagnosis module. It is used to output a graded early warning according to the reserve driving type in response to the critical deceleration determination time, the interface structure trigger time, and the reserve diagnosis completion time satisfying the causal leading timing condition.

[0116] This embodiment also provides an electronic device applicable to a method for early warning of hydrogen sulfide concentration based on deposition layer metabolic thermal deviation, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the method for early warning of hydrogen sulfide concentration based on deposition layer metabolic thermal deviation as proposed in the above embodiment.

[0117] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a method for early warning of hydrogen sulfide concentration based on metabolic thermal deviation of the deposition layer, as proposed in the above embodiment.

[0118] The storage medium proposed in this embodiment and the method for early warning of hydrogen sulfide concentration based on the metabolic thermal deviation of the deposition layer proposed in the above embodiment belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0119] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0120] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for early warning of hydrogen sulfide concentration based on metabolic heat deviation of deposited layer, characterized in that, The method comprises the following steps: extracting a deposition layer metabolic heat deviation field, determining an interface physical center according to a sensing layer with the largest absolute value of spatial gradient in the deposition layer metabolic heat deviation field; sequentially applying a first thermal micro-perturbation and a second thermal micro-perturbation to the sensing layer where the interface physical center is located, the amplitude of the second thermal micro-perturbation being greater than that of the first thermal micro-perturbation, constructing a nonlinear instability coefficient based on the position recovery characteristics of the interface physical center, and recording a critical deceleration judgment moment in response to the continuous and monotonous increase of the nonlinear instability coefficient and exceeding a preset upper limit of the reference; in response to the interface physical center satisfying a preset evolution condition, locking the interface state as a reference state and recording an interface structure triggering moment; determining an interface zone sensing layer and an oxidation zone sensing layer based on the reference state, applying an equal parameter thermal pulse to the interface zone sensing layer and the oxidation zone sensing layer, and constructing a biological amplification factor, and determining active enhancement type interface erosion in response to the biological amplification factor monotonously increasing after the metabolic heat deviation response quantity of the oxidation zone sensing layer reaches a peak value; in response to the active enhancement type interface erosion determination being established, applying a controlled hydrodynamic pulse to diagnose the reserve driving type according to the gradient peak position migration characteristics of the unrecovered zone, and recording a reserve diagnosis completion moment; in response to the critical deceleration judgment moment, the interface structure triggering moment and the reserve diagnosis completion moment satisfying a causal leading time sequence condition, outputting a hierarchical early warning according to the reserve driving type.

2. The method for early warning of hydrogen sulfide concentration based on metabolic heat deviation of deposited layer according to claim 1, characterized in that, The method comprises the following steps: substituting the measured temperature time sequence of each sensing layer into the heat diffusion equation, and constructing a deposition layer metabolic heat deviation value of the sensing layer according to the obtained heat equation residual; arranging the deposition layer metabolic heat deviation values of all sensing layers along the vertical depth direction to form the deposition layer metabolic heat deviation field; determining a heat diffusion coefficient estimate value with a candidate heat diffusion coefficient that globally minimizes the spatial variation coefficient of the deposition layer metabolic heat deviation field, and determining a reference heat diffusion reference period number based on the heat diffusion coefficient estimate value; defining a noise floor with the root mean square of the deposition layer metabolic heat deviation values of all sensing layers; performing shape-preserving smoothing processing on the deposition layer metabolic heat deviation field, and defining an inflection point with the depth position where the sign changes and the absolute value takes a local maximum in the smoothed difference sequence.

3. The method of claim 2, wherein the method is based on the deviation of the metabolic heat of the deposited layer. The preset evolution condition satisfies one of the following conditions: the interface physical center monotonously migrates to the shallow layer in an interval with a continuous sampling period number greater than or equal to the reference heat diffusion reference period number, and the total migration amount is greater than or equal to an adjacent sensing layer spacing; defining an interface sharpness with the number of sensing layers between the shallowest sensing layer with the deposition layer metabolic heat deviation value greater than the noise floor and the interface physical center, the interface sharpness monotonously decreasing in an interval with a continuous sampling period number greater than or equal to the reference heat diffusion reference period number, and the total decrease amount being greater than or equal to one sensing layer; the total number of the inflection points in the deposition layer metabolic heat deviation field changes from one to zero; the total number of the inflection points in the deposition layer metabolic heat deviation field is greater than or equal to two.

