Method for determining rock brittleness based on acoustic emission experiment

Abstract

The invention discloses a method for determining rock brittleness based on an acoustic emission experiment, relates to the field of rock mechanics testing in oil and gas field development engineering, and aims to overcome the defects of single parameter, large error and difficulty in dynamic characterization of rock brittleness based on static state at present, the method comprises the following steps: preparing a standard rock sample with the diameter of 25mm and the height of 25mm, applying an axial load by adopting an RTR-1000 testing machine, and determining the rock brittleness based on the acoustic emission experiment. The SAEU2S system collects whole-course acoustic emission signals; acoustic emission characteristic parameters are extracted, an RA value and an AF value are calculated, and a fracture mode is represented; calculating an acoustic emission b value by using a least square method and a sliding window method based on an earthquake magnitude-frequency relational expression, and representing a fracture scale through an average value and a standard deviation of the acoustic emission b value; and by taking the RA value, the AF value, the average value of the b value and the standard deviation as input, constructing a brittleness prediction model by adopting a support vector regression algorithm, and outputting a result. The rock dynamic fracture signal is directly captured, multi-dimensional comprehensive evaluation is achieved, complex data processing is avoided, errors are small, the standardization degree is high, economy and efficiency are achieved, and the real rock brittleness can be accurately depicted.

Description

Technical Field

[0001] This invention relates to the field of rock mechanics testing technology in oil and gas field development engineering, specifically a method for determining rock brittleness based on acoustic emission experiments. Background Technology

[0002] Rock brittleness is an important reference indicator for evaluating the fracturability of unconventional oil and gas reservoirs and designing hydraulic fracturing schemes. It is also an important influencing factor in horizontal well deployment and the selection of engineering sweet spots. Rocks with high brittleness are more likely to form complex fracture networks after fracturing, resulting in better reservoir stimulation effects.

[0003] Currently, there is no unified definition of brittleness, resulting in numerous calculation methods. Generally, brittleness characterizes the ability of a rock to resist inelastic deformation before failure and to generate and maintain crack propagation after fracturing, and is closely related to the rock's failure process. Previous researchers have primarily determined rock brittleness through uniaxial or triaxial rock compression tests, tensile strength tests, and XRD whole-rock mineral analysis, considering mechanical parameters, stress-strain curves throughout the entire process, and rock mineral composition. Some scholars use Poisson's ratio and elastic modulus from elastic parameters to characterize rock brittleness; others use tensile strength and fracture toughness from rock strength parameters to calculate brittleness; still others represent rock brittleness based on the content of brittle minerals in the rock; additionally, dividing the stress-strain curve throughout the entire process into energy regions (dissipated energy, elastic energy, fracture energy) and reading energy evolution parameters is also a method for calculating rock brittleness.

[0004] Among similar technical solutions, Wei Jingyi[1] proposed to evaluate the brittleness of rocks based on the distribution law of energy in rock acoustic emission signals by wavelet packet decomposition and the characteristic that rocks with high brittle mineral content usually exhibit a more concentrated distribution of acoustic emission signal energy (i.e., energy release is faster and more concentrated when fractured).

[0005] Existing brittleness calculation methods all have certain limitations: Using elastic parameters (such as the brittleness index based on elastic modulus and Poisson's ratio) to calculate rock brittleness can only reflect the mechanical properties of rocks in the elastic deformation stage in isolation, and cannot fully characterize rock brittleness. Brittleness is a comprehensive mechanical behavior parameter that reflects the entire process of rock from damage accumulation, yielding to post-peak fracture and even instability. Calculating rock brittleness using mineral composition is essentially a static and empirical method. It ignores the combined effects of rock formation, microstructure, geostress environment, and temperature and pressure conditions on brittleness, and cannot accurately distinguish rock brittleness. Even rocks with the same mineral composition may exhibit drastically different brittleness characteristics under different regions or burial depths due to different stresses and geological histories. While calculating the rock brittleness index by dividing the energy evolution process (such as elastic strain energy and dissipated energy) using the stress-strain curve throughout the entire process has a clear physical meaning, it is prone to large human errors when accurately dividing the energy region and precisely reading the characteristic parameter points. The methods mentioned above all start from a single perspective or static properties. The parameters used (such as brittle mineral content, elastic modulus and Poisson's ratio) are a certain aspect of the static properties or macroscopic mechanical response of rocks. Brittleness is a parameter that describes the complex characteristics of the dynamic fracture process of rocks. Its essence is the concentrated manifestation of the mechanical behavior of the dynamic process of microcrack initiation, propagation, convergence and macroscopic failure. Therefore, traditional methods are difficult to comprehensively, accurately and dynamically depict the true brittleness of rocks. Summary of the Invention

[0006] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a method for determining rock brittleness based on acoustic emission experiments. This method has the advantage of quantitative characterization of rock brittleness in scenarios such as evaluation of the fracturability of unconventional oil and gas reservoirs, design of hydraulic fracturing schemes, deployment of horizontal wells, and selection of engineering sweet spots. It solves the problem of difficulty in comprehensively, accurately, and dynamically depicting the true brittleness of rocks.

