A single-well fracture identification method based on rock mechanics and bi-directional constraint of ground stress

Abstract

The application discloses a single-well fracture identification method based on rock mechanics and bi-directional constraint of ground stress. The single-well fracture identification method comprises the following steps: obtaining and analyzing core well data, special logging data and conventional logging data in a research area; calculating rock mechanics parameters and ground stress parameters according to conventional logging curves; determining a fracture development index, a horizontal stress difference and a stress heterogeneity coefficient of a fracture development position characterized by a rock mechanics level and a ground stress level; comparing the fracture development index, the horizontal stress difference and the stress heterogeneity coefficient with single-well fracture characteristic parameters and fracture development position characteristic parameters to obtain a parameter fluctuation interval of the fracture development position; screening wells with a single-well fracture development position to be predicted according to the parameter fluctuation interval of the fracture development position; and constructing a comprehensive fracture identification curve according to the screened fluctuation interval to predict the single-well fracture development position, thereby improving the precision of single-well fracture identification.

Description

Technical Field

[0001] This application relates to the field of oil and gas geological exploration and development technology, specifically to a single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress. Background Technology

[0002] Accurate and efficient identification and prediction of reservoir fractures has always been a key research focus in oilfield exploration and development. Common methods for predicting reservoir fractures include: precise identification and characterization of small-scale fractures using core samples; intuitive identification and data extraction analysis of fractures in single wells using imaging logging data; amplification of anomaly responses in conventional logging curves at small- to medium-scale fracture sites using various mathematical methods; and identification and prediction of large-scale fractures using various seismic attribute techniques. However, due to the relatively limited availability of core data, the high cost of imaging logging deployment, and the large scale of seismic methods, a comprehensive analysis suggests that conventional logging, with its advantages of easy acquisition, low cost, and simple processing, is the most important research direction for single-well fracture identification and characterization.

[0003] Patent document CN106526693A discloses a fracture identification method and apparatus. The method involves: acquiring fracture data of a study area; determining the development characteristics and distribution patterns of fractures in the study area based on the fracture data; establishing an electrical property identification standard for lithology to classify various lithologies; extracting fracture characteristic parameters for each lithology based on well logging curves; establishing a nonlinear fracture identification model based on the fracture characteristic parameters and obtaining fracture identification results for individual wells within the study area based on this model; and determining a three-dimensional model of fracture intensity in the study area based on the fracture identification results of individual wells, combined with production dynamic data, fracture development characteristics, and fracture distribution patterns.

[0004] A patent document with publication number CN111781638A discloses a method for predicting effective fracture zones. This method identifies effective fractures, classifies them into types, and determines the development range of effective fracture zones in a single well. It analyzes the differences in the physical properties of formation rocks caused by effective fractures and establishes a cross-sectional diagram of different rock physical properties. Based on this cross-sectional diagram, it selects physical properties used to distinguish different fracture zones. Using Bayesian discriminant analysis, it establishes a discrimination formula for effective fracture zones based on these physical properties. Finally, it acquires a three-dimensional data volume of the distinguishing physical properties of the formation to be tested, and combines this data with the discrimination formula to perform three-dimensional discrimination of effective fracture zones, thus obtaining the spatial distribution of the effective fracture zones.

[0005] The patent with publication number CN110320569B discloses a method for quantitatively evaluating the fracture development intensity of a single well in a tight sandstone reservoir. The method involves determining characteristic parameters for identifying fractures in a single well; determining comprehensive indicator parameters for fractures in the single well to be evaluated based on these parameters; quantitatively identifying fracture layers in the single well based on these comprehensive indicator parameters; determining the fracture development intensity index of the single well to be evaluated; and quantitatively evaluating the fracture development intensity of the single well based on the fracture development intensity index.

[0006] The patent with publication number CN104360415B discloses a method for identifying fractures in tight sandstone reservoirs. By analyzing the relationship between characteristic parameters of fracture logging response in a single well, relevant characteristic parameters for fracture identification in a single well are established. Then, a weighted arithmetic mean method is used to construct a comprehensive fracture evaluation model parameter—the comprehensive fracture index. This method enables the identification of fractures in tight sandstone reservoir sections to be identified in a single well by analyzing the magnitude of the comprehensive fracture index. This method can accurately and reliably identify fracture sections, providing a basis for the rational and effective development of tight sandstone oil and gas reservoirs.

