Airiness semi-quantitative prediction method, device and equipment and storage medium

Abstract

The application provides a gas-bearing semi-quantitative prediction method and device, equipment and a storage medium, which comprises the following steps: collecting typical well logging data, and establishing a viscoelastic medium rock physics model; based on the viscoelastic medium rock physics model, the data corresponding to different gas-bearing saturations are calculated; selecting a suitable seismic wavelet to perform viscoelastic medium forward modeling on the data corresponding to different gas-bearing saturations, and obtaining the prestack angle domain gathers corresponding to different gas-bearing saturations; extracting the curves of the amplitude variation rate changing with the incident angle at the gas-bearing layer position for the prestack angle domain gathers corresponding to different gas-bearing saturations, normalizing the curves, and obtaining the prestack seismic response characteristics corresponding to different gas-bearing saturations; and applying the prestack seismic response characteristics corresponding to different gas-bearing saturations and the measured prestack angle domain gathers to predict the gas-bearing saturation result.

Description

Technical Field

[0001] This application relates to the field of geophysical exploration, and in particular to a method, apparatus, equipment and storage medium for semi-quantitative prediction of gas content. Background Technology

[0002] Most current quantitative prediction methods for gas content rely on establishing a quantitative relationship between elastic parameters and gas saturation. Based on pre-stack inversion, the elastic parameters are first inverted to calculate the gas saturation.

[0003] This method has two drawbacks:

[0004] 1. There is a cumulative error in the fitting relationship between elastic parameters and gas saturation.

[0005] 2. The effectiveness of pre-stack inversion is affected by a variety of parameters. Summary of the Invention

[0006] To address the aforementioned issues, this application provides a method, apparatus, device, and storage medium for semi-quantitative prediction of gas content.

[0007] This application provides a semi-quantitative method for predicting gas content, including:

[0008] S1: Collect typical well logging data and establish a viscoelastic medium rock physics model;

[0009] S2: Based on the viscoelastic medium rock physics model, calculate the gas saturation data corresponding to different gas saturation conditions;

[0010] S3: Select appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels to obtain the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0011] S4: For pre-stack angle domain gathers with different gas saturation, extract the curves of amplitude change rate as a function of incident angle at the gas-bearing layer location, and normalize these curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturation.

[0012] S5: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results.

[0013] In some embodiments, the typical well logging data includes:

[0014] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation.

[0015] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant.

[0016] In some embodiments, the different gas saturation conditions include:

[0017] Gas saturation of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90%.

[0018] In some embodiments, the gas saturation data includes:

[0019] Longitudinal wave velocity, transverse wave velocity, density, and attenuation factor.

[0020] In some embodiments, the pre-stack angle domain gathers corresponding to different gas saturation conditions include:

[0021] Pre-stack angle domain gathers corresponding to gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%.

[0022] In some embodiments, the specific method for predicting gas saturation results by applying the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers includes:

[0023] By applying the pre-stack seismic response characteristics corresponding to different gas saturation levels, the curve of amplitude change rate versus incident angle is extracted for each point in the pre-stack seismic data. The curve is then fitted twice, and the slope volume representing the amplitude change rate versus incident angle of the pre-stack seismic data can be obtained through calculation. This slope volume is then normalized to a range of 0 to 100%.

[0024] This application provides a semi-quantitative prediction device for gaseous substances, comprising:

[0025] The module includes a rock physics modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module.

[0026] The rock physics modeling module collects typical well logging data and establishes a viscoelastic medium rock physics model.

[0027] The gas saturation data calculation module calculates the gas saturation data corresponding to different gas saturation conditions based on the viscoelastic medium rock physics model.

[0028] The viscoelastic medium forward modeling module: selects appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels, and obtains the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0029] The pre-stack seismic response feature module extracts curves of amplitude variation rate with incident angle at the gas-bearing layer location from pre-stack angle domain gathers with different gas saturation levels, and normalizes these curves to obtain pre-stack seismic response features corresponding to different gas saturation levels.

