A method for calculating the bubble size in an underwater porous medium formation

Abstract

The present invention discloses a method for calculating the bubble size of an underwater pore medium formation, which relates to the technical field of geophysical exploration of underwater pore medium formations, and includes: S1, obtaining the petrophysical parameters of the underwater formation to be measured; S2, deploying a sound wave transmitting transducer and a receiver at the measurement point, the sound wave transmitting transducer emits a set signal to determine the measurement frequency range, and the receiver records the sound wave velocity and attenuation coefficient at each frequency point; S3, determining whether there are adjacent frequency points that satisfy the condition that the sound wave velocity decreases and the attenuation coefficient increases. If so, re-measure and extract the sound wave velocity and attenuation coefficient corresponding to the bubble resonance characteristics; otherwise, record the number of times without bubble characteristics. If the number of times does not reach the threshold, continue to adjust the number of frequency points and then return to step 2; S4, constructing an objective function; S5, under the condition that the angular frequency and the sound wave velocity are known, solving the independent variable, bubble radius and bubble saturation that minimize the objective function, and determining the final bubble size and saturation.

Description

Technical Field

[0001] The invention belongs to the technical field of geophysical detection of underwater porous medium strata, and in particular relates to a method for calculating bubble size in underwater porous medium strata. Background Art

[0002] The size of bubbles in underwater porous media has important scientific significance and practical application value. The size of bubbles in seafloor porous media can reveal the stability and decomposition dynamics of natural gas hydrates, providing key parameters for resource reserve assessment; at the same time, the bubble size characteristics can indicate the deep oil and gas leakage path, optimize acoustic exploration technology, improve the accuracy of seafloor resource detection, and provide a scientific basis for carbon sequestration safety assessment. The size of bubbles directly regulates the release flux of greenhouse gases such as methane: small bubbles dissolve in water to slow down emissions, and large bubbles go directly to the atmosphere to intensify warming. Studying its distribution law can improve the global carbon cycle model, and at the same time reveal the impact of bubble release on seafloor acidification, microbial activity and ecosystems, providing theoretical support for ecological protection. Bubble aggregation can reduce sediment strength and induce submarine landslides. Its size monitoring can build a disaster warning system; in the engineering field, bubble size affects pipeline cavitation rate, platform foundation stability and resource extraction efficiency. The research results can provide key technical parameters for deep-sea engineering safety design and ecological risk prevention and control.

[0003] In summary, the study of bubble size in underwater porous medium formations is a core topic in the fields of geophysical exploration, environmental assessment and marine engineering safety. The existing technical system and bottlenecks mainly include: experimental characterization technology: using micro-CT imaging combined with image segmentation algorithm to extract bubble morphology, or using acoustic inversion (such as Biot-Stoll model) to infer the bubble equivalent radius, but limited by laboratory conditions and model parameters are difficult to obtain, it is impossible to simulate the underwater formation environment; numerical simulation method: simulating bubble migration based on pore network model or discrete bubble dynamics, but the cross-scale coupling algorithm is not yet mature; in-situ observation technology: relying on laser diffraction sensors, resistivity tomography (ERT) and other equipment to obtain bubble distribution, but the underwater formation environment causes severe attenuation of optical signals and complex interference, and there is a lack of long-term continuous observation data. The above limitations have seriously hindered the in-depth study of the stability assessment of submarine natural gas hydrates, the analysis of greenhouse gas release mechanisms and the risk prevention and control of submarine engineering. The existing patents analyze the bubble saturation of underwater formations, but do not involve bubble size assessment. Therefore, it is urgent to develop new technical solutions to overcome the difficulties in accurate characterization and dynamic monitoring of bubble size in underwater formations.

