Quantitative evaluation method for crack complexity after compression damage

Abstract

The invention belongs to the technical field of petroleum and natural gas geology and rock mechanics, and particularly relates to a quantitative evaluation method for crack complexity after compression damage. Compared with an existing method based on statistics and mainly evaluating from single factors (crack length, density, form, trend and the like), the method provided by the invention has the advantages that on the basis of an in-situ compression CT scanning experiment, the crack connectivity index and the crack fractal dimension of the post-compression plunger sample are calculated, and the weight coefficients of the two are respectively obtained by utilizing an entropy weight method; and comprehensively evaluating the crack complexity after pressure damage. According to the method, the fracture connectivity index and the fracture fractal dimension are fully considered, factors are comprehensively considered, the operability is high, and the result credibility is high. The method is not only suitable for exploitation effect evaluation of shale oil and tight oil reservoirs, but also can be applied to other types of oil reservoirs and rock engineering.

Description

Technical Field

[0001] This invention belongs to the fields of petroleum and natural gas geology and rock mechanics, and specifically relates to a method for quantitatively evaluating the complexity of fractures after compressive failure. Background Technology

[0002] Currently, the commercial development of unconventional shale oil and gas, tight oil and gas, and coalbed methane generally requires fracturing. Therefore, conducting quantitative evaluation of the complexity of fractures after pressure failure is of great practical significance.

[0003] Patent CN106769463B, authorized by patent number CN106769463B, proposes a method for quantitatively characterizing the post-fracturing complexity of core samples. It extracts the dip angle and area of ​​each fracture from post-fracturing images of the plunger-shaped core, calculates the surface fracture ratio and fracture dip angle dispersion of the post-fracturing core, normalizes these figures, and then averages and sums them to obtain the post-fracturing complexity of the core sample. This method can quantitatively evaluate the ability to form a fracture network during fracturing. Patent CN112304770A, applied for by patent, proposes a method and system for quantitatively analyzing the post-fracturing complexity of fractures. It quantitatively evaluates the post-fracturing complexity of fractures by using the number of peaks in the GdP / dG curve, the maximum slope of the first part of the GdP / dG curve, and the standard deviation of the second part. The first part refers to the curve portion of the GdP / dG curve from the origin to the first peak and then to the first trough, and the second part refers to the curve portion of the GdP / dG curve from the first trough to the endpoint. Patent application CN115808352A proposes a method and apparatus for extracting and characterizing the complexity of rock fractures based on digital cores. First, a simulated fracturing experiment is conducted on the cut and processed core sample to obtain CT scan images of the core sample before and after the simulated fracturing experiment. Based on these images, digital cores are constructed for both the pre- and post-fracturing stages, and the original fracture features and post-fracturing fracture features are extracted. Then, fracture increment and fracture morphology are obtained, and finally, a three-dimensional complexity characterization model of the post-fracturing fractures is constructed. Patent application CN111597671A proposes a method and system for determining the complexity of fracture networks based on probability distribution. A three-dimensional space containing all microseismic events is established based on event information from microseismic events formed during hydraulic fracturing. Microseismic event information at different locations within a preset three-dimensional space is selected according to predetermined rules, and the fracture network complexity is determined based on the event information selected at different locations within the three-dimensional space.

[0004] The methods mentioned above often evaluate crack complexity based on a single factor, or consider multiple factors but fail to account for their weights, leading to errors in the evaluation results. Summary of the Invention

[0005] The purpose of this invention is to provide a method for quantitatively evaluating the complexity of cracks after compressive failure, thereby overcoming the aforementioned technical problems in the prior art.

