Method for Identifying Volcanic Rock Formation Faults and Fault Structures Using Mud Logging Parameters

Abstract

The present invention provides a method for identifying faults and fault structures in volcanic rock formations using logging parameters. The method for identifying faults and fault structures in volcanic rock formations using logging parameters includes: Step 1: Determine the well sections where faults develop and divide the fault structures; Step 2: On the basis of determining the fault well sections, determine the logging parameter characteristics of the faults and fault structures; Step 3: On the basis of clarifying the logging characteristics of the faults and fault structures, establish a recognition model for the logging parameters of the fault structures; Step 4: Establish a recognition standard for the fault structures. The method for identifying faults and fault structures in volcanic rock formations using logging parameters can provide technical support for the optimal selection of oil and gas field exploration and the comprehensive evaluation of reservoirs.

Description

Technical Field

[0001] The present invention relates to the technical field of oil geological exploration and development, and particularly to a method for identifying faults and fault structures in volcanic rock formations by using logging parameters. Background Art

[0002] Faults can serve as both channels for oil and gas migration and barriers for oil and gas accumulation during the formation of oil and gas reservoirs, playing an important controlling role in oil and gas accumulation and the type of oil reservoirs. The fault structure and its subsequent evolution are the key to the size of the fault's conduction and sealing capabilities.

[0003] Faults encountered during drilling can provide important data for the study of fault opening and closing properties, and are also the only true and reliable data, significantly superior to field, simulation, and other data. The identification and study of faults and fault structures in the wellbore mainly utilize drilling core sampling, imaging logging, and conventional logging data, and relatively mature identification and evaluation technologies have been formed. In oil development wells, due to economic and technical reasons, especially in the horizontal well sections of oil and gas development wells, due to the high requirements and high cost of logging technology, a large number of wells do not conduct core sampling and logging, and the identification of faults and fault structures in the horizontal well sections has become an urgent problem to be solved.

[0004] In the Chinese patent application with the application number: CN201611105453.6, it relates to a method for evaluating fault opening and closing properties based on fault fracture structures, including the following steps: clarifying the fracture structure characteristics of various types of faults in the target area; obtaining the permeability of different fault structure parts according to the fracture structure characteristics; calculating the opening and closing probabilities of the corresponding parts by using the permeability of different parts of the fault structure, then calculating the opening and closing probabilities of the faults in the corresponding intervals by using the opening and closing probabilities of the corresponding parts, and finally evaluating the opening and closing properties of the faults in the target area through the opening and closing probabilities of the faults in different intervals.

[0005] In the Chinese patent application with the application number: CN201310485186.X, it relates to a three-dimensional modeling method for fault structures. First, integrate fault data into a three-dimensional visualization system, extract fault control points from it, and interpret them to form fault lines; then conduct connection analysis in various situations and revise the fault lines and fault attributes, calculate the relationships between faults, and establish a fault network reflecting its topological structure; after that, intersect the fault plane with the constructed initial formation model to obtain the initial intersection lines of the formation and the fault, calculate the fault displacement for each breakpoint on the initial intersection line, and obtain 3D fault lines including the hanging wall and footwall; finally, set weights for various types of fault data generated above, conduct fault plane fitting to form a fault plane network, and conduct formation model construction.

[0006] In the Chinese patent application with the application number CN201610183490.2, a quantitative evaluation method for the three-dimensional sealing of faults based on in-situ stress simulation is involved, which includes the following steps: Step 1, testing the mechanical parameters of rock strength; Step 2, testing the magnitude and direction of the current in-situ stress; Step 3, establishing a fault tectonic mechanical model; Step 4, calculating the sealing evaluation parameters; Step 5, optimizing the fault sealing index; Step 6, three-dimensional sealing evaluation of faults.