[0004] The research finds that when the formation acoustic signal approaches the bubble resonance frequency, the sound speed first drops sharply to a minimum value with the increase of frequency, and then rises sharply to a peak value. The acoustic wave attenuation coefficient shows a significant peak at the bubble resonance frequency, with a sharp peak shape and the largest amplitude. Moreover, the frequency at the sound speed peak is always lower than the frequency at the attenuation peak. This phenomenon is directly related to the change of the bubble's phase response. And the bubble resonance frequency is extremely sensitive to the response of the bubble radius. Therefore, the present invention proposes a method for calculating the bubble size in the bottom water pore medium formation, mainly solving the technical problem that the prior art cannot evaluate the bubble size in the seabed formation. Summary of the Invention

[0005] To solve the above technical problems, the present invention proposes a method for calculating the bubble size in the bottom water pore medium formation, which can quickly identify the bubble-free area through a threshold judgment mechanism, reduce the ineffective exploration cost, and improve the operation efficiency.

[0006] To achieve the above object, the present invention provides a method for calculating the bubble size in the bottom water pore medium formation, including:

[0007] S1. Obtain the petrophysical parameters of the bottom water formation to be measured through geological surveys;

[0008] S2. Deploy an acoustic wave transmitting transducer and a receiver at the point to be measured. The acoustic wave transmitting transducer emits a set signal to determine the measurement frequency range, and the receiver records the acoustic wave velocity and attenuation coefficient at each frequency point;

[0009] S3. Judge whether there are adjacent frequency points that satisfy the conditions that the acoustic wave velocity decreases and the attenuation coefficient increases. If so, reset the maximum frequency point and reduce the step size to 1 / 10 of the original step size, and re-measure and extract the acoustic wave velocity and attenuation coefficient corresponding to the bubble resonance characteristics; otherwise, record the number of times of no bubble characteristics. If the number of times does not reach the threshold, continue to adjust the number of frequency points and then return to step 2;

[0010] S4. Construct an objective function;

[0011] S5. Under the known conditions of angular frequency and acoustic wave velocity, use the grid division method to solve the independent variable, bubble radius, and bubble saturation degree that minimize the objective function, and determine the final bubble size and saturation degree.

[0012] Optionally, the measurement frequency range is , , , where is the step size, is the number of frequency points.

[0013] Optionally, the objective function includes:

[0014] ;

[0015] Among them, is the objective function; and are the weights respectively; is the frequency corresponding to the starting point of the attenuation coefficient under the current working condition, that is, the place where the attenuation coefficient suddenly increases; is the theoretical formula for calculating the bubble resonance frequency under the current working condition; is the theoretical formula for calculating the bottom formation velocity under the current working condition; is the acoustic velocity with bubble resonance characteristics.

[0016] Optionally, the theoretical formula for calculating the bubble resonance frequency under the current working condition includes:

[0017] ;

[0018] Among them, is the specific heat ratio of the gas in the bubble; is the hydrostatic pressure of the formation; is the equivalent density of the current formation; is the equivalent density of the gas in the bubble; is the pore fluid density; is the formation skeleton density; is the current formation shear modulus; is the angular frequency, is the specific heat of the gas at constant pressure, is the thermal conductivity of the gas.

[0019] Optionally, the theoretical formula for calculating the bottom formation velocity under the current working condition includes:

[0020] ;

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] ;

[0026] ;

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] ;

[0032] ;

[0033] Among them, is the bubble saturation; is the gas volume modulus in the bubble; is the pore liquid volume modulus; is the particle volume modulus of the formation skeleton; is the formation skeleton volume modulus.

[0034] Optionally, during grid meshing, the independent variable, bubble radius, and bubble saturation corresponding to the minimum objective function are equally divided by step lengths respectively. Each variable is divided into N equal parts where N is not less than 20, and the objective function is calculated at the nodes, and the node corresponding to the minimum value is selected as the initial solution.

[0035] Optionally, the adjacent eight units of the grid where the initial solution is located are further subdivided into N equal parts, and after recalculating the objective function, the node with the minimum value is selected as the final solution.

[0036] Optionally, in S3, if bubble resonance characteristics exist at all frequency points, the formation velocity takes the maximum value of the measured values as the average acoustic velocity.

