Fracture-vug stratum well wall rock mechanical parameter prediction method based on well drilling chipping rock hardness

Abstract

The invention discloses a fracture-vug stratum well wall rock mechanical parameter prediction method based on well drilling chipping rock hardness in the fields of geomechanics, oil and gas well engineering and petroleum and natural gas exploitation. The method comprises the following steps: (1) well drilling chipping rock pretreatment and hardness testing; (2) constructing a quantitative relationship between rock skeleton mechanical parameters and hardness based on a homogeneous isotropic numerical model; (3) extracting stratum fracture-cavity structure characteristic parameters, and constructing fracture-cavity development rock numerical models of different sizes; (4) performing numerical simulation to calculate rock mechanical parameters of the fracture-vug development rock numerical models of different sizes; (5) well wall rock mechanical parameters of the fracture-cavity stratum are obtained through calculation; the invention provides a brand new theory and method for predicting and evaluating the mechanical parameters of the well wall rock of the complex structure stratum, and has important significance on safe drilling, efficient fracturing and the like of unconventional oil and gas resources such as deep and ultra-deep oil and gas, especially deep shale oil and gas of fracture-cavity development, deep complex carbonate rock oil and gas and the like.

Description

Technical Field

[0001] This invention relates to a method for predicting the rock mechanical parameters of fractured and cavernous formations based on the hardness of rock fragments during drilling, belonging to the fields of geomechanics, oil and gas well engineering, and oil and gas extraction. Background Technology

[0002] Wellbore rock mechanics is a key and fundamental aspect of engineering design, optimization, and implementation for oil and gas drilling fluid density design, wellbore stability evaluation, optimization of fracture propagation morphology, and improvement of reservoir fracturing efficiency. Currently, it is mainly achieved through methods such as rock mechanics laboratory analysis and calculation based on well logging information. However, rock mechanics experiments require drilling and coring of formation rocks, and the reliability of the results calculated using well logging data depends on the correction and constraints of rock mechanics experiments. In other words, accurate evaluation of wellbore rock mechanics parameters currently requires drilling and coring, followed by rock mechanics experiments. However, core sampling in oil and gas wells is costly, and fractured and cavernous formations are easily broken, making complete core sampling impossible. As a result, most well sections do not undergo formation coring, leading to widespread technical problems of poor accuracy and reliability in predicting wellbore mechanical parameters for uncorked sections. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for predicting the rock mechanical parameters of fractured and caved formations based on the hardness of rock that has detached during drilling. This method includes the following steps: (1) pretreatment and hardness testing of the rock that has detached during drilling; (2) constructing a quantitative relationship between the rock skeleton mechanical parameters and hardness based on a homogeneous isotropic numerical model; (3) extracting the structural characteristic parameters of the formation fractures and caves and constructing numerical models of fractured and caved rocks of different sizes; (4) numerically simulating and calculating the rock mechanical parameters of numerical models of fractured and caved rocks of different sizes; (5) calculating the rock mechanical parameters of the wellbore of fractured and caved formations. This invention is for complex structures. This method provides a novel theory and approach for predicting and evaluating the rock mechanics parameters of wellbore walls in formations. Furthermore, it eliminates the need for core drilling, utilizing rock fragments during the drilling process to reliably predict and evaluate these parameters. This new approach offers a fresh perspective on predicting and evaluating the rock mechanics parameters of wellbore walls in complex formations. It provides crucial support for ensuring wellbore stability, optimizing drilling and completion design, reducing the risk of wellbore collapse, controlling fracture propagation, and improving reservoir stimulation efficiency. This not only enhances engineering safety and economy but also holds significant importance for the safe and efficient drilling and exploitation of deep oil and gas, especially unconventional oil and gas resources such as shale gas and shale oil.