[0030] The gas saturation prediction module uses the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results.

[0031] This application provides a semi-quantitative gas content prediction device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, performs any of the aforementioned semi-quantitative gas content prediction methods.

[0032] This application provides a storage medium storing a computer program that can be executed by one or more processors and can be used to implement the gas content semi-quantitative prediction method described in any of the above claims.

[0033] This application provides a method, apparatus, equipment, and storage medium for semi-quantitative prediction of gas content.

[0034] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0035] (2) Only earthquake data is involved in the calculation process, with minimal human influence. Attached Figure Description

[0036] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings.

[0037] Figure 1 A schematic diagram illustrating the implementation process of a semi-quantitative prediction method for gas content provided in this application embodiment;

[0038] Figure 2 Typical well logging data provided for embodiments of this application;

[0039] Figures 3(a)-(i) show the pre-stack gather forward modeling of fluid replacement data provided in the embodiments of this application;

[0040] Figure 4 The embodiments of this application provide pre-stack seismic response characteristics corresponding to different gas saturation levels;

[0041] Figure 5 This application provides a well profile diagram of actual work area prediction data for embodiments.

[0042] Figure 6 A flowchart illustrating the implementation of a semi-quantitative prediction method for gas content provided in this application embodiment.

[0043] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0045] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0046] If the application documents contain similar descriptions such as "first, second, third", the following explanation shall be added: In the following description, the terms "first, second, third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0048] Before introducing the semi-quantitative prediction method for gas content provided in the embodiments of this application, a brief introduction is given to the problems existing in the related technologies:

[0049] Most current quantitative prediction methods for gas content rely on establishing a quantitative relationship between elastic parameters and gas saturation. Based on pre-stack inversion, the elastic parameters are first inverted to calculate the gas saturation. This method has two drawbacks: 1. There is a cumulative error in the fitting relationship from elastic parameters to gas saturation; 2. The effectiveness of pre-stack inversion is affected by various parameters.

[0050] To address the problems existing in related technologies, this application provides a method for semi-quantitative prediction of gas content. The method is applied to a semi-quantitative gas content prediction device, which can be an electronic device, such as a computer or mobile terminal. The functionality of the semi-quantitative gas content prediction method provided in this application can be implemented by the processor of the electronic device calling program code, wherein the program code can be stored in a computer storage medium.

[0051] Example 1

[0052] Figure 1 This is a schematic diagram illustrating the implementation process of a semi-quantitative prediction method for gas content provided in an embodiment of this application. The embodiment of this application provides a semi-quantitative prediction method for gas content, such as... Figure 6 The diagram shown is a schematic representation of the implementation process of a semi-quantitative prediction method for gas content provided in an embodiment of this application, including:

[0053] S1: Collect typical well logging data and establish a viscoelastic medium rock physics model;

[0054] S2: Based on the viscoelastic medium rock physics model, calculate the gas saturation data corresponding to different gas saturation conditions;

[0055] S3: Select appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels to obtain the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0056] S4: For pre-stack angle domain gathers with different gas saturation, extract the curves of amplitude change rate as a function of incident angle at the gas-bearing layer location, and normalize these curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturation.

[0057] S5: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results.

[0058] This application provides a semi-quantitative prediction method for gas content.

[0059] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0060] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0061] Example 2

[0062] Based on the foregoing embodiments, this application further provides a semi-quantitative prediction method for gas content, including:

[0063] S1: Collect typical well logging data and establish a viscoelastic medium rock physics model;

[0064] In some embodiments, the typical well logging data includes:

[0065] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0066] S22: Based on the viscoelastic medium rock physics model, calculate the corresponding gas saturation data under different gas saturation conditions;

[0067] S23: Select appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels to obtain the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0068] S24: For pre-stack angle domain gathers with different gas saturation, extract the curves of amplitude change rate as a function of incident angle at the gas-bearing layer location, and normalize these curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturation.

