Biogenic gas hydrocarbon quantity estimation method, device, equipment, medium and product

Abstract

The application discloses a biological gas hydrocarbon amount estimation method, device, equipment, medium and product, relates to the field of marine exploration, and the method comprises the following steps: acquiring seismic data, identifying a seabed simulation reflection layer to obtain burial depth and distribution characteristics; acquiring water depth data to calculate seabed temperature; inferring a geothermal gradient based on the burial depth of the seabed simulation reflection layer, the seabed temperature and a natural gas hydrate phase equilibrium relationship; determining a geological age and calculating a sedimentation rate; determining the area of a research area based on the distribution characteristics, determining the thickness of a hydrocarbon generation window based on the geothermal gradient and the seabed temperature, and estimating the sediment volume; and estimating the biological gas hydrocarbon amount based on the sediment volume, the sedimentation rate and a hydrocarbon generation potential parameter. The application infers the geothermal gradient by identifying the seabed simulation reflection layer through the seismic data, realizes rapid inference of a thermal field in a well-free or well-scarce area, and improves the estimation accuracy of the hydrocarbon amount.

Description

Technical Field

[0001] This application relates to the field of marine exploration, and in particular to a method, apparatus, equipment, medium, and product for estimating biogenic hydrocarbon generation. Background Technology

[0002] Biogenic gas is an important component of marine oil and gas resources, accounting for a significant proportion of offshore natural gas resources. In marine exploration, accurately estimating the hydrocarbon generation of biogenic gas is crucial for resource assessment and the prediction of favorable areas. However, in areas such as the deep sea where drilling data is scarce, traditional geochemical simulation methods relying on temperature gradients and sedimentary parameters result in insufficient accuracy in estimating the hydrocarbon generation of biogenic gas. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, equipment, medium, and product for estimating biogenic gas-generated hydrocarbons. By using seismic data to identify simulated seafloor reflective layers, combining the phase equilibrium relationship of natural gas hydrates to infer the geothermal gradient, and on this basis, quantitatively estimating biogenic gas-generated hydrocarbons in conjunction with sedimentation rates, the aim is to solve the problem of insufficient accuracy in estimating biogenic gas-generated hydrocarbons in existing technologies.

[0004] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a method for estimating the amount of hydrocarbons generated by biogenic gas, including: Seismic data of the target sea area is acquired, and the seabed simulated reflective layer is identified and traced based on the seismic data to obtain the burial depth and distribution characteristics of the seabed simulated reflective layer. Acquire water depth data for the target sea area, and calculate seabed temperature based on the water depth data; Based on the burial depth of the simulated seabed reflector, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates, the geothermal gradient of the target sea area is inferred. The geological age is determined based on the interpretation results of the seismic reflection horizons in the target sea area, and the sedimentation rate is calculated based on the burial depth of the seismic reflection horizons and the geological age. The area of ​​the study area is determined based on the distribution characteristics, the thickness of the hydrocarbon generation window is determined based on the geothermal gradient and the seafloor temperature, and the sediment volume is estimated based on the area of ​​the study area and the thickness of the hydrocarbon generation window. The biogenic hydrocarbon generation is estimated based on the sediment volume, the sedimentation rate, and the hydrocarbon generation potential parameters.

[0005] Optionally, the step of identifying and tracing the simulated seafloor reflector layer based on the seismic data to obtain the burial depth and distribution characteristics of the simulated seafloor reflector layer specifically includes: The seismic data is preprocessed, including amplitude equalization, noise suppression, gather correction, and time-depth conversion preparation. On the seismic profile, a reflection interface is identified that satisfies the response characteristics of the simulated seabed reflection layer in terms of reflection amplitude, parallel relationship with the seabed, oblique relationship with the stratum reflection axis, and reflection polarity. This reflection interface is then interpreted as the simulated seabed reflection layer. The simulated seabed reflective layer is continuously traced along the survey line to obtain its planar distribution and profile development characteristics within the study area, and the burial depth of the simulated seabed reflective layer is obtained based on the time-depth conversion relationship.

[0006] Optionally, acquiring water depth data of the target sea area and calculating seabed temperature based on the water depth data specifically includes: The water depth of the target sea area is obtained based on the seismic data or three-dimensional seabed topographic bathymetry data. Based on the water depth, it is determined whether the target sea area has measured seabed temperature data. If measured seabed temperature data is available, the seabed temperature is obtained using the measured seabed temperature data. If measured seabed temperature data is not available, an empirical relationship for regional seabed temperature is established based on the measured temperature, salinity, and depth data of the target sea area, and the seabed temperature is calculated based on the water depth and the empirical relationship for regional seabed temperature.

[0007] Optionally, inferring the geothermal gradient of the target sea area based on the burial depth of the simulated seabed reflective layer, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates specifically includes: Calculate the total pressure at the simulated seabed reflective layer based on the water depth and the burial depth of the simulated seabed reflective layer; The temperature at the simulated seabed reflective layer is determined based on the total pressure and the equilibrium temperature-pressure relationship of the natural gas hydrate phase. The geothermal gradient is obtained by dividing the temperature difference between the simulated seabed reflective layer and the seabed temperature by the burial depth of the simulated seabed reflective layer.