[0004] To achieve the above technical effects, the following technical solution is adopted: A method for predicting the rock mechanical parameters of fractured and caved formation wellbore based on the hardness of rock spalling during drilling, characterized by the following steps: Step 1: Pre-treatment and hardness testing of rock fragments dropped during drilling; Step 2: Construct a quantitative relationship between the mechanical parameters of the rock skeleton and its hardness based on a homogeneous isotropic numerical model; Step 3: Extract the structural feature parameters of the fractures and cavities in the strata and construct numerical models of rocks with fractures and cavities of different sizes; Step 4: Numerical simulation calculation of rock mechanical parameters for numerical models of rocks with different sizes of fractures and cavities; Step 5: Calculate the wellbore rock mechanical parameters of the fractured-vuggy formation; Furthermore, step 1 is performed according to the following steps: Step 11: Select drilling block samples that meet the size requirements. The size requirements for the blocks are: the length of the long side is not less than 20 mm and the thickness is not less than 8 mm. Step 12: Grind the two end faces of the chipped sample perpendicular to the thickness surface to make the two end faces flat and parallel. Step 13: Select a cross-section and mark the locations for the hardness test on it; Step 14: Perform hardness tests at each location point, record the load-displacement curve, and calculate the average hardness Py according to equation (1). avg , Py avg =∑(Py i ) / N (1) In the formula: Py avg Average hardness; N is the number of hardness test points; Py i Let be the hardness test value at the i-th position, in MPa, where i = 1, 2, ..., N; Furthermore, in step 13, there are no fewer than three hardness test locations, and the interval between each location is no less than 5 mm. Furthermore, step 2 is performed as follows: Step 21: Construct a homogeneous numerical model PM with a diameter of 25 mm and a thickness of 20 mm, and a homogeneous numerical model CM with a diameter of 25 mm and a height of 20 mm. Step 22: Set the mesoscopic elastic modulus of the numerical model PM with a diameter of 25 mm and a thickness of 20 mm to MesoE. M0 A closer look at the Poisson ratio reveals MesoU M0 Meso compressive strength is MesoCO M0 A numerical simulation experiment on the hardness of the model was conducted to obtain the hardness value Py. M0 ; Step 23: Repeat step 22 for a total of M simulation calculations; Step 24: For the numerical model CM with a diameter of 25mm and a height of 50mm, set the mesoscopic elastic modulus to MesoE. M0 +j×5000, Poisson's ratio is MesoU M0 +j×0.04, compressive strength is MesoCO M0 +j×5, conduct numerical simulation of compression mechanics to obtain the macroscopic elastic modulus E of the sample. Mj Poisson's ratio U Mj Compressive strength CO Mj Where j = 0, 1, 2, ..., M; and M ≥ 5, a total of M+1 numerical simulations of compressive mechanics are carried out; Step 25, regress the quantitative functional relationship F between the statistical elastic modulus and hardness. EHI The quantitative functional relationship between Poisson's ratio and hardness F UHI Quantitative functional relationship between compressive strength and hardness F COHI The calculation formula is as follows: E M = F EHI (Py M (2) U M = F UHI (Py M (3) CO M = F COHI (Py M (4) In the formula, F EHI F represents the quantitative functional relationship between elastic modulus and hardness. UHI F represents the quantitative functional relationship between Poisson's ratio and hardness. COHI This represents the quantitative functional relationship between compressive strength and hardness; where E M For the elastic modulus sequence, U M Poisson's ratio sequence, CO M For compressive strength sequence, Py M The hardness sequence is calculated using the following formula: E M =[ E0, E1, E2, ..., E j ...] U M =[ U0, U1, U2, ..., U j ...] CO M =[CO0, CO1, CO2, ..., CO j ...] Py M =[ Py0, Py1, Py2, ..., Py j ...] Where j = 0, 1, 2, ..., M; Furthermore, in step 23, during the j-th simulation, the mesoscopic elastic modulus is set to MesoE. M0 +j×5000, the Poisson ratio at a fine scale is MesoU M0 +j×0.04, Meso compressive strength is MesoCO M0 +j×5, simulation yields the hardness value Py Mj Where j = 1, 2, ..., M; and M ≥ 5; Furthermore, step 3 is performed as follows: Step 31: Identify and evaluate fractures in the evaluation interval based on imaging logging, and extract fracture development characteristic parameters, including fracture density (Den). Frac , Crack Advantage Trend Stri Frac , Crack dominant dip angle Dip Fra ; Step 32: Identify and evaluate pores in the evaluation interval based on imaging logging, and extract pore development characteristic parameters, including the average pore diameter (diam). cavite Pore ​​density Den cavite ; Step 33: Construct a numerical model FCM1 with a diameter of 25 mm and a height of 50 mm based on the crack development characteristic parameters and the cavity development characteristic parameters; Step 34, repeat step 41 to construct numerical models FCM2 with a diameter of 50mm and a height of 100mm; FCM3 with a diameter of 75mm and a height of 150mm; FCM4 ​​with a diameter of 100mm and a height of 200mm; and FCM5 with a diameter of 150mm and a height of 300mm. Furthermore, the crack development characteristic parameters mentioned in step 33 include crack density Den. Frac , Crack Advantage Trend Stri Frac , Crack dominant dip angle Dip Fra ; Furthermore, the porosity development characteristic parameters mentioned in step 33 include the average porosity diameter (diam). cavite Pore ​​density Den cavite ; Furthermore, step 4 is performed as follows: Step 41, average hardness Py avg Substituting into equations (2), (3), and (4) respectively, the elastic modulus E of the stratigraphic rock skeleton is calculated. M-AVG Poisson's ratio U M-AVG Compressive strength CO M-AVG ; Step 42: For numerical models of different sizes (FCM1, FCM2, FCM3, FCM4, FCM5), set the elastic modulus to the elastic modulus E of the rock skeleton. M-AVG Set the Poisson's ratio as the Poisson's ratio U of the rock framework. M-AVG The compressive strength is set to the compressive strength CO of the rock skeleton. M-AVG ; Step 43: Using numerical models of different sizes (FCM1, FCM2, FCM3, FCM4, FCM5), rock compression numerical simulations are performed. Based on the stress-strain curves obtained from the numerical simulations, the elastic modulus E1, elastic modulus E2, elastic modulus E3, elastic modulus E4, elastic modulus E5, Poisson's ratio U1, Poisson's ratio U2, Poisson's ratio U3, Poisson's ratio U4, Poisson's ratio U5, compressive strength CO1, compressive strength CO2, compressive strength CO3, compressive strength CO4, and compressive strength CO5 of the formation rock at different sizes are calculated. Furthermore, step 5 is performed as follows: Step 51: Statistical analysis is used to obtain the elastic modulus E of the strata rocks. LR With the sample diameter L R Relationship F ER Poisson's ratio U of strata rocks LR With the sample diameter L R Relationship F UR The compressive strength CO of the strata of rock LR With the sample diameter L R Relationship F COR The formula is as follows: E LR = F ER (L R (5) U LR = F UR (L R (6) CO LR = F COR (L R (7) In the formula; E LR U is the elastic modulus of the strata rocks. LR CO is the Poisson's ratio of the strata rocks. LR L represents the compressive strength of the strata rocks. R F represents the diameter of the sample. ER E is the elastic modulus of the strata rocks. LR With the sample diameter L R Relationship, F UR U is the Poisson's ratio of the strata rocks. LRWith the sample diameter L R Relationship, F COR CO is the compressive strength of the strata rocks LR With the sample diameter L R Relationship; Step 52, adjust the wellbore diameter R. w Substituting into equations (5), (6), and (7), the elastic modulus E of the wellbore rock is calculated. RW Poisson's ratio U RW Compressive strength CO RW .