[0037] Technical effects of the present invention: The present invention discloses a method for calculating the bubble size of an underwater porous medium formation. By using an acoustic wave transmitting transducer to emit a specific pulse signal, the acoustic wave velocity and attenuation coefficient at different frequencies are measured. Utilizing the characteristics that the acoustic velocity first drops sharply and then rises near the bubble resonance frequency, and the attenuation coefficient changes in the opposite way, a target function including the theoretical resonance frequency and the theoretical formation velocity is constructed. Through the grid meshing optimization algorithm, under the condition of minimizing the error of the target function, the bubble saturation, bubble radius, and resonance frequency are inversely calculated simultaneously. The present invention innovatively combines acoustic characteristics with porous medium theory, providing a reliable means for quantitatively evaluating bubble parameters for submarine resource exploration, submarine gas storage, and geological disaster warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings forming a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation to this application. In the drawings:

[0039] Figure 1 is a schematic flow chart of a method for calculating the bubble size of an underwater porous medium formation according to an embodiment of the present invention;

[0040] Figure 2 Schematic diagram showing the variation characteristics of the normalized acoustic wave velocity, attenuation coefficient, and resonance frequency of the embodiments of the present invention with frequency in the bubble resonance frequency range. Detailed implementation manners

[0041] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The following will describe the present application in detail with reference to the drawings and in combination with the embodiments.

[0042] It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0043] As Figure 1 shown, a method for calculating the bubble size of an underwater pore medium formation is provided in this embodiment, including:

[0044] Step 1: Conduct a geological survey to determine the petrophysical parameters of the underwater formation to be measured;

[0045] Step 2: At the point to be measured in the underwater formation, the acoustic wave transmitting transducer emits a pulse signal with a pulse width of and an amplitude of . The measurement frequency range is , the step size is , and the number of frequency points is greater than 3;

[0046] , ;

[0047] The acoustic wave signal receiver is placed in the underwater formation pointed by the acoustic wave transmitting transducer, and the distance from the transmitter is greater than one wavelength. Record the received signal at each frequency point to obtain the acoustic wave velocity and the attenuation coefficient ;

[0048] Step 3: Determine whether there are adjacent frequency points where both the acoustic wave velocity decreases and the attenuation coefficient increases. Here, adjacent frequency points refer to those with a frequency point serial number difference of 1;

[0049] If so, splice all adjacent frequency points together in sequence, find the maximum frequency point and the minimum frequency point, return to Step 2, assign the maximum frequency point to in Step 2, reduce the step size to make the number of frequency points become ten times the original, re-measure and calculate, extract the acoustic wave velocity and the attenuation coefficient with bubble resonance characteristics, and extract the frequency corresponding to the starting point of the attenuation coefficient., the acoustic wave velocities without bubble resonance characteristics are averaged and denoted as , if all frequency points have bubble resonance characteristics, then take the maximum value of all measured velocities and proceed to step 4;

[0050] If not, record the number of non-existences nongas. If nongas is less than the given threshold Maxnongas, return to step 2 and change the number of frequency points to 10 times. If the number of non-existences is equal to the given threshold Maxnongas, end this measurement, indicating that there are no bubbles in the bottom formation within the measured frequency range.

[0051] Step 4: Construct the error and objective function. The errors here include: the error between the measured velocity and the theoretical velocity, and the error between the bubble resonance frequency and the theoretical frequency;

[0052] The objective function is defined as:

[0053] ;

[0054] where is the frequency corresponding to the starting point of the attenuation coefficient under the current working condition, that is, the place where the attenuation coefficient suddenly increases, is the theoretical formula for calculating the bubble resonance frequency under the current working condition; is the theoretical formula for calculating the velocity of the bottom formation under the current working condition, and are weights;

[0055] The theoretical formula for the bubble resonance frequency under the current working condition is taken as:

[0056] ;

[0057] where is the specific heat ratio of the gas in the bubble, is the hydrostatic pressure of the formation; is the equivalent density of the current formation; is the equivalent density of the gas in the bubble; is the pore fluid density; is the formation skeleton density; is the shear modulus of the current formation; angular frequency , is the specific heat of the gas at constant pressure, is the thermal conductivity of the gas;

