Micro-fracture evaluation method and apparatus

Abstract

The present invention relates to the technical field of oil and gas geology and exploration and development engineering. Disclosed are a micro-fracture evaluation method and apparatus. The method comprises: determining a standard interval from a specified interval according to electrical imaging logging data, array acoustic logging data and rock core micro-fracture development information of the specified interval; and according to electrical imaging logging data, array acoustic logging data and rock core micro-fracture development information of the standard interval, analyzing electrical imaging logging data and array acoustic logging data of an interval to be analyzed, and determining the micro-fracture position, attitude and density of the interval to be analyzed. According to the present invention, micro-fractures of a stratum can be continuously evaluated with low cost, high accuracy and high universality.

Description

Microcrack evaluation method and device Technical Field

[0001] The present invention relates to the technical field of petroleum and natural gas geology and exploration and development engineering, and in particular to a method and device for evaluating microcracks. Background Art

[0002] This section is intended to provide a background or context for embodiments of the present invention. No description herein is admitted to be prior art by virtue of its inclusion in this section.

[0003] Fractures significantly improve the permeability of tight reservoirs. Tight reservoirs with well-developed fractures have relatively high productivity, and measures such as fracturing and water injection can significantly increase production. Currently, fracture logging evaluation methods are often effective for larger fractures, but smaller microfractures are often difficult to identify and evaluate through logging.

[0004] In the existing technology, there are generally four methods for evaluating microcracks:

[0005] 1. Direct observation: This method involves obtaining cores and observing and identifying microfractures using thin section analysis, scanning electron microscopy, and hand specimens. This method offers the advantage of intuitive and accurate identification results, but has the disadvantages of high coring costs and the inability to continuously assess microfracture development.

[0006] 2. Conventional logging curve combination method: Utilizing K-Φ crossplots and experimental result calibration, the microfracture sensitivity curve is identified, and multiple curve combinations are used to identify microfractures. The advantage of this method is the richness of conventional logging curve data, allowing for continuous depth assessment of microfracture development in the formation. However, its disadvantages are high multi-solution complexity and the small size of microfractures, which makes conventional logging curves inadequate for accurate evaluation.

[0007] 3. Machine Learning: This method uses acoustic, gamma, neutron, resistivity, and experimental data combined with artificial neural networks and wavelet transforms to accurately identify microfractures. This method leverages the computing power of computers to improve identification speed and interpretation accuracy. However, it requires a large number of training samples to ensure accuracy, making it difficult to apply in areas with limited exploration. Furthermore, the resulting models are often only applicable to specific areas, resulting in limited versatility.

[0008] 4. Electrical imaging logging: This method uses electrical imaging images to comprehensively analyze and extract effective information sensitive to fractures and establish a microfracture identification model. This method is very effective for larger fractures, but its disadvantage is that the scale of some microfractures (such as those visible in core hand specimens but not in electrical imaging logging) is smaller than the resolution of imaging logging, making the method itself lose its application value.

[0009] In summary, the existing technology cannot achieve low-cost, high-accuracy, high-versatility, and continuous evaluation of micro-fractures in formations.

[0010] Summary of the Invention

[0011] An embodiment of the present invention provides a method for evaluating microcracks, which is used to achieve low-cost, high-accuracy, high-versatility, and continuous evaluation of microcracks in formations. The method includes:

[0012] Based on the electrical imaging logging data, array acoustic logging data, and core microfracture development information of the specified interval, a standard interval is determined from the specified interval. The standard interval represents an interval in which the fast shear wave direction is deflected, but there are no structures that can cause abnormal wellbore stress, and the core has unfilled microfractures or semi-filled microfractures. The structures that can cause abnormal wellbore stress are picked up based on the electrical imaging logging data of the specified interval.

[0013] Analyze the stress information and the first acoustic wave information of the layer section to be analyzed based on the stress information and the first acoustic wave information of the standard layer section, and determine the location of the microcracks in the layer section to be analyzed;

[0014] Taking any two receivers as a receiver combination, determining the receiver combination corresponding to the optimal solution from multiple receiver combinations based on the second acoustic wave information received by different receivers in the standard layer section;

[0015] The occurrence of micro-fractures in the layer to be analyzed is determined by using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution;

[0016] The third acoustic wave information of the standard interval is used to determine the correlation between the microcrack index and the microcrack density;

[0017] The microcrack density of the layer to be analyzed is determined by using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density;

[0018] The evaluation result of the microcracks in the layer to be analyzed is determined according to the microcrack positions, microcrack occurrence and microcrack density in the layer to be analyzed.

[0019] An embodiment of the present invention provides a microcrack evaluation device for continuously evaluating microcracks in formations with low cost, high accuracy, and high versatility. The device includes:

[0020] The standard interval determination module is used to determine a standard interval from a specified interval based on the electrical imaging logging data, array acoustic logging data, and core microfracture development information of the specified interval. The standard interval represents an interval in which the fast shear wave orientation is deflected, but there is no structure that can cause abnormal wellbore stress, and there are unfilled microfractures or semi-filled microfractures in the core. The structure that can cause abnormal wellbore stress is picked up based on the electrical imaging logging data of the specified interval.

[0021] A position determination module is used to analyze the stress information and the first acoustic wave information of the layer section to be analyzed based on the stress information and the first acoustic wave information of the standard layer section, and determine the position of the microcracks in the layer section to be analyzed;

[0022] a receiver determination module, configured to treat any two receivers as a receiver combination, and determine a receiver combination corresponding to an optimal solution from a plurality of receiver combinations based on second acoustic wave information received by different receivers in a standard layer section;

[0023] An occurrence determination module is used to determine the occurrence of microfractures in the layer to be analyzed by using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution;

[0024] A relationship determination module is used to determine the correlation between the microcrack index and the microcrack density using the third acoustic wave information of the standard layer section;

[0025] A density determination module is used to determine the microcrack density of the layer to be analyzed by using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density;

[0026] The result determination module is used to determine the evaluation result of the microcracks in the layer section to be analyzed according to the microcrack positions, microcrack occurrence and microcrack density of the layer section to be analyzed.

[0027] An embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following method is implemented:

[0028] Based on the electrical imaging logging data, array acoustic logging data, and core microfracture development information of the specified interval, a standard interval is determined from the specified interval. The standard interval represents an interval in which the fast shear wave direction is deflected, but there are no structures that can cause abnormal wellbore stress, and the core has unfilled microfractures or semi-filled microfractures. The structures that can cause abnormal wellbore stress are picked up based on the electrical imaging logging data of the specified interval.

[0029] Analyze the stress information and the first acoustic wave information of the layer section to be analyzed based on the stress information and the first acoustic wave information of the standard layer section, and determine the location of the microcracks in the layer section to be analyzed;

[0030] Taking any two receivers as a receiver combination, determining the receiver combination corresponding to the optimal solution from multiple receiver combinations based on the second acoustic wave information received by different receivers in the standard layer section;

[0031] The occurrence of micro-fractures in the layer to be analyzed is determined by using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution;

[0032] The third acoustic wave information of the standard interval is used to determine the correlation between the microcrack index and the microcrack density;

[0033] The microcrack density of the layer to be analyzed is determined by using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density;

[0034] The evaluation result of the microcracks in the layer to be analyzed is determined according to the microcrack positions, microcrack occurrence and microcrack density in the layer to be analyzed.

[0035] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following method is implemented:

[0036] Based on the electrical imaging logging data, array acoustic logging data, and core microfracture development information of the specified interval, a standard interval is determined from the specified interval. The standard interval represents an interval in which the fast shear wave direction is deflected, but there are no structures that can cause abnormal wellbore stress, and the core has unfilled microfractures or semi-filled microfractures. The structures that can cause abnormal wellbore stress are picked up based on the electrical imaging logging data of the specified interval.

[0037] Analyze the stress information and the first acoustic wave information of the layer section to be analyzed based on the stress information and the first acoustic wave information of the standard layer section, and determine the location of the microcracks in the layer section to be analyzed;

[0038] Taking any two receivers as a receiver combination, determining the receiver combination corresponding to the optimal solution from multiple receiver combinations based on the second acoustic wave information received by different receivers in the standard layer section;

[0039] The occurrence of micro-fractures in the layer to be analyzed is determined by using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution;

[0040] The third acoustic wave information of the standard interval is used to determine the correlation between the microcrack index and the microcrack density;

[0041] The microcrack density of the layer to be analyzed is determined by using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density;

[0042] The evaluation result of the microcracks in the layer to be analyzed is determined according to the microcrack positions, microcrack occurrence and microcrack density in the layer to be analyzed.