[0006] Therefore, the technical solution provided by the present invention is as follows: A method for quantitatively evaluating the complexity of cracks after compressive failure includes the following steps: Step 1) Collect core samples from the target formation in the study area and record the sampling depth and lithology of the samples; Step 2) Prepare the core sample into a plunger test sample; Step 3) Use CT scans to scan the plunger test samples. After three-dimensional reconstruction, select three similar plunger test samples and number them S1, S2, and S3 respectively. Step 4) Perform in-situ compression CT scan experiments on the three selected plunger test samples until the plunger test samples are destroyed. Apply the same displacement to the three plunger test samples, obtain three-dimensional scan data CT images, and obtain the three-dimensional volume of the test samples based on this. Step 5) Based on the three-dimensional volume of the experimental sample, calculate the crack connectivity index using topological structure theory. I ; Step 6) Based on the three-dimensional volume of the experimental sample, calculate the fractal dimension of the crack using fractal analysis theory. C ; Step 7) Calculate the crack connectivity index I and the fractal dimension of the crack C Normalize them separately; Step 8) Based on data normalization, calculate the weight coefficients between the two using the entropy weight method. p and q This allows for a quantitative evaluation of the crack complexity after compressive failure. F , F It is in the range of 0-1, and the larger the value, the more complex it is.

[0007] In step 1), the lithology is clastic rock or carbonate.

[0008] In step 2), the diameter of the plunger experimental sample is 6 mm and the height is 12 mm. The upper and lower end faces are made parallel by grinding or lathe.

[0009] In step 3), three similar plunger test samples are selected based on porosity, permeability, and pore structure.

[0010] In step 4), Avizo or Dragonfly software is used to perform 3D reconstruction to obtain the 3D volume of the experimental sample.

[0011] In step 5), the crack connectivity index is calculated using topological structure theory. I Specifically, it is calculated using the following formula:

[0012] In the formula: N I express I Number of nodes N Y express Y Number of nodes N X express X Number of nodes.

[0013] Step 6) Calculate the fractal dimension of the crack using fractal analysis theory. C Specifically as follows: The fractal dimension of the crack was calculated using the area coverage method. C :

[0014] In the formula: N For the number, S″ It is per unit area. δ This is the scaling factor.

[0015] In step 7), normalization is performed to remove the influence of units, using the Max-Min method:

[0016] In the formula: X i Represents normalized data. x max This represents the maximum value of the data. x min This represents the minimum value of the data. x i Represents any data.

[0017] Step 8) Crack complexity F The following formula is used to calculate:

[0018] In the formula: j Indicates the plunger test sample number. I j * Indicates the first j Normalized value of crack connectivity index of each plunger test sample C j * Indicates the first j Normalized value of the crack fractal dimension of each plunger test sample; p j express I j *The weighting coefficients, q j express C j *of Weighting coefficients.

[0019] The beneficial effects of this invention are: The present invention provides a quantitative evaluation method for fracture complexity after compressive failure, which comprehensively considers fracture connectivity and fracture fractal dimension. Based on in-situ compression CT scanning, it uses the entropy weight method to obtain the weight coefficients of fracture connectivity and fracture fractal dimension, and then comprehensively evaluates the fracture complexity after compressive failure. The evaluation has high accuracy and reliability, can more comprehensively reflect the complexity of fractures, and can more accurately assess the impact of fractures on oil and gas flow and reservoir development. Attached Figure Description

[0020] Figure 1 This is a technical flowchart for characterizing fracture complexity based on three-dimensional CT analysis of drilling cores; Figure 2 This is a schematic diagram showing the sample specifications for the core plunger experiment and the three-dimensional reconstruction results from CT scans. Figure 3 This is a schematic diagram of crack connectivity in topological analysis; Figure 4 It is a quantitative evaluation of the complexity of cracks after compressive failure. Detailed Implementation

[0021] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification.

[0022] Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0023] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0024] Example 1 This embodiment provides a method for quantitatively evaluating the complexity of cracks after compressive failure, such as... Figure 1 As shown, it includes the following steps: Step 1) Collect core samples from the target formation in the study area and record the sampling depth and lithology of the samples; Step 2) Prepare the core sample into a plunger test sample; Step 3) Use CT scans to scan the plunger test samples. After three-dimensional reconstruction, select three similar plunger test samples and number them S1, S2, and S3 respectively. Step 4) Perform in-situ compression CT scan experiments on the three selected plunger test samples until the plunger test samples are destroyed. Apply the same displacement to the three plunger test samples, obtain three-dimensional scan data CT images, and obtain the three-dimensional volume of the test samples based on this. Step 5) Based on the three-dimensional volume of the experimental sample, calculate the crack connectivity index using topological structure theory. I ; Step 6) Based on the three-dimensional volume of the experimental sample, calculate the fractal dimension of the crack using fractal analysis theory. C ; Step 7) Calculate the crack connectivity index I and the fractal dimension of the crack C Normalize them separately; Step 8) Based on data normalization, calculate the weight coefficients between the two using the entropy weight method. p and q This allows for a quantitative evaluation of the crack complexity after compressive failure. F , F It is in the range of 0-1, and the larger the value, the more complex it is.