[0058] The theoretical formula for the formation velocity under the current working condition is taken as:

[0059] ;

[0060] ;

[0061] ;

[0062] ;

[0063] ;

[0064] ;

[0065] ;

[0066] ;

[0067] ;

[0068] ;

[0069] ;

[0070] ;

[0071] ;

[0072] Among them, is the bubble saturation; is the gas volume modulus in the bubble, is the pore liquid volume modulus; is the particle volume modulus that constitutes the formation skeleton; is the formation skeleton volume modulus;

[0073] Step 5. Based on the known data and , under the condition of minimizing the objective function value Error, solve the independent variables and ;

[0074] Given a reasonable value range for the independent variables, and , perform an equal-step grid division of N equal parts for each variable. Calculate the objective function value at the grid nodes, and select the node corresponding to the minimum value. If there are multiple nodes with the minimum value, select the node closer to the center of the region;

[0075] For the grid where the minimum value node is located, regard the adjacent eight cells as a whole, divide each side into N equal parts again, and calculate the objective function value at the grid nodes, and select the node corresponding to the minimum value ( is recorded as the final solution, and thus the bubble saturation of the active bottom formation , and the size of the bubbles .

[0076] Further, the measurement frequency range in step 2 is , and according to the range of bubble sizes of interest, the upper and lower frequency bounds are set to improve the calculation efficiency.

[0077] Further, in step 3, it is determined whether the formation acoustic signal has the characteristics of bubble resonance, and based on this characteristic, the acoustic information is extracted by refining the frequency sweep grid.

[0078] Further, in step 4, the dimension is eliminated by setting weights, and the two errors are made dimensionless and close in magnitude.

[0079] A specific application embodiment of the present invention is as follows:

[0080] This embodiment provides a method for calculating the bubble size in a bottom pore medium formation, and its steps are as follows:

[0081] Step 1: Conduct a geological survey to determine the rock physical parameters of the bottom formation to be measured;

[0082] Step 2: At the point to be measured in the bottom formation, the acoustic wave transmitting transducer emits a CW pulse signal with a pulse width of and an amplitude of = 1 [V], the measurement frequency range is , the step size is , and the number of frequency points is 91;

[0083] , ;

[0084] The acoustic wave signal receiver is placed in the bottom formation pointed by the acoustic wave transmitting transducer, and the distance from the transmitter is 0.4 [m]. The received signal at each frequency point is recorded to obtain the acoustic wave velocity and the attenuation coefficient ;

[0085] Step 3: Determine whether there are adjacent frequency points where both the acoustic wave velocity decreases and the attenuation coefficient increases, see Figure 2 , where adjacent frequency points refer to those with a frequency point number difference of 1;

[0086] If so, splice all adjacent frequency points together in sequence, find the maximum frequency point and the minimum frequency point, return to step 2, assign the maximum frequency point to in step 2, equally divide the frequency range to make the number of frequency points ten times the original, re-measure and calculate, and extract the acoustic wave velocity with the characteristics of bubble resonance and the attenuation coefficient , extract the frequency corresponding to the starting point of the attenuation coefficient , take the average value of the acoustic wave velocities without bubble resonance characteristics, denoted as , if all frequency points have bubble resonance characteristics, then take the maximum value of all measured velocities and enter step 4;

[0087] If it does not exist, record the non-existence times nongas. If nongas is less than the given threshold Maxnongas, return to step 2 and change the number of frequency points to 10m. If the non-existence times is equal to the given threshold Maxnongas, end this measurement, and there are no bubbles in the bottom formation within the measured frequency range.