[0007] The above existing technologies are all quite different from the present invention and cannot solve the technical problems we want to solve. Therefore, we have invented a new method for identifying faults and fault structures in volcanic rock formations using logging parameters. Summary of the Invention

[0008] The purpose of the present invention is to provide a method for identifying faults and fault structures in volcanic rock formations using logging parameters, which can provide technical support for the optimization of oil and gas field exploration and the comprehensive evaluation of reservoirs.

[0009] The purpose of the present invention can be achieved by the following technical measures: A method for identifying faults and fault structures in volcanic rock formations using logging parameters, which includes:

[0010] Step 1: Determine the well sections with fault development and divide the fault structures.

[0011] Step 2: On the basis of determining the fault well sections, determine the logging parameter characteristics of the faults and fault structures.

[0012] Step 3: On the basis of clarifying the logging characteristics of the faults and fault structures, establish a logging parameter identification model for the fault structures.

[0013] Step 4: Establish the identification criteria for the fault structures.

[0014] The purpose of the present invention can also be achieved by the following technical measures:

[0015] In Step 1, the seismic data interpretation method, the drilling core method, and the logging data determination method are combined to more accurately determine the faults; the drilling core method and the logging data determination method are used to divide the fault structures.

[0016] In Step 1, the seismic data interpretation method is to use seismic data, and according to the faulted reflection characteristics of the faults on the seismic data, determine the faults, perform time-depth conversion, and determine the fault development depth.

[0017] In Step 1, the drilling core method is to use the drilling core, and through the observation of the core, judge whether it is a fault from the characteristics of fracture morphology, slickensides, fragmentation, and offset, and determine the fault structure according to the core fragmentation and fracture characteristics.

[0018] In Step 1, the logging data determination method uses the fault well sections determined by core calibration and seismic interpretation to clarify the faults and fault structures, and then establishes a logging model for identifying faults to identify the faults and fault structures.

[0019] In Step 2, based on the determination of the fault well sections, the logging parameter characteristics of the fault sections and the non-fault sections are compared and analyzed to clarify the variation characteristics of the logging parameters in the fault sections. On the basis of determining the logging characteristics of the faults, the logging parameter characteristics of different structural zones such as fault fracture zones and fracture zones are studied to clarify the differences in the logging characteristics of different fault structural zones.

[0020] In Step 2, the logging parameters include lithology, gas logging, and drilling time.

[0021] In Step 2, the variation characteristics of the logging parameters in the fault sections include rock changes, rock fragmentation, striations, fractures, filling, as well as gas logging anomalies and drilling time changes.

[0022] In Step 2, the logging parameter characteristics of different structural zones include the rupture situation of rock particles, lithology changes, the number of fractures, the filling degree, as well as the differences in the size of gas logging anomalies and drilling time changes.

[0023] In Step 3, on the basis of clarifying the logging characteristics of the faults and fault structures, the logging parameters with obvious responses in the fault well sections are selected, different weight values are assigned to the logging parameters respectively, and a comprehensive identification parameter for the faults and fault structures is established.

[0024] In Step 3, the formula for the comprehensive identification parameter of the faults and fault structures established is:

[0025] F 断层 = a * methane + b * ethane + c * propane + d * butane + e * drilling time + f * lithology +... Formula 1 is to overcome the excessive influence of abnormally large values of logging parameters on the comprehensive identification parameter, eliminate the abnormal values, and perform a normalization process. The values are unified to the range of 0 to 1 and processed by stratification and lithology.

[0026] In Formula 1: methane, ethane, propane, and butane are gas logging values; the drilling time is the time for drilling per meter; the lithology with striation and tectonic fracture characteristics is 0.5, the lithology with fault breccia and fault gouge characteristics is 1, and the lithology without the above characteristics is 0; the coefficients a, b, c, d, and f are determined according to the correlation strength between the above logging parameters and the fault structures. The stronger the correlation, the greater the weight value assigned, and vice versa, the smaller the weight value assigned.