[0008] Optionally, the total pressure at the simulated seabed reflective layer is calculated based on the water depth and the burial depth of the simulated seabed reflective layer, using the following formula: P BSR =ρ w gH+ρgZ BSR +P0; Among them, P BSR ρ is the total pressure at the simulated seabed reflective layer. w Let g be the density of seawater, H be the acceleration due to gravity, ρ be the water depth, and Z be the density of sediment. BSR P0 represents the burial depth of the simulated seabed reflective layer and atmospheric pressure.

[0009] Optionally, the interpretation results of the seismic reflection horizons based on the target sea area determine the geological age, and the sedimentation rate is calculated based on the burial depth of the seismic reflection horizons and the geological age, specifically including: Identify the key shallow seismic reflection horizons in the target sea area, and determine the geological age corresponding to the key seismic reflection horizons by combining regional stratigraphic correlation data or chronostratigraphic framework. The deposition rate is obtained by dividing the burial depth of the key seismic reflection layer by its corresponding geological age; or by dividing the difference in burial depth of two comparable layers by their corresponding geological age difference.

[0010] Secondly, this application provides a biogenic gas hydrocarbon generation estimation device, comprising: The distribution feature extraction module is used to acquire seismic data of the target sea area, identify and track the simulated seabed reflector layer based on the seismic data, and obtain the burial depth and distribution characteristics of the simulated seabed reflector layer. The seabed temperature calculation module is used to acquire water depth data of the target sea area and calculate the seabed temperature based on the water depth data. The geothermal gradient inference module is used to infer the geothermal gradient of the target sea area based on the burial depth of the simulated seabed reflector, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates. The sedimentation rate analysis module is used to determine the geological age based on the interpretation results of the seismic reflection horizons of the target sea area, and to calculate the sedimentation rate according to the burial depth of the seismic reflection horizons and the geological age. The hydrocarbon generation estimation module is used to determine the area of ​​the study area based on the distribution characteristics, determine the thickness of the hydrocarbon generation window based on the geothermal gradient and the seafloor temperature, estimate the sediment volume based on the area of ​​the study area and the thickness of the hydrocarbon generation window, and estimate the amount of biogenic gas hydrocarbons based on the sediment volume, the sedimentation rate and hydrocarbon generation potential parameters.

[0011] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the biogenic hydrocarbon generation estimation method described above.

[0012] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the biogenic hydrocarbon generation estimation method described above.

[0013] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the biogenic hydrocarbon generation estimation method described above.

[0014] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method, apparatus, equipment, medium, and product for estimating biogenic hydrocarbon generation. By acquiring seismic data and identifying a simulated seafloor reflector layer, it can quickly obtain the burial depth and distribution characteristics directly related to the geothermal gradient, providing a data foundation for subsequent thermal field inference and avoiding the reliance on well-measured geothermal gradients in traditional methods. Secondly, by acquiring water depth data, it can flexibly choose to directly use measured seafloor temperature data or establish regional empirical relationships based on measured temperature, salinity, and depth data to calculate seafloor temperature, providing accurate upper boundary conditions for geothermal gradient calculation. Thirdly, by combining the burial depth of the simulated seafloor reflector layer, seafloor temperature, and the phase equilibrium relationship of natural gas hydrates, it infers the geothermal gradient. Utilizing the physical significance of the simulated seafloor reflector layer representing the bottom boundary of the natural gas hydrate stability domain, it transforms seismic response characteristics into thermodynamic parameters, enabling rapid inference of regional thermal fields under well-free or few-well conditions, solving the problem of difficulty in obtaining geothermal gradients due to the scarcity of drilling data. Building upon this foundation, geological ages were determined by interpreting seismic reflection horizons and sedimentation rates were calculated, quantitatively characterizing sediment burial rates and organic matter preservation conditions. This provided crucial control for determining gas-producing parameters and organic carbon content in subsequent hydrocarbon generation estimations. Furthermore, by determining the study area based on distribution characteristics, calculating the hydrocarbon generation window thickness according to geothermal gradients and seafloor temperatures, and estimating sediment volume based on the study area area and hydrocarbon generation window thickness, precise location and quantitative calculation of hydrocarbon generation space were achieved, avoiding the errors of homogenization of the entire sedimentary segment in traditional methods. Finally, by combining sediment volume, sedimentation rate, and hydrocarbon generation potential parameters to estimate biogenic gas hydrocarbon generation, multi-factor synergistic quantitative calculations were realized, thus completely resolving the technical problem of insufficient accuracy in biogenic gas hydrocarbon generation estimation caused by the difficulty in obtaining geothermal gradients in existing technologies. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating a method for estimating biogenic hydrocarbon generation in an embodiment of this application; Figure 2 Key stratigraphic layers and seismic interpretation profiles of simulated seafloor reflectors provided in an embodiment of this application; Figure 3This is a schematic diagram of the relationship between the burial depth of the simulated seabed reflector layer and the geothermal gradient provided in an embodiment of this application; Figure 4 A depth distribution map of a temperature window suitable for biological activity provided in an embodiment of this application; Figure 5 A plan view for evaluating and predicting biogenic hydrocarbon generation in an embodiment of this application; Figure 6 A schematic diagram of the functional modules of a biogenic gas hydrocarbon generation estimation device provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] In one exemplary embodiment, such as Figure 1 As shown, a method for estimating biogenic hydrocarbon generation is provided. This method is executed by a computer device, specifically a terminal or server, or both. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps 101 to 206. Wherein: Step 101: Obtain seismic data for the target sea area, identify and trace the simulated seabed reflector layer based on the seismic data, and obtain the burial depth and distribution characteristics of the simulated seabed reflector layer.