[0043] In an embodiment of the present invention, a standard layer section is determined from the specified layer section based on the electrical imaging logging data, array acoustic logging data and core microfracture development information of the specified layer section. The standard layer section indicates that the fast shear wave azimuth in the specified layer section is deflected, but there is no structure that can cause abnormal wellbore stress, and there are unfilled microfractures or semi-filled microfractures in the core; the structure that can cause abnormal wellbore stress is picked up based on the electrical imaging logging data of the specified layer section; based on the stress information and the first acoustic wave information of the standard layer section, the stress information and the first acoustic wave information of the layer section to be analyzed are analyzed to determine the position of the microfractures in the layer section to be analyzed; any two receivers are used as a A receiver combination is provided, and according to the second acoustic wave information received by different receivers of the standard layer section, the receiver combination corresponding to the optimal solution is determined from multiple receiver combinations; the second acoustic wave information of the layer section to be analyzed received by the receiver combination corresponding to the optimal solution is used to determine the microcrack occurrence of the layer section to be analyzed; the third acoustic wave information of the standard layer section is used to determine the correlation between the microcrack index and the microcrack density; the third acoustic wave information of the layer section to be analyzed and the correlation between the microcrack index and the microcrack density are used to determine the microcrack density of the layer section to be analyzed; and the evaluation result of the microcracks in the layer section to be analyzed is determined according to the microcrack position, microcrack occurrence and microcrack density of the layer section to be analyzed. Compared with existing technical solutions for evaluating microfractures, this method does not require expensive core experimental measurements. Instead, it merely obtains electrical imaging logging data, array acoustic logging data, and core microfracture development information from a specified layer segment, and determines a standard layer segment for identifying microfractures using fast shear wave azimuth deflection from the specified layer segment. This allows continuous evaluation of microfractures in the layer segment to be analyzed based on the standard layer segment. Furthermore, the combination of electrical imaging logging data and array acoustic logging data allows effective identification of the location, occurrence, and density of microfractures. Therefore, the present invention can achieve low-cost, high-accuracy, high-versatility, and continuous evaluation of microfractures in formations. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of this application, and do not constitute a limitation of the present invention. In the drawings:

[0045] FIG1 is a flow chart of a microcrack evaluation method provided in an embodiment of the present invention;

[0046] FIG2 is a flow chart of a method for determining a standard layer section from a specified layer section based on electrical imaging logging data, array acoustic logging data, and core microfracture development information of the specified layer section, provided in an embodiment of the present invention;

[0047] FIG3 is a flow chart of a method provided in an embodiment of the present invention, wherein any two receivers are used as a receiver combination, and the P-wave attenuation and S-wave attenuation of standard intervals corresponding to the plurality of receiver combinations are calculated based on the array P-wave amplitudes and array S-wave amplitudes received by different receivers in the standard interval.

[0048] FIG4 is a flow chart of a method for determining a receiver combination corresponding to an optimal solution from multiple receiver combinations using a preset receiver screening function and the P-wave attenuation and S-wave attenuation of standard layer sections corresponding to the multiple receiver combinations, provided in an embodiment of the present invention;

[0049] 5 is a flow chart of a method for determining the correlation between a microcrack index and a microcrack density using third acoustic wave information of a standard layer interval, provided in an embodiment of the present invention;

[0050] FIG6 is a schematic diagram of the correlation between the microcrack index and the microcrack density provided in an embodiment of the present invention;

[0051] FIG7 is a schematic diagram of microfracture evaluation results of a well provided in an embodiment of the present invention;

[0052] FIG8 is a schematic diagram of a microcrack evaluation device provided in an embodiment of the present invention;

[0053] FIG9 is a schematic diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0055] The term "and / or" herein simply describes an association relationship, indicating that three relationships can exist. For example, "A and / or B" can represent the existence of A alone, the simultaneous existence of A and B, and the existence of B alone. Furthermore, the term "at least one" herein refers to any combination of at least two of any one or more of a plurality of items. For example, "at least one of A, B, and C" can represent any one or more elements selected from the set consisting of A, B, and C.

[0056] In the description of this specification, the terms "include", "including", "have", "contain", etc. are all open terms, which mean including but not limited to. The descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", etc. mean that the specific features, structures or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. The order of steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the order of steps therein is not limited and can be appropriately adjusted as needed.

[0057] Research has found that there are roughly four evaluation methods for microcracks in the existing technology:

[0058] 1. Direct observation: This method involves obtaining cores and observing and identifying microfractures using thin section analysis, scanning electron microscopy, and hand specimens. This method offers the advantage of intuitive and accurate identification results, but has the disadvantages of high coring costs and the inability to continuously assess microfracture development.

[0059] 2. Conventional logging curve combination method: Utilizing K-Φ crossplots and experimental result calibration, the microfracture sensitivity curve is identified, and multiple curve combinations are used to identify microfractures. The advantage of this method is the richness of conventional logging curve data, allowing for continuous depth assessment of microfracture development in the formation. However, its disadvantages are high multi-solution complexity and the small size of microfractures, which makes conventional logging curves inadequate for accurate evaluation.

[0060] 3. Machine Learning: This method uses acoustic, gamma, neutron, resistivity, and experimental data combined with artificial neural networks and wavelet transforms to accurately identify microfractures. This method leverages the computing power of computers to improve identification speed and interpretation accuracy. However, it requires a large number of training samples to ensure accuracy, making it difficult to apply in areas with limited exploration. Furthermore, the resulting models are often only applicable to specific areas, resulting in limited versatility.

[0061] 4. Electrical imaging logging: This method uses electrical imaging images to comprehensively analyze and extract effective information sensitive to fractures and establish a microfracture identification model. This method is very effective for larger fractures, but its disadvantage is that the scale of some microfractures (such as those visible in core hand specimens but not in electrical imaging logging) is smaller than the resolution of imaging logging, making the method itself lose its application value.

[0062] In response to the problems existing in the above-mentioned microcrack evaluation methods, the embodiments of the present invention provide a solution that can achieve low cost, high accuracy, high versatility, and can continuously evaluate microcracks in formations.

[0063] FIG1 is a flow chart of a microcrack evaluation method provided by an embodiment of the present invention, the method comprising the following steps:

[0064] Step 101: Based on the electrical imaging logging data, array acoustic logging data, and core microfracture development information of the designated interval, a standard interval is determined from the designated interval. The standard interval represents an interval in which the fast shear wave orientation is deflected, but no structures that can cause abnormal wellbore stress exist, and unfilled microfractures or partially filled microfractures exist in the core. The structures that can cause abnormal wellbore stress are identified based on the electrical imaging logging data of the designated interval.

[0065] Step 102: Analyze the stress information and the first acoustic wave information of the layer segment to be analyzed based on the stress information and the first acoustic wave information of the standard layer segment to determine the location of microcracks in the layer segment to be analyzed;

[0066] Step 103: taking any two receivers as a receiver combination, and determining a receiver combination corresponding to an optimal solution from a plurality of receiver combinations based on the second acoustic wave information received by different receivers in the standard layer interval;

[0067] Step 104, using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution, to determine the occurrence of microfractures in the layer to be analyzed;

[0068] Step 105: using the third acoustic wave information of the standard layer section, determining the correlation between the microcrack index and the microcrack density;

[0069] Step 106, using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density, determine the microcrack density of the layer to be analyzed;

[0070] Step 107 : determining the evaluation result of the microcracks in the layer to be analyzed according to the microcrack positions, microcrack occurrence and microcrack density in the layer to be analyzed.

[0071] In an embodiment of the present invention, a standard layer section is determined from the specified layer section based on the electrical imaging logging data, array acoustic logging data and core microfracture development information of the specified layer section. The standard layer section indicates that the fast shear wave azimuth in the specified layer section is deflected, but there is no structure that can cause abnormal wellbore stress, and there are unfilled microfractures or semi-filled microfractures in the core; the structure that can cause abnormal wellbore stress is picked up based on the electrical imaging logging data of the specified layer section; based on the stress information and the first acoustic wave information of the standard layer section, the stress information and the first acoustic wave information of the layer section to be analyzed are analyzed to determine the position of the microfractures in the layer section to be analyzed; any two receivers are used as a A receiver combination is provided, and according to the second acoustic wave information received by different receivers of the standard layer section, the receiver combination corresponding to the optimal solution is determined from multiple receiver combinations; the second acoustic wave information of the layer section to be analyzed received by the receiver combination corresponding to the optimal solution is used to determine the microcrack occurrence of the layer section to be analyzed; the third acoustic wave information of the standard layer section is used to determine the correlation between the microcrack index and the microcrack density; the third acoustic wave information of the layer section to be analyzed and the correlation between the microcrack index and the microcrack density are used to determine the microcrack density of the layer section to be analyzed; and the evaluation result of the microcracks in the layer section to be analyzed is determined according to the microcrack position, microcrack occurrence and microcrack density of the layer section to be analyzed. Compared with the existing technical solutions for evaluating microfractures, there is no need to spend a lot of money on core experimental measurements. By simply obtaining the electrical imaging logging data, array acoustic logging data and core microfracture development information of the specified layer segment, the standard layer segment for identifying microfractures by fast shear wave azimuth deflection can be determined from the specified layer segment. The microfractures in the layer segment to be analyzed can be continuously evaluated based on the standard layer segment. Moreover, the combination of electrical imaging logging data and array acoustic logging data can effectively identify the position, occurrence and density of microfractures. Therefore, the embodiment of the present invention can achieve low-cost, high-accuracy, high-versatility and continuous evaluation of microfractures in the formation.

[0072] The evaluation method of microcracks shown in FIG1 will be described in detail below.

[0073] Before the above step 101, first, electrical imaging logging data, array acoustic logging data and core microfracture development information of the designated layer are obtained, and electrical imaging logging data and array acoustic logging data of the layer to be analyzed are obtained.