[0069] S25: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results.

[0070] This application provides a semi-quantitative prediction method for gas content.

[0071] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0072] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0073] Example 3

[0074] Based on the foregoing embodiments, this application further provides a semi-quantitative prediction method for gas content, including:

[0075] S31: Collect typical well logging data and establish a viscoelastic medium rock physics model;

[0076] In some embodiments, the typical well logging data includes:

[0077] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0078] S32: Based on the viscoelastic medium rock physics model, calculate the corresponding gas saturation data under different gas saturation conditions;

[0079] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0080] S33: Select appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels to obtain the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0081] S34: For pre-stack angle domain gathers with different gas saturation, extract the curves of amplitude change rate as a function of incident angle at the gas-bearing layer location, and normalize these curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturation.

[0082] S35: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results.

[0083] This application provides a semi-quantitative prediction method for gas content.

[0084] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0085] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0086] Example 4

[0087] Based on the foregoing embodiments, this application further provides a semi-quantitative prediction method for gas content, including:

[0088] S41: Collect typical well logging data and establish a viscoelastic medium rock physics model;

[0089] In some embodiments, the typical well logging data includes:

[0090] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0091] S42: Based on the viscoelastic medium rock physics model, calculate the corresponding gas saturation data under different gas saturation conditions;

[0092] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0093] In some embodiments, the different gas saturation conditions include:

[0094] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0095] S43: Select appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels to obtain the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0096] S44: For pre-stack angle domain gathers with different gas saturation, extract the curves of amplitude change rate as a function of incident angle at the gas-bearing layer location, and normalize these curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturation.

[0097] S45: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results.

[0098] This application provides a semi-quantitative prediction method for gas content.

[0099] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0100] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0101] Example 5

[0102] Based on the foregoing embodiments, this application further provides a semi-quantitative prediction method for gas content, including:

[0103] S51: Collect typical well logging data and establish a viscoelastic medium rock physics model;

[0104] In some embodiments, the typical well logging data includes:

[0105] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0106] S52: Based on the viscoelastic medium rock physics model, calculate the corresponding gas saturation data under different gas saturation conditions;

[0107] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0108] In some embodiments, the different gas saturation conditions include:

[0109] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0110] In some embodiments, the gas saturation data includes:

[0111] Longitudinal wave velocity, transverse wave velocity, density, and attenuation factor;

[0112] S53: Select appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels to obtain the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0113] S54: For pre-stack angle domain gathers with different gas saturation, extract the curves of amplitude change rate as a function of incident angle at the gas-bearing layer location, and normalize these curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturation.

[0114] S55: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results.

[0115] This application provides a semi-quantitative prediction method for gas content.

[0116] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0117] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0118] Example 6

[0119] Based on the foregoing embodiments, this application further provides a semi-quantitative prediction method for gas content, including:

[0120] S61: Collect typical well logging data and establish a viscoelastic medium rock physics model;

[0121] In some embodiments, the typical well logging data includes:

[0122] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0123] S62: Based on the viscoelastic medium rock physics model, calculate the gas saturation data corresponding to different gas saturation conditions;

[0124] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0125] In some embodiments, the different gas saturation conditions include:

[0126] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0127] In some embodiments, the gas saturation data includes:

[0128] Longitudinal wave velocity, transverse wave velocity, density, and attenuation factor;

[0129] S63: Select appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels to obtain the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0130] In some embodiments, the pre-stack angle domain gathers corresponding to different gas saturation conditions include:

[0131] Pre-stack angle domain gathers corresponding to gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0132] S64: For pre-stack angle domain gathers with different gas saturation, extract the curves of amplitude change rate as a function of incident angle at the gas-bearing layer location, and normalize these curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturation.

[0133] S65: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results.

[0134] This application provides a semi-quantitative prediction method for gas content.