[0020] In this embodiment of the application, marine seismic exploration technology is used to observe the target sea area and obtain two-dimensional seismic data, three-dimensional seismic data, or a combination of two-dimensional and three-dimensional seismic data of the target sea area. Figure 2 This diagram shows a cross-section used for seismic interpretation of key stratigraphic layers and simulated seafloor reflectors using the method described in this application. See also... Figure 2 A set of anomalous reflection interfaces with strong reflection amplitudes were identified on the seismic profile. These interfaces were nearly parallel to the seabed interface, obliquely intersecting the reflection axis of normal strata, and exhibiting polarity reversal relative to the seabed reflection. These interfaces were interpreted as the simulated seabed reflection layer L. BSR.

[0021] As an optional implementation, the step of identifying and tracing the simulated seafloor reflector layer based on the seismic data to obtain the burial depth and distribution characteristics of the simulated seafloor reflector layer specifically includes: The seismic data is preprocessed, including amplitude equalization, noise suppression, gather correction, and time-depth conversion preparation. On the seismic profile, a reflection interface is identified that satisfies the response characteristics of the simulated seabed reflection layer in terms of reflection amplitude, parallel relationship with the seabed, oblique relationship with the stratum reflection axis, and reflection polarity. This reflection interface is then interpreted as the simulated seabed reflection layer. The simulated seabed reflective layer is continuously traced along the survey line to obtain its planar distribution and profile development characteristics within the study area, and the burial depth of the simulated seabed reflective layer is obtained based on the time-depth conversion relationship.

[0022] In this embodiment, the seismic data is not limited to two-dimensional, three-dimensional, time-domain, or depth-domain seismic data. When the acquired seismic data is time-domain data, time-depth conversion is also required to obtain the true burial depth of the simulated seafloor reflector layer. For areas with few or no wells, to eliminate the influence of overlying water and sediment compaction on the depth, a layered time-depth conversion method is used to obtain the true burial depth of the simulated seafloor reflector layer. With a given empirical value of 1500 m / s for seawater velocity, the stacked velocity spectrum data from the seismic data processing stage is extracted, and the root mean square velocity V at the seafloor interface is read. RMS1 and the corresponding two-way propagation time t sf and the root mean square velocity V at the interface of the simulated seabed reflector layer. RMS2 and the corresponding two-way propagation time t BSR The root mean square velocity was converted into the layer velocity V of the sedimentary strata between the seabed and the simulated seabed reflector using the Dix formula. int The calculation formula is as follows: ; In this embodiment, the two-way travel time (TWT, the total time it takes for a seismic wave to travel downwards from the epicenter, be reflected by the geological interface, and return to the receiving point) of the simulated seabed reflector is converted into depth, and then the difference between TWT and the water depth is used to obtain the burial depth Z of the simulated seabed reflector. BSR , which indicates the depth of burial below the seabed.

[0023] This implementation method, by identifying simulated seafloor reflective layers using seismic data, can quickly obtain the burial depth and distribution characteristics directly related to the geothermal gradient, providing a data foundation for subsequent thermal field inference. For areas with few or no wells, the layered time-depth conversion method can eliminate the influence of overlying water and sediment compaction on depth, improving the accuracy of burial depth calculations.

[0024] Step 102: Obtain water depth data of the target sea area and calculate seabed temperature based on the water depth data.

[0025] In this embodiment of the application, the water depth H of the target sea area is obtained based on seismic data or three-dimensional seabed topographic bathymetry data. For example... Figure 2 As shown, taking line segment a as an example, the calculation is carried out. The round-trip travel time here is 2400ms. The seismic data is in the time domain. Time-depth conversion is performed. The seawater velocity is 1500m / s, and the water depth is obtained as H=1500×2.4 / 2=1800m.

[0026] As an optional implementation, the step of acquiring water depth data of the target sea area and calculating seabed temperature based on the water depth data specifically includes: The water depth of the target sea area is obtained based on the seismic data or three-dimensional seabed topographic bathymetry data. Based on the water depth, it is determined whether the target sea area has measured seabed temperature data. If measured seabed temperature data is available, the seabed temperature is obtained using the measured seabed temperature data. If measured seabed temperature data is not available, an empirical relationship for regional seabed temperature is established based on the measured temperature, salinity, and depth data of the target sea area, and the seabed temperature is calculated based on the water depth and the empirical relationship for regional seabed temperature.