[0074] Among them, the electrical imaging logging data of the specified layer section and the layer section to be analyzed may include the maximum horizontal principal stress orientation; the array acoustic logging data may include the fast shear wave orientation, the array fast shear wave time difference, the array slow shear wave time difference, the array longitudinal wave amplitude and the array shear wave amplitude received by different receivers; the core microfracture development information of the specified layer section may include the microfracture density and microfracture filling information of the core; the microfracture filling information includes unfilled or semi-filled.

[0075] It is understood that the designated interval is a interval where core sampling has been performed and core observation has confirmed the development of microfractures in the core. It is necessary to count the unfilled or partially filled microfractures in the core. The interval to be analyzed is a interval that has not been cored.

[0076] In specific implementation, information on borehole collapse and induced fractures can be picked up from the electrical imaging logging data to obtain the maximum horizontal principal stress orientation; structures that can cause stress anomalies near the wellbore wall can also be picked up from the electrical imaging logging data. Structures that can cause stress anomalies near the wellbore wall can include dissolution holes, cracks, borehole collapse, diameter expansion, bedding, etc.

[0077] In specific implementation, fast shear wave azimuth, array fast shear wave time difference, array slow shear wave time difference, array P-wave amplitude and array S-wave amplitude received by different receivers, etc. can be extracted from array acoustic logging data.

[0078] In the above step 101, a standard layer section can be determined from the designated layer section based on the electrical imaging logging data, array acoustic logging data and core microfracture development information of the designated layer section.

[0079] Among them, the standard layer section indicates that the fast shear wave direction in the specified layer section is deflected, but there is no structure that can cause abnormal wellbore stress, and the core has unfilled microfractures or semi-filled microfractures. The structure that can cause abnormal wellbore stress is picked up based on the electrical imaging logging data of the specified layer section.

[0080] It is understood that the standard layer section refers to a layer section determined in a specified layer section in which microfractures can be identified using fast shear wave azimuth deflection, and is used as a benchmark for microfracture evaluation in layer sections that have not been cored.

[0081] In one embodiment, as shown in FIG2 , step 101 may specifically include:

[0082] Step 201, comparing the maximum horizontal principal stress orientation in the electrical imaging logging data of a specified interval with the fast shear wave orientation in the array acoustic logging data, and determining a well section in which the maximum horizontal principal stress orientation and the fast shear wave orientation are inconsistent in the specified interval;

[0083] Step 202: If there is no structure in the inconsistent well section that can cause abnormal wellbore stress, and there are unfilled microfractures or semi-filled microfractures in the core of the inconsistent well section, the inconsistent well section is determined as a standard layer section.

[0084] In one embodiment, the structures that can cause abnormal wellbore stress include one or any combination of corrosion holes, cracks, wellbore collapse, diameter expansion, and bedding.

[0085] In practice, according to the principles of array acoustic logging, the fast shear wave azimuth represents the orientation of the maximum principal stress in the formation. However, formations with developed dissolution, fractures, wellbore collapse, borehole expansion, bedding, and microfractures can cause stress anomalies near the wellbore wall, leading to significant deviations in the fast shear wave azimuth. Therefore, the maximum horizontal principal stress azimuth from the electrical imaging logging data for a given interval is first compared with the fast shear wave azimuth from the array acoustic logging data to identify sections within the specified interval where the maximum horizontal principal stress azimuth and the fast shear wave azimuth do not match. These discrepancies are then analyzed to determine the standard interval.

[0086] In specific implementation, the inconsistent well section is analyzed. First, the presence of structures that could cause abnormal wellbore stress is determined based on the electrical imaging logging data of the inconsistent well section. Furthermore, the presence of unfilled or partially filled microfractures is determined based on the microfracture development information in the core of the inconsistent well section. If there are no structures that could cause abnormal wellbore stress, and unfilled or partially filled microfractures are present in the core, the inconsistent well section can be determined as a standard interval.

[0087] In step 102, after the standard layer segment is determined, the stress information and the first acoustic wave information of the layer segment to be analyzed may be analyzed based on the stress information and the first acoustic wave information of the standard layer segment to determine the location of microcracks in the layer segment to be analyzed.

[0088] In one embodiment, the stress information may be the maximum horizontal principal stress orientation in electrical imaging logging data; and the first acoustic wave information may be the fast shear wave orientation in array acoustic wave logging data.

[0089] In specific implementation, the maximum horizontal principal stress orientation and fast shear wave orientation of the layer to be analyzed can be analyzed according to the maximum horizontal principal stress orientation and fast shear wave orientation of the standard layer section to determine the microcrack position of the layer to be analyzed.

[0090] In specific implementation, the location of microfractures in the layer section to be analyzed (the well section not cored) can be identified based on the fast shear wave azimuth deflection parameters of the standard layer section.

[0091] In one embodiment, step 102 may specifically include:

[0092] Calculate the angular difference between the maximum horizontal principal stress orientation and the fast shear wave orientation in the standard interval;

[0093] According to the angle difference, the maximum horizontal principal stress orientation and the fast shear wave orientation of the layer segment to be analyzed are analyzed to determine the position of the microcracks in the layer segment to be analyzed.

[0094] In one embodiment, based on the angle difference, the maximum horizontal principal stress orientation and the fast shear wave orientation of the layer segment to be analyzed are analyzed to determine the location of microcracks in the layer segment to be analyzed, which may specifically include:

[0095] Substitute the maximum horizontal principal stress orientation and fast shear wave orientation of the layer to be analyzed into the following formula 1. When formula 1 is valid, the microcrack position of the layer to be analyzed is determined according to the fast shear wave orientation of the layer to be analyzed: |AZI DT _ FAST -SH MAX |>α Formula 1

[0096] Among them, AZI DT _ FAST is the fast shear wave orientation of the layer to be analyzed; SH MAX is the maximum horizontal principal stress orientation of the interval to be analyzed; α is the angle difference. The units of the fast shear wave orientation, maximum horizontal principal stress orientation, and angle difference are all degrees (°).

[0097] In specific implementation, the angular difference between the maximum horizontal principal stress azimuth and the fast shear wave azimuth of the standard layer section can be calculated, and the angular difference can be used as the minimum angular difference between the fast shear wave azimuth and the maximum horizontal principal stress azimuth. If the absolute value of the difference between the maximum horizontal principal stress azimuth and the fast shear wave azimuth of the layer section to be analyzed is greater than the angular difference, it is considered that the fast shear wave azimuth of the layer section to be analyzed has undergone a significant deflection, and if there is no structure that can cause abnormal wellbore stress at the location where the fast shear wave azimuth has undergone a significant deflection, it can be considered that there are unfilled microcracks or semi-filled microcracks at the location where the fast shear wave azimuth has undergone a significant deflection, and the location of the microcracks in the layer section to be analyzed can be obtained.

[0098] In step 103 , after the standard layer section is determined, any two receivers can be used as a receiver combination, and the receiver combination corresponding to the optimal solution can be determined from multiple receiver combinations based on the second acoustic wave information received by different receivers in the standard layer section.

[0099] In one embodiment, the second acoustic wave information may include: array longitudinal wave amplitude and array shear wave amplitude in array acoustic logging data.

[0100] In specific implementation, the array P-wave amplitude and array S-wave amplitude received by different receivers in the standard layer section can be extracted from the array acoustic logging data of the specified layer section; any two receivers are regarded as a receiver combination, and the receiver combination corresponding to the optimal solution is determined from multiple receiver combinations based on the array P-wave amplitude and array S-wave amplitude of the standard layer section received by the two receivers in one receiver combination.

[0101] In one embodiment, step 103 may specifically include:

[0102] Take any two receivers as a receiver combination, and calculate the P-wave attenuation and S-wave attenuation of the standard layer corresponding to the multiple receiver combinations according to the array P-wave amplitude and array S-wave amplitude received by different receivers in the standard layer;

[0103] The receiver combination corresponding to the optimal solution is determined from the multiple receiver combinations by using a preset receiver screening function and the P-wave attenuation and S-wave attenuation of the standard layer sections corresponding to the multiple receiver combinations.

[0104] In one embodiment, as shown in FIG3 , any two receivers are regarded as a receiver combination. Based on the array P-wave amplitudes and array S-wave amplitudes received by different receivers in the standard layer, the P-wave attenuation and S-wave attenuation of the standard layer corresponding to the multiple receiver combinations are calculated. Specifically, the calculation may include:

[0105] Step 301, taking any two receivers as a receiver combination, and determining the distance between the two receivers in each receiver combination;

[0106] Step 302, determining the array P-wave amplitudes and array S-wave amplitudes received by two receivers in each receiver combination in the standard interval based on the array P-wave amplitudes and array S-wave amplitudes received by different receivers in the standard interval;

[0107] Step 303, calculating the P-wave attenuation of the standard layer section corresponding to each receiver combination based on the distance between the two receivers in each receiver combination and the array P-wave amplitude received by the two receivers in each receiver combination in the standard layer section;

[0108] Step 304 , calculating the shear wave attenuation of the standard layer section corresponding to each receiver combination based on the distance between the two receivers in each receiver combination and the array shear wave amplitude received by the two receivers in each receiver combination in the standard layer section.