[0088] Step 4: Construct the error and objective function. The errors here include: the error between the measured velocity and the theoretical velocity, and the error between the bubble resonance frequency and the theoretical frequency;

[0089] Preferably, the objective function is defined here as

[0090] ;

[0091] Wherein, is the bubble radius under the current working condition corresponding to the actual bubble resonance frequency, is the theoretical formula for calculating the bubble resonance frequency under the current working condition, is the theoretical formula for calculating the velocity of the bottom formation under the current working condition, and are weights;

[0092] Preferably, the theoretical formula for the bubble resonance frequency under the current working condition is taken as:

[0093] ;

[0094] Wherein, is the specific heat ratio of the gas in the bubble, [Pa] is the hydrostatic pressure of the formation, is the equivalent density of the current formation; [kg / ] is the equivalent density of the gas in the bubble, = 1013 [kg / ] is the pore fluid density, = 2300 [kg / ] is the formation skeleton density, [Pa] is the shear modulus of the current formation, angular frequency , = 2.19 [J / C] is the specific heat of the gas at constant pressure, = 0.03 [J / smC] Thermal conductivity of the gas;

[0095] Preferably, the theoretical formula for the formation velocity under the current working conditions is taken as:

[0096] ;

[0097] ;

[0098] ;

[0099] ;

[0100] ;

[0101] ;

[0102] ;

[0103] ;

[0104] ;

[0105] ;

[0106] ;

[0107] ;

[0108] ;

[0109] Among them, Bubble saturation, Bulk modulus of the gas in the bubble, Bulk modulus of the pore liquid, Bulk modulus of the particles constituting the formation skeleton, Bulk modulus of the formation skeleton;

[0110] Step 5. Based on the known data and under the condition of minimizing the objective function value Error, solve the independent variables and ;

[0111] Preferably, a reasonable value range is given for the independent variables, , and , perform an equal-step grid division of N = 10 equal parts for each variable, and calculate the objective function value , select the node corresponding to the minimum value ( ), if there are multiple nodes with the minimum value, select the node closer to the center of the area;

[0112] Furthermore, for the grid where the minimum value node is located, regard the eight adjacent units as a whole, divide each side into N = 10 equal parts again, and calculate the objective function value at the grid nodes , select the node corresponding to the minimum value ( ) and denote it as the final solution. Thus, the bubble saturation of the active bottom formation , and the size of the bubbles .

[0113] According to the provided invention content, the advantages and positive effects of the present invention are summarized as follows:

[0114] I. Technical advantages:

[0115] (1) Multi-parameter synchronous inversion ability: Through the attenuation characteristics of acoustic signals during frequency changes, the bubble saturation, bubble radius, and resonance frequency in the bottom formation can be estimated simultaneously. This characteristic breaks through the limitation of single-parameter evaluation in traditional methods.

[0116] (2) Adaptive measurement optimization mechanism: Adopt a dynamic frequency point adjustment strategy (step 3), and automatically optimize the measurement frequency range and step size by judging the change characteristics of acoustic wave velocity and attenuation coefficient, significantly improving the data acquisition efficiency and avoiding invalid measurements.

[0117] (3) Deep integration of theoretical model and measured data: By constructing a composite objective function (step 4) that includes the theoretical formula of bubble resonance frequency ( ) and the theoretical formula of formation velocity ( ), the accurate matching between acoustic characteristics and the physical model of porous media is achieved.

[0118] (4) High-precision grid optimization algorithm: Adopt a grid meshing and hierarchical optimization strategy (step 5), and conduct multi-level grid searches on variables , r, to ensure the global optimal solution of the inversion result within a reasonable value range.

[0119] II. Positive effects:

[0120] (1) Improve the accuracy of marine resource exploration: Provide accurate bubble size parameters for scenarios such as natural gas hydrate exploration and submarine leakage monitoring, and assist in judging the gas-bearing characteristics of the formation.

[0121] (2) Wide range of engineering applications: The method is compatible with different formation rock physical parameters (step 1) and is applicable to fields such as marine geological surveys, oil and gas field development, and environmental monitoring.

[0122] (3)Technological innovation breakthrough: For the first time, the phase difference feature of sound velocity - attenuation coefficient (the peak - valley frequency of sound velocity lags behind the peak value of attenuation coefficient) is used for inversion calculation, expanding the application boundary of acoustic detection technology.