[0007] (II) Technical Solution To achieve the quantitative characterization of rock brittleness in scenarios such as evaluation of the fracturability of unconventional oil and gas reservoirs, design of hydraulic fracturing schemes, deployment of horizontal wells, and selection of engineering sweet spots, the present invention provides the following technical solution: A method for determining rock brittleness based on acoustic emission experiments includes the following steps: S1. A cylindrical rock core is drilled from the full-diameter rock core and processed into a standard specimen. An axial load is applied to the standard specimen using a programmable servo rock rigidity testing machine. At the same time, an acoustic emission testing system is used to monitor and collect the full-process acoustic emission signal generated during the compression process of the specimen. S2. Read the rise time, amplitude, ring count and duration characteristic parameters from the collected acoustic emission signal, and calculate the RA value and AF value, where the RA value is the ratio of rise time to amplitude and the AF value is the ratio of ring count to duration. The RA value and AF value reflect the rock fracture mode. S3. Based on the magnitude-frequency relationship proposed by Gutenberg and Richter in seismology.

[0008] Where M is the magnitude of the earthquake; N is the number of earthquakes at that magnitude; a and b are constants, where b is the b-value in seismology. In the calculation of acoustic emission b-value, the magnitude M is represented by the acoustic emission amplitude divided by 20 or the logarithm of the energy. The number of acoustic emission events N with an amplitude greater than A within a window is used instead of the number of earthquakes at magnitude M. The acoustic emission b-value is calculated using the least squares method and the sliding window method. The rock fracture scale is characterized by the mean and standard deviation of the b-value. S4. Using the average value of b and the standard deviation of b obtained in step S3, and the RA value and AF value obtained in step S2 as input parameters, a rock brittleness prediction model is constructed using the support vector regression algorithm and energy theory as the output basis. S5. Output the rock brittleness evaluation results through the brittleness prediction model. Preferably, the standard sample in step S1 has a diameter of 25 mm and a height of 25 mm.

[0009] Preferably, the programmable servo rock rigidity testing machine mentioned in step S1 is an RTR-1000 programmable servo rock rigidity testing machine, and the acoustic emission testing system is an SAEU2S acoustic emission testing system.

[0010] Preferably, in step S2, when reflecting the rock fracture mode, high RA value and low AF value correspond to the development and propagation of shear cracks, and low RA value and high AF value correspond to the development and propagation of tensile cracks. Furthermore, cases with an RA / AF value greater than 0.25 are classified as shear crack development and propagation.

[0011] Preferably, the formula for calculating the acoustic emission b-value using the least squares method in step S3 is as follows:

[0012] in, Dm Classify acoustic emission events by interval; M i Let i be the number of acoustic emission events in the i-th segment; N i Let be the number of events in the i-th level.

[0013] Preferably, when using the sliding window method in step S3, the magnitude interval is set to 0.2, the sample sliding window size is set to 200, the step size is set to 20, and each sliding maintains 90% data overlap between windows.

[0014] Preferably, in step S3, the lower the average value of b, the stronger the overall brittleness of the rock; the larger the standard deviation of b, the more active the microfractures in the rock and the stronger the brittleness.

[0015] Preferably, the higher the proportion of tensile cracks in step S2, the more significant the brittleness of the rock is; in step 3), the decrease of the b value indicates an increase in the proportion of large-scale fractures in the rock and a stronger brittleness.

[0016] (III) Beneficial Effects Compared with existing technologies, the present invention provides a method for determining the brittleness of rocks based on acoustic emission experiments, which has the following advantages: 1. This invention is mainly based on a rock acoustic emission experiment method. This method directly captures and analyzes the acoustic emission response signals of rocks throughout the entire process from microcrack initiation and propagation to macroscopic failure, effectively reflecting the nature of brittle fracture. It avoids the limitations of traditional methods that rely on indirect calculations based on static parameters (such as mineral composition) or stress-strain curve morphology, and is more in line with the definition of brittleness as a comprehensive characteristic reflecting a dynamic fracture process.