[0005] The beneficial effects of this invention are as follows: This invention provides a method for predicting rock mechanical parameters in complex fractured and porous formations based on the hardness of rock fragments during drilling. The method involves preprocessing and hardness testing of the rock fragments, constructing a quantitative relationship between rock skeleton mechanical parameters and hardness based on a homogeneous isotropic numerical model; extracting characteristic parameters of the fractured and porous structure to construct numerical models of fractured and porous rocks of different sizes; numerically simulating and calculating the rock mechanical parameters of these models; and finally calculating the wellbore rock mechanical parameters of fractured and porous formations, thus realizing the prediction of wellbore rock mechanical parameters for fractured and porous formations. This invention eliminates the need for core drilling, utilizing rock fragments during drilling to reliably predict and evaluate wellbore rock mechanical parameters in fractured and porous formations. It provides a novel theory and method for predicting and evaluating wellbore rock mechanical parameters in complex formations, offering crucial support for ensuring wellbore stability, optimizing drilling and completion design, reducing wellbore collapse risk, controlling fracture propagation, and improving reservoir stimulation efficiency. This not only enhances engineering safety and economy but also has significant implications for the safe and efficient drilling and exploitation of deep oil and gas, especially unconventional oil and gas resources such as shale gas and shale oil. Attached Figure Description