[0007] However, current methods for identifying and characterizing fractures in single wells using well logging curves often rely on mathematical approaches to analyze the response characteristics of various types of curves to fracture development areas. This approach neglects the fact that when fractures exist, the rock's mechanical properties and geostress disturbance phenomena will significantly deviate from the original formation, resulting in low identification accuracy. Summary of the Invention

[0008] Therefore, this application provides a single-well fracture identification method based on two-way constraints of rock mechanics and geostress to solve the problem of low identification accuracy in existing single-well fracture identification methods.

[0009] To achieve the above objectives, this application provides the following technical solution:

[0010] Firstly, a single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress includes:

[0011] Step 1: Obtain core well data, special logging data, and conventional logging data for the study area;

[0012] Step 2: Determine the fracture characteristic parameters of a single well based on the core well data;

[0013] Step 3: Determine the characteristic parameters of the fracture development location based on the specific logging data;

[0014] Step 4: Obtain conventional logging curves based on the conventional logging data;

[0015] Step 5: Calculate the rock mechanics parameters based on the conventional logging curves, and determine the fracture development index, which characterizes the fracture development location in the rock mechanics layer;

[0016] Step 6: Calculate the geostress parameters based on the conventional logging curves, and determine the horizontal stress difference and stress heterogeneity coefficient of the geostress layer that characterize the fracture development area;

[0017] Step 7: Compare the fracture development index, the horizontal stress difference, and the stress heterogeneity coefficient with the single-well fracture characteristic parameters and the fracture development location characteristic parameters to obtain the fluctuation range of the fracture development location parameters;

[0018] Step 8: Based on the fluctuation range of the fracture development location parameters, screen the wells for which the fracture development location needs to be predicted by the fluctuation range.

[0019] Step 9: Construct a comprehensive fracture identification curve based on the screened fracture development index, horizontal stress difference, and stress heterogeneity coefficient, and predict the fracture development location in a single well.

[0020] Preferably, in step 2, the single-well fracture characteristic parameters include fracture development location, depth, and fracture length data.

[0021] Preferably, in step 3, the special logging includes imaging logging and dipole shear wave logging.

[0022] Preferably, in step 4, the conventional logging curves include sonic transit time curves, density curves, and wellbore diameter curves.

[0023] Preferably, in step 5, when calculating rock mechanical parameters based on the conventional logging curves, if the study area has the dipole shear wave logging and can collect the target layer available shear wave logging curves, firstly, the P-wave logging curve is calculated based on the shear wave logging curve using the P-wave to S-wave conversion formula, then the Young's modulus and Poisson's ratio in the rock mechanical parameters are calculated using the P-wave and S-wave transit time, and finally, the fracture development index is calculated based on the Young's modulus and Poisson's ratio.

[0024] Preferably, if the dipole shear wave logging exists in the study area, but no usable shear wave logging curves for the target layer are collected or the collected shear wave logging curves are unusable, a correlation fitting curve needs to be constructed based on the existing shear wave logging curves and the sonic transit time curves, so as to convert the conventional logging curves into shear wave transit time curves, and then calculate the longitudinal wave transit time curves.

[0025] Preferably, in step 6, the horizontal stress difference and the stress heterogeneity coefficient are calculated based on the Poisson's ratio and the triaxial geostress of a single well.

[0026] Preferably, in step 9, three curves need to be constructed when building the comprehensive crack identification curve.

[0027] Secondly, a single-well fracture identification device based on bidirectional constraints of rock mechanics and geostress includes:

[0028] The data acquisition module is used to acquire core well data, special logging data, and conventional logging data in the study area;

[0029] The core well data analysis module is used to determine the fracture characteristic parameters of a single well based on the core well data.

[0030] A special logging data analysis module is used to determine characteristic parameters of fracture development locations based on the special logging data;

[0031] The conventional logging data analysis module is used to obtain conventional logging curves based on the conventional logging data;

[0032] The rock mechanics parameter calculation module is used to calculate rock mechanics parameters based on the conventional logging curves and determine the fracture development index, which characterizes the fracture development location in the rock mechanics layer.

[0033] The geostress parameter calculation module is used to calculate geostress parameters based on the conventional logging curves, and to determine the horizontal stress difference and stress heterogeneity coefficient of the geostress layer characterizing the fracture development area.

