Measurement and logging integrated stratum compressive strength while-drilling monitoring method

Abstract

The invention discloses a logging-logging-fused stratum compressive strength monitoring-while-drilling method which comprises the following steps: (1) establishing a drill bit compressive strength prediction-while-drilling model based on target area engineering logging information, and obtaining logging-information-based compressive strength while drilling; (2) calculating according to the logging information to obtain the logging compressive strength, fusing and comparing the logging compressive strength with the logging information-based compressive strength while drilling, and determining different lithologic compressive strength while drilling inversion correction coefficients; and (3) determining lithologic characteristic minerals and elements by utilizing a Pearson correlation analysis method, establishing a mineral and element multiple regression equation about the while-drilling inversion correction coefficient of the compressive strength of the rock, and monitoring the compressive strength value of the drilling stratum in real time by utilizing the while-drilling inversion compressive strength and the compressive strength correction coefficient multiple regression equation. According to the method, the rock compressive strength while-drilling interpretation result can be corrected in real time through the rock debris logging information, the mineral diffraction logging information and the element logging information, and the compressive strength while-drilling prediction precision is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas logging, and in particular relates to a method for monitoring formation compressive strength while drilling by integrating logging and logging. Background Art

[0002] At present, the rock properties of deep formations are complex, and problems such as low mechanical drilling speed and frequent complex accidents often occur during drilling work. Real-time and effective rock compressive strength monitoring while drilling is needed to provide guidance for speeding up and improving efficiency. In terms of reflecting compressive strength, logging and mud logging information have their own advantages and disadvantages. Logging information is stable and accurate, but logging needs to be performed after drilling is completed, and its real-time performance is poor; mud logging information is collected while drilling, and its real-time performance is good, but it is affected by the construction conditions and wellbore environment, and the stability and accuracy of mud logging feedback information while drilling are reduced. Summary of the invention

[0003] The present invention is proposed to solve the problems existing in the prior art, and its purpose is to provide a method for monitoring formation compressive strength while drilling by integrating well logging and measurement.

[0004] The present invention is achieved through the following technical solutions:

[0005] A method for monitoring formation compressive strength while drilling by integrating logging and well logging, comprising the following steps:

[0006] (I) A drill bit compressive strength while drilling prediction model is established based on the target area engineering logging information to obtain the drill bit compressive strength while drilling based on the logging information, specifically including the following steps:

[0007] (Ⅰ-ⅰ) Recording the drilling data;

[0008] The drilling bit data includes drilling tool assembly conditions, drill bit type, drill bit size and drill bit newness;

[0009] (I-II) Collection of engineering parameters

[0010] The engineering parameters are collected by a well site tool parameter collection instrument;

[0011] The engineering parameters include drilling pressure while drilling, rotation speed, torque, drilling time, mud density, inlet and outlet displacement and standpipe pressure;

[0012] (I-III) Eliminate initial drilling bottom hole modeling data and abnormal well section data;

[0013] The initial drilling bottom hole modeling data and abnormal well section data are eliminated by using a data organizer;

[0014] The initial drilling bottom hole shaping data is the data before the peak value of the parameters that fluctuate violently during the initial entry of the new drill bit into the well and breaking the rock; the reason for the removal is that during the initial entry of the new drill bit into the well and breaking the rock, the contact, deformation and shear crushing process between the drill bit teeth and the formation are unstable and vary greatly, and the drilling pressure, torque and mechanical specific energy parameters will fluctuate violently, which cannot effectively reflect the formation characteristics, gradually reach the peak value, then fall, and finally tend to be stable, so the data before the peak value is removed;

[0015] The abnormal well section data includes abnormal drilling data, empty data and well depth sudden jump data; the abnormal drilling data, empty data and well depth sudden jump data such as tripping and stopping drilling are eliminated, and only the normal drilling section data is retained;

[0016] (I-IV) Establishing a dynamic prediction model for drill bit wear coefficient according to drill bit type and calculating the drill bit wear coefficient;

[0017] When the drill bit type is a PDC drill bit, the expression of the drill bit wear coefficient dynamic prediction model is:

[0018]