[0006] Figure 1 This is a flowchart illustrating an embodiment of the present invention; Figure 2 This is a graph showing the relationship between the elastic modulus and hardness of a rock skeleton constructed based on a homogeneous isotropic numerical model, according to an embodiment of the present invention. Figure 3 This is a graph showing the relationship between Poisson's ratio and hardness of a rock skeleton constructed based on a homogeneous isotropic numerical model, according to an embodiment of the present invention. Figure 4 This is a graph showing the relationship between the compressive strength and hardness of a rock skeleton constructed based on a homogeneous isotropic numerical model according to an embodiment of the present invention. Figure 5 Numerical models of rocks with different sizes of fissures and cavities in embodiments of the present invention; Figure 6 This is a graph showing the relationship between the elastic modulus of the formation rocks and the size of the rock sample model in an embodiment of the present invention. Figure 7 This is a graph showing the relationship between Poisson's ratio of stratigraphic rocks and rock sample model size in an embodiment of the present invention. Figure 8 This is a graph showing the relationship between the compressive strength of the formation rocks and the size of the rock sample model in an embodiment of the present invention. Detailed Implementation

[0007] like Figure 1 As shown, a method for predicting the rock mechanical parameters of fractured and caved formation wellbore based on the hardness of rock spalling during drilling includes the following steps: Step 1, Pre-treatment and hardness testing of rock fragments from drilling, shall be carried out in the following manner: (1) Screen drilling block samples that meet the size requirements. The size requirements for the blocks are: the length of the long side should not be less than 20 mm and the thickness should not be less than 8 mm. (2) Grind the two end faces of the chipped sample perpendicular to the thickness surface to make the two end faces flat and as parallel as possible; (3) Select a cross section and mark the hardness test locations on it. There shall be no less than 3 hardness test locations and the interval between each location shall be no less than 5 mm. (4) Perform hardness tests at each location point, record the load-displacement curve, and analyze the hardness value Py at the test location point. i The average hardness Py is calculated according to equation (1). avg ; Py avg =∑(Py i ) / N (1) In the formula: N is the number of hardness test points; Py i Let be the hardness test value (MPa) at the i-th position, where i = 1, 2, ..., N.

[0008] The hardness test values ​​at each test point are shown in Table 1: Table 1 Hardness test values ​​at different test points

[0009] Step 2: Construct a quantitative relationship between the mechanical parameters of the rock skeleton and its hardness based on a homogeneous isotropic numerical model, specifically as follows: (1) Construct a homogeneous numerical model PM with a diameter of 25 mm and a thickness of 20 mm, and a homogeneous numerical model CM with a diameter of 25 mm and a height of 20 mm, respectively; (2) For the numerical model PM with a diameter of 25 mm and a thickness of 20 mm, the mesoscopic elastic modulus is set to MesoE. M0 A closer look at the Poisson ratio reveals MesoUM0 Meso compressive strength is MesoCO M0 Then, a numerical simulation experiment on the hardness of the model was conducted to obtain the hardness value Py. M0 ; (3) Repeat step 22 for a total of M simulations. In the j-th simulation, the mesoscopic elastic modulus is set to MesoE. M0 +j×5000, the Poisson's ratio is MesoU. M0 +j×0.04, Mesocompass strength is MesoCO M0 +j×5, simulation yields the hardness value Py Mj Where j = 1, 2, ..., M; and M ≥ 5; (4) For the numerical model CM with a diameter of 25 mm and a height of 50 mm, the mesoscopic elastic modulus is set to MesoE. M0 +j×5000, Poisson's ratio is MesoU M0 +j×0.04, compressive strength is MesoCO M0 +j×5, conduct numerical simulation of compression mechanics to obtain the macroscopic elastic modulus E of the sample. Mj Poisson's ratio U Mj Compressive strength CO Mj Where j = 0, 1, 2, ..., M; and M ≥ 5, a total of M+1 numerical simulations of compressive mechanics are carried out; (5) Statistical regression of the quantitative functional relationship between elastic modulus and hardness F EHI The quantitative functional relationship between Poisson's ratio and hardness F UHI Quantitative functional relationship between compressive strength and hardness F COHI ; E M = F EHI (Py M (2) U M = F UHI (Py M (3) CO M = F COHI (Py M (4) Among them, E M For the elastic modulus sequence, U M Poisson's ratio sequence, CO M For compressive strength sequence, Py M The hardness sequence is calculated using the following formula: E M =[ E0, E1, E2, ..., E j ...] UM =[ U0, U1, U2, ..., U j ...] CO M =[CO0, CO1, CO2, ..., CO j ...] Py M =[ Py0, Py1, Py2, ..., Py j ...] Where j = 0, 1, 2, ..., M.