[0135] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0136] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0137] Example 7

[0138] Based on the foregoing embodiments, this application further provides a semi-quantitative prediction method for gas content, including:

[0139] S71: Collect typical well logging data and establish a viscoelastic medium rock physics model;

[0140] In some embodiments, the typical well logging data includes:

[0141] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0142] S72: Based on the viscoelastic medium rock physics model, calculate the corresponding gas saturation data under different gas saturation conditions;

[0143] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0144] In some embodiments, the different gas saturation conditions include:

[0145] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0146] In some embodiments, the gas saturation data includes:

[0147] Longitudinal wave velocity, transverse wave velocity, density, and attenuation factor;

[0148] S73: Select appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels to obtain the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0149] In some embodiments, the pre-stack angle domain gathers corresponding to different gas saturation conditions include:

[0150] Pre-stack angle domain gathers corresponding to gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0151] S74: For pre-stack angle domain gathers with different gas saturation, extract the curves of amplitude change rate as a function of incident angle at the gas-bearing layer location, and normalize these curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturation.

[0152] S75: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results;

[0153] In some embodiments, the specific method for predicting gas saturation results by applying the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers includes:

[0154] By applying the pre-stack seismic response characteristics corresponding to different gas saturation levels, the curve of amplitude change rate versus incident angle is extracted for each point in the pre-stack seismic data. The curve is then fitted twice, and the slope volume representing the amplitude change rate versus incident angle of the pre-stack seismic data can be obtained through calculation. This slope volume is then normalized to a range of 0 to 100%.

[0155] This application provides a semi-quantitative prediction method for gas content.

[0156] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0157] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0158] Example 8

[0159] Based on the method of Embodiment Seven, this application provides embodiments based on real data:

[0160] S81: Collect logging data from typical wells and establish a viscoelastic medium rock physics model;

[0161] In some embodiments, the typical well logging data includes:

[0162] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0163] In some embodiments, Figure 2 The logging curves from left to right represent P-wave velocity, density, S-wave velocity, clay content, water saturation, and porosity, respectively. In the figure, sandtop and sandbase represent the top and bottom of the gas-bearing sandstone, respectively.

[0164] S82: Based on the viscoelastic medium rock physics model, calculate the corresponding gas saturation data under different gas saturation conditions;

[0165] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0166] In some embodiments, the different gas saturation conditions include:

[0167] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0168] In some embodiments, the gas saturation data includes:

[0169] Longitudinal wave velocity, transverse wave velocity, density, and attenuation factor;

[0170] S83: As shown in Figures 3(a)-(i), a 30Hz Ricker wavelet was selected to perform forward modeling of viscoelastic media on data with different gas saturation levels. The gas saturation levels are 10% as shown in Figure (a), 20% as shown in Figure (f), 30% as shown in Figure (b), 40% as shown in Figure (g), 50% as shown in Figure (c), 60% as shown in Figure (h), 70% as shown in Figure (d), 80% as shown in Figure (i), and 90% as shown in Figure (e). The pre-stack angle domain gathers corresponding to different gas saturation levels were obtained.

[0171] In some embodiments, the pre-stack angle domain gathers corresponding to different gas saturation conditions include:

[0172] Pre-stack angle domain gathers corresponding to gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0173] S84: For pre-stack angle domain gathers with different gas saturation levels, extract curves showing the rate of amplitude change as a function of the incident angle at the gas-bearing layer location, and normalize these curves, such as... Figure 4 As shown, the pre-stack seismic response characteristics corresponding to different gas saturation levels are obtained; from Figure 4 The vertical axis represents the amplitude change rate, and the horizontal axis represents the incident angle. It can be seen that there are significant differences in the seismic response characteristic curves for different gas saturation levels. A quadratic fitting of the amplitude change rate versus incident angle curve shows that when the gas saturation is 90%-10%, the corresponding slopes are 0.015, 0.0136, 0.0127, 0.0119, 0.0112, 0.011, 0.0093, 0.0077, and 0.0062, respectively. When the gas saturation is less than 40%, the slope of the amplitude change rate with the incident angle decreases significantly. In actual mining operations, it is generally difficult to mine when the gas saturation is below 40%. Therefore, identifying properties with gas saturation above 40% is very effective in actual production.