[0034] The fluctuation range determination module is used to compare the fracture development index, the horizontal stress difference, and the stress heterogeneity coefficient with the single-well fracture characteristic parameters and the fracture development location characteristic parameters to obtain the fluctuation range of the fracture development location parameters.

[0035] The fluctuation range screening module is used to screen wells for which the fracture development location needs to be predicted based on the fluctuation range of the fracture development location parameter.

[0036] The single-well fracture development location prediction module is used to construct a comprehensive fracture identification curve based on the screened fracture development index, horizontal stress difference, and stress heterogeneity coefficient, and to predict the fracture development location of a single well.

[0037] Thirdly, a computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of a single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress.

[0038] Compared with the prior art, this application has at least the following beneficial effects:

[0039] This application provides a single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress. It acquires core well data, special logging data, and conventional logging data from the study area, and determines single-well fracture characteristic parameters, fracture development location characteristic parameters, and conventional logging curves. Based on the conventional logging curves, rock mechanics parameters and geostress parameters are calculated, and fracture development indices, horizontal stress differences, and stress heterogeneity coefficients characterizing fracture development locations at rock mechanics and geostress levels are determined. The fracture development indices, horizontal stress differences, and stress heterogeneity coefficients are compared with the single-well fracture characteristic parameters and fracture development location characteristic parameters to obtain the fluctuation range of fracture development location parameters. Based on the fluctuation range of fracture development location parameters, wells for which single-well fracture development locations need to be predicted are screened. A comprehensive fracture identification curve is constructed based on the screened fracture development indices, horizontal stress differences, and stress heterogeneity coefficients to predict the fracture development location of a single well. This application starts with the rock mechanical properties and geostress disturbance phenomena when rocks have fractures, and predicts the fracture development location of single wells. This greatly reduces the error caused by using mathematical methods to study the response of various types of curves at fracture development locations, and improves the accuracy of single-well fracture identification. Attached Figure Description

[0040] To more intuitively illustrate the prior art and this application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application; for example, based on the technical concept disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, size ratios, etc. of certain units (components).

[0041] Figure 1 A flowchart illustrating a single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress, provided in Embodiment 1 of this application;

[0042] Figure 2 This is a schematic diagram of the screening results for crack development index, horizontal stress difference, and stress heterogeneity coefficient provided in Embodiment 1 of this application.

[0043] Figure 3 This is a schematic diagram of the predicted fracture development location in a single well, provided in Embodiment 1 of this application. Detailed Implementation

[0044] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] In the description of this application: unless otherwise stated, "a plurality of" means two or more. The terms "first," "second," "third," etc., in this application are intended to distinguish the objects referred to and do not have any special meaning in terms of technical connotation (e.g., they should not be construed as an emphasis on importance or order). Expressions such as "comprising," "including," and "having" also mean "not limited to" (certain units, components, materials, steps, etc.).

[0046] The terms used in this application, such as "upper," "lower," "left," "right," and "middle," are generally used to indicate the general relative positional relationship for the purpose of intuitive understanding by referring to the accompanying drawings, and are not absolute limitations on the positional relationship in the actual product.

[0047] Example 1

[0048] Please see Figure 1 This embodiment provides a single-well fracture identification method based on two-way constraints of rock mechanics and geostress, including:

[0049] S1: Acquire core well data, special logging data, and conventional logging data for the study area;

[0050] Specifically, a core well is a well used in geological exploration to extract rock cores from underground. Core well data includes information such as the distribution of core wells, the core formation, the core recovery rate, and the core length.

[0051] S2: Determine the fracture characteristic parameters of a single well based on core well data;

[0052] Specifically, this step involves identifying the characteristic parameters of fractures in a single-well core sample. Since the goal of this embodiment is to predict the location of fracture development, it is only necessary to collect information on the location, depth, and length of fractures when identifying the characteristic parameters of fractures in a single well, thereby accurately locating the influence range of fractures in the vertical direction of the single well.

[0053] S3: Determine characteristic parameters of fracture development locations based on special logging data;

[0054] This step involves analyzing specific logging data to identify characteristic parameters of fracture development locations and performing statistical analysis. Specifically, the specific logging methods in this embodiment include two types: imaging logging and dipole shear wave logging. For imaging logging, it is crucial to collect dynamic and static images and FVDC curves. Dynamic and static images allow researchers to visually observe the location, depth, and length of fractures, while FVDC curves verify the accuracy of artificial fracture identification. Dipole shear wave logging requires collecting the acquired shear wave logging curves, which serve as the data basis for rock mechanics and geostress calculations.