[0017] 2. This invention comprehensively calculates brittleness from two physically distinct and complementary core aspects: fracture mode and fracture scale. The RA-AF value reveals the microscopic mechanism of fracture (the higher the proportion of tensile fracture, the more significant the brittle characteristics), while the b-value reflects the energy distribution and evolution of the fracture event (a decrease in the b-value indicates large-scale fracture and higher brittleness). This multi-dimensional evaluation overcomes the one-sidedness of traditional methods (such as relying solely on mineral composition or elastic parameters) from a single perspective, making the evaluation results more comprehensive and accurate.

[0018] 3. This invention only requires standard rock acoustic emission experiments, eliminating the need for complex and subjective energy region division and parameter reading of stress-strain curves, greatly reducing errors. The operation process is standardized and highly repeatable. Furthermore, this method saves time and costs in subsequent data processing, making it an economical, efficient, and reliable means of brittleness assessment with promising application prospects. Attached Figure Description

[0019] Figure 1 Block diagram of rock acoustic emission test system; Figure 2 To simplify the waveform parameters of the acoustic emission signal; Figure 3 This is a density distribution map of RA-AF values; Figure 4 This is a graph showing the change in the value of b. Figure 5 The image shows the fitting effect of the acoustic emission-based model. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] (1) Quantitative description of rock fracture modes based on acoustic emission experiments This invention monitors the acoustic emission signals of rocks under stress through rock acoustic emission experiments, calculates the RA and AF values ​​of the rocks, and quantitatively describes the rock fracture mode.

[0022] The acoustic emission experiments were conducted using an RTR-1000 programmable servo rock rigidity testing machine and a SAEU2S acoustic emission testing system. Cylindrical core samples drilled from full-diameter rock cores were processed into standard specimens with a diameter of 25 mm and a height of 25 mm. An axial load was applied to the specimens, and the acoustic emission signals generated by the rock during the compression process were monitored. Figure 1 As shown in the figure. 1 is the AE transducer, 2 is the preamplifier, and 3 is a spacer; this illustrates the hardware composition and connection relationships for acoustic emission signal acquisition. Characteristic parameters are reread from the acoustic emission signal to calculate the RA and AF values. The RA value is the ratio of rise time to amplitude, and the AF value is the ratio of ring count to duration. Figure 2 As shown. The RA and AF values ​​can reflect the rock fracture mode. Generally, high RA and low AF values ​​correspond to the development and propagation of shear cracks; low RA and high AF values ​​correspond to the development and propagation of tensile cracks. Values ​​with RA / AF greater than 0.25 are used for further classification, such as... Figure 3 As shown; (2) Quantitative description of rock fracture scale based on b-value like Figure 4 and Figure 5 As shown, this invention uses the acoustic emission b-value to reflect the variation in the scale of microcracks within rocks. The b-value is derived from the magnitude-frequency relationship proposed by Gutenberg and Richter in seismological research.

[0023] In the formula, M is the magnitude of the earthquake; N is the number of earthquakes at that magnitude; a and b are constants, where b is the b-value in seismology. In the calculation of the acoustic emission b-value, the magnitude M is usually represented by the acoustic emission amplitude divided by 20 or the logarithm of the energy, and the number of acoustic emission events with an amplitude greater than A within a window is used to replace the number of earthquakes N with magnitude M.

[0024] The least squares method was used to calculate the acoustic emission b-value, with a magnitude interval of 0.2. The sample sliding window size was set to 200 and the step size to 20. Each sliding motion could maintain 90% data overlap between windows, thus giving the b-value calculation higher temporal resolution.

[0025]

[0026] In the formula, Dm Classify acoustic emission events by interval; Mi Let i be the number of acoustic emission events in the i-th segment; N i Let be the number of events in the i-th level.

[0027] An increase in the b-value indicates an increase in the proportion of small-scale rupture events, while a decrease in the b-value indicates an increase in the proportion of large-scale rupture events. Therefore, this is used.

[0028] (3) Characterizing rock brittleness based on rock fracture mode and fracture scale The proportion of large-scale fracturing events is characterized using the mean and standard deviation of acoustic emission b-values. A lower mean value indicates greater brittleness, reflecting the overall brittleness level. The standard deviation reflects the fluctuation range of the b-values; larger fluctuations indicate more active micro-fractures and greater brittleness. The proportion of tensile fracturing events is represented using RA and AF values. A brittleness prediction model is constructed using support vector regression with energy theory as the output, employing four parameters—mean b-value, standard deviation b-value, RA, and AF—as input parameters.