[0174] S85: Using the pre-stack seismic response characteristics corresponding to different gas saturation levels and the measured pre-stack angle domain gathers, predict the gas saturation results;

[0175] In some embodiments, the specific method for predicting gas saturation results by applying the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers includes:

[0176] By applying the pre-stack seismic response characteristics corresponding to different gas saturation levels, the curve of amplitude change rate versus incident angle is extracted for each point in the pre-stack seismic data. The curve is then fitted twice, and the slope volume representing the amplitude change rate versus incident angle of the pre-stack seismic data can be obtained through calculation. This slope volume is then normalized to make its value range from 0 to 100%.

[0177] Based on the understanding from step S4, the curve of amplitude change rate versus incident angle is extracted for each point in the pre-stack seismic data. A second fitting is performed on it, and the slope volume representing the amplitude change rate versus incident angle of the pre-stack seismic data can be obtained by calculation. It is then normalized so that its value range is 0 to 100%. Figure 5 The diagram shows the well profile of the actual work area based on the predicted data. Well A is a gas-producing well (predicted data value of 68%), Well B is a water-producing well (gas saturation of 35%), Well C is a high-producing gas well (predicted data value of 88%), and Well D is a poor-producing gas well (predicted data value of 48%). The predicted results are consistent with the actual production data.

[0178] This application provides a semi-quantitative prediction method for gas content.

[0179] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0180] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0181] Example 9

[0182] Based on the foregoing embodiments, this application provides a semi-quantitative gas content prediction device, comprising:

[0183] The module includes a rock physics modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module.

[0184] The rock physics modeling module collects typical well logging data and establishes a viscoelastic medium rock physics model.

[0185] The gas saturation data calculation module calculates the gas saturation data corresponding to different gas saturation conditions based on the viscoelastic medium rock physics model.

[0186] The viscoelastic medium forward modeling module: selects appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels, and obtains the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0187] The pre-stack seismic response feature module extracts curves of amplitude variation rate with incident angle at the gas-bearing layer location from pre-stack angle domain gathers with different gas saturation levels, and normalizes these curves to obtain pre-stack seismic response features corresponding to different gas saturation levels.

[0188] The gas saturation prediction module uses the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results.

[0189] This application provides a semi-quantitative prediction device for gas content.

[0190] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0191] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0192] Example 10

[0193] Based on the foregoing embodiments, this application provides a semi-quantitative gas content prediction device, comprising:

[0194] The module includes a rock physics modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module.

[0195] The rock physics modeling module collects typical well logging data and establishes a viscoelastic medium rock physics model.

[0196] In some embodiments, the typical well logging data includes:

[0197] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0198] The gas saturation data calculation module calculates the gas saturation data corresponding to different gas saturation conditions based on the viscoelastic medium rock physics model.

[0199] The viscoelastic medium forward modeling module: selects appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels, and obtains the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0200] The pre-stack seismic response feature module extracts curves of amplitude variation rate with incident angle at the gas-bearing layer location from pre-stack angle domain gathers with different gas saturation levels, and normalizes these curves to obtain pre-stack seismic response features corresponding to different gas saturation levels.

[0201] The gas saturation prediction module uses the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results.

[0202] This application provides a semi-quantitative prediction device for gas content.

[0203] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0204] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0205] Example 11

[0206] Based on the foregoing embodiments, this application provides a semi-quantitative gas content prediction device, comprising:

[0207] The module includes a rock physics modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module.

[0208] The rock physics modeling module collects typical well logging data and establishes a viscoelastic medium rock physics model.