[0027] In Step 4, the comprehensive identification parameter is calibrated using the faults identified and the fault structures divided by drilling cores and logging data from multiple wells and multiple well sections to determine the numerical range values for identifying faults and fault structures by the comprehensive identification parameter.

[0028] The existing technical methods for determining faults mainly utilize seismic data, logging data, and core data. However, due to the particularity of volcanic rock formations, it is difficult to identify fault seismic data, and the accuracy is relatively low. The cost of drilling core data is high, the cored well sections are few, and the probability of obtaining faults is low. Although logging data is relatively accurate and practical for determining faults, due to cost, technology, and other reasons, some wells, especially horizontal wells, do not conduct logging, and there is no logging data, making it impossible to determine the fault well sections and fault structures. The method for identifying faults and fault structures in volcanic rock formations using mud logging parameters in the present invention solves the problem of determining fault well sections and fault structures in the absence of logging data and drilling cores, and plays an important role in the study of oil and gas distribution and oil and gas development. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 FIG. is a flowchart of a specific embodiment of the method for identifying faults and fault structures in volcanic rock formations using mud logging parameters of the present invention;

[0030] Figure 2 FIG. is a fault identification structure diagram of mud logging parameters of volcanic rock formations in the Chepaizi area of the Junggar Basin in a specific embodiment of the present invention;

[0031] Figure 3 FIG. is a fault identification structure diagram of mud logging parameters of volcanic rock formations in the Junggar Basin in a specific embodiment of the present invention;

[0032] Figure 4 FIG. is a fault identification structure diagram of mud logging parameters of volcanic rock formations in the Bohai Bay Basin in a specific embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0034] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0035] Volcanic rock formations are brittle. Large and medium-sized faults often form large-scale fracture zones, significantly improving the physical properties of reservoirs, especially the permeability of reservoirs. They are the main reservoir spaces and production sections for oil and gas. The identification of faults and fault structures can provide technical support for reservoir evaluation and the study of fault sealing properties. It is difficult to identify faults in volcanic rocks by seismic methods. Identifying faults using wellbores can correct seismic interpretations and more accurately interpret faults.

[0036] Such as Figure 1 shown Figure 1 is the flow chart of the method for identifying faults and fault structures in volcanic rock formations using mud logging parameters according to the present invention. The method for identifying faults and fault structures in volcanic rock formations using mud logging parameters includes the following steps:

[0037] Step 1: Determination of fault-developed well sections and division of fault structures.

[0038] There are mainly three methods for determining fault well sections: seismic data interpretation method, drilling core method, and logging data determination method. Combining the three can more accurately determine faults. The division of fault structures mainly includes the drilling core method and the logging data determination method.

[0039] ① Seismic data interpretation method: Using seismic data, according to the faulted reflection characteristics of faults on the seismic data, determine the faults, perform time-depth conversion, and determine the fault development depth.

[0040] ② Drilling core method: Using drilling cores, through core observation, judge whether it is a fault from characteristics such as fracture morphology, slickensides, and faulting, and determine the fault structure according to core fragmentation and fracture characteristics. This method is the most direct evidence for identifying faults and fault structures and is the most accurate.

[0041] ③ Logging data determination method: Using the fault well sections determined by core calibration, seismic interpretation, etc., clarify the faults and fault structures, and then establish a logging model for identifying faults in logging to identify faults and fault structures.

[0042] Step 2: Determination of logging parameter characteristics of faults and fault structures.

[0043] On the basis of determining the fault well sections, compare and analyze the logging parameter characteristics of the fault sections and non-fault sections. The logging parameters include but are not limited to lithology, gas logging, drilling time, etc., and clarify the change characteristics of the logging parameters in the fault sections, such as rock changes, rock fragmentation, slickensides, fractures, filling, and gas logging anomalies, drilling time changes, etc. On the basis of determining the logging characteristics of faults, study the logging parameter characteristics of different structural zones such as fault fracture zones and fracture zones, such as the rupture of rock particles, lithology changes, the number of fractures, filling degree, and differences in gas logging anomaly sizes, drilling time changes, etc., and clarify the differences in logging characteristics of different fault structural zones.