[0055] S4: Obtain conventional logging curves based on conventional logging data;

[0056] In actual oilfield exploration and development, conventional logging deployment is quite common. Therefore, collecting conventional logging curves is relatively simple. However, it is important to ensure that the collected conventional logging curves include AC (acoustic transit time curve), DEN (density curve), and CAL (caliper curve). Some wells may lack DEN (density curve), in which case at least AC (acoustic transit time curve) and CAL (caliper curve) must be included.

[0057] For conventional logging, there is a risk of units not being converted due to changes in testing equipment or multiple sampling. In such cases, it is necessary to standardize and correct the units of the same type of logging curve in the target layer before proceeding with subsequent calculations. There may also be cases where large sections of logging data are lost or abnormal due to engineering accidents such as well leakage or well collapse. In such cases, it is necessary to standardize the well section and set it to 0 or a maximum value to avoid the abnormal data in the well section affecting the subsequent calculation results.

[0058] S5: Calculate rock mechanics parameters based on conventional logging curves and determine the fracture development index (FI) of the rock mechanics layer, which characterizes the fracture development location.

[0059] Specifically, when calculating rock mechanics parameters based on well logging curves from the study area, it is important to note that when dipole shear wave logging exists in the study area and usable shear wave logging curves for the target layer can be collected, the P-wave logging curve should first be calculated based on the shear wave logging curve using the P-wave to S-wave conversion formula. The P-wave to S-wave conversion formula is as follows:

[0060]

[0061] In the above formula, Δtc and Δts represent the P-wave time difference and S-wave time difference, respectively, with units of μ. s / f t (microseconds / foot); ρ b The density of rock is expressed in g / cm³. 3 .

[0062] After conversion, the Young's modulus (E) and Poisson's ratio (σ) in rock mechanics parameters are calculated using the P-wave and S-wave transit time differences. The formulas for both are as follows:

[0063]

[0064] In the above formula, E is the dynamic Young's modulus calculated from well logging, in MPa; σ is Poisson's ratio, dimensionless.

[0065] Finally, a fracture development index (FI) based on Young's modulus (E) and Poisson's ratio (σ) is constructed to characterize the location of fracture development at rock mechanical levels:

[0066]

[0067] In the above formula, E ma This is the elastic modulus of the rock skeleton, which is a constant under the same lithology.

[0068] When dipole shear wave logging exists in the study area, but no usable shear wave logging curves are collected for the target layer, or the collected shear wave logging curves are unusable, a correlation fitting curve needs to be constructed based on the existing shear wave logging curves and the conventional logging curve AC (acoustic transit time curve). This converts the conventional logging curve AC (acoustic transit time curve) into a shear wave transit time curve, and then the longitudinal wave transit time curve is calculated.

[0069] S6: Calculate the geostress parameters based on conventional well logging curves, and determine the horizontal stress difference and stress heterogeneity coefficient of the geostress layer that characterizes the fracture development area;

[0070] Specifically, after calculating rock mechanical parameters using well logging curves, the Poisson's ratio σ obtained is used to calculate the triaxial geostress of a single well. The calculation formula is as follows:

[0071]

[0072] In the above formula, σ V σ represents vertical stress, in MPa; H represents burial depth (m); ρ(z) represents rock density at burial depth z, which can be obtained from density logging data; H It is the maximum horizontal principal stress, in MPa; σ h The minimum horizontal principal stress is expressed in MPa; ω1 and ω2 represent the horizontal geostress coefficients; α represents the Biot coefficient; σ represents Poisson's ratio; P P This indicates pore pressure, measured in MPa.

[0073] It should be noted that the horizontal stress coefficients ω1 and ω2, as well as the Biot coefficient α, need to be determined based on the actual conditions of the study area.

[0074] Then, based on the triaxial geostress calculation results, horizontal stress difference (S) and stress heterogeneity coefficient (Y) are constructed to characterize the fracture development location in the geostress layer:

[0075] S=σ1-σ3

[0076] Y = σ1 / σ3.