[0109] In one embodiment, step 303 may specifically include:

[0110] Substitute the distance between the two receivers in each receiver combination and the array P-wave amplitude received by the two receivers in each receiver combination in the standard layer into the following formula 2 to calculate the P-wave attenuation in the standard layer corresponding to each receiver combination: ACOA mn =f(COA m , COA n , l, m, n) Formula 2

[0111] Where m and n represent the serial numbers of the two receivers in a receiver combination, ACOA mn Indicates the P-wave attenuation of the standard layer when the receiver combination is m, n; COA mIndicates the array longitudinal wave amplitude received by receiver m, COA n It represents the array longitudinal wave amplitude received by receiver n.

[0112] In one embodiment, step 304 may specifically include:

[0113] Substitute the distance between the two receivers in each receiver combination and the array shear wave amplitude received by the two receivers in each receiver combination in the standard layer into the following formula 3 to calculate the shear wave attenuation in the standard layer corresponding to each receiver combination: ASHA mn =f(SHA m , SHA n , l, m, n) Formula 3

[0114] Among them, m, n represent the serial numbers of the two receivers in a receiver combination, ASHA mn Indicates the shear wave attenuation of the standard layer when the receiver combination is m, n; SHA m represents the array shear wave amplitude received by receiver m, SHA n It represents the array shear wave amplitude received by receiver n.

[0115] In specific implementation, Formula 2 and Formula 3 can be used to calculate the longitudinal wave attenuation and shear wave attenuation of the standard layer section corresponding to each receiver combination. In Formula 2 and Formula 3, the relationship between the serial numbers m and n of the two receivers of a receiver combination can be m>n>0.

[0116] In specific implementation, in order to obtain the logging-calculated microfracture occurrence with the highest degree of consistency with the microfracture occurrence of the core, a function with two receiver sequence number combinations as independent variables can be pre-defined as a receiver screening function. The receiver screening function and the longitudinal wave attenuation and shear wave attenuation of the standard layer sections corresponding to multiple receiver combinations are used to determine the receiver combination corresponding to the optimal solution from multiple receiver combinations.

[0117] In one embodiment, as shown in FIG4 , a receiver combination corresponding to an optimal solution is determined from multiple receiver combinations using a preset receiver screening function and the P-wave attenuation and S-wave attenuation of standard intervals corresponding to multiple receiver combinations. Specifically, the determination may include:

[0118] Step 401: Determine the logical value of microcrack occurrence in the standard layer section corresponding to the multiple receiver combinations based on the P-wave attenuation and S-wave attenuation of the standard layer section corresponding to the multiple receiver combinations; wherein, when the P-wave attenuation of the standard layer section is greater than the S-wave attenuation, the logical value of the microcrack occurrence in the standard layer section corresponding to the receiver combination is 0; and when the P-wave attenuation of the standard layer section is less than or equal to the S-wave attenuation, the logical value of the microcrack occurrence in the standard layer section corresponding to the receiver combination is 1;

[0119] In step 402, a receiver combination corresponding to an optimal solution is determined from among multiple receiver combinations using a preset receiver screening function, the longitudinal wave attenuation and the shear wave attenuation of the standard layer sections corresponding to the multiple receiver combinations, and the microfracture occurrence logic values ​​of the standard layer sections corresponding to the multiple receiver combinations.

[0120] In one embodiment, the receiver screening function may be as follows: g(m,n)=Max(∑δ(ik(ACOA mn , ASHA mn ))) Formula 4

[0121] Where m and n represent the serial numbers of the two receivers in a receiver combination; i represents the logical value of the microfracture occurrence of the standard layer when the receiver combination is m and n; ACOA mn ASHA represents the P-wave attenuation of the standard layer when the receiver combination is m, n; mn represents the shear wave attenuation of the standard layer when the receiver combination is m, n; k() represents the discriminant function of microcrack occurrence; δ() represents the Dirac function; Max() represents the maximum value function.

[0122] In specific implementations, when the P-wave attenuation is greater than the S-wave attenuation, the microcrack occurrence can be determined as low-angle microcracks; when the P-wave attenuation is less than or equal to the S-wave attenuation, the microcrack occurrence can be determined as high-angle microcracks. Therefore, the microcrack occurrence logic value can be set to 0 for low-angle microcracks and 1 for high-angle microcracks. This determines the microcrack occurrence logic value for the standard interval corresponding to each receiver combination.

[0123] In the specific implementation, in the formula of the receiver screening function, k() represents the discriminant function of the microcrack occurrence. Specifically, when ACOA mn Larger than ASHA mn When the value of k() is 0, when ACOA mn Less than or equal to ASHA mn When k() is 1, δ() represents the Dirac function, which is a discriminant function. Specifically, when i- k(ACOA mn , ASHA mn ) is 0, the value of δ() is 1, when ik(ACOA mn , ASHA mn ) is not 0, the value of δ() is 0; Max() represents the maximum value function, which is used to determine the pair of receiver combinations with the highest cumulative accuracy among all receiver combinations (that is, the receiver combination corresponding to the optimal solution) and return the values ​​of m and n.

[0124] In the above step 104, after obtaining the receiver combination corresponding to the optimal solution, the microcrack occurrence of the layer to be analyzed can be determined using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution.

[0125] In one embodiment, step 104 may specifically include:

[0126] The P-wave attenuation and S-wave attenuation of the layer to be analyzed are calculated using the array P-wave amplitude and array S-wave amplitude of the layer to be analyzed received by the receiver combination corresponding to the optimal solution;

[0127] The occurrence of microcracks in the layer to be analyzed is determined based on the longitudinal wave attenuation and shear wave attenuation in the layer to be analyzed.

[0128] In specific implementations, the array P-wave amplitude and S-wave amplitude received by the receiver combination corresponding to the optimal solution can be obtained from the array acoustic logging data of the layer to be analyzed. The P-wave amplitude received by the receiver combination corresponding to the optimal solution can be substituted into the above formula 2 to calculate the P-wave attenuation of the layer to be analyzed. The S-wave amplitude received by the receiver combination corresponding to the optimal solution can be substituted into the above formula 3 to calculate the S-wave attenuation of the layer to be analyzed. Based on the P-wave attenuation and S-wave attenuation of the layer to be analyzed, the microfracture occurrence in the layer to be analyzed can be determined.

[0129] In one embodiment, determining the occurrence of microcracks in the layer to be analyzed based on the longitudinal wave attenuation and the shear wave attenuation of the layer to be analyzed may specifically include:

[0130] When the longitudinal wave attenuation of the layer to be analyzed is greater than the shear wave attenuation, the microcrack occurrence of the layer to be analyzed is determined to be low-angle; when the longitudinal wave attenuation of the layer to be analyzed is less than or equal to the shear wave attenuation, the microcrack occurrence of the layer to be analyzed is determined to be high-angle.

[0131] In the above step 105, the third acoustic wave information of the standard layer section can be used to determine the correlation between the microcrack index and the microcrack density.

[0132] In one embodiment, the third acoustic wave information may include the array fast shear wave time difference and the array slow shear wave time difference in the array acoustic logging data; the array fast shear wave time difference and the array slow shear wave time difference may include: the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths.

[0133] In specific implementation, a microfracture index can be constructed by extracting the array fast shear wave time difference and array slow shear wave time difference of the standard layer section from the array acoustic logging data of the specified layer section to determine the microfracture index of the standard layer section; then, the microfracture index of the standard layer section is fitted with the microfracture density of the core of the standard layer section to obtain the correlation between the microfracture index and the microfracture density.

[0134] Among them, the microcrack index is used to indicate the degree of development of microcracks.

[0135] In one embodiment, the above step 105, as shown in FIG5 , may specifically include:

[0136] Step 501, calculating the difference between the array fast shear wave moveout and the array slow shear wave moveout at each radial detection depth of the standard interval;

[0137] Step 502, calculating the average value of the difference between the array fast shear wave moveout and the array slow shear wave moveout at different radial detection depths of the standard layer segment based on the difference between the array fast shear wave moveout and the array slow shear wave moveout at each radial detection depth of the standard layer segment;

[0138] Step 503: Determine the microcrack index of the standard layer section by using the difference between the array fast shear wave moveout and the array slow shear wave moveout at each radial detection depth of the standard layer section, and the average value of the difference between the array fast shear wave moveout and the array slow shear wave moveout at different radial detection depths of the standard layer section;

[0139] Step 504 : Fit the microfracture index of the standard layer section and the microfracture density of the core of the standard layer section to obtain a correlation between the microfracture index and the microfracture density.

[0140] In specific implementation, in step 501, the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer is calculated by formula 5: p =Δt skow_p -Δt fast_p Formula 5

[0141] Where Δt slow_p represents the array slow shear wave time difference at the pth radial detection depth; Δt fast_p The array fast shear wave time difference at the pth radial detection depth; X p It represents the difference between the array slow shear wave time difference and the array fast shear wave time difference at the p-th radial detection depth.

[0142] In specific implementation, in step 502, the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer is calculated using Formula 6:

[0143] In one embodiment, step 503 may specifically include:

[0144] Substitute the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer section, as well as the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer section into the following formula 7 to determine the microcrack index of the standard layer section:

[0145] Among them, X p represents the difference between the array slow shear wave time difference and the array fast shear wave time difference at the pth radial detection depth; μ represents the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths; j represents the number of different radial detection depths; MFI represents the microcrack index.

[0146] In specific implementation, after determining the microcrack index of the standard layer section, the microcrack index of the standard layer section can be fitted with the microcrack density of the core of the standard layer section (obtained from the microcrack development information of the core of the standard layer section) to obtain the correlation relationship between the microcrack index and the microcrack density.