[0044] Step 3: Establishment of a logging parameter identification model for fault structures.

[0045] On the basis of clarifying the logging characteristics of faults and fault structures, logging parameters with obvious responses in the fault intervals are selected, different weights are assigned to the logging parameters respectively, and a comprehensive identification parameter for faults and fault structures (F 断层 ) is established, as shown in Formula 1. To overcome the excessive influence of abnormally large values of logging parameters on the comprehensive identification parameter, abnormal points are removed and unified processing is carried out, and the values are unified to the range of 0 to 1.

[0046] F 断层 = a * methane + b * ethane + c * propane + d * butane + e * drilling time + f * lithology +... Formula 1

[0047] In Formula 1: methane, ethane, propane, and butane are gas logging values; the drilling time is the time for drilling per meter; the lithology with scratch marks and tectonic fracture characteristics is 0.5, the lithology with fault breccia and fault gouge characteristics is 1, and the lithology without the above characteristics is 0; the coefficients a, b, c, d, and f are determined according to the correlation strength between the above logging parameters and the fault structure. The stronger the correlation, the greater the weight assigned, and vice versa, the smaller the weight assigned.

[0048] Step 4: Establishment of fault structure identification criteria.

[0049] The comprehensive identification parameter (F 断层 ) is calibrated using the faults identified and the fault structures divided from the drilling cores and logging data of multiple wells and multiple well intervals, and the numerical range values for identifying faults and fault structures of the comprehensive identification parameter (F 断层 ) are determined.

[0050] In a specific Embodiment 1 of the application of the present invention, the method for identifying faults and fault structures in volcanic rock formations using logging parameters includes the following steps:

[0051] (1) Determination of fault-developed intervals and division of fault structures.

[0052] ① Using core data, through core observation, the faults and fault structures are determined from the characteristics such as core fragmentation, fracture morphology, scratch marks, and offset, as shown in Figure 2 (the core characteristics in the third column, the faults in the fifth column, and the fault structures in the sixth column).

[0053] ② On the basis of determining the faults and fault structures using seismic data and core data, the logging data is compared, and the logging curves sensitive to fault structures are selected, as shown in Table 1.

[0054] Table 1 Identification criteria table for logging curves of volcanic rock fault structures in the Chepaizi area of the Junggar Basin

[0055]

[0056] ③Using fault structure-sensitive logging curves, establish a fault structure indicator parameter (F 测井 ), as shown in Equation 2.

[0057] F 测井 = (0.26×︱AC - XAC︱ / Xmax) + (0.30×︱DEN - XDEN︱ / Xmax) + (0.25×︱CAL - BS︱ / Xmax) + (0.19×︱lg(RXO) - lg(XRXO)︱ / Xmax) Equation 2

[0058] Where: F 测井 —Fault structure indicator parameter; AC—Acoustic time difference logging value; XAC—Original rock acoustic time difference logging value; DEN—Density logging value; XDEN—Original rock density logging value; CAL—Hole diameter logging value; BS—Bit diameter value; RXO—Shallow resistivity logging value; XRXO—Shallow original rock resistivity logging value; Xmax—The maximum difference between the corresponding curve logging value and the original rock logging value, used for normalization.

[0059] The calculation results are shown in Figure 2 (Column 4, fault structure indicator parameter).

[0060] (2) Determination of the characteristics of fault and fault structure logging parameters.

[0061] On the basis of determining the fault interval, by comparing the logging parameter characteristics of different fault structures in the fault section and the non-fault section, through correlation analysis, the strong and weak relationships between gas logging components, lithology, drilling time, etc. and faults and fault structures in the study area are clarified, as shown in Table 2.