[0209] In some embodiments, the typical well logging data includes:

[0210] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0211] The gas saturation data calculation module calculates the gas saturation data corresponding to different gas saturation conditions based on the viscoelastic medium rock physics model.

[0212] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0213] The viscoelastic medium forward modeling module: selects appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels, and obtains the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0214] The pre-stack seismic response feature module extracts curves of amplitude variation rate with incident angle at the gas-bearing layer location from pre-stack angle domain gathers with different gas saturation levels, and normalizes these curves to obtain pre-stack seismic response features corresponding to different gas saturation levels.

[0215] The gas saturation prediction module uses the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results.

[0216] This application provides a semi-quantitative prediction device for gas content.

[0217] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0218] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0219] Example 12

[0220] Based on the foregoing embodiments, this application provides a semi-quantitative gas content prediction device, comprising:

[0221] The module includes a rock physics modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module.

[0222] The rock physics modeling module collects typical well logging data and establishes a viscoelastic medium rock physics model.

[0223] In some embodiments, the typical well logging data includes:

[0224] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0225] The gas saturation data calculation module calculates the gas saturation data corresponding to different gas saturation conditions based on the viscoelastic medium rock physics model.

[0226] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0227] In some embodiments, the different gas saturation conditions include:

[0228] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0229] The viscoelastic medium forward modeling module: selects appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels, and obtains the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0230] The pre-stack seismic response feature module extracts curves of amplitude variation rate with incident angle at the gas-bearing layer location from pre-stack angle domain gathers with different gas saturation levels, and normalizes these curves to obtain pre-stack seismic response features corresponding to different gas saturation levels.

[0231] The gas saturation prediction module uses the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results.

[0232] This application provides a semi-quantitative prediction device for gas content.

[0233] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0234] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0235] Example 13

[0236] Based on the foregoing embodiments, this application provides a semi-quantitative gas content prediction device, comprising:

[0237] The module includes a rock physics modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module.

[0238] The rock physics modeling module collects typical well logging data and establishes a viscoelastic medium rock physics model.

[0239] In some embodiments, the typical well logging data includes:

[0240] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0241] The gas saturation data calculation module calculates the gas saturation data corresponding to different gas saturation conditions based on the viscoelastic medium rock physics model.

[0242] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0243] In some embodiments, the different gas saturation conditions include:

[0244] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0245] In some embodiments, the gas saturation data includes:

[0246] Longitudinal wave velocity, transverse wave velocity, density, and attenuation factor;

[0247] The viscoelastic medium forward modeling module: selects appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels, and obtains the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0248] The pre-stack seismic response feature module extracts curves of amplitude variation rate with incident angle at the gas-bearing layer location from pre-stack angle domain gathers with different gas saturation levels, and normalizes these curves to obtain pre-stack seismic response features corresponding to different gas saturation levels.

[0249] The gas saturation prediction module uses the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results.

[0250] This application provides a semi-quantitative prediction device for gas content.

[0251] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0252] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0253] Example 14

[0254] Based on the foregoing embodiments, this application provides a semi-quantitative gas content prediction device, comprising:

[0255] The module includes a rock physics modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module.

[0256] The rock physics modeling module collects typical well logging data and establishes a viscoelastic medium rock physics model.

[0257] In some embodiments, the typical well logging data includes:

[0258] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0259] The gas saturation data calculation module calculates the gas saturation data corresponding to different gas saturation conditions based on the viscoelastic medium rock physics model.

[0260] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0261] In some embodiments, the different gas saturation conditions include:

[0262] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0263] In some embodiments, the gas saturation data includes:

[0264] Longitudinal wave velocity, transverse wave velocity, density, and attenuation factor;

[0265] The viscoelastic medium forward modeling module: selects appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels, and obtains the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0266] In some embodiments, the pre-stack angle domain gathers corresponding to different gas saturation conditions include:

[0267] Pre-stack angle domain gathers corresponding to gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0268] The pre-stack seismic response feature module extracts curves of amplitude variation rate with incident angle at the gas-bearing layer location from pre-stack angle domain gathers with different gas saturation levels, and normalizes these curves to obtain pre-stack seismic response features corresponding to different gas saturation levels.