[0027] Specifically, for the mid-deep water continental slope and deep-water basin areas of the northern continental margin of the South China Sea, the empirical formula derived by Chi and Reed (2008) in Liao's (2014) paper, based on a database of measured water depths covering different depths in the northern continental margin of the South China Sea, can be used to calculate seabed temperature. This formula is applicable to the calculation of seabed temperature in the mid-deep water continental slope and deep-water basin areas of the northern continental margin of the South China Sea. The empirical formula is: T sf =0.2597×(lnH) 3 -3.802×(lnH) 2 +10.67×lnH+26.96 Where H is the water depth, and T sf Let T be the seabed temperature. Based on the above formula, T is obtained. sf =2.7℃. For areas outside the applicable range of the aforementioned empirical relationship, it is preferable to use measured seabed temperature data, or to re-establish the regional seabed temperature empirical relationship based on measured temperature, salinity, and depth data of the target sea area.

[0028] This implementation method, by using an empirical formula applicable to the target sea area to calculate the seabed temperature, can obtain a relatively accurate seabed temperature without relying on measured data, providing a reliable upper boundary condition for calculating the geothermal gradient and reducing data acquisition costs.

[0029] Step 103: Based on the burial depth of the simulated seabed reflective layer, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates, infer the geothermal gradient of the target sea area.

[0030] In this embodiment of the application, the core idea of ​​this step is as follows: first, calculate the total pressure at the simulated seabed reflector layer; then, calculate the temperature at the simulated seabed reflector layer based on the phase equilibrium relationship of natural gas hydrates; and finally, calculate the regional geothermal gradient by combining the seabed temperature and the burial depth of the simulated seabed reflector layer.

[0031] As an optional implementation, the step of inferring the geothermal gradient of the target sea area based on the burial depth of the simulated seabed reflector, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates specifically includes: Calculate the total pressure at the simulated seabed reflective layer based on the water depth and the burial depth of the simulated seabed reflective layer; The temperature at the simulated seabed reflective layer is determined based on the total pressure and the equilibrium temperature-pressure relationship of the natural gas hydrate phase. The geothermal gradient is obtained by dividing the temperature difference between the simulated seabed reflective layer and the seabed temperature by the burial depth of the simulated seabed reflective layer.

[0032] In this embodiment of the application, the burial depth Z of the simulated seabed reflective layer is obtained based on the simulated seabed reflective layer explained in step 101. BSR The pressure at the simulated seabed reflector layer is determined by considering the water depth. This pressure is divided into three parts: atmospheric pressure, the pressure of the overlying seawater, and the pressure of the sediments overlying the simulated seabed reflector layer. The total pressure at the simulated seabed reflector layer is calculated using the following formula: P BSR =ρ w gH+ρgZ BSR +P0 Where P BSR ρ represents the total pressure of the formation at the simulated seafloor reflector layer. w ρ is the density of seawater, ρ is the density of sediments in the stable zone, g is the acceleration due to gravity, H is the water depth, and Z is the density of seawater. BSR Let P0 be the depth of the simulated seabed reflector layer, and P0 be the atmospheric pressure. In the above formula, the first term ρ... w gH represents the hydrostatic pressure exerted by the seawater column on the simulated reflective layer on the seabed. The second term ρgZ BSR The first term represents the formation pressure exerted by the overlying sediments below the seabed on the simulated seabed reflector layer. The third term, P0, represents the atmospheric pressure at sea level. The total pressure P at the simulated seabed reflector layer is obtained by adding these three terms. BSR In practical applications, seawater density and sediment density can be determined by measured values ​​or by empirical values ​​commonly used in the study area. In this embodiment, the seawater density is given as an empirical value of 1.3 g / cm³. 3The sediment density, obtained through seismic inversion, is 2.6 g / cm³. 3 Based on a water depth of H=1800m and the simulated seabed reflector depth Z... BSR =420m, substituting into the formula, we get P. BSR = 29.29MPa.

[0033] In this embodiment of the application, after obtaining the total pressure at the simulated seabed reflector layer, the temperature T at the simulated seabed reflector layer is determined based on the equilibrium temperature-pressure relationship of natural gas hydrate phase. BSR .

[0034] As an optional implementation method, the following formula is adopted: When 3.14MPa <P BSR When <9.94MPa, T BSR =8245 / (33.4-Ln(P BSR / P0))-273.15; When 9.94MPa <P BSR When <56MPa, T BSR =10602 / (41.636-Ln(P BSR / P0))-273.15; Where T BSR The temperature P at the simulated reflective layer on the seabed BSR Let P0 be the total pressure at the simulated seafloor reflector layer, and P0 be the atmospheric pressure. Based on the calculated pressure P0... BSR =29.29MPa, select a suitable temperature-pressure formula to calculate the temperature, and substitute it into the formula to get T. BSR =21.6℃.

[0035] In this embodiment of the application, when obtaining the seabed temperature T sf Temperature T at the simulated seabed reflector layer BSR and the burial depth Z of the simulated seabed reflector BSR Next, the regional geothermal gradient Tg is calculated using the following formula: Tg=(T BSR -T sf ) / Z BSR ; T BSR =21.6℃, T sf =2.7℃, Z BSR Substituting 420m into the formula, we obtain the geothermal gradient Tg = 45℃ / km. For example... Figure 3 As shown, a model of the relationship between the burial depth of the simulated seabed reflector layer and the geothermal gradient is presented. The horizontal axis represents the geothermal gradient, and the vertical axis represents the burial depth of the simulated seabed reflector layer. The two show a positive correlation.