[0019] Where: t df A is the wear coefficient of PDC drill bit, dimensionless; f is the abrasiveness of the formation, dimensionless, determined by rock abrasiveness experiments; WOB is the bit pressure, in kN; RPM is the rotation speed, in r / min; h d is the dimensionless wear of PDC bit teeth, which is the ratio of tooth wear height Δh to cutting tooth radius dc / 2; a, b, c are coefficients;

[0020] When the drill bit type is a roller drill bit, the expression of the drill bit wear coefficient dynamic prediction model is:

[0021]

[0022] Where: t cf A is the wear coefficient of the roller drill bit, dimensionless; f is the abrasiveness of the formation, dimensionless, determined by rock abrasiveness experiments; RPM is the rotation speed, in r / min; WOB is the bit pressure, in kN; h c is the dimensionless wear of the teeth of the cone drill bit, which is 0 for a new drill bit and 1 for a fully worn drill bit; Q1, Q2, D1, D2, C1 are coefficients;

[0023] (I-V) Establishing a prediction model for the compressive strength of a drill bit while drilling based on the drill bit type, and obtaining the compressive strength of a drill bit while drilling based on the logging information;

[0024] When the drill bit type is a PDC drill bit, based on the rock-breaking mechanism of the PDC drill bit, a prediction model of the PDC drill bit's compressive strength while drilling based on the PDC drill bit-rock interaction mechanism is established;

[0025] The expression of the PDC drill bit compressive strength prediction model while drilling is:

[0026]

[0027] Where: CCS sz is the compressive strength while drilling, in MPa; N c is the total number of cutting teeth, dimensionless; WOB is the bit pressure, in kN; RPM is the rotation speed, in r / min; D b is the drill bit diameter, in mm; ROP is the mechanical drilling speed, in m / h; θ is the back tilt angle, in °; α is the side rotation angle, in °; h d is the dimensionless wear of PDC bit teeth, which is the ratio of tooth wear height Δh to cutting tooth radius dc / 2; μ f is the rock friction coefficient, dimensionless; a, e, g, K are all coefficients, dimensionless;

[0028] When the drill bit type is a roller drill bit, based on the rolling rock breaking mechanism of the roller drill bit, a prediction model of the compressive strength of the roller drill bit while drilling based on the roller drill bit-rock interaction mechanism is established;

[0029] The expression of the prediction model of the compressive strength of the roller drill bit while drilling is:

[0030]

[0031] Where: CCS sz is the compressive strength while drilling, in MPa; WOB is the bit pressure, in kN; n t is the number of teeth in contact with the bottom rock, dimensionless; l is the tooth penetration length, in mm; ROP is the mechanical drilling speed, in m / h; D b is the drill diameter, in mm; ψ is the cutting angle, in °; n t is the number of teeth in contact with the bottom rock, dimensionless; m is the number of teeth engaged per revolution, dimensionless; RPM is the rotation speed, unit is r / min; h c is the dimensionless wear of the teeth of the roller drill bit, which is 0 for a new drill bit and 1 for a fully worn drill bit; a, e, g, K, C1, C2 are coefficients, dimensionless; w is the tooth penetration width, mm

[0032] (II) The logging compressive strength is calculated based on the logging information, and the logging compressive strength is compared with the while-drilling compressive strength based on the logging information to determine the while-drilling inversion correction coefficient of the compressive strength of different lithologies, which specifically includes the following steps:

[0033] (II-i) Extracting P-wave time difference data based on geophysical logging information;

[0034] (II-ii) Calculate the logging compressive strength based on the P-wave time difference-compressive strength empirical formula;

[0035] The longitudinal wave time difference-compressive strength empirical formula is:

[0036] CCS DT = k·DT a

[0037] Where: CCS DT is the logging compressive strength, in MPa; DT is the P-wave time difference, in us / ft; k and a are coefficients of the empirical formula, determined by rock mechanics experiments;

[0038] (II-III) Combining the logging compressive strength and the while-drilling compressive strength based on the logging information, the correction coefficient of the rock compressive strength based on the fusion of logging and well logging is calculated;

[0039] The calculation formula of the rock compressive strength correction coefficient is:

[0040] α=CCS DT / CCS sz

[0041] Where: α is the correction coefficient of rock compressive strength, dimensionless; CCS DT is the logging compressive strength, in MPa; CCS sz is the compressive strength while drilling based on logging information, in MPa;

[0042] (II-IV) Based on the cuttings logging information and the rock compressive strength correction coefficient based on the fusion of logging and logging, the rock compressive strength correction coefficient corresponding to different lithologies is determined.