[0269] The gas saturation prediction module uses the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results.

[0270] This application provides a semi-quantitative prediction device for gas content.

[0271] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0272] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0273] Example 15

[0274] Based on the foregoing embodiments, this application provides a semi-quantitative gas content prediction device, comprising:

[0275] The module includes a rock physics modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module.

[0276] The rock physics modeling module collects typical well logging data and establishes a viscoelastic medium rock physics model.

[0277] In some embodiments, the typical well logging data includes:

[0278] Longitudinal wave velocity, transverse wave velocity, density, mineral content, porosity, and gas saturation;

[0279] The gas saturation data calculation module calculates the gas saturation data corresponding to different gas saturation conditions based on the viscoelastic medium rock physics model.

[0280] In some embodiments, before calculating the gas saturation data corresponding to different gas saturation conditions, the method further includes: performing fluid replacement while keeping the porosity value constant;

[0281] In some embodiments, the different gas saturation conditions include:

[0282] Gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0283] In some embodiments, the gas saturation data includes:

[0284] Longitudinal wave velocity, transverse wave velocity, density, and attenuation factor;

[0285] The viscoelastic medium forward modeling module: selects appropriate seismic wavelets to perform viscoelastic medium forward modeling on data with different gas saturation levels, and obtains the pre-stack angle domain gathers corresponding to different gas saturation conditions;

[0286] In some embodiments, the pre-stack angle domain gathers corresponding to different gas saturation conditions include:

[0287] Pre-stack angle domain gathers corresponding to gas saturation levels of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%;

[0288] The pre-stack seismic response feature module extracts curves of amplitude variation rate with incident angle at the gas-bearing layer location from pre-stack angle domain gathers with different gas saturation levels, and normalizes these curves to obtain pre-stack seismic response features corresponding to different gas saturation levels.

[0289] The gas saturation prediction module: uses the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results;

[0290] In some embodiments, the specific method for predicting gas saturation results by applying the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers includes:

[0291] By applying the pre-stack seismic response characteristics corresponding to different gas saturation levels, the curve of amplitude change rate versus incident angle is extracted for each point in the pre-stack seismic data. The curve is then fitted twice, and the slope volume representing the amplitude change rate versus incident angle of the pre-stack seismic data can be obtained through calculation. This slope volume is then normalized to a range of 0 to 100%.

[0292] This application provides a semi-quantitative prediction device for gas content.

[0293] (1) Based on rock physics modeling, the pre-stack seismic response characteristics corresponding to gas saturation that conform to the actual situation of the work area are obtained through forward modeling. The method is highly targeted.

[0294] (2) Only earthquake data is involved in the calculation process, with minimal human influence.

[0295] It should be noted that, in the embodiments of this application, if the above-mentioned semi-quantitative prediction method for gas content is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0296] Accordingly, this application provides a storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the steps in the semi-quantitative gas content prediction method provided in the above embodiments.

[0297] Example 16

[0298] This application provides a memory and processor for a gas-containing semi-quantitative prediction device. The memory stores a computer program. When the processor executes the computer program, the processor is configured to execute a program for a multi-scale electromagnetic field component denoising method stored in the memory, so as to implement the steps in the multi-scale electromagnetic field component denoising method provided in the above embodiment.