[0029] In summary, given the difficulty in accurately and comprehensively characterizing rock brittleness using conventional rock mechanical parameters (such as mineral composition and elastic parameters), this invention can, based on rock acoustic emission experiments, calculate the RA-AF value and b-value—two characteristic parameters—by analyzing the acoustic emission signals generated during loading. This allows for the quantitative characterization of the rock's fracture mode and fracture scale, and the integration of both parameters enables a scientific evaluation of rock brittleness.

[0030] This invention only involves rock acoustic emission experiments. The calculation of rock brittleness can be completed by collecting and analyzing acoustic emission signals without the need for complex subsequent data processing (such as dividing the stress-strain curve into energy stages). This reduces the errors caused by indirect parameter calculations, greatly saves experimental and analysis costs, and is economical and effective in determining the brittle characteristics of rocks.

[0031] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for determining the brittleness of rocks based on acoustic emission experiments, comprising the following steps: S1. A cylindrical rock core is drilled from the full-diameter rock core and processed into a standard specimen. An axial load is applied to the standard specimen using a programmable servo rock rigidity testing machine. At the same time, an acoustic emission testing system is used to monitor and collect the full-process acoustic emission signal generated during the compression process of the specimen. S2. Read the rise time, amplitude, ring count and duration characteristic parameters from the collected acoustic emission signal, and calculate the RA value and AF value, where the RA value is the ratio of rise time to amplitude and the AF value is the ratio of ring count to duration. The RA value and AF value reflect the rock fracture mode. S3. Based on the magnitude-frequency relationship proposed by Gutenberg and Richter in seismology. ； Where M is the magnitude of the earthquake; N is the number of earthquakes at that magnitude; a and b are constants, where b is the b-value in seismology. In the calculation of acoustic emission b-value, the magnitude M is represented by the acoustic emission amplitude divided by 20 or the logarithm of the energy. The number of acoustic emission events N with an amplitude greater than A within a window is used instead of the number of earthquakes at magnitude M. The acoustic emission b-value is calculated using the least squares method and the sliding window method. The rock fracture scale is characterized by the mean and standard deviation of the b-value. S4. Using the average value of b and the standard deviation of b obtained in step S3, and the RA value and AF value obtained in step S2 as input parameters, a rock brittleness prediction model is constructed by using the support vector regression algorithm and the brittleness index of energy evolution theory as the output basis. S5. Output the rock brittleness evaluation results through the brittleness prediction model.

2. The method for determining rock brittleness based on acoustic emission experiments according to claim 1, characterized in that, The standard sample in step S1 has a diameter of 25 mm and a height of 25 mm.

3. The method for determining rock brittleness based on acoustic emission experiments according to claim 1, characterized in that, The programmable servo rock rigidity testing machine mentioned in step S1 is an RTR-1000 programmable servo rock rigidity testing machine, and the acoustic emission testing system is an SAEU2S acoustic emission testing system.

4. The method for determining rock brittleness based on acoustic emission experiments according to claim 1, characterized in that, In step S2, when reflecting the rock fracture mode, high RA values ​​and low AF values ​​correspond to the development and propagation of shear cracks, while low RA values ​​and high AF values ​​correspond to the development and propagation of tensile cracks. Furthermore, cases with RA / AF values ​​greater than 0.25 are classified as shear crack development and propagation.

5. The method for determining rock brittleness based on acoustic emission experiments according to claim 1, characterized in that, The formula for calculating the acoustic emission b-value using the least squares method in step S3 is as follows: ； in, Dm Classify acoustic emission events by interval; M i Let i be the number of acoustic emission events in the i-th segment; N i Let be the number of events in the i-th level.

6. The method for determining rock brittleness based on acoustic emission experiments according to claim 1, characterized in that, In step S3, when using the sliding window method, the magnitude interval is set to 0.2, the sample sliding window size is set to 200, the step size is set to 20, and each sliding maintains 90% data overlap between windows.

7. The method for determining rock brittleness based on acoustic emission experiments according to claim 1, characterized in that, In step S3, the lower the average value of b, the stronger the overall brittleness of the rock; the larger the standard deviation of b, the more active the microfractures in the rock and the stronger the brittleness.

8. The method for determining rock brittleness based on acoustic emission experiments according to claim 1, characterized in that, In step S2, the higher the proportion of tensile cracks, the more significant the brittleness of the rock; in step 3), the decrease of the b value indicates an increase in the proportion of large-scale fractures and stronger brittleness of the rock.

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