[0043] The calculation formula for the correction coefficient of rock compressive strength corresponding to different lithologies is:

[0044]

[0045] Where: α ri is the correction coefficient of rock compressive strength corresponding to a certain lithology, dimensionless; i represents a certain lithology, i is selected from any one of fine sandstone, mudstone, conglomerate or siltstone; α in is the correction coefficient of rock compressive strength, dimensionless; n is the number of data belonging to this lithology in the correction coefficient of rock compressive strength;

[0046] (III) Using the Pearson correlation analysis method, determine the lithological characteristic minerals and elements, establish the mineral and element multiple regression equation for the rock compressive strength while drilling inversion correction coefficient obtained in step (II-III), and use the multiple regression equation of the while drilling inversion compressive strength and compressive strength correction coefficient to monitor the compressive strength value of the drilled formation in real time, so as to provide decision support for the optimization of drilling construction parameters and drill bit adaptability.

[0047] The specific steps include:

[0048] (III-i) Collecting mineral composition and elemental composition through a while-drilling XRD mineral diffraction tester and an XRF elemental composition tester;

[0049] (III-ii) Using the data organizer, extract the rock compressive strength correction coefficient data according to the mineral & element data depth;

[0050] (III-III) Calculate the correlation values ​​between mineral components and element components and the correction coefficient of rock compressive strength, and select mineral components and element components with absolute values ​​of correlation values ​​greater than 0.3;

[0051] The calculation formula for the correlation value of the mineral component and element component with the correction coefficient of rock compressive strength is:

[0052]

[0053] Where: r is the correlation value of the correction coefficient of mineral components and element components to rock compressive strength; ω is the content of mineral components and element components, %; α r is the correction factor for rock compressive strength calculated in step (II-IV), dimensionless; It is the arithmetic mean of the contents of mineral components and element components, %; It is the arithmetic mean of the correction coefficient of rock compressive strength and is dimensionless;

[0054] (III-IV) Establishing a multiple regression model between the mineral components and element components with large correlation values ​​selected in step (III-III) and the correction coefficient of rock compressive strength;

[0055] The expression of the multivariate regression model of the mineral components and element components and the correction coefficient of rock compressive strength is:

[0056] α mra =a·ω 石英 +b·ω 白云石 +c·ω 粘土矿物 +…+l·ω Si +m·ω Al +n·ω K +…

[0057] Where: α mrais the correction coefficient of rock compressive strength, dimensionless; ω i is the content of mineral component / element component, %; i represents mineral component or element component, i is selected from quartz, feldspar, calcite, dolomite, clay minerals, etc. and Si, Al, K, Fe, Ca, etc.; a, b, c, l, m, n are all coefficients of parameters of the multiple regression equation;

[0058] (III-V) Based on the rock compressive strength correction coefficient and the compressive strength while drilling based on the logging information, the compressive strength of the rock encountered during drilling is calculated in real time.

[0059] The calculation formula for real-time calculation of the compressive strength of rock encountered in formation drilling is:

[0060] CCS=α·CCS sz

[0061] Where: CCS is the corrected compressive strength of the rock encountered in the formation, in MPa; sz is the compressive strength while drilling, in MPa; α is calculated by step (Ⅱ-ⅳ) or step (Ⅲ-ⅳ). When the target well has only lithology information, the value calculated by step (Ⅱ-iv) is selected; when the target well contains XRD mineral diffraction logging or XRF element logging information, the value calculated by step (Ⅲ-iv) is selected.

[0062] The beneficial effects of the present invention are:

[0063] The present invention provides a method for monitoring formation compressive strength while drilling by integrating logging and well logging. The method integrates actual well logging and well logging detection data, establishes a regional rock compressive strength correction coefficient calculation model through an algorithm, realizes the integration of logging and well logging to improve prediction accuracy, and forms high-precision real-time monitoring of rock compressive strength while drilling. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 is a flow chart of the method of the present invention;

[0065] Figure 2 This is a result diagram of a field application example of rock compressive strength tracking and evaluation while drilling according to Example 1 of the present invention.

[0066] For ordinary technicians in this field, other relevant drawings can be obtained based on the above drawings without any creative work. DETAILED DESCRIPTION

[0067] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0068] Example 1

[0069] like Figure 1 As shown, a method for monitoring formation compressive strength while drilling by integrating well logging and well measurement comprises the following steps:

[0070] Step 1: Record the drilling tool assembly, drill bit type, size and newness, etc., as shown in Table 1 below.

[0071] Table 1: Drilling tool assembly, drill bit type, size and newness data

[0072]

[0073] Step 2: Use the well site engineering parameter acquisition instrument to monitor parameters such as drilling pressure, rotation speed, torque, drilling time, mud density, inlet and outlet displacement, and riser pressure while drilling.

[0074] Step 3: Use the data organizer to remove the initial drilling bottom shape data and abnormal well section data.

[0075] Step 3-1: When a new drill bit is initially put into the well to break rock, the mechanical specific energy will fluctuate violently due to the unstable contact, deformation and shear crushing process between the drill bit teeth and the formation, gradually reaching a peak value and then falling, and finally stabilizing. The data before the peak value is discarded.

[0076] Step 3-2: Remove abnormal drilling data such as tripping, drilling stop, empty data and well depth jump data, and only retain normal drilling section data.

[0077] Step 4: Establish a dynamic prediction model for drill bit wear coefficient according to the drill bit type and calculate the drill bit wear coefficient;

[0078] When the drill bit type is PDC drill bit, the dynamic prediction model of PDC drill bit wear coefficient is:

[0079]

[0080] Where: t df A is the wear coefficient of PDC drill bit, dimensionless; f is the abrasiveness of the formation, dimensionless, determined by rock abrasiveness experiments; WOB is the bit pressure, in kN; RPM is the rotation speed, in r / min; h d is the dimensionless wear of PDC bit teeth, which is the ratio of tooth wear height Δh to cutting tooth radius dc / 2; a, b, c are coefficients;

[0081] When the drill bit type is a roller drill bit, the dynamic prediction of the wear coefficient of the roller drill bit is:

[0082]

[0083] Where: t cf A is the wear coefficient of the roller drill bit, dimensionless;f is the abrasiveness of the formation, dimensionless, determined by rock abrasiveness experiments; RPM is the rotation speed, in r / min; WOB is the bit pressure, in kN; h c is the dimensionless wear of the teeth of the cone drill bit, which is 0 for a new drill bit and 1 for a fully worn drill bit; Q1, Q2, D1, D2, C1 are coefficients;

[0084] Step 5: Establish a prediction model for the compressive strength of the drill bit while drilling according to the drill bit type. When the drill bit type is a PDC drill bit, based on the PDC drill bit cutting and rock breaking mechanism, establish a real-time prediction method for the compressive strength of the PDC drill bit based on the PDC drill bit-rock interaction mechanism.

[0085]

[0086] Where: CCS sz is the compressive strength while drilling, in MPa; N is the total number of cutting teeth, dimensionless; WOB is the bit pressure, in kN; RPM is the rotation speed, in r / min; D b is the drill bit diameter, in mm; ROP is the mechanical drilling speed, in m / h; θ is the back tilt angle, in °; α is the side rotation angle, in °; h d is the dimensionless wear of PDC bit teeth, which is the ratio of tooth wear height Δh to cutting tooth radius dc / 2; μ f is the rock friction coefficient, dimensionless; a, c, g, K are all coefficients, dimensionless;

[0087] When the drill bit type is a roller drill bit, based on the rolling rock breaking mechanism of the roller drill bit, a real-time prediction method for the compressive strength of the roller drill bit based on the roller drill bit-rock interaction mechanism is established.

[0088]

[0089] Where: CCS sz is the compressive strength while drilling, in MPa; WOB is the bit pressure, in kN; n t is the number of teeth in contact with the bottom rock, dimensionless; l is the tooth penetration length, in mm; ROP is the mechanical drilling speed, in m / h; D b is the drill diameter, in mm; ψ is the cutting angle, in °; n t is the number of teeth in contact with the bottom rock, dimensionless; m is the number of teeth engaged per revolution, dimensionless; RPM is the rotation speed, unit is r / min; h c is the dimensionless wear of the teeth of the roller drill bit, which is 0 for a new drill bit and 1 for a fully worn drill bit; a, e, g, K, C1, C2 are coefficients, dimensionless; w is the tooth penetration width, mm;

[0090] Step 6: Extract P-wave time difference data based on geophysical logging information.

[0091] Step 7: Calculate the logging compressive strength based on the P-wave time difference-compressive strength empirical formula. The P-wave time difference-compressive strength empirical formula of the BZ block determined by rock mechanics experiments is:

[0092] CCS DT =1.1908×10 7 ·DT -3

[0093] Where: CCS DT —Logging compressive strength, MPa, mm; DT—Pituitary wave time difference, us / ft.

[0094] Step 8: Calculate the rock compressive strength correction factor by combining the logging compressive strength and the while-drilling compressive strength, as shown in Table 2 below.

[0095] Table 2: Depth, logging compressive strength, while drilling compressive strength and rock compressive strength correction coefficient

[0096] Depth(m) Logging compressive strength (MPa) Compressive strength while drilling (MPa) Correction factor of rock compressive strength 2600 17.098284 16.916527 1.0107443 2605 17.576021 17.628468 0.9970248 2610 17.03254 17.850092 0.954199 2615 18.411227 16.821668 1.0944947 2620 19.144075 16.543161 1.1572199 2625 18.299655 15.821477 1.1566338 2630 18.733709 16.808988 1.1145055 2635 19.937205 16.267488 1.225586 2640 21.113239 15.537022 1.3588987 2645 33.945326 15.072247 2.2521743

[0097] Step 9: Based on the lithology logging information and the rock compressive strength correction coefficient calculated by the fusion of logging and logging, determine the rock compressive strength correction coefficient corresponding to different lithologies.

[0098] Step 10: Collect mineral components and elemental components through the XRD mineral diffraction tester and XRF elemental component tester.

[0099] Step 11: Use the data organizer to extract the rock compressive strength correction factor data according to the mineral & element data depth.

[0100] Step 12: Screen the mineral & element components whose absolute value of correlation with the correction coefficient of rock compressive strength is greater than 0.3, as shown in Table 3 below.

[0101] Table 3: Correlation values ​​of mineral & element composition and correction coefficient of rock compressive strength

[0102]

[0103] Step 13: Establish a multiple regression model of rock compressive strength correction coefficient based on mineral & element information.

[0104] α mra =a·ω 石英 +b·ω 白云石 +c·ω 粘土矿物 +l·ω Si +m·ω Al +n·ωK

[0105] Where: α mra is the correction coefficient of rock compressive strength, dimensionless; ω i is the content of mineral components and element components, %; i = mineral components (quartz, dolomite, clay minerals) and element components (Si, Al, K); a, b, c, l, m, n are the coefficients of the parameters of the multiple regression equation;

[0106] Step 14: Based on the rock compressive strength correction coefficient and the compressive strength while drilling, the compressive strength of the rock encountered during drilling is calculated in real time.

[0107] CCS=α mra ·CCS sz

[0108] Where: CCS is the corrected compressive strength of the rock encountered in the formation, in MPa; sz is the compressive strength while drilling, in MPa; α mra It is the correction coefficient of rock compressive strength and is dimensionless.

[0109] The applicant declares that the above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention are within the protection scope and disclosure scope of the present invention.

Claims

1. A method for monitoring formation compressive strength while drilling by integrating logging and well measurement, characterized in that: The following steps are involved: (I) A drill bit compressive strength while drilling prediction model is established based on the target area engineering logging information to obtain the drill bit compressive strength while drilling based on the logging information; (II) The logging compressive strength is calculated based on the logging information, and the logging compressive strength is compared with the while-drilling compressive strength based on the logging information to determine the while-drilling inversion correction coefficient for the compressive strength of different lithologies; (III) The Pearson correlation analysis method is used to determine the characteristic minerals and elements of the lithology, and a multiple regression equation for the minerals and elements related to the correction coefficient of the rock compressive strength during drilling is established. The compressive strength of the drilled formation is monitored in real time using the multiple regression equation of the inversion of the compressive strength during drilling and the correction coefficient of the compressive strength.

2. The method for monitoring formation compressive strength while drilling by integrating well logging and logging according to claim 1, characterized in that: The step (I) specifically comprises the following steps: (Ⅰ-ⅰ) Recording the drilling data; (I-II) Collection of engineering parameters (I-III) Eliminate initial drilling bottom hole modeling data and abnormal well section data; (I-IV) Establishing a dynamic prediction model for drill bit wear coefficient according to drill bit type and calculating the drill bit wear coefficient; (I-V) A prediction model for the compressive strength of the drill bit while drilling is established according to the drill bit type, and the compressive strength of the drill bit while drilling based on the logging information is obtained.

3. The method for monitoring formation compressive strength while drilling by integrating well logging and logging according to claim 2, characterized in that: The drilling bit data includes the drilling tool combination, drill bit type, drill bit size and drill bit newness; the engineering parameters are collected by the well site tool parameter collector; the engineering parameters include drilling pressure, rotation speed, torque, drilling time, mud density, inlet and outlet displacement and standpipe pressure collected while drilling.

4. The method for monitoring formation compressive strength while drilling by integrating well logging and logging according to claim 2, characterized in that: The initial drilling bottom hole modeling data and abnormal well section data are eliminated by using a data organizer; the abnormal well section data include abnormal drilling data, empty data and well depth sudden jump data.

5. The method for monitoring formation compressive strength while drilling by integrating well logging and logging according to claim 2, characterized in that: When the drill bit type is a PDC drill bit, the expression of the drill bit wear coefficient dynamic prediction model is: Where: t df A is the wear coefficient of PDC drill bit, dimensionless; f is the abrasiveness of the formation, dimensionless, determined by rock abrasiveness experiments; WOB is the bit pressure, in kN; RPM is the rotation speed, in r / min; h d is the dimensionless wear of PDC bit teeth, which is the ratio of tooth wear height Δh to cutting tooth radius dc / 2; a, b, c are coefficients; When the drill bit type is a roller drill bit, the expression of the drill bit wear coefficient dynamic prediction model is: Where: t cf A is the wear coefficient of the roller drill bit, dimensionless; f is the abrasiveness of the formation, dimensionless, determined by rock abrasiveness experiments; RPM is the rotation speed, in r / min; WOB is the bit pressure, in kN; h c is the dimensionless wear of the roller drill teeth. The new drill bit is 0 and the drill bit is 1 when it is fully worn. Q1, Q2, D1, D2, C1 are coefficients.

6. The method for monitoring formation compressive strength while drilling by integrating well logging and logging according to claim 2, characterized in that: When the drill bit type is a PDC drill bit, based on the rock-breaking mechanism of the PDC drill bit, a prediction model of the PDC drill bit's compressive strength while drilling based on the PDC drill bit-rock interaction mechanism is established; The expression of the PDC drill bit compressive strength prediction model while drilling is: Where: CCS sz is the compressive strength while drilling, in MPa; N c is the total number of cutting teeth, dimensionless; WOB is the bit pressure, in kN; RPM is the rotation speed, in r / min; D b is the drill bit diameter, in mm; ROP is the mechanical drilling speed, in m / h; θ is the back tilt angle, in °; α is the side rotation angle, in °; h d is the dimensionless wear of PDC bit teeth, which is the ratio of tooth wear height Δh to cutting tooth radius dc / 2; μ f is the rock friction coefficient, dimensionless; a, e, g, K are all coefficients, dimensionless; When the drill bit type is a roller drill bit, based on the rolling rock breaking mechanism of the roller drill bit, a prediction model of the compressive strength of the roller drill bit while drilling based on the roller drill bit-rock interaction mechanism is established; The expression of the prediction model of the compressive strength of the roller drill bit while drilling is: Where: CCS sz is the compressive strength while drilling, in MPa; WOB is the bit pressure, in kN; n t is the number of teeth in contact with the bottom rock, dimensionless; l is the tooth penetration length, in mm; ROP is the mechanical drilling speed, in m / h; D b is the drill diameter, in mm; ψ is the cutting angle, in °; n t is the number of teeth in contact with the bottom rock, dimensionless; m is the number of teeth engaged per revolution, dimensionless; RPM is the rotation speed, unit is r / min; h c is the dimensionless wear of the roller drill teeth, which is 0 for a new drill bit and 1 when the drill bit is fully worn out; a, e, g, K, C1, C2 are coefficients, which are dimensionless; w is the tooth penetration width, in mm.

7. The method for monitoring formation compressive strength while drilling by integrating well logging and logging according to claim 1, characterized in that: The step (II) specifically comprises the following steps: (II-i) Extracting P-wave time difference data based on geophysical logging information; (II-ii) Calculate the logging compressive strength based on the P-wave time difference-compressive strength empirical formula; The longitudinal wave time difference-compressive strength empirical formula is: CCS DT =k·DT a Where: CCS DT is the logging compressive strength, in MPa; DT is the P-wave time difference, in us / ft; k and a are coefficients of the empirical formula, determined by rock mechanics experiments; (II-III) Combining the logging compressive strength and the while-drilling compressive strength based on the logging information, the correction coefficient of the rock compressive strength based on the fusion of logging and well logging is calculated; The calculation formula of the rock compressive strength correction coefficient is: α=CCS DT / CCS sz Where: α is the correction coefficient of rock compressive strength, dimensionless; CCS DT is the logging compressive strength, in MPa; CCS sz is the compressive strength while drilling based on logging information, in MPa; (II-IV) Based on the cuttings logging information and the rock compressive strength correction coefficient based on logging fusion, the rock compressive strength correction coefficient corresponding to different lithologies is determined; The calculation formula for the correction coefficient of rock compressive strength corresponding to different lithologies is: Where: α ri is the correction coefficient of rock compressive strength corresponding to a certain lithology, i represents the lithology, which can be selected from any one of fine sandstone, mudstone, conglomerate or siltstone; α in is the rock compressive strength correction coefficient calculated in step (II-iii), which is dimensionless; n is the number of data belonging to this lithology in the rock compressive strength correction coefficient.

8. The method for monitoring formation compressive strength while drilling by integrating well logging and logging according to claim 1, characterized in that: The step (III) specifically comprises the following steps: (III-i) Collecting mineral composition and elemental composition by using a downhole XRD mineral diffraction tester and an XRF elemental composition tester; (III-ii) Using the data organizer, extract the rock compressive strength correction factor data according to the mineral and element data depth; (III-III) Calculate the correlation value between each mineral component and each element component and the correction coefficient of rock compressive strength, and select the mineral components and element components with the absolute value of the correlation value greater than 0.3; The calculation formula for the correlation value between the mineral component / element component and the correction coefficient of rock compressive strength is: Where: r is the correlation value of the correction coefficient of mineral component or element component to rock compressive strength; ω is the content of mineral component or element component, %; α r is the correction coefficient of rock compressive strength, dimensionless, and the values ​​under the same lithology are obtained by step (II-IV); It is the arithmetic mean of the contents of all mineral components and element components, %; It is the arithmetic mean of the correction coefficient of rock compressive strength and is dimensionless; (III-IV) Establishing a multivariate regression model between the mineral components and element components with large correlation values ​​selected in step (III-III) and the correction coefficient of rock compressive strength; The expression of the multivariate regression model of the mineral components and element components and the correction coefficient of rock compressive strength is: a mra =a·ω 石英 +b·ω 白云石 +c·ω 粘土矿物 +…+l·ω Si +m·h Al +n·ω K +… Where: α mra is the correction coefficient of rock compressive strength, dimensionless; ω i is the content of mineral components or element components, %; i represents mineral components or element components, i is selected from quartz, feldspar, calcite, dolomite, clay minerals, Si, Al, K, Fe, Ca; a, b, c, l, m, n are the coefficients of each parameter of the multiple regression equation; (III-V) Based on the rock compressive strength correction coefficient and the compressive strength while drilling based on the logging information, the compressive strength of the rock encountered during drilling is calculated in real time. The calculation formula for real-time calculation of the compressive strength of rock encountered in formation drilling is: CCS=α·CCS sz Where: CCS is the corrected compressive strength of the rock encountered in the formation, in MPa; sz is the compressive strength while drilling, in MPa; α is calculated in step (Ⅱ-ⅳ) or step (Ⅲ-ⅳ).

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