[0010] The quantitative functional relationship between elastic modulus and hardness F EHI like Figure 2 As shown; the quantitative functional relationship between Poisson's ratio and hardness F UHI like Figure 3 As shown; the quantitative functional relationship F between compressive strength and hardness COHI like Figure 4 As shown.

[0011] Step 3: Extract the structural feature parameters of the fractures and cavities in the strata, and construct numerical models of rocks with fractures and cavities of different sizes. This is carried out in the following manner: (1) Based on imaging logging, identify and evaluate fractures in the evaluation intervals, and extract fracture development characteristic parameters, including fracture density Den. Frac , Crack Advantage Trend Stri Frac , Crack dominant dip angle Dip Fra ; (2) Identify and evaluate cavities in the evaluation interval based on imaging logging, and extract characteristic parameters of cavity development, including the average diameter of the cavities (diam). cavite Pore ​​density Den cavite ; (3) Based on the characteristic parameters of crack development (including crack density Den) Frac , Crack Advantage Trend Stri Frac , Crack dominant dip angle Dip Fra ), Pore development characteristic parameters (including average pore diameter diam) cavite Pore ​​density Den cavite Construct a numerical model FCM1 with a diameter of 25 mm and a height of 50 mm; (4) Repeat step 41 to construct numerical models FCM2 with a diameter of 50 mm and a height of 100 mm; FCM3 with a diameter of 75 mm and a height of 150 mm; FCM4 ​​with a diameter of 100 mm and a height of 200 mm; and FCM5 with a diameter of 150 mm and a height of 300 mm. The established numerical model is as follows Figure 5 As shown.

[0012] Step 4: Numerical simulation calculation of rock mechanical parameters for numerical models of rocks with fractures and cavities of different sizes, specifically as follows: (1) The average hardness Py avg Substituting into equations (2), (3), and (4) respectively, the elastic modulus E of the stratigraphic rock skeleton is calculated. M-AVG Poisson's ratio U M-AVG Compressive strength CO M-AVG ; (2) For numerical models of FCM1, FCM2, FCM3, FCM4, and FCM5 of different sizes, the elastic modulus is set to the elastic modulus E of the rock skeleton. M-AVG Set the Poisson's ratio as the Poisson's ratio U of the rock framework. M-AVG The compressive strength is set to the compressive strength CO of the rock skeleton. M-AVG ; (3) Using numerical models of different sizes, FCM1, FCM2, FCM3, FCM4 ​​and FCM5, respectively, rock compression numerical simulation was carried out. Based on the stress-strain curves obtained from the numerical simulation, the elastic modulus (E1, E2, E3, E4, E5), Poisson's ratio (U1, U2, U3, U4, U5), and compressive strength (CO1, CO2, CO3, CO4, CO5) of the formation rock under different sizes were obtained. Table 2 shows the rock mechanical parameters calculated by different size models.

[0013] Table 2 Rock mechanical parameters calculated from models of different sizes

[0014] Step 5: Calculate the wellbore rock mechanical parameters of the fractured-vuggy formation, specifically as follows: (1) Statistical analysis yielded the elastic modulus E of the strata rocks. LR With the sample diameter L R Relationship F ER Poisson's ratio U of strata rocks LR With the sample diameter L R Relationship F UR The compressive strength CO of the strata rocks LR With the sample diameter L R Relationship F COR The formula is as follows: E LR = F ER (L R (5) U LR = F UR (L R (6) CO LR = FCOR (L R (7) In the formula; E LR U is the elastic modulus of the strata rocks. LR CO is the Poisson's ratio of the strata rocks. LR L represents the compressive strength of the strata rocks. R F represents the diameter of the sample. ER E is the elastic modulus of the strata rocks. LR With the sample diameter L R Relationship, F UR U is the Poisson's ratio of the strata rocks. LR With the sample diameter L R Relationship, F COR CO is the compressive strength of the strata rocks LR With the sample diameter L R Relationships; such as Figure 6 , Figure 7 , Figure 8 As shown; (2) The well diameter R w Substituting into equations (5), (6), and (7), the elastic modulus E of the wellbore rock is calculated. RW Poisson's ratio U RW Compressive strength CO RW .