[0123] (4)Remarkable economic benefits: The bubble - free area is quickly identified through the threshold judgment mechanism (Maxnongas), reducing the ineffective exploration cost and improving the operation efficiency.

[0124] Through the collaborative innovation of acoustic signal processing and theoretical models, the present invention provides a solution with both theoretical depth and engineering practicability for the evaluation of gas - bearing properties of underwater strata.

[0125] The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed in the present application should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for calculating the bubble size in an underwater pore medium formation, characterized in that Including: S1. Obtain the petrophysical parameters of the bottom water formation to be measured through geological surveys; S2. Deploy a sound wave transmitting transducer and a receiver at the point to be measured. The sound wave transmitting transducer emits a set signal to determine the measurement frequency range, and the receiver records the sound wave velocity and attenuation coefficient at each frequency point; S3. Determine whether there are adjacent frequency points where the sound wave velocity decreases and the attenuation coefficient increases. If so, reset the maximum frequency point and reduce the step size to 1 / 10 of the original step size, and re-measure and extract the sound wave velocity and attenuation coefficient corresponding to the bubble resonance characteristics; otherwise, record the number of times without bubble characteristics. If the number of times does not reach the threshold, continue to adjust the number of frequency points and then return to step 2; S4. Construct an objective function; S5. Under the condition that the angular frequency and sound wave velocity are known, use the grid division method to solve the independent variable, bubble radius, and bubble saturation that minimize the objective function, and determine the final bubble size and saturation.

2. The method for calculating the bubble size of the bottom water pore medium formation according to claim 1, wherein: The measurement frequency range is , , where is the step size, is the number of frequency points.

3. The method for calculating the bubble size of the bottom water pore medium formation according to claim 2, wherein: The objective function includes: ； Among them, is the objective function; and are the weights respectively; is the resonance frequency corresponding to the decay coefficient jump point under the current working condition; is the theoretical formula for calculating the bubble resonance frequency under the current working condition; is the theoretical formula for calculating the bottom formation velocity under the current working condition; is the acoustic wave velocity with bubble resonance characteristics.

4. The method for calculating the bubble size of the bottom water pore medium formation according to claim 3, wherein: The theoretical formula for calculating the bubble resonance frequency under the current working condition includes: ； Among them, is the specific heat ratio of the gas in the bubble; is the hydrostatic pressure of the formation; is the equivalent density of the current formation; is the equivalent density of the gas in the bubble; is the pore fluid density; is the formation matrix density; is the current formation shear modulus; is the angular frequency, is the specific heat of the gas at constant pressure, is the thermal conductivity of the gas, is the bubble saturation.

5. The method for calculating the bubble size of the bottom water pore medium formation according to claim 4, wherein: The theoretical formula for calculating the bottom water formation velocity under the current working condition includes: ； ； ； ； ； ； ； ； ； ； ； ； ； Among them, is the bulk modulus of the gas in the bubble; is the bulk modulus of the pore liquid; is the bulk modulus of the particles constituting the formation skeleton; is the bulk modulus of the formation skeleton.

6. The method for calculating the bubble size of the bottom water pore medium formation according to claim 1, wherein: During grid division, the independent variable, bubble radius, and bubble saturation that minimize the objective function are divided into equal step sizes respectively. Each variable is divided into N equal parts not less than 20, and the objective function is calculated at the nodes, and the node corresponding to the minimum value is selected as the initial solution.

7. The method for calculating the bubble size of the bottom water pore medium formation according to claim 6, wherein: The adjacent eight units of the grid where the initial solution is located are further divided into N equal parts, and after re-calculating the objective function, the node corresponding to the minimum value is selected as the final solution.

8. The method for calculating the bubble size of the bottom water pore medium formation according to claim 1, wherein: In S3, if the bubble resonance characteristics exist at all frequency points, the formation velocity takes the maximum value of the measured values as the average sound wave velocity.

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