[0077] S7: By comparing the fracture development index, horizontal stress difference, and stress heterogeneity coefficient with the characteristic parameters of fractures in a single well and the characteristic parameters of fracture development locations, the fluctuation range of parameters in fracture development locations can be obtained.

[0078] Specifically, this step compares the fracture development index (FI) calculated from rock mechanical parameters (Young's modulus E and Poisson's ratio σ) and the horizontal stress difference (S) and stress heterogeneity coefficient (Y) calculated from geostress parameters with the fracture development locations statistically obtained from core wells and imaging logging. This allows us to determine the data fluctuation range of the rock mechanical layer at the fracture development location.

[0079] It should be noted that the parameters currently used to study rock mechanics parameters, determine the fracture development index (FI) which characterizes fracture development locations at rock mechanics levels, and study geostress parameters, determine the horizontal stress difference (S) and stress heterogeneity coefficient (Y) which characterize fracture development locations at geostress levels, should be wells that simultaneously possess core samples from the target layer and contain imaging logging information, or wells that only possess core samples from the target layer and contain imaging logging information. The purpose of these wells is to statistically analyze the fluctuation ranges of various parameters at fracture development locations, providing data preparation for fracture prediction in single wells that do not possess core samples from the target layer but contain imaging logging information.

[0080] S8: Screen wells for which the fracture development location needs to be predicted by the fluctuation range of parameters at the fracture development location.

[0081] Specifically, this step screens wells for which the fracture development location needs to be predicted based on the fluctuation range of parameters such as fracture development index (FI), horizontal stress difference (S), and stress heterogeneity coefficient (Y) in the fracture development location.

[0082] More specifically, this step involves determining the fracture development index (FI), horizontal stress difference (S), and stress heterogeneity coefficient (Y) within the parameter fluctuation range of fracture development locations for wells containing core samples of the target layer, imaging logging information, or only core samples of the target layer and imaging logging information. Then, for wells whose fracture development locations need to be predicted, the fracture development index (FI), horizontal stress difference (S), and stress heterogeneity coefficient (Y) are calculated. Finally, by using the fracture development index (FI), horizontal stress difference (S), and stress heterogeneity coefficient (Y) within the parameter fluctuation range of fracture development locations, the fracture development locations of the single wells to be predicted are screened out.

[0083] S9: Construct a comprehensive fracture identification curve based on the screened fracture development index, horizontal stress difference, and stress heterogeneity coefficient, and predict the fracture development location in a single well.

[0084] Specifically, since the response of a single fracture development index (FI), horizontal stress difference (S), and stress heterogeneity coefficient (Y) to fractures is random, combining these three curves can further improve prediction accuracy. Therefore, a comprehensive fracture identification curve (Z) is constructed to predict the location of fractures in a single well:

[0085] Z = FI * S * Y

[0086] After normalizing the composite crack identification curve (Z), it can better reflect the location of crack development:

[0087]

[0088] To more clearly illustrate the single-well fracture identification method based on two-way constraints of rock mechanics and geostress provided in this embodiment, a specific example is provided:

[0089] First, by surveying the distribution of coring wells in the study area, data on the coring intervals, coring recovery rates, and core lengths of each coring well were obtained. Individual fracture characteristic parameters of each coring well were identified and statistically analyzed to accurately locate the longitudinal influence range of fractures in each well. Second, imaging logging data from special logging methods in the study area were collected, particularly dynamic and static images from these special logging methods. This allowed for observation of fracture development locations, depths, and lengths in wells containing special logging data, compensating for the limited coring of the target intervals in the coring wells. Furthermore, collecting FVDC curves from special logging methods improved the accuracy of artificial fracture identification. Finally, conventional logging data from coring wells and wells to be predicted were collected, ensuring at least AC (acoustic transit time curve) and CAL (caliber curve). All conventional logging curves were standardized to facilitate subsequent calculations and identification of fracture development locations in individual wells. Additionally, dipole shear wave logging data from special logging methods should be collected based on the actual conditions of the study area to facilitate subsequent calculations and identification of fracture development locations in individual wells.