[0299] The descriptions of the display device and storage medium embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the computer device and storage medium embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0300] It should be noted that the descriptions of the storage medium and device embodiments above are similar to the descriptions of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0301] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0302] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0303] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0304] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0305] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0306] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0307] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a controller to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0308] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A gas content semi-quantitative prediction method characterized by, The method comprises the following steps: S1: collecting typical well logging data to establish a viscoelastic medium rock physics model; S2: based on the viscoelastic medium rock physics model, calculating corresponding gas saturation data under different gas saturation conditions; S3: selecting a suitable seismic wavelet to perform viscoelastic medium forward modeling on the data of different gas saturations to obtain corresponding pre-stack angle domain gathers under different gas saturation conditions; S4: extracting the curve of the amplitude variation rate changing with the incident angle at the gas-bearing layer position from the pre-stack angle domain gathers of different gas saturations, and normalizing the curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturations; S5: applying the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation result. The specific method of applying the pre-stack seismic response characteristics corresponding to different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation result comprises: applying the pre-stack seismic response characteristics corresponding to different gas saturations to extract the curve of the amplitude variation rate changing with the incident angle for each point of data in the pre-stack seismic data, performing quadratic fitting on the curve, and obtaining a slope body representing the amplitude variation rate of the pre-stack seismic data changing with the incident angle by calculation, and normalizing the slope body to make the value range 0 to 100%.

2. The method of claim 1, wherein, The typical well logging data comprises: P-wave velocity, S-wave velocity, density, mineral content, porosity, and gas saturation.

3. The method of claim 2, wherein, Before the step of calculating the gas saturation data corresponding to different gas saturation conditions, the method further comprises: performing fluid replacement under the condition that the porosity value is kept unchanged.

4. The method of claim 3, wherein, The different gas saturation conditions comprise: 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90% of the gas saturation.

5. The method of claim 2, wherein, The gas saturation data comprises: P-wave velocity, S-wave velocity, density, and attenuation factor.

6. The method of claim 4, wherein, The pre-stack angle domain gathers corresponding to different gas saturation conditions comprise: The pre-stack angle domain gathers corresponding to the conditions that the gas saturation is 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90%.

7. An apparatus for gasness semi-quantitative prediction, characterized by, The method comprises: a rock physics model modeling module, a gas saturation data calculation module, a viscoelastic medium forward modeling module, a pre-stack seismic response characteristic module, and a gas saturation prediction module; the rock physics model modeling module: collecting typical well logging data to establish a viscoelastic medium rock physics model; the gas saturation data calculation module: based on the viscoelastic medium rock physics model, calculating corresponding gas saturation data under different gas saturation conditions; the viscoelastic medium forward modeling module: selecting a suitable seismic wavelet to perform viscoelastic medium forward modeling on the data of different gas saturations to obtain corresponding pre-stack angle domain gathers under different gas saturation conditions; the pre-stack seismic response characteristic module: extracting the curve of the amplitude variation rate changing with the incident angle at the gas-bearing layer position from the pre-stack angle domain gathers of different gas saturations, and normalizing the curves to obtain the pre-stack seismic response characteristics corresponding to different gas saturations; The gas saturation prediction module: applying the pre-stack seismic response characteristics corresponding to the different gas saturations and the measured pre-stack angle domain gathers, to predict the gas saturation results; The specific method of applying the pre-stack seismic response characteristics corresponding to the different gas saturations and the measured pre-stack angle domain gathers to predict the gas saturation results comprises: applying the pre-stack seismic response characteristics corresponding to the different gas saturations to extract the curve of the amplitude variation rate changing with the incidence angle for each point data in the pre-stack seismic data, performing quadratic fitting on the curve, obtaining the slope body representing the amplitude variation rate changing with the incidence angle of the pre-stack seismic data by calculation, and performing normalization to make the value range of the slope body 0 to 100%.

8. An air content semi-quantitative prediction device characterized by comprising: The computer program stored on the storage medium can be executed by one or more processors and can be used to implement the gas-bearing semi-quantitative prediction method according to any one of claims 1 to 6.

9. A storage medium, characterized by The computer program stored on the storage medium can be executed by one or more processors and can be used to implement the gas-bearing semi-quantitative prediction method according to any one of claims 1 to 6.

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