[0147] In one embodiment, the correlation between the microcrack index and the microcrack density can be shown as Formula 8: ρ = g(MFI) Formula 8

[0148] Where ρ represents the microcrack density and MFI represents the microcrack index.

[0149] During specific implementation, g() can select various types of functions such as linear, exponential, logarithmic, polynomial, power function, etc., which are not specifically limited here.

[0150] In step 106, the array fast shear wave time difference and the array slow shear wave time difference of the layer to be analyzed can be obtained from the array acoustic logging data of the layer to be analyzed. The array fast shear wave time difference and the array slow shear wave time difference of the layer to be analyzed are substituted into the above formula 7 to calculate the microfracture index of the layer to be analyzed. Then, based on the correlation between the microfracture index and microfracture density, that is, the above formula 8, the microfracture index of the layer to be analyzed is substituted into formula 8 to calculate the microfracture density of the layer to be analyzed.

[0151] In the above step 107, the evaluation result of the microcracks in the layer to be analyzed is determined according to the microcrack positions, microcrack occurrence and microcrack density of the layer to be analyzed.

[0152] Thus, compared with the existing microcrack evaluation method, the above microcrack evaluation method has the following advantages:

[0153] 1. Compared with the direct observation method: The direct observation method can accurately identify microfractures by using core observation and microscopic identification. However, the cost of obtaining cores is high, and it is not possible to obtain a considerable number of cores for each well. The above-mentioned microfracture evaluation method can be promoted and applied within a certain exploration area (specified layer section) after core calibration (determining the standard layer section from the specified layer section) (using the standard layer section to evaluate microfractures in the layer section to be analyzed), eliminating the need for costly core experimental measurements.

[0154] 2. Compared with the conventional logging curve combination method: The conventional logging curve combination method is to find conventional logging curves that are sensitive to microfractures and combine them to form a microfracture identification method at the scale of thin section identification results. This method has a certain effect on microfracture identification under conventional oil reservoir conditions, but it is very ineffective for unconventional oil and gas reservoirs. Due to the interference of multiple factors such as source rock characteristics, physical properties, oil content, and ground stress characteristics, the multi-solution nature of the conventional logging microfracture identification method is prominent; the above-mentioned microfracture evaluation method does not use conventional logging data, but starts from multipole acoustic logging data (array acoustic logging data) with higher resolution and less interference from other factors, and uses a combination of electrical imaging logging data and array acoustic logging data to effectively identify microfractures.

[0155] 3. Compared with machine learning methods: Machine learning algorithms rely on a large number of data samples to train their training models to ensure accuracy. This condition is difficult to meet in areas with low exploration levels, thus limiting its application. The above-mentioned microcrack evaluation method does not use machine learning algorithms in microcrack feature identification and quantitative evaluation. It is more suitable for unconventional oil and gas exploration fields with low exploration levels and has higher versatility.

[0156] 4. Compared with the electrical imaging logging method: The premise of the electrical imaging method for identifying fractures is "observability on the image". However, for fractures that cannot be observed on the image, it is very difficult to determine the location of the fracture development. The above-mentioned microfracture evaluation method first uses a combination of electrical imaging logging data and array acoustic logging data to determine the location of microfracture development, and then extracts the array acoustic wave sensitive parameters to evaluate the development degree and occurrence of microfractures.

[0157] In order to more clearly understand the microcrack evaluation method provided by the embodiment of the present invention, the microcrack evaluation method is described below using a specific example.

[0158] Take the shale oil formation in a certain area as an example.

[0159] First, the target layer (specified interval) rock samples must be observed and microfracture characteristics such as depth, length, density, and whether they are filled are recorded. This is to obtain core microfracture development information for the specified interval. Electrical imaging logging data and array acoustic logging data are also required for the target layer.

[0160] The electrical imaging logging of the target layer is used to determine the maximum horizontal principal stress orientation, and the electrical imaging logging of the target layer is used to pick up structures that can cause stress anomalies near the wellbore wall, including but not limited to dissolution holes, cracks, wellbore collapse, diameter expansion, bedding, etc.

[0161] Extract the fast shear wave azimuth of the target layer from array acoustic logging, compare the fast shear wave azimuth of the target layer with the maximum horizontal principal stress azimuth determined by electrical imaging logging, and look for well sections where the fast shear wave azimuth is significantly inconsistent with the maximum principal stress azimuth. If these well sections do not have structures that can cause stress anomalies near the wellbore wall, and if the cores of these well sections have unfilled or semi-filled microfractures, then these well sections can be used as standard sections for identifying microfractures using fast shear wave azimuth deflection.

[0162] After determining the standard layer section, the above formula 1 can be used to identify the development location of unfilled and semi-filled microfractures in the well section without core sampling (the layer section to be analyzed), that is: |AZI DT_FAST -SH MAX |>α

[0163] Among them, AZI DT_FAST is the fast shear wave direction of the well section without core sampling; SH MAX is the maximum horizontal principal stress orientation in the well section without core sampling; α is the angle difference.

[0164] For well sections without core sampling, the presence of microfractures can be determined as long as the following two conditions are met: 1. The fast shear wave orientation is abnormal and there are no other structural disturbances; 2. The difference between the fast shear wave orientation and the horizontal principal stress orientation in this section is greater than 10° (i.e., the angle difference α). 10° is the difference between the fast shear wave orientation and the horizontal principal stress orientation in a standard interval.

[0165] After determining the location of microfractures in the well section without core sampling, the occurrence of microfractures can be further determined. According to the principle of acoustic logging, longitudinal waves are sensitive to medium and low angle fractures, while shear waves are sensitive to medium and high angle fractures. Therefore, the occurrence of microfractures can be determined by the attenuation of the acoustic amplitude of the array longitudinal wave and array shear wave. The specific calculation method for longitudinal wave attenuation and shear wave attenuation is:

[0166] The above formula 2 can be specifically expressed as:

[0167] The above formula 3 can be specifically expressed as:

[0168] One embodiment of the present invention utilizes Schlumberger's sonicscanner logging tool, which has 13 receivers. Therefore, 13≥m>n>0, and l=0.15 meters (the distance between two receivers).

[0169] Since the sound wave attenuation requires two different receivers to calculate, and the number of combinations of each two receivers is Specifically, the 78 receiver combinations must be calculated based on the P-wave and S-wave attenuation of the standard interval. The optimal receiver combination must be selected based on the well logging results that best agree with the core fracture pattern. Manual selection is clearly inefficient. Therefore, to obtain the best possible agreement between the well logging results and the core fracture pattern, a computer program is required to determine the optimal receiver combination. A function g(m, n) is defined with two receiver number combinations as independent variables, i.e., the receiver screening function (Equation 4). This function identifies the receiver combination with the highest calculation accuracy among the 78 receiver combinations, which is the optimal receiver combination (i.e., the receiver combination corresponding to the optimal solution).

[0170] In the implementation of the present invention, the final receiver combination is determined to be m = 13, n = 6. After finding the optimal receiver combination, the occurrence of microfractures can be determined using the optimal receiver combination for well sections where no cores have been taken.

[0171] After completing the evaluation of the microcrack occurrence in the well section without core sampling, the microcrack sensitivity parameter is constructed using the difference in the fast and slow shear wave properties of the array to achieve a quantitative evaluation of the microcrack density. In this embodiment of the present invention, the expression of the constructed microcrack index is:

[0172] Among them, X p =Δt slow_p -Δt fast_p ;

[0173] First, array acoustic logging of the standard interval is processed to obtain array fast shear wave time differences and array slow shear wave time differences at 2.5-inch intervals from the wellbore wall (0, 2.5, 5, 7.5, 10, 12.5, 15, 17.5, 20, and 22.5 inches, for a total of 10 radial depths). The microfracture development degree is then characterized using the constructed expression for the microfracture index. In this embodiment, j = 10, i.e., 10 radial depths.

[0174] The resulting microfracture index of the standard interval is then fitted with the unfilled and partially filled microfracture densities of the core in the standard interval to obtain a correlation between the microfracture index and microfracture density. This correlation can be used as a quantitative assessment of microfracture density. Figure 6 shows a schematic diagram of the correlation between the microfracture index and microfracture density provided by the present invention.

[0175] As shown in FIG6 , a polynomial fitting type with a high correlation coefficient is selected, and the expression of the correlation relationship is obtained as follows: g(x)=2.1798x 2 +3.143x+3.904

[0176] Where x represents the microcrack index MFI and g(x) represents the microcrack density. As can be seen from Figure 5, there is an obvious positive correlation between the two.

[0177] Finally, the microfracture index of the well section without core sampling is calculated, and the microfracture density is calculated based on the microfracture index of the well section without core sampling to obtain the indicator curve of microfracture development.