[0036] This implementation method, by combining the burial depth of the simulated seafloor reflector, seafloor temperature, and the phase equilibrium relationship of natural gas hydrates, infers the geothermal gradient. The simulated seafloor reflector represents the physical boundary of the natural gas hydrate stability domain, transforming seismic response characteristics into thermodynamic parameters. This enables rapid inference of the regional thermal field under well-less or low-well conditions, significantly improving the efficiency and feasibility of geothermal gradient acquisition. By calculating and summing the pressure separately from the hydrostatic pressure of the sea column, the pressure of the overlying sediments, and atmospheric pressure, the actual pressure state at the simulated seafloor reflector can be more accurately reflected, improving the accuracy of geothermal gradient inference.

[0037] Step 104: Determine the geological age based on the interpretation results of the seismic reflection horizons in the target sea area, and calculate the sedimentation rate based on the burial depth of the seismic reflection horizons and the geological age.

[0038] In this embodiment of the application, key shallow seismic reflection horizons in the study area are first identified, and then, in conjunction with regional stratigraphic correlation data or a chronostratigraphic framework, the geological age corresponding to these horizons is determined. For example... Figure 2 As shown, the deposition rate was calculated using the key layer L1 as interpreted. Due to significant tectonic alteration in this region, Figure 2 In this context, 'a' represents the apparent thickness of the strata. When calculating the deposition rate, the true thickness of the strata should be used. Figure 2 In this case, b represents the true thickness of stratum L1, which can be obtained using the formula b = a × sinθ. Figure 2 L1 is the top of the Pliocene strata, corresponding to a geological age of 2.58 Ma. The apparent thickness 'a' of L1, after time-depth conversion and subtraction of the seawater depth, is 3000 m. The included angle 'θ' is measured to be approximately 20.5° in the figure. b = a × sinθ = 1050 m.

[0039] As an optional implementation, the interpretation results of the seismic reflection horizons based on the target sea area determine the geological age, and the sedimentation rate is calculated based on the burial depth of the seismic reflection horizons and the geological age, specifically including: Identify the key shallow seismic reflection horizons in the target sea area, and determine the geological age corresponding to the key seismic reflection horizons by combining regional stratigraphic correlation data or chronostratigraphic framework. The deposition rate is obtained by dividing the burial depth of the key seismic reflection layer by its corresponding geological age; or by dividing the difference in burial depth of two comparable layers by their corresponding geological age difference.

[0040] If the seismic data is in the time domain, a time-depth conversion needs to be performed using a seismic velocity model, and then the seawater depth needs to be subtracted to obtain the current burial depth of the stratum, in order to estimate the average sedimentation rate of the target stratum. When the interpreted stratum L1 can be traced to existing wells, boreholes, core samples, or publicly drilled points in the adjacent area, and its age t1 is determined by a biostratigraphic, magnetostratigraphic, or regional chronostratigraphic framework, the age is calculated according to V=Depth. L1 / t1 calculation. When direct dating results are lacking for interpretable stratum L1, the two adjacent strata L2 and L3 are preferred, with corresponding ages t2 and t3, and burial depths converted to time depths of t1 and t3, respectively. L2 Depth L3 The average deposition rate of this layer is calculated as V=(Depth L3 -Depth L2 ) / (t3-t2) is used for calculation. Where V is the deposition rate, and Depth... L1 t1 represents the burial depth of layer L1, and t1 represents the geological age corresponding to layer L1. L2 t2 represents the burial depth of layer L2, and t2 represents the geological age corresponding to layer L2. L3 t3 represents the burial depth of layer L3, and t3 represents the geological age corresponding to layer L3.

[0041] In this embodiment, the sedimentation rate characterizes the burial rate of sediments and the preservation conditions of organic matter, and is one of the important control parameters for subsequent quantitative evaluation of hydrocarbon generation. In this application, a sedimentation rate greater than 300 m / Ma is considered suitable for the development of biogenic gas source rocks. In this embodiment, substituting into the formula V=1050 / 2.58=407 m / Ma, it meets the conditions for the development of biogenic gas source rocks.

[0042] This implementation method, by interpreting seismic reflection horizons and calculating depositional rates, quantitatively characterizes sediment burial rates and organic matter preservation conditions, providing key control parameters for hydrocarbon generation assessment. Different depositional rate calculation formulas are used for different geological conditions, applicable to both horizons with available dating data and those lacking direct dating results, thus improving the method's applicability and flexibility.

[0043] Step 105: Determine the area of ​​the study area based on the distribution characteristics, determine the thickness of the hydrocarbon generation window based on the geothermal gradient and the seafloor temperature, and estimate the sediment volume based on the area of ​​the study area and the thickness of the hydrocarbon generation window.