4. The method of claim 3, wherein the method is based on the deviation of the metabolic heat of the deposited layer. The first thermal micro-perturbation and the second thermal micro-perturbation are applied to the same sensing layer where the interface physical center is located. The first thermal micro-disturbance causes the interface physical center to generate a displacement equal to one adjacent sensing layer spacing; The second thermal micro-disturbance causes the interface physical center to generate a displacement equal to two adjacent sensing layer spacings; Both the first thermal micro-disturbance and the second thermal micro-disturbance are upper limited by not causing irreversible structural changes of the deposited layer; The non-linear destabilization coefficient is constructed by a non-linear increase characteristic of a position recovery time length of the interface physical center after the second thermal micro-disturbance stops relative to a position recovery time length of the interface physical center after the first thermal micro-disturbance stops.

5. The method of claim 4, wherein the method is based on the deviation of the metabolic heat of the deposited layer. The constructed biological amplification factor includes: The interface zone sensing layer is defined by the sensing layer where the interface physical center is located in the reference state, and the oxidation zone sensing layer is defined by the sensing layer above the interface physical center and having a spacing greater than or equal to two sensing layer spacings from the interface physical center in the reference state; The gain characteristic of the metabolic heat deviation response amount of the interface zone sensing layer to the equal-parameter thermal pulse relative to the metabolic heat deviation response amount of the oxidation zone sensing layer to the equal-parameter thermal pulse defines the biological amplification factor; The sampling time when the metabolic heat deviation response amount of the oxidation zone sensing layer reaches a peak value defines a peak time, and a post-peak section is defined by a sampling interval after the peak time.

6. The method of claim 5, wherein the method is based on the deviation of the metabolic heat of the deposited layer. The diagnosis of the reserve driving type by the gradient peak migration characteristic in the unrecovered zone includes: The number of dynamic thermal diffusion reference periods is determined by the position recovery time length of the interface physical center after the second thermal micro-disturbance stops; The unrecovered zone is defined by the sensing layer region in the metabolic heat deviation field of the deposited layer that has not recovered to the reference state after the controlled hydrodynamic pulse is applied, and the recovered front is defined by the boundary sensing layer between the unrecovered zone and the recovered zone; When the number of continuous sampling periods during which the gradient peak in the unrecovered zone continuously exists is greater than or equal to the number of dynamic thermal diffusion reference periods, the gradient peak migrates monotonously to the shallow layer and merges with the recovered front, the diagnosis is of the interface self-organization type; When the number of independently evolved gradient peaks in the unrecovered zone is greater than or equal to two, the diagnosis is of the multi-domain splitting type; in response to the merging of part of the gradient peaks in the multi-domain splitting type with the recovered front, when the depth change amount of the gradient peak that has not merged with the recovered front to the shallow layer is greater than the depth change amount of the gradient peak that has not merged with the recovered front to the shallow layer before the merging of part of the gradient peaks is completed, an additional cascade activation risk label is added; When the gradient peak migration characteristic in the unrecovered zone does not meet the interface self-organization type determination condition and the number of independently evolved gradient peaks is less than two, the diagnosis is of the deep passive diffusion type.

7. The method of claim 6, wherein the method is based on the deviation of the metabolic heat of the deposited layer. The causal precursor timing condition simultaneously satisfies the following two conditions: The critical deceleration determination time is earlier than the interface structure triggering time, and the interface structure triggering time is earlier than the reserve diagnosis completion time; The time length from the critical deceleration determination time to the interface structure triggering time is greater than or equal to the position recovery time length of the interface physical center after the second thermal micro-disturbance stops recorded at the critical deceleration determination time.

8. A hydrogen sulfide concentration early warning system based on metabolic heat deviation of sediment layer, applying a hydrogen sulfide concentration early warning method based on metabolic heat deviation of sediment layer according to any one of claims 1-7, characterized in that, It includes: a metabolic heat deviation field extraction module configured to extract a metabolic heat deviation field of the sedimentary layer and determine a physical center of the interface; a critical deceleration monitoring module connected to the metabolic heat deviation field extraction module, configured to construct a nonlinear instability coefficient based on a position recovery characteristic of the physical center of the interface and record a critical deceleration judgment time; a reference state latching module connected to the metabolic heat deviation field extraction module, configured to latch the interface state as a reference state and record an interface structure trigger time; a cause discrimination module connected to the reference state latching module, configured to construct a biological amplification factor based on the reference state and determine active enhancement type interface erosion; a reserve diagnosis module connected to the cause discrimination module, configured to diagnose a reserve driving type and record a reserve diagnosis completion time; an early warning output module connected to the critical deceleration monitoring module, the reference state latching module, and the reserve diagnosis module, configured to output a hierarchical early warning according to the reserve driving type in response to the critical deceleration judgment time, the interface structure trigger time, and the reserve diagnosis completion time satisfying a cause-effect leading time sequence condition. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the hydrogen sulfide concentration advanced early warning method based on the metabolic heat deviation of the sedimentary layer according to any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the hydrogen sulfide concentration advanced early warning method based on the metabolic heat deviation of the sedimentary layer according to any one of claims 1 to 7.

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