[0178] FIG7 is a schematic diagram of microfracture evaluation results of a well provided by an embodiment of the present invention, FIG7 includes:

[0179] The areas of semi-filled and unfilled microfracture development obtained from core observations are the color-filled areas under the heading of semi-filled-unfilled microfractures in the core (the fifth column from the left to the right in Figure 7 );

[0180] The area where the fast shear wave azimuth has obvious deflection, that is, the color-filled part under the Fast Shear Wave Azimuth title, is the location where the fast shear wave azimuth has obvious deflection (the sixth column from the left to the right in Figure 7);

[0181] The location of microcracks determined using the method of an embodiment of the present invention, i.e., the color-filled portion under the heading "Microcrack Location Determined by Array Acoustic Waves" (the seventh column from the left of FIG. 7 );

[0182] Comparison of calculated microfracture density and observed microfracture density in cores, i.e., under the headings of calculated half-filled-unfilled microfracture density and core half-filled-unfilled microfracture density, the color filling is the calculated half-filled-unfilled microfracture density and the dots are the core microfracture density (the eighth column from the left to the right in Figure 7);

[0183] Microcrack occurrence, i.e., under the headings of P-wave attenuation and S-wave attenuation, dark filling indicates low-angle cracks, and light filling indicates high-angle cracks (9th column from the left to the right in Figure 7);

[0184] Acoustic time difference curves of fast and slow shear waves received by receivers at 10 different radial detection depths (the 10th and 11th columns from the left to the right in Figure 7).

[0185] Among them, the microfracture index has the same trend as the microfracture density observed in the core. Therefore, there is an obvious positive correlation between the microfracture density and the microfracture index, which also shows that the constructed microfracture index can better characterize the degree of microfracture development.

[0186] In summary, the location, occurrence, and density of microfractures in the well section without core sampling can be obtained.

[0187] The present invention also provides a microcrack evaluation device, as described in the following embodiments. Since the principle of the device to solve the problem is similar to that of the microcrack evaluation method, the implementation of the device can refer to the implementation of the microcrack evaluation method, and the repeated parts will not be repeated.

[0188] FIG8 is a schematic diagram of a microcrack evaluation device provided by an embodiment of the present invention. The device may include:

[0189] The standard interval determination module 801 is configured to determine a standard interval from a specified interval based on electrical imaging logging data, array acoustic logging data, and core microfracture development information of the specified interval. The standard interval represents an interval in which the fast shear wave orientation is deflected, but no structures that can cause abnormal wellbore stress exist, and unfilled microfractures or partially filled microfractures exist in the core. The structures that can cause abnormal wellbore stress are picked up based on the electrical imaging logging data of the specified interval.

[0190] A position determination module 802 is configured to analyze the stress information and the first acoustic wave information of the layer segment to be analyzed based on the stress information and the first acoustic wave information of the standard layer segment, and determine the position of the microcracks in the layer segment to be analyzed;

[0191] The receiver determination module 803 is configured to treat any two receivers as a receiver combination, and determine a receiver combination corresponding to an optimal solution from a plurality of receiver combinations based on the second acoustic wave information received by different receivers in the standard layer section;

[0192] The occurrence determination module 804 is configured to determine the occurrence of microfractures in the layer to be analyzed using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution;

[0193] The relationship determination module 805 is used to determine the correlation between the microcrack index and the microcrack density using the third acoustic wave information of the standard layer section;

[0194] The density determination module 806 is configured to determine the microcrack density of the layer to be analyzed by using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density;

[0195] The result determination module 807 is used to determine the evaluation result of the microcracks in the layer to be analyzed according to the microcrack positions, microcrack occurrence and microcrack density of the layer to be analyzed.

[0196] In one embodiment, the standard interval determination module may be used to:

[0197] Compare the maximum horizontal principal stress orientation in the electrical imaging logging data of the specified interval with the fast shear wave orientation in the array acoustic logging data to determine the well section where the maximum horizontal principal stress orientation and the fast shear wave orientation are inconsistent in the specified interval;

[0198] When there is no structure that can cause abnormal wellbore stress in the inconsistent well section and unfilled microfractures or semi-filled microfractures exist in the core of the inconsistent well section, the inconsistent well section is determined as a standard layer section.

[0199] In one embodiment, the structure capable of causing abnormal wellbore stress may include one or any combination of corrosion holes, cracks, wellbore collapse, diameter expansion, and bedding.

[0200] In one embodiment, the stress information may be the maximum horizontal principal stress orientation in electrical imaging logging data; and the first acoustic wave information may be the fast shear wave orientation in array acoustic wave logging data.

[0201] In one embodiment, the location determination module may be specifically configured to:

[0202] Calculate the angular difference between the maximum horizontal principal stress orientation and the fast shear wave orientation in the standard interval;

[0203] According to the angle difference, the maximum horizontal principal stress orientation and the fast shear wave orientation of the layer segment to be analyzed are analyzed to determine the position of the microcracks in the layer segment to be analyzed.

[0204] In one embodiment, the location determination module may further be used to:

[0205] Substitute the maximum horizontal principal stress orientation and fast shear wave orientation of the layer to be analyzed into the following formula. When the following formula is established, the microcrack position of the layer to be analyzed is determined according to the fast shear wave orientation of the layer to be analyzed: |AZI DT_FAST -SH MAX |>α

[0206] Among them, AZI DT_FAST is the fast shear wave orientation of the layer to be analyzed; SH MAX is the maximum horizontal principal stress orientation of the layer to be analyzed; α is the angle difference.

[0207] In one embodiment, the second acoustic wave information may include: array longitudinal wave amplitude and array shear wave amplitude in array acoustic logging data.

[0208] In one embodiment, the receiver determination module may be specifically configured to:

[0209] Take any two receivers as a receiver combination, and calculate the P-wave attenuation and S-wave attenuation of the standard layer corresponding to the multiple receiver combinations according to the array P-wave amplitude and array S-wave amplitude received by different receivers in the standard layer;

[0210] The receiver combination corresponding to the optimal solution is determined from the multiple receiver combinations by using a preset receiver screening function and the P-wave attenuation and S-wave attenuation of the standard layer sections corresponding to the multiple receiver combinations.

[0211] In one embodiment, the receiver determination module may be specifically configured to:

[0212] Taking any two receivers as a receiver combination, determine the distance between the two receivers in each receiver combination;

[0213] Determine the array P-wave amplitudes and array S-wave amplitudes received by two receivers in each receiver combination in the standard layer according to the array P-wave amplitudes and array S-wave amplitudes received by different receivers in the standard layer;

[0214] Calculate the P-wave attenuation of the standard interval corresponding to each receiver combination according to the distance between the two receivers in each receiver combination and the array P-wave amplitude received by the two receivers in each receiver combination in the standard interval;

[0215] The shear wave attenuation of the standard layer section corresponding to each receiver combination is calculated based on the distance between the two receivers in each receiver combination and the array shear wave amplitude received by the two receivers in each receiver combination in the standard layer section.

[0216] In one embodiment, the receiver determination module may further be configured to:

[0217] Substitute the distance between the two receivers in each receiver combination and the array P-wave amplitude received by the two receivers in each receiver combination in the standard layer into the following formula to calculate the P-wave attenuation in the standard layer corresponding to each receiver combination: ACOA mn =f(COA m , COA n , l, m, n)

[0218] Where m and n represent the serial numbers of the two receivers in a receiver combination, ACOA mn Indicates the P-wave attenuation of the standard layer when the receiver combination is m, n; COA m Indicates the array longitudinal wave amplitude received by receiver m, COA n It represents the array longitudinal wave amplitude received by receiver n.

[0219] In one embodiment, the receiver determination module may further be configured to:

[0220] Substitute the distance between the two receivers in each receiver combination and the array shear wave amplitude received by the two receivers in each receiver combination in the standard layer into the following formula to calculate the shear wave attenuation in the standard layer corresponding to each receiver combination: ASHA mn =f(SHA m , SHA n , l, m, n)

[0221] Among them, m, n represent the serial numbers of the two receivers in a receiver combination, ASHA mn Indicates the shear wave attenuation of the standard layer when the receiver combination is m, n; SHA m represents the array shear wave amplitude received by receiver m, SHA n It represents the array shear wave amplitude received by receiver n.

[0222] In one embodiment, the receiver determination module may further be configured to:

[0223] According to the P-wave attenuation and S-wave attenuation of the standard layer sections corresponding to the multiple receiver combinations, the logical values ​​of the microcrack occurrence of the standard layer sections corresponding to the multiple receiver combinations are determined; wherein, when the P-wave attenuation of the standard layer section is greater than the S-wave attenuation, the logical value of the microcrack occurrence of the standard layer section corresponding to the receiver combination is 0; when the P-wave attenuation of the standard layer section is less than or equal to the S-wave attenuation, the logical value of the microcrack occurrence of the standard layer section corresponding to the receiver combination is 1;

[0224] The receiver combination corresponding to the optimal solution is determined from the multiple receiver combinations by using a preset receiver screening function, the longitudinal wave attenuation and the shear wave attenuation of the standard layer sections corresponding to the multiple receiver combinations, and the logical values ​​of the microcrack occurrence of the standard layer sections corresponding to the multiple receiver combinations.

[0225] In one embodiment, the receiver screening function may be as follows: g(m,n)=Max(∑δ(ik(ACOA mn , ASHA mn )))

[0226] Where m and n represent the serial numbers of the two receivers in a receiver combination; i represents the logical value of the microfracture occurrence of the standard layer when the receiver combination is m and n; ACOA mn ASHA represents the P-wave attenuation of the standard layer when the receiver combination is m, n; mn represents the shear wave attenuation of the standard layer when the receiver combination is m, n; k() represents the discriminant function of microcrack occurrence; δ() represents the Dirac function; Max() represents the maximum value function.