[0044] In this embodiment of the application, based on the distribution characteristics of the simulated seabed reflective layer obtained in step 101, the planar distribution range of the simulated seabed reflective layer in the study area is determined, thereby determining the area S of the study area.

[0045] In this embodiment of the application, the seabed temperature T obtained according to the above steps is... sf and regional geothermal gradient T g The appropriate temperature window for microbial activity is determined. In this application, as an optional implementation, the temperature range for biological activity is given as 15°C to 75°C based on theoretical experience. Figure 4 The diagram shows the depth distribution of suitable temperature windows for biological activity. The vertical axis represents depth, and the horizontal axis represents temperature. The shaded areas mark the depth range corresponding to temperature windows of 15°C to 75°C for biological activity. Based on the seabed temperature and the geothermal gradient, the preset suitable temperature windows for microbial activity are converted into corresponding burial depth ranges, thereby determining the hydrocarbon generation window thickness ΔZ in the study area. In this embodiment, ΔZ represents the effective thickness of the layer suitable for microbial activity and possessing biogenic gas generation potential within the study area, ranging from approximately 500 to 1000 m.

[0046] In this embodiment, the microbial activity space is then calculated based on the study area S. The area unit for calculating the biological activity space is m². 2 The thickness is measured in meters (m). A double integral is performed to calculate the volume of sediment suitable for biological activity. This is achieved by performing a double integral on the stratigraphic thickness function over a known planar area region; that is, by summing the area-weighted thicknesses of the stratigraphic layers at each point within the region. The thickness function can be obtained on a computer, and the double integral can also be performed on a computer. For example... Figure 5 The diagram shown is a plan view for evaluating and predicting biogenic hydrocarbon generation according to an embodiment of this application, with an area of ​​1.269 × 10⁻⁶. 10 m 2 In the planar diagram, different gray areas represent the differences in the planar distribution of biogenic hydrocarbon generation. The sediment volume determined in this embodiment is 7.0529 × 10⁻⁶. 12 m 3 .

[0047] This implementation method determines the study area based on distribution characteristics, calculates the thickness of the hydrocarbon-generating window according to geothermal gradients and seafloor temperatures, and estimates the sediment volume of the effective hydrocarbon-generating layer accordingly. This achieves precise positioning of the hydrocarbon-generating space and avoids the errors caused by homogenizing the entire sedimentary layer in traditional methods. Calculating the sediment volume using double integrals more accurately reflects the contribution of thickness variations at different locations within the study area to the total volume, thus improving the accuracy of volume estimation.

[0048] Step 106: Estimate the biogenic hydrocarbon generation based on the sediment volume, the sedimentation rate, and the hydrocarbon generation potential parameters.

[0049] In this embodiment, after obtaining the effective area S of the study area, the hydrocarbon generation window thickness ΔZ, the hydrocarbon generation conditions under deposition rate control, and the hydrocarbon generation potential parameters, the amount of hydrocarbons generated by biogenic gas is quantitatively estimated. This embodiment uses the following formula: Q = S × ΔZ × Pg × TOC; Where Q represents the estimated hydrocarbon generation from biogenic gas, and S represents the area of ​​the study area in m². 2 ΔZ represents the hydrocarbon generation window thickness in meters (m), TOC represents the organic carbon content, and Pg represents the comprehensive biogenic gas production parameters per unit area, unit thickness, and unit organic carbon content, in units of 10⁻⁶. -6 bcf / m 2 / m / %Toc, meaning that under the conditions of 1 square meter area, 1 meter thickness, and 1% TOC, the biogenic gas production in this area is equivalent to 10. -6 BCF is a standard industry unit for assessing natural gas resources / reserves, referring to one billion cubic feet.

[0050] In this embodiment, the Pg is preferably determined through anaerobic incubation experiments of shallow sediment samples; in the absence of experimental and calibration data, a preliminary value can also be assigned based on analogous parameters from neighboring areas or the theoretical gas production capacity range. TOC is preferably obtained using geochemical parameters when core samples are available. For areas with low exploration levels, TOC values ​​from adjacent basins with the same sedimentary background can be used, or predicted using seismic inversion methods. Pre-stack inversion is performed on seismic data of the target area to obtain the P-wave impedance and sediment density of the target layer. A TOC conversion model is established using the classic Schmoker density-TOC empirical physical model: TOC = a / ρ b +b, where ρ b is the sediment density obtained from seismic inversion, and a and b are regional empirical constants for fitting measured rock physical parameters of adjacent similar basins, which can be changed according to the actual region and actual situation.

[0051] In this embodiment, the biogenic hydrocarbon generation is calculated based on the parameters obtained in the above steps. Specifically, the study area is 1.269 × 10⁻⁶. 10 m 2 m 2 The hydrocarbon generation window thickness ranges from 500 to 1000 μm, the total organic carbon (TOC) content is 0.5%, and the hydrocarbon generation potential, i.e., the gas production parameter Pg, is specifically valued at 0.2 × 10⁻⁶ based on experimental data. -6 bcf / m 2 / m / %Toc. Substituting the above parameters into the formula Q=S×ΔZ×Pg×TOC, the biogenic hydrocarbon generation in this embodiment is calculated to be approximately 1.997×10. 13 m 3.