[0025] Existing methods for evaluating fracture complexity after compressive failure are mostly based on statistical methods, often evaluating single factors (fracture length, density, morphology, orientation, etc.), or considering multiple factors but without considering their weights, resulting in relatively low accuracy and significant errors in assessing fracture network complexity. The method proposed in this invention, based on in-situ compression CT scanning experiments, calculates the fracture connectivity index and fracture fractal dimension of the post-compression plunger sample, and uses the entropy weight method to obtain the weight coefficients of these two factors, thereby comprehensively evaluating the fracture complexity after compressive failure. This method fully considers the fracture connectivity index and fracture fractal dimension, comprehensively considers factors, is highly operable, and yields highly reliable results. It is not only applicable to evaluating the development effect of shale oil and tight oil reservoirs, but can also be applied to other types of reservoirs and rock engineering.

[0026] Example 2 Based on Example 1, this example provides a method for quantitatively evaluating the complexity of cracks after compressive failure. The specific steps are as follows: Step 1) Collect typical interbedded shale oil reservoir samples from the study area, and record the sampling depth and lithology of the samples. The selected samples cover various geological conditions that affect mobility, including reservoir layer thickness, porosity, average pore size, shale layer thickness, and total organic carbon content.

[0027] Step 2) Prepare several plunger test samples from the collected drilling core samples, each 6 mm in diameter and 12 mm in height. Machine the end faces of the samples using a grinder or lathe to ensure the upper and lower end faces are parallel. The plunger test samples are as follows: Figure 2 As shown; Step 3) Using CT scans of the plunger test samples prepared in Step 2, after three-dimensional reconstruction, select three plunger test samples with similar porosity, permeability and pore structure, and record the plunger test sample numbers as S1, S2 and S3 respectively. Step 4) Perform in-situ compression CT scans on the three plunger test samples until the samples are destroyed. All three samples are subjected to the same displacement, and 3D CT scan data are obtained. Based on this, the 3D volume of the test samples is reconstructed using Avizo and Dragonfly software. Figure 2 As shown; Step 5) Based on the obtained three-dimensional volume of the experimental sample, such as... Figure 3 As shown, the crack connectivity index is calculated using topological structure theory. I：

[0028] In the formula: N I express I Number of nodes N Y express Y Number of nodes N X express X Number of nodes; Step 6) Based on the obtained three-dimensional volume of the experimental sample, such as... Figure 4 As shown, the fractal dimension of the crack is calculated using the area coverage method based on fractal analysis theory. C : The fractal dimension of the crack was calculated using the area coverage method. C :

[0029] In the formula: N For the number, S″ It is per unit area. δ This is the scaling factor.

[0030] Step 7) In the obtained I and CBased on this, normalization is performed separately to remove the influence of units, and the Max-Min method is used:

[0031] In the formula: X i Represents normalized data. x max This represents the maximum value of the data. x min This represents the minimum value of the data. x i Represents any data; Step 8) Based on data normalization, such as... Figure 4 As shown; the weighting coefficients between the two are calculated using the entropy weighting method. p and q This allows for a quantitative evaluation of the crack complexity after compressive failure. F :

[0032] In the formula: j Indicates the plunger test sample number. I j * Indicates the first j Normalized value of crack connectivity index of each plunger test sample C j * Indicates the first j Normalized value of the crack fractal dimension of each plunger test sample; p j express I j * The weighting coefficients, q j express C j *of Weighting coefficients; Among them, crack complexity F The value is between 0 and 1, and the larger the value, the more complex it is.