[0062] Table 2 Correlation table between volcanic rock fault structures and logging parameters in the Chepaizi area of the Junggar Basin

[0063] Logging parameters Correlation with fault structure Methane Strong Ethane Relatively strong Propane Weak Butane Weak Penetration rate Relatively strong Lithology Strong

[0064] (3) Establishment of a fault structure logging parameter identification model.

[0065] On the basis of clarifying the strong and weak correlations between faults and fault structures and logging characteristics, select the parameters with strong correlations with faults and fault structures to establish a comprehensive identification parameter for faults and fault structures (F 断层 ), as shown in Equation 3. To overcome the excessive influence of abnormal logging parameter values on the comprehensive identification parameter, remove the large abnormal values and perform normalization processing, and unify the values to between 0 and 1. Finally, perform smoothing processing. The calculation results are shown in Figure 2 (Column 4, comprehensive identification parameter F 断层 ).

[0066] F 断层 = 0.45*methane + 0.15*ethane - 0.05*drilling time + 0.5*lithology Equation 3

[0067] In Formula 3: methane, ethane, and drilling time are normalized values. The lithology with scratch marks and tectonic fracture characteristics is 0.5, and the numerical values of tectonic breccia and fault gouge intervals are 1.

[0068] (4) Establishment of fault structure identification criteria.

[0069] Use the faults and fault structures identified from the cores and logging data of multiple wells to calibrate the comprehensive identification parameter (F 断层 ), and analyze and determine the numerical range values of the comprehensive identification parameter (F 断层 ) for identifying faults and fault structures, as shown in Table 3. Use this parameter to identify fault structures, as shown in Figure 2 (the 5th column for faults and the 6th column for fault structures).

[0070] Table 3 Identification range table of volcanic rock fault structures in the Chepaizi area of the Junggar Basin

[0071] Fault structure <![CDATA[Comprehensive identification parameter (F 断层 )]]> Fractured zone <![CDATA[F 断层 ≧0.4]]> Fissure zone <![CDATA[0.1 < F 断层 <0.4]]> Original rock <![CDATA[F 断层 <0.1]]>

[0072] In a specific Embodiment 2 of applying the present invention, in the area of Embodiment 2, horizontal wells are mainly drilled for oil and gas development. Only a small number of wells collect logging data, and most horizontal wells do not collect logging data.

[0073] (1) Determination of fault-developed intervals and division of fault structures.

[0074] Use seismic data and logging data to determine fault intervals and divide fault structures, as shown in Figure 3 (the 3rd column for faults and the 4th column for fault structures).

[0075] (2) Determination of logging parameter characteristics of faults and fault structures.

[0076] On the basis of determining the fault intervals, compare the logging parameter characteristics of different fault structures in the fault sections and the non-fault sections. Through correlation analysis, clarify the strength relationship between gas logging components, lithology, drilling time, etc. in the study area and faults and fault structures, as shown in Table 4.

[0077] Table 4 Correlation table between volcanic rock fault structures and logging parameters in a certain area of the Junggar Basin

[0078] Logging parameters Correlation with fault structure Methane Strong Ethane Weak Propane Weak Butane Weak Penetration rate Relatively strong Lithology Strong

[0079] (3) Establishment of a logging parameter identification model for fault structures.

[0080] On the basis of clarifying the strength of the correlation between faults and fault structures and logging characteristics, select the parameters with relatively strong correlation with faults and fault structures to establish a comprehensive identification parameter (F 断层) as shown in Formula 4. To overcome the excessive influence of abnormal logging parameters on the comprehensive identification parameters, the abnormal values are removed and unified, and the values are unified to the range of 0 to 1. Finally, smoothing processing is performed. The calculation results are shown in Figure 3 (the 4th column, the comprehensive identification parameter F 断层 ).

[0081] F 断层 = 0.5 * methane - 0.1 * drilling time + 0.6 * lithology

[0082] Formula 4

[0083] In Formula 4: methane and drilling time are the normalized values, and the lithology with scratch marks and structural fracture characteristics is 0.5, and the numerical values in the intervals of tectonic breccia and fault gouge are 1.