[0052] Table 1. Calculation of Hydrocarbon Production from Biogenic Gases

[0053] In practice, Pg and TOC can be assigned values ​​to different zones based on parameter differences in different blocks and sedimentary facies zones. Then, the hydrocarbon generation in each zone can be calculated separately and summed to obtain the total hydrocarbon generation for the entire zone. If SI units are required, the results can be converted from bcf to standard cubic meters after the calculation is completed.

[0054] This implementation method estimates biogenic hydrocarbon generation by combining sediment volume and hydrocarbon generation potential parameters, achieving quantitative calculations based on multiple factors. For areas with few or no wells in low-exploration areas, it provides various methods for obtaining gas production parameters and organic carbon content, enabling more efficient and accurate prediction of biogenic hydrocarbon generation and improving the accuracy of resource assessment in low-exploration areas.

[0055] Steps 101 to 106 above, by acquiring seismic data and identifying simulated seafloor reflectors, can quickly obtain the burial depth and distribution characteristics directly related to the geothermal gradient, providing a data foundation for subsequent thermal field inference. Calculating seafloor temperature using water depth data provides accurate upper boundary conditions for determining the geothermal gradient. By combining the burial depth of the simulated seafloor reflector, seafloor temperature, and the phase equilibrium relationship of natural gas hydrates, the geothermal gradient is inferred. The simulated seafloor reflector represents the physical boundary of the stable domain of natural gas hydrates, transforming seismic response characteristics into thermodynamic parameters, enabling rapid inference of the regional thermal field under well-less or low-well conditions. Based on this, by interpreting the seismic reflector horizon and calculating the deposition rate, the burial rate of sediments and organic matter preservation conditions are quantitatively characterized. Furthermore, by determining the study area based on distribution characteristics, determining the thickness of the hydrocarbon generation window according to the geothermal gradient and seafloor temperature, and estimating the sediment volume of the effective hydrocarbon generation zone, the precise location of the hydrocarbon generation space is achieved. Finally, by combining sediment volume and hydrocarbon generation potential parameters to estimate biogenic gas hydrocarbon generation, a multi-factor synergistic quantitative calculation was achieved, thus completely solving the technical problem of insufficient accuracy in estimating biogenic gas hydrocarbon generation due to the difficulty in obtaining geothermal gradients in existing technologies.

[0056] Based on the same inventive concept, this application also provides a biogenic gas hydrocarbon generation estimation device for implementing the above-mentioned biogenic gas hydrocarbon generation estimation method. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more biogenic gas hydrocarbon generation estimation device embodiments provided below can be found in the limitations of the biogenic gas hydrocarbon generation estimation method above, and will not be repeated here.

[0057] In one exemplary embodiment, such as Figure 6 As shown, a biogenic hydrocarbon generation estimation device is provided, comprising: The distribution feature extraction module 201 is used to acquire seismic data of the target sea area, identify and track the simulated seabed reflector layer based on the seismic data, and obtain the burial depth and distribution characteristics of the simulated seabed reflector layer. The seabed temperature calculation module 202 is used to acquire water depth data of the target sea area and calculate the seabed temperature based on the water depth data. The geothermal gradient inference module 203 is used to infer the geothermal gradient of the target sea area based on the burial depth of the simulated seabed reflective layer, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates. The sedimentation rate analysis module 204 is used to determine the geological age based on the interpretation results of the seismic reflection horizon of the target sea area, and to calculate the sedimentation rate according to the burial depth of the seismic reflection horizon and the geological age. The hydrocarbon generation estimation module 205 is used to determine the area of ​​the study area based on the distribution characteristics, determine the thickness of the hydrocarbon generation window based on the geothermal gradient and the seafloor temperature, estimate the sediment volume based on the area of ​​the study area and the thickness of the hydrocarbon generation window, and estimate the amount of biogenic gas hydrocarbons based on the sediment volume, the sedimentation rate and hydrocarbon generation potential parameters.

[0058] This implementation method, through the collaborative work of various modules, can automatically complete data input, calculation and result output, thereby improving the efficiency of estimating biogenic hydrocarbon generation based on simulated seabed reflector layers.

[0059] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 7 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores biogenic hydrocarbon generation estimation data. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the biogenic hydrocarbon generation estimation method.

[0060] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0061] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0062] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0063] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0064] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0065] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0066] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0067] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for estimating biogenic hydrocarbon generation, characterized in that, The method for estimating biogenic hydrocarbon generation includes: Seismic data of the target sea area is acquired, and the seabed simulated reflective layer is identified and traced based on the seismic data to obtain the burial depth and distribution characteristics of the seabed simulated reflective layer. Acquire water depth data for the target sea area, and calculate seabed temperature based on the water depth data; Based on the burial depth of the simulated seabed reflector, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates, the geothermal gradient of the target sea area is inferred. The geological age is determined based on the interpretation results of the seismic reflection horizons in the target sea area, and the sedimentation rate is calculated based on the burial depth of the seismic reflection horizons and the geological age. The area of ​​the study area is determined based on the distribution characteristics, the thickness of the hydrocarbon generation window is determined based on the geothermal gradient and the seafloor temperature, and the sediment volume is estimated based on the area of ​​the study area and the thickness of the hydrocarbon generation window. The biogenic hydrocarbon generation is estimated based on the sediment volume, the sedimentation rate, and the hydrocarbon generation potential parameters.