[0033] This invention comprehensively considers fracture connectivity and fracture fractal dimension, and uses the entropy weight method to obtain the weight coefficients of fracture connectivity and fracture fractal dimension respectively, which improves the accuracy and reliability of the evaluation, can more comprehensively reflect the complexity of fractures, and can more accurately assess the impact of fractures on oil and gas flow and reservoir development.

[0034] The above examples are merely illustrative of the present invention and do not constitute a limitation on the scope of protection of the present invention. All designs that are the same as or similar to the present invention are within the scope of protection of the present invention.

Claims

1. A method for quantitatively evaluating the complexity of cracks after compressive failure, characterized in that: Includes the following steps: Step 1) Collect core samples from the target formation in the study area and record the sampling depth and lithology of the samples; Step 2) Prepare the core sample into a plunger test sample; Step 3) Use CT scans to scan the plunger test samples. After three-dimensional reconstruction, select three similar plunger test samples and number them S1, S2, and S3 respectively. Step 4) Perform in-situ compression CT scan experiments on the three selected plunger test samples until the plunger test samples are destroyed. Apply the same displacement to the three plunger test samples, obtain three-dimensional scan data CT images, and obtain the three-dimensional volume of the test samples based on this. Step 5) Based on the three-dimensional volume of the experimental sample, calculate the crack connectivity index using topological structure theory. I ; Step 6) Based on the three-dimensional volume of the experimental sample, calculate the fractal dimension of the crack using fractal analysis theory. C ; Step 7) Calculate the crack connectivity index I and the fractal dimension of the crack C Normalize them separately; Step 8) Based on data normalization, calculate the crack connectivity index using the entropy weight method. I and the fractal dimension of the crack C Weighting coefficients p and q This allows for a quantitative evaluation of the crack complexity after compressive failure. F , F It is in the range of 0-1, and the larger the value, the more complex it is.

2. The method for quantitatively evaluating the complexity of cracks after compressive failure according to claim 1, characterized in that: In step 1), the lithology is clastic rock or carbonate.

3. The method for quantitatively evaluating the complexity of cracks after compressive failure according to claim 1, characterized in that: In step 2), the diameter of the plunger experimental sample is 6 mm and the height is 12 mm. The upper and lower end faces are made parallel by grinding or lathe.

4. The method for quantitatively evaluating the complexity of cracks after compressive failure according to claim 1, characterized in that: In step 3), three similar plunger test samples are selected based on porosity, permeability, and pore structure.

5. The method for quantitatively evaluating the complexity of cracks after compressive failure according to claim 1, characterized in that: In step 4), Avizo or Dragonfly software is used to perform 3D reconstruction to obtain the 3D volume of the experimental sample.

6. The method for quantitatively evaluating the complexity of cracks after compressive failure according to claim 1, characterized in that: In step 5), the crack connectivity index is calculated using topological structure theory. I Specifically, it is calculated using the following formula: In the formula: N I express I Number of nodes N Y express Y Number of nodes N X express X Number of nodes.

7. The method for quantitatively evaluating the complexity of cracks after compressive failure according to claim 1, characterized in that: Step 6) Calculate the fractal dimension of the crack using fractal analysis theory. C Specifically as follows: The fractal dimension of the crack was calculated using the area coverage method. C : In the formula: N For the number, S″ It is per unit area. δ This is the scaling factor.

8. The method for quantitatively evaluating the complexity of cracks after compressive failure according to claim 1, characterized in that: In step 7), normalization is performed to remove the influence of units, using the Max-Min method: In the formula: X i Represents normalized data. x max This represents the maximum value of the data. x min This represents the minimum value of the data. x i Represents any data.

9. The method for quantitatively evaluating the complexity of cracks after compressive failure according to claim 1, characterized in that: Step 8) Crack complexity F The following formula is used to calculate: In the formula: j Indicates the plunger test sample number. I j * Indicates the first j Normalized value of crack connectivity index of each plunger test sample C j * Indicates the first j Normalized value of the crack fractal dimension of each plunger test sample; p j express I j * The weighting coefficients, q j express C j *of Weighting coefficients.

Images