[0227] In one embodiment, the production status determination module may be specifically configured to:

[0228] The P-wave attenuation and S-wave attenuation of the layer to be analyzed are calculated using the array P-wave amplitude and array S-wave amplitude of the layer to be analyzed received by the receiver combination corresponding to the optimal solution;

[0229] The occurrence of microcracks in the layer to be analyzed is determined based on the longitudinal wave attenuation and shear wave attenuation in the layer to be analyzed.

[0230] In one embodiment, the production status determination module may further be used to:

[0231] When the longitudinal wave attenuation of the layer to be analyzed is greater than the shear wave attenuation, the microcrack occurrence of the layer to be analyzed is determined to be low-angle; when the longitudinal wave attenuation of the layer to be analyzed is less than or equal to the shear wave attenuation, the microcrack occurrence of the layer to be analyzed is determined to be high-angle.

[0232] In one embodiment, the third acoustic wave information may include array fast shear wave time difference and array slow shear wave time difference in array acoustic logging data; the array fast shear wave time difference and array slow shear wave time difference in the array acoustic logging data include: array fast shear wave time difference and array slow shear wave time difference at different radial detection depths;

[0233] The relationship determination module can be used to:

[0234] Calculate the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer;

[0235] According to the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer, the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer is calculated;

[0236] The microcrack index of the standard layer section is determined by using the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer section, and the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer section;

[0237] The microcrack index of the standard layer section and the microcrack density of the core of the standard layer section are fitted to obtain the correlation between the microcrack index and the microcrack density.

[0238] In one embodiment, the relationship determination module may also be used to:

[0239] The microcrack index of the standard layer section is determined by substituting the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer section and the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer section into the following formula:

[0240] Among them, Xp represents the difference between the array slow shear wave time difference and the array fast shear wave time difference at the pth radial detection depth; μ represents the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths; j represents the number of different radial detection depths; MFI represents the microcrack index.

[0241] In one embodiment, the correlation between the microcrack index and the microcrack density is as follows: ρ = g(MFI)

[0242] Where ρ represents the microcrack density and MFI represents the microcrack index.

[0243] An embodiment of the present invention also provides a computer device, as shown in Figure 9, which is a schematic diagram of a computer device in an embodiment of the present invention. The computer device 900 includes a memory 910, a processor 920, and a computer program 930 stored in the memory 910 and executable on the processor 920. When the processor 920 executes the computer program 930, the above-mentioned microcrack evaluation method is implemented.

[0244] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned microcrack evaluation method is implemented.

[0245] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the computer program implements the above-mentioned microcrack evaluation method.

[0246] In an embodiment of the present invention, a standard layer section is determined from the specified layer section based on the electrical imaging logging data, array acoustic logging data and core microfracture development information of the specified layer section. The standard layer section indicates that the fast shear wave azimuth in the specified layer section is deflected, but there is no structure that can cause abnormal wellbore stress, and there are unfilled microfractures or semi-filled microfractures in the core; the structure that can cause abnormal wellbore stress is picked up based on the electrical imaging logging data of the specified layer section; based on the stress information and the first acoustic wave information of the standard layer section, the stress information and the first acoustic wave information of the layer section to be analyzed are analyzed to determine the position of the microfractures in the layer section to be analyzed; any two receivers are used as a A receiver combination is provided, and according to the second acoustic wave information received by different receivers of the standard layer section, the receiver combination corresponding to the optimal solution is determined from multiple receiver combinations; the second acoustic wave information of the layer section to be analyzed received by the receiver combination corresponding to the optimal solution is used to determine the microcrack occurrence of the layer section to be analyzed; the third acoustic wave information of the standard layer section is used to determine the correlation between the microcrack index and the microcrack density; the third acoustic wave information of the layer section to be analyzed and the correlation between the microcrack index and the microcrack density are used to determine the microcrack density of the layer section to be analyzed; and the evaluation result of the microcracks in the layer section to be analyzed is determined according to the microcrack position, microcrack occurrence and microcrack density of the layer section to be analyzed. Compared with the existing technical solutions for evaluating microfractures, there is no need to spend a lot of money on core experimental measurements. By simply obtaining the electrical imaging logging data, array acoustic logging data and core microfracture development information of the specified layer segment, the standard layer segment for identifying microfractures by fast shear wave azimuth deflection can be determined from the specified layer segment. The microfractures in the layer segment to be analyzed can be continuously evaluated based on the standard layer segment. Moreover, the combination of electrical imaging logging data and array acoustic logging data can effectively identify the position, occurrence and density of microfractures. Therefore, the embodiment of the present invention can achieve low-cost, high-accuracy, high-versatility and continuous evaluation of microfractures in the formation.

[0247] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0248] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0249] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0250] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0251] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for evaluating microcracks, characterized in that: include: According to the electrical imaging logging data, array acoustic logging data and core microfracture development information of the designated layer section, a standard layer section is determined from the designated layer section, wherein the standard layer section indicates a layer section in which the fast shear wave azimuth is deflected, but there is no structure that can cause abnormal wellbore stress, and there are unfilled microfractures or semi-filled microfractures in the core; the structure that can cause abnormal wellbore stress is picked up according to the electrical imaging logging data of the designated layer section; Analyze the stress information and the first acoustic wave information of the layer section to be analyzed according to the stress information and the first acoustic wave information of the standard layer section, and determine the position of the microcracks in the layer section to be analyzed; Taking any two receivers as a receiver combination, determining a receiver combination corresponding to an optimal solution from a plurality of receiver combinations according to second acoustic wave information received by different receivers in a standard layer section; Determine the occurrence of micro-fractures in the layer to be analyzed by using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution; The third acoustic wave information of the standard layer is used to determine the correlation between the microcrack index and the microcrack density; The microcrack density of the layer to be analyzed is determined by using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density; The evaluation result of the microcracks in the layer section to be analyzed is determined according to the microcrack positions, microcrack occurrence and microcrack density in the layer section to be analyzed.

2. The method according to claim 1, characterized in that Based on the electrical imaging logging data, array acoustic logging data and core microfracture development information of the specified layer, the standard layer section is determined from the specified layer section, including: Compare the maximum horizontal principal stress orientation of the specified layer section with the fast shear wave orientation, and determine the well section where the maximum horizontal principal stress orientation and the fast shear wave orientation are inconsistent in the specified layer section; When there is no structure that can cause abnormal wellbore stress in the inconsistent well section, and unfilled microfractures or semi-filled microfractures exist in the core of the inconsistent well section, the inconsistent well section is determined as a standard layer section.

3. The method according to any one of claims 1 to 2, characterized in that: The structures that can cause abnormal wellbore stress include one or any combination of corrosion holes, cracks, wellbore collapse, diameter expansion, and bedding.

4. The method according to claim 1, characterized in that The stress information is the maximum horizontal principal stress orientation in the electrical imaging logging data; the first acoustic wave information is the fast shear wave orientation in the array acoustic wave logging data.

5. The method according to claim 4, characterized in that According to the stress information and the first acoustic wave information of the standard layer section, the stress information and the first acoustic wave information of the layer section to be analyzed are analyzed to determine the location of the microcracks in the layer section to be analyzed, including: Calculate the angle difference between the maximum horizontal principal stress orientation and the fast shear wave orientation in the standard layer section; According to the angle difference, the maximum horizontal principal stress orientation and the fast shear wave orientation of the layer segment to be analyzed are analyzed to determine the position of the microcracks in the layer segment to be analyzed.

6. The method according to claim 5, characterized in that According to the angle difference, the maximum horizontal principal stress orientation and the fast shear wave orientation of the layer section to be analyzed are analyzed to determine the position of the microcracks in the layer section to be analyzed, including: Substitute the maximum horizontal principal stress orientation and fast shear wave orientation of the layer to be analyzed into the following formula. When the following formula is established, the microcrack position of the layer to be analyzed is determined according to the fast shear wave orientation of the layer to be analyzed: |AZI DT_FAST -SH MAX |>α Among them, AZI DT_FAST is the fast shear wave orientation of the layer to be analyzed; SH MAX is the maximum horizontal principal stress orientation of the layer to be analyzed; α is the angle difference.

7. The method according to claim 1, characterized in that The second acoustic wave information includes: array longitudinal wave amplitude and array shear wave amplitude in array acoustic wave logging data.

8. The method according to claim 7, characterized in that Any two receivers are regarded as a receiver combination, and according to the second acoustic wave information received by different receivers in the standard layer section, the receiver combination corresponding to the optimal solution is determined from multiple receiver combinations, including: Taking any two receivers as a receiver combination, according to the array P-wave amplitude and array S-wave amplitude received by different receivers in the standard layer section, the P-wave attenuation and S-wave attenuation of the standard layer section corresponding to the multiple receiver combinations are calculated; By using a preset receiver screening function and the longitudinal wave attenuation and the shear wave attenuation of the standard layer sections corresponding to the multiple receiver combinations, a receiver combination corresponding to the optimal solution is determined from the multiple receiver combinations.