2. The method for estimating biogenic hydrocarbon generation according to claim 1, characterized in that, The process of identifying and tracing the simulated seafloor reflector layer based on the seismic data, and obtaining the burial depth and distribution characteristics of the simulated seafloor reflector layer, specifically includes: The seismic data is preprocessed, including amplitude equalization, noise suppression, gather correction, and time-depth conversion preparation. On the seismic profile, a reflection interface is identified that satisfies the response characteristics of the simulated seabed reflection layer in terms of reflection amplitude, parallel relationship with the seabed, oblique relationship with the stratum reflection axis, and reflection polarity. This reflection interface is then interpreted as the simulated seabed reflection layer. The simulated seabed reflective layer is continuously traced along the survey line to obtain its planar distribution and profile development characteristics within the study area, and the burial depth of the simulated seabed reflective layer is obtained based on the time-depth conversion relationship.

3. The method for estimating biogenic hydrocarbon generation according to claim 1, characterized in that, The acquisition of water depth data for the target sea area and the calculation of seabed temperature based on the water depth data specifically include: The water depth of the target sea area is obtained based on the seismic data or three-dimensional seabed topographic bathymetry data. Based on the water depth, it is determined whether the target sea area has measured seabed temperature data. If measured seabed temperature data is available, the seabed temperature is obtained using the measured seabed temperature data. If measured seabed temperature data is not available, an empirical relationship for regional seabed temperature is established based on the measured temperature, salinity, and depth data of the target sea area, and the seabed temperature is calculated based on the water depth and the empirical relationship for regional seabed temperature.

4. The method for estimating biogenic hydrocarbon generation according to claim 3, characterized in that, The inference of the geothermal gradient of the target sea area based on the burial depth of the simulated seabed reflector, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates specifically includes: Calculate the total pressure at the simulated seabed reflective layer based on the water depth and the burial depth of the simulated seabed reflective layer; The temperature at the simulated seabed reflective layer is determined based on the total pressure and the equilibrium temperature-pressure relationship of the natural gas hydrate phase. The geothermal gradient is obtained by dividing the temperature difference between the simulated seabed reflective layer and the seabed temperature by the burial depth of the simulated seabed reflective layer.

5. The method for estimating biogenic hydrocarbon generation according to claim 4, characterized in that, The total pressure at the simulated seabed reflective layer is calculated based on the water depth and the burial depth of the simulated seabed reflective layer, using the following formula: P BSR =p w gH+ρgZ BSR +P0; Among them, P BSR ρ is the total pressure at the simulated seabed reflective layer. w Let g be the density of seawater, H be the acceleration due to gravity, ρ be the water depth, and Z be the density of sediment. BSR P0 represents the burial depth of the simulated seabed reflective layer and atmospheric pressure.

6. The method for estimating biogenic hydrocarbon generation according to claim 1, characterized in that, The interpretation results of the seismic reflection horizons based on the target sea area determine the geological age, and the sedimentation rate is calculated based on the burial depth of the seismic reflection horizons and the geological age, specifically including: Identify the key shallow seismic reflection horizons in the target sea area, and determine the geological age corresponding to the key seismic reflection horizons by combining regional stratigraphic correlation data or chronostratigraphic framework. The deposition rate is obtained by dividing the burial depth of the key seismic reflection layer by its corresponding geological age; or by dividing the difference in burial depth of two comparable layers by their corresponding geological age difference.

7. A biogenic hydrocarbon generation estimation device, characterized in that, The biogenic hydrocarbon generation estimation device includes: The distribution feature extraction module is used to acquire seismic data of the target sea area, identify and track the simulated seabed reflector layer based on the seismic data, and obtain the burial depth and distribution characteristics of the simulated seabed reflector layer. The seabed temperature calculation module is used to acquire water depth data of the target sea area and calculate the seabed temperature based on the water depth data. The geothermal gradient inference module is used to infer the geothermal gradient of the target sea area based on the burial depth of the simulated seabed reflector, the seabed temperature, and the phase equilibrium relationship of natural gas hydrates. The sedimentation rate analysis module is used to determine the geological age based on the interpretation results of the seismic reflection horizons of the target sea area, and to calculate the sedimentation rate according to the burial depth of the seismic reflection horizons and the geological age. The hydrocarbon generation estimation module is used to determine the area of ​​the study area based on the distribution characteristics, determine the thickness of the hydrocarbon generation window based on the geothermal gradient and the seafloor temperature, estimate the sediment volume based on the area of ​​the study area and the thickness of the hydrocarbon generation window, and estimate the amount of biogenic gas hydrocarbons based on the sediment volume, the sedimentation rate and hydrocarbon generation potential parameters.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the biogenic hydrocarbon generation estimation method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the biogenic hydrocarbon generation estimation method according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the biogenic hydrocarbon generation estimation method according to any one of claims 1-6.

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