[0090] After the initial operations are completed, rock mechanical parameters are calculated using the method provided in this embodiment. The fracture development index (FI), a parameter representing the fracture development location in the rock mechanical layer, is determined. The geostress parameters, horizontal stress difference (S) and stress heterogeneity coefficient (Y), which represent the fracture development location in the geostress layer, are determined using the well logging curve. By comparing the three-parameter curves with the fracture development locations statistically obtained from core wells and imaging wells, the data fluctuation range of the rock mechanical layer in the fracture development location can be determined. After statistically analyzing the fluctuation range of parameters in the crack development index (FI) across crack development locations, three crack development ranges were found: 0.493–0.563, 0.593–0.603, and 0.663–0.673. Four crack development ranges were found for the horizontal stress difference (S): 35.567–35.812, 36.057–36.302, 37.282–37.527, and 39.977–40.712. Two crack development ranges were found for the stress heterogeneity coefficient (Y): 1.407–1.4105 and 1.4315–1.163. Figure 2As shown. After constructing a comprehensive fracture identification curve (Z) using the fracture development intervals of the three parameters, a comprehensive prediction of the fracture development location in a single well can be performed, such as... Figure 3 As shown.

[0091] This embodiment provides a single-well fracture identification method based on two-way constraints of rock mechanics and geostress. Based on statistical analysis results of core samples and fractures from special logging in the study area, it clarifies the parameter fluctuation range of fracture development locations after calculating rock mechanics and geostress parameters using conventional logging curves. This parameter fluctuation range is then used to filter the rock mechanics and geostress parameters of the single well to be predicted. A comprehensive fracture identification curve is constructed using constraints in both directions, and then the fracture development location of the single well is predicted. This method addresses the problem that when using logging curves for reservoir fracture identification and characterization, many methods rely on mathematical approaches to analyze the response characteristics of various types of curves to fracture development locations, neglecting the fact that the rock mechanics properties and geostress disturbance phenomena of the rock itself when fractures exist will significantly deviate from the original formation, thus resulting in limited identification accuracy. This method improves the accuracy of single-well fracture identification.

[0092] This embodiment starts with the rock mechanical properties and geostress disturbance phenomena when rocks have fractures, and predicts the location of fracture development in a single well. This greatly reduces the error caused by using mathematical methods to study the response of various types of curves at the location of fracture development, improves the accuracy of single-well fracture identification, and provides an effective solution for professionals who predict the location of fracture development in a single well.

[0093] Example 2

[0094] This embodiment provides a single-well fracture identification device based on bidirectional constraints of rock mechanics and geostress, including:

[0095] The data acquisition module is used to acquire core well data, special logging data, and conventional logging data in the study area;

[0096] The core well data analysis module is used to determine the fracture characteristic parameters of a single well based on the core well data.

[0097] A special logging data analysis module is used to determine characteristic parameters of fracture development locations based on the special logging data;

[0098] The conventional logging data analysis module is used to obtain conventional logging curves based on the conventional logging data;

[0099] The rock mechanics parameter calculation module is used to calculate rock mechanics parameters based on the conventional logging curves and determine the fracture development index, which characterizes the fracture development location in the rock mechanics layer.

[0100] The geostress parameter calculation module is used to calculate geostress parameters based on the conventional logging curves, and to determine the horizontal stress difference and stress heterogeneity coefficient of the geostress layer characterizing the fracture development area.

[0101] The fluctuation range determination module is used to compare the fracture development index, the horizontal stress difference, and the stress heterogeneity coefficient with the single-well fracture characteristic parameters and the fracture development location characteristic parameters to obtain the fluctuation range of the fracture development location parameters.

[0102] The fluctuation range screening module is used to screen wells for which the fracture development location needs to be predicted based on the fluctuation range of the fracture development location parameter.

[0103] The single-well fracture development location prediction module is used to construct a comprehensive fracture identification curve based on the screened fracture development index, horizontal stress difference, and stress heterogeneity coefficient, and to predict the fracture development location of a single well.

[0104] For details on the implementation of each module in a single-well fracture identification device based on rock mechanics and geostress bidirectional constraints, please refer to the above description of the limitations of a single-well fracture identification method based on rock mechanics and geostress bidirectional constraints, which will not be repeated here.

[0105] Example 3

[0106] This embodiment provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of a single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress.

[0107] The technical features of the above embodiments can be combined in any way (as long as there is no contradiction in the combination of these technical features). For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described; these embodiments not explicitly written should also be considered to be within the scope of this specification.