[0084] (4) Establishment of the fault structure identification standard.

[0085] Use the faults and fault structures identified from the cores and logging data of multiple wells to calibrate the comprehensive identification parameter (F 断层 ), analyze and determine the numerical range values of the comprehensive identification parameter (F 断层 ) for identifying faults and fault structures, as shown in Table 5. Use this parameter to identify the fault structure, as shown in Figure 3 (the 3rd column for faults and the 4th column for fault structures).

[0086] Table 5 Identification Range Table of Volcanic Rock Fault Structures in a Certain Area of the Junggar Basin

[0087] Fault structure <![CDATA[Comprehensive discrimination parameter (F 断层 )]]> Fractured zone <![CDATA[F 断层 ≥ 0.45]]> Fissure zone <![CDATA[0.1 < F 断层 <0.45]]> Original rock <![CDATA[F 断层 <0.1]]>

[0088] In the specific embodiment 3 of applying the present invention, due to engineering reasons, logging data acquisition cannot be carried out, and only seismic and logging data are available

[0089] (1) Determination of the fault-developed well intervals and division of fault structures.

[0090] Use seismic data to determine the well intervals where faults may develop.

[0091] (2) Determination of the logging parameter characteristics of faults and fault structures.

[0092] There is no oil and gas show in most well intervals of this well, and the gas logging data has no correlation with faults. According to the logging parameter characteristics of volcanic rocks in the adjacent area of Well 3 in this example and other areas, determine the logging parameter characteristics of faults and fault structures. The faults in volcanic rock strata have a strong correlation with lithology and drilling time. The main characteristics of logging parameters are: in the well intervals where faults develop, the lithology shows characteristics such as fault breccia, fault gouge, fractures, and scratch marks, and the drilling time values of faults with the same lithology are smaller.

[0093] (3) Establishment of the logging parameter identification model for fault structures.

[0094] Based on the clear identification of the strong and weak correlations between faults, fault structures, and logging characteristics, parameters with a relatively strong correlation with faults and fault structures are selected to establish a comprehensive identification parameter (F 断层 ) for faults and fault structures, as shown in Formula 5. The calculation results are shown in Figure 4 (Column 6, comprehensive identification parameter F 断层 ).

[0095] F 断层 = 1.05 * lithology - 0.18 * drilling time

[0096] Formula 5

[0097] In Formula 5: The drilling time is the normalized value. The lithology with scratch and fracture characteristics is 0.5, and the numerical values for the intervals of tectonic breccia and fault gouge are 1.

[0098] (4) Establishment of the identification criteria for fault structures.

[0099] Referring to the comprehensive identification parameter (F 断层 ) of the fault logging parameters in the volcanic rock strata of the adjacent area, analyze and determine the numerical range values of the comprehensive identification parameter (F 断层 ) for identifying faults and fault structures, as shown in Table 6. Use this parameter to identify fault structures, as shown in Figure 4 (Column 3 for faults and Column 4 for fault structures).

[0100] Table 6 Identification Range Table of Volcanic Rock Fault Structures in a Certain Area of the Bohai Bay Basin

[0101] Fault structure <![CDATA[Comprehensive discrimination parameter (F 断层 )]]> Fractured zone <![CDATA[F 断层 ≥ 0.5]]> Fissure zone <![CDATA[0.1 < F 断层 <0.5]]> Original rock <![CDATA[F 断层 <0.1]]>

[0102] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

[0103] Except for the technical features described in the specification, the rest are well-known technologies to those skilled in the art.