9. The method according to claim 8, characterized in that Take any two receivers as a receiver combination, and calculate the P-wave attenuation and S-wave attenuation of the standard layer corresponding to the multiple receiver combinations according to the array P-wave amplitude and array S-wave amplitude received by different receivers in the standard layer, including: Taking any two receivers as a receiver combination, determine the distance between the two receivers in each receiver combination; According to the array P-wave amplitudes and array S-wave amplitudes received by different receivers in the standard layer section, the array P-wave amplitudes and array S-wave amplitudes received by two receivers in each receiver combination in the standard layer section are determined; Calculate the P-wave attenuation of the standard layer section corresponding to each receiver combination according to the distance between the two receivers in each receiver combination and the array P-wave amplitude received by the two receivers in each receiver combination in the standard layer section; The shear wave attenuation of the standard layer section corresponding to each receiver combination is calculated according to the distance between the two receivers in each receiver combination and the array shear wave amplitude received by the two receivers in each receiver combination in the standard layer section.

10. The method according to claim 9, characterized in that According to the distance between the two receivers in each receiver combination and the array P-wave amplitude received by the two receivers in each receiver combination in the standard layer section, the P-wave attenuation of the standard layer section corresponding to each receiver combination is calculated, including: Substitute the distance between the two receivers in each receiver combination and the array P-wave amplitude received by the two receivers in each receiver combination in the standard layer into the following formula to calculate the P-wave attenuation in the standard layer corresponding to each receiver combination: ACOA mn =f(COA m ,COA n ,l,m,n) Where m and n represent the serial numbers of the two receivers in a receiver combination, ACOA mn Indicates the P-wave attenuation of the standard layer when the receiver combination is m, n; COA m represents the array longitudinal wave amplitude received by receiver m, COA n It represents the amplitude of the array longitudinal wave received by receiver n.

11. The method according to claim 9, characterized in that According to the distance between the two receivers in each receiver combination and the array shear wave amplitude received by the two receivers in each receiver combination in the standard layer section, the shear wave attenuation of the standard layer section corresponding to each receiver combination is calculated, including: Substitute the distance between the two receivers in each receiver combination and the array shear wave amplitude received by the two receivers in each receiver combination in the standard layer into the following formula to calculate the shear wave attenuation in the standard layer corresponding to each receiver combination: ASHA mn =f(SHA m ,SHA n ,l,m,n) Where m and n represent the serial numbers of the two receivers in a receiver combination. mn Indicates the shear wave attenuation of the standard layer when the receiver combination is m, n; SHA m represents the array shear wave amplitude received by receiver m, SHA n represents the array shear wave amplitude received by receiver n.

12. The method according to claim 8, characterized in that By using the preset receiver screening function and the P-wave attenuation and S-wave attenuation of the standard layer sections corresponding to the multiple receiver combinations, the receiver combination corresponding to the optimal solution is determined from the multiple receiver combinations, including: According to the P-wave attenuation and S-wave attenuation of the standard layer sections corresponding to the multiple receiver combinations, the logical value of the microcrack occurrence of the standard layer sections corresponding to the multiple receiver combinations is determined; wherein, when the P-wave attenuation of the standard layer section is greater than the S-wave attenuation, The logic value of the microcrack occurrence of the standard layer section corresponding to the receiver combination is 0; when the longitudinal wave attenuation of the standard layer section is less than or equal to the shear wave attenuation, the logic value of the microcrack occurrence of the standard layer section corresponding to the receiver combination is 1; By using a preset receiver screening function, the longitudinal wave attenuation and the shear wave attenuation of the standard layer sections corresponding to the multiple receiver combinations, and the microcrack occurrence logic values ​​of the standard layer sections corresponding to the multiple receiver combinations, the receiver combination corresponding to the optimal solution is determined from the multiple receiver combinations.

13. The method according to claim 12, characterized in that The receiver screening function is as follows: g(m,n)=Max(∑δ(ik(ACOA mn , ASHA mn ))) Where m, n represent the serial numbers of the two receivers in a receiver combination; i represents the logical value of the microfracture occurrence of the standard layer when the receiver combination is m, n; ACOA mn ASHA represents the P-wave attenuation of the standard layer when the receiver combination is m and n; mn It represents the shear wave attenuation of the standard layer when the receiver combination is m, n; k() represents the discriminant function of the microcrack occurrence; δ() represents the Dirac function; Max() represents the maximum value function.

14. The method according to claim 7, characterized in that The second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution is used to determine the occurrence of microcracks in the layer to be analyzed, including: The P-wave attenuation and S-wave attenuation of the layer to be analyzed are calculated by using the array P-wave amplitude and array S-wave amplitude of the layer to be analyzed received by the receiver combination corresponding to the optimal solution; According to the longitudinal wave attenuation and shear wave attenuation of the layer section to be analyzed, the occurrence of micro-fractures in the layer section to be analyzed is determined.

15. The method according to claim 14, characterized in that According to the longitudinal wave attenuation and shear wave attenuation of the layer to be analyzed, the occurrence of micro-cracks in the layer to be analyzed is determined, including: When the longitudinal wave attenuation of the layer to be analyzed is greater than the shear wave attenuation, the microcrack occurrence of the layer to be analyzed is determined to be low angle; when the longitudinal wave attenuation of the layer to be analyzed is less than or equal to the shear wave attenuation, the microcrack occurrence of the layer to be analyzed is determined to be high angle.

16. The method according to claim 1, wherein: The third acoustic wave information includes the array fast shear wave time difference and the array slow shear wave time difference in the array acoustic wave logging data; the array fast shear wave time difference and the array slow shear wave time difference include: the array fast shear wave time difference and the array slow shear wave time difference of different radial detection depths; Using the third acoustic wave information of the standard layer, the correlation between the microcrack index and the microcrack density is determined, including: Calculate the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer segment; According to the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer section, the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer section is calculated; The microcrack index of the standard layer section is determined by using the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer section and the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer section; The microfracture index of the standard layer section and the microfracture density of the core of the standard layer section are fitted to obtain the correlation between the microfracture index and the microfracture density.

17. The method according to claim 16, characterized in that The microcrack index of the standard layer section is determined by using the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer section, and the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer section, including: Substitute the difference between the array fast shear wave time difference and the array slow shear wave time difference at each radial detection depth of the standard layer section, and the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths of the standard layer section into the following formula to determine the microcrack index of the standard layer section: Among them, X p represents the difference between the array slow shear wave time difference and the array fast shear wave time difference at the pth radial detection depth; μ represents the average value of the difference between the array fast shear wave time difference and the array slow shear wave time difference at different radial detection depths; j represents the number of different radial detection depths; MFI represents the microcrack index.

18. The method of claim 1, wherein: The correlation between the microcrack index and the microcrack density is as follows: ρ = g(MFI) Wherein, ρ represents the microcrack density and MFI represents the microcrack index.

19. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following method is implemented: According to the electrical imaging logging data, array acoustic logging data and core microfracture development information of the designated layer section, a standard layer section is determined from the designated layer section, wherein the standard layer section indicates a layer section in which the fast shear wave azimuth is deflected, but there is no structure that can cause abnormal wellbore stress, and there are unfilled microfractures or semi-filled microfractures in the core; the structure that can cause abnormal wellbore stress is picked up according to the electrical imaging logging data of the designated layer section; Analyze the stress information and the first acoustic wave information of the layer section to be analyzed according to the stress information and the first acoustic wave information of the standard layer section, and determine the position of the microcracks in the layer section to be analyzed; Taking any two receivers as a receiver combination, determining a receiver combination corresponding to an optimal solution from a plurality of receiver combinations according to second acoustic wave information received by different receivers in a standard layer section; Determine the occurrence of micro-fractures in the layer to be analyzed by using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution; The third acoustic wave information of the standard layer is used to determine the correlation between the microcrack index and the microcrack density; The microcrack density of the layer to be analyzed is determined by using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density; The evaluation result of the microcracks in the layer section to be analyzed is determined according to the microcrack positions, microcrack occurrence and microcrack density in the layer section to be analyzed.

20. A computer-readable storage medium, characterized in that: The computer readable storage medium stores a computer program, and when the computer program is executed by a processor, the following method is implemented: According to the electrical imaging logging data, array acoustic logging data and core microfracture development information of the designated layer section, a standard layer section is determined from the designated layer section, wherein the standard layer section indicates a layer section in which the fast shear wave azimuth is deflected, but there is no structure that can cause abnormal wellbore stress, and there are unfilled microfractures or semi-filled microfractures in the core; the structure that can cause abnormal wellbore stress is picked up according to the electrical imaging logging data of the designated layer section; Analyze the stress information and the first acoustic wave information of the layer section to be analyzed according to the stress information and the first acoustic wave information of the standard layer section, and determine the position of the microcracks in the layer section to be analyzed; Taking any two receivers as a receiver combination, determining a receiver combination corresponding to an optimal solution from a plurality of receiver combinations according to second acoustic wave information received by different receivers in a standard layer section; Determine the occurrence of micro-fractures in the layer to be analyzed by using the second acoustic wave information of the layer to be analyzed received by the receiver combination corresponding to the optimal solution; The third acoustic wave information of the standard layer is used to determine the correlation between the microcrack index and the microcrack density; The microcrack density of the layer to be analyzed is determined by using the third acoustic wave information of the layer to be analyzed and the correlation between the microcrack index and the microcrack density; The evaluation result of the microcracks in the layer section to be analyzed is determined according to the microcrack positions, microcrack occurrence and microcrack density in the layer section to be analyzed.

Images