[0015] The wellbore size R of the analyzed well section w The thickness is 165.1 mm. The calculated elastic modulus of the well wall rock is 14286.9 MPa, the Poisson's ratio is 0.393, and the compressive strength is 53.48 MPa.

[0016] The above descriptions are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for predicting the rock mechanical parameters of fractured and cavernous formations based on the hardness of rock fragments during drilling, characterized in that: Includes the following steps: Step 1: Pre-treatment and hardness testing of rock fragments dropped during drilling; Step 2: Construct a quantitative relationship between the mechanical parameters of the rock skeleton and its hardness based on a homogeneous isotropic numerical model; Step 3: Extract the structural feature parameters of the fractures and cavities in the strata and construct numerical models of rocks with fractures and cavities of different sizes; Step 4: Numerical simulation calculation of rock mechanical parameters for numerical models of rocks with different sizes of fractures and cavities; Step 5: Calculate the wellbore rock mechanical parameters of the fractured-cavity formation.

2. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 1, is characterized in that: Step 1 is performed as follows: Step 11: Select drilling block samples that meet the size requirements. The size requirements for the blocks are: the length of the long side is not less than 20 mm and the thickness is not less than 8 mm. Step 12: Grind the two end faces of the chipped sample perpendicular to the thickness surface to make the two end faces flat and parallel. Step 13: Select a cross-section and mark the locations for the hardness test on it; Step 14: Perform hardness tests at each location point, record the load-displacement curve, and calculate the average hardness Py according to equation (1). avg , Py avg =∑(Py i ) / N (1) In the formula: Py avg The average hardness is represented by N; N is the number of hardness test points. Py i Let be the hardness test value at the i-th position, in MPa, where i = 1, 2, ..., N.

3. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 2, is characterized in that: In step 13, there are no fewer than three hardness test points, and the interval between each point is no less than 5 mm.

4. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 1, is characterized in that: Step 2 is performed as follows: Step 21: Construct a homogeneous numerical model PM with a diameter of 25 mm and a thickness of 20 mm, and a homogeneous numerical model CM with a diameter of 25 mm and a height of 20 mm. Step 22: Set the mesoscopic elastic modulus of the numerical model PM with a diameter of 25 mm and a thickness of 20 mm to MesoE. M0 A closer look at the Poisson ratio reveals MesoU M0 Meso compressive strength is MesoCO M0 A numerical simulation experiment on the hardness of the model was conducted to obtain the hardness value Py. M0 ; Step 23: Repeat step 22 for a total of M simulation calculations; Step 24: For the numerical model CM with a diameter of 25mm and a height of 50mm, set the mesoscopic elastic modulus to MesoE. M0 +j×5000, Poisson's ratio is MesoU M0 +j×0.04, compressive strength is MesoCO M0 +j×5, conduct numerical simulation of compression mechanics to obtain the macroscopic elastic modulus E of the sample. Mj Poisson's ratio U Mj Compressive strength CO Mj Where j = 0, 1, 2, ..., M; a total of M+1 numerical simulations of compressive mechanics were carried out; Step 25, regress the quantitative functional relationship F between the statistical elastic modulus and hardness. EHI The quantitative functional relationship between Poisson's ratio and hardness F UHI Quantitative functional relationship between compressive strength and hardness F COHI The calculation formula is as follows: E M = F EHI (Py M ) (2) U M = F UHI (Py M ) (3) WHAT M = F COHI (Py M ) (4) In the formula, F EHI F represents the quantitative functional relationship between elastic modulus and hardness. UHI F represents the quantitative functional relationship between Poisson's ratio and hardness. COHI This represents the quantitative functional relationship between compressive strength and hardness; E M For the elastic modulus sequence, U M Poisson's ratio sequence, CO M For compressive strength sequence, Py M The hardness sequence is calculated using the following formula: AND M =[ E0, E1, E2, ..., E j …] U M =[ U0、U1、U2、…、U j 、…] WHAT M =[ CO0、CO1、CO2、…、CO j 、…] Py M =[ Py0、Py1、Py2、…、Py j 、…] Where j = 0, 1, 2, ..., M; and M ≥ 5.

5. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 4, is characterized in that: In step 23, during the j-th simulation, the mesoscopic elastic modulus is set to MesoE. M0 +j×5000, the Poisson ratio at a fine scale is MesoU M0 +j×0.04, Meso compressive strength is MesoCO M0 +j×5, simulation yields the hardness value Py Mj Where j = 1, 2, ..., M; and M ≥ 5.

6. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 1, is characterized in that: Step 3 is performed as follows: Step 31: Identify and evaluate fractures in the evaluation interval based on imaging logging, and extract fracture development characteristic parameters, including fracture density (Den). Frac , Crack Advantage Trend Stri Frac , Crack dominant dip angle Dip Fra ; Step 32: Identify and evaluate pores in the evaluation interval based on imaging logging, and extract pore development characteristic parameters, including the average pore diameter (diam). cavite Pore ​​density Den cavite ; Step 33: Construct a numerical model FCM1 with a diameter of 25 mm and a height of 50 mm based on the crack development characteristic parameters and the cavity development characteristic parameters; Step 34, repeat step 41, and construct numerical models FCM2 with a diameter of 50mm and a height of 100mm; FCM3 with a diameter of 75mm and a height of 150mm; FCM4 ​​with a diameter of 100mm and a height of 200mm; and FCM5 with a diameter of 150mm and a height of 300mm.

7. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 6, is characterized in that: The crack development characteristic parameters mentioned in step 33 include crack density Den. Frac , Crack Advantage Trend Stri Frac , Crack dominant dip angle Dip Fra .

8. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 6, is characterized in that: The porosity development characteristic parameters mentioned in step 33 include the average porosity diameter (diam). cavite Pore ​​density Den cavite .

9. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 1, is characterized in that: Step 4 is performed as follows: Step 41, average hardness Py avg Substituting into equations (2), (3), and (4) respectively, the elastic modulus E of the stratigraphic rock skeleton is calculated. M-AVG Poisson's ratio U M-AVG Compressive strength CO M-AVG ; Step 42: For numerical models of different sizes (FCM1, FCM2, FCM3, FCM4, FCM5), set the elastic modulus to the elastic modulus E of the rock skeleton. M-AVG Set the Poisson's ratio as the Poisson's ratio U of the rock framework. M-AVG The compressive strength is set to the compressive strength CO of the rock skeleton. M-AVG ; Step 43: Using numerical models of different sizes (FCM1, FCM2, FCM3, FCM4, FCM5), rock compression numerical simulations are performed. Based on the stress-strain curves obtained from the numerical simulations, the elastic modulus E1, E2, E3, E4, E5, Poisson's ratio U1, U2, U3, U4, U5, and compressive strength CO1, CO2, CO3, CO4, and CO5 of the formation rock at different sizes are calculated.

10. The method for predicting wellbore rock mechanical parameters of fractured and cavernous formations based on the hardness of rock spalling during drilling, as described in claim 1, is characterized in that: Step 5 is performed as follows: Step 51: Statistical analysis is used to obtain the elastic modulus E of the strata rocks. LR With the sample diameter L R Relationship F ER Poisson's ratio U of strata rocks LR With the sample diameter L R Relationship F UR The compressive strength CO of the strata rocks LR With the sample diameter L R Relationship F COR The formula is as follows: E LR = F ER (L R ) (5) And LR = F UR (L R ) (6) WHAT LR = F COR (L R ) (7) In the formula; E LR U is the elastic modulus of the strata rocks. LR CO is the Poisson's ratio of the strata rocks. LR L represents the compressive strength of the strata rocks. R F represents the diameter of the sample. ER E is the elastic modulus of the strata rocks. LR With the sample diameter L R Relationship, F UR Poisson's ratio U of strata rocks LR With the sample diameter L R Relationship, F COR CO is the compressive strength of the strata rocks LR With the sample diameter L R Relationship; Step 52, adjust the wellbore diameter R. w Substituting into equations (5), (6), and (7), the elastic modulus E of the wellbore rock is calculated. RW Poisson's ratio U RW Compressive strength CO RW .

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