Claims

1. A method for identifying volcanic rock formation faults and fault structures using mud logging parameters, characterized in that, The method for identifying faults and fault structures in volcanic rock formations using mud logging parameters includes: Step 1: Determine the well sections with fault development and divide the fault structures; Step 2: On the basis of determining the fault well sections, determine the mud logging parameter characteristics of the faults and fault structures; Step 3: On the basis of clarifying the mud logging characteristics of the faults and fault structures, establish a mud logging parameter identification model for the fault structures; Step 4: Establish a fault structure identification criterion; In Step 1, the seismic data interpretation method, the drilling core-taking method, and the logging data determination method are combined to determine the faults; the drilling core-taking method and the logging data determination method are used to divide the fault structures; In Step 2, on the basis of determining the fault well sections, compare and analyze the mud logging parameter characteristics of the fault sections and the non-fault sections, clarify the variation characteristics of the mud logging parameters in the fault sections, and on the basis of determining the mud logging characteristics of the faults, study the mud logging parameter characteristics of different structural zones such as fault fracture zones and fracture zones, and clarify the differences in the mud logging characteristics of different fault structural zones; In Step 3, on the basis of clarifying the mud logging characteristics of the faults and fault structures, select the mud logging parameters with obvious responses in the fault well sections, assign different weight values to the mud logging parameters respectively, and establish a comprehensive identification parameter for the faults and fault structures; In Step 3, the formula for the comprehensive identification parameter of the faults and fault structures is: F 断层 = a * methane + b * ethane + c * propane + d * butane + e * drilling time + f * lithology + … Formula 1 To overcome the excessive influence of abnormally large values of mud logging parameters on the comprehensive identification parameter, eliminate the abnormal values, and perform normalization processing to unify the values to between 0 and 1; In Formula 1: Methane, ethane, propane, and butane are gas logging values; the drilling time is the time for drilling per meter; the lithology with scratch marks and tectonic fracture characteristics is 0.5, the lithology with fault breccia and fault gouge characteristics is 1, and the lithology without the above characteristics is 0; the coefficients a, b, c, e, d, and f are determined according to the correlation strength between the above mud logging parameters and the fault structures. The stronger the correlation, the greater the weight value assigned, and vice versa, the smaller the weight value assigned; In Step 4, use the faults identified by drilling core-taking and logging data of multiple wells and multiple well sections and the divided fault structures to calibrate the comprehensive identification parameter, and determine the numerical range values for identifying the faults and fault structures by the comprehensive identification parameter.

2. The method for identifying faults and fault structures in volcanic rock formations using mud logging parameters according to claim 1, wherein, In Step 1, the seismic data interpretation method is to use seismic data, determine the faults according to the fault offset reflection characteristics on the seismic data, perform time-depth conversion, and determine the fault development depth.

3. The method for identifying faults and fault structures in volcanic rock formations using mud logging parameters according to claim 1, wherein In Step 1, the drilling core-taking method is to use drilling core-taking, and judge whether it is a fault through the observation of the core from the characteristics of fracture morphology, scratch marks, fragmentation, and offset, and determine the fault structure according to the core fragmentation and fracture characteristics.

4. The method for identifying faults and fault structures in volcanic rock formations using mud logging parameters according to claim 1, characterized in that, In Step 1, the logging data determination method is to use the fault well sections determined by core calibration and seismic interpretation, clarify the faults and fault structures, and then establish a logging model for identifying faults to identify the faults and fault structures.

5. The method for identifying volcanic rock formation faults and fault structures using mud logging parameters according to claim 1, characterized in that, In Step 2, the mud logging parameters include lithology, gas logging, and drilling time.

6. The method for identifying faults and fault structures in volcanic rock formations using mud logging parameters according to claim 1, characterized in that, In Step 2, the variation characteristics of the mud logging parameters in the fault sections include rock changes, rock fragmentation, scratch marks, fractures, filling, as well as gas logging anomalies and drilling time changes.

7. The method for identifying volcanic rock formation faults and fault structures using mud logging parameters according to claim 1, characterized in that In Step 2, the mud logging parameter characteristics of different structural zones include the rupture situation of rock particles, lithology changes, formation changes, fractures and their filling degrees, as well as differences in gas logging anomaly sizes and drilling time changes.

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