Claims

1. A single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress, characterized in that, include: Step 1: Obtain core well data, special logging data, and conventional logging data for the study area; Step 2: Determine the fracture characteristic parameters of a single well based on the core well data; Step 3: Determine the characteristic parameters of the fracture development location based on the specific logging data; Step 4: Obtain conventional logging curves based on the conventional logging data; Step 5: Calculate the rock mechanics parameters based on the conventional logging curves, and determine the fracture development index, which characterizes the fracture development location in the rock mechanics layer; Step 6: Calculate the geostress parameters based on the conventional logging curves, and determine the horizontal stress difference and stress heterogeneity coefficient of the geostress layer that characterize the fracture development area; Step 7: Compare the fracture development index, the horizontal stress difference, and the stress heterogeneity coefficient with the single-well fracture characteristic parameters and the fracture development location characteristic parameters to obtain the fluctuation range of the fracture development location parameters; Step 8: Based on the fluctuation range of the fracture development location parameters, screen the wells for which the fracture development location needs to be predicted by the fluctuation range. Step 9: Construct a comprehensive fracture identification curve based on the screened fracture development index, horizontal stress difference, and stress heterogeneity coefficient, and predict the fracture development location in a single well.

2. The single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress as described in claim 1, characterized in that, In step 2, the single-well fracture characteristic parameters include fracture development location, depth, and fracture length data.

3. The single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress as described in claim 1, characterized in that, In step 3, the special logging includes imaging logging and dipole shear wave logging.

4. The single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress as described in claim 3, characterized in that, In step 4, the conventional logging curves include sonic transit time curves, density curves, and wellbore diameter curves.

5. The single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress as described in claim 4, characterized in that, In step 5, when calculating rock mechanical parameters based on the conventional logging curves, if the dipole shear wave logging exists in the study area and the target layer can be collected with usable shear wave logging curves, the P-wave logging curve is first calculated based on the shear wave logging curve using the P-wave to S-wave conversion formula. Then, the Young's modulus and Poisson's ratio in the rock mechanical parameters are calculated using the P-wave and S-wave transit times. Finally, the fracture development index is calculated based on the Young's modulus and Poisson's ratio.

6. The single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress as described in claim 5, characterized in that, If the dipole shear wave logging exists in the study area, but no usable shear wave logging curves are collected for the target layer, or the collected shear wave logging curves are unusable, a correlation fitting curve needs to be constructed based on the existing shear wave logging curves and the sonic transit time curves to convert the conventional logging curves into shear wave transit time curves, and then the longitudinal wave transit time curves are calculated.

7. The single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress as described in claim 5, characterized in that, In step 6, the horizontal stress difference and the stress heterogeneity coefficient are calculated based on the Poisson's ratio and the triaxial geostress of a single well.

8. The single-well fracture identification method based on bidirectional constraints of rock mechanics and geostress as described in claim 1, characterized in that, In step 9, three curves need to be constructed when building the comprehensive crack identification curve.

9. A single-well fracture identification device based on bidirectional constraints of rock mechanics and geostress, characterized in that, include: The data acquisition module is used to acquire core well data, special logging data, and conventional logging data in the study area; The core well data analysis module is used to determine the fracture characteristic parameters of a single well based on the core well data. A special logging data analysis module is used to determine characteristic parameters of fracture development locations based on the special logging data; The conventional logging data analysis module is used to obtain conventional logging curves based on the conventional logging data; The rock mechanics parameter calculation module is used to calculate rock mechanics parameters based on the conventional logging curves and determine the fracture development index, which characterizes the fracture development location in the rock mechanics layer. The geostress parameter calculation module is used to calculate geostress parameters based on the conventional logging curves, and to determine the horizontal stress difference and stress heterogeneity coefficient of the geostress layer characterizing the fracture development area. The fluctuation range determination module is used to compare the fracture development index, the horizontal stress difference, and the stress heterogeneity coefficient with the single-well fracture characteristic parameters and the fracture development location characteristic parameters to obtain the fluctuation range of the fracture development location parameters. The fluctuation range screening module is used to screen wells for which the fracture development location needs to be predicted based on the fluctuation range of the fracture development location parameter. The single-well fracture development location prediction module is used to construct a comprehensive fracture identification curve based on the screened fracture development index, horizontal stress difference, and stress heterogeneity coefficient, and to predict the fracture